Climatology and trends of downward shortwave radiation over Brazil

2020 ◽  
pp. 105347
Author(s):  
Cristian Felipe Zuluaga ◽  
Alvaro Avila-Diaz ◽  
Flavio B. Justino ◽  
Aaron B. Wilson
Keyword(s):  
Shortwave Radiation ◽  
Downward Shortwave Radiation

A synergic study on estimating surface downward shortwave radiation from satellite data

2021 ◽  
Vol 264 ◽  
pp. 112639
Author(s):  
Dongdong Wang ◽  
Shunlin Liang ◽  
Ruohan Li ◽  
Aolin Jia
Keyword(s):  
Satellite Data ◽  
Shortwave Radiation ◽  
Downward Shortwave Radiation

scholarly journals Estimation of Surface Downward Shortwave Radiation over China from Himawari-8 AHI Data Based on Random Forest

2020 ◽  
Vol 12 (1) ◽  
pp. 181 ◽  
Author(s):  
Ning Hou ◽  
Xiaotong Zhang ◽  
Weiyu Zhang ◽  
Yu Wei ◽  
Kun Jia ◽  
...  
Keyword(s):  
Random Forest ◽  
Temporal Resolution ◽  
Great Influence ◽  
Radiant Energy ◽  
Shortwave Radiation ◽  
Mean Bias Error ◽  
Bias Error ◽  
Validation Data ◽  
Downward Shortwave Radiation ◽  
Comparison Results

Downward shortwave radiation (RS) drives many processes related to atmosphere–surface interactions and has great influence on the earth’s climate system. However, ground-measured RS is still insufficient to represent the land surface, so it is still critical to generate high accuracy and spatially continuous RS data. This study tries to apply the random forest (RF) method to estimate the RS from the Himawari-8 Advanced Himawari Imager (AHI) data from February to May 2016 with a two-km spatial resolution and a one-day temporal resolution. The ground-measured RS at 86 stations of the Climate Data Center of the Chinese Meteorological Administration (CDC/CMA) are collected to evaluate the estimated RS data from the RF method. The evaluation results indicate that the RF method is capable of estimating the RS well at both the daily and monthly time scales. For the daily time scale, the evaluation results based on validation data show an overall R value of 0.92, a root mean square error (RMSE) value of 35.38 (18.40%) Wm−2, and a mean bias error (MBE) value of 0.01 (0.01%) Wm−2. For the estimated monthly RS, the overall R was 0.99, the RMSE was 7.74 (4.09%) Wm−2, and the MBE was 0.03 (0.02%) Wm−2 at the selected stations. The comparison between the estimated RS data over China and the Clouds and Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) RS dataset was also conducted in this study. The comparison results indicate that the RS estimates from the RF method have comparable accuracy with the CERES-EBAF RS data over China but provide higher spatial and temporal resolution.

scholarly journals A New Set of MODIS Land Products (MCD18): Downward Shortwave Radiation and Photosynthetically Active Radiation

2020 ◽  
Vol 12 (1) ◽  
pp. 168 ◽  
Author(s):  
Dongdong Wang ◽  
Shunlin Liang ◽  
Yi Zhang ◽  
Xueyuan Gao ◽  
Meredith G. L. Brown ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Photosynthetically Active Radiation ◽  
Process Models ◽  
Surface Radiation ◽  
Shortwave Radiation ◽  
Glass Product ◽  
Ancillary Data ◽  
Diurnal Variability ◽  
Active Radiation ◽  
Downward Shortwave Radiation

Surface downward shortwave radiation (DSR) and photosynthetically active radiation (PAR), its visible component, are key parameters needed for many land process models and terrestrial applications. Most existing DSR and PAR products were developed for climate studies and therefore have coarse spatial resolutions, which cannot satisfy the requirements of many applications. This paper introduces a new global high-resolution product of DSR (MCD18A1) and PAR (MCD18A2) over land surfaces using the MODIS data. The current version is Collection 6.0 at the spatial resolution of 5 km and two temporal resolutions (instantaneous and three-hour). A look-up table (LUT) based retrieval approach was chosen as the main operational algorithm so as to generate the products from the MODIS top-of-atmosphere (TOA) reflectance and other ancillary data sets. The new MCD18 products are archived and distributed via NASA’s Land Processes Distributed Active Archive Center (LP DAAC). The products have been validated based on one year of ground radiation measurements at 33 Baseline Surface Radiation Network (BSRN) and 25 AmeriFlux stations. The instantaneous DSR has a bias of −15.4 W/m2 and root mean square error (RMSE) of 101.0 W/m2, while the instantaneous PAR has a bias of −0.6 W/m2 and RMSE of 45.7 W/m2. RMSE of daily DSR is 32.3 W/m2, and that of the daily PAR is 13.1 W/m2. The accuracy of the new MODIS daily DSR data is higher than the GLASS product and lower than the CERES product, while the latter incorporates additional geostationary data with better capturing DSR diurnal variability. MCD18 products are currently under reprocessing and the new version (Collection 6.1) will provide improved spatial resolution (1 km) and accuracy.

scholarly journals Estimating Surface Downward Shortwave Radiation over China Based on the Gradient Boosting Decision Tree Method

2018 ◽  
Vol 10 (2) ◽  
pp. 185 ◽  
Author(s):  
Lu Yang ◽  
Xiaotong Zhang ◽  
Shunlin Liang ◽  
Yunjun Yao ◽  
Kun Jia ◽  
...  
Keyword(s):  
Decision Tree ◽  
Shortwave Radiation ◽  
Gradient Boosting ◽  
Downward Shortwave Radiation ◽  
Decision Tree Method ◽  
Tree Method

scholarly journals Influence of Land Cover Change on Regional Water Cycles in Eastern Siberia

2013 ◽  
Vol 52 (2) ◽  
pp. 484-497 ◽  
Author(s):  
Ryuhei Yoshida ◽  
Masahiro Sawada ◽  
Takeshi Yamazaki ◽  
Takeshi Ohta ◽  
Tetsuya Hiyama
Keyword(s):  
Energy Flux ◽  
Land Surface ◽  
Water Surface ◽  
Water Cycle ◽  
Parameter Sensitivity ◽  
Shortwave Radiation ◽  
Downward Shortwave Radiation ◽  
Precipitation Response ◽  
Surface Expansion ◽  
Sensitivity Method

AbstractThis study evaluated the effect of recent eastern Siberian land surface changes, such as water surface expansion, on water-energy fluxes and precipitation and focused on land surface parameters using a three-dimensional atmospheric model [the Japan Meteorological Agency Nonhydrostatic model (JMA-NHM)]. Five parameters were set (viz., surface albedo, evaporative efficiency, roughness length, heat capacity, and thermal conductivity), and a response of evaporation and precipitation was evaluated. Increased precipitation corresponded to 75% of the increased evaporation on interparameter average, indicating strong land–atmosphere coupling. Water-energy flux and precipitation responses to water surface expansion were evaluated by two methods: JMA-NHM and the parameter sensitivity method. The latter method used a linear combination of parameter sensitivity on the fluxes and precipitation and parameter changes with land surface change. JMA-NHM demonstrated an increase in evaporation and precipitation and a decrease in downward shortwave radiation with low-level cloud increases. The parameter sensitivity method gave the same order as JMA-NHM in the estimation. This method has minimal calculation cost; thus, water-energy flux and precipitation response with further water surface expansion and decreases in forest area were simulated, producing various land surface data. The enhancement of the precipitation response to evaporation was weak for further water surface expansion in the largely expanded water surface area; however, the ratio increased dramatically for the small water surface expanding area, indicating intense water cycle enhancement at the beginning of water surface expansion. Although grassland formation from forest has minimal impact, if incoming downward shortwave radiation were to increase because of the disappearance of the forest shading effect and the water surface formed by permafrost melting, the water cycle would be enhanced intensely.

scholarly journals Analysis of the Radiation Fluxes over Complex Surfaces on the Tibetan Plateau

Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3084
Author(s):  
Chunxiao Wang ◽  
Yaoming Ma ◽  
Binbin Wang ◽  
Weiqiang Ma ◽  
Xuelong Chen ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Air Temperature ◽  
Surface Albedo ◽  
Longwave Radiation ◽  
Heat Fluxes ◽  
Shortwave Radiation ◽  
The Tibetan Plateau ◽  
Downward Shortwave Radiation ◽  
Downward Longwave Radiation

Analysis of long-term, ground-based observation data on the Tibetan Plateau help to enhance our understanding of land-atmosphere interactions and their influence on weather and climate in this region. In this paper, the daily, monthly, and annual averages of radiative fluxes, surface albedo, surface temperature, and air temperature were calculated for the period of 2006 to 2019 at six research stations on the Tibetan Plateau. The surface energy balance characteristics of these six stations, which include alpine meadow, alpine desert, and alpine steppe, were then compared. The downward shortwave radiation at stations BJ, QOMS, and NAMORS was found to decrease during the study period, due to increasing cloudiness. Meanwhile, the upward shortwave radiation and surface albedo at all stations were found to have decreased overall. Downward longwave radiation, upward longwave radiation, net radiation, surface temperature, and air temperature showed increasing trends on inter-annual time scales at most stations. Downward shortwave radiation was maximum in spring at BJ, QOMS, NADORS, and NAMORS, due to the influence of the summer monsoon. Upward shortwave radiation peaked in October and November due to the greater snow cover. BJ, QOMS, NADORS, and NAMORS showed strong sensible heat fluxes in the spring while MAWORS showed strong sensible heat fluxes in the summer. The monthly and diurnal variations of surface albedo at each station were “U” shaped. The diurnal variability of downward longwave radiation at each station was small, ranging from 220 to 295 W·m−2.The diurnal variation in surface temperature at each station slightly lagged behind changes in downward shortwave radiation, and the air temperature, in turn, slightly lagged behind the surface temperature.

scholarly journals Short-term forecasting of regional biospheric CO<sub>2</sub> fluxes in Europe using a light-use-efficiency model (VPRM, MPI-BGC version 1.2)

2020 ◽  
Vol 13 (9) ◽  
pp. 4091-4106
Author(s):  
Jinxuan Chen ◽  
Christoph Gerbig ◽  
Julia Marshall ◽  
Kai Uwe Totsche
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Vegetation Type ◽  
Weather Prediction ◽  
Shortwave Radiation ◽  
Light Use Efficiency ◽  
Co2 Fluxes ◽  
Downward Shortwave Radiation ◽  
Use Efficiency ◽  
Light Use Efficiency Model

Abstract. Forecasting atmospheric CO2 concentrations on synoptic timescales (∼ days) can benefit the planning of field campaigns by better predicting the location of important gradients. One aspect of this, accurately predicting the day-to-day variation in biospheric fluxes, poses a major challenge. This study aims to investigate the feasibility of using a diagnostic light-use-efficiency model, the Vegetation Photosynthesis Respiration Model (VPRM), to forecast biospheric CO2 fluxes on the timescale of a few days. As input, the VPRM model requires downward shortwave radiation, 2 m temperature, and enhanced vegetation index (EVI) and land surface water index (LSWI), both of which are calculated from MODIS reflectance measurements. Flux forecasts were performed by extrapolating the model input into the future, i.e., using downward shortwave radiation and temperature from a numerical weather prediction (NWP) model, as well as extrapolating the MODIS indices to calculate future biospheric CO2 fluxes with VPRM. A hindcast for biospheric CO2 fluxes in Europe in 2014 has been done and compared to eddy covariance flux measurements to assess the uncertainty from different aspects of the forecasting system. In total the range-normalized mean absolute error (normalized) of the 5 d flux forecast at daily timescales is 7.1 %, while the error for the model itself is 15.9 %. The largest forecast error source comes from the meteorological data, in which error from shortwave radiation contributes slightly more than the error from air temperature. The error contribution from all error sources is similar at each flux observation site and is not significantly dependent on vegetation type.

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