Forest cover resilience to climate change over India using the MC2 dynamic vegetation model.

It is imperative to understand the climate change impact on the forest ecosystem to develop appropriate mitigation and management strategies. We have employed a process-based dynamic vegetation modeling (MAPSS-CENTURY: MC) approach to project change in vegetation life forms under projected climate conditions that attained 81% overall accuracy. The present and projected climate conditions suggested highly resilient/stable forest covers in wet climate regimes and moderately resilient in dry semi-arid regions. Several forested grids in the seasonally dry tropical forest in the Eastern Ghats and dry Deccan peninsula regions are estimated to be less resilient, which may experience a regime shift toward scrub and grassland. The future prediction demonstrated an upward temperature shift in the Western Himalayas and trans-Himalaya, which may facilitate forest spread at higher elevations. Although the forest cover resilience may increase in future climate conditions, the disturbances in several regions in the Deccan Peninsula and the Eastern Ghats may trigger forest to scrub and grassland transition. The inaccuracy in model simulation in the Western Himalayas could be attributed to coarse resolution grids (0.5°) failing to resolve the narrow climate niches. The spatially explicit model simulation provides opportunities to develop long-term climate change adaptation and conservation strategies.

Evaluation and bias correction of global climate models in the CMIP5 over the Indian Ocean region.

Global climate model (GCM) simulations driven by various emission scenarios are widely used for the projections of future climate change. In this study, an assessment was carried out by using 35 GCMs under Coupled Model Intercomparison Project (CMIP5) in reproducing the present day wind speed changes over six selected regions in the Indian Ocean region based on altimetry-measured merged wind speed product in the Indian Ocean. The relative ranking of the GCMs is performed based on the evaluation of the CMIP5 historical simulations for the period 1993-2005. The skill level of GCMs in representing the various metrics such as annual mean, mean seasonal cycle, linear trend, correlation coefficient, and seasonal standard deviations was accounted for the relative ranking of the GCMs. The models CMCC-CESM, HadGEM2-ES, and GFDL-ESM2G are found to be better for the Arabian Sea region. The GCM products such as HadCM3, CSIRO-Mk3.6.0, HadGEM2-CC, HadGEM2-AO, and MIROC5 were noticed better for the Bay of Bengal (BoB) region. Large bias in wind speed (~ 3 m/s) is observed for the head BoB and the Southern Ocean region. Bias corrections for the present-day Representative Concentration Pathway (RCP) simulations (2006-2016) were performed based on quantile mapping (QM) method, and the present-day wind changes are also compared with observations. The findings from study recommend that suitable bias correction for different GCMs is an essential pre-requisite for climate change studies.

Potential generation sites of internal solitary waves and their propagation characteristics in the Andaman Sea-a study based on MODIS true-colour and SAR observations.

The presence of large-amplitude Internal Solitary Waves (ISWs or solitons) is quite common in the Andaman Sea, located in the north-eastern Indian Ocean basin. ISWs are known to induce strong vertical velocities which can play an essential role in the mixing transport of nutrients and are proven hazardous to offshore oil platforms. The surface signatures of ISWs can be detected using remote sensing instruments like Synthetic Aperture Radar (SAR) and sunglint true-colour images. The present study makes an effort to delineate as well as detect the possible potential generation locations of mode-1 long living ISWs in the Andaman Sea using remote sensing observations. To accomplish this, the Moderate Resolution Imaging Spectroradiometer (MODIS) true-colour images of Terra/Aqua satellites for the months of March and April during 2014-2016 are used to map the distribution and propagation characteristics of ISWs. These maps along with SAR imgaes from ENVISAT and TerraSAR-X are used to detect the possible generation locations of ISWs. The study considers the possible generation location of ISW as the circumcentre of each wave packet as they radially propagate along a two-dimensional frame. The analysis reveals five potential ISW generation hotspots that are distributed along the Northern Andaman Sea, as well as locations in the discontinuities off the Nicobar Islands and the great passage. The ISWs that form over these regions are hitting the continental shelf within the Andaman Sea. Interestingly, the waves from two potential generation sites between the Nicobar Islands appear to radiate waves in two opposite directions, towards the Andaman Sea and the southern Bay of Bengal.

CMIP5 wind speed comparison between satellite altimeter and reanalysis products for the Bay of Bengal.

A proper evaluation and performance assessment of climate model projections have received considerable attention during the recent past amongst the scientific community. Quality of wind datasets used for analysis is of paramount importance to meteorologists, oceanographers, and climatologist as an essential pre-requisite for modelling needs. This study examined the measured wind speeds obtained from satellite altimetry available from IFREMER/CERSAT, along with two atmospheric reanalysis products ECMWF ERA-Interim and NCEP-CFSR. The reanalysis products and altimeter data were compared with wind speed simulated from 33 different models under WCRP-CMIP5 project for the Bay of Bengal (BoB) region. Study investigated both historical and projections of CMIP5 data providing an opportunity to inter-compare the wind speeds resulting from various emission scenarios with Representative Concentration Pathways (RCPs) 2.6, 4.5, 6.0, and 8.5, respectively. The objective is to establish and find out a suitable emission scenario applicable to the BoB region. Temporal and spatial analyses of CMIP5 data infer variability in terms of correlation, bias, and root mean square error. For the historical runs (1991-2005) based on analysis of 29 CMIP5 models, it could be ascertained that the correlation coefficient in wind speed varied between 0.6 and 0.9 and with a bias ranging from - 1.6 to 4 ms-1. Similar analysis of the CMIP5 projections was carried out with 11 models for RCP 2.6, 29 models for RCP 4.5, 10 models for RCP 6.0, and 28 models for RCP 8.5. Basin-scale mean using altimeter and re-analysis products indicates that RCPs 2.6 and 6.0 showed less correlation with a higher bias for the study region. Analysis of historical model runs signifies that HadGEM2-ES, HadGEM2-AO, HadGEM2-CC, MIROC5, GISS-E2R, and CNRM-CM5 are the best performing models for the study domain. Findings from the study indicate that RCP 4.5 wind speed stands better for the Bay of Bengal region. In a broader perspective, due to various uncertainties involved in climate model outputs, it is imperative to perform a comprehensive analysis amongst multiple data sources to establish and identify the best quality data for scientific needs.

Multi-hazard risk assessment of coastal vulnerability from tropical cyclones - A GIS based approach for the Odisha coast.

The coastal region bordering the East coast of India is a thickly populated belt exposed to high risk and vulnerability from natural hazards such as tropical cyclones. Tropical cyclone frequencies that develop over the Bay of Bengal (average of 5-6 per year) region are much higher as compared to the Arabian Sea thereby posing a high risk factor associated with storm surge, inland inundation, wind gust, intense rainfall, etc. The Odisha State in the East coast of India experiences the highest number of cyclone strikes as compared to West Bengal, Andhra Pradesh, and Tamil Nadu. To express the destructive potential resulting from tropical cyclones the Power Dissipation Index (PDI) is a widely used metric globally. A recent study indicates that PDI for cyclones in the present decade have increased about six times as compared to the past. Hence there is a need to precisely ascertain the coastal vulnerability and risk factors associated with high intense cyclones expected in a changing climate. As such there are no comprehensive studies attempted so far on the determination of Coastal Vulnerability Index (CVI) for Odisha coast that is highly prone to cyclone strikes. With this motivation, the present study makes an attempt to investigate the physical, environmental, social, and economic impacts on coastal vulnerability associated with tropical cyclones for the Odisha coast. The study also investigates the futuristic projection of coastal vulnerability over this region expected in a changing climate scenario. Eight fair weather parameters along with storm surge height and onshore inundation were used to estimate the Physical Vulnerability Index (PVI). Thereafter, the PVI along with social, economic, and environmental vulnerability was used to determine the overall CVI using the GIS based approach. The authors believe that the comprehensive nature of this study is expected to benefit coastal zone management authorities.