Improving weather modeling in South America through IDD-Brasil
Abstract
The IDD-Brasil constitutes of an international collaboration among Universidade Federal do Rio de Janeiro (LPM/UFRJ), Centro de Previsão de Tempo e Estudos Climáticos (CPTEC/INPE) and the Unidata Program Center (Unidata/UCAR), which connects several universities and research centers across the Americas in a network to share real-time hydro meteorological data. Using this network as a new path to deliver and acquire observational data, IDD-Brazil participants are capable of receiving observational data from GTS (Global Telecommunication System), locally ingested data from several automatic weather stations networks (mesonets) from INPE, the entire array of METAR and SYNOP observations, and several model outputs and satellite imagery. During recent years Numerical Models have been used constantly, especially in mesoscale research, but the lack of a dense observational network in South America leads to several constraints during the data assimilation and model validation. Since the IDD-Brasil offers an improved and simple method to have new datasets readily accessible, it has been used continuously as a new manner to distribute surface observations that are not currently available in GTS, such as several mesonets in Brazil that account for an increase in data density. Through the usage of data ingested in IDD-Brasil as guess fields it is possible to study how the assimilation in several global models frequently used as initial conditions for mesoscale simulations can be affected, since in certain areas in Brazil the density of data nearly doubles if compared to GTS. Therefore it is also possible to better validate the results generated in mesoscale simulations, in view of the fact that the network has an improved spatial distribution. It is expected that the increase of locally held numerical model output from South American institutions in IDD- Brasil leads to an increased awareness of the need to constantly validate these results with observational data, thus improving mesoscale research.
- Publication:
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AGU Spring Meeting Abstracts
- Pub Date:
- May 2007
- Bibcode:
- 2007AGUSMIN33A..22C
- Keywords:
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- 0545 Modeling (4255);
- 0550 Model verification and validation;
- 0840 Evaluation and assessment;
- 3315 Data assimilation