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National Centre for Medium Range Weather Forecasting

GovernmentNoida, India
About: National Centre for Medium Range Weather Forecasting is a government organization based out in Noida, India. It is known for research contribution in the topics: Monsoon & Weather Research and Forecasting Model. The organization has 176 authors who have published 368 publications receiving 4749 citations.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the CERES-Rice v3.0 crop simulation model was used for analysing the effect of climate change on rice productivity in the state of Kerala.
Abstract: The CERES-Rice v3. crop simulation model, calibrated and validated for its suitability to simulate rice production in the tropical humid climate Kerala State of India, is used for analysing the effect of climate change on rice productivity in the state. The plausible climate change scenario for the Indian subcontinent as expected by the middle of the next century, taking into account the projected emissions of greenhouse gases and sulphate aerosols, in a coupled atmosphere-ocean model experiment performed at Deutsches Klimarechenzentrum, Germany, is adopted for the study. The adopted scenario represented an increase in monsoon seasonal mean surface temperature of the order of about 1.5°C, and an increase in rainfall of the order of 2 mm per day, over the state of Kerala in the decade 2040–2049 with respect to the 1980s. The IPCC Business-as-usual scenario projection of plant usable concentration of CO2 about 460 PPM by the middle of the next century are also used in the crop model simulation. On an average over the state with the climate change scenario studied, the rice maturity period is projected to shorten by 8% and yield increase by 12%. When temperature elevations only are taken into consideration, the crop simulations show a decrease of 8% in crop maturity period and 6% in yield. This shows that the increase in yield due to fertilisation effect of elevated CO2 and increased rainfall over the state as projected in the climate change scenario nearly makes up for the negative impact on rice yield due to temperature rise. The sensitivity experiments of the rice model to CO2 concentration changes indicated that over the state, an increase in CO2 concentration leads to yield increase due to its fertilisation effect and also enhance the water use efficiency of the paddy. The temperature sensitivity experiments have shown that for a positive change in temperature up to 5°C, there is a continuous decline in the yield. For every one degree increment the decline in yield is about 6%. Also, in another experiment it is observed that the physiological effect of ambient CO2 at 425 ppm concentration compensated for the yield losses due to increase in temperature up to 2°C. Rainfall sensitivity experiments have shown that increase in rice yield due to increase in rainfall above the observed values is near exponential. But decrease in rainfall results in yield loss at a constant rate of about 8% per 2 mm/day, up to about 16 mm/day.

225 citations

Journal ArticleDOI
TL;DR: In this article, vulnerability of wheat and rice crops in northwest India to projected climate change is examined, where sensitivity experiments with these models showed that a 3°C (2°C) rise in air temperature nearly cancels out the positive effect of elevated CO2 on the wheat yields.

213 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigate the capabilities of the tropical rain measurement mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and the recently released integrated multi-satellitE Retrievals for GPM (IMERG) in detecting and estimating heavy rainfall across India.

210 citations

Journal ArticleDOI
TL;DR: In this paper, two advanced high resolution multi-satellite precipitation products namely, Integrated Multi-satellitE Retrievals for GPM (IMERG) and Global Satellite Mapping of Precipitation (GSMaP) version 6 are released.

208 citations

Journal ArticleDOI
TL;DR: In this article, an algorithm to merge TRMM Multi-satellite Precipitation Analysis (TMPA) satellite estimates with the India Meteorological Department (IMD) rain-gauge values is tested for the Indian monsoon region.
Abstract: The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR) have enhanced the accuracy of rainfall estimation from satellites over ocean and land. An algorithm to merge TRMM Multi-satellite Precipitation Analysis (TMPA) satellite estimates with the India Meteorological Department (IMD) rain-gauge values is tested for the Indian monsoon region. A daily merged gauge and satellite data product (NMSG) at 1° latitude-longitude resolution for the Indian monsoon region is prepared to depict the large-scale aspects of monsoon rainfall. The satellite product used as a first guess is the TRMM TMPA for daily estimates. Incorporation of IMD gauge data corrects the mean biases of the TMPA values. TMPA alone is able to depict the space-time distribution of monsoon rainfall patterns. The merging of gauge data enhances the value of the satellite information; therefore, the NMSG is more representative than TMPA. Daily, monthly, and seasonal fields are prepared and compared with the land-only gridded data of the India Meteorological Department National Climate Centre (IMDNCC) at the same resolution. This inter-comparison with another independent dataset confirms the utility of the NMSG, produced by this objective analysis algorithm. The comparison of the merged data with the TMPA data reveals the regions where the satellite estimates have mean biases. Objective statistical scores also confirm the goodness of NMSG. The NMSG data are meant for use in verification of large-scale rainfall features from numerical models for the monsoon region.

181 citations


Authors

Showing all 179 results

NameH-indexPapersCitations
U. C. Mohanty373065501
Raghavan Krishnan371084033
Ashis K. Mitra22851645
Satya Prakash201551785
Sarat C. Kar1858876
E. N. Rajagopal1543754
A. Routray1546774
Someshwar Das1538585
M.P. Raju1319555
Nachiketa Acharya1230475
Raghavendra Ashrit1245938
Upal Saha1225328
G. R. Iyengar1129329
Sujata Pattanayak1125364
V. S. Prasad1147324
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20232
20226
202158
202047
201940
201821