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2. PrISM at Operational Scale: Monitoring Irrigation District Water Use during Droughts.

Author

Paolini, Giovanni, Escorihuela, Maria Jose, Bellvert, Joaquim, Merlin, Olivier, and Pellarin, Thierry

Subjects
IRRIGATION water, WATER districts, DROUGHTS, WATER use, SPRINKLERS, STANDARD deviations
Abstract

Efficient water management strategies are of utmost importance in drought-prone regions, given the fundamental role irrigation plays in avoiding yield losses and food shortages. Traditional methodologies for estimating irrigation amounts face limitations in terms of overall precision and operational scalability. This study proposes to estimate irrigation amounts from soil moisture (SM) data by adapting the PrISM (Precipitation Inferred from Soil Moisture) methodology. The PrISM assimilates SM into a simple Antecedent Precipitation Index (API) model using a particle filter approach, which allows the creation and estimation of irrigation events. The methodology is applied in a semi-arid region in the Ebro basin, located in the north-east of Spain (Catalonia), from 2016 to 2023. Multi-year drought, which started in 2020, particularly affected the region starting from the spring of 2023, which led to significant reductions in irrigation district water allocations in some of the areas of the region. This study demonstrates that the PrISM approach can correctly identify areas where water restrictions were adopted in 2023, and monitor the water usage with good performances and reliable results. When compared with in situ data for 8 consecutive years, PrISM showed a significant person's correlation between 0.58 and 0.76 and a cumulative weekly root mean squared error (rmse) between 7 and 11 mm. Additionally, PrISM was applied to three irrigation districts with different levels of modernization, due to the different predominant irrigation systems: flood, sprinkler, and drip. This analysis underlined the strengths and limitations of PrISM depending on the irrigation techniques monitored. PrISM has good performances in areas irrigated by sprinkler and flood systems, while difficulties are present over drip irrigated areas, where the very localized and limited irrigation amounts could not be detected from S M observations. [ABSTRACT FROM AUTHOR]

Published
2024
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5. Assessment of the SMAP Level-4 Surface and Root-Zone Soil Moisture Product Using In Situ Measurements

Author

Reichle, Rolf H., De Lannoy, Gabrielle J. M., Liu, Qing, Ardizzone, Joseph V., Colliander, Andreas, Conaty, Austin, Crow, Wade, Jackson, Thomas J., Jones, Lucas A., Kimball, John S., Koster, Randal D., Mahanama, Sarith P., Smith, Edmond B., Berg, Aaron, Bircher, Simone, Bosch, David, Caldwell, Todd G., Cosh, Michael, González-Zamora, Ángel, Collins, Chandra D. Holifield, Jensen, Karsten H., Livingston, Stan, Lopez-Baeza, Ernesto, Martínez-Fernández, José, McNairn, Heather, Moghaddam, Mahta, Pacheco, Anna, Pellarin, Thierry, Prueger, John, Rowlandson, Tracy, Seyfried, Mark, Starks, Patrick, Su, Zhongbo, Thibeault, Marc, Van Der Velde, Rogier, Walker, Jeffrey, Wu, Xiaoling, and Zeng, Yijian

Published
2017

10. Assessing typhoon-induced compound flood drivers: a case study in Ho Chi Minh City, Vietnam.

Author

Rodrigues do Amaral, Francisco, Gratiot, Nicolas, Pellarin, Thierry, and Tu, Tran Anh

Subjects
STORM surges, RAINFALL anomalies, RAINFALL, FLOODS, WATER levels, FLOOD warning systems, LANDFALL
Abstract

We investigate the most severe rainfall event ever experienced in Ho Chi Minh City (HCMC), Vietnam. It occurred on 25 November 2018 when Typhoon (TY) Usagi directly hit HCMC. During this event, there was more than 300 mm of rainfall over 24 h which led to flooding and considerable material damage. We propose an in-depth study of TY-induced, compound flood drivers at a short timescale by focusing on the days before and after the event. We use a set of data analysis and signal processing tools to characterize and quantify both coastal and inland effects on the hydrosystem. We found that TY Usagi made landfall without forming a significant storm surge. The extreme rainfall does not translate into immediate river discharge but presents a 16 h time lag between peak precipitation and peak residual discharge. Nevertheless, increased river water levels can be seen at both urban and upstream stations with a similar time lag. At the upstream river station, residual discharge represents 1.5 % of available rainwater, and evidence of upstream widespread flooding was found. At the urban river station, we assess the potential surface runoff during the event to be 8.9 % of the upstream residual discharge. However, a time lag in peak river water level and peak rainfall was found and attributed to the combination of high tide and impervious streets which prevented the evacuation of rainwater and resulted in street flooding of up to 0.8 m. Overall, it was found that despite not having a significant storm surge, the coastal tidal forcing is the predominant compound flood driver even during severe, heavy rainfall with tidal fluctuations in river water level and respective discharge much larger than the residuals. [ABSTRACT FROM AUTHOR]

Published
2023
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11. Reducing the carbon footprint of a public research laboratory in Geosciences. Assessing a reduction strategy built with laboratory members after a 3-year experimentation

Author

Pellarin, Thierry, primary, Champollion, Nicolas, additional, Gratiot, Nicolas, additional, Teran-Escobar, Claudia, additional, Ruin, Isabelle, additional, Panthou, Geremy, additional, Hingray, Benoit, additional, Delaygue, Gilles, additional, Jager, Eliot, additional, Lamothe, Alexis, additional, Piton, Guillaume, additional, Evin, Guillaume, additional, Blanchet, Juliette, additional, Philippon, Nathalie, additional, Philip, Armelle, additional, Martinerie, Patricia, additional, and Picard, Ghislain, additional

Published
2023
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15. Hydraulic response of a tropical urban estuary to a typhoon event: case study of Ho Chi Minh City and typhoon Usagi.

Author

Amaral, Francisco Rodrigues do, Gratiot, Nicolas, and Pellarin, Thierry

Subjects
STORM surges, RAINFALL anomalies, TYPHOONS, RAINFALL, TIDE-waters, MUNICIPAL water supply, WATER levels, RAINWATER
Abstract

We investigate the most severe rainfall event ever experienced in Ho Chi Minh City (HCMC), Vietnam. It occurred on November 25th, 2018 when typhoon (TY) Usagi directly hit HCMC. During this event, there was more than 300 mm in rainfall over 24 h which led to flooding and considerable material damages. We propose an in-depth study of the hydrological response of this urban estuary region at a short time scale by focusing on the days before and after typhoon Usagi. We use a set of data analysis and signal processing tools to characterize and quantify both coastal and continental effects on the hydrosystem. We found that TY Usagi made landfall without forming a significant storm surge. The extreme rainfall does not translate in immediate river discharge but presents a 10 hour time lag between peak precipitation and peak residual discharge. Nevertheless, increased water levels can be seen at both urban and upstream river stations with a similar time lag. At the upstream station, residual discharge represents 1.5 % of available rain water and evidence of upstream wide spread flooding was found. At the urban station, we assess the potential surface run off during the event to be 8.9 % of the upstream residual discharge. Hence, the Saigon river would be capable of evacuating the urban flood water after the event. However, a time lag in peak water level and peak rainfall was found and attributed to the combination of high tide and impervious streets which prevented the evacuation of rain water and resulted in street flooding of up to 0.8 m. Overall, it was found that despite not having a significant storm surge, the coastal tidal forcing is predominant in the hydrodynamics of the river even during severe heavy rainfall with tidal fluctuations of water level and respective discharge much larger than the residuals. [ABSTRACT FROM AUTHOR]

Published
2023
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19. Validation of Soil Moisture Data Products From the NASA SMAP Mission

Author

Colliander, Andreas, primary, Reichle, Rolf H., additional, Crow, Wade T., additional, Cosh, Michael H., additional, Chen, Fan, additional, Chan, Steven, additional, Das, Narendra Narayan, additional, Bindlish, Rajat, additional, Chaubell, Julian, additional, Kim, Seungbum, additional, Liu, Qing, additional, O'Neill, Peggy E., additional, Dunbar, R. Scott, additional, Dang, Land B., additional, Kimball, John S., additional, Jackson, Thomas J., additional, Al-Jassar, Hala Khalid, additional, Asanuma, Jun, additional, Bhattacharya, Bimal K., additional, Berg, Aaron A., additional, Bosch, David D., additional, Bourgeau-Chavez, Laura, additional, Caldwell, Todd, additional, Calvet, Jean-Christophe, additional, Collins, Chandra Holifield, additional, Jensen, Karsten H., additional, Livingston, Stan, additional, Lopez-Baeza, Ernesto, additional, Martinez-Fernandez, Jose, additional, McNairn, Heather, additional, Moghaddam, Mahta, additional, Montzka, Carsten, additional, Notarnicola, Claudia, additional, Pellarin, Thierry, additional, Greimeister-Pfeil, Isabella, additional, Pulliainen, Jouni, additional, Ramos, Judith Gpe., additional, Seyfried, Mark, additional, Starks, Patrick J., additional, Su, Zhongbo, additional, van der Velde, R., additional, Zeng, Yijian, additional, Thibeault, Marc, additional, Vreugdenhil, Mariette, additional, Walker, Jeffrey P., additional, Zribi, Mehrez, additional, Entekhabi, Dara, additional, and Yueh, Simon H., additional

Published
2022
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21. List of Authors

Author

Baghdadi, Nicolas, primary, Barbu, Alina L., additional, Bernier, Monique, additional, Boniface, Karen, additional, Boulet, Gilles, additional, Boussetta, Souhail, additional, Calmant, Stéphane, additional, Calvet, Jean-Christophe, additional, Cretaux, Jean-François, additional, Dedieu, Jean-Pierre, additional, De Rosnay, Patricia, additional, Duguay, Yannick, additional, Dumont, Marie, additional, Egido, Alejandro, additional, Frappart, Frédéric, additional, Frison, Pierre-Louis, additional, Gascoin, Simon, additional, Jarlan, Lionel, additional, Kerr, Yann, additional, Lagouarde, Jean-Pierre, additional, Leroux, Delphine, additional, Magagi, Ramata, additional, Motte, Erwan, additional, Mougin, Eric, additional, Pellarin, Thierry, additional, Ramillien, Guillaume, additional, Remy, Frédérique, additional, Roussel, Nicolas, additional, Seoane, Lucía, additional, Wigneron, Jean-Pierre, additional, and Zribi, Mehrez, additional

Published
2016
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22. Scientific Committee

Author

Paloscia, Simonetta, primary, Louamgne, Cécile, additional, Pellarin, Thierry, additional, de Rosnay, Patricia, additional, Calvet, Jean-Christophe, additional, Albergel, Clément, additional, Zine, Sonia, additional, Hagolle, Olivier, additional, Bernier, Monique, additional, Gay, Michel, additional, De Seve, Danielle, additional, Maillard, Philippe, additional, Benveniste, Jerome, additional, Maisongrande, Philippe, additional, Dechambre, Monique, additional, Leblanc, Marc, additional, Biancamaria, Sylvain, additional, Lemoine, Jean-Michel, additional, Banville, Simon, additional, Bergeot, Nicolas, additional, Darrozes, José, additional, Olioso, Albert, additional, Merlin, Olivier, additional, Belaud, Gilles, additional, Gascoin, Simon, additional, Ottle, Catherine, additional, Jarlan, Lionel, additional, Zribi, Mehrez, additional, and Baghdadi, Nicolas, additional

Published
2016
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23. The International Soil Moisture Network: serving Earth system science for over a decade

Author

Dorigo, Wouter, primary, Himmelbauer, Irene, additional, Aberer, Daniel, additional, Schremmer, Lukas, additional, Petrakovic, Ivana, additional, Zappa, Luca, additional, Preimesberger, Wolfgang, additional, Xaver, Angelika, additional, Annor, Frank, additional, Ardö, Jonas, additional, Baldocchi, Dennis, additional, Bitelli, Marco, additional, Blöschl, Günter, additional, Bogena, Heye, additional, Brocca, Luca, additional, Calvet, Jean-Christophe, additional, Camarero, J. Julio, additional, Capello, Giorgio, additional, Choi, Minha, additional, Cosh, Michael C., additional, van de Giesen, Nick, additional, Hajdu, Istvan, additional, Ikonen, Jaakko, additional, Jensen, Karsten H., additional, Kanniah, Kasturi Devi, additional, de Kat, Ileen, additional, Kirchengast, Gottfried, additional, Kumar Rai, Pankaj, additional, Kyrouac, Jenni, additional, Larson, Kristine, additional, Liu, Suxia, additional, Loew, Alexander, additional, Moghaddam, Mahta, additional, Martínez Fernández, José, additional, Mattar Bader, Cristian, additional, Morbidelli, Renato, additional, Musial, Jan P., additional, Osenga, Elise, additional, Palecki, Michael A., additional, Pellarin, Thierry, additional, Petropoulos, George P., additional, Pfeil, Isabella, additional, Powers, Jarrett, additional, Robock, Alan, additional, Rüdiger, Christoph, additional, Rummel, Udo, additional, Strobel, Michael, additional, Su, Zhongbo, additional, Sullivan, Ryan, additional, Tagesson, Torbern, additional, Varlagin, Andrej, additional, Vreugdenhil, Mariette, additional, Walker, Jeffrey, additional, Wen, Jun, additional, Wenger, Fred, additional, Wigneron, Jean Pierre, additional, Woods, Mel, additional, Yang, Kun, additional, Zeng, Yijian, additional, Zhang, Xiang, additional, Zreda, Marek, additional, Dietrich, Stephan, additional, Gruber, Alexander, additional, van Oevelen, Peter, additional, Wagner, Wolfgang, additional, Scipal, Klaus, additional, Drusch, Matthias, additional, and Sabia, Roberto, additional

Published
2021
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25. Validation of Soil Moisture Data Products from the NASA SMAP Mission

Author

Colliander, Andreas, primary, Reichle, Rolf, primary, Crow, Wade, primary, Cosh, Michael, primary, Chen, Fan, primary, Chan, Steven, primary, Das, Narendra, primary, Bindlish, Rajat, primary, Chaubell, Julian, primary, Kim, Seungbum, primary, Liu, Qing, primary, O'Neill, Peggy, primary, Dunbar, Scott, primary, Dang, Lan, primary, Kimball, John, primary, Jackson, Tom, primary, AlJassar, Hala, primary, Asanuma, Jun, primary, Bhattacharya, Bimal, primary, Berg, Aaron, primary, Bosch, David, primary, Bourgeau-Chavez, Laura, primary, Caldwell, Todd, primary, Calvet, Jean-Christophe, primary, Collins, Chandra Holifield, primary, Jensen, Karsten, primary, Livingston, Stan, primary, López-Baeza, Ernesto, primary, Martínez-Fernández, José, primary, McNairn, Heather, primary, Moghaddam, Mahta, primary, Montzka, Carsten, primary, Notarnicola, Claudia, primary, Pellarin, Thierry, primary, Pfeil, Isabella, primary, Pulliainen, Jouni, primary, Ramos, Judith, primary, Seyfrie, Mark, primary, Starks, Patrick, primary, Su, Z, primary, Thibeault, Marc, primary, van der Velde, R., primary, Vreugdenhil, Mariette, primary, Walker, Jeffrey, primary, Zeng, Y., primary, Zribi, Mehrez, primary, Entekhabi, Dara, primary, and Yueh, Simon, primary

Published
2021
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26. Synergy of SMOS microwave radiometer and optical sensors to retrieve soil moisture at global scale

Author

Cros, Sylvain, Chanzy, Andre, Weiss, Marie, Pellarin, Thierry, Calvet, Jean-Christophe, and Wigneron, Jean-Pierre

Subjects
Soil moisture -- Observations, Soil moisture -- Analysis, Vegetation dynamics -- Analysis, Business, Earth sciences, Electronics and electrical industries
Abstract

Methods to retrieve surface soil moisture were assessed at the global scale for one entire year by using simulated Soil Moisture and Ocean Salinity brightness temperatures ([T.sub.B]) and vegetation coverage information which can be derived from optical sensors. The global [T.sub.B] database consists of half-degree continental pixels and accounts for within-pixel heterogeneity, based on 1-km resolution land cover maps. The retrievals were performed by using a three-parameter inversion method applied to the L-band Microwave Emission of the Biosphere model. By using a Bayesian approach, vegetation data were injected as a priori information. Two options were investigated to profit from normalized difference vegetation index products: providing an a priori knowledge either on vegetation optical depth or on the vegetation cover fraction ([f.sub.cover]). The latter option allows for a better description of the surface heterogeneity by considering a bare soil fraction. When an error of 1 K is applied to the [T.sub.B], both synergistic schemes significantly improved the soil moisture accuracy compared with methods using microwave data only. Using the vegetation a priori information, about 80% of the pixels present soil moisture retrieval accuracy less than 0.04 [m.sup.3] * [m.sup.-3] in terms of root-mean-square error, whereas methods based only on the microwave data provide 63% of pixels of the studied area with this accuracy. If the error in [T.sub.B] is larger (2 or 3 K), the soil moisture retrieval accuracy decreases significantly for both methods. The use of optical data to give a priori value of vegetation optical option is then the best for these cases. Index Terms--Microwave radiometry, microwave remote sensing, moisture, normalized difference vegetation index (NDVI), satellite applications, Soil Moisture and Ocean Salinity (SMOS), surface soil moisture, synergy, vegetation.

Published
2008

27. Soil Moisture Product Validation Good Practices Protocol

Author

Montzka, Carsten, Cosh, Michael H., Bayat, Bagher, Al Bitar, Ahmad, Berg, Aaron, Bindlish, Rajat, Reemt Bogena, Heye, Bolten, John D., Cabot, Francois, Caldwell, Todd, Chan, Steven, Colliander, Andreas, Crow, Wade, Das, Narendra N., De Lannoy, Gabrielle, Dorigo, Wouter, Evett, Steven R., Gruber, Alexander, Hahn, Sebastian, Jagdhuber, Thomas, Jones, Scott, Kerr, Yann, Kim, Seungbum, Koyama, Christian, Kurum, Mehmed, Lopez-Baeza, Ernesto, Mattia, Francesco, McColl, Kaighin A., Mecklenburg, Susanne, Mohanty, Binayak, O ́Neill, Peggy, Or, Dani, Pellarin, Thierry, Petropoulos, George P., Piles, Maria, Reichle, Rolf H., Rodriguez-Fernandez, Nemesio, Rüdiger, Christoph, Scanlon, Tracy, Schwartz, Robert C., Spengler, Daniel, Srivastava, Prashant, Suman, Swati, van der Schalie, Robin, Wagner, Wolfgang, Wegmüller, Urs, Wigneron, Jean-Pierre, Camacho, Fernando, and Nickeson, Jaime

Subjects
good practices, ddc:610, protocol, soil moisture, product validation
Published
2020

28. Issues about retrieving sea surface salinity in coastal areas from SMOS data

Author

Zine, Sonia, Boutin, Jacqueline, Waldteufel, Philippe, Vergely, Jean-Luc, Pellarin, Thierry, and Lazure, Pascal

Subjects
Coasts -- Analysis, Artificial satellites in geographical research -- Usage, Salinity -- Analysis, Business, Earth sciences, Electronics and electrical industries
Abstract

This paper aims at studying the quality of the sea surface salinity (SSS) retrieved from Soil Moisture and Ocean Salinity (SMOS) data in coastal areas. These areas are characterized by strong and variable SSS gradients [several practical salinity units (psu)] on relatively small scales: the extent of river plumes is highly variable, typically at kilometric and daily scales. Monitoring this variability from SMOS measurements is particularly challenging because of their resolution (typically 30-100 km) and because of the contamination by the nearby land. A set of academic tests was conducted with a linear coastline and constant geophysical parameters, and more realistic tests were conducted over the Bay of Biscay. The bias of the retrieved SSS has been analyzed, as well as the root mean square (rms) of the bias, and the retrieved SSS compared to a numerical hydrodynamic model in the semirealistic case. The academic study showed that the Blackman apodization window provides the best compromise in terms of magnitude and fluctuations of the bias of the retrieved SSS. Whatever the type of vegetation cover, a strong negative bias, greater than 1 psu, was found when nearer than 36 km from the coast. Between 44 and 80 km, the type of vegetation cover has an impact of less than a factor 2 on the bias, and no influence further than 80 km from the coast. The semirealistic study conducted in the Bay of Biscay showed a bias over ten days lower than 0.2 psu for distances greater than 47 km, due to an averaging over various geometries (coastline orientation, swath orientation, etc.). The bias showed a weak dependence on the location of the grid point within the swath. Despite the noise on the retrieved SSS, contrasts due to the plume of the Loire River and the Gironde estuary remained detectable on ten-day averaged maps with an rms of 0.57 psu. Finally, imposing thresholds on the major axis of the measurements brought little improvement to the bias, whereas it increased the rms and could lead to strong swath restriction: a 49-km threshold on the major axis resulted in an effective swath of 800-900 km instead of 1200 km. Index Terms--Coastal areas, L-band radiometry, sea surface salinity (SSS) retrieval, Soil Moisture and Ocean Salinity (SMOS) mission.

Published
2007

29. Global simulation of brightness temperatures at 6.6 and 10.7 GHz over land based on SMMR data set analysis

Author

Pellarin, Thierry, Kerr, Yann H., and Wigneron, Jean-Pierre

Subjects
Radiometers -- Usage, Soil moisture -- Research, Salinity -- Research, Temperature measurements -- Observations, Business, Earth sciences, Electronics and electrical industries
Abstract

In the framework of the Soil Moisture and Ocean Salinity mission, a two-year (1987-1988) global simulation of brightness temperatures (TB) at L-band was performed using a simple model [L-band microwave emission of the biosphere, (L-MEB)] based on radiative transfer equations. However, the lack of alternative L-band spaceborne measurements corresponding to real-world data prevented from assessing the realism of the simulated global-scale TB fields. In this study, using a similar modeling approach, TB simulations were performed at C-band and X-band. These simulations required the development of C-MEB and X-MEB models, corresponding to the equivalent of L-MEB at C-band and X-band, respectively. These simulations were compared with Scanning Multichannel Microwave Radiometer (SMMR) measurements during the period January to August 1987 (corresponding to the end of life of the SMMR mission). A sensitivity study was also carried out to assess, at a global scale, the relative contributions of the main MEB parameters (particularly the roughness and vegetation model parameters). Regional differences between simulated and measured TBs were analyzed, discriminating possible issues either linked to the radiative transfer model (C-MEB and X-MEB) or due to land surface simulations. A global agreement between observations and simulations was discussed and allowed to evaluate regions where soil moisture retrievals would give best results. This comparison step made at C-band and X-band allowed to better assess how realistic and/or accurate the L-band simulations could be. Index Terms--Global scale, L-, C-, X-band radiometry, simple emission model, Scanning Multichannel Microwave Radiometer (SMMR), Soil Moisture and Ocean Salinity (SMOS), soil moisture.

Published
2006

30. Two-year global simulation of L-band brightness temperatures over land

Author

Pellarin, Thierry, Wigneron, Jean-Pierre, Calvet, Jean-Christophe, Berger, Michael, Douville, Herve, Ferrazzoli, Paolo, Kerr, Yann H., Lopez-Baeza, Ernesto, Pulliainen, Jouni, Simmonds, Lester P., and Waldteufel, Philippe

Subjects
Radiation -- Measurement, Topographical surveying -- Methods, Landforms, Business, Earth sciences, Electronics and electrical industries
Abstract

This letter presents a synthetic L-band (1.4 GHz) multiangular brightness temperature dataset over land surfaces that was simulated at a half-degree resolution and at the global scale. The microwave emission of various land-covers (herbaceous and woody vegetation, frozen and unfrozen bare soil, snow, etc.) was computed using a simple model [L-band Microwave Emission of the Biosphere (L-MEB)] based on radiative transfer equations. The soil and vegetation characteristics needed to initialize the L-MEB model were derived from existing land-cover maps. Continuous simulations from a land-surface scheme for 1987 and 1988 provided time series of the main variables driving the L-MEB model: soil temperature at the surface and at depth, surface soil moisture, proportion of frozen surface soil moisture, and snow cover characteristics. The obtained global maps constitute a useful dataset for a first evaluation of the sensitivity of future satellite-based L-band radiometry data to soil moisture. Index Terms--Global scale, L-band radiometry, modeling, soil moisture.

Published
2003

31. Surface soil moisture retrieval from L-band radiometry: a global regression study

Author

Pellarin, Thierry, Calvet, Jean-Christophe, and Wigneron, Jean-Pierre

Subjects
Landforms, Soil moisture -- Measurement, Business, Earth sciences, Electronics and electrical industries
Abstract

Using a global simulation of L-band (1.4 GHz) brightness temperature ([T.sub.B]) for two years (1987 and 1988), the relationship between L-band brightness temperatures and surface soil moisture was analyzed using simple regression models. The global [T.sub.B] dataset describes continental pixels at a half-degree spatial resolution and accounts for within-pixel heterogeneity, based on 1-km resolution land cover maps. Two different statistical methods were investigated. First, a single regression model was obtained using a linear combination of [T.sub.B] indexes. This method consisted in retrieving surface soil moisture using the same global regression model for all the pixels. Second, a regression model was calibrated over each pixel using similar linear combinations of the [T.sub.B] indexes. In both cases, the influence of the radiometric noise on [T.sub.B] was investigated. Applying these two methods, the capability of L-band [T.sub.B] observations to monitor surface soil moisture was evaluated at the global scale and during a two-year time period. Global maps of the estimated accuracy of the soil moisture retrievals were produced. These results contribute to better define the potential of the observations from future spaceborne missions such as the Soil Moisture and Ocean Salinity (SMOS) mission. Index Terms--Global scale, L-band radiometry, soil moisture.

Published
2003

32. Can We Use Satellite-Based Soil-Moisture Products at High Resolution to Investigate Land-Use Differences and Land–Atmosphere Interactions? A Case Study in the Savanna

Author

Román-Cascón, Carlos, primary, Lothon, Marie, additional, Lohou, Fabienne, additional, Ojha, Nitu, additional, Merlin, Olivier, additional, Aragonés, David, additional, González-Dugo, María P., additional, Andreu, Ana, additional, Pellarin, Thierry, additional, Brut, Aurore, additional, Soriguer, Ramón C., additional, Díaz-Delgado, Ricardo, additional, Hartogensis, Oscar, additional, and Yagüe, Carlos, additional

Published
2020
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33. A daily 25 km short-latency rainfall product for data-scarce regions based on the integration of the Global Precipitation Measurement mission rainfall and multiple-satellite soil moisture products

Author

Massari, Christian, primary, Brocca, Luca, additional, Pellarin, Thierry, additional, Abramowitz, Gab, additional, Filippucci, Paolo, additional, Ciabatta, Luca, additional, Maggioni, Viviana, additional, Kerr, Yann, additional, and Fernandez Prieto, Diego, additional

Published
2020
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38. The Precipitation Inferred from Soil Moisture (PrISM) Near Real-Time Rainfall Product: Evaluation and Comparison

Author

Pellarin, Thierry, primary, Román-Cascón, Carlos, additional, Baron, Christian, additional, Bindlish, Rajat, additional, Brocca, Luca, additional, Camberlin, Pierre, additional, Fernández-Prieto, Diego, additional, Kerr, Yann H., additional, Massari, Christian, additional, Panthou, Geremy, additional, Perrimond, Benoit, additional, Philippon, Nathalie, additional, and Quantin, Guillaume, additional

Published
2020
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39. Evolution of surface hydrology in the Sahelo-Sudanian strip : an updated review

Author

Descroix, Luc, Guichard, FranÇoise, Grippa, Manuela, Lambert, Laurent, Panthou, Gérémy, Fisjak, Yu, GAL, LAETITIA, Dardel, Cécile, Quantin, Guillaume, Kergoat , Laurent, Bouaita, Yasmin, Hiernaux, Pierre, Vischel, Theo, Pellarin, Thierry, Faty, Bakary, Wilcox, Catherine, Malam Abdou, Moussa, Mamadou, Ibrahim, Vandervaere, Jean-Pierre, Diongue-Niang, Aïda, Ndiaye, Ousmane, Sané, Youssouph, Dacosta, Honoré, Gosset, Marielle, Cassé, Claire, Sultan, Benjamin, Barry, Aliou, Amogu, Okechukwu, Nka Nnomo, Bernadette, Barry, Alseny, Paturel, Jean-Emmanuel, Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Géosciences Environnement Toulouse (GET), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Qatar University, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Hydrosciences Montpellier (HSM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Patrimoines Locaux et Gouvernance (PALOC), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD), Agence Nationale de l’Aviation Civile et de la Météorologie (ANACIM), UMR 228 Espace-Dev, Espace pour le développement, Institut de Recherche pour le Développement (IRD)-Université de Perpignan Via Domitia (UPVD)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM)-Université de Guyane (UG)-Université des Antilles (UA), Direction Nationale de l'Hydraulique (DNH), Ministère de l'Hydraulique, Centre de Recherches Hydrologiques, Université de Yaoundé I, Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Université de Guyane (UG)-Université des Antilles (UA)-Institut de Recherche pour le Développement (IRD)-Université de Perpignan Via Domitia (UPVD)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM), Centre National de la Recherche Scientifique (CNRS)-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut de Recherche pour le Développement (IRD)-Centre National d'Études Spatiales [Toulouse] (CNES), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Agence Nationale de l’Aviation Civile et de la Météorologie, Université des Antilles (UA)-Université de Guyane (UG)-Université de Montpellier (UM)-Université de La Réunion (UR)-Avignon Université (AU)-Université de Perpignan Via Domitia (UPVD)-Institut de Recherche pour le Développement (IRD), and Université de Yaoundé I [Yaoundé]

Subjects
lcsh:TD201-500, lcsh:Hydraulic engineering, water holding capacity, [SDE.MCG]Environmental Sciences/Global Changes, land use, land use/land cover changes, land cover changes, lcsh:Water supply for domestic and industrial purposes, climate change, lcsh:TC1-978, Sahel, re-greening, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, ComputingMilieux_MISCELLANEOUS, hydrological paradox
Abstract

In the West African Sahel, two paradoxical hydrological behaviors have occurred during the last five decades. The first paradox was observed during the 1968&ndash, 1990s &lsquo, Great Drought&rsquo, period, during which runoff significantly increased. The second paradox appeared during the subsequent period of rainfall recovery (i.e., since the 1990s), during which the runoff coefficient continued to increase despite the general re-greening of the Sahel. This paper reviews and synthesizes the literature on the drivers of these paradoxical behaviors, focusing on recent works in the West African Sahelo/Sudanian strip, and upscaling the hydrological processes through an analysis of recent data from two representative areas of this region. This paper helps better determine the respective roles played by Land Use/Land Cover Changes (LULCC), the evolution of rainfall intensity and the occurrence of extreme rainfall events in these hydrological paradoxes. Both the literature review and recent data converge in indicating that the first Sahelian hydrological paradox was mostly driven by LULCC, while the second paradox has been caused by both LULCC and climate evolution, mainly the recent increase in rainfall intensity.

Published
2018

41. Supplementary material to "A daily/25 km short-latency rainfall product for data scarce regions based on the integration of the GPM IMERG Early Run with multiple satellite soil moisture products"

Author

Massari, Christian, primary, Brocca, Luca, additional, Pellarin, Thierry, additional, Abramowitz, Gab, additional, Filippucci, Paolo, additional, Ciabatta, Luca, additional, Maggioni, Viviana, additional, Kerr, Yann, additional, and Fernandez Prieto, Diego, additional

Published
2019
Full Text
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42. SMOS-HR: A High Resolution L-Band Passive Radiometer for Earth Science and Applications

Author

Rodriguez-Fernandez, Nemesio J., primary, Mialon, Arnaud, additional, Merlin, Olivier, additional, Suere, Christophe, additional, Cabot, Francois, additional, Khazaal, Ali, additional, Costeraste, Josiane, additional, Palacin, Baptiste, additional, Rodriguez-Suquet, Raquel, additional, Tournier, Thierry, additional, Decoopman, Thibaut, additional, Anterrieu, Eric, additional, Colom, Miguel, additional, Morel, Jean-Michel, additional, Kerr, Yann H., additional, Rouge, Bernard, additional, Boutin, Jaqueline, additional, Picard, Ghislain, additional, Pellarin, Thierry, additional, Escorihuela, Maria Jose, additional, Al Bitar, Ahmad, additional, and Richaume, Philippe, additional

Published
2019
Full Text
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43. Evaluation of remotely sensed rainfall products over Central Africa

Author

Camberlin, Pierre, primary, Barraud, Geoffrey, additional, Bigot, Sylvain, additional, Dewitte, Olivier, additional, Makanzu Imwangana, Fils, additional, Maki Mateso, Jean‐Claude, additional, Martiny, Nadège, additional, Monsieurs, Elise, additional, Moron, Vincent, additional, Pellarin, Thierry, additional, Philippon, Nathalie, additional, Sahani, Muhindo, additional, and Samba, Gaston, additional

Published
2019
Full Text
View/download PDF

46. SMOS and hydrology

Author

Kerr, Yann, Bircher, Simone, Rodriguez-Fernandez, Nemesio, Molero, Beatriz, Parrens, Marie, Leroux, Delphine, Pellarin, Thierry, Wigneron, Jean-Pierre, Mecklenburg, Susanne, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), PhyREV - Processus Hydrologiques pour les Ressources en Eau Vulnérables, Laboratoire d’étude des Transferts en Hydrologie et Environnement (LTHE), Interactions Sol Plante Atmosphère (ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), ESRIN, European Space Agency (ESA), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (UMR ISPA), and ESA Centre for Earth Observation (ESRIN)

Subjects
remote sensing, bilan hydrologique, télédétection, [SDE.MCG]Environmental Sciences/Global Changes, projet smos, acquisition de données, water budget, radiometer, radiomètre, donnée satellite, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

SMOS, a L Band radiometer using aperture synthesis to achieve a good spatial resolution, was successfully launched on November 2, 2009. It was developed and made under the leadership of the European Space Agency (ESA) as an Earth Explorer Opportunity mission. It is a joint program with the Centre National d’Etudes Spatiales (CNES) in France and the Centro para el Desarrollo Teccnologico Industrial (CDTI) in Spain. SMOS carries a single payload, an L band 2D interferometric, radiometer in the 1400-1427 MHz protected band. This wavelength penetrates well through the vegetation and the atmosphere is almost transparent enabling to infer both soil moisture and vegetation water content. SMOS achieves an unprecedented spatial resolution of 50 km at L-band maximum (43 km on average) with multi angular-dual polarized (or fully polarized) brightness temperatures over the globe and with a revisit time smaller than 3 days. SMOS has been now acquiring data for 5.5 years. The data quality exceeds what was expected, showing very good sensitivity and stability. The data is unfortunately impaired by man-made emission in the protected band, leading to degraded measurements in several areas including parts of Europe and of China. However, many different international teams are now addressing data use in various fields including hydrology. We have now acquired data over a number of significant “extreme events” such as droughts and floods giving useful information of potential applications. We are now working on the coupling with other models and or disaggregation to address soil moisture distribution over watersheds. We are also concentrating efforts on water budget and regional impacts. Assimilation of SMOS data into hydrological modelling showed positive impact in terms of stream flow and soil moisture estimation.With the development of a near real time soil moisture product using neural network approach, a wealth of new applications is bound to occur. From all those studies, it is now possible to express the “lessons learned” and derive a possible way forward. This paper thus gives an overview of the water cycle science goals of the SMOS mission, a description of its main elements, and a taste of the first results including performances at brightness temperature as well as at geophysical parameters level and how they are being put in good use for hydrological applications.

Published
2016

47. SMOS level 3 soil moisture database

Author

Mialon, Arnaud, Ahmad, Al Bitar, Cabot, François, Tarot, Stéphane, Pellarin, Thierry, Richaume, Philippe, Vandermarcq, Olivier, Wigneron, Jean-Pierre, Kerr, Yann H., Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), SISMER - Service des Systèmes d'Informations Scientifiques pour la MER, Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Laboratoire d’étude des Transferts en Hydrologie et Environnement (LTHE), Centre National d'Études Spatiales [Toulouse] (CNES), Interactions Sol Plante Atmosphère (ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), and Interactions Sol Plante Atmosphère (UMR ISPA)

Subjects
[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], projet smos, acquisition de données, température de brillance
Abstract

SMOS has been delivering data since January 2010. Three ground segments have been developed among which the CATDS (Centre Aval de Traitements des Données SMOS) by the French space agency CNES [2]. This ground segment is providing the users with level 3 data that are a bit different from ESA level 1 and level 2 as these products : i) are temporally aggregated as daily, during 3-day and 10-day time window and monthly averages ii) are projected on the EASE Grid version 2 iii) using the netcdf format iv) are derived using a modified algorithm taking advantage of 3 consecutive SMOS overpasses [4] v) brightness temperatures are averaged by bin of incidence angles in the Earth reference frame, i.e. H and V polarizations. Since the beginning of the mission the algorithm to derive the SMOS data has evolved due to improvements of the models and also due to better quality SMOS brightness temperatures. A reprocessing campaign has been done in fall 2015 to deliver the entire time series (2010-spring 2015) using the latest versions of the processors and with a more accurate brightness temperatures (improved bias reconstruction). The data are available on line (http://www.catds.fr/sipad/startPage.do) through the SIPAD (Système d’Information, de Préservation et d’Accès aux Données) which is a user-friendly dissemination service that allows the users to download their own products according to their criteria (as area of interest, period of time, subset of fields...). The aim of this communication is then to present the last updates and version of the products delivered by the CATDS that is the Version 3. Derived soil moisture values are validated by comparing to SMOS level 2 and in situ measurements acquired at various climate conditions.

Published
2016

48. Soil moisture in French alpine valley using L-Band radiometer

Author

Mialon, Arnaud, Pellarin, Thierry, Lemaître, François, Richaume, Philippe, Wigneron, Jean-Pierre, Cabot, François, Kerr, Yann H., Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d’étude des Transferts en Hydrologie et Environnement (LTHE), ONERA - The French Aerospace Lab [Palaiseau], ONERA, Interactions Sol Plante Atmosphère (ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), ONERA-Université Paris Saclay (COmUE), Interactions Sol Plante Atmosphère (UMR ISPA), Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), ONERA - The French Aerospace Lab [Toulouse], and European Space Agency (ESA). INT.

Subjects
remote sensing, sonde de mesure, sensor, [SDV]Life Sciences [q-bio], télédétection, [SDE.MCG]Environmental Sciences/Global Changes, [SDE]Environmental Sciences, diffusion des résultats, température de brillance, radiometer, radiomètre, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

International audience; Since the launch of the satellite, a constant activity has been to compare SMOS derived soil moisture to in situ measurements to validate and improve the soil moisture retrieval. Many sites have been equipped with soil moisture probes and a few of them with L-Band radiometer placed on structures of ~10 m. height. The observed surfaces are homogeneous, i.e. one type of vegetation cover, whereas SMOS (~40km of resolution) observes more heterogeneous scenes, i.e. mix of different landscapes. Keeping this issue in mind, a new experimental site is proposed with the main objective to observe complex scenes to test the SMOS soil moisture retrieval. The LEWIS radiometer (L-Band radiometer for Estimating Water in Soil) has been placed by a cliff in St Hilaire du Touvet (French Alps) since May 2014. Its position allows us to monitor a surface 800m down below in the valley du Grésivaudan which is flat, avoiding topographic effect. The instrument has a beam width of 13.6° which implies a field of view of several hundreds of meters, covering various landscapes (agricultural fields, forest, lake). The instrument is equipped with 2 motors so that it moves in two directions (azimuth and elevation) and monitors regularly several areas of interest. It can also be pointed towards the deep sky for calibration. In addition, soil moisture and temperatures probes are placed in different fields in the Valley and a pyrometer is installed with the radiometer to measure the skin temperature of the observed scene. The first data confirm the consistency of Lewis measurements. The deep sky presents brightness temperatures of TBH = 5.4K et TBV = 4.3K, which is similar to what was observed at the SMOSREX site. This new site is planed to last 4 years to insure long time observations (L-band brightness temperatures and surface soil moisture) of heterogeneous scenes. Further works will also imply sun glint effect, snow detection and effect of urban areas.

Published
2016

49. Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia

Author

Brocca, Luca, Pellarin, Thierry, Crow, Wade T., Ciabatta, Luca, Massari, Christian, Ryu, Dongryeol, Su, Chun Hsu, Rüdiger, Christoph, and Kerr, Yann

Subjects
remote sensing, rainfall, soil moisture, SMOS
Abstract

Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches has the potential to improve the quality of near-real-time rainfall estimates from remote sensing in the near future.

Published
2016

50. SMOS and hydrology

Author

Kerr, Yann H., Ahmad, Al Bitar, Leroux, Delphine, Pellarin, Thierry, Molero, Beatriz, Choné, Audrey, Parrens, Marie, Wigneron, Jean-Pierre, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), and Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)

Subjects
radiométrie microonde, impact régional, télédétection, [SDE.MCG]Environmental Sciences/Global Changes, Signal and Image processing, Traitement du signal et de l'image, projet smos, Milieux et Changements globaux, donnée satellite, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

International audience; SMOS, a L Band radiometer using aperture synthesis to achieve a good spatial resolution, was successfully launched on November 2, 2009. It was developed and made under the leadership of the European Space Agency (ESA) as an Earth Explorer Opportunity mission. It is a joint program with the Centre National d’Etudes Spatiales (CNES) in France and the Centro para el Desarrollo Teccnologico Industrial (CDTI) in Spain. SMOS carries a single payload, an L band 2D interferometric, radiometer in the 1400‐1427 MHz protected band. This wavelength penetrates well through the vegetation and the atmosphere is almost transparent enabling to infer both soil moisture and vegetation water content. SMOS achieves an unprecedented spatial resolution of 50 km at L‐band maximum (43 km on average) with multi angular‐dual polarized (or fully polarized) brightness temperatures over the globe and with a revisit time smaller than 3 days. SMOS has been now acquiring data for 5.5 years. The data quality exceeds what was expected, showing very good sensitivity and stability. The data is however impaired by man‐made emission in the protected band, leading to degraded measurements in several areas including parts of Europe and of China. However, many different international teams are now addressing data use in various fields including hydrology. We have now acquired data over a number of significant “extreme events” such as droughts and floods giving useful information of potential applications. We are now working on the coupling with other models and or disaggregation to address soil moisture distribution over watersheds. We are also concentrating efforts on water budget and regional impacts. From all those studies, it is now possible to express the “lessons learned” and derive a possible way forward. This paper thus gives an overview of the water cycle science goals of the SMOS mission, a description of its main elements, and a taste of the first results including performances at brightness temperature as well as at geophysical parameters level and how they are being put in good use for hydrological applications.

Published
2015

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