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Climate Data and Future Scenarios for the Cauvery Delta Zone

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Climate Data and Future Scenarios for the Cauvery Delta Zone Technical Assistance Consultant’s Report Project Number: TA 8166 December 2013 India: Climate Adaptation through Sub-Basin Development Investment Program Cauvery Delta Zone: Climate Data and Future Scenarios —Final Report This consultant’s report does not necessarily reflect the views of ADB or the Government concerned, and ADB and the Government cannot be held liable for its contents. All the views expressed herein may not be incorporated into the proposed project’s design. IND (44429): Climate Adaptation through Sub-Basin Development Investment Program Cauvery Delta Tamil Nadu, India Final Report Cauvery Delta Zone: Climate Data and Future Scenarios 1 Table of Contents 1. INTRODUCTION 8 1.1. PROJECT BACKGROUND 8 1.2. GEOGRAPHICAL CONTEXT 8 1.3. CLIMATOLOGY 8 1.4. REVIEW OF EARLIER STUDIES 9 1.5. ORGANIZATION OF THIS REPORT 11 2. APPROACH AND METHODOLOGY 12 2.1. STRATEGY 12 2.2. SPATIAL DOMAIN 12 2.3. HISTORICAL CLIMATE DATA 13 STATION DATA 13 GRIDDED IMD DATA 14 APHRODITE GRIDDED PRECIPITATION DATA 14 2.4. CLIMATE MODELS USED 14 CMIP5 GCMS 14 ASSESSMENT OF MONSOON SIMULATIONS 16 SELECTION OF GCMS 16 REGIONAL CLIMATE MODEL (RCM) 17 2.5. DELIVERED DATA SETS 17 DATA EXTRACTION 18 BIAS CORRECTION 19 2.6. TROPICAL CYCLONES ANALYSIS 19 3. BASELINE CLIMATE AND EVALUATION 20 3.1. OBSERVED CLIMATOLOGY 20 SEASONALITY 20 TRENDS 22 RAINFALL 26 3.2. BASIC STATISTICS 26 3.3. EVALUATION OF GCM AND RCM 31 TEMPERATURE SEASONAL CYCLE 31 RAINFALL SEASONAL CYCLE EVALUATION 33 RAINFALL DAILY CLIMATOLOGY 35 SPATIAL PATTERNS IN SUMMER MAXIMUM TEMPERATURES 37 SPATIAL PATTERNS IN RAINFALL 38 3.4. BIAS CORRECTION 42 4. PROJECTIONS 43 4.1. CLIMATE CHANGE SCENARIO 43 2 S EASONAL CYCLE 43 DAILY RAINFALL PROJECTIONS 47 4.2. BASIC STATISTICS 49 4.4. SPATIAL CHANGES 51 5. DAILY RAINFALL ANALYSIS 55 5.1. RETURN PERIOD ANALYSIS FOR BASELINE 55 5.2. RETURN PERIODS FOR PROJECTED RAINFALL DATA 56 5.3. PROBABILITY OF RAINFALL 57 BASELINE 57 FUTURE PROJECTIONS 58 6. TROPICAL CYCLONES 60 6.1. CURRENT TRENDS AND VARIATIONS 60 6.2. TROPICAL CYCLONES AND POSSIBLE INFLUENCE OF CLIMATE CHANGE 62 7. CONCLUSIONS 64 8. REFERENCES 65 ANNEX I 67 S TATION OBSERVATIONS 67 GRIDDED DATASETS 69 REANALYSIS DATASETS 69 CYCLONIC STORMS TRACKS DATA 69 LIST OF IMD DISTRICT RAINFALL MONIOTRING SCHEME (DRMS) STATIONS 71 SUMMARY OF DATA PROVIDED BY PWD, TAMIL NADU 76 ANNEX II 79 INVENTORY OF DAILY DATA FROM CIMIP5 GCMS 79 ANNEX III 81 D ESCRIPTION OF DATA EXTRACTED FOR CDZ 81 DATA STRUCTURE OF DISTRIBUTED CLIMATE DATASETS 82 DATA SETS PRODUCED FOR CDZ 83 DATASETS FOR STATION LOCATIONS 84 DERIVED DATA 85 FILE STRUCTURE 86 3 LIST OF ACRONYMS ADB Asian Development Bank APHRODITE Asian Precipitation—Highly-Resolved Observational Data Integration Towards Evaluation CDZ Cauvery Delta Zone GCM General Circulation Model (also Global Climate Model) GHGs Green House Gases msl Mean sea level INCCA Indian Network for Climate Change Assessment IPCC Inter -governmental Panel on Climate Change IPRC International Pacific Research Center (IPRC), University of Hawaii IPRC-RegCM IPRC Regional Climate Model IWRM Integrated Water Resources Management LLNL Lawrence Livermore National Laboratory, California, USA RCM Regional Climate Model PCMDI Program for Climate Model Diagnosis and Intercomparison PPTA Project Preparatory Technical Assistance TN Tamil Nadu 4 EXECUTIVE SUMMARY The project was aimed to prepare an assessment of current climate and future climate change over the Cauvery delta of Tamil Nadu, and to provide related data, analysis and interpretations, based on the latest science. This was mainly intended to support hydrologic analysis, particularly to build climate resilience in future designs for drainage improvement, flood control and irrigation structures being planned under the over-arching Climate Adaptation through Sub- basin Development investment Program (CASDP) of the Asian Development Bank (ADB). Impacts of future climate change are expected to be more pronounced in areas that are already vulnerable due higher population densities and exposure to natural hazards. In such contexts, effective use of climate information in planning strategies are of greater relevance now, than ever before. The present project effort brought together a variety of observational data sets, including long- term site-specific climate data to enable better characterization of local climate. Climate change scenarios up to the 2050s have been generated and analyzed from state-of-the-art GCMs and downscaled using a Regional Climate Model (RCM) to higher resolutions appropriate for water sector adaptation strategies. The importance of the Cauvery River and the Cauvery Delta Zone (CDZ) to the culture and livelihoods of the people of Tamil Nadu cannot be overstated. The tropical climate of the Tamil Nadu region is characterized around seasonal rainfall contributed by both South West (SW) and the North East (NE) monsoons influencing the Indian sub-continent. Set within this larger climatological context, the deltaic region of River Cauvery comes mainly under the influence of NE monsoon. Cyclonic disturbances, while providing important additional water resource to the CDZ in their benign forms, can cause substantial damage to life and property when they reach severe intensities. Although the mean annual temperatures over the Cauvery delta area is around 30 C, summer peaks can go up to 43 C with consequences to both water demand and evaporative losses. The task of the climate component of the project involved initial scoping of available data from the point of view of requirements of the water sector groups. An inventory of observed climate data sets for the CDZ was prepared from this initial scoping and some details are included in the this report. Observed climate data for project location available from the meteorological stations of the India Meteorological Department (IMD), data from available Government of Tamil Nadu Public Works Department (PWD), and gridded data sets of both IMD and other global sources were inventoried and assessed. A sub-set of these observed data sets were used to characterize the baseline climatology of the project location. General Circulation Models (GCMs) are the main tools available to project future climate and its change in response to various greenhouse gas emission scenarios. GCMs, projections are however still too coarse (~200 km) for use in sub-basin level climate change assessments. This study has therefore used Regional Climate Model (RCM) - downscaled high-resolution (~30 km) scenarios generated from coarse resolution GCMs projections, in addition to GCMs results. Results available from current genre of CMIP5 GCMs (Coupled Model Inter-comparison Project phase 5) models and dynamically downscaled RCM results forced with CMIP5 and CMIP3 lateral boundary conditions were used for preparing baseline and future climate change scenarios for the study area. 5 Both the GCMs, and the RCMs capture the seasonal evolution in temperatures but with a cold bias in certain cases pertaining to the GCMs and warm bias in case of the CCSM4 driven RCM. Among the model results compared temperature biases are of the order of about 2-3 C for maximum temperatures. Overall the models are able to closely capture temperature variations during the season as well as spatial patterns. The temperature evaluation indicates that there is more confidence in temperature projections, which is probably higher during the drier months of the year. Simulation of rainfall accurately is difficult for climate models, as rainfall is an end product of many inter-linked processes in the earth’s climate system. This gets even more challenging when projections are required over a small area like the CDZ because rainfall’s natural variability increases as we go from larger to smaller domains. However, It is encouraging to note that the GCMs and RCMs used in this assessment pick up the seasonal cycle of rainfall over the CDZ quite well. Significant biases do exist, which in one of the regional model results has been corrected using a bias correction procedure. Model results compared over a daily time scale showed quite a good similarity with respect to observed rainfall. Due to higher variability of rainfall there is lesser confidence in rainfall estimates and projections. Analysis of temperature observations from stations in the CDZ area shows an increasing trend in both maximum and minimum temperatures. The annual mean maximum temperatures are increasing at a rate of about 0.13 to 0.33 C/10 years. Both maximum and minimum temperature trends are most prominent during the cooler months of January and February. Historical observations of rainfall from both gridded and station observations show very little trends with predominance of year-to-year variability. The climate change scenarios for CDZ have been prepared for time horizons up to 2050 keeping in view the planning needs of water sector projects. Particular focus of our analysis was on temperature and rainfall variables as they are the key variables for the hydrological analysis and have also been extensively evaluated with relatively higher reliability as compared to other variables. However, data sets have been provided for other variables like humidity, wind speed, solar radiation, evaporation and mean sea-level pressure. Maximum temperature change over the CDZ projected by the models show a range from about 1.0 to 1.5°C by the 2050s. Minimum temperatures show a larger increase with changes ranging from 2-3°C. Spatially, the temperatures changes show a large variation over the TN region with the range going from 2-6°C for maximum temperatures in the 2050s, with the RCM driven by GFDL showing higher temperature increase. These results are consistent with the earlier climate model projection studies undertaken by other research groups. These rising temperatures will have consequences to the water sector, in terms of higher water demand and enhanced evaporative losses. Higher mean temperatures may also translate into longer spells of heat waves in summers.
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