scholarly journals Exploring the Potential of Satellite Solar-Induced Fluorescence to Constrain Global Transpiration Estimates

2019 ◽  
Vol 11 (4) ◽  
pp. 413 ◽  
Author(s):  
Brianna Pagán ◽  
Wouter Maes ◽  
Pierre Gentine ◽  
Brecht Martens ◽  
Diego Miralles
Keyword(s):  
Eddy Covariance ◽  
Land Surface ◽  
Radiant Energy ◽  
Energy System ◽  
Plant Responses ◽  
Natural Ecosystem ◽  
Growing Seasons ◽  
Phenological Changes ◽  
Opening And Closing

The opening and closing of plant stomata regulates the global water, carbon and energy cycles. Biophysical feedbacks on climate are highly dependent on transpiration, which is mediated by vegetation phenology and plant responses to stress conditions. Here, we explore the potential of satellite observations of solar-induced chlorophyll fluorescence (SIF)—normalized by photosynthetically-active radiation (PAR)—to diagnose the ratio of transpiration to potential evaporation (‘transpiration efficiency’, τ). This potential is validated at 25 eddy-covariance sites from seven biomes worldwide. The skill of the state-of-the-art land surface models (LSMs) from the eartH2Observe project to estimate τ is also contrasted against eddy-covariance data. Despite its relatively coarse (0.5°) resolution, SIF/PAR estimates, based on data from the Global Ozone Monitoring Experiment 2 (GOME-2) and the Clouds and Earth’s Radiant Energy System (CERES), correlate to the in situ τ significantly (average inter-site correlation of 0.59), with higher correlations during growing seasons (0.64) compared to decaying periods (0.53). In addition, the skill to diagnose the variability of in situ τ demonstrated by all LSMs is on average lower, indicating the potential of SIF data to constrain the formulations of transpiration in global models via, e.g., data assimilation. Overall, SIF/PAR estimates successfully capture the effect of phenological changes and environmental stress on natural ecosystem transpiration, adequately reflecting the timing of this variability without complex parameterizations.

scholarly journals Estimation of the All-Wave All-Sky Land Surface Daily Net Radiation at Mid-Low Latitudes from MODIS Data Based on ERA5 Constraints

2021 ◽  
Vol 14 (1) ◽  
pp. 33
Author(s):  
Shaopeng Li ◽  
Bo Jiang ◽  
Jianghai Peng ◽  
Hui Liang ◽  
Jiakun Han ◽  
...  
Keyword(s):  
Satellite Data ◽  
Land Surface ◽  
Radiant Energy ◽  
Energy System ◽  
Sufficient Information ◽  
Net Radiation ◽  
Modis Data ◽  
Low Latitudes ◽  
Moderate Resolution Imaging Spectroradiometer

The surface all-wave net radiation (Rn) plays an important role in the energy and water cycles, and most studies of Rn estimations have been conducted using satellite data. As one of the most commonly used satellite data sets, Moderate Resolution Imaging Spectroradiometer (MODIS) data have not been widely used for radiation calculations at mid-low latitudes because of its very low revisit frequency. To improve the daily Rn estimation at mid-low latitudes with MODIS data, four models, including three models built with random forest (RF) and different temporal expansion models and one model built with the look-up-table (LUT) method, are used based on comprehensive in situ radiation measurements collected from 340 globally distributed sites, MODIS top-of-atmosphere (TOA) data, and the fifth generation of European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) data from 2000 to 2017. After validation against the in situ measurements, it was found that the RF model based on the constraint of the daily Rn from ERA5 (an RF-based model with ERA5) performed the best among the four proposed models, with an overall validated root-mean-square error (RMSE) of 21.83 Wm−2, R2 of 0.89, and a bias of 0.2 Wm−2. It also had the best accuracy compared to four existing products (Global LAnd Surface Satellite Data (GLASS), Clouds and the Earth’s Radiant Energy System Edition 4A (CERES4A), ERA5, and FLUXCOM_RS) across various land cover types and different elevation zones. Further analyses illustrated the effectiveness of the model by introducing the daily Rn from ERA5 into a “black box” RF-based model for Rn estimation at the daily scale, which is used as a physical constraint when the available satellite observations are too limited to provide sufficient information (i.e., when the overpass time is less than twice per day) or the sky is overcast. Overall, the newly-proposed RF-based model with ERA5 in this study shows satisfactory performance and has strong potential to be used for long-term accurate daily Rn global mapping at finer spatial resolutions (e.g., 1 km) at mid-low latitudes.

Hydrological functioning of irrigated maize crops in southwest France using Eddy Covariance measurements and a land surface model

2021 ◽  
Author(s):  
Oluwakemi Dare-Idowu ◽  
Lionel Jarlan ◽  
Aurore Brut ◽  
Valerie Le-Dantec ◽  
Vincent Rivalland ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Land Surface ◽  
Sap Flow ◽  
Heat Fluxes ◽  
Added Value ◽  
Surface Model ◽  
Data Set ◽  
Flow Measurements ◽  
Ground Heat Flux

<p>This study aims to analyze the main components of the energy and hydric budgets of irrigated maize in southwestern France. To this objective, the ISBA-A-gs (<span>Interactions between Soil, Biosphere, and Atmosphere) </span>is run over six maize growing seasons. As a preliminary step, the ability of the ISBA-A-gs model to predict the different terms of the energy and water budgets is assessed thanks to a large database of <em>in situ</em> measurements by comparing the single budget version of the model with the new Multiple Energy Balance version solving an energy budget separately for the soil and the vegetation. The <em>in situ</em> data set acquired at the Lamasquere site (43.48<sup>o</sup> N, 1.249<sup>o</sup> E) includes half-hourly measurements of sensible (H) and latent heat fluxes (LE) estimated by an Eddy Covariance system. Measurements also include net radiation (Rn), ground heat flux (G), plant transpiration with sap flow sensors, meteorological variables, and 15-days measurements of vegetation characteristics. The seasonal dynamics of the turbulent fluxes were properly reproduced by both configurations of the model with an R² ranging from 0.66 to 0.89, and a root mean square error lower than 48 W m<sup>-2</sup>. Statistical metrics showed that H was better predicted by MEB with R² of 0.80 in comparison to ISBA-Ags (0.73). However, the difference between the RMSE of ISBA-Ags and MEB during the well-developed stage of the plants for both H and LE does not exceed 8 W m<sup>-2</sup>. This implies that MEB only has a significant added value over ISBA-Ags when the soil and the canopy are not fully coupled, and over a heterogeneous field. Furthermore, this study made a comparison between the sap flow measurements and the transpiration simulated by ISBA-A-gs and MEB. A good dynamics was reproduced by ISBA-A-gs and MEB, although, MEB (R²= 0.91) provided a slightly more realistic estimation of the vegetation transpiration. Consequently, this study investigated the dynamics of the water budget during the growing maize seasons. Results indicated that drainage is almost null on the site, while the observed values of cumulative evapotranspiration that was higher than the water inputs are related to a shallow ground table that provides supplement water to the crop. This work provides insight into the modeling of water and energy exchanges over maize crops and opens perspectives for better water management of the crop in the future.</p>

Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition-4.0 Data Product

2018 ◽  
Vol 31 (2) ◽  
pp. 895-918 ◽  
Author(s):  
Norman G. Loeb ◽  
David R. Doelling ◽  
Hailan Wang ◽  
Wenying Su ◽  
Cathy Nguyen ◽  
...  
Keyword(s):  
Regional Differences ◽  
Radiant Energy ◽  
Energy System ◽  
Polar Regions ◽  
Marine Stratocumulus ◽  
Clear Sky ◽  
Data Product ◽  
Cloud Radiative Effect ◽  
Global Mean

The Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) top-of-atmosphere (TOA), Edition 4.0 (Ed4.0), data product is described. EBAF Ed4.0 is an update to EBAF Ed2.8, incorporating all of the Ed4.0 suite of CERES data product algorithm improvements and consistent input datasets throughout the record. A one-time adjustment to shortwave (SW) and longwave (LW) TOA fluxes is made to ensure that global mean net TOA flux for July 2005–June 2015 is consistent with the in situ value of 0.71 W m−2. While global mean all-sky TOA flux differences between Ed4.0 and Ed2.8 are within 0.5 W m−2, appreciable SW regional differences occur over marine stratocumulus and snow/sea ice regions. Marked regional differences in SW clear-sky TOA flux occur in polar regions and dust areas over ocean. Clear-sky LW TOA fluxes in EBAF Ed4.0 exceed Ed2.8 in regions of persistent high cloud cover. Owing to substantial differences in global mean clear-sky TOA fluxes, the net cloud radiative effect in EBAF Ed4.0 is −18 W m−2 compared to −21 W m−2 in EBAF Ed2.8. The overall uncertainty in 1° × 1° latitude–longitude regional monthly all-sky TOA flux is estimated to be 3 W m−2 [one standard deviation (1 σ)] for the Terra-only period and 2.5 W m−2 for the Terra– Aqua period both for SW and LW fluxes. The SW clear-sky regional monthly flux uncertainty is estimated to be 6 W m−2 for the Terra-only period and 5 W m−2 for the Terra– Aqua period. The LW clear-sky regional monthly flux uncertainty is 5 W m−2 for Terra only and 4.5 W m−2 for Terra– Aqua.

Validation of Clear-Sky Global LAnd Surface Satellite (GLASS) Longwave Radiation Product

2020 ◽  
Author(s):  
Qi Zeng ◽  
Jie Cheng ◽  
Feng Yang
Keyword(s):  
Land Surface ◽  
Water Cycle ◽  
Radiant Energy ◽  
Remote Sensing Data ◽  
Longwave Radiation ◽  
Energy System ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Clear Sky ◽  
Global Land

<p>Surface longwave (LW) radiation plays an important rolein global climatic change, which is consist of surface longwave upward radiation (LWUP), surface longwave downward radiation (LWDN) and surface longwave net radiation (LWNR). Numerous studies have been carried out to estimate LWUP or LWDN from remote sensing data, and several satellite LW radiation products have been released, such as the International Satellite Cloud Climatology Project‐Flux Data (ISCCP‐FD), the Global Energy and Water cycle Experiment‐Surface Radiation Budget (GEWEX‐SRB) and the Clouds and the Earth’s Radiant Energy System‐Gridded Radiative Fluxes and Clouds (CERES‐FSW). But these products share the common features of coarse spatial resolutions (100-280 km) and lower validation accuracy.</p><p>Under such circumstance, we developed the methods of estimating long-term high spatial resolution all sky  instantaneous LW radiation, and produced the corresponding products from MODIS data from 2000 through 2018 (Terra and Aqua), named as Global LAnd Surface Satellite (GLASS) Longwave Radiation product, which can be free freely downloaded from the website (http://glass.umd.edu/Download.html).</p><p>In this article, ground measurements collected from 141 sites in six independent networks (AmerciFlux, AsiaFlux, BSRN, CEOP, HiWATER-MUSOEXE and TIPEX-III) are used to evaluate the clear-sky GLASS LW radiation products at global scale. The bias and RMSE is -4.33 W/m<sup>2 </sup>and 18.15 W/m<sup>2 </sup>for LWUP, -3.77 W/m<sup>2 </sup>and 26.94 W/m<sup>2</sup> for LWDN, and 0.70 W/m<sup>2 </sup>and 26.70 W/m<sup>2</sup> for LWNR, respectively. Compared with validation results of the above mentioned three LW radiation products, the overall accuracy of GLASS LW radiation product is much better. We will continue to improve the retrieval algorithms and update the products accordingly.</p>

Multi-scale phenology from digital time-lapse camera to Sentinel-2 and MODIS over Australian pastures

2020 ◽  
Author(s):  
Yuxia Liu ◽  
Alfredo Huete ◽  
Qiaoyun Xie ◽  
Ha Nguyen
Keyword(s):  
Land Surface ◽  
Spatial Scales ◽  
Time Lapse ◽  
Atmospheric Effects ◽  
Natural Ecosystem ◽  
Modis Evi ◽  
Satellite Sensors ◽  
Digital Time ◽  
Sentinel 2

<p>As a natural ecosystem dominated by grasses, phenological studies of pastures have attracted increased attention for their important roles in global carbon cycling, ecosystem biodiversity, and public health. To better understand pasture phenology from in-situ to regional scales, accurate monitoring of pasture greenness variations across different scales is critical. As an alternative approach to labor-intensive field surveys, digital time-lapse cameras (termed phenocams) can provide diurnal and long-term vegetation greenness observation at in-situ scale with less impact from atmospheric effects. Even so, monitoring of phenology at regional to global scales only can be obtained by satellite remote sensing. The data from satellite sensors whether medium-resolution (i.e. Moderate Resolution Imaging Spectrodiometer, MODIS, 250 m) or fine spatial resolution (i.e. Sentinel-2 mission, 10 m) is widely used for vegetation phenology monitoring. However, achieving accurate pasture greenness dynamics using satellite data remains challenging due to limitations resulting from heterogeneity in Australian pastures.   </p><p>Combining phenocam, Sentinel-2 data and MODIS land surface products, this study aimed to (1) compare differences in temporal profiles of pasture greenness derived from ground-based phenocam and satellite sensors with fine- and medium-spatial resolutions, respectively; (2) assess the capacity of Sentinel-2 pixels for representing the phenocam footprint for monitoring greenness dynamics; and (3) evaluate the potential of improving greenness upscaling from phenocam to MODIS by masking non-grass areas via Sentinel-2 data.</p><p>A set of RGB phenocams was deployed over sites located over eastern Australian pastures. Green chromatic coordinate (GCC) was calculated from phenocam images. Six spatial footprints centered at phenocam sites were defined (i.e. 10 m, 30 m, 90 m, 250 m, 750 m and 1250 m), in which the Enhanced Vegetation Index (EVI) was calculated from Sentinel-2 and MODIS. The correlations between phenocam GCC and Sentinel-2 EVI were analyzed at single and multiple sites within the phenocam footprint (< 100 m) across all phenophases. Similarly, the correlations between GCC and EVI derived from Sentinel-2 and MODIS were analyzed for larger scales (> 100 m). Finally, we analyzed the relationships between GCC and MODIS EVI derived after applying a Sentinel-2 grass mask.</p><p>First, generally consistent temporal patterns of GCC and EVI were found at all spatial scales and phenophases, though there were differences at larger scales. Second, relationships between GCC and Sentinel-2 EVI within the phenocam footprint (< 100 m) kept nearly consistent regression trends and significant correlations whether from single or multiple sites, but decreasing at scales beyond 100 m. Third, correlations between GCC and MODIS EVI were similar to Sentinel-2 EVI at the same scales (< 100 m). However, at > 250 m scale, EVI derived from Sentinel-2 non-grass filtered data improved the correlation with GCC compared with EVI from all Sentinel-2 pixels and MODIS pixels. Our results indicate that Sentinel-2 can enable retrieval of grass pasture phenology in heterogeneous landscapes with higher accuracy compared with MODIS, and demonstrated the potential of Sentinel-2 data as a land cover filter to improve phenocam upscaling to MODIS.  </p>

scholarly journals QUANTIFYING THE CONTRIBUTIONS OF ENVIRONMENTAL PARAMETERS TO CERES SURFACE NET RADIATION ERROR IN CHINA

2018 ◽  
Vol XLII-3 ◽  
pp. 1339-1345
Author(s):  
X. Pan ◽  
Y. Yang ◽  
Y. Liu ◽  
X. Fan ◽  
L. Shan ◽  
...  
Keyword(s):  
Land Surface ◽  
Southern China ◽  
Radiant Energy ◽  
Environmental Parameters ◽  
High Sensitivity ◽  
Precipitable Water ◽  
Energy System ◽  
Net Radiation ◽  
Error Source ◽  
Error Sources

Error source analyses are critical for the satellite-retrieved surface net radiation (Rn) products. In this study, we evaluate the Rn error sources in the Clouds and the Earth’s Radiant Energy System (CERES) project at 43 sites from July in 2007 to December in 2007 in China. The results show that cloud fraction (CF), land surface temperature (LST), atmospheric temperature (AT) and algorithm error dominate the Rn error, with error contributions of ~-20, ~15, ~10 and ~10&amp;thinsp;W/m<sup>2</sup> (net shortwave (NSW)/longwave (NLW) radiation), respectively. For NSW, the dominant error source is algorithm error (more than 10&amp;thinsp;W/m<sup>2</sup>), particularly in spring and summer with abundant cloud. For NLW, due to the high sensitivity of algorithm and large LST/CF error, LST and CF are the largest error sources, especially in northern China. The AT influences the NLW error large in southern China because of the large AT error in there. The total precipitable water has weak influence on Rn error even with the high sensitivity of algorithm. In order to improve Rn quality, CF and LST (AT) error in northern (southern) China should be decreased.

How accurate are satellite-derived surface solar radiation products over tropical oceans?

2020 ◽  
Author(s):  
Wenjun Tang ◽  
Kun Yang ◽  
Jun Qin ◽  
Jun Li ◽  
Jiangang Ye
Keyword(s):  
Solar Radiation ◽  
Spatial Resolution ◽  
Radiant Energy ◽  
Energy System ◽  
Marine Ecology ◽  
Surface Solar Radiation ◽  
Tropical Oceans ◽  
In Situ Observations ◽  
Land Surfaces

AbstractSurface solar radiation (SSR) over the ocean is essential for studies of ocean-atmosphere interactions and marine ecology, and satellite remote sensing is a major way to obtain the SSR over ocean. A new high-resolution (10 km, 3 hour) SSR product has recently been developed, mainly based on the newly released cloud product of the International Satellite Cloud Climatology Project H-series (ISCCP-HXG), and is available for the period from 1983.7 to 2017.6. In this study, we compared this SSR product with in-situ observations from 70 buoy sites in the Global Tropical Moored Buoy Array (GTMBA), and also compared it with another well-known satellite-derived SSR product from the Clouds and the Earth’s Radiant Energy System (CERES, edition 4.1), which has a spatial resolution of approximately 100 km. The results show that the ISCCP-HXG SSR product is generally more accurate than the CERES SSR product for both ocean and land surfaces. We also found that the accuracy of both satellite-derived SSR products (ISCCP-HXG and CRERS) was higher over ocean than over land, and that the accuracy of ISCCP-HXG SSR improves significantly when the spatial resolution of the product is coarsened to >= 30 km.

scholarly journals Validation of Geolocation of Measurements of the Clouds and the Earth’s Radiant Energy System (CERES) Scanning Radiometers aboard Three Spacecraft

2009 ◽  
Vol 26 (11) ◽  
pp. 2379-2391 ◽  
Author(s):  
G. Louis Smith ◽  
Kory J. Priestley ◽  
Phillip C. Hess ◽  
Chris Currey ◽  
Peter Spence
Keyword(s):  
Solar Radiation ◽  
World Bank ◽  
Land Surface ◽  
Radiant Energy ◽  
Tropical Rainfall Measuring Mission ◽  
Energy System ◽  
Scientific Investigations ◽  
The World Bank ◽  
The Earth ◽  
The Cross

Abstract The Clouds and the Earth’s Radiant Energy System (CERES) instrument is a scanning radiometer for measuring Earth-emitted and -reflected solar radiation to understand Earth’s energy balance. One CERES instrument was placed into orbit aboard the Tropical Rainfall Measuring Mission (TRMM) in 1997; two were aboard the Terra spacecraft, launched in 1999; and two were aboard the Aqua spacecraft, launched in 2002. These measurements are used together with data from higher-resolution instruments to generate a number of data products. The nominal footprint size of the pixel at Earth’s surface is 16 km in the cross-scan direction and 23 km in the scan direction for the TRMM platform and 36 km in the cross-scan direction and 46 km in the scan direction for the Terra and Aqua platforms. It is required that the location on Earth of each pixel be known to 1–2 km to use the CERES data with the higher-resolution instruments on a pixel basis. A technique has been developed to validate the computed geolocation of the measurements by use of coastlines. Scenes are chosen in which the reflected solar radiation changes abruptly from the land surface to the darker ocean surface and the Earth-emitted radiation changes from the warm land to the cool ocean, or vice versa, so that scenes can be detected both day and night. The computed coastline location is then compared with the World Bank II map. The method has been applied to data from the three spacecraft and shows that the pixel geolocations are accurate to within 10% of the pixel size and that the geolocation is adequate for current scientific investigations.

scholarly journals Comparisons of Clear-Sky Outgoing Far-IR Flux Inferred from Satellite Observations and Computed from the Three Most Recent Reanalysis Products

2013 ◽  
Vol 26 (2) ◽  
pp. 478-494 ◽  
Author(s):  
Xiuhong Chen ◽  
Xianglei Huang ◽  
Norman G. Loeb ◽  
Heli Wei
Keyword(s):  
Land Surface ◽  
Radiant Energy ◽  
Longwave Radiation ◽  
Precipitable Water ◽  
Energy System ◽  
High Elevation ◽  
Radiation Budget ◽  
Distribution Models ◽  
Atmospheric Infrared Sounder ◽  
Clear Sky

Abstract The far-IR spectrum plays an important role in the earth’s radiation budget and remote sensing. The authors compare the near-global (80°S–80°N) outgoing clear-sky far-IR flux inferred from the collocated Atmospheric Infrared Sounder (AIRS) and Clouds and the Earth’s Radiant Energy System (CERES) observations in 2004 with the counterparts computed from reanalysis datasets subsampled along the same satellite trajectories. The three most recent reanalyses are examined: the ECMWF Interim Re-Analysis (ERA-Interim), NASA Modern-Era Retrospective Analysis for Research and Application (MERRA), and NOAA/NCEP Climate Forecast System Reanalysis (CFSR). Following a previous study by X. Huang et al., clear-sky spectral angular distribution models (ADMs) are developed for five of the CERES land surface scene types as well as for the extratropical oceans. The outgoing longwave radiation (OLR) directly estimated from the AIRS radiances using the authors’ algorithm agrees well with the OLR in the collocated CERES Single Satellite Footprint (SSF) dataset. The daytime difference is 0.96 ±2.02 W m−2, and the nighttime difference is 0.86 ±1.61 W m−2. To a large extent, the far-IR flux derived in this way agrees with those directly computed from three reanalyses. The near-global averaged differences between reanalyses and observations tend to be slightly positive (0.66%–1.15%) over 0–400 cm−1 and slightly negative (−0.89% to −0.44%) over 400–600 cm−1. For all three reanalyses, the spatial distributions of such differences show the largest discrepancies over the high-elevation areas during the daytime but not during the nighttime, suggesting discrepancies in the diurnal variation of such areas among different datasets. The composite differences with respect to temperature or precipitable water suggest large discrepancies for cold and humid scenes.

Evaluation of net shortwave radiation over China with a regional climate model

2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Monsoon Region ◽  
Clear Sky ◽  
Sky Conditions

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.

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