Abstract. This paper describes a new gas optical depth parameterisation implemented in the most recent release, version 13, of the radiative transfer model RTTOV (Radiative Transfer for TOVS). RTTOV is a fast, one-dimensional radiative transfer model for simulating top-of-atmosphere visible, infrared, and microwave radiances observed by downward-viewing space-borne passive sensors. A key component of the model is the fast parameterisation of absorption by the various gases in the atmosphere. The existing parameterisation in RTTOV has been extended over many years to allow for additional variable gases in RTTOV simulations and to account for solar radiation and better support geostationary sensors by extending the validity to higher zenith angles. However, there are limitations inherent in the current approach which make it difficult to develop it further, for example by adding new variable gases. We describe a new parameterisation that can be applied across the whole spectrum, that allows for a wide range of zenith angles in support of solar radiation and geostationary sensors, and for which it will be easier to add new variable gases in support of user requirements. Comparisons against line-by-line radiative transfer simulations and against observations in the ECMWF operational system yield promising results, suggesting that the new parameterisation generally compares well with the old one in terms of accuracy. Further validation is planned, including testing in operational numerical weather prediction data assimilation systems.
The Global Positioning System (GPS) Radio Occultation (RO) technique allows valuable information to be obtained about the state of the atmosphere through vertical profiles obtained at various processing levels. From the point of view of data assimilation, there is a consensus that less processed data are preferable because of their lowest addition of uncertainties in the process. In the GPSRO context, bending angle data are better to assimilate than refractivity or atmospheric profiles; however, these data have not been properly explored by data assimilation at the CPTEC (acronym in Portuguese for Center for Weather Forecast and Climate Studies). In this study, the benefits and possible deficiencies of the CPTEC modeling system for this data source are investigated. Three numerical experiments were conducted, assimilating bending angles and refractivity profiles in the Gridpoint Statistical Interpolation (GSI) system coupled with the Brazilian Global Atmospheric Model (BAM). The results highlighted the need for further studies to explore the representation of meteorological systems at the higher levels of the BAM model. Nevertheless, more benefits were achieved using bending angle data compared with the results obtained assimilating refractivity profiles. The highest gain was in the data usage exploring 73.4% of the potential of the RO technique when bending angles are assimilated. Additionally, gains of 3.5% and 2.5% were found in the root mean square error values in the zonal and meridional wind components and geopotencial height at 250 hPa, respectively.
The Center for Weather Forecast and Climate Studies [Centro de Previsão e Tempo e Estudos Climáticos (CPTEC)] at the Brazilian National Institute for Space Research [Instituto Nacional de Pesquisas Espaciais (INPE)] has recently operationally implemented a three-dimensional variational data assimilation (3DVAR) scheme based on the Gridpoint Statistical Interpolation analysis system (GSI). Implementation of the GSI system within the atmospheric global circulation model from CPTEC/INPE (AGCM-CPTEC/INPE) is hereafter referred to as the Global 3DVAR (G3DVAR) system. The results of an observing system experiment (OSE) measuring the impacts of radiosonde, satellite radiance, and GPS radio occultation (RO) data on the new G3DVAR system are presented here. The observational impact of each of these platforms was evaluated by measuring the degradation of the geopotential height anomaly correlation and the amplification of the RMSE of the wind. Losing the radiosonde, GPS RO, and satellite radiance data in the OSE resulted in negative impacts on the geopotential height anomaly correlations globally. Nevertheless, the strongest impacts were found over the Southern Hemisphere and South America when satellite radiance data were withheld from the data assimilation system.
Abstract. This paper describes a new gas optical depth parameterisation implemented in the most recent release, version 13, of the radiative transfer model RTTOV (Radiative Transfer for TOVS). RTTOV is a fast, one-dimensional radiative transfer model for simulating top-of-atmosphere visible, infrared and microwave radiances observed by downward-viewing space-borne passive sensors. A key component of the model is the fast parameterisation of absorption by the various gases in the atmosphere. The existing parameterisation in RTTOV has been extended over many years to allow for additional variable gases in RTTOV simulations and to account for solar radiation and better support geostationary sensors by extending the validity to higher zenith angles. However, there are limitations inherent in the current approach which make it difficult to develop it further, for example by adding new variable gases. We describe a new parameterisation that can be applied across the whole spectrum, allows for a wide range of zenith angles in support of solar radiation and geostationary sensors, and for which it will be easier to add new variable gases in support of user requirements. Comparisons against line-by-line radiative transfer simulations, and against observations in the ECMWF operational system yield promising results, suggesting that the new parameterisation generally compares well with the old one in terms of accuracy. Further validation is planned, including testing in operational numerical weather prediction data assimilation systems.
RESUMOAs medidas do AMSU-A para os canais que são sensíveis à superfície terrestre sobre os continentes não tem sido amplamente utilizadas para ajustar a previsão numérica de tempo de curto prazo (PNTs), devido à complexidade das características da superfície terrestre. Nesse sentido, o presente artigo utiliza o Sistema de Assimilação de Dados (G3DVAR) do Centro de Previsão de Tempo e Estudos Climáticos do Instituto Nacional de Pesquisas Espaciais (CPTEC/INPE), que inclui tais medidas de radiâncias feitas pelo sensor que está a bordo dos satélites da série NOAA. A versão operacional do sistema G3DVAR contempla apenas o satélite NOAA-15. Adicionalmente, foram realizados experimentos numéricos que incluíram os satélites NOAA-18 e NOAA-19. É feita uma avaliação sobre a variável temperatura de brilho simulada para os canais sensíveis à superfície terrestre (i), através de uma comparação com observações, e (ii) através da avaliação da equação de transferência radiativa, para os três satélites. Os resultados indicaram que o modelo de transferência radiativa em média superestima a temperatura de brilho nos canais sensíveis à superfície terrestre para os três satélites na região da América do Sul para os meses de verão. Além disso, as observações dos satélites incorporadas no sistema tiveram um aceite superior ao do satélite NOAA-15, de maneira que os satélites NOAA-18 e NOAA-19 podem ser incorporados no modo operacional do Sistema G3DVAR. Palavras-chave: Assimilação de dados, radiância, observação, simulação, AMSU-A, NOAA. ABSTRACT: EVALUATION OF THE WINDOWS CHANNEL BRIGHTNESS TEMPERATURE IN G3DVAR SYSTEM OF CPTEC/INPE: SERIE NOAAChannels sensitive to the terrestrial surface have not been widely used in Numerical Weather Prediction (NWP) due to the inherent complexities of the land surface. Thus, the present paper tested the tridimensional variational data assimilation framework implemented in the Global Model (G3DVAR) at the Center for Weather Forecast and Climate Studies (CPTEC) from the National Institute for Space Research (INPE) with near surface radiances from the NOAA-15 satellite. Since the operational version of the G3DVAR uses only NOAA-15, other experiments including the NOAA-18 and NOAA-19 satellites were performed. An assessment of the simulated brightness temperature for the near surface channels was made (i) through a comparison against observations and (ii) through a validation of the radiative transfer equation for the three satellites. The results indicate that the radiative transfer model overestimate, on average, the brightness temperature from the channels sensitive to the earth surface for all the considered satellites over South America during the austral summer. Furthermore, the number of observations accepted by the assimilation system increased substantially when NOAA-18 and NOAA-19 satellites were included, suggesting that incorporating these two new satellites should bring a positive impact to the G3DVAR operational system at CPTEC/INPE.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.