Copyright 2008 Elsevier B.V., All rights reserved.The Fifth Generation Mesoscale Model (MM5) is used to study the effect of assimilated satellite and conventional data on the prediction of three monsoon depressions over India using analysis nudging. The satellite data comprised the vertical profiles of temperature and humidity (NOAA-TOVS: - National Oceanic and Atmospheric Administration-TIROS Operational Vertical Sounder; MODIS: - MODerate resolution Imaging Spectroradiometer) and the surface wind vector over the sea (QuikSCAT: - Quick Scatterometer); the conventional meteorological data included the upper-air and surface data from the India Meteorological Department (IMD). Two sets of numerical experiments are performed for each case: the first set, NOFDDA (no nudging), utilizes NCEP reanalysis (for the initial conditions and lateral boundary conditions) in the simulation, the second set, FDDA, employs the satellite and conventional meteorological data for an improved analysis through analysis nudging. Two additional experiments are performed to study the effect of increased vertical and horizontal resolution as well as convective parameterization for one of the depressions for which special fields observations were available. The results from the simulation are compared with each other and with the analysis and observations. The results show that the predicted sea level pressure (SLP), the lower tropospheric cyclonic circulation, and the precipitation of the FDDA simulation reproduced the large-scale structure of the depression as manifested in the NCEP reanalysis. The simulation of SLP using no assimilation high-resolution runs (HRSKF10KM, HRSKF3.3KM) with the Kain-Fritsch cumulus parameterization scheme appeared poor in comparison with the FDDA run, while the no assimilation high-resolution runs (HRSGR10KM, HRSGR3.3KM) with the Grell cumulus scheme provided better results. However, the space correlation and the root mean square (rms) error of SLP for the HRSKF10KM was better than the FDDA; the largest and smallest space correlation for HRSKF10KM, FDDA, and HRSGR10KM were 0.894 and 0.623, 0.663 and 0.195, and 0.733 and 0.338 respectively; the smallest and largest rms error for HRSKF10KM, FDDA and HRSGR10KM were 1.879 and 5.245, 2.308 and 4.242, and 2.055 and 4.909 respectively. The precipitation simulations with the 3.3 km high-resolution, no assimilation runs performed no better than the precipitation simulation with the FDDA run. Thus, a significant finding of this study is that over the Indian monsoon region, the improvements in the simulation using nudging in the FDDA run are of similar magnitude (or better) than the improvements in the simulation due to high-resolution and to cumulus parameterization sensitivity. The improvements in the FDDA run due to analysis nudging were also verified in two more depression cases. The current operational regional models in India do not incorporate the data assimilation of NOAA-TOVS/MODIS and QuikSCAT satellite data, and hence the results of this study are relevant to ...
This study explores the role played by ocean processes in influencing Indian summer monsoon rainfall (ISMR) and compares the observed findings with National Centers for Environmental Prediction (NCEP)-coupled model Climate Forecast System, version 2 (CFSv2). The excess and deficit ISMR clearly brings out the distinct signatures in sea surface height (SSH) anomaly, thermocline and mixed layer depth over north Indian Ocean. CFSv2 is successful in simulating SSH anomalies, especially over Arabian Sea and Bay of Bengal region. CFSv2 captures observed findings of SSH anomalies during flood and drought (e.g., Rossby wave propagation which reaches western Bay of Bengal (BoB) during flood years, Rossby wave propagation which did not reach western BoB during drought). It highlights the ability of CFSv2 to simulate the basic ocean processes which governs the SSH variability. These differences are basically generated by upwelling and downwelling caused by the equatorial and coastal Kelvin and Rossby waves, thereby causing difference in SSH anomaly and thermocline, and subsequently modifying the convection centers, which dictates precipitation over the Indian subcontinent region. Since the observed SSH anomaly and thermal structure show distinct characteristic features with respect to strong and weak ISMR variability, the assimilation of real ocean data in terms of satellite products (like SSHA from AVISO/SARAL) bestow great promise for the future improvement.
Seasonal variation of the hydrography along the southeast Arabian Sea is described using data collected onboard FORV Sagar Sampada in September--October 2003 (later phase of Southwest monsoon, SWM) and March--April 2004 (Spring inter monsoon, SIM). During the later phase of the SWM, upwelling was in the withdrawal phase and the frontal structure was clearer in the northern sections (13 and 15 degrees N lat) indicating strong upwelling in the area. The driving force of upwelling is identified as the combination of alongshore wind stress and remote forcing with a latitudinal variability. Although a more prominent upwelling was found in the north, a maximum surface Chlorophyll-a was found in the south (10 degrees N). During the SIM, the area was characterized by oligotrophic water with relatively high Sea Surface Temperature (>29 degrees C) and low salinity (33.8 to 35.4). During March, the surface hydrography was found to be controlled mainly by the intrusion of low-saline waters from the south, while during September by the high saline water from the north. The presence of various water masses [Arabian Sea High Salinity Water (ASHSW), Persian Gulf Water (PGW), Red Sea Water (RSW)] and their seasonal variations in the region is discussed and their decreasing influence towards the south is noted during both periods of observation. During the SWM, the dynamic topography showed the equator-ward flow of the West India Coastal Current (WICC) at the surface and a pole-ward coastal under current at sub-thermocline depth. During the SIM, surface circulation revealed the WICC flowing pole-ward north of 13 degrees N, but equator-ward flow in the south, with a clockwise circulation around the Lakshadweep High.
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