HR: 1400h
AN: IN33A-22 [Abstracts]
TI: Improving weather modeling in South America through IDD-Brasil
AU: * Chagas, G O
EM: goc@ufrj.br
AF: Universidade Federal do Rio de Janeiro, Cidade Universitária, Ilha do Fundão, Rio de
Janeiro, RJ 21949-900, Brazil
AB:
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.
DE: 0545 Modeling (4255)
DE: 0550 Model verification and validation
DE: 0840 Evaluation and assessment
DE: 3315 Data assimilation
SC: Earth and Space Science Informatics [IN]
MN: 2007 Joint Assembly