Advanced search
Start date
Betweenand
(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Impact of including moisture perturbations on short-range ensemble forecasts

Full text
Author(s):
Bustamante, Josiane F. [1] ; Chou, Sin Chan [1]
Total Authors: 2
Affiliation:
[1] Natl Inst Space Res, Ctr Weather Predict & Climate Studies, BR-12630000 Cachoeira Paulista, SP - Brazil
Total Affiliations: 1
Document type: Journal article
Source: JOURNAL OF GEOPHYSICAL RESEARCH; v. 114, OCT 28 2009.
Web of Science Citations: 2
Abstract

We are developing a Short-Range Ensemble Prediction (SREP) system based on the Eta Model for use over South America. The Eta Model SREP system uses the CPTEC global model Ensemble Prediction System (EPS) forecasts as initial and lateral boundary conditions. The objectives of this work are to verify the impacts of including moisture perturbations in the global EPS on the SREP and to evaluate the forecast quality from the resulting SREP. We compare the SREP constructed with and without moisture perturbations. We chose four cases of South Atlantic Convergence Zone events that produced heavy rainfall for the tests and evaluation. The Eta Model was set with a horizontal resolution of 10 km and integrated for 6 days. The mean errors of the forecasts based on the two perturbation methodologies are similar, which indicates that including moisture did not increase the forecast error. Precipitation forecasts showed major improvement when moisture perturbation was included. The root mean square error (RMSE) of the SREP ensemble mean forecast from both initial condition perturbations is smaller than the RMSE of the control run. The constructed SREP system exhibits forecast RMSE growth rate larger than the ensemble forecast spread, on the other hand, this difference is reduced compared to the driver global model ensemble forecast system. (AU)

FAPESP's process: 04/09649-0 - Predictability study of heavy rainfall events in the Serra do Mar
Grantee:Chou Sin Chan
Support type: Research Projects - Thematic Grants