Future Climate Change Scenario at Hot Semi-arid Climate of Ahmedabad (23.04°N, 72.38°E), India Based on Statistical Downscaling by LARS-WG Model

2016 ◽  
Vol 13 (1) ◽  
pp. 35-42
Author(s):  
Jayanta Sarkar ◽  
J.R. Chicholikar
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Climate Change Scenario ◽  
Future Climate ◽  
Arid Climate ◽  
Future Climate Change ◽  
Change Scenario ◽  
Future Climate Change Scenario ◽  
Semi Arid

CHILDHOOD ASTHMA PROJECTIONS FOR ATLANTA UNDER A FUTURE CLIMATE CHANGE SCENARIO

Epidemiology ◽  
2004 ◽  
Vol 15 (4) ◽  
pp. S97
Author(s):  
Jonathan Patz ◽  
Howard Frumkin ◽  
Michell Klein ◽  
Michelle Bell ◽  
Hugh Ellis ◽  
...  
Keyword(s):  
Climate Change ◽  
Childhood Asthma ◽  
Climate Change Scenario ◽  
Future Climate ◽  
Future Climate Change ◽  
Change Scenario ◽  
Future Climate Change Scenario

scholarly journals Climate change scenario analysis for Baro-Akobo river basin, Southwestern Ethiopia

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Teressa Negassa Muleta
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Water Resources Management ◽  
Climate Change Scenario ◽  
Emission Scenario ◽  
Future Climate ◽  
Future Climate Change ◽  
Change Scenario ◽  
Resources Management ◽  
Future Climate Change Scenario

Abstract Background Several water resources projects are under planning and implementation in the Baro-Akobo basin. Currently, the planning and management of these projects is relied on historical data. So far, hardly any study has addressed water resources management and adaptation measures in the face of changing water balances due to climate change in the basin. The main bottleneck to this has been lack of future climate change scenario base data over the basin. The current study is aimed at developing future climate change scenario for the basin. To this end, Regional Climate Model (RCM) downscaled data for A1B emission scenario was employed and bias corrected at basin level using observed data. Future climate change scenario was developed using the bias corrected RCM output data with the basic objective of producing baseline data for sustainable water resources development and management in the basin. Result The projected future climate shows an increasing trend for both maximum and minimum temperatures; however, for the case of precipitation it does not manifest a systematic increasing or decreasing trend in the next century. The projected mean annual temperature increases from the baseline period by an amount of 1 °C and 3.5 °C respectively, in 2040s and 2090s. Similarly, evapotranspiration has been found to increase to an extent of 25% over the basin. The precipitation is predicted to experience a mean annual decrease of 1.8% in 2040s and an increase of 1.8% in 2090s over the basin for the A1B emission scenario. Conclusion The study resulted in a considerable future change in climatic variables (temperature, precipitation, and evapotranspiration) on the monthly and seasonal basis. These have an implication on hydrologic extremes-drought and flooding, and demands dynamic water resources management. Hence the study gives a valuable base information for water resources planning and managers, particularly for modeling reservoir inflow-climate change relations, to adapt reservoir operation rules to the real-time changing climate.

scholarly journals Evaluation of long term forest fires in India with respect to state administrative boundary, forest category of LULC and future climate change scenario: A Geospatial Perspective

2018 ◽  
Vol 79 (4) ◽  
pp. 335-343
Author(s):  
Firoz Ahmad ◽  
Md Meraj Uddin ◽  
Laxmi Goparaju
Keyword(s):  
Climate Change ◽  
Forest Fire ◽  
Forest Fires ◽  
Climate Change Scenario ◽  
Fire Frequency ◽  
Future Climate ◽  
Future Climate Change ◽  
Change Scenario ◽  
Future Climate Change Scenario

Abstract Analysing the forest fires events in climate change scenario is essential for protecting the forest from further degradation. Geospatial technology is one of the advanced tools that has enormous capacity to evaluate the number of data sets simultaneously and to analyse the hidden relationships and trends. This study has evaluated the long term forest fire events with respect to India’s state boundary, its seasonal monthly trend, all forest categories of LULC and future climate anomalies datasets over the Indian region. Furthermore, the spatial analysis revealed the trend and their relationship. The state wise evaluation of forest fire events reflects that the state of Mizoram has the highest forest fire frequency percentage (11.33%) followed by Chhattisgarh (9.39%), Orissa (9.18%), Madhya Pradesh (8.56%), Assam (8.45%), Maharashtra (7.35%), Manipur (6.94%), Andhra Pradesh (5.49%), Meghalaya (4.86%) and Telangana (4.23%) when compared to the total country’s forest fire counts. The various LULC categories which represent the forest show some notable forest fire trends. The category ‘Deciduous Broadleaf Forest’ retain the highest fire frequency equivalent to 38.1% followed by ‘Mixed Forest’ (25.6%), ‘Evergreen Broadleaf Forest’ (16.5%), ‘Deciduous Needle leaf Forest’ (11.5%), ‘Shrub land’ (5.5%), ‘Evergreen Needle leaf Forest’ (1.5%) and ‘Plantations’ (1.2%). Monthly seasonal variation of forest fire events reveal the highest forest fire frequency percentage in the month of ‘March’ (55.4%) followed by ‘April’ (28.2%), ‘February’ (8.1%), ‘May’ (6.7%), ‘June’ (0.9%) and ‘January’ (0.7%). The evaluation of future climate data for the year 2030 shows significant increase in forest fire seasonal temperature and abrupt annual rainfall pattern; therefore, future forest fires will be more intensified in large parts of India, whereas it will be more crucial for some of the states such as Orissa, Chhattisgarh, Mizoram, Assam and in the lower Sivalik range of Himalaya. The deciduous forests will further degrade in future. The highlight/results of this study have very high importance because such spatial relationship among the various datasets is analysed at the country level in view of the future climate scenario. Such analysis gives insight to the policymakers to make sustainable future plans for prioritization of the various state forests suffering from forest fire keeping in mind the future climate change scenario.

scholarly journals Model and Scenario Variations in Predicted Number of Generations of Spodoptera litura Fab. on Peanut during Future Climate Change Scenario

PLoS ONE ◽  
2015 ◽  
Vol 10 (2) ◽  
pp. e0116762 ◽  
Author(s):  
Mathukumalli Srinivasa Rao ◽  
Pettem Swathi ◽  
Chitiprolu Anantha Rama Rao ◽  
K. V. Rao ◽  
B. M. K. Raju ◽  
...  
Keyword(s):  
Climate Change ◽  
Spodoptera Litura ◽  
Climate Change Scenario ◽  
Future Climate ◽  
Future Climate Change ◽  
Change Scenario ◽  
Future Climate Change Scenario

scholarly journals Future climate change scenario in hot semi-arid climate of Saurashtra, Gujarat by using statistical downscaling by LARS-WG model

MAUSAM ◽  
2021 ◽  
Vol 68 (4) ◽  
pp. 589-596
Author(s):  
JAYANTA SARKAR ◽  
J. R. CHICHOLIKAR
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Minimum Temperature ◽  
Daily Rainfall ◽  
Arid Climate ◽  
Weather Data ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Semi Arid ◽  
Far Future

Climate change is considered to be the greatest challenge faced by mankind in the twenty first century which can lead to severe impacts on different major sectors of the world such as water resources, agriculture, energy and tourism and are likely to alter trends and timing of precipitation and other weather drivers. Analyses and prediction of change in critical climatic variables like rainfall and temperature are, therefore, extremely important. Keeping this in mind, this study aims to verify the skills of LARS-WG (Long Ashton Research - Weather Generator), a statistical downscaling model, in simulating weather data in hot semi-arid climate of Saurashtra and analyze the future changes of temperature (maximum and minimum) and precipitation downscaled by LARS-WG based on IPCC SRA2 scenario generated by seven GCMs' projections for the near (2011-2030), medium (2046-2065) and far (2080-2099) future periods. Rajkot (22.3° N, 70.78° E) observatory of IMD, representing hot semi-arid climate of Saurashtra, Gujarat state was chosen for this purpose. Daily rainfall, maximum and minimum temperature data for the period of 1969-2013 have been utilized.             LARS-WG is found to show reasonably good skill in downscaling daily rainfall and excellent skill in downscaling maximum and minimum temperature. The downscaled rainfall indicated no coherent change trends among various GCMs’ projections of rainfall during near, medium and far future periods. Contrary to rainfall projections, simulations from the seven GCMs have coherent results for both the maximum and minimum temperatures. Based on the ensemble mean of seven GCMs, projected rainfall at Rajkot in monsoon season (JJAS) showed an increase in near future, i.e., 2011-2030, medium future (2046-2065) and far future (2080-2099) periods to the tune of 2, 11 and 14% respectively compared to the baseline value. Model studies indicating tropospheric warming leading to enhancement of atmospheric moisture content could be the reason for this increasing trend. Further, at the study site summer (MAM) maximum temperature is projected to increase by 0.5, 1.7 and 3.3°C during 2011-2030, 2046-2065 and 2080-2099 respectively and winter (DJF) minimum temperature is projected to increase by 0.8, 2.2 and 4.5 °C during 2011-2030, 2046-2065 and 2080-2099 respectively.  

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