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Rathore, L. S.
- Predicting Future Changes in Temperature and Precipitation in Arid Climate of Kutch, Gujarat: Analyses Based on LARS-WG Model
Abstract Views :220 |
PDF Views:99
Authors
Affiliations
1 India Meteorological Department, Ahmedabad 382 475, IN
2 India Meteorological Department, New Delhi 110 003, IN
1 India Meteorological Department, Ahmedabad 382 475, IN
2 India Meteorological Department, New Delhi 110 003, IN
Source
Current Science, Vol 109, No 11 (2015), Pagination: 2084-2093Abstract
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
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- Rice (Oryza sativa L.) Yield Gap Using the CERSE-Rice Model of Climate Variability for Different Agroclimatic Zones of India
Abstract Views :303 |
PDF Views:133
Authors
P. K. Singh
1,
K. K. Singh
1,
L. S. Rathore
1,
A. K. Baxla
1,
S. C. Bhan
1,
Akhilesh Gupta
2,
G. B. Gohain
1,
R. Balasubramanian
3,
R. S. Singh
4,
R. K. Mall
4
Affiliations
1 Agromet Service Cell, India Meteorological Department, Lodhi Road, New Delhi 110 003, IN
2 Deparment of Science and Technology, New Delhi 110 016, IN
3 Agrimet Pune, New Delhi 411 005, IN
4 Banaras Hindu University, Varanasi 221 005, IN
1 Agromet Service Cell, India Meteorological Department, Lodhi Road, New Delhi 110 003, IN
2 Deparment of Science and Technology, New Delhi 110 016, IN
3 Agrimet Pune, New Delhi 411 005, IN
4 Banaras Hindu University, Varanasi 221 005, IN
Source
Current Science, Vol 110, No 3 (2016), Pagination: 405-413Abstract
The CERES (crop estimation through resource and Environment Synthesis)-rice model incorporated in DSSAT version 4.5 was calibrated for genetic coefficients of rice cultivars by conducting field experiments during the kharif season at Jorhat, Kalyani, Ranchi and Bhagalpur, the results of which were used to estimate the gap in rice yield. The trend of potential yield was found to be positive and with a rate of change of 26, 36.9, 57.6 and 3.7 kg ha-1 year-1 at Jorhat, Kalyani, Ranchi and Bhagalpur districts respectively. Delayed sowing in these districts resulted in a decrease in rice yield to the tune of 35.3, 1.9, 48.6 and 17.1 kg ha-1 day-1 respectively. Finding reveals that DSSAT crop simulation model is an effective tool for decision support system. Estimation of yield gap based on the past crop data and subsequent adjustment of appropriate sowing window may help to obtain the potential yields.Keywords
Agroclimatic Zones, Genetic Coefficients, Rice Model, Yield Gap.References
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- Singh, P. K., Singh, K. K., Baxla, A. K. and Rathore, L. S., Impact of climatic variability on Rice productivity using CERES-rice models Eastern plain zone of Uttar Pradesh. In Third International Agronomy Congress on ‘Agriculture Diversification, Climate Change Management and Livelihoods’, IARI, New Delhi, 26–30 November 2012 and extended summaries vol. (2), 2012, pp. 236– 237.
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- Why IMD Got the Seasonal Forecast of 2015 Southwest Monsoon Rainfall Right
Abstract Views :257 |
PDF Views:83
Authors
Affiliations
1 India Meteorological Department, New Delhi 110 003, IN
1 India Meteorological Department, New Delhi 110 003, IN
Source
Current Science, Vol 109, No 12 (2015), Pagination: 2167-2168Abstract
No Abstract.- Impact of Projected Climate Change on Rice (Oryza sativa L.) Yield Using CERES-Rice Model in Different Agroclimatic Zones of India
Abstract Views :243 |
PDF Views:86
Authors
P. K. Singh
1,
K. K. Singh
1,
S. C. Bhan
1,
A. K. Baxla
1,
Sompal Singh
2,
L. S. Rathore
1,
Akhilesh Gupta
3
Affiliations
1 Agromet Service Cell, India Meteorological Department, Lodhi Road, New Delhi 110 003, IN
2 Department of Agriculture Meteorology, Punjab Agriculture University, Ludhiana 141 004, IN
3 Department of Science and Technology, New Delhi 110 016, IN
1 Agromet Service Cell, India Meteorological Department, Lodhi Road, New Delhi 110 003, IN
2 Department of Agriculture Meteorology, Punjab Agriculture University, Ludhiana 141 004, IN
3 Department of Science and Technology, New Delhi 110 016, IN