scholarly journals An Improved Parameterization for Retrieving Clear-Sky Downward Longwave Radiation from Satellite Thermal Infrared Data

2019 ◽  
Vol 11 (4) ◽  
pp. 425
Author(s):  
Shanshan Yu ◽  
Xiaozhou Xin ◽  
Qinhuo Liu ◽  
Hailong Zhang ◽  
Li Li

Surface downward longwave radiation (DLR) is a crucial component in Earth’s surface energy balance. Yu et al. (2013) developed a parameterization for retrieving clear-sky DLR at high spatial resolution by combined use of satellite thermal infrared (TIR) data and column integrated water vapor (IWV). We extended the Yu2013 parameterization to Moderate Resolution Imaging Spectroradiometer (MODIS) data based on atmospheric radiative simulation, and we modified the parameterization to decrease the systematic negative biases at large IWVs. The new parameterization improved DLR accuracy by 1.9 to 3.1 W/m2 for IWV ≥3 cm compared to the Yu2013 algorithm. We also compared the new parameterization with four algorithms, including two based on Top-of-Atmosphere (TOA) radiance and two using near-surface meteorological parameters and water vapor. The algorithms were first evaluated using simulated data and then applied to MODIS data and validated using surface measurements at 14 stations around the globe. The results suggest that the new parameterization outperforms the TOA-radiance based algorithms in the regions where ground temperature is substantially different (enough that the difference between them is as large as 20 K) from skin air temperature. The parameterization also works well at high elevations where atmospheric parameter-based algorithms often have large biases. Furthermore, comparing different sources of atmospheric input data, we found that using the parameters interpolated from atmospheric reanalysis data improved the DLR estimation by 7.8 W/m2 for the new parameterization and 19.1 W/m2 for other algorithms at high-altitude sites, as compared to MODIS atmospheric products.

2021 ◽  
pp. 1-56
Author(s):  
Shusaku Sugimoto ◽  
Bo Qiu ◽  
Niklas Schneider

AbstractThe Kanto district, Japan, including Tokyo, has 40 million inhabitants and its summer climate is characterized by high temperature and humidity. The Kuroshio that flows off the southern coast of Kanto district has taken a large meander (LM) path since the summer of 2017 for the first time since the 2004–2005 event. Recently-developed satellite observations detected marked coastal warming off the Kanto-Tokai district during the LM path period. By conducting regional atmospheric model experiments, it is found that summertime coastal warming increases water vapor in the low-level atmosphere through enhanced evaporation from the ocean and influences near-surface winds via the vertical mixing effect over the warming area. These two changes induce an increase in water vapor in Kanto district, leading to an increase in downward longwave radiation at the surface and then surface warming through a local greenhouse effect. Resultantly the summer in Kanto district becomes increasingly hot and humid in LM years, with double the number of discomfort days compared with non-LM years. Our simulations and supplementary observational studies reveal the significant impacts of the LM-induced coastal warming on the summertime climate in Japan, which can exceed previously identified atmospheric teleconnections and climate patterns. Our results could improve weather and seasonal climate forecasts in this region.


2019 ◽  
Vol 77 (1) ◽  
pp. 199-216 ◽  
Author(s):  
Joseph P. Clark ◽  
Steven B. Feldstein

Abstract Radiative transfer calculations are conducted to determine the contribution of temperature and water vapor anomalies toward the surface clear-sky downward longwave radiation (DLR) anomalies of the NAO. These calculations are motivated by the finding that the NAO’s skin temperature anomalies are driven primarily by changes in surface DLR. The clear-sky radiative transfer calculations follow the result that the clear-sky surface DLR anomalies can account for most of the all-sky surface DLR anomalies of the NAO. The results of the radiative transfer calculations prompt an analysis of the thermodynamic energy and total column water (TCW) budget equations, as water vapor and temperature anomalies are found to be equally important drivers of the surface DLR anomalies of the NAO. Composite analysis of the thermodynamic energy equation reveals that the temperature anomalies of the NAO are wind driven: the advection of climatological temperature by the anomalous wind drives the NAO’s temperature anomalies at all levels except for those in the upper troposphere–lower stratosphere where the advection of anomalous temperature by the climatological wind becomes dominant. A similar analysis of the TCW budget reveals that changes in TCW are driven by water flux convergence. In addition to determining the drivers of the temperature and TCW anomalies, the thermodynamic energy and water budget analyses reveal that the decay of the temperature anomalies occurs primarily through vertical mixing, and that of the water anomalies mostly by evaporation minus precipitation.


2014 ◽  
Vol 9 (11) ◽  
pp. 114015 ◽  
Author(s):  
Yonghua Chen ◽  
Catherine M Naud ◽  
Imtiaz Rangwala ◽  
Christopher C Landry ◽  
James R Miller

2014 ◽  
Vol 27 (19) ◽  
pp. 7250-7269 ◽  
Author(s):  
Neil P. Barton ◽  
Stephen A. Klein ◽  
James S. Boyle

Abstract Previous research has found that global climate models (GCMs) usually simulate greater lower tropospheric stabilities compared to reanalysis data. To understand the origins of this bias, the authors examine hindcast simulations initialized with reanalysis data of six GCMs and find that four of the six models simulate within five days a positive bias in Arctic lower tropospheric stability during the Arctic polar night over sea ice regions. These biases in lower tropospheric stability are mainly due to cold biases in surface temperature, as very small potential temperature biases exist aloft. Similar to previous research, polar night surface temperature biases in the hindcast runs relate to all-sky downwelling longwave radiation in the models, which very much relates to the cloud liquid water. Also found herein are clear-sky longwave radiation biases and a fairly large clear-sky longwave radiation bias in the day one hindcast. This clear-sky longwave bias is analyzed by running the same radiation transfer model for each model’s temperature and moisture profile, and the model spread in clear-sky downwelling longwave radiation with the same radiative transfer model is found to be much less, suggesting that model differences other than temperature and moisture are aiding in the spread in downwelling longwave radiation. The six models were also analyzed in Atmospheric Model Intercomparison Project (AMIP) mode to determine if hindcast simulations are analogous to free-running simulations. Similar winter lower tropospheric stability biases occur in four of the six models with surface temperature biases relating to the winter lower tropospheric stability values.


2021 ◽  
Author(s):  
Lirong Ding ◽  
Zhiyong Long ◽  
Ji Zhou ◽  
Shaofei Wang ◽  
Xiaodong Zhang

<p>The downward longwave radiation (DLR) is a critical parameter for radiation balance, energy budget, and water cycle studies at regional and global scales. The accurate estimation of the all-weather DLR with a high temporal resolution is important for the estimation of the surface net radiation and evapotranspiration. However, the most DLR products involve instantaneous DLR estimates based on polar orbiting satellite data under clear-sky conditions. To obtain an in-depth understanding of the performances of different models in the estimation of the DLR over the Tibetan Plateau, which is a focus area of climate change study, this study tested eight methods under clear-sky conditions and six methods under cloudy conditions based on ground-measured data. The results show that the Dilley and O’Brien model and the Lhomme model are most suitable under clear-sky conditions and cloudy conditions, respectively. For the Dilley and O’Brien model, the average root mean square error (RMSE) of the DLR under clear-sky conditions is approximately 22.5 W/m<sup>2</sup> at nine ground sites; for the Lhomme model, the average RMSE is approximately 23.2 W/m<sup>2</sup>. Based on the estimated cloud fraction and meteorological data provided by the China land surface data assimilation system (CLDAS), the hourly all-weather daytime DLR with 0.0625° over the Tibetan Plateau was estimated. The results show that the average RMSE of the estimated hourly all-weather DLR was approximately 26.4 W/m<sup>2</sup>. With the combined all-weather DLR model, the hourly all-weather daytime DLR dataset with a 0.0625° resolution from 2008 to 2016 over the Tibetan Plateau was generated. This dataset can better contribute to studies associated with the radiation balance and energy budget, water cycle, and climate change over the Tibetan Plateau.</p>


2011 ◽  
Vol 26 (3) ◽  
pp. 443-450 ◽  
Author(s):  
Carlos Antonio Costa dos Santos ◽  
Bernardo Barbosa da Silva ◽  
Tantravahi Venkata Ramana Rao ◽  
Prakki Satyamurty ◽  
Antonio Ocimar Manzi

The main objective of this paper is to assess the performance of nine downward longwave radiation equations for clear-sky condition and develop a locally adjusted equation using the observed vapor pressure and air temperature data. The radiation and atmospheric parameters were measured during the months of October 2005 to June 2006 at a micrometeorological tower installed at the experimental site in a banana orchard in the semiarid region of Northeast Brazil. The comparative statistics for the performance of the downward longwave radiation calculation models during daytime and nighttime compared to measured data have shown that the parameterizations with more physical foundations have the best results. The locally adjusted equation and Sugita and Brutsaert model developed in 1993 showed errors less than 1.0% in comparison with measured values. Downward longwave radiation is one of the most expensive and difficult component of the radiation budget to be monitored in micrometeorological studies. Hence, the locally adjusted equation can be used to estimate downward longwave energy, needed as input to some agricultural and hydrological models, in semi-arid regions of the Northeast Brazil, where this component is not monitored.


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