2020
DOI: 10.1002/qj.3816
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Using Megha‐Tropiques satellite data to constrain humidity in regional convective simulations: A northern Australian test case

Abstract: Convective initiation and growth are sensitive to atmospheric conditions, especially humidity, in ways that need to be understood and quantified. It is not clear, however, how well current observations and modelling systems can serve to test this understanding. We simulate multiple cases of convergent cloud lines observed during January 2016 over northeastern Australia using the Weather Research and Forecasting (WRF) model (version 3.7.1), initialized by and nudged to reanalysis data. Overall, WRF appears to s… Show more

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Cited by 3 publications
(2 citation statements)
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References 96 publications
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“…It is the world's most used mesoscale model and provides capabilities for a range of applications in terrestrial systems. The WRF model has been widely employed for estimating high-resolution meteorological data [28][29][30]. It is all-important to assess the reasonableness of using the WRF model to generate highresolution atmospheric profiles to perform, in conjunction with an RTM, more accurate AC/LST retrieval.…”
Section: Introductionmentioning
confidence: 99%
“…It is the world's most used mesoscale model and provides capabilities for a range of applications in terrestrial systems. The WRF model has been widely employed for estimating high-resolution meteorological data [28][29][30]. It is all-important to assess the reasonableness of using the WRF model to generate highresolution atmospheric profiles to perform, in conjunction with an RTM, more accurate AC/LST retrieval.…”
Section: Introductionmentioning
confidence: 99%
“…Differences in local atmospheric processes and topography are among the most significant factors affecting the efficiency of reanalysis (Schafer et al, 2003;Alghamdi, 2020). New weather prediction models enjoy better computing performance and parameterization of physical processes to improve the reanalysis forecast accuracy (Evans et al, 2012;Hassanli & Rahimzadegan, 2019;Prasad et al, 2020). As mentioned above, coarse resolution of global-scale data may not be suitable for local use.…”
Section: Introductionmentioning
confidence: 99%