Wednesday, June 20, 2012

Critique: ICRIER-GC Policy Paper on Climate, Agriculture & Food Security: Climate, Agriculture & Food Security


ICRIER is an independent economic policy think tank founded in 1981 with our Prime Minister, ManMohan Singh as one of its co-founders. Last month, ICRIER published a document under their policy series entitled “Impact of Climate Agriculture & Food Security”.
Read the full study here

ICRIER invited reactions from the public for this research paper authored by Anna Ranuzzi and S Richa, researchers with NGO, Gene Campaign.

There were two basic reasons why this blog was prompted to critique the paper:

a. The first and foremost reason was as a NGO Livelihood specialist with 32 years of experience, the subjects of agriculture and food security are close to my heart.
    
b. Secondly, the paper being totally oriented within the Anthropological Global Warming (AGW) paradigm is formulated in a way to mislead policymakers and the general public about the hypothetical “catastrophic” consequences of this so called modern demon. As a climate sceptic subscribing to a heliocentric theory to climate change, I felt strongly compelled to challenge the axioms, assumptions, contradictions and misleading claims made by this study.

  Introduction: 

An axiom is a premise or starting point of reasoning, assumed to be true. In the case of the ICRIER-Gene Campaign (ICRIER-GC) paper, this was equating climate change with accelerated global warming as the climate scenario of the future.
The phenomenon of “global warming” was treated by the paper as a matter of fact within the analysis part of the study, being mentioned only in its executive summary, that too in a totally unsubstantiated manner with claims being bandied around without any citation and without any discussion on any other plausible alternative explanations of climate change. 

Shoddy research? Maybe, maybe not. What is certain is that the approach of the ICRIER-GC paper is tactical and in sync with  global warmist "best practice". The Institute for Public Policy Research (IPPR) is the UK’s leading Left think-tank, established in 1988 and commands huge influence with international NGOs and climate change science and activist movements.  In a strategy paper titled "Warm Words: How are we telling the climate story and can we tell it better?", they advise:
“To help address the chaotic nature of the climate change discourse in the UK today, interested agencies now need to treat the argument as having been won, at least for popular communications...
This means simply behaving as if climate change exists and is real, and that individual actions are effective. The ‘facts’ need to be treated as being so taken-for-granted that they need not be spoken.”
Such tactics usually adopt a deductive methodology which is what the ICRIER-GC paper appears to have adopted. The fundamental property of a deductively valid argument is this: If all of its premises are true, then its conclusion must be true also, because the claim asserted by its conclusion already has been stated in its premises, although usually only implicitly.

However, the strength of any deductive argument revolve around three things: first, there must be agreement about the general principle with which the argument begins; second, the special application must be correct and clear, with no disputes about its soundness; and, third, the conclusion must be derived properly from putting these two together.

The ICRIER-GC paper while meeting the criteria of logical validity fails the soundness principle. This is because the both the general principle with which the argument begins with and the special application of the argument are highly disputed as there exists other plausible alternative explanations for the observed co-variations.

Whenever an explanatory variable is omitted from an analysis, its explanatory power gets wrongly attributed to any correlated variables that are included. This problem is manifest at the very heart of the ICRIER-GC study and is built into each step of its analysis. Serious evaluation of any science for policy formulation needs to look at science from diverse angles and theories and then select the best plausible one among these, based on available scientific evidence. The approach of the ICRIER-GC paper miserably fails this fundamental prerequisite.
It is commonly argued that Anthropological Global Warming (AGW) is a scientific theory because it is favoured by "the consensus" of scientists. This argument invokes the logical fallacy of argument from authority; the authorities are the scientists that belong to the so called “consensus" - the Inter-governmental Panel on Climate Change (IPCC). Whether "the consensus" represents the view of most scientists can be hotly debated but in more substantive terms, this is totally irrelevant to science as Albert Einstein highlighted:
“No amount of experimentation can ever prove me right; a single experiment can prove me wrong.”
Einstein’s words express a foundational principle of science intoned by the logician, Karl Popper: Falsifiability. A thousand observations may appear to verify a hypothesis, but one critical failure could result in its demise. The history of science is littered with such examples, among which, many of Einstein’s own theories.

According to Popperian principles, a theory is only scientific if it is falsifiable. Popper additionally argues that though we cannot prove that a theory is true, we can certainly show that a prediction is false. A prediction can be tested to discover it is not true by using the logical concept - ‘modus tolens’ to either validate or refute the theory:

If the theory is true, then the prediction is true
The prediction is not true.
Therefore, the theory is not true.  

The ICRIER-GC study relies as sources for its references, studies mainly relying on computer models based on the AGW paradigm, the gold standard of which are the reports of the UN-Inter-governmental Panel on Climate Change (IPCC).

And yet, in one of the IPCC reports viz AR3 2001, they however admitted:
“The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible.”
It follows that the IPCC's models are not falsifiable and thereby are not scientific models. What the IPCC reports provide in lieu of "predictions" are computer simulated "projections" based on several assumed scenarios.  The difference between the two terminologies is as follows: 
- a projection is a mathematical function that maps the time to the computed global average temperature;

- a prediction is a proposition that states the outcome of a statistical event.  
The key differential being that only a prediction lends itself to be falsifiable not a projection. So while the ICRIER-GC paper uses the term “predict”, in their narrative, these references are in fact only projections that cannot be falsified and as such, do not meet the definition of scientific evidence. And this difference comes handy to climate alarmists whenever confronted with any of their long list of failed “predictions”; their standard alarmist reaction is to disavow their “predictions”. They will say that those are not “predictions” at all; they are merely projections—and indirectly confirming that AGW is not a scientific theory at all. 
Accordingly, the ICRIER-GC paper could be considered only as a piece of political propaganda material packaged as a policy paper. Joseph Goebbel’s, Hitler’s communication minister once said:
“It is not propaganda’s task to be intelligent; its task is to lead to success"
Whether ICRIER-GC paper is intelligent or not is accordingly immaterial as that is not the primary task of propaganda. But if by chance it leads to success by influencing the country’s agriculture policy, either in part or whole, this could create impacts, to borrow a commonly used climate alarmist jargon, of possible “catastrophic” proportions for both the farming sector and the economy of the country.

On one hand, our post critiques the ICRIER-GC paper and on the other hand we offer an alternative theory to climate change. If the axiom of any paper can be demolished using scientific evidence, the whole edifice of the paper crumbles down. This would make the solutions recommended by the ICRIER-GC paper practically meaningless. That in short would be the primary objective of this critique, structured into 5 sections as follows: 
 
1.  Continued re-positioning signals a total retreat of AGW Theory

Synopsis: In marketing, the only real way a brand can have a long, successful life cycle is for it to deliver on the promise of its positioning.
So it was to global warming where its failure to deliver on the promise of its positioning resulted in a series of re-branding/repositioning exercise. Within a span of just three decades; global warming metamorphosed first into climate change and more recently to climate chaos/disruption/weirding.

From a focus on increasing temperatures initially, the emphasis has progressively shifted to effects created by weather extremities as reflected in their changed terminology.

 
The ICRIER-GC paper uses the terms global warming and climate change interchangeably without attempting to define both terminologies. This is either another illustration of shoddy research or of the authors hiding a political agenda by deliberately blurring the distinction between these two phenomena, notwithstanding the fact that the terms are now commonly used interchangeably.

Though causally related, “global warming” and ‘climate change' however technically refer to two different physical phenomena. As the name suggests, 'global warming' refers to the long-term trend of a rising mean global temperature. 'Climate change' is defined as average weather for a period (now considered as thirty years). Again as the name suggests, climate change refers to the changes in the global climate which could also result from changes in the mean global temperature.

Such temperature changes can trigger two basically different directional changes in the climate, depending whether they flow from temperature increases (warming) or temperature declines (cooling) which in turn, respectively and perversely affects weather related patterns such as precipitation and extreme events such as floods; drought; heatwave; cold snap; cyclones etc.

Global warming became the dominant popular term in June 1988, when NASA climate modeller and Director of Goddard Institute of Space Studies (GISS),  James E. Hansen testified to the US Congress about climate, specifically referring to global warming. He said:
"...global warming has reached a level such that we can ascribe with a high degree of confidence a cause and effect relationship between the greenhouse effect and the observed warming." (J.P. Schuldt et al, 2011, Public Opinion Quarterly)
Hansen's testimony was very widely reported in popular and business media, and after that popular use of the term global warming exploded as NASA described its impact. The result of this testimony eventually led to the establishment of the IPCC whose current Chairman is former Indian Railways engineer, Rajendra Pachauri.

The earth’s age is estimated around 4.5 billion years and during this time the planet’s temperature has waxed and waned hundreds and thousands of time even before the evolution of the homo-sapiens species. But it is only during the last 3 to 4 decades, global warming was blamed on mankind for the first time due to our so called “carbon footprint”! This claim however cut a chord with common global citizens and politicians during the 90s as the decade bore the brunt of a recent global warming cycle that started around 1977, that appeared, reinforcing climate alarmist claims. 

 
However the warming stopped after 1998. Since then, temperatures have been trending flat, and more recently, with a slightly downward bias. For a planet-roasting crisis that threatened the human race with extinction, a scenario where common people, largely science illiterates, were conditioned to believe by cleverly designed hysterical campaigns, trending flat temperatures proved too much of a perceptual dissonance even for them. Consequently public support for global warming began to slump as climate scepticism took roots.

To stem the erosion of public support, global warming was re-branded and/or re-positioned as climate change with a difference - climate change now no longer included global cooling and exclusively equated with global warming caused by greenhouse gases. This is exactly how the ICRIER report treats both the phenomena by using the two terms inter-changeably. But success, if any, was short-lived as from 2010 a series of events substantially negated any gains by this re-branding exercise:
-  It all started with Climategate, the controversy over a set of documents that were hacked from the computers of the University of East Anglia's (UEA) Climatic Research Unit (CRU) in November 2009. These documents exposed climate scientists as manipulating or hiding data; working in concert to frustrate people legally demanding access to their data and conspiring to prevent papers they disagreed with from being published in scientific journals. Climategate rendered a body blow to climate alarmism because the CRU was singularly responsible for the historic reconstruction of global temperatures - the same foundational dataset used by all other climate research centres in the world. This made all global (surface) temperature datasets a suspect in their reliability and reduced public confidence in the global warming claims.
-  A bigger body blow was suffered by climate alarmists when the 4th Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) was torn apart by a series of media exposé. This included the claim of Himalayan Glaciers disappearing by 2030. The IPCC reports till then were considered by climate alarmists as their Gold Standard. Once a series of errors were revealed, the report ended in the trash can.

-  The first IPCC Assessment Report (AR1) was published in 1990. 2010 marked 20 years of its publication, which is adequate time to validate their 1990 “predictions”. Not one of their “predictions” was confirmed by the real world observational data which are discussed in more detail in the later sections of this critique.

 

As public confidence in the term “climate change” began to drop steeply again, desperate efforts began to re-position AGW again. The first attempt ended in coining alternate terminologies such as “Climate Chaos and Climate Disruption” but these were withdrawn quickly as it did not touch a chord with the public. Here steps in Obama’s Climate Czar John Holdren to coin the new jargon “Climate Weirding” . Though this term too did not register well with the general public, it continues to be used by a small but influential section of the warmist media such as the BBC, Guardian; New York Times, Huffington Post etc
We live in this age of marketing and advertising where if something isn't working, the first remedy is often to change the offending name and/or reposition the product in the marketplace. Repeated attempts to re-brand and re-position global warming serves only a confirmation of a theory that has been for all practical purposes, falsified many times over.

Even as climate alarmism repositioned itself by retreating or even exiting the claims of accelerated global warming to focus now on the touted worsening frequency and intensity of the effects of climate change, the ICRIER-GC paper still remain fixated on the theory of accelerated global warming, assuming the worst of its impact on agriculture on the basis of which a set of adaptation strategies was recommended!
 
2.  Given the performance record of AGW computer modeling, why should their warnings be taken seriously?

SYNOPSIS: The evidence supporting the claim that the earth has grown warmer is shaky; the theory is weak; and the models on which the conclusions are based are not able to replicate either the current or past climate. If these computer models are unable to predict known climate, how can they be expected to predict the unknown climates of the future?

The claims of the ICRIER-GC study based on computer models can be accordingly refuted by observational data.  We use the same set of studies assumingly used by the ICRIER-GC paper, supplemented by others to refute the claim that accelerated global warming is happening and will condition the future climate scenarios as the basis for drawing up agriculture climate adaptation strategies.

GLOBAL TEMPERATURES

ICRIER-GC: “Accelerated warming has already been observed in the recent period 1971-2007, mainly due to intense warming in the recent decade 1998-2007...

Overall in India, it is predicted that, physical impact of climate change will be seen as (1) an increase in the average surface temperature by 2-4 degrees C...

It is predicted that for every 20C (which has been predicted by 2030) rise in temperature, the GDP will reduce by 5 per cent.”

Without any citation it is very difficult to understand the context these statements had been made. So we web searched available literature  and our search ended with an Indian Institute of Tropical Meteorology (IITM), Pune publication where we found a perfect wording match.

The paper we traced out was titled:  “Surface air temperature variability over India during 1901–2007, and its association with ENSO” authored by D. R. Kothawale, A. A. Munot, K. Krishna Kumar published in 2010. Read here.

This same paper is extensively quoted in the report titled ‘Climate Change and India: A 4X4 Assessment’, (2010) Ministry of Environment & Forest, India. Read  here.

These are the two studies we repeatedly refer to in this critique in order to refute the accelerated global warming and related claims of the ICRIER-GC paper. The assumption that these were the reference sources of the ICRIER-GC paper maybe right or wrong. Nevertheless, it matters little as these are the official documents of the Government of India (GoI) and thus commands authenticity.      

 
 CLICK IMAGE TO ENLARGE
So what the Kothawale paper claims is that the Indian experience suggests that the country warmed at the rate of 0.51 deg C/100 years or at the rate of 0.05 deg/10 years during the period 1901-2007. But according to the IPCC, the globe warmed at the rate of 0.74°C/100 years or 0.07/10  years  for the period 1906–2005.

These numbers clearly establishes that there is no 1:1 relationship between global and Indian mean temperature responses to climate change, with the country demonstrating warming at only 2/3rds the rate which the planet  warmed during the last century. This fact strongly aligns with findings from several palaeo-climatic research studies which indicate that warmer poles did not necessarily mean hotter tropical climates. For example, researchers have found evidence for relatively stable temperatures in the lower latitudes around the equator when comparing the Cretaceous epoch to modern times.

Further, according to an IITM presentation to India’s former Environmental Minister, Mr. Jairam Ramesh by Krishna Kumar, a team member of the Kothawale et al paper, admitted: 
“Flattening of trends during the current decade with a warming of 0.1C/10yrs”
Krishna Kumar was referring to the same graph of the Kothawale et al study where he was a team member. What this graph shows is that warming rate which was 0.2 deg C/per decade for the period 1971-1997 dropped significantly to 0.09 deg C/per decade for the period 1998-2007 - demonstrating a clear cooling trend.

Yet the Kothawale et al paper strangely claims “.. intense warming in the recent decade 1998-2007” but their own graph contradicts this claim and what Krishna Kumar, their team member claimed in his presentation to our former Union Environment Minister.

This cooling we experienced in India during the last decade is consistent with those experienced globally: 

  CLICK IMAGE TO ENLARGE
 
While global satellite temperature indicates a total absence of statistically significant warming since 1998, global surface temperature datasets such as GISS and HadCRUT data claims 1998, 2005 and 2010 as being statistically tied for the warmest years in recorded history

A commonality of all these years was that these were El Niño years, which is a naturally occurring oceanic cycle - statistically better treated as as an outlier.

Further, to use a stock market analogy, this temperature peak is indicative of what could be the equivalent of a strong resistance level.  More importantly, a triple top is a highly bearish signal and that does seem exactly happening to the climate currently as well as evidenced by the current cooling trend!

The latest NASA-UAH satellite global temperature data for month, ending May 2012 below  shows that for the period 1979-2012, global temperatures stood at a mere 0.29 deg C.

 
So where’s the accelerated global warming the ICRIER-GC study bases itself as their axiom? If there is no warming, what’s the use of the solutions they peddle?

The ICRIER-GC study also claimed a 2 deg C rise is predicted by 2030 (presumably based on the IPCC model forecast). This is less than 18 years away. At the current rate of 0.09 deg C per decade warming in India, is a 2 deg C rise even possible by 2030?

So let us speculate on the temperature profile needed to confirm this IPCC prediction. If the trend lines of the two plots (current and forecasted) had to coincide, it is apparent that it is not sufficient that temperatures simply rose to meet the predicted line. This is because  the trend line of the actual temperatures would then be below the trend line of the modeled temperatures.

Even if the timeline is extended to 30 years from now, the rate of temperature rise needed is still extremely high and thus looks highly improbable to be realized.  And the prospect of a  4 deg C global temperature rise by end of this century, as predicted by the IPCC, again simply does not look probable at all, going by current temperature trends.

More significantly, the latest SREX IPCC Report AR5 to be released next year acknowledged that the prospect of any global warming, leave alone accelerated warming, does not seem even probable during the next 2-3 decades!: 
 “...climate change signals are expected to be relatively small compared to natural climate variability".
In plain IPCC speak, it means that the signals of the positive external forcing of CO2 (global warming) is expected to be overwhelmed by forces of natural variability (global cooling) in future!

This statement by the IPCC is heavily loaded signifying a whole scale retreat of the AGW theory. If the IPCC conceded that natural variation exists and can have a negative effect exceeding the warming caused by greenhouse gases to cause cooling, there is no reason logically why  natural variation could not have behaved similarly to account for the warming seen during the period 1977-98. 


Jochem Marotzke, Director of the warmist Max Planck Institute for Meteorology in Hamburg admitted the lack of warming in an interview and confessed being unable to explain it:
"In the models they occur about every 80 years. However, none of them up to now have shown a pause of 15 years. Also the models that run on the super-computers of the Hamburg Climate Research Centre also show such plateau phases. The physical causes are still unclear, and ours show them occurring at other times. Thus the models are not consistent with the current observations".
According to the NOAA State of the Climate 2008 report, if climate computer model  do not show that the planet has  warmed for periods of 15 years or more, the climate models predicting man-made warming from CO2 will be falsified at a confidence level of 95%. The Climategate emails in addition have several references of IPCC scientists admitting the cooling trend.  In one of the hacked Climategate emails, Phil Jones, the Director of UK’s CRU, East Anglia University was found observing: 
“...the no upward trend has to continue for a total of 15 years before we get worried"; 
Since 1998, there has been an absence of statistically significant warming and 2013 would mark 15 years of a no warming trend. Such a conclusion is apparent which ever global temperature dataset is referred to and cuts across the surface vs satellite temperature dataset divide. Climate models are on verge of being falsified at the 95% confidence level in a matter of months and would trigger the signal to revert back to the null hypothesis that man-made CO2 is not causing global warming.

The hacked Climategate emails revealed that climate alarmist scientists had even longer been aware of the lack of warming as admitted in their private communications as could be observed in the following extracts of these emails:     
 1) I think we have been too readily explaining the slow changes over past decade as a result of variability–that explanation is wearing thin. I would just suggest, as a backup to your prediction, that you also do some checking on the sulphate issue, just so you might have a quantified explanation in case the prediction is wrong. Otherwise, the sceptics will be all over us–the world is really cooling, the models are no good, etc.  http://bit.ly/eIf8M5

2) Yeah, it wasn’t so much 1998 and all that that I was concerned about, used to dealing with that, but the possibility that we might be going through a longer – 10 year – period [it's been over 13 years now since January 1998] of relatively stable temperatures beyond what you might expect from La Nina etc. Speculation, but if I see this as a possibility then others might also. Anyway, I’ll maybe cut the last few points off the filtered curve before I give the talk again as that’s trending down as a result of the end effects and the recent coldish years. http://bit.ly/ajuqdN

3) The scientific community would come down on me in no uncertain terms if I said the world had cooled from 1998. OK it has but it is only 7 years of data and it isn’t statistically significant. [stated by Phil Jones in 2005] http://bit.ly/6qYf9a
At a time wherein the AGW theory stands at the precipice of being falsified, the ICRIER-GC study still treats it as the gold standard to recommend so called solutions as adaptation measures for agriculture to counter a future “accelerated warming” trend!

 IMPACT OF CLIMATE ON GDP

ICRIER-GC: “It is predicted that for every 2 deg C (which has been predicted by 2030) rise in temperature, the GDP will reduce by 5 per cent.”

This claim that warming could significantly eat into the GDP is nothing but a recycling of those made by the Stern Review on the Economics of Climate Change (October 2006) which took climate scaremongering to dizzy new heights. It was compiled by a team headed by former World Bank chief economist Nicholas Stern at the request of Britain’s Tony Blair government. It argues that: 
 "..if we don’t act, the overall costs and risk of climate change will be equivalent to losing at least 5% of global GDP [gross domestic product] each year, now and forever."
 In the worst-case scenario of his report, the estimates of damage: 
"..could rise to 20% of GDP or more, causing major disruption to economic and social activity, on a scale similar to those associated with the great wars and the economic depression of the first half of the 20th century..
In contrast, stabilizing greenhouse gas emissions at no more than 550 parts per million (ppm) would ‘avoid the worst impacts of climate change’, and the cost would be ‘limited to around 1% of global GDP each year’.
 For India the report estimates that by 2030 significant drought could produce countrywide agricultural losses of more than $7 billion, decreasing the income of 10% of the population. Under the high climate change scenario, severe droughts occurring historically every 25 years could happen, every eight years. However, referring to the state of Maharashtra, mitigation measures such as more efficient irrigation, better drainage construction and crop engineering could eliminate much of this loss due to drought.

Stern’s message is that either we spend $450 billion per year now, or we’ll end up paying up to $9.6 trillion per year later. Many scientists and economists have expressed concern at the poor quality of the Stern Report.

Economist Richard Tol calls it ‘alarmist and incompetent’, and points out that it selectively quotes only the most pessimistic studies on the impacts of climate change. Stern’s doomsday visions are based on the use of an artificially low discount rate to assess whether it makes sense to spend money now to reap a hypothetical payoff in many decades’ time. Such was the criticism of the report; it was rejected at the Copenhagen Climate Summit to be part of its closing statement.

In the latest SREX IPCC Report AR5, the IPCC finally concedes that there is no scientific evidence to attribute extreme events to AGW:
"Long-term trends in normalized economic disaster losses cannot be reliably attributed to natural or anthropogenic climate change..."


Agriculture’s contribution to GDP of the country has been steadily going down over the years and now stands just around 15%. Even if agriculture production declines by 10% of average in any year, this can’t even take a toll of 1% of our GDP. Historically the 2004 Asian Tsunami and the earlier Gujarat Earthquake that caused widespread damage could not cause more than a pinprick to our GDP. This was not only the case with India but also Thailand; Indonesia; Sri Lanka and Maldives - all significantly impacted by the massive Tsunami waves. Reconstruction efforts that followed was found to spur their GDP growth! 

In the year 2010, which global surface temperature datasets  claimed was the warmest year in the entire instrumental record history, the country’s agriculture growth rate still stood at +0.4% - this when the SW Monsoon demonstrated a rainfall deficiency by over 20%. The expansion of irrigation over the years have already inbuilt a certain degree of adaptation cushion to a warming climate.

The third and most important factor is that all these calculations are based on IPCC’s various scenario computer modelling whose projections do not match real world observations and thus cannot be taken seriously. This issue is discussed in greater detail in the later section of this critique.

 CLICK TO ENLARGE

The last but more significant problem is that economic growth is actually the solution to the perceived problems, not the cause. Stern, being an economist, failed to recognise this truism. As seen in the above graph taken from the Stern Report, higher economic growth will more than offset damages, if any, from global warming.

  SEASONAL WARMING

ICRIER-GC: “This warming is mainly contributed by the winter and post-monsoon seasons, which have increased by 0.80°C and 0.82°C in the last hundred years, respectively. The pre-monsoon and monsoon temperatures also indicate a warming trend.”

So we learn from this study that the winter, pre-monsoon and monsoon seasons are all indicating a warming trend. If so, this would leave our tropical summer, seasonally and typically where temperatures hits the roof, as the only one season that is now presumably cool in the country. If only true, common Indian citizens should give a huge sigh of relief.

Such an analysis however does not make much sense. So let’s look at the Kothawale et al study once again. Its title goes as:
“Surface air temperature variability over India during 1901–2007, and its association with ENSO”. 
So what’s ENSO? It stands for El Niño Southern Oscillation - the alternate cycles of El Niño and La Niña. And this is what the Kothawale et al study abstract actually says: 
“On a seasonal scale, pronounced warming trends in mean temperature were observed in winter and monsoon seasons, and a significant influence of El Niño Southern Oscillation events on temperature anomalies during certain seasons across India was observed. 

The composites of maximum and minimum temperatures of El Niño years showed positive anomalies during monsoon, post-monsoon and subsequent year winter and pre-monsoon seasons. However, statistically significant positive anomalies were observed only during monsoon and post-monsoon seasons over large areas of the country.

The composite temperature anomalies of La Niña years were almost opposite to El Niño composites: the negative temperature anomalies associated with La Niña events persisted from the current monsoon season to the subsequent year pre-monsoon season.“  
So what we find here is the  IGRIER-GC study stooping so low that they take to misquoting the Kothwale et al study in order to portray an accelerated warming alarmist scenario consistent with the axiom of their study.

What the Kothwale et al study actually say is that positive seasonal temperature anomalies are typical of El Niño years while negative seasonal temperature anomalies are typical of La Niña years! Both El Niño and La Niña are natural climatic phenomena and it is only perfectly logic that temperatures spike during an El Niño event and plunges during a La Niña event. Both El Niño and La Niña repeatedly occur in 3-5 years alternate cycles.

However, to portray a warming trend, only data of El Niño years are cherry picked. The fact that in La Niña years, the same seasons demonstrate negative temperature anomalies and in non-ENSO years, the data show little or no temperature fluctuations are suppressed by research!

To be noted, the intensity and frequency of El Niños and La Niñas are  linked to the Pacific Decadal Oscillation (PDO) as later discussed in this critique.  As and when the PDO flips, it accordingly significantly impacts these seasonal temperature variations.


But perhaps more interesting are the Kothawale et al study’s Tmax and Tmin graphs as could be seen above. You will find the Tmax trends are flat, in fact currently very slightly declining at the rate of -0.03 deg C/per decade.  So there is no reason for any warming scare on the score of Tmax.
It is only Tmin trends that suggest a currently increasing temperature trend at 0.17 deg C/per decade. But even they are not as extreme as they were in the past, in fact demonstrating relatively a cooling trend as compared to the period 1976-1997.

The scientific understanding of Tmin’s effect on agriculture is too rudimentary but generally plants respond to the combined effect of Tmax and Tmin and not to their individual effects separately. This is evidenced by the fact that global food production quadrupled during the last century even when the planet warmed. This couldn’t have been possible if Tmin adversely affected agriculture productivity. Besides an increase in Tmin should logically boost nocturnal productivity of plants, a principle successfully applied in greenhouse/glasshouse agricultural productions.

This scenario of the Tmax slightly cooling while the Tmin slightly warming, should theoretically lead to reduction rather than increasing of weather extremities. This is so as its impact would decrease the contrast between hot and cold temperatures which are main drivers of wind speeds. This is confirmed by the observation that average wind speeds are reducing both globally and in India.

The irony is that within this scenario where average wind speeds are significantly decreasing, climate alarmists are still hyping on wind energy as an option for policy adoption as a replacement for fossil fuels! This serves as an illustration why foreign funded NGO recommendations are to be viewed with extreme caution, whether they come in the form of Gene Campaign; Oxfam; Greenpeace; ChristianAid or ActionAid. Their world view is not to give a fillip to the economy but to wreck it. Tamilnadu which attracts a disproportionate share of foreign funding of NGOs in the country went so called “Green” with wind energy constituting almost one-third of their overall energy mix. The results are there for all to see - from a net exporter of power, the state was reduced to a net importer of power! 

CLIMATE CHANGE & MONSOONS

ICRIER-GC: “Overall in India, it is predicted that, physical impact of climate change will be seen as (2) changes in rainfall (both distribution and frequency) during monsoon and non-monsoon months, (3) a decrease in the number of rainy days by more than 15 days, (5) an increase in the intensity of rain by 1-4mm/day”

The IPCC AR4 report had this to say of future of the Indian Summer Monsoons:
“Using eight AOGCMs, Ueda et al. (2006) demonstrate that pronounced warming over the tropics results in a weakening of the Asian summer monsoon circulations in relation to a reduction in the meridional thermal gradients between the Asian continent and adjacent oceans.

Despite weakening of the dynamical monsoon circulation, atmospheric moisture build-up due to increased greenhouse gases and consequent temperature increase results in a larger moisture flux and more precipitation for the Indian monsoon (Douville et al., 2000; IPCC, 2001; Ashrit et al., 2003; Meehl and Arblaster, 2003; May, 2004; Ashrit et al., 2005).”
Put simply, the IPCC models show that while the Indian monsoon increases in strength as the earth warms, wind circulation weakens. That contradiction could be possible because the winds should now carry more water vapour with them—with the earth getting hotter, more water evaporates off the Indian Ocean and is drawn on to land by the subcontinent’s low-pressure ‘vacuum’ created by the summer heat.  Also assumed are decreases in snowfall over western Eurasia and the Tibetan plateau during winter and spring, which intensifies the low pressure over India, which are considered an extremely positive indicator for a good monsoon.

CLICK IMAGE TO ENLARGE
While the IPCC models projects higher rainfall for India, as the IMD graph illustrates the monsoons demonstrate a 30-40 year multi-decadal cycle of alternate above average and below average cycles. The latter finds no alignment with the AGW theory but find relatively a much better correlation fit with the Pacific Decadal Oscillation (PDO) cycle.

As mentioned earlier, the AGW theory states that global warming induces an increase in global precipitation through the augmentation of water evaporation. Warmer seas should heat up the monsoon winds that carry moisture from the ocean to the land. In turn, warmer winds should carry more moisture, so warmer oceans should lead to more rain. This should in turn imply that global relative humidity and evaporation levels should increase. So goes the AGW theory.

As the IMD graph shows, we in India have had no such luck. Total rainfall during the Indian Summer Monsoon is stable but with a slight tendency towards a negative mean departure, practically falsifying the AGW hypothesis!! Global relative humidity and evaporation levels have been decreasing - indicating a cooling trend. BN Goswami, Director of IITM and chief of India’s Monsoon Forecasting Mission admitted during a seminar in Pune: 
“The potential evaporation has decreased over the country and there has been a weakening of surface winds.”

 
Rainfall is a significantly larger variable to agricultural productivity than temperature. Despite warming, agriculture booms where rainfall is adequate and is challenged when rainfall fails. While our Met Dept and climatologists were still desperately trying to figure out the reason for declining rainfall pattern for the last century, it is clear that global warming doesn’t increase the Indian summer monsoon rainfall as AGW models predict; it in fact appears to have reduced it: 
“In yet another pertinent study, Fleitmann et al. (2004) developed a stable isotope history from three stalagmites in a cave in Southern Oman that provided an annually-resolved 780-year record of Indian Ocean monsoon rainfall.  Over the last eight decades of the 20th century, when global temperatures rose dramatically as the earth emerged from the Little Ice Age and entered the Modern Warm Period, Indian Ocean monsoon rainfall declined dramatically, while the other most dramatic decline in monsoon rainfall coincided with the major temperature spike that is evident in the temperature records of Keigwin, Holmgren et al. and McIntyre and McKitrick.”
In contrast to the AGW theory, an Indian Institute of Astrophysics study illustrates, the monsoon indicates a perfect correlation fit with sunspot activity:
“...We subject the Indian Monsoon rainfall and the sunspot occurrence activities with FFT and wavelet analysis. It is found that both the activities have a common periodicity of 22 year indicating that the solar cycle and activity phenomena strongly influence the rainfall activity.”

  CLICK IMAGE TO ENLARGE

Regarding the claim of the ICRIER-GC study that: “Changes in rainfall (both distribution and frequency) during monsoon and non-monsoon months”; the latest IPCC SREX Report observed:
“There have been statistically significant trends in the number of heavy precipitation events in some regions. It is likely that more of these regions have experienced increases than decreases, although there are strong regional and sub-regional variations in these trends.”
Note that the IPCC does not give a very high probability for such trends. There are of course changes in the distribution and frequency of rainfall but certainly with no cause for alarm as could be observed from the above table from an IIT-Rookeee-National Institute of Hydology study where the underlined data marks those statistically significant deviations.

All areas of the country cannot be assumed to have even rainfall. At any point of time, some areas will always experience higher than average rainfall; some others will experience lower than average rainfall with most areas demonstrating no change in rainfall.  The spatial distribution also changes over time as the climate is not a static phenomenon but changes with reference to time. A study, “A 135-Year Rainfall History of India: 1871-2005” published in the Hydrological Sciences Journal gives a confirmation these facts:
“Half of the sub-divisions showed an increasing trend in annual rainfall, but for only three was this trend statistically significant...
Similarly, only one sub-division indicated a significant decreasing trend out of the 15 sub-divisions showing decreasing trend in annual rainfall...

In terms of monthly rainfall during the monsoon months of June to September, they found that "during June and July, the number of sub-divisions showing increasing rainfall is almost equal to those showing decreasing rainfall, and in August the number of sub-divisions showing an increasing trend exceeds those showing a decreasing trend, whereas in September, the situation is the opposite...

In addition, the majority of sub-divisions showed very little change in monthly rainfall in most of the months while for the whole of India; no significant trend was detected for annual, seasonal, or monthly rainfall....

Thus this study could not find any evidence of the increase in rainfall that the IPCC had suggested would occur over India due to “accelerated global warming.”
It has to be appreciated that the phenomenon of monsoons are not fully understood, leave alone predicted successfully. The monsoons, by character, exhibit a wide range of natural variability on the spatial, temporal, intra-seasonal, inter-annual and decadal scale that characterise it’s pattern of distribution, frequency and intensity of rainfall. The monsoon has always had its natural vagaries and it is going to show them in future too.

Nothing in the ICRIER-GC paper adequately explains or provides empirical evidence that “climate change” has created a totally new set of variability of monsoons that exacerbate its extreme event potential. In contrast to the ICRIER-GC paper, the MoE&F paper - ‘Climate Change and India: A 4X4 Assessment’, provides a very balance and non-alarmist discussion for monsoon variability in terms of distribution, frequency and intensity.  Read here.

But the problem with the MoE&F paper is their reliance on computer model simulation for forecasting the future. The Indian Meteorological Department (IMD)’s statistical model has a success rate of only 22% while their new dynamic model being experimented with has 26% - meaning that their predictions have only one out of four or five probability of getting their monsoon predictions right. This implies that computer modelled monsoon projections are highly undependable. Rupa Kumar Kohli, now head of the World Meteorological Organization (WMO), one of the two co-founding agencies of the IPCC conceded to the Times of India
“Empirical models are statistical projections based on observed meteorological data. They are limited according to the data you are using.  Climate models are three-dimensional, atmospheric-general circulation models, global in nature. These use known thermodynamic laws to describe the atmosphere and its motions. So there's no data window.

From the scientific perspective, models still have problems in realistically representing the Indian monsoon. This has implications for the models' utility on a global scale. Improving monsoon in models is a major challenge even in the developed world.”

Agriculture besides should primarily adapt to the weather first and then climate (average weather over a period) in that order. This should be considered the first principle for appropriate adaptation strategy as far as agriculture is concern.

And why is this so?  This is because climate is just a mean curve that had smoothened out all extreme weather fluctuations. For academic researchers who produced the ICRIER-GC paper, such a smoothened curve may mean nothing more than a statistical necessity for analysis purpose. But to the farmers, who primarily live off the income of their fields, these year-to-year fluctuations are matter of life and death for them.

For example, if we were to assume the temperature increase projections of 2 deg C by 2030 of the ICRIER-GC study’s is successfully realized, it will be still extremely erroneous to infer that temperature increases follow a linear pattern year-to-year. This is so as weather and consequently climate are basically non-linear, chaotic systems which means climatic changes are basically random walks and thus consequently renders most cause-effect assumptions redundant.

Explained more simply, due to the chaotic and non-linear character of the climate system, the 2012-30 temperature curve could take on different shapes because of these random walks. For example:
-  it is possible that the planet cools to -2 deg C till 2026 and then temperature spikes suddenly to demonstrate a +2 deg C temperature anomaly by 2030! 
       
-  the planet warm to 1.8 deg C till 2015, and then rapidly cool to -1.5 deg C till  2020 and then return to normal by 2027 before demonstrating a + 2 deg  C temperature spike by 2030. 
In each of these hypothetical scenarios, the adaptation strategies that would be needed at different time points will be different as compared to the standardized solutions the ICRIER-GC paper dishes out.

Further such linear projections of temperature rises do not factor in teleconnection climatic events such as ENSO (El Niño Southern Oscillation) which have an even more pervasive impact on the Indian summer monsoons. e.g. Let’s assume that the current monsoon season is influenced midway by an El Niño that can cause below average rainfall while for 2013-14 and 2014-2015 seasons we have a back-to-back La Niña that causes above average rainfall within the country.

Such ENSO events can have an insidious influence on agriculture and to the lives and livelihoods of our farmers and need to be factored into any adaptation strategies for agriculture. Even here, the ICRIER-GC paper is found totally lacking.

Weather being also a chaotic system is the reason why predictions are extremely difficult beyond 5 days, where the skill of the model begins to progressively decline as the time period extends itself. If this is the situation with weather, imagine the nightmare of predicting climate changes! Monsoons additionally show wide variability at the inter-annual and decadal scales in terms of its overall mean, spatial distribution and “breaks”.

Climate Smart Agriculture (CSA) therefore should encourage adopting flexible year-to-year adaptation solutions that find a strong alignment with the monsoon’s natural dynamic behavioral characteristics. Instead what we find are NGOs offering straight jacket, one-fit-all solutions as observed in the ICRIER-GA paper. 

CLIMATE CHANGE & CYCLONES

ICRIER-GC: “Overall in India, it is predicted that, physical impact of climate change will be seen as an (6) increase in the frequency and intensity of cyclonic storms.”


The AGW theory states that tropical cyclonic winds would increase with increasing ocean temperature. But only the northern parts of the Indian Ocean demonstrated a consistent warming trend for the period 1976-2007. As seen in the above graphs, the frequency of cyclones decreased even in the northern parts of the Indian Ocean, leave alone the Bay of Bengal and the Arabian Sea!!!

These trends are consistent with global cyclonic/hurricane trends. According to Ryan N. Maue of the Center for Ocean and Atmosphere Studies, Department of Earth, Ocean and Atmospheric Science, Florida State University, tropical cyclone accumulated cyclone energy (ACE) has exhibited strikingly large global inter-annual variability during the past 40-years. Since 2006, Northern Hemisphere and global tropical cyclone ACE has decreased dramatically to the lowest levels since the late 1970s. Additionally, the global frequency of tropical cyclones has reached a historical low. The latest ACE graph is given below from which it can be discovered how low it is.


Tropical cyclones have active and passive cycles, alternating roughly every 20-25 years. Since AGW ignores natural variability in favour of CO2 as the prime driver of climate, the lack of frequency and intensity of global tropical cyclones hitting a low, ended up falsifying the AGW theory.
Eating crow, the latest SREX IPCC AR5 report finally conceded there is no scientific evidence to attribute extreme events like cyclone to AGW:
“There is low confidence in any observed long-term (i.e., 40 years or more) increases in tropical cyclone activity (i.e., intensity, frequency, duration), after accounting for past changes in observing capabilities.”
Yet, we find the ICRIER-GC paper still warning us of increasing cyclones!

3. How has climate changed in the past and what can we learn from them in terms of its impact on agriculture?

Synopsis: “Global cooling is generally associated with a collapse of civilization whereas global warming is associated with great advances in civilization…  If we need to fear something, then the best candidate is a global mega-drought associated with cooling and driven by solar activity. ” (Ian Plimer).

The Little Ice Age and Medieval Warm Period readily testifies to this fact. Besides, if increasing temperature and CO2 are detrimental to agriculture, it won’t be possible to explain how global agriculture production demonstrated an almost a 4 fold increase during the last century.

Carbon is the building block of life. Notwithstanding the attempts by climate activists to term it a pollutant, all life in Earth is carbon based life forms, with a handful of exceptions.

The carbon cycle moves carbon from the atmosphere, through the food web, and returns to the atmosphere. This is through a process called photosynthesis, unique to plants. Carbon dioxide, water, and sunlight combine to produce glucose, water, and oxygen as given in the following equation:

6CO2 + 12H2O + sunlight = C6H12O6 + 6O2

According to AGW theory, an increase in CO2 leads to increases in global temperatures which in turn should induce an increase in global humidity and precipitation trends through the augmentation of water evaporation. So all three inputs - temperature, CO2 and water availability (increase precipitation from ocean warming) - critical for photosynthesis, should be theoretically increasing according to AGW theory due to global warming. We know for sure that CO2 has increased in the atmosphere as we can physically measure it. We are further told the world is warming with various data but the surprising aspect of this claim is the absence of statistically significant increased humidity and precipitation trends which must accompany a global warming trend! In fact, global humidity and precipitation trends offer themselves as the perfect proxies for temperature trends!

Theoretically, by increased availability of critical inputs in a chemical reaction like photosynthesis, agriculture productivity can be increased. This hypothesis is proved in practice through the use of greenhouses or glasshouses in agriculture wherein both temperature and CO2 levels are elevated to result in increased yields.

We are told by the AGW theory that CO2 drives temperatures and not the other way around. This claim is falsified as CO2 levels rises and falls with the seasons or time of day. CO2 levels rise in the autumn and winter as temperature declines as green plants go dormant or die. The plants cease to “process” CO2 as part of their food chain. In spring and summer, CO2 levels fall as temperature rises, these same plants come back to life and consume CO2 in photosynthesis CO2 levels accordingly fluctuate due to the differential metabolic rates of plants during nights and days. The principle of greenhouse/glasshouse centres on increasing agriculture productivity through not only controlling temperatures and CO2 levels but also by ensuring their elevated levels during the growing season of plants besides increasing nocturnal productivity of plants for higher yields.

 
CO2’s beneficial effect to agriculture by acting as an aerial fertilizer is proved by many research studies. Physiologically, most plants growing in enhanced CO2 environments exhibit increased rates of net photosynthesis.

The higher photosynthesis rates are then manifested in higher leaf area, dry matter production, and yield for many crops (Kimball, 1983; Acock and Allen, 1985; Cure, 1985). In several cases, high CO2 has contributed to upward shifts in temperature optima for photosynthesis (Jurik et al., 1984) and to enhanced growth with higher temperatures (Idso et al., 1987).

CO2 enrichment also tends to close plant stomates, and by doing so, reduces transpiration per unit leaf area while still enhancing photosynthesis.  However, crop transpiration per ground area may not be reduced commensurately, because decreases in individual leaf conductance tend to be offset by increases in crop leaf area (Allen et al., 1985).

In any case, higher CO2 often improves water-use efficiency, defined as the ratio between crop biomass accumulation or yield and the amount of water used in evapo-transpiration. Increases in photosynthesis and resistance with higher CO2 have been shown to occur at less than optimal levels of other environmental variables, such as light, water, and some of the mineral nutrients (Acock and Allen, 1985).

The above graph illustrates the perfect correlation of food production and increase in CO2 atmospheric concentration. But correlation is not causation and the Green Revolution and Norman Borlaug had alot to do with the food production increase seen during this period. But what it does confirm is that increasing temperatures and CO2 doesn't seem to have any detrimental effect on food production.

Nonetheless, a 2009 research study conducted by the University of Illinois and the U.S. Dept. of Agriculture, published in the journal Proceedings of the National Academy of Sciences concluded elevated levels of CO2 significantly boosts plant respiration which in turn significantly boosts yields. Since plants draw CO2 from the atmosphere and make sugars through the process of photosynthesis the study aimed to ascertain how elevated CO2 affects plant respiration and accordingly influence future food supplies by the extent to which plants can capture CO2 from the air and store it as carbon in their tissues. Plants were grown in an environment containing CO2 at 550 ppm compared to those grown in ambient conditions with CO2 380 ppm. Their conclusion:
"At least 90 different genes coding the majority of enzymes in the cascade of chemical reactions that govern respiration were switched on (expressed) at higher levels in the soybeans grown at high CO2 levels. This explained how the plants were able to use the increased supply of sugars from stimulated photosynthesis under high CO2 conditions to produce energy.

The rate of respiration increased 37 percent at the elevated CO2 levels. The enhanced respiration is likely to support greater transport of sugars from leaves to other growing parts of the plant, including the seeds.

The expression of over 600 genes was altered by elevated CO2 in total, which will help to understand how the response is regulated and also hopefully produce crops that will perform better in the future."
Despite all the beneficial effects of increased CO2 to agriculture, climate alarmists tell us that these basic principles of science do not work in the present climate ‘crisis’ as climate as a system has become more complex and the present warming trends if allowed to accelerate would adversely affect agriculture.  If this is true, it needs to be validated from past climatic behavioral impact on agriculture.  So let’s have a look at it.

 
As it is not possible here to discuss the effects of climatic changes on agriculture during Earth’s entire geological history, this paper will confine its scope to the last 2,000 years.  The graph above clearly establishes that both temperature and CO2 has widely fluctuated within Earth’s geological history, showing poor correlation with each other.

We are presently within the Holocene Epoch, an inter-glacial period within the present Ice Age. The typical inter-glacial period lasts around 12,000 years though there is a one or two that lasted around 28,000 years. Since the Holocene Epoch’s estimated age is over 11,500 years, it’s anyone’s guess when it is ending. Man evolved during the last ice age, the Younger Dras and lived mainly as food gathers and scavengers. 

Modern man apparently evolved into his current genotype between 40,000 and 200,000 years ago. But it was only because of the warmth provided during the Holocene; he was able take to agriculture, by actually growing crops from which he had so far only collected till then.

The rapid cooling in the late glacial period took about 100 to 150 years to complete and realized about 2 deg C variation in temperature within 100 years, more than is being forecast for the next century. There were at least 3 periods in the current epoch that were warmer than present - the Holocene Optimum; Roman Optimum and the Medieval Warm Period (MWP). Even the IPCC admits:
“The early Holocene was generally warmer than the 20th century”.
Since CO2 levels were lower in these periods despite temperatures being higher than present, these eras contradicts the AGW Theory of CO2 driving up temperatures. 


MEDIEVAL WARM PERIOD

 
 
The Medieval Warm Period (MWP) being more recent to current times offers a great deal of literature as documented evidence of the period. MWP refers to a time interval between AD 900 and 1300 which were warmer than during the period known as the Little Ice Age that followed it, and also warmer than the period of glacial advance preceding the MWP. Large extents of Iceland were farmed in the 10th century AD. At this time, Norse Vikings colonised Greenland, while a reduction of sea ice allowed regular voyages at these northern latitudes. The Vikings could do this because there was less sea ice. They travelled by boats to Greenland among other places through seas that would later become blocked by sea ice during the Little Ice Age.

During the MWP, history records tremendous growth in the population, major construction projects, a significant expansion in arts and culture - all indicating of a  that society that  is prosperous. The population growth of Europe had exploded, reaching levels that were not matched in some places until the nineteenth century. If the population is expanding, food must be plentiful, disease cannot be overwhelming, and living standards must be satisfactory. Art and culture flourished - the Renaissance, Shakespeare, Haydn, Schubert, Mozart, and Beethoven all belong to this time all indicating prosperity. 

LITTLE ICE AGE (LIA)

The transition from the Medieval Warming to the Little Ice Age (LIA) seems to have been abrupt with climate change believed to have occurred in less than three decades and was caused by a decrease in solar activity. LIA announced its arrival in a spectacular manner - the failure of agriculture to cope with cooling led to mass famines and this is how Wikipedia described it: 
“The Great Famine of 1315–1317 (occasionally dated 1315–1322) was the first of a series of large scale crises that struck Northern Europe early in the fourteenth century.

From the Pyrenees to Russia and from Scotland to Italy it caused millions of deaths over an extended number of years and marks a clear end to an earlier period of growth and prosperity during the eleventh to thirteenth centuries..” 
While not a true ice age, the term was introduced into the scientific literature by François E. Matthes in 1939. The Little Ice Age had two distinct phases: in phase one, from 1280 to 1550 AD, the climate was characterized by large and sudden variations in temperature. In phase two, from 1550 until 1850 AD, it was still colder. The period known as the Maunder Minimum (1645 – 1715) was the coldest time within the Little Ice Age and coincidence with a period where sunspots were extremely rare.  Professor Ian Plimer in his book Heaven and Earth describes the impact of LIA on agriculture: 
“Land abandonment, crop failure and soil losses were catastrophic because 90% of the population were subsistence farm families who needed enough grain to see them through winter and enough spare grain to sow for the following year’s crop. Both the quantity and quality of harvests were vital for survival. Grain rotted in the fields and sometimes couldn’t be planted at all.

Crop failure led to famine, famine led to disease and death, famine led to a breakdown in society and even cannibalism. Gangs of desperately hungry peasants roamed the countryside searching for food. The harvesting and storage of wet grain, especially rye, stimulated ergot fungus which ruined grain stockpiles. Hungry people ate mouldy grain which contained fungal toxins.”

The noted climatologist HH Lamb, who established the Climate Research Unit (CRU), East Anglia University, UK pointed out that growing season changed by 15 to 20 percent between the warmest and coldest times of the millennium. That is enough to affect almost any type of food production, especially crops highly adapted to use the full-season warm climatic periods. Using the price of wheat and rye, respectively, in various European countries during the LIA, Lamb correlated the variable with cold intensity.
Each of the peaks in prices corresponds to a particularly poor harvest, mostly due to unfavourable climates with the most notable peak in the year 1816 - "the year without a summer." One of the worst famines in the seventeenth century occurred in France due to the failed harvest of 1693. Millions of people in France and surrounding countries were killed at the time of Marie Antoinette, the last Queen of France in the 1790s who asked peasants to eat cake when peasants had no bread. 

According to Lamb, in Greenland, the Vikings did not survive the Little Ice Age. Greenland colonized during the Medieval Warming when the population was able to grow wheat and grass for their cattle and sheep; the cooling at the onset of the Little Ice Age brought about freezing temperatures that resulted in crop failures and famine. Increased sea ice made it difficult for fishing boats to reach the open sea. The dramatic malnourishment of the Viking population was demonstrated in a study that compared the height of skeletons before and after the onset of the Little Ice age. The average height of skeletons buried in the first 200 years after the beginning of the Little Ice Age is 12 cm (about 4 inches) less than skeletons buried during the Medieval Warming.



Dr Briesen, a visiting Professor at JNU, Delhi in a lecture gave an insightful understanding of the historic significance of the LIA. The cooling led to periodic outbreak of famines and agriculture stagnation that created a “hunger crisis” with an estimated 60 per cent of the European population simply struggling for survival. And as Europe's economy and agriculture went into a tailspin, this led to huge social unrest and political instability, plunging Europe into many major wars, the emphasis shifted to strengthening European armies and navies. This was a period also coinciding with the largest out-migration ever seen in their history, with Europeans drawn to new lands like North and South America, Africa, Australia and Asia.

The hunger crisis also created a powerful motivation for Europeans to get aggressive to conquer other parts of the world including India.  The late M.H. Panhwar, a historian from undivided India wrote an excellent book how the LIA affected the Indian sub-continent who were colonalized by different forces, including various European powers and the Central Asian Islamists during this time. Read here.

Since the 17th century, as European powers set up colonies in other parts of the world, new food products began arriving in Europe, which had been produced  abroad to serve the needy European consumers there. The foundations for a new food cycle were, ironically, laid outside Europe. Potatoes, for instance, originated from South America, liquor in large quantities was first distilled in the English colonies in North America, refined sugar imported from the Dutch, French and later English colonies, coffee initially from Mauritius and Sri Lanka and others.

“The demand for colonial commodities and the nutrition crisis modified European, including German, agriculture and led to the production of sugar beet, potato, and chicory. This production had a deep impact on agriculture and induced an often underestimated technological revolution in agriculture,” contended Dr Briesen.

BEING AN INCONVENIENT FACT, THE IPCC ERASES THE MWP & LIA


 
In their first report AR1 in 1990, the IPCC acknowledged that the periods such as the Holocene Optimum, the Roman Optimum and Medieval Optimum were warmer than present times. This could be observed in the upper graph. By 2001, the graph was changed with both the MWP and LIA disappeared and modern day warming represented as warming steeply, giving the shape of a hockey stick as seen in the bottom graph. It was produced by an IPCC climatologist called Michael Mann, who was then a Phd student who used tree rings as a temperature proxy.

The use of tree ring violates IPCC own standards in the use of proxies. In Section 2.3.2.1 of the IPCC TAR WG1 (Paleoclimate proxy indicators) has a whole sub-section devoted to a detailed discussion of tree ring data which indicates a very clear and explicit discussion of the shortcomings of high latitude tree rings and therefore discouraging its adoption as a proxy.

The hockey stick was consequently falsified by climate sceptics in peer researched studies and exposed for gross data manipulation, which Climategate emails exposed, was designed “to hide the decline” (temperatures). The statistical techniques used by Mann meant that whatever random numbers punched in, always generated always a hockey stick curve! The IPCC stopped using the hockey stick in their 2007 report and even removed it from their 2001 report, so much was their embarrassment.

One of the defenses of Michael Mann for the statistical treatment of historic temperatures in the hockey stick was the claim that the MWP and LIA were Europe or Northern Hemisphere specific climatic events. However, there are now several peer reviewed studies that prove that MWP and LIA were truly global events with evidences from all over the world. These are collaborated with evidence from other disciplines - history; archaeology; geology; literature; paintings etc.  A new peer reviewed study published in the renowned science journal - Earth and Planetary Science Letters - hammered the final nail to Mann’s hockey stick - by providing scientific evidences that the effects of the MWP and LIA were felt as far south in Antarctica.

Some of the studies, a majority of these peer reviewed, clearly establishes that the MWP and LIA affected India read here. here. here. here. here. here. here.

The Little Ice Age and Medeival Warm Period readily testifies to this fact the warming is beneficial for agriculture while cooling is detrimental. Now a new study published in the Journal of Geographic Sciences, using Leaf Area Index (LAI), concluded that LAI is on the increase during the present warming period. Three Chinese scientists used satellite data to detect changes occurring in vegetation throughout the world and concluded:
“Results show that, over the past 26 years, LAI has generally increased at a rate of 0.0013 per year around the globe. The strongest increasing trend is around 0.0032 per year in the middle and northern high latitudes (north of 30°N). LAI has prominently increased in Europe, Siberia, Indian Peninsula, America and south Canada, South region of Sahara, southwest corner of Australia and Kgalagadi Basin; while noticeably decreased in Southeast Asia, southeastern China, central Africa, central and southern South America and arctic areas in North America.”

Source: Liu, S., R. Liu, and Y. Liu. 2010. Spatial and temporal variation of global LAI during 1981–2006. Journal of Geographical Sciences, 20, 323-332.
A recent article in Forbes hits the hammer on the nail:
“A recent study of a wide variety of policy options by Yale economist William Nordhaus showed that nearly the highest benefit-to-cost ratio is achieved for a policy that allows 50 more years of economic growth unimpeded by greenhouse gas controls.

This would be especially beneficial to the less-developed parts of the world that would like to share some of the same advantages of material well-being, health and life expectancy that the fully developed parts of the world enjoy now. Many other policy responses would have a negative return on investment. And it is likely that more CO2 and the modest warming that may come with it will be an overall benefit to the planet.”
Removing subsidy for chemical fertilizers in the Indian economy perhaps cannot be accomplished without some adverse impact on agricultural yields. But pump more CO2 into the atmosphere and this negative impact on removal of fertilizer subsidy will find a mitigatory effect. The more CO2 pumped into the atmosphere, the greater this mitigatory effect.

4. What is the basis for predicting future climate?

Synopsis: There are two approaches to climate prediction. One approach is through use of AGW based climate models and the other is through models based on observational data and natural modes of climate variability. The ICRIER-GC paper bases its future projections on AGW climate. 
“The hypothesis and the computer model simulation used to predict global climate has consistently failed. It’s not surprising because weather forecast models don’t work either, and climate is the average of the weather. It is not science and should never be the basis of policy. “

(Richard Lindzen - Professor in MIT and a former IPCC Lead Reviewer, who quit the body accusing the IPCC of being a political rather than a scientific body).
The observation of rising atmospheric CO2, alone, is not enough to certify anything except a rising level of atmospheric CO2. Not one of the projections of climate models had been realized, throwing the AGW theory in disarray.

On the other hand, models based on natural climate indices have runaway successes of predicting the past and present climate and therefore more suited for forecasting future climates.

CLIMATE MODELS

ICRIER-GC: “It is predicted that for every 2 deg C (which has been predicted by 2030) rise in temperature, the GDP will reduce by 5 per cent.”

The media and NGOs act as if there is a ring of absolute certainty about these “predictions”. But they are not even “predictions” as admitted by the IPCC but merely “projections under various assumption scenarios”. The basis of ICRIER-GC study is entirely on the projections of these climate models though they treat them as “predictions”.

According to the 2007 AR4 report of the IPCC; model based projections of future global warming range from a 1.1 C to a 6.4.C temperature. Recent studies go even further to project an increase of more than 8 degrees. Such a massive range implies enormous uncertainty in climate modelling results.

In one of the IPCC reports viz AR3 2001, the IPCC admitted: 
“In sum, a strategy must recognise what is possible. In climate research and modelling, we should recognise that we are dealing with a coupled non-linear chaotic system, and therefore that the long-term prediction of future climate states is not possible.

The most we can expect to achieve is the prediction of the probability distribution of the system’s future possible states by the generation of ensembles of model solutions. This reduces climate change to the discernment of significant differences in the statistics of such ensembles.”


A German Phd thesis commented in the same vein:
“The chaotic, nonlinearity of the climate not only prevents a thorough understanding of the system but also the impossibility of observing all relevant climate variables in the oceans, the atmosphere, and other spheres...

The main practical problem of climate modelling is the problem of parameterisation, which is the need to represent processes of the climate system in the modelling approach that are insufficiently understood or on a smaller scale than the resolution of the model.

Parameterisations in nonlinear models make it nearly impossible to detect chains of causes and effects in a climate model. There are many processes in the climate system which has already been discovered but which are not understood or are too small to consider in climate models.
 
In order to nevertheless represent them in models simulating the climate they are displayed as parameters. Some parameters’ values can be assigned that have counterparts in the real world but others result only from model fitting...

This lack of data is a fundamental problem and the most important one for climate modelling. The nonlinearity of the climate system is accompanied by its enormous complexity, which makes it even more disturbing. Many climatic processes originate in internal feedback mechanisms of the system’s dynamics that interact in a nonlinear and thus unforeseeable way.”
If the model is flawed, if important parts have been left out, or the initial conditions are incorrect, no model can provide trustworthy answers. It is an axiom of mathematical modelling of natural processes that only a fraction of the various events, large and small, that constitute the process are actually expressed in the equations. The other points may not be so self-evident or absent. And this is only one of its fundamental problems of computer models.

The major limitations of computer models are: 1. Model imperfection 2. Omission of important processes 3. Lack of knowledge of initial conditions 4. Sensitivity to initial conditions 5. Unresolved heterogeneity 6. Occurrence of external forcing 7. Inapplicability of the factor of safety concept.

Nevertheless, the use of computer models has been passed off as science fact when it is actually a technique used when real observations and genuine understanding are not available. As fundamentally weak as the IPCC's methodology is, the media and the public are brainwashed that facts have been established and consensus has been reached in the scientific community.

In a chaotic system, very tiny changes can create large impacts.  This logic had been used to support the claim that CO2 which constitute a miniscule 0.03% of the atmosphere is the main driver of climate change. Applying the same logic, climate computer models embedded with colossally large error rates should generate even greater degree of errors in their forecast of future global temperatures.


But a group of scientists led by Dr. Koutsoyiannis used the IPCC’s gridded 20th century global climate to reconstruct what these climate models said about the 20th century temperature record of the continental US. The IPCC's GCM climate models got it very wrong. They also used the GCM retrodiction to reconstruct the 20th century temperature and precipitation records at 58 locations around the world. The reconstructions failed badly on comparison with the real data. This raises a fundamental question. Since the experiment proved that the IPCC climate models cannot reproduce the known climate, why should anyone believe they can reliably predict an unknown climate.
A random walk is a mathematical formalisation of a trajectory that consists of taking successive random steps.
A 2011 study using the random walk concept gave a confirmation why AGW based climate models are unsuitable for providing inputs for policy making. Published in the Journal of Forecasting the study took the same data set and compared model predictions against a “random walk” alternative, consisting simply of using the last period’s value in each location as the forecast for the next period’s value in that location. The test measures the sum of errors relative to the random walk. The climate models got scores ranging from 2.4 to 3.7, indicating a total failure to provide valid forecast information at the regional level, even on long time scales. The authors commented:
“This implies that the current [climate] models are ill-suited to localized decadal predictions, even though they are used as inputs for policy making.”……”
Dr Andy Edmonds in an incisive article entitled “The Chaos theoretic argument that undermines Climate Change modelling” in the blog WUWT observed:
“So, what does it mean to say that a system can behave seemingly randomly? Surely if a system starts to behave randomly the laws of cause and effect are broken?

Chaotic systems are not entirely unpredictable, as something truly random would be. They exhibit diminishing predictability as they move forward in time, and this diminishment is caused by greater and greater computational requirements to calculate the next set of predictions....prediction accuracy will drop off rapidly the further you try to predict into the future. Chaos doesn’t murder cause and effect; it just wounds it!

Edward Lorenz estimated that the global weather exhibited a Lyapunov exponent equivalent to one bit of information every 4 days. This is an average over time and the world’s surface. There are times and places where weather is much more chaotic, as anyone who lives in England can testify. What this means though, is that if you can predict tomorrows weather with an accuracy of 1 degree C, then your best prediction of the weather on average 5 days hence will be +/- 2 degrees, 9 days hence +/-4 degrees and 13 days hence +/- 8 degrees, so to all intents and purposes after 9-10 days your predictions will be useless. Of course, if you can predict tomorrow’s weather to +/- 0.1 degree, then the growth in errors is slowed, but since they grow exponentially, it won’t be many days till they become useless again.

Interestingly the performance of weather predictions made by organisations like the UK Met office drop off in exactly this fashion. This is proof of a positive Lyapunov exponent, and thus of the existence of chaos in weather, if any were still needed.

So that’s weather prediction, how about long term modelling?”  
In 2005, NASA boss James Hansen stated in an article in the journal ‘Science’ that confirmation of the planetary energy imbalance can be obtained by measuring the heat content of the oceans which are the principal reservoir for excess energy.

A problem for the AGW hypothesis now is that the oceans have been cooling as measurements from thousands of Argo sensors floating on the sea indicate.  So the lame explanation that:
“Overall, the missing heat doesn't change expectations for future climate change, because the heat won't stay missing forever. Eventually it will resurface and impact the climate system, and the recent and deceptive reprieve from rapid warming we've enjoyed will come to an expected end.”
Indeed there is no known mechanism to account for what some describe as vast amounts of missing heat, suggesting that contrary to the AGW hypothesis, heat is not accumulating in the climate system and there is no longer any radiative imbalance from all the carbon dioxide and other greenhouse gases.

NATURAL VARIABILITY MODELS



Phil Jones, Director of the CRU, UK when asked the justification behind attributing global temperatures to human influence during a BBC interview replied:
 “The fact that we can't explain the warming from the 1950s by solar and volcanic forcing” 
So the theory of AGW linked human influence on climate though they didn’t have any actual physical evidence to support this hypothesis. They arrived at this conclusion deductively, through the principle of exclusion. Darwin, on the basis of his own personal experience rejected the principle of exclusion; at least as a primary scientific tool. However, alarmist climate science has not. Instead, the principle of exclusion is one of the most-cited arguments to support the AGW hypothesis. Like Jones, the IPCC’s 2007 report notes:  
“Most of the observed increase in globally averaged temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations.”
The IPCC accordingly offers no empirical proof that human carbon emissions are the main cause of planetary warming; the “proof” is that the scientists can’t find another explanation, i.e., the principle of exclusion.

So climate models were accordingly designed to over-estimate the contribution of CO2 as the driver of climate and either excluded or under-estimated the contribution of natural variability. Till 1998, when the planet was warming, these models appeared infallible as temperature rises found good correlation fit with their model projections. This followed the principle that whenever an explanatory variable is omitted from a statistical analysis, its explanatory power gets wrongly attributed to any correlated variables that are included.

But after 1998, when temperatures began to trend flat and later started to marginally decline, AGW based climate models began to look increasingly fallible. It became obvious that the simplest and most logical explanation for climate change, in the past, now, and in the future, is natural variation so much so the latest the latest SREX IPCC AR5  itself were forced acknowledged its significance:
“...climate change signals are expected to be relatively small compared to natural climate variability".
So what are those phenomena which constitute natural variability? There is a whole array of factors of natural variability. Dr Roy Spencer of NASA-University of Alabama in Huntsville who produces the UAH Global Temperature dataset took into consideration three of them - Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO) which have similar time scales to warming and cooling periods during the 20th Century together with the Southern Oscillation Index (SOI), a measure of ENSO activity.

What Spencer did was to come up with a model of temperature variability, and then see if that statistical model can “predict” the strong warming over the most recent 50 year period. The falsifiability criterion for the hypothesis was if the relationship between temperature and these 3 climate indices for the first half of the 20th Century was just coincidental, it will fail to predict the temperatures for the latter 50 years of the last century. He used the concept of temperature change rate, instead of temperature. This is because if natural climate cycles are correlated to the time rate of change of temperature, that meant they represented heating or cooling influences, such as changes in global cloud cover (albedo).

He then chose to use the (Had)CRUTem3 yearly record of Northern Hemispheric temperature variations for the period 1900 through 2009 to compute the yearly change rates in temperature. He then linearly regressed these 1-year temperature change rates against the yearly average values of the PDO, AMO, and SOI. The period from 1900 through 1960 was used for “training”to derive this statistical relationship, and then applied it to the period 1961 through 2009 to see how well it predicted the yearly temperature change rates for that 50 year period. Then, to get the model-predicted temperatures, he simply added up the temperature change rates over time.

The result of this exercise in shown in the plot above that amazingly found a tight correlation fit between  the rate of observed warming of the Northern Hemisphere since the 1970’s and the PDO, AMO, and SOI together predict, based upon those natural cycles’ previous relationships to the temperature change rate (prior to 1960).
It is to be noted that this model cannot predict future global temperature but can only confirm the correlation between natural variable indices and global temperatures observed. This is because it doesn’t have the ability to be extended into the future, as the future PDO, SOI, and AMO haven’t yet been observed.

 PACIFIC DECADAL OSCILLATION (PDO)


 

The Pacific Decadal Oscillation (PDO) is the predominant source of inter-decadal climate variability in the Pacific Northwest (PNW). The PDO (like ENSO) is characterized by changes in sea surface temperature, sea level pressure, and wind patterns. The PDO is described as being in one of two phases: a warm phase and a cool phase. The PDO shifts its modes alternately once every 25-30 years bringing about climatic flips within the same time intervals and as seen below:

    1.     1890 to 1925  Cold
    2.     1925 to 1946  Warm
    3.     1945 to 1977  Cold
    4.     1977 to 2007  Warm
    5.     2007 to 2030  Cool??

Global average temperatures since 1890 accordingly appear to follow a predictable path  cold-warm alternate cycles that finds a correlation fit with the PDO cycle.

 CLICK IMAGE TO ENLARGE

These cold-warm alternating cycles are well documented by the media coverage of climate during these epochs.  The media have warned about impending climate “doom” four different times in the last 100 years.

Many publications now claiming the world is on the brink of a global warming disaster said the same about an impending ice age – just 30 years ago. Several major ones, including The New York Times, Time magazine and Newsweek, have reported on three or even four different climate shifts since 1895.

From 1945 t0 1977, the PDO switched to its cold mode that brought a mild cooling globally. And just as climate hysteria was warning of an impending ice age, the PDO switched to its warm mode in 1977 that brought about the most recent warming episode. Since 1998, the PDO however had been switching erratically between warm and cold to warm modes until 2007, when it slipped into its cold mode decisively.  A month before the Copenhagen Climate Summit in 2010, Mojib Latif a well known warmist scientist from the Max Plank Institute in Germany, publicly admitted that global warming would be taking a vacation for the next 20-30 years. Though Latif attracted alot of flak from climate alarmists for this admission, he was apparently basing his assessment from the PDO switching to is negative mode.

Though AGW is not able to explain the lack of warming during the last decade and still searching for the “missing heat”, the PDO switching to its cold mode is able to perfectly explain it.  Now that the PDO has shifted to its negative mode, any adaptation strategy for agriculture should be for global cooling that can be expected to last for the next 20-30 years.
 
As seen from the above graphs, El Niños tend to be more frequent and demonstrate higher intensity during the warm phase of a PDO while La Niñas tend to be more frequent and demonstrate higher intensity during the cool phase of a PDO.  
With reference to India, El Niños usually bring deficient rainfall as seen during the 2009-10 monsoon season while La Niñas bring above average rainfalls as seen during the 2010-11 and 2011-12 monsoon seasons. Consequently, being a monsoon dependent economy, agriculture growth rate spikes during La Niña years while plunges during an El Niño year, though irrigation expansion over the years have cushioned its adverse effects significantly in recent times.

SUNSPOTS


As the graph illustrates, solar irradiance (brightness) has been increasing since the Little Ice Age (LIA) that seem to suggest a high correlation fit with global temperature rise. After 1700 A.D., the number of observed sunspots increased sharply from nearly zero to more than 50 and the global climate warmed. Between 1930 and 2000, the Sun was more active than at almost any time in the last 10,000 years. 

 It wasn't until 1980, with the aid of NASA satellites, that scientists definitively proved that the sun's brightness - or radiance - varies in intensity, and that these variations occur in predictable cyclical patterns.

This was a crucial discovery because the climate models used by AGW proponents always assumed that the sun's radiance was constant. With that assumption in hand, they could ignore solar influences and focus on other influences, including human.

That turned out to be a reckless assumption. Further investigation revealed that there is a strong correlation between the variations in solar irradiance and fluctuations in the Earth's temperature. When the sun gets dimmer, the Earth gets cooler; when the sun gets brighter, the Earth gets hotter. So important is the sun in climate change that half of the 0.6° C temperature increase since 1850 is directly attributable to changes in the sun. According to NASA scientists David Lind and Judith Lean, only one-quarter of a degree can be ascribed to other causes, such as greenhouse gases, through which human activities can theoretically exert some influence.
As NASA notes: 
“Early records of sunspots indicate that the Sun went through a period of inactivity in the late 17th century. Very few sunspots were seen on the Sun from about 1645 to 1715. Although the observations were not as extensive as in later years, the Sun was in fact well observed during this time and this lack of sunspots is well documented.
This period of solar inactivity also corresponds to a climatic period called the "Little Ice Age" when rivers that are normally ice-free froze and snow fields remained year-round at lower altitudes. There is evidence that the Sun has had similar periods of inactivity in the more distant past.”
As Professor Easterbrook further observed: 

 


 “The global cooling that occurred during the Maunder Minimum was neither the first nor the only such event. The Maunder was preceded by the Sporer Minimum (~1410–1540 A.D.) and the Wolf Minimum (~1290–1320 A.D.) and succeeded by the Dalton Minimum (1790–1830), the unnamed 1880–1915 minima, and the unnamed 1945–1977 Minima (Fig.). Each of these periods is characterized by low numbers of sunspots, cooler global climates, and changes in the rate of production of C14 and Be10 in the upper atmosphere. As shown in Fig. each minimum was a time of global cooling, recorded in the advance of alpine glaciers... 
What can we learn from this historic data? Clearly, a strong correlation exists between solar variation and temperature. Although this correlation is too robust to be merely coincidental, exactly how solar variations are translated into climatic changes on Earth is not clear. For many years, solar scientists considered variation in solar irradiance to be too small to cause significant climate changes.

However, Svensmark (Svensmark and Calder, 2007; Svensmark and Friis-Christensen, 1997; Svensmark et al., 2007) has proposed a new concept of how the sun may impact Earth’s climate. Svensmark recognized the importance of cloud generation as a result of ionization in the atmosphere caused by cosmic rays. Clouds reflect incoming sunlight and tend to cool the Earth. The amount of cosmic radiation is greatly affected by the sun’s magnetic field, so during times of weak solar magnetic field, more cosmic radiation reaches the Earth. Thus, perhaps variation in the intensity of the solar magnetic field may play an important role in climate change.” 
But confirmation of Svensmark’s theory last year came from CERN, the European Organization for Nuclear Research, and the world's leading laboratory for particle physics. Last year CERN published a paper in Nature, the most cited science journal entitled Role of sulphuric acid, ammonia and galactic cosmic rays in atmospheric aerosol nucleation.

The findings of this paper have significant implications for climate science because water vapour and clouds play a large role in determining global temperatures. Tiny changes in overall cloud cover can result in relatively large temperature changes - supporting a "heliocentric" rather than "anthropogenic" approach to climate change since the sun plays a large role in modulating the quantity of cosmic rays reaching the upper atmosphere of the Earth.

Jasper Kirkby of CERN observed in a press release:
"We’ve found that cosmic rays significantly enhance the formation of aerosol particles in the mid troposphere and above. These aerosols can eventually grow into the seeds for clouds...”
Former ISRO physicist chairman who is also one of India’s well respected scientists, Dr.  U.R. Rao similarly proved cosmic rays having a much larger impact on global warming than IPCC claims. Dr Rao in fact argues that the contribution of decreasing cosmic ray activity to global warming is almost 40% in a paper published in Current Science, the preeminent Indian science journal. The IPCC model, on the other hand, says that the contribution of carbon emissions is over 90 per cent.  The continuing increase in solar activity has caused a 9 per cent decrease in cosmic ray intensity over the last 150 years, which results in less cloud cover, which in turn results in less albedo i.e. radiation being reflected back to the space, causing an increase in the Earth's surface temperature.

In a paper published in the journal - Applied Physics Research, astrophysicist Dr Habibullo Abdussamatov of Russia’s Pulkovo Observatory predicted a Little Ice Age (LIA) by 2042 ±11 by looking at Total Solar Irradiance (TSI). 

The current prediction for Sunspot Cycle 24 gives a smoothed sunspot number maximum of about 60 in the Spring of 2013. We are currently over three years into Cycle 24. The current predicted size makes this the smallest sunspot cycle in about 100 years. We are now at what should be the peak (maxima) of ‘Cycle 24’ but sunspot numbers are running at less than half those seen during cycle peaks in the 20th Century. Analysis by experts at NASA and the University of Arizona suggest that Cycle 25, whose peak is due in 2022, will be a great deal weaker still. 

The polar fields should have flipped at the end of cycle C23, around 2008-09, but they continued with the same polarity, showing a stretched pattern similar to what happened at the end of the 1960′s but more pronounced, which could lead to “break” of the field into a “quadripolar” mode very soon. This is another indication of the very low intensity of the present cycle. This low intensity could lead to a period of no sunspots as observed during the Maunder minimum between the period 1640 to 1710

There is growing evidence that a Grand Minimum similar to the either the Dalton or Maunder is in our future, see references herehere, here, here and here.


5. What is in store for us the next 25-30 years in terms of climate change? Which strategic direction should Agriculture Adapt?

Synopsis:  There could be four plausible climate scenarios for the next two decades viz.  the status quo continues ; climate reverts back to accelerated warming trend; climate of mild cooling and climate flipping back to Little Ice Age (LIA) conditions.

However, the ICRIER-GC paper’s “adaptation strategies” are ostensibly geared to only one of these scenarios - climate flipping back to accelerated warming trends. But this scenario is highly unlikely. Even the IPCC in their latest report rules out such a scenario for the next two decades!  

 
Considering the climate is a chaotic and non-linear system, it is not possible to anticipate future climate behaviour with absolute certainty.  Nevertheless, there could be four plausible scenarios of the climate for the next two decades as discussed below:

SCENARIO 1: STABLE CLIMATE OF LAST DECADE TO CONTINUE



The first scenario assumes the last decade’s stable climate with global warming hiatus, if not with temperatures trending slightly decline will continue till 2030.

Accordingly, the “adaptation strategies” for agriculture, recommended by the ICRIER-GC paper are irrelevant as it bases itself on the AGW paradigm.

SCENARIO 2: ACCELERATED GLOBAL WARMING

 
 
This scenario assumes this stable state of climate of the last decade will flip once again to resume the accelerated global warming trend observed during the 1976-1998 period. 

The probability of this scenario is considered very unlikely as even the latest SREX IPCC Report AR5 ruled it out:

“...climate change signals are expected to be relatively small compared to natural climate variability".
Global temperatures are currently demonstrating a marginal decline. But even so, if the climate were to reverse back to its accelerated warming path, there would still no hurry to put to work the adaptation strategies for agriculture as recommended by the ICRIER-GC paper. To borrow an analogy from the equity market, the strategy would be await a confirmation of bottoming up and evidence of a decisive buy signal. Accordingly, as and when temperature trends reverses decisively, the recommendations of the ICRIER-GC paper for agriculture climate adaptation can then be re-visited to take a call on their relevance.

It is to be appreciated that agriculture had been performing well during the last global warming cycle 1976-98. Such an outcome cannot be assumed possible without any adaptation by agriculture to a warming climate. So even if the climate’s random walk results to the return of an accelerated warming scenario, the adaptation by agriculture to the last global warming cycle should provide a cushion in terms of its climate vulnerability if any.


SCENARIO 3:  GLOBAL COOLING


 
The third scenario is one where the climate enters into a mild global cooling cycle brought about by the shift of the Pacific Decadal Oscillation (PDO) to its cold mode.  This scenario is consistent with  SREX IPCC Report AR5  who conceded:
 “...climate change signals are expected to be relatively small compared to natural climate variability".
The implication of this scenario is a return to the mildly cold temperatures seen during the period 1945-77 or to a relatively stronger cold period as experienced during 1890 to 1925. As the PDO shifted to its cold mode as far back as 2007, we could see the prospect of accelerated cooling kicking in as early as 2014 after the completion of the solar maxima expected by next May.  But it would be during the next solar cycle 25, expected to start around 2018-19 where the cooling is expected to really come into full play.

If the past is any indication of the future, India has every reason to rejoice. With above average monsoons to accompany this global cooling cycle expected to last till 2030, here too the adaptation strategies for agriculture as recommended by the ICRIER-GC paper become irrelevant as it bases itself on the AGW paradigm. 

Not only agriculture could be expected to boom during the next two decades, but India could eye to be one of the biggest exporters of agriculture commodities, capitalizing on the likely decline of agriculture production in temperate latitudes encompassing the bread basket of the world - countries such as US, Canada, Europe and Russia.  The latter will be brought about by not only falling temperatures but shortening of the growing season.

Continuation of various agriculture subsidies or even enhancing them within this scenario, though creating fiscal problems during the near term, could nevertheless yield India very large paybacks through agricultural exports over the medium to long timelines.

SCENARIO 4:  RETURN TO THE LITTLE ICE AGE
 


If forecasts of LIA were to be realized, then we should be looking at a global cooling climate for all through the next 100 years, the very least.  If the past is an indicator of the future, then it would be only agriculture within the equatorial latitudes that would be somewhat be insulated, from LIA’s detrimental impact on agriculture.
Though initially a LIA may be beneficial for India, as evaporation rates decreases significantly, it can be expected to in turn lead to decrease rainfall and mega droughts.  In the past, LIA has been found to often establish itself in a matter of a couple of decades. Radical adaptation by agriculture would then be required to mitigate LIA impact. But even here, since the ICRIER-GC paper bases itself on the AGW paradigm, it rules itself out as an appropriate strategy.

Unlike other natural variability factors such as PDO, AMO etc, solar effects on climate however remain a contentious theory. Even among climate sceptics, a section is not totally convinced about the solar effects on climate. Additionally, nearly all forecasts of an impending LIA are around the year 2050. This is almost 4 decades away, which provides a time buffer to evolve suitable adaptation measures, if needed. And hence there is no hurry to implement currently any radical policy initiatives. A wait and watch policy is more prudent. Depending upon how Solar Cycle 25 (expected to start around 2018-19) pans out, a more realistic understanding of probabilities of an impending LIA could be gained and based on this, suitable adaptation strategies for agriculture could be drawn up.

CONCLUSIONS


People were racing to Y2K their computers and systems. TV news crews had reporters stationed at bank machines, at train traffic centers in NYC, at airports, all waiting to see if the machines and the computers that run them, stopped working when the clock went from 1999 23:59:59 to 2000 00:00:00 because in the early days of programming, to save memory, they used two digit years instead of four, and the fear was that computers would reset themselves to the year 1900 rather than 2000, and stop functioning.”

These are extracts from the UK Independent’s article entitled “Is catastrophic global warming, like the Millennium Bug, a mistake?”  And you can’t blame them. Climate hysteria is littered with a long list of failed “predictions”, the lack of warming seen during the last decade being only one of them. 

For example, in 2005, the United Nations Environment Programme predicted that climate change would create 50 million climate refugees by 2010. These people, it was said, would flee a range of disasters including sea level rise, increases in the numbers and severity of hurricanes, and disruption to food production.The UNEP even provided a handy map. The map showed the places most at risk including the very climate sensitive low lying islands of the Pacific and Caribbean. Two years after this deadline had passed, in each and every location, there was no such evidence come across of such a horrendous calamity having struck with their population even registering a healthy increase!

Believing the climate is predictable as the ICRIER-GC paper does, when it is not, does not make it so. With climate being a chaotic and non-linear system, there is no model or expert that is currently able to forecast future changes with absolute certainty. The IPCC tried and failed miserably.  Leave alone the climate, the uncertainties of weather makes accuracy of advance prediction more than 5 days a challenge which progressively increase as additional days are added. With more than 100 years of experience, the IMD’s success rate of predicting the monsoons remain just one of five.

The reality remains that it is still a matter of conjecture which direction the climate will flip or how long the global climate’s current stable state will continue. Policies cannot be formulated based on mere conjectures and blanket exclusions (in this case, global cooling’s exclusion), particularly in context to a phenomenon like climate which demonstrates a high level of unpredictability in its behavioral traits.

Climate Smart Agriculture therefore should be equated to being prepared for whatever direction the random walks the climate might take. This is what the ICRIER-GC paper basically fails to appreciate. If one works out “solutions” assuming an accelerated global warming future scenario and what we actually get instead is accelerated cooling or vice versa, rather than enhancing agriculture’s adaptability to climate changes it ends up increasing its vulnerability to climate changes!

NGOs are certainly legitimate part of democratic governance, possessing the right to influence policy. But this brings us to the question that if we do not commission an auto mechanic to undertake an open heart surgery, why is it when it comes to climate change, any Tom Dick or Harry in the NGO sector is allowed to lay claim to an expertise good enough to write “policy papers” on the subject when they have not much to talk of?

This doesn’t mean that they need any formal academic credentials in climatology. All it means is that they need to have sufficient theoretical grasp of a complex subject like climate change to be confident enough to publicly debate science with those who do have the academic training in climatology. This is where the legitimacy of NGO advocacy campaigns faces immense criticism. They write many fancy papers but always shy away to openly debate the science of climate change with qualified climatologists.

Within this context, attempts by NGOs like Gene Campaign and their researchers demonstrating an audacity to write a policy paper on how agriculture should adapt to future climate changes appear an exercise in tragic comedy. A comedy because of pretensions to an expertise where they had none and a tragedy because it undermines the credibility of their advocacy campaigns in areas where they do have the expertise.

Our recommendation to ICRIER is to withdraw the paper as an official ICRIER policy paper as it fails to meet the basic standards of research!

No comments:

Post a Comment