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Proceedings Paper

Improvements in simulation of atmospheric boundary layer parameters through data assimilation in ARPS mesoscale atmospheric model
Author(s): D. Bala Subrahamanyam; Radhika Ramachandran; P. K. Kunhikrishnan
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Paper Abstract

In a broad sense, 'Data Assimilation' refers to a technique, whereby the realistic observational datasets are injected to a model simulation for bringing accurate forecasts. There are several schemes available for insertion of observational datasets in the model. In this piece of research, we present one of the simplest, yet powerful data assimilation techniques - known as nudging through optimal interpolation in the ARPS (Advanced Regional Prediction System) model. Through this technique, we firstly identify the assimilation window in space and time over which the observational datasets need to be inserted and the model products require to be adjusted. Appropriate model variables are then adjusted for the realistic observational datasets with a proper weightage being given to the observations. Incorporation of such a subroutine in the model that takes care of the assimilation in the model provides a powerful tool for improving the forecast parameters. Such a technique can be very useful in cases, where observational datasets are available at regular intervals. In this article, we demonstrate the effectiveness of this technique for simulation of profiles of Atmospheric Boundary Layer parameters for a tiny island of Kaashidhoo in the Republic of Maldives, where regular GPS Loran Atmospheric Soundings were carried out during the Intensive Field Phase of Indian Ocean Experiment (INDOEX, IFP-99).

Paper Details

Date Published: 12 December 2006
PDF: 10 pages
Proc. SPIE 6404, Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions, 64040K (12 December 2006); doi: 10.1117/12.694106
Show Author Affiliations
D. Bala Subrahamanyam, Vikram Sarabhai Space Ctr. (India)
Radhika Ramachandran, DOS (India)
P. K. Kunhikrishnan, Vikram Sarabhai Space Ctr. (India)

Published in SPIE Proceedings Vol. 6404:
Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions
Tiruvalam N. Krishnamurti; B. N. Goswami; Toshiki Iwasaki, Editor(s)

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