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Kumar P.,Atmospheric and Oceanic science Group | Bhattacharya B.K.,Space Applications Center | Pal P.K.,Atmospheric and Oceanic science Group
Agricultural and Forest Meteorology | Year: 2013

Indian economy is largely depending upon the agricultural productivity and thus influences the trade among the SAARC countries. High-resolution and good-quality regional weather forecasts are necessary for planners, resource managers, insurers and national agro-advisory services. In this study, high resolution updated land-surface state in terms of vegetation fraction (VF) from operational vegetation index products of Indian geostationary satellite (INSAT 3A) sensor (CCD) was utilized in numerical weather prediction (NWP) model (e.g. WRF) to investigate its impact on short-range weather forecast over the control run. Results showed that the updated vegetation fraction from INSAT 3A CCD improved the low-level 24. h temperature (∼18%) and moisture (∼10%) forecast in comparison to control run. The 24. h rainfall forecast was also improved (more than 5%) over central and southern India with the use of updated vegetation fraction compared to control experiment. INSAT 3A VF based experiment also showed a net improvement of 27% in surface sensible heat fluxes from WRF in comparison to control experiment when both were compared with area-averaged measurements from Large Aperture Scintillometer (LAS). This triggers the need of more and more use of realistic and updated land surface states through satellite remote sensing data as well as in situ micrometeorological measurements to improve the forecast quality, skill and consistency. © 2012 Elsevier B.V.

Chakraborty A.,Atmospheric and Oceanic science Group | Kumar R.,Atmospheric and Oceanic science Group
Remote Sensing Letters | Year: 2013

Daily and 12 hourly gridded analysed wind vectors (AWVs) over global ocean were generated using the simple spatial interpolation scheme of 'box averaging', with a horizontal resolution of 0.5° × 0.5°. For daily analysed winds, observations only from Oceansat-2 Scatterometer (O°CAT) were used. The 12 hourly AWVs were generated by combining the data from both O°CAT and Advanced Scatterometer (A°CAT). Apart from ocean wind vectors, an effort was made also to produce analysed wind stress, divergence and curl of wind stress. The daily and 12 hourly analysed winds were validated using in situ observations from 97 global moored buoys and data from European°Centre for Medium Range Weather Forecasting analyses for a period of 9 months. The validation result shows a good agreement between AWV products and the buoy and model analysis data, yielding a standard deviation of around 2 m s-1 in wind speed and around 20° in wind direction. © 2012 Taylor & Francis.

Kumar P.,Atmospheric and Oceanic science Group | Harish Kumar K.P.,AIR INDIA | Pal P.K.,Atmospheric and Oceanic science Group
IEEE Transactions on Geoscience and Remote Sensing | Year: 2013

The Indian Space Research Organisation launched the Oceansat-2 scatterometer (OSCAT) for atmospheric and oceanographic applications. In this paper, a case study has been performed to assess the impact of OSCAT-retrieved wind vectors on the simulation of tropical cyclone Phet over the Arabian Sea. Three-dimensional variational data assimilation of the Weather Research and Forecasting model is used for this purpose. In addition to OSCAT winds, wind speed and precipitable water derived from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) are also used for assimilation to evaluate the impact of scatterometer and radiometer data on tropical cyclone prediction. Results show that an ∼60-km track error is observed in control and TMI experiments when compared with Joint Typhoon Warning Center observed cyclone center at 1800 UTC 01 June 2010. An approximately 40-km track error is determined in the initial center position of OSCAT experiments. The mean track error forecast is less in OSCAT experiments (∼ 80 km) in comparison with TMI experiments (∼ 110 km). Only OSCAT data experiments are able to predict the track of the cyclone toward the Oman coast. Assimilation of scatterometer wind direction improves the track forecast; but it degrades the forecast of the intensity, maximum magnitude, and evolution of the cyclone. None of these experiments are able to capture the observed minimum sea level pressure (964 hPa at 1200 UTC 02 June 2010) accurately. TMI experiments are slightly better than OSCAT experiments in capturing the intensity of cyclone Phet, whereas wind direction from OSCAT improves the track forecast of the cyclone. © 1980-2012 IEEE.

Karaseva M.O.,Kyrgyz Russian Slavic University | Prakash S.,Atmospheric and Oceanic science Group | Gairola R.M.,Atmospheric and Oceanic science Group
Theoretical and Applied Climatology | Year: 2012

This paper presents the validation of monthly precipitation using Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA)-3B43 product with conventional rain gauge observations for the period 1998-2007 over Kyrgyzstan. This study is carried out to quantify the accuracy of TMPA-3B43 product over the high latitude and complex orographic region. The present work is quite important because it is highly desirable to compare the TMPA precipitation product with the ground truth data at a regional scale, so that the satellite product can be fine-tuned at that scale. For the validation, four different types of spatial collocation have been used: station wise, climatic zone wise, topographically and seasonal. The analysis has been done at the same spatial and temporal scales in order to eliminate the sampling biases in the comparisons. The results show that TMPA-3B43 product has statistically significant correlation (r = 0.36-0.88) with rain gauge data over the most parts of the country. The minimum linear correlation is observed around the large continental water bodies (e. g., Issyk-Kul lake; r = 0.17-0.19). The overall result suggests that the precipitation estimated using TMPA-3B43 product performs reasonably well over the plain regions and even over the orographic regions except near the big lake regions. Also, the negative bias suggests the systematic underestimation of high precipitation by TMPA-3B43 product. The analyses suggest the need of a better algorithm for precipitation estimation over this region separately to capture the different types of rain events more reliably. © 2011 Springer-Verlag.

Jaiswal N.,Atmospheric and Oceanic science Group | Kishtawal C.M.,Atmospheric and Oceanic science Group
IEEE Transactions on Geoscience and Remote Sensing | Year: 2011

In the present work, a new technique based on the data mining approach has been discussed for the prediction of tropical cyclogenesis using the ocean wind vectors derived from the sea-winds scatterometer on QuikScat satellite. The technique is based on similarity of given wind pattern with wind vector signatures of developing systems, available from the past observations. A database has been formed in this work using the QuikScat-observed vector wind patterns associated with the early stages of tropical cyclones that developed in the North Indian basin during the years 2000-2008. The prediction of possibility of cyclogenesis, in a given scene, is determined by matching it with all the archived scenes in a database using vector block matching algorithm. The system is predicted as developing, if its matching index exceeds the predetermined threshold value (0.5). The prediction of cyclogenesis can be made 24-96 h prior to its classification as a tropical storm by the Joint Typhoon Warning Centre. The probability of detection of the technique is determined using the equivalent of the Jackknife approach in the database as 0.93. The algorithm is tested with a continuous wind data of years 2007-2009 for active cyclone months (excluding the scenes archived in a database). All the 14 tropical disturbances that developed into tropical storms during the test period were predicted using the discussed method, and two false alarms were found. © 2011 IEEE.

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