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Varma A.K.,Meteorology and Oceanography Group | Liu G.,Florida State University
Journal of Geophysical Research: Atmospheres | Year: 2010

Classification of rain type in satellite microwave observations is useful for various studies ranging from numerical weather prediction and precipitation climatology to satellite retrieval of rain amounts. In this study we have first examined the possibility of determining the distribution of convective/ stratiform rain within a typical microwave radiometric pixel size area represented by the Tropical Rainfall Measuring Mission Microwave Imager (TMI) and then formulated an empirical relation between the convective to stratiform ratio and observed brightness temperatures. Rain classification with satellite microwave observation is hampered by the small size of the rain events. It is found from the rain observations during July 2000 that a significant number of 53% convective and 28% stratiform rain fill less than one fourth of the TMI pixel size area. The nonlinear relationship between brightness temperature and rain rate, along with horizontal and vertical inhomogeneity of the rain type distribution within the pixel, makes it difficult to work out the exact proportion of convective to stratiform istribution within the pixel. Here an algorithm is proposed to determine rain type on the basis of regression with 10 functions of 19, 37, and 85 GHz channels into three broad convectivestratiform proportions. This algorithm is able to identify rain types in about 70% of the TMI pixels accurately. To broaden the utility of the proposed method, a procedure has been developed by which the method can be applied to any other microwave radiometers with similar channels to TMI. Using this procedure, a successful application of the algorithm to Special Sensor Microwave Imager observations is demonstrated. Copyright 2010 by the American Geophysical Union.

Rakesh V.,CSIR - Central Electrochemical Research Institute | Singh R.,Meteorology and Oceanography Group | Joshi P.C.,Meteorology and Oceanography Group
Pure and Applied Geophysics | Year: 2011

This study examines the short-range forecast accuracy of the Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5) as applied to the July 2006 episode of the Indian summer monsoon (ISM) and the model's sensitivity to the choice of different cumulus parameterization schemes (CPSs), namely Betts-Miller, Grell (GR) and Kain-Fritsch (KF). The results showed that MM5 day 1 (0-24 h prediction) and day 2 (24-48 h prediction) forecasts using all three CPSs overpredicted monsoon rainfall over the Indian landmass, with the larger overprediction seen in the day 2 forecasts. Among the CPSs, the rainfall distribution over the Indian landmass was better simulated in forecasts using the KF scheme. The KF scheme showed better skill in predicting the area of rainfall for most of the rainfall thresholds. The root mean square error (RMSE) in day 1 and day 2 rainfall forecasts using different CPSs showed that rainfall simulated using the KF scheme agreed better with the observed rainfall. As compared to other CPSs, simulation using the GR scheme showed larger RMSE in wind speed prediction at 850 and 200 hPa over the Indian landmass. MM5 24-h temperature forecasts at 850 hPa with all the CPSs showed a warm bias of the order of 1 K over the Indian landmass and the bias doubled in 48-h model forecasts. The mean error in temperature prediction at 850 hPa over the Indian region using the KF scheme was comparatively smaller for all the forecast intervals. The model with all the CPSs over predicted humidity at 850 hPa. The improved prediction by MM5 with the KF scheme is well complemented by the smaller error shown by the KF scheme in vertical distribution of heat and mean moist static energy in the lower troposphere. In this study, the KF scheme which explicitly resolve the downdrafts in the cloud column tended to produce more realistic precipitation forecasts as compared to other schemes which did not explicitly incorporate downdraft effects. This is an important result especially given that the area covered by monsoon-precipitating systems is largely from stratiform-type clouds which are associated with strong downdrafts in the lower levels. This result is useful for improving the treatment of cumulus convection in numerical models over the ISM region. © 2010 Springer Basel AG.

Govindan R.,Meteorology and Oceanography Group | Kumar R.,Meteorology and Oceanography Group | Basu S.,Meteorology and Oceanography Group | Sarkar A.,Meteorology and Oceanography Group
IEEE Geoscience and Remote Sensing Letters | Year: 2011

It is known that wave period can be estimated from altimeter measurements of wave height, wind speed, radar backscatter cross section, etc., using empirical relationship. Of late, the data adaptive approach of neural networks has been used to derive wave period from altimeter data, and it has been shown that the technique appears to be superior compared to the empirical approaches. Another powerful data adaptive approach of genetic algorithm has been advocated more recently in oceanographic studies. Although primarily used for forecasting time series, the algorithm can be tuned to find a relationship between input and output variables. In the present work, this algorithm has been used to find estimates of wave period from altimeter-observed parameters, and the performance of the algorithm has been found to be quite satisfactory. It has been also found that the introduction of wave age leads to significant enhancement of the accuracy of the estimate. © 2006 IEEE.

Singh R.,Meteorology and Oceanography Group | Kishtawal C.M.,Meteorology and Oceanography Group | Pal P.K.,Meteorology and Oceanography Group | Joshi P.C.,Meteorology and Oceanography Group
Meteorology and Atmospheric Physics | Year: 2011

Weather Research and Forecasting (WRF-ARW) model and its three-dimensional variational data assimilation (3D-Var) system are used to investigate the impact of the Quick Scatterometer (QuikSCAT) near surface winds, Special Sensor Microwave/Imager (SSM/I)-derived Total Precipitable Water (TPW), and Meteosat-7-derived Atmospheric Motion Vectors (AMVs) on the track and intensity prediction of tropical cyclones over the North Indian Ocean. The case of tropical cyclone, Gonu (June 2007; Arabian Sea), is first tested and the results show significant improvements particularly due to the assimilation of QuikSCAT winds. Three other cases, cyclone Mala (April 2006; Bay of Bengal), Orissa super cyclone (October 1999; Bay of Bengal), and Very Severe Cyclonic storm (October 1999; Bay of Bengal), are then examined. The prediction of cyclone tracks improved significantly with the assimilation of QuikSCAT winds. The track improvement resulted from the relocation of the initial cyclonic vortices after the assimilation of QuikSCAT wind vectors. After the assimilation of QuikSCAT winds, the mean (for four cyclone cases) track errors for first, second, and third day forecasts are reduced to 72, 101, and 166 km, respectively, from 190, 250, and 381 km of control (without QuikSCAT winds) runs. The assimilation of QuikSCAT winds also shows positive impact on the intensity (in terms of maximum surface level winds) prediction particularly for those cyclones, which are at their initial stages of the developments at the time of data assimilation. The assimilation of SSM/I TPW has significant influence (negative and positive) on the cyclone track. In three of the four cases, the assimilation of the SSM/I TPW resulted in drying of lower troposphere over cyclonic region. This decrease of moisture in TPW assimilation experiment resulted in reduction of cyclonic intensity. In three of the four cyclones, the assimilation of Meteosat-7 AMVs shows negative impact on the track prediction. © 2011 Springer-Verlag.

Jaiswal N.,Meteorology and Oceanography Group | Kishtawal C.M.,Meteorology and Oceanography Group
IEEE Geoscience and Remote Sensing Letters | Year: 2011

In this letter, a new method is discussed for the automatic determination of the center of tropical cyclones (TCs) by extracting the spiral features within it using the infrared (IR) images from geostationary satellites. Meteosat-5 IR images of two TCs viz., Mala (April 2429, 2006), and Sub Tropical Storm 4 (STS-4) (October 1518, 1999) have been analyzed using the image processing techniques, and the center of the TC is then estimated by fitting the spiral at different locations. The present method provides accurate estimates of the cyclone center for the images where the spiral patterns are well featured. However, the method leads to larger errors during formative or decaying phase of cyclone due to the absence of robust pattern in the images. The present method has a potential to be applied in a completely automated mode and can be used to replace the manual center determination which is being done traditionally. © 2010 IEEE.

Gohil B.S.,Meteorology and Oceanography Group | Sharma P.,Meteorology and Oceanography Group | Sikhakolli R.,Meteorology and Oceanography Group | Sarkar A.,Meteorology and Oceanography Group
IEEE Geoscience and Remote Sensing Letters | Year: 2010

A new directional-ambiguity removal algorithm has been developed for improving the wind fields derived from a scatterometer. Exploiting the natural spatial variability of ocean surface wind directions and invoking the conservation of backscattering, a new directional stability-weighted low-pass filter has been designed to complement the circular median filtering. It improves the directional-ambiguity removal by reducing the directional noise while retaining the natural wind flow. On the basis of analysis, which will be described later, indicating the lower spatial stability (conversely, the variability) of the wind direction and the lower direction-retrieval skills of the scatterometer-derived winds at low-intensity winds (< 3 m/s) as compared to those for winds above 3 m/s, the ambiguity removal has been performed separately for these two wind regimes. The proposed Directional Stability and Conservation of Scattering (DiSCS) algorithm is applicable to the full swath of the scatterometer. Using the DiSCS algorithm, the wind fields derived from QuikSCAT Level-2A backscatter data over global oceans for 57 orbits during July 1-4, 2005, have been compared with the winds from the National Centers for Environmental Predictions and European Centre for Medium-Range Weather Forecasts models. Similar comparisons of QuikSCAT Level-2B finished products direction interval retrieval with thresholded nudging winds (referred to hereinafter as FP) with the winds from these two models have been performed. The QuikSCAT-derived winds are found to be closer to the model winds as compared to those QuikSCAT FP winds. © 2010 IEEE.

Dash M.K.,Indian Institute of Technology Kharagpur | Pandey P.C.,Indian Institute of Technology Bhubaneswar | Vyas N.K.,Meteorology and Oceanography Group | Turner J.,British Antarctic Survey
International Journal of Climatology | Year: 2013

The linkages between the El Niño Southern Oscillation (ENSO) and the sea ice extent (SIE) in the Weddell Sea (South Atlantic) and the Bellingshausen-Amundsen Sea (South-Eastern Pacific) sectors of the Southern Ocean have been studied for the period 1979-2005 using crosswavelet analysis. The analysis showed that the relationship between the tropical expression of ENSO and the SIE in these two areas are different before and after 1992. Further, we investigated the structure and strength of the regional Ferrel cell (RFC) during El Niño and La Niña episodes using composite latitude-pressure cross-sections of wind anomalies for these two periods. Contrasting features were observed in the structure and strength of the RFC before and after 1992 in both, the South Atlantic and the South-Eastern Pacific. These modulations in the RFC control the heat transport from the tropics to high latitudes and hence the extent of sea ice in both the regions. We propose that the modulation of the RFC is responsible for the phase shift in the tropical-polar teleconnection. © 2012 Royal Meteorological Society.

Deb S.K.,Meteorology and Oceanography Group | Kishtawal C.M.,Meteorology and Oceanography Group | Pal P.K.,Meteorology and Oceanography Group
Monthly Weather Review | Year: 2010

The water vapor winds from the operational geostationary Indian National Satellite (INSAT) Kalpana-1 have recently become operational at the Space Applications Centre (SAC). A series of experimental forecasts are attempted here to evaluate the impact of water vapor winds derived from Kalpana-1 for the track and intensity prediction of two Bay of Bengal tropical cyclones (TCs), Sidr and Nargis, using the Weather Research and Forecasting (WRF) modeling system. The assimilation of water vapor winds has made some impact in the initial position errors as well as track forecasts when compared with the corresponding control experiments for both TCs. However, no statistically significant improvement is noticed in the simulations of TC intensities [i.e., minimum sea level pressure (MSLP) and maximum surface winds forecasts when satellite winds are used for assimilation]. Moreover, the performance of Kalpana-1 winds is evaluated by repeating the same sets of experiments using Meteosat-7 winds derived at the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) and compared with observed data. The simulation of initial position errors, and track and intensity forecasts using the assimilation of water vapor winds from both satellites are comparable. Though, these results are preliminary with respect to the Kalpana-1 winds, the present study can provide some insight to the WRF model users over the Indian Ocean region. © 2010 American Meteorological Society.

Prakash S.,Meteorology and Oceanography Group | Mahesh C.,Meteorology and Oceanography Group | Gairola R.M.,Meteorology and Oceanography Group | Pal P.K.,Meteorology and Oceanography Group
Meteorology and Atmospheric Physics | Year: 2010

In the present study, an attempt has been made to estimate and validate the daily and monthly rainfall during the Indian summer monsoon seasons of 2008 and 2009 using INSAT (Indian National Satellite System) Multispectral Rainfall Algorithm (IMSRA) technique utilizing Kalpana-1 very high resolution radiometer (VHRR) measurements. In contrary to infrared (IR), microwave (MW) rain rates are based on measurements that sense precipitation in clouds and do not rely merely on cloud top temperature. Geostationary satellites provide broad coverage and frequent refresh measurements but microwave measurements are accurate but sparse. IMSRA technique is the combination of the infrared and microwave measurements which make use of the best features of both IR- and MW-based rainfall estimates. The development of this algorithm included two major steps: (a) classification of rain-bearing clouds using proper cloud classification scheme utilizing Kalpana-1 IR and water vapor (WV) brightness temperatures (Tb) and (b) collocation of Kalpana-1 IR brightness temperature with Tropical Rainfall Measuring Mission (TRMM)-Precipitation Radar (PR) surface rain rate and establishment of a regression relation between them. In this paper, the capability of IMSRA as an operational algorithm has been tested for the two monsoon seasons 2008 and 2009. For this, IMSRA has been used to estimate daily and monthly rainfall and has been intercompared on daily and monthly scales with TRMM Multisatellite Precipitation Analysis (TMPA)-3B42 V6 product and Global Precipitation Climatology Project (GPCP) rain product during these two monsoon years. The daily and monthly IMSRA rainfall has also been validated against ground-based observations from Automatic Weather Station (AWS) Rain Gauge and Buoy data. The algorithm proved to be in good correlation with AWS data over land up to 0.70 for daily rain estimates except orographic regions like North-East and South-West India and 0.72 for monthly rain estimates. The validation with Buoys gives the reasonable correlation of 0.49 for daily rain estimates and 0.66 for monthly rain estimates over Tropical Indian Ocean. © 2010 Springer-Verlag.

Singh R.,Meteorology and Oceanography Group | Pal P.K.,Meteorology and Oceanography Group | Joshi P.C.,Meteorology and Oceanography Group
Journal of Geophysical Research: Atmospheres | Year: 2010

The very high resolution radiometer (VHRR) channel 3 (at 6.2 μm) on the Indian Geostationary satellite Kalpana is sensitive to mid-upper tropospheric water vapor. This paper describes the assimilation of Kalpana VHRR channel 3 clear-sky radiances (hereafter water vapor (WV) radiances) in the Weather Research and Forecasting (WRF) three-dimensional variational assimilation (3D-Var) system. The Kalpana WV radiances (in terms of blackbody equivalent brightness temperatures) are used in combination with a fast radiative transfer model and 3D-Var assimilation system in the WRF model. Extensive preassimilation monitoring of the WV radiances has been carried out, showing a diurnal bias of approximately 1 K in the Kalpana WV radiances compared to radiances simulated from the WRF model first-guess fields. The control (without Kalpana WV radiances) as well as experimental (which assimilated bias corrected Kalpana WV radiances) runs were made for 24 h starting at 0000 UTC during July 2008. The assimilation experiments for July 2008 (22 cases) demonstrated a positive impact of the assimilated Kalpana WV radiances on both the analysis state as well as subsequently short-term (6-24 h) forecasts. At 0 h (analysis), the agreement of mid-upper tropospheric moisture sensitive channels (channels 11 and 12) in NOAA/HIRS, which is an independent observation, is improved (improvement is 19% for channel 11 and 17% for channel 12) with the assimilation of Kalpana WV radiances compared to control experiment. In the radiance assimilation experiment, at 6 h (24 h), the root mean square differences between model equivalent Kalpana WV radiances and Kalpana observed WV radiances showed an improvement of 20% (1.7%) relative to the control experiment. Compared with National Center for Environmental Prediction analysis, assimilation of Kalpana WV radiances shows positive impact on the mid-upper tropospheric moisture and a neutral impact on the temperature and wind forecasts. Compared with atmospheric infrared sounder retrieved and radiosonde observed thermodynamic profiles, Kalpana radiances show positive impact on the mid-upper tropospheric moisture and temperature and a mixed (negative/positive) impact on the lower and upper tropospheric moisture and temperature forecasts. The comparison of model predicted rainfall with TRMM measurements indicates that Kalpana radiances impacted the rainfall positively. Copyright 2010 by the American Geophysical Union.

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