scholarly journals An efficient hybrid method for estimating clear-sky surface downward longwave radiation from MODIS data

2017 ◽  
Vol 122 (5) ◽  
pp. 2616-2630 ◽  
Author(s):  
Jie Cheng ◽  
Shunlin Liang ◽  
Wenhui Wang ◽  
Yamin Guo
Keyword(s):  
Hybrid Method ◽  
Longwave Radiation ◽  
Modis Data ◽  
Clear Sky ◽  
Downward Longwave Radiation

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
Keyword(s):  
Water Vapor ◽  
Simulated Data ◽  
Longwave Radiation ◽  
Thermal Infrared ◽  
Reanalysis Data ◽  
Atmospheric Parameter ◽  
Near Surface ◽  
Modis Data ◽  
Clear Sky ◽  
Downward Longwave Radiation

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.

Estimation of All-weather Downward Longwave Radiation over the Tibetan Plateau

2021 ◽  
Author(s):  
Lirong Ding ◽  
Zhiyong Long ◽  
Ji Zhou ◽  
Shaofei Wang ◽  
Xiaodong Zhang
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Energy Budget ◽  
Water Cycle ◽  
Longwave Radiation ◽  
Radiation Balance ◽  
The Tibetan Plateau ◽  
Clear Sky ◽  
Downward Longwave Radiation ◽  
Sky Conditions

<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>

scholarly journals Downward longwave radiation estimates for clear-sky conditions over northeast Brazil

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
Keyword(s):  
Arid Regions ◽  
Longwave Radiation ◽  
Radiation Budget ◽  
Semiarid Region ◽  
Northeast Brazil ◽  
Hydrological Models ◽  
Experimental Site ◽  
Clear Sky ◽  
Downward Longwave Radiation ◽  
Sky Conditions

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.

scholarly journals Estimation of clear-sky land surface longwave radiation from MODIS data products by merging multiple models

2012 ◽  
Vol 117 (D22) ◽  
pp. n/a-n/a ◽  
Author(s):  
Haoran Wu ◽  
Xiaotong Zhang ◽  
Shunlin Liang ◽  
Hua Yang ◽  
Gongqi Zhou
Keyword(s):  
Land Surface ◽  
Longwave Radiation ◽  
Multiple Models ◽  
Modis Data ◽  
Clear Sky ◽  
Data Products

scholarly journals A revisit of parametrization of summer downward longwave radiation over the Tibetan Plateau from high temporal resolution measurements

2019 ◽  
Author(s):  
Mengqi Liu ◽  
Xiangdong Zheng ◽  
Jinqiang Zhang ◽  
Xiangao Xia
Keyword(s):  
Tibetan Plateau ◽  
Temporal Resolution ◽  
Longwave Radiation ◽  
Surface Energy Budget ◽  
Coefficient Of Determination ◽  
Cloud Base ◽  
High Temporal Resolution ◽  
The Tibetan Plateau ◽  
Clear Sky ◽  
Downward Longwave Radiation

Abstract. The Tibetan Plateau (TP) is one of hot spots in the climate research due to its unique geographical location, high altitude, highly sensitive to climate change as well potential effects on climate in East Asia. Downward longwave radiation (DLR), as a key component in the surface energy budget, is of practical implications for many research fields. Several attempts have been made to measure hourly or daily DLR and then model it over the TP. This study uses 1-minute radiation and meteorological measurements at three stations over the TP to parameterize DLR during summer months. Three independent methods are used to discriminate clear-sky observations by making maximal use of collocated measurements of downward shortwave and longwave radiation as well as Lidar backscatter measurements with high temporal resolution. This guarantees a reliable separation of clear-sky and cloudy samples that favors for proper parameterizations of DLR under these two contrast conditions. Clear-sky and cloudy DLR models with original parameters are firstly assessed. These models are then locally calibrated based on 1-minute observations. DLR estimation is notably improved since specific conditions over the TP are accounted for by local calibration, which is indicated by smaller root mean square error (RMSE) and larger coefficient of determination (R2). The best local parametrization can estimate clear-sky DLR with RMSE of 3.8 W⸱m-2. Overestimation of clear-sky DLR by previous study is evident, likely due to potential residue cloud contamination on the clear-sky samples. Cloud base height under overcast conditions is shown to be intimately related to cloudy DLR parameterization, which is considered by this study in the locally calibrated parameterization over the TP for the first time.

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