Journal
ATMOSPHERIC RESEARCH
Volume 270, Issue -, Pages -Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.atmosres.2022.106086
Keywords
Madeira River basin; Ensemble intra-seasonal prediction; Downscaling; Eta regional model; Bias correction
Categories
Funding
- Fundac ~ao de Amparo `a Pes-quisa do Estado do Amazonas (FAPEAM) [01.02.016301.00268/2021]
- FAPEAM
- CAPES [23038.019802/ 2018-07]
- CNPq [PQ 306.595/2013-3]
- [? 23038.019802/2018-07]
Ask authors/readers for more resources
This study used the Eta Regional Model for dynamic downscaling at a 30-day scale and found that the ensemble mean had good skill and reproduced the seasonal and spatial distribution of hydrological variables. Members using the Betts-Miller-Janjic relaxation technique performed the best.
Eta Regional Model of CPTEC-INPE is used to obtain intraseasonal (30-day) 8-member ensemble forecasts over the Madeira River basin for the period 2002-2012. The initial and boundary conditions are taken from Atmospheric General Circulation Global Model in six members and from Global Coupled Ocean-Atmosphere Model in two members. The intraseasonal forecasts produced by dynamic downscaling with Eta Regional model ensemble have satisfactory skill. The skill of the ensemble mean is better than the individual members up to 15-days lead time forecasts. The ensemble mean reproduces the seasonal cycle and spatial distribution of the hydrological variables. Members with the relaxation technique of Betts-Miller-Janjic produced better results. The forecasts by the members that used Kain-Fritsch scheme presented larger deviations from observations. Substantial improvements in skill are obtained through bias correction. This is the first work to attempt dynamic downscaling over the Madeira Basin in the intraseasonal time scale for a period of 10 years. The ensemble downscaled products have potential to be fed into surface hydrological models for forecasting droughts and floods and related hydrological variables over the basin.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available