By Arpita Mondal
Attribution analyses not only help in better understanding of the processes leading up to an extreme event and how such processes have changed or will change in future, attribution information can also potentially remove resistance to climate policy inaction.
In the aftermath of the heavy rainfall and devastating flooding event in Kerala, in August this year, it is natural for the press, public, practitioners and policy-makers to ask whether the event was caused by climate change and global warming. The science of probabilistic event attribution, a tool often adopted to answer such questions, developed only recently, following a seminal work published by scientists in the U.K. Met Office and Oxford University in 2004, concluding that human activities have very likely doubled the risk of the European heat wave of 2003.
Among the host of research studies that have since been published on probabilistic extreme event attribution, the most notable is the annual special issue in the Bulletin of the American Meteorological Society (BAMS) that discusses worldwide events from the previous year. Attribution analyses not only help in better understanding of the processes leading up to an extreme event and how such processes have changed or will change in future, attribution information can also potentially remove resistance to climate policy inaction.
The basic idea behind such an attribution analysis is drawn from epidemiology, where it can be never concluded with certainty, whether a particular person’s lung cancer is caused by smoking; however, there are enough reasons to believe that smoking increases the chance of a person having cancer. Think of it this way – you are rolling a loaded dice and a ‘six’ is the outcome. You could never say with certainty whether six would have never come up, had the dice not been loaded. However, you have enough reasons to also believe that since the dice was loaded (and wasn’t really a ‘fair’ dice), it was inherently more likely that you get a six as an outcome. Similarly, a world under global warming may be loaded towards more extreme events such as heat waves, floods, droughts and wildfires because of the warmer state in which it already exists.
Let us look at some possible physical outcomes of global warming that can translate to a higher risk of extreme weather events, as detailed by the IPCC’s Special Report on Extremes published in 2012: i) Higher average temperatures can lead to a shift in the distribution of temperatures, making heat waves or temperature extremes more ‘normal’ than they used to be. ii) A warmer atmosphere can hold more moisture, resulting in an intensified water cycle, making heavy rainfall and flooding more common, even though average rainfall might not change significantly. iii) On the other hand, higher evaporation and transpiration in a warmer world can use up available water, eventually leading to droughts.
While there is greater confidence in attributing changes in temperature to human-induced warming, the inherent variability in precipitation or rainfall across space and time is so large that the effects of warming can vary greatly in different parts of the world.
In very simple terms, an event attribution analysis compares the probabilities of occurrence of a particular event, such as a heat wave, or a flood or a drought, in a world under global warming – the factual world, vis-à-vis a world that could have been, had there been no anthropogenic emissions – the counterfactual world. Such probabilities are often simulated from computer-based models of the earth’s climate system, called the General Circulation Models or Global Climate Models (GCMs).
These models are limited by their coarse resolution and inadequate representation of processes. For example, none of these models have been found to be performing very well when it comes to simulating features such as trends in the Indian monsoon. For extreme rainfall over India, anthropogenic signals are found to be hard to detect. Further, one aspect of the climate system that is relatively poorly understood is how tiny pollutants called aerosols influence the energy budget of the earth locally and how they can influence the climate/weather systems. In most world regions, aerosols, primarily sulfates, are known to cause an overall cooling. However, the biomass-burning anthropogenic black carbons that are abundant in India, behave differently and can, in fact, contribute to warming.
Therefore, any outcome of an event attribution analysis will be as good as the models or our understanding of the physical or biogeochemical processes represented by them. Further, when it comes to hydrological events such as flooding or drought, it is not just rainfall or temperature that is important; discharge, depth and velocity of flow in channels or over land, reservoirs and dams and local water management practices are equally important. For example, preliminary observation-based analysis show that the 2015 Marathwada drought is likely a result of poor management of water resources and in the 2018 Kerala flood, exceptionally large reservoir storages played an important role.
The free availability of good quality and quantity of observed hydrological data may be limited in India, particularly for basins dealing with inter-governmental riparian conflicts, adding on to the challenge. Finally, undocumented factors such an encroachment of flood plains, unregulated urbanisation, unpermitted settlements or cultivation, unaccounted water withdrawals, etc. make attribution even harder for hydrological events in India.
The science of event attribution is still in a very nascent stage in India. While the heat waves of 2015 and 2016 have been attributed to anthropogenic climate change with some confidence, particularly when considering a combination of temperature and humidity, conclusions of attribution of heavy rainfall events are never unequivocal. Even for the heat waves in India, confounding roles of irrigation and aerosol-related cooling are reportedly noteworthy.
Attribution analysis of the heavy rainfall in Chennai in December 2015 does not reveal enough evidence to say with certainty that greenhouse gas-related warming played a significant role. Rather, aerosols would have likely counteracted such warming. It is also worth noting that the climate models are configured differently and they do not tell a consistent story always. For example, though this study on the heavy rainfall in Uttarakhand and North India in June 2013 reports increased chances of such events in a warmer world, it also shows that the different climate models lead to different conclusions on attribution.
For a densely populated, rapidly developing and highly vulnerable region such as India, the science of event attribution must be encouraged, and it must integrate climate studies, hydrology, social sciences and related disciplines. Challenges are far too many, in understanding how climate change, climate variability, air pollution, engineered regulations and interventions and socio-economic vulnerabilities together influence the cause and impact of an extreme event. Scientific progress in addressing such challenges must continue undeterred, irrespective of whether attribution conclusions shape climate policy in the near future. For, whether the evidence of attribution is discernible or not, the magnitude, intensity and frequency or extreme events may be changing already, rendering adaptation, mitigation and preparedness unavoidable.
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