Evaluation and intercomparison of multiple satellite-derived and reanalysis downward shortwave radiation products in China

Author(s):
Tong, Liu; He, Tao; Ma, Yichuan; Zhang, Xiaotong
Publication title: International Journal of Digital Earth
2023
 | Volume: 16 | Issue: 1
2023
DOI: 10.1080/17538947.2023.2212918
Abstract:
Downward shortwave radiation (DSR) is a critical variable in energy balance driving Earth’s surface processes. Satellite-derived and reanalysis DSR pr… Downward shortwave radiation (DSR) is a critical variable in energy balance driving Earth’s surface processes. Satellite-derived and reanalysis DSR products have been developed and continuously improved during the last decades. However, as those products have different temporal resolutions, their performances in different time scales have not been well-documented, particularly in China. This study intended to evaluate several DSR products across multiple time scales (i.e. instantaneous, 1-hourly, daily, and monthly average) and ecosystems in China. Six DSR products, including GLASS, BESS, CLARA-A2, MCD18A1, ERA5 and MERRA-2, were evaluated against ground measurements at Chinese Ecosystem Research Network (CERN) and integrated land-atmosphere interaction observation (TPDC) sites from 2009 to 2012. The instantaneous DSR of MCD18 showed a root mean square error (RMSE) of 146.02 W/m2. The hourly RMSE of ERA5 (155.52 W/m2) was largely smaller than MERRA-2 (188.53 W/m2). On the daily and monthly scale, BESS had the most optimized accuracy among the six products (RMSE of 36.82 W/m2). For the satellite-derived DSR products, the monthly accuracy at CERN can meet the threshold accuracy requirement set by World Meteorological Organization (WMO) for Global Numerical Weather Prediction (20 W/m2). more
Atmosphere CM-SAF Climate Data Records Validation

Evaluating the First Year On-Orbit Radiometric Calibration Performance of GIIRS Onboard Fengyun-4B

Author(s):
Wang, W.; Huang, P.; Xu, N.; Li, J.; Di, D.; Zhang, Z.; Gao, L.; Ji, Z.; Min, M.
Publication title: IEEE Geoscience and Remote Sensing Letters
2024
 | Volume: 21
2024
DOI: 10.1109/LGRS.2024.3422976
Abstract:
The geostationary interferometric infrared sounder (GIIRS) onboard the Fengyun-4B (FY-4B) is the first operational geostationary hyperspectral infrare… The geostationary interferometric infrared sounder (GIIRS) onboard the Fengyun-4B (FY-4B) is the first operational geostationary hyperspectral infrared (IR) sounder. This study analyzes the first-year FY-4B/GIIRS on-orbit calibration performance by comparing it to the collocated IR atmospheric sounder interferometer (IASI) observations and radiative transfer (RT) simulations. The results reveal that the mid-wave IR (MWIR) channels had a slightly larger calibration bias compared to the long-wave IR (LWIR) channels. However, the operational FY-4B/GIIRS showed improved performance compared to the experimental FY-4A/GIIRS. Furthermore, this study also found that most channels exhibited negligible annual and weak diurnal variations in calibration bias. However, there was a significant degradation in the LWIR channels ( more
Climate Data Records NWP-SAF Software for CDR development

Evaluation of 18 satellite- and model-based soil moisture products using in situ measurements from 826 sensors

Author(s):
Beck, Hylke E.; Pan, Ming; Miralles, Diego G.; Reichle, Rolf H.; Dorigo, Wouter A.; Hahn, Sebastian; Sheffield, Justin; Karthikeyan, Lanka; Balsamo, Gianpaolo; Parinussa, Robert M.; van Dijk, Albert I. J. M.; Du, Jinyang; Kimball, John S.; Vergopolan, Noemi; Wood, Eric F.
Publication title: Hydrology and Earth System Sciences
2021
 | Volume: 25 | Issue: 1
2021
DOI: 10.5194/hess-25-17-2021
Abstract:
Abstract. Information about the spatiotemporal variability of soil moisture is critical for many purposes, including monitoring of hydrologic extremes… Abstract. Information about the spatiotemporal variability of soil moisture is critical for many purposes, including monitoring of hydrologic extremes, irrigation scheduling, and prediction of agricultural yields. We evaluated the temporal dynamics of 18 state-of-the-art (quasi-)global near-surface soil moisture products, including six based on satellite retrievals, six based on models without satellite data assimilation (referred to hereafter as “open-loop” models), and six based on models that assimilate satellite soil moisture or brightness temperature data. Seven of the products are introduced for the first time in this study: one multi-sensor merged satellite product called MeMo (Merged soil Moisture) and six estimates from the HBV (Hydrologiska Byråns Vattenbalansavdelning) model with three precipitation inputs (ERA5, IMERG, and MSWEP) with and without assimilation of SMAPL3E satellite retrievals, respectively. As reference, we used in situ soil moisture measurements between 2015 and 2019 at 5 cm depth from 826 sensors, located primarily in the USA and Europe. The 3-hourly Pearson correlation (R) was chosen as the primary performance metric. We found that application of the Soil Wetness Index (SWI) smoothing filter resulted in improved performance for all satellite products. The best-to-worst performance ranking of the four single-sensor satellite products was SMAPL3ESWI, SMOSSWI, AMSR2SWI, and ASCATSWI, with the L-band-based SMAPL3ESWI (median R of 0.72) outperforming the others at 50 % of the sites. Among the two multi-sensor satellite products (MeMo and ESA-CCISWI), MeMo performed better on average (median R of 0.72 versus 0.67), probably due to the inclusion of SMAPL3ESWI. The best-to-worst performance ranking of the six open-loop models was HBV-MSWEP, HBV-ERA5, ERA5-Land, HBV-IMERG, VIC-PGF, and GLDAS-Noah. This ranking largely reflects the quality of the precipitation forcing. HBV-MSWEP (median R of 0.78) performed best not just among the open-loop models but among all products. The calibration of HBV improved the median R by +0.12 on average compared to random parameters, highlighting the importance of model calibration. The best-to-worst performance ranking of the six models with satellite data assimilation was HBV-MSWEP+SMAPL3E, HBV-ERA5+SMAPL3E, GLEAM, SMAPL4, HBV-IMERG+SMAPL3E, and ERA5. The assimilation of SMAPL3E retrievals into HBV-IMERG improved the median R by +0.06, suggesting that data assimilation yields significant benefits at the global scale. more
Climate Data Records H-SAF Land Validation

Evaluation of Cloud-Phase Retrieval Methods for SEVIRI on Meteosat-8 Using Ground-Based Lidar and Cloud Radar Data

Author(s):
Wolters, Erwin L. A.; Roebeling, Robert A.; Feijt, Arnout J.
Publication title: Journal of Applied Meteorology and Climatology
2008
 | Volume: 47 | Issue: 6
2008
DOI: 10.1175/2007JAMC1591.1
Abstract:
Abstract Three cloud-phase determination algorithms from passive satellite imagers are explored to assess their suitability for climate mo… Abstract Three cloud-phase determination algorithms from passive satellite imagers are explored to assess their suitability for climate monitoring purposes in midlatitude coastal climate zones. The algorithms are the Moderate Resolution Imaging Spectroradiometer (MODIS)-like thermal infrared cloud-phase method, the Satellite Application Facility on Climate Monitoring (CM-SAF) method, and an International Satellite Cloud Climatology Project (ISCCP)-like method. Using one year (May 2004–April 2005) of data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on the first Meteosat Second Generation satellite (Meteosat-8), retrievals of the methods are compared with collocated and synchronized ground-based cloud-phase retrievals obtained from cloud radar and lidar observations at Cabauw, Netherlands. Three aspects of the satellite retrievals are evaluated: 1) instantaneous cloud-phase retrievals, 2) monthly-averaged water and ice cloud occurrence frequency, and 3) diurnal cycle of cloud phase for May–August 2004. For the instantaneous cases, all methods have a very small bias for thick water and ice cloud retrievals (∼5%). The ISCCP-like method has a larger bias for pure water clouds (∼10%), which is likely due to the 260-K threshold leading to misdetection of water clouds existing at lower temperatures. For the monthly-averaged water and ice cloud occurrence, the CM-SAF method is best capable of reproducing the annual cycle, mainly for the water cloud occurrence frequency, for which an almost constant positive bias of ∼8% was found. The ISCCP- and MODIS-like methods have more problems in detecting the annual cycle, especially during the winter months. The difference in annual cycle detection among the three methods is most probably related to the use of visible/near-infrared reflectances that enable a more direct observation of cloud phase. The diurnal cycle in cloud phase is reproduced well by all methods. The MODIS-like method reproduces the diurnal cycle best, with correlations of 0.89 and 0.86 for water and ice cloud occurrence frequency, respectively. more
Atmosphere CM-SAF Climate Data Records Validation

Evaluation of Downward Shortwave Radiation Products Over the Loess Plateau

Author(s):
Tian, Qianqian; Zhang, Shuhua; Duan, Weili; Ming, Guanghui
Publication title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
2024
 | Volume: 17
2024
DOI: 10.1109/JSTARS.2023.3346032
Abstract:
Downward shortwave radiation (DSR) is a key component of the surface energy budget, influencing atmospheric circulation and climate change. DSR produc… Downward shortwave radiation (DSR) is a key component of the surface energy budget, influencing atmospheric circulation and climate change. DSR products derived from remote sensing observations or generated from reanalysis systems are commonly used as inputs for ecohydrological and climate models. The Loess Plateau is severely affected by soil erosion and has experienced frequent extreme weather events in recent years. Therefore, an accurate DSR product is crucial for accurately simulating climate change and surface-atmosphere processes on the Loess Plateau. In this study, newly released satellite DSR products CLouds, Albedo and Radiation Edition 3 data (CLARA-A3) and Moderate Resolution Imaging Spectroradiometer land surface Downward Shortwave Radiation Version 6.1 data (MCD18A1 V6.1), along with the reanalysis product Land component of the Fifth Generation European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5-Land), were evaluated over the Loess Plateau and its surrounding areas. Intraday, daily, monthly, and seasonal DSR were evaluated against ground measurements which were collected from five observation networks. CLARA-A3 outperformed MCD18A1 and ERA5-Land on both monthly and daily scales. The root-mean-square error for monthly (daily) DSR from CLARA-A3, ERA5-Land, and MCD18A1 were 19.31 (31.3) W/m2, 25.36 (39.74) W/m2, and 25.03 (46.14) W/m2, respectively. The study explored potential factors contributing to significant errors in DSR products. Results indicated that snow cover was one possible factor influencing the error in MCD18A1, and CLARA-A3 exhibited greater sensitivity to terrain influence compared to ERA5-Land and MCD18A1. The findings can be the reference for selecting DSR products over the Loess Plateau. more
Atmosphere CM-SAF Climate Data Records Validation

Evaluation of PERSIANN-CCS-CDR, ERA5, and SM2RAIN-ASCAT rainfall products for rainfall and drought assessment in a semi-arid watershed, Morocco

Author(s):
Najmi, Adam; Igmoullan, Brahim; Namous, Mustapha; El Bouazzaoui, Imane; Brahim, Yassine Ait; El Khalki, El Mahdi; Saidi, Mohamed El Mehdi
Publication title: Journal of Water and Climate Change
2023
 | Volume: 14 | Issue: 5
2023
DOI: 10.2166/wcc.2023.461
Abstract:
Satellite-based precipitation products, with simultaneously high spatial and temporal resolutions, are mostly needed to assess climate change repercus… Satellite-based precipitation products, with simultaneously high spatial and temporal resolutions, are mostly needed to assess climate change repercussions. Previous research used datasets neglecting either good temporal or good spatial resolution, PERSIANN-CCSCDR, ERA5, and SM2RAIN-ASCAT are some of the projects aiming to remedy these limitations. This study's goal is to evaluate the accuracy of the PERSIANN-CCS-CDR, ERA5, and SM2RAIN-ASCAT at a monthly scale and their suitability for drought assessment in a Moroccan semiarid watershed. Several statistical indices were computed, the drought SPI was calculated using PERSIANN-CCS-CDR estimates, ERA5 products, and observed records as an input in the SPI formula using Gamma distribution to simulate drought from 1983 to 2017. The preliminary comparison and evaluation results of PERSIANN-CCS-CDR estimates and ERA5 datasets showed good CC on a basin scale for monthly precipitation, with a slight overestimation of the observed precipitation shown by the PBIAS. The NSE scored 0.41 for PERSIANN-CCS-CDR and 0.72 for ERA5. The results for SM2RAIN-ASCAT showed an overestimation of the observed precipitation data. At the basin scale, the SPI3 correlation coefficients between the PERSIANN-CCS-CDR monthly estimates and observed gauge rainfall data were greater than 0.67, and the RMSE was closer to 0, outperforming ERA5 in the SPI3 evaluation. more
Atmosphere Climate Data Records H-SAF Validation

Evaluation of Sea Ice Radiative Forcing according to Surface Albedo and Skin Temperature over the Arctic from 1982–2015

Author(s):
Seong, Noh-Hun; Kim, Hyun-Cheol; Choi, Sungwon; Jin, Donghyun; Jung, Daeseong; Sim, Suyoung; Woo, Jongho; Kim, Nayeon; Seo, Minji; Lee, Kyeong-Sang; Han, Kyung-Soo
Publication title: Remote Sensing
2022
 | Volume: 14 | Issue: 11
2022
DOI: 10.3390/rs14112512
Abstract:
Rapid warming of the Arctic has resulted in widespread sea ice loss. Sea ice radiative forcing (SIRF) is the instantaneous perturbation of Earth’s rad… Rapid warming of the Arctic has resulted in widespread sea ice loss. Sea ice radiative forcing (SIRF) is the instantaneous perturbation of Earth’s radiation at the top of the atmosphere (TOA) caused by sea ice. Previous studies focused only on the role of albedo on SIRF. Skin temperature is also closely related to sea ice changes and is one of the main factors in Arctic amplification. In this study, we estimated SIRF considering both surface albedo and skin temperature using radiative kernels. The annual average net-SIRF, which consists of the sum of albedo-SIRF and temperature-SIRF, was calculated as −54.57 ± 3.84 W/m2 for the period 1982–2015. In the net-SIRF calculation, albedo-SIRF and temperature-SIRF made similar contributions. However, the albedo-SIRF changed over the study period by 0.12 ± 0.07 W/m2 per year, while the temperature-SIRF changed by 0.22 ± 0.07 W/m2 per year. The SIRFs for each factor had different patterns depending on the season and region. In summer, rapid changes in the albedo-SIRF occurred in the Kara and Barents regions. In winter, only a temperature-SIRF was observed, and there was little difference between regions compared to the variations in albedo-SIRF. Based on the results of the study, it was concluded that the overall temperature-SIRF is changing more rapidly than the albedo-SIRF. This study indicates that skin temperatures may have a greater impact on the Arctic than albedo in terms of sea ice surface changes. more
Application CM-SAF Climate Data Records Cryosphere

Evaluation of snow cover properties in ERA5 and ERA5-Land with several satellite-based datasets in the Northern Hemisphere in spring 1982-2018

Author(s):
Kouki, K.; Luojus, K.; Riihelä, A.
Publication title: Cryosphere
2023
 | Volume: 17 | Issue: 12
2023
DOI: 10.5194/tc-17-5007-2023
Abstract:
Seasonal snow cover of the Northern Hemisphere (NH) greatly influences surface energy balance; hydrological cycle; and many human activities, such as … Seasonal snow cover of the Northern Hemisphere (NH) greatly influences surface energy balance; hydrological cycle; and many human activities, such as tourism and agriculture. Monitoring snow cover at a continental scale is only possible from satellites or using reanalysis data. This study aims to analyze the time series of snow water equivalent (SWE), snow cover extent (SCE), and surface albedo in spring in ERA5 and ERA5-Land reanalysis data and to compare the time series with several satellite-based datasets. As reference data for the SWE intercomparison, we use bias-corrected SnowCCI v1 data for non-mountainous regions and the mean of Brown, MERRA-2, and Crocus v7 datasets for the mountainous regions. For surface albedo, we use the black-sky albedo datasets CLARA-A2 SAL, based on AVHRR data, and MCD43D51, based on MODIS data. Additionally, we use Rutgers and JAXA JASMES SCE products. Our study covers land areas north of 40N and the period between 1982 and 2018 (spring season from March to May). The analysis shows that both ERA5 and ERA5-Land overestimate total NH SWE by 150% to 200% compared to the SWE reference data. ERA5-Land shows larger overestimation, which is mostly due to very high SWE values over mountainous regions. The analysis revealed a discontinuity in ERA5 around the year 2004 since adding the Interactive Multisensor Snow and Ice Mapping System (IMS) from the year 2004 onwards considerably improves SWE estimates but makes the trends less reliable. The negative NH SWE trends in ERA5 range from-249 to-236Gt per decade in spring, which is 2 to 3 times larger than the trends detected by the other datasets (ranging from-124 to-77Gt per decade). SCE is accurately described in ERA5-Land, whereas ERA5 shows notably larger SCE than the satellite-based datasets. Albedo estimates are more consistent between the datasets, with a slight overestimation in ERA5 and ERA5-Land. The negative trends in SCE and albedo are strongest in May, when the albedo trend varies from-0.011 to-0.006 per decade depending on the dataset. The negative SCE trend detected by ERA5 in May (-1.22×106km2 per decade) is about twice as large as the trends detected by all other datasets (ranging from-0.66 to-0.50×106km2 per decade). The analysis also shows that there is a large spatial variability in the trends, which is consistent with other studies. © 2023 Kerttu Kouki et al. more
CM-SAF Climate Data Records Land Validation

Evaluation of Summertime Passive Microwave and Reanalysis Sea-Ice Concentration in the Central Arctic

Author(s):
Song, K.; Minnett, P.J.
Publication title: Earth and Space Science
2024
 | Volume: 11 | Issue: 1
2024
DOI: 10.1029/2023EA003214
Abstract:
Passive microwave (PM) observations have been used to monitor ice retreat in the Arctic. However, various PM sea ice concentration (SIC) algorithms ar… Passive microwave (PM) observations have been used to monitor ice retreat in the Arctic. However, various PM sea ice concentration (SIC) algorithms are prone to underestimate ice fraction during summer. We evaluated the accuracy of 2002–2019 low SICs in the Central Arctic Ocean of four PM products from the University of Bremen, the National Snow and Ice Data Center (NSIDC), and the Ocean and Sea Ice Satellite Application Facility (OSI SAF), and two reanalysis data sets from the fifth generation of European ReAnalysis (ERA5) and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2). Three reference fields were used: (a) Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) true-color composites, (b) MODIS sea ice extent, and (c) multi-product ensemble (MPE-SIC) comprising the median of collocated SIC estimates. Our results indicate SICs derived from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) and the Advanced Microwave Scanning Radiometer 2 (AMSR2) high frequency channels have the best accuracy. Reanalysis SICs indicate almost identical patterns as their remote sensing inputs. The assessment shows that the Bremen (+1.06%) and NSIDC (+0.99%) SICs are higher than the median field, while the OSI-401 (−6.65%) and OSI-408 (−4.64%) have negative mean deviations. The mean error of MODIS-derived SIC (−0.80%) is smaller than PM SICs. These small mean values belie wide distributions of values. The correlation coefficients of pairs of time series of Low sea-Ice Concentration Index range from 0.37 to 0.96. © 2024 The Authors. Earth and Space Science published by Wiley Periodicals LLC on behalf of American Geophysical Union. more
Climate Data Records Cryosphere OSI-SAF Validation

Evaluation of the 15-year ROM SAF monthly mean GPS radio occultation climate data record

Author(s):
Gleisner, Hans; Lauritsen, Kent B.; Nielsen, Johannes K.; Syndergaard, Stig
Publication title: Atmospheric Measurement Techniques
2020
 | Volume: 13 | Issue: 6
2020
DOI: 10.5194/amt-13-3081-2020
Abstract:
Abstract. We here present results from an evaluation of the Radio Occultation Meteorology Satellite Application Facility (ROM SAF) gridded monthly mea… Abstract. We here present results from an evaluation of the Radio Occultation Meteorology Satellite Application Facility (ROM SAF) gridded monthly mean climate data record (CDR v1.0), based on Global Positioning System (GPS) radio occultation (RO) data from the CHAMP (CHAllenging Minisatellite Payload), GRACE (Gravity Recovery and Climate Experiment), COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate), and Metop satellite missions. Systematic differences between RO missions, as well as differences of RO data relative to ERA-Interim reanalysis data, are quantified. The methods used to generate gridded monthly mean data are described, and the correction of monthly mean RO climatologies for sampling errors, which is essential for combining data from RO missions with different sampling characteristics, is evaluated. We find good overall agreement between the ROM SAF gridded monthly mean CDR and the ERA-Interim reanalysis, particularly in the 8–30 km height interval. Here, the differences largely reflect time-varying biases in ERA-Interim, suggesting that the RO data record has a better long-term stability than ERA-Interim. Above 30–40 km altitude, the differences are larger, particularly for the pre-COSMIC era. In the 8–30 km altitude region, the observational data record exhibits a high degree of internal consistency between the RO satellite missions, allowing us to combine data into multi-mission records. For global mean bending angle, the consistency is better than 0.04 %, for refractivity it is better than 0.05 %, and for global mean dry temperature the consistency is better than 0.15 K in this height interval. At altitudes up to 40 km, these numbers increase to 0.08 %, 0.11 %, and 0.50 K, respectively. The numbers can be up to a factor of 2 larger for certain latitude bands compared to global means. Below about 8 km, the RO mission differences are larger, reducing the possibilities to generate multi-mission data records. We also find that the residual sampling errors are about one-third of the original and that they include a component most likely related to diurnal or semi-diurnal cycles. more
Atmosphere Climate Data Records ROM-SAF Validation
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