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Predicting Future Changes in Temperature and Precipitation in Arid Climate of Kutch, Gujarat: Analyses Based on LARS-WG Model


Affiliations
1 India Meteorological Department, Ahmedabad 382 475, India
2 India Meteorological Department, New Delhi 110 003, India
 

Keeping in mind the challenge of climate change faced by mankind in the 21st century, this study attempts to analyse and predict changes in critical climatic variables (rainfall and temperature) to develop strategies and make informed decisions about the future water allocation for different sectors and manage available water resources. The aim of this study is to verify the skills of LARS-WG in simulating weather data in arid climate of Kutch, Gujarat, and predict and analyse the future changes in them for the near (2011-2030), medium (2046-2065) and far (2080-2099) future periods. Data utilised, for this study, are daily rainfall, maximum and minimum temperature for the period of 1969-2013. LARS-WG is found to show reasonably good (excellent) skill in downscaling daily rainfall (temperature). The downscaled precipitation indicated no coherent change trends among various global climate models (GCMs) predictions for near, medium and far future periods. Ensemble means of rainfall predictions from 7 GCMs indicated 9-17% increase in monsoon (JJAS) rainfall compared to the base line during medium future; however, in the far future this increase is predicted to be reduced and remain in the range 3-12%. Winter minimum temperature is predicted to increase by 0.6-1°C during 2011-2030; for 2046-2065 and 2080-2099 this increase is predicted to be around 3.0 and 5.0°C respectively. Summer maximum temperature is predicted to increase by 0.1-0.2°C during 2011-2030; for 2046-2065 and 2080-2099 this increase is predicted to be around 1.1-1.5°C and around 3.0°C respectively.

Keywords

Arid Climate, Climate Change, Global Climate Models, Precipitation, Temperature.
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  • Intergovernmental Panel on Climate Change, Special report on emission scenarios, 2000; http://www.grida.no/climate/ipcc/emission/ index.htm

  • Wilby, R. L. and Dawson, C. W., SDSM - a decision support tool for the assessment of regional climate change impacts. Environ. Model. Software, 2002, 17, 145-157.

  • Dibike, Y. B. and Coulibaly, P., Hydrologic impact of climate change in the Saguenay watershed: comparison of downscaling methods and hydrologic models. J. Hydrol., 2005, 307, 145-163.

  • Kilsby, C. G. and Jones, P. D., A daily weather generator for use in climate change studies. Environ. Model. Software, 2007, 22, 1705-1719.

  • Wilks, D. S., Adapting stochastic weather generation algorithms for climate change studies. Climatic Change, 1992, 22, 67-84.

  • Wilks, D. S., Multisite downscaling of daily precipitation with a stochastic weather generator. Climate Res., 1999, 11, 125-136.

  • Semenov, M. A., Brooks, R. J., Barrow, E. M. and Richardson, C.

  • W., Comparison of the WGEN and LARS-WG stochastic weather generators in diverse climates. J. Climate Res., 1998, 10, 95-107.

  • Semenov, M. A. and Barrow, E. M., Use of a stochastic weather generator in the development of climate change scenarios. Climatic Change, 1997, 35, 397-414.

  • Reddy, K. S., Kumar, M., Maruthi, V., Umesha, B., Vijayalaxmi and Nageswar Rao, C. V. K., Climate change analysis in southern Telangana region, Andhra Pradesh using LARS-WG model. Curr. Sci., 2014, 107, 54-62.

  • Hashmi, M. Z., Shamseldin, A. Y. and Melville, B. W., Downscaling of future rainfall extreme events: a weather generator based approach. In 18th World IMACS/MODSIM Congress, Cairns, Australia, 2012, pp. 13-17.

  • Racsko, P., Szeidl, L. and Semenov, M., A serial approach to local stochastic weather models. J. Ecol. Model., 1991, 57, 27-41.

  • Semenov, M. A., LARS-WG: a stochastic weather generator for use in climate impact studies. User Manual, 2002, pp. 1-27 (http://www.rothamsted.ac.uk/masmodels/larswg.php).

  • Semenov, M. A. and Stratonovitch, P., Use of multi-model ensembles from global climate models for assessment of climate change impacts. Climate Res., 2010, 1, 1-14.

  • Chen, H., Guo, J., Zhang, Z. and Xu, C.-Y., Prediction of temperature and precipitation in Sudan and South Sudan by using LARSWG in future. Theor. Appl. Climatol., 2013, 113, 363-375.


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  • Predicting Future Changes in Temperature and Precipitation in Arid Climate of Kutch, Gujarat: Analyses Based on LARS-WG Model

Abstract Views: 339  |  PDF Views: 165

Authors

Jayanta Sarkar
India Meteorological Department, Ahmedabad 382 475, India
J. R. Chicholikar
India Meteorological Department, Ahmedabad 382 475, India
L. S. Rathore
India Meteorological Department, New Delhi 110 003, India

Abstract


Keeping in mind the challenge of climate change faced by mankind in the 21st century, this study attempts to analyse and predict changes in critical climatic variables (rainfall and temperature) to develop strategies and make informed decisions about the future water allocation for different sectors and manage available water resources. The aim of this study is to verify the skills of LARS-WG in simulating weather data in arid climate of Kutch, Gujarat, and predict and analyse the future changes in them for the near (2011-2030), medium (2046-2065) and far (2080-2099) future periods. Data utilised, for this study, are daily rainfall, maximum and minimum temperature for the period of 1969-2013. LARS-WG is found to show reasonably good (excellent) skill in downscaling daily rainfall (temperature). The downscaled precipitation indicated no coherent change trends among various global climate models (GCMs) predictions for near, medium and far future periods. Ensemble means of rainfall predictions from 7 GCMs indicated 9-17% increase in monsoon (JJAS) rainfall compared to the base line during medium future; however, in the far future this increase is predicted to be reduced and remain in the range 3-12%. Winter minimum temperature is predicted to increase by 0.6-1°C during 2011-2030; for 2046-2065 and 2080-2099 this increase is predicted to be around 3.0 and 5.0°C respectively. Summer maximum temperature is predicted to increase by 0.1-0.2°C during 2011-2030; for 2046-2065 and 2080-2099 this increase is predicted to be around 1.1-1.5°C and around 3.0°C respectively.

Keywords


Arid Climate, Climate Change, Global Climate Models, Precipitation, Temperature.

References





DOI: https://doi.org/10.18520/cs%2Fv109%2Fi11%2F2084-2093