Simulation of a Himalayan cloudburst event

Intense rainfall often leads to floods and landslides in the Himalayan region even with rainfall amounts that are considered comparatively moderate over the plains; for example, ‘cloudbursts’, which are devastating convective phenomena producing sudden high-intensity rainfall (∼10 cm per hour) over a small area. Early prediction and warning of such severe local weather systems is crucial to mitigate societal impact arising from the accompanying flash floods. We examine a cloudburst event in the Himalayan region at Shillagarh village in the early hours of 16 July 2003. The storm lasted for less than half an hour, followed by flash floods that affected hundreds of people. We examine the fidelity of MM5 configured with multiple-nested domains (81, 27, 9 and 3 km grid-resolution) for predicting a cloudburst event with attention to horizontal resolution and the cloud microphysics parameterization. The MM5 model predicts the rainfall amount 24 hours in advance. However, the location of the cloudburst is displaced by tens of kilometer

Skills of different mesoscale models over Indian region during monsoon season: Forecast errors

Performance of four mesoscale models namely, the MM5, ETA, RSM and WRF, run at NCMRWF for short range weather forecasting has been examined during monsoon-2006. Evaluation is carried out based upon comparisons between observations and day-1 and day-3 forecasts of wind, temperature, speci.c humidity, geopotential height, rainfall, systematic errors, root mean square errors and specific events like the monsoon depressions. It is very difficult to address the question of which model performs best over the Indian region? An honest answer is 'none'. Perhaps an ensemble approach would be the best. However, if we must make a final verdict, it can be stated that in general, (i) the WRF is able to produce best All India rainfall prediction compared to observations in the day-1 forecast and, the MM5 is able to produce best All India rainfall forecasts in day-3, but ETA and RSM are able to depict the best distribution of rainfall maxima along the west coast of India, (ii) the MM5 is able to produce least RMSE of wind and geopotential fields at most of the time, and (iii) the RSM is able to produce least errors in the day-1 forecasts of the tracks, while the ETA model produces least errors in the day-3 forecasts

Heavy rainfall episode over Mumbai on 26 July 2005: Assessment of NWP guidance

In the present work a qualitative assessment of guidance from NCMRWF operational global and regional Numerical Weather Prediction (NWP) systems in the episode of unprecedented rainfall over Mumbai has been attempted. This also consolidates and examines the predictions that were provided by some of the leading global operational centres. Some hindcast runs were also made with different initial conditions. It reveals that the use of very high resolution global and regional models with advanced data assimilation techniques (4D Var), that optimally utilizes information from satellite observations, could significantly enhance the usefulness of NWP guidance

Farmer’s understanding and adoption of agricultural practices in southern part of India

Abstract India is fulfilling the consumption requirement of its pulses and oilseeds largely through importing. Andhra Pradesh is a leading state in the country, significantly contributes to the production of these crops. Low yield of pulses and groundnuts in India should be addressed through adoption of proven technological interventions along with enhancing farmers knowledge. The present study aimed to determine the differences in knowledge of Sustainable Agricultural Practices (SAPs) and adoption of improved agricultural practices (IAPs) among farmers at the baseline and endline phase of the study. The association of possible factors such as age, gender, education, farm experience, mass media, social participation, risk orientation, innovativeness with knowledge and adoption of Sustainable agricultural practices was evaluated. The study also examined the result of the technological intervention on crop yield at pre and post intervention. The study included 240 farmers with poor pulse and groundnut yield from villages of Andhra Pradesh with inadequate technological developments. At biotech intervention phase, farmers received training, field demonstration etc. The results revealed that at endline, 80% of farmers had knowledge of SAPs (compared to 48% at baseline) and the adoption rate of IAPs was 50% (compared to 3% at baseline). Factors such as mass media, social participation, risk orientation showed significant reduced risk on farmers with high knowledge of SAPs and with complete adoption of IAPs. The average yield per hectare of pulses during baseline was found to be 403.5 kg/ha ± 128.4 while during endline it was 601.25 kg/ha ± 206.8 (p-value = 0.001). The average yield per hectare of groundnut during baseline was found to be 983.75 kg/ha ± 444.9 and during endline it was 1216.78 kg/ha ± 473.9 (p-value = 0.000). Innovative technological interventions and capacity building of farmers increased yield of crops in Andhra Pradesh

Sensitivity of a GCM simulation of two contrasting Indian monsoons to SST anomaly distributions

One of the major forcings for the interannual variability of the Asian Summer Monsoon is the Sea Surface Temperature (SST) distribution in the tropical Pacific Ocean. El Nino years are characterized by a negative Southern Oscillation Index (SOI) and a decreased monsoon rainfall over India leading to drought conditions. On the other hand, La Nina years are characterized by a positive SOI and generally good monsoon conditions over India. The monsoon ENSO relation is not a consistent one. The monsoons of 1991 and 1994 are good examples. The spring SOI was the same (-1.3) during both years. However, the All India Summer Monsoon Rainfall (AISMR) was 91.4 of normal in 1991 and 110 in 1994. Though the SOI was same during the spring of both years, the spatial distribution of SSTs was different. In the present study, the impacts of different SST distributions in the tropical Pacific Ocean, on the monsoons of 1991 and 1994 have been examined, to assess the UKMO-unified model's sensitivity to SST. It is observed that the simulated monsoon was much stronger in 1994 than in 1991, in terms of precipitation and circulation. The wind and the Outgoing Long-wave Radiation (OLR) simulated by the model are compared with NCEP/NCAR reanalyses data, while precipitation is compared with Xie-Arkin merged rainfall data

ENSO-Monsoon relationships in a green house warming scenario

Recent studies based on observed climatic data indicate weakening of the relationship between El Niño-Southern Oscillation (ENSO) and Indian summer monsoon rainfall, possibly due to global warming. Transient climate change simulations of a coupled ocean-atmosphere GCM (ECHAM4/OPYC3) project a change towards enhanced ENSO activities in the tropical Pacific, as well as increase in mean monsoon rainfall and variability over India. However, the interannual correlations between the two are strong throughout the 240 year simulation. Analysis of monsoon viz-a-viz ENSO in the model simulations suggest a diminished impact of warm ENSO (El Niño) events on monsoon, while the impact of cold ENSO (La Niña) events remains unchanged in the scenario. Anomalous warming over the Eurasian landmass as well as enhanced moisture conditions over the Indian monsoon region in the global warming scenario have possibly contributed to the weakening of the impact of warm ENSO events on monsoon