Improvement of precipitable water vapour and water vapour mixing ratio profile in atmospheric infrared sounder retrievals: differential linear adjustment model

Chang, Liang; Li, Yanxing; Han, Zhen; Feng, Gao; Li, Yangdong; Zhang, Yang

doi:10.1080/01431161.2020.1750736

Cited by 6 publications

(8 citation statements)

References 19 publications

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“…Modeling climate and weather on regional and global scales requires accurate monitoring of atmospheric parameters such as air temperature, wind speed, and water vapor content in the air (Sobrino et al, 2015). Water vapor plays a critical role in governing the terrestrial atmospheric processes (Sherwood et al, 2010;Jiang et al, 2019;Chang et al, 2020). It can be considered the most important greenhouse gas, influencing the planetary radiative budget and therefore the climate balance (Held & Soden, 2000;Filioglou et al, 2017;Chang et al, 2020;De Rosa et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Water vapor plays a critical role in governing the terrestrial atmospheric processes (Sherwood et al, 2010;Jiang et al, 2019;Chang et al, 2020). It can be considered the most important greenhouse gas, influencing the planetary radiative budget and therefore the climate balance (Held & Soden, 2000;Filioglou et al, 2017;Chang et al, 2020;De Rosa et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Notably, the continuous and accurate monitoring of the vertical structure of atmospheric parameters on global and regional scales is a key issue for assessing climate change (Sobrino et al, 2015;Chang et al, 2020;Rao et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Besides all of the above weather and climate related issues, the accurate description of the vertical water vapor and temperature variability is also required to Numerical Weather Prediction (NWP) and to improve the mesoscale models for any meteorological research (Turner et al, 2000;Chang et al, 2020;Zhao et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, radiosondes are quite expensive and have poor coverage over oceans and in the southern hemisphere (Li et al, 2003;Xu et al, 2015;Chang et al, 2020;De Rosa et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Using the WRF Model to Refine NCEP CFSv2 Reanalysis Atmospheric Profile: A Southern Brazil Test Case

et al. 2020

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ABSTRACT. The vertical distribution of atmospheric parameters is pivotal to understand atmospheric dynamic processes. This study analyzes the use of the Weather Research and Forecasting (WRF) model to generate atmospheric profiles as an alternative for a local radiosonde. We performed simulations in the WRF model for two dates with distinct weather conditions (01/09/2018 – cloudy and 03/14/2018 – clear-sky). The simulated data were compared with radiosondes launched in the study area, both (i) along the entire profile and (ii) with focus on the Planetary Boundary Layer (PBL) – for the variables water vapor mixing ratio (q), potential temperature (θ) and wind speed (Speed). The results showed a high correlation between the simulated and observed profiles, with most R values higher than 0.9. Bias and RMSE, respectively, ranged between -1.29 – 0.66 g/kg and 0.48 – 2.01 g/kg for q; -0.52 – 0.25 K and 0.44 – 3.00 K for θ; and -0.20 – 1.31 m/s and 1.61 – 2.77 m/s for Speed. The difference between the profiles from different WRF nested grids was minimal, suggesting that a resolution of approximately 12 km is enough to a good trade-off between detailing and computational cost. WRF model seems suitable to simulate fine atmospheric profiles. Keywords: vertical profiles, numerical weather prediction, meteorology, remote sensing, planetary boundary layer. Uso do Modelo WRF para refinar perfis atmosféricos de reanálise NCEP CFSv2: um estudo de caso no Sul do BrasilRESUMO. A distribuição vertical dos parâmetros atmosféricos é fundamental para entender os processos dinâmicos da atmosfera. Este estudo analisa o uso do modelo Weather Research and Forecasting (WRF) na geração de perfis atmosféricos, como uma alternativa à radiossondagens locais. Foram realizadas simulações com o WRF para duas datas em condições de tempo distintas (09/01/2018 – alta nebulosidade e 14/03/2018 – céu claro). Os dados simulados foram comparados com radiossondagens lançadas na área de estudo, (i) ao longo de todo o perfil e (ii) com foco na camada limite planetária (PBL) – para as variáveis razão de mistura do vapor de água (q), temperatura potencial (θ) e velocidade do vento (Speed). Os resultados mostraram uma alta correlação entre os perfis simulados e observados, com a maioria dos valores de R superiores a 0,9. Viés e RMSE, respectivamente, variaram entre -1,29 – 0,66 g/kg e 0,48 – 2,01 g/kg para q; -0,52 – 0,25 K e 0,44 – 3,00 K para θ; e -0,20 – 1,31 m/s e 1,61 – 2,77 m/s para Speed. Mínimas diferenças entre os perfis das diferentes grades aninhadas sugerem que uma resolução horizontal de aproximadamente 12 km é um bom balanço entre detalhamento e custo computacional. O WRF mostrou potencial na simulação de perfis atmosféricos refinados. Palavras-chave: perfis verticais, previsão numérica do tempo, meteorologia, sensoriamento remoto, camada limite planetária.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Moreover, radiosondes are quite expensive and have poor coverage over oceans and in the southern hemisphere (Li et al, 2003;Xu et al, 2015;Chang et al, 2020;De Rosa et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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