Sensitivity of Initial Conditions on Diurnal Variability of Indian Summer Monsoon

Autor: Pradip K. Pal, Sukanta Kumar Das, S. K. Deb, C. M. Kishtawal
Rok vydání: 2014
Předmět:
Zdroj: Pure and Applied Geophysics. 172:2777-2790
ISSN: 1420-9136
0033-4553
Popis: The diurnal cycle of different surface parameters, viz. surface air temperature, surface pressure, and rain intensities, simulated by the Community Atmosphere Model (CAM) in the operational seasonal forecast of ISM-2012 using initial conditions (ICs) taken at synoptic hours of the day has been examined and compared with observations. Four members were simulated with ICs at 0000, 0600, 1200, and 1800 UTC on 1 August 2012. The impact of the initial conditions at the synoptic hours of the day was more visible over the landmass compared with the oceanic regions. The diurnal variation of the surface temperature in the model simulation showed the major features when compared with the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis except for the warm pool of northwest India and the Tibetan region. The surface pressure in the ECMWF reanalysis showed the semidiurnal cycle with two peaks at 0600 UTC and 1800 UTC; however, the range of the cycle was underestimated by the model simulation, showing only one peak at 0600 UTC. Significant variations in the diurnal cycle of rain intensities were seen among the different members. The model captured the diurnal cycle as the positive and negative peaks at 1200 and 0000 UTC with intensities at the peaks ~0.5 mm high and low, respectively, in the model simulation when compared with the observations. Presently, the seasonal forecast of ISM is generated through ensemble CAM experiments using different ICs taken from different dates but all at 0000 UTC. Consideration of ICs at different times of the day will add different ranges of diurnal variations in all the surface parameters within the family of ensemble members and also increase the number of members in the family. Indeed, these improve the ensemble processes in generating the seasonal forecast of ISM.
Databáze: OpenAIRE
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