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Atmosphere 2018, 9(4), 123; https://doi.org/10.3390/atmos9040123

Sensitivity of Numerical Weather Prediction to the Choice of Variable for Atmospheric Moisture Analysis into the Brazilian Global Model Data Assimilation System

1
National Institute for Space Research, Center for Weather Forecasting and Climate Research, Cachoeira Paulista, SP 12227-010, Brazil
2
Climatempo, São José dos Campos, SP 12247-016, Brazil
3
Instituto Tecnológico Vale, Belém, PA 66055-090, Brazil
*
Author to whom correspondence should be addressed.
Received: 9 February 2018 / Revised: 12 March 2018 / Accepted: 13 March 2018 / Published: 23 March 2018
(This article belongs to the Section Climatology and Meteorology)
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Abstract

Due to the high spatial and temporal variability of atmospheric water vapor associated with the deficient methodologies used in its quantification and the imperfect physics parameterizations incorporated in the models, there are significant uncertainties in characterizing the moisture field. The process responsible for incorporating the information provided by observation into the numerical weather prediction is denominated data assimilation. The best result in atmospheric moisture depend on the correct choice of the moisture control variable. Normalized relative humidity and pseudo-relative humidity are the variables usually used by the main weather prediction centers. The objective of this study is to assess the sensibility of the Center for Weather Forecast and Climate Studies to choose moisture control variable in the data assimilation scheme. Experiments using these variables are carried out. The results show that the pseudo-relative humidity improves the variables that depend on temperature values but damage the moisture field. The opposite results show when the simulation used the normalized relative humidity. These experiments suggest that the pseudo-relative humidity should be used in the cyclical process of data assimilation and the normalized relative humidity should be used in non-cyclic process (e.g., nowcasting application in high resolution). View Full-Text
Keywords: atmospheric water vapor; numerical weather prediction; variational data assimilation; moisture control variable; pseudo-relative humidity; normalized relative humidity atmospheric water vapor; numerical weather prediction; variational data assimilation; moisture control variable; pseudo-relative humidity; normalized relative humidity
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Campos, T.B.; Sapucci, L.F.; Lima, W.; Ferreira, D.S. Sensitivity of Numerical Weather Prediction to the Choice of Variable for Atmospheric Moisture Analysis into the Brazilian Global Model Data Assimilation System. Atmosphere 2018, 9, 123.

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