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Su Z, Wen J, Zeng Y, Zhao H, Lv S, van der Velde R, Zheng D, Wang X, Wang Z, Schwank M, Kerr Y, Yueh S, Colliander A, Qian H, Drusch M, Mecklenburg S. Multiyear in-situ L-band microwave radiometry of land surface processes on the Tibetan Plateau. Sci Data 2020; 7:317. [PMID: 32999274 PMCID: PMC7527448 DOI: 10.1038/s41597-020-00657-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 08/21/2020] [Indexed: 11/26/2022] Open
Abstract
We report a unique multiyear L-band microwave radiometry dataset collected at the Maqu site on the eastern Tibetan Plateau and demonstrate its utilities in advancing our understandings of microwave observations of land surface processes. The presented dataset contains measurements of L-band brightness temperature by an ELBARA-III microwave radiometer in horizontal and vertical polarization, profile soil moisture and soil temperature, turbulent heat fluxes, and meteorological data from the beginning of 2016 till August 2019, while the experiment is still continuing. Auxiliary vegetation and soil texture information collected in dedicated campaigns are also reported. This dataset can be used to validate the Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellite based observations and retrievals, verify radiative transfer model assumptions and validate land surface model and reanalysis outputs, retrieve soil properties, as well as to quantify land-atmosphere exchanges of energy, water and carbon and help to reduce discrepancies and uncertainties in current Earth System Models (ESM) parameterizations. Measurement cases in winter, pre-monsoon, monsoon and post-monsoon periods are presented.
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Affiliation(s)
- Z Su
- Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands.
- Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, School of Water and Environment, Chang'an University, Xi'an, 710054, China.
| | - J Wen
- College of Atmospheric Sciences, Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu University of Information Technology, Chengdu, China.
| | - Y Zeng
- Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands
| | - H Zhao
- Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands
| | - S Lv
- College of Atmospheric Sciences, Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu University of Information Technology, Chengdu, China
| | - R van der Velde
- Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands
| | - D Zheng
- Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
| | - X Wang
- Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
| | - Z Wang
- Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
| | - M Schwank
- Swiss Federal Research Institute WSL, Birmensdorf, Switzerland
- Gamma Remote Sensing AG, Gümligen, Switzerland
| | - Y Kerr
- CESBIO (CNES/CNRS/UPS/IRD), Toulouse, France
| | - S Yueh
- Jet Propulsion Laboratory, Pasadena, USA
| | | | - H Qian
- Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, School of Water and Environment, Chang'an University, Xi'an, 710054, China
| | - M Drusch
- European Space Agency, ESTEC, Earth Observation Programmes, Noordwijk, The Netherlands
| | - S Mecklenburg
- European Space Agency, ESA Climate Office, Harwell Campus, Oxfordshire, UK
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Mangiarotti S, Peyre M, Zhang Y, Huc M, Roger F, Kerr Y. Chaos theory applied to the outbreak of COVID-19: an ancillary approach to decision making in pandemic context. Epidemiol Infect 2020; 148:e95. [PMID: 32381148 PMCID: PMC7231667 DOI: 10.1017/s0950268820000990] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 05/01/2020] [Accepted: 05/05/2020] [Indexed: 11/30/2022] Open
Abstract
While predicting the course of an epidemic is difficult, predicting the course of a pandemic from an emerging virus is even more so. The validity of most predictive models relies on numerous parameters, involving biological and social characteristics often unknown or highly uncertain. Data of the COVID-19 epidemics in China, Japan, South Korea and Italy were used to build up deterministic models without strong assumptions. These models were then applied to other countries to identify the closest scenarios in order to foresee their coming behaviour. The models enabled to predict situations that were confirmed little by little, proving that these tools can be efficient and useful for decision making in a quickly evolving operational context.
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Affiliation(s)
- S. Mangiarotti
- Centre d'Etudes Spatiales de la Biosphère., CESBIO/OMP, UMR UPS-CNES-CNRS-IRD-INRA, 18, Av. Edouard Belin, 31401Toulouse Cedex 9, France
| | - M. Peyre
- Animal Santé Territoires Risques Ecosystèmes, ASTRE/CIRAD, UMR CIRAD-INRAE-University of Montpellier (I-MUSE), 34398Montpellier, France
| | - Y. Zhang
- Centre d'Etudes Spatiales de la Biosphère., CESBIO/OMP, UMR UPS-CNES-CNRS-IRD-INRA, 18, Av. Edouard Belin, 31401Toulouse Cedex 9, France
| | - M. Huc
- Centre d'Etudes Spatiales de la Biosphère., CESBIO/OMP, UMR UPS-CNES-CNRS-IRD-INRA, 18, Av. Edouard Belin, 31401Toulouse Cedex 9, France
| | - F. Roger
- Animal Santé Territoires Risques Ecosystèmes, ASTRE/CIRAD, UMR CIRAD-INRAE-University of Montpellier (I-MUSE), 34398Montpellier, France
| | - Y. Kerr
- Centre d'Etudes Spatiales de la Biosphère., CESBIO/OMP, UMR UPS-CNES-CNRS-IRD-INRA, 18, Av. Edouard Belin, 31401Toulouse Cedex 9, France
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Al-Yaari A, Wigneron JP, Kerr Y, Rodriguez-Fernandez N, O'Neill PE, Jackson TJ, De Lannoy GJM, Al Bitar A, Mialon A, Richaume P, Walker JP, Mahmoodi A, Yueh S. Evaluating soil moisture retrievals from ESA's SMOS and NASA's SMAP brightness temperature datasets. Remote Sens Environ 2017; 193:257-273. [PMID: 29743730 PMCID: PMC5937273 DOI: 10.1016/j.rse.2017.03.010] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
Two satellites are currently monitoring surface soil moisture (SM) using L-band observations: SMOS (Soil Moisture and Ocean Salinity), a joint ESA (European Space Agency), CNES (Centre national d'études spatiales), and CDTI (the Spanish government agency with responsibility for space) satellite launched on November 2, 2009 and SMAP (Soil Moisture Active Passive), a National Aeronautics and Space Administration (NASA) satellite successfully launched in January 2015. In this study, we used a multilinear regression approach to retrieve SM from SMAP data to create a global dataset of SM, which is consistent with SM data retrieved from SMOS. This was achieved by calibrating coefficients of the regression model using the CATDS (Centre Aval de Traitement des Données) SMOS Level 3 SM and the horizontally and vertically polarized brightness temperatures (TB) at 40° incidence angle, over the 2013 - 2014 period. Next, this model was applied to SMAP L3 TB data from Apr 2015 to Jul 2016. The retrieved SM from SMAP (referred to here as SMAP_Reg) was compared to: (i) the operational SMAP L3 SM (SMAP_SCA), retrieved using the baseline Single Channel retrieval Algorithm (SCA); and (ii) the operational SMOSL3 SM, derived from the multiangular inversion of the L-MEB model (L-MEB algorithm) (SMOSL3). This inter-comparison was made against in situ soil moisture measurements from more than 400 sites spread over the globe, which are used here as a reference soil moisture dataset. The in situ observations were obtained from the International Soil Moisture Network (ISMN; https://ismn.geo.tuwien.ac.at/) in North of America (PBO_H2O, SCAN, SNOTEL, iRON, and USCRN), in Australia (Oznet), Africa (DAHRA), and in Europe (REMEDHUS, SMOSMANIA, FMI, and RSMN). The agreement was analyzed in terms of four classical statistical criteria: Root Mean Squared Error (RMSE), Bias, Unbiased RMSE (UnbRMSE), and correlation coefficient (R). Results of the comparison of these various products with in situ observations show that the performance of both SMAP products i.e. SMAP_SCA and SMAP_Reg is similar and marginally better to that of the SMOSL3 product particularly over the PBO_H2O, SCAN, and USCRN sites. However, SMOSL3 SM was closer to the in situ observations over the DAHRA and Oznet sites. We found that the correlation between all three datasets and in situ measurements is best (R > 0.80) over the Oznet sites and worst (R = 0.58) over the SNOTEL sites for SMAP_SCA and over the DAHRA and SMOSMANIA sites (R= 0.51 and R= 0.45 for SMAP_Reg and SMOSL3, respectively). The Bias values showed that all products are generally dry, except over RSMN, DAHRA, and Oznet (and FMI for SMAP_SCA). Finally, our analysis provided interesting insights that can be useful to improve the consistency between SMAP and SMOS datasets.
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Affiliation(s)
- A Al-Yaari
- INRA, UMR1391 ISPA, Villenave d'Ornon, France
| | | | - Y Kerr
- CESBIO, CNES/CNRS/IRD/UPS, UMR 5126, Toulouse, France
| | | | - P E O'Neill
- NASA, Goddard Space Flight Center, Greenbelt, MD 20771, USA
| | - T J Jackson
- USDA-ARS Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705-2350 USA
| | - G J M De Lannoy
- KU Leuven, Department of Earth and Environmental Sciences, Heverlee, Belgium
| | - A Al Bitar
- CESBIO, CNES/CNRS/IRD/UPS, UMR 5126, Toulouse, France
| | - A Mialon
- CESBIO, CNES/CNRS/IRD/UPS, UMR 5126, Toulouse, France
| | - P Richaume
- CESBIO, CNES/CNRS/IRD/UPS, UMR 5126, Toulouse, France
| | - J P Walker
- Department of Civil Engineering, Monash University, Clayton, Melbourne, Victoria, Australia
| | - A Mahmoodi
- CESBIO, CNES/CNRS/IRD/UPS, UMR 5126, Toulouse, France
| | - S Yueh
- Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA
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de Rosnay P, Drusch M, Boone A, Balsamo G, Decharme B, Harris P, Kerr Y, Pellarin T, Polcher J, Wigneron JP. AMMA Land Surface Model Intercomparison Experiment coupled to the Community Microwave Emission Model: ALMIP-MEM. ACTA ACUST UNITED AC 2009. [DOI: 10.1029/2008jd010724] [Citation(s) in RCA: 94] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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