The Soil Moisture Active Passive (SMAP) Mission
Massachusetts Institute of Technology1, California Institute of Technology2, Goddard Space Flight Center3, Agricultural Research Service4, Ohio State University5, University of Montana6, University of Michigan7, United States Department of Agriculture8, University of California, Santa Barbara9, University of Washington10
06 May 2010-Vol. 98, Iss: 5, pp 704-716
TL;DR: The Soil Moisture Active Passive mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey to make global measurements of the soil moisture present at the Earth's land surface.
Abstract: The Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey SMAP will make global measurements of the soil moisture present at the Earth's land surface and will distinguish frozen from thawed land surfaces Direct observations of soil moisture and freeze/thaw state from space will allow significantly improved estimates of water, energy, and carbon transfers between the land and the atmosphere The accuracy of numerical models of the atmosphere used in weather prediction and climate projections are critically dependent on the correct characterization of these transfers Soil moisture measurements are also directly applicable to flood assessment and drought monitoring SMAP observations can help monitor these natural hazards, resulting in potentially great economic and social benefits SMAP observations of soil moisture and freeze/thaw timing will also reduce a major uncertainty in quantifying the global carbon balance by helping to resolve an apparent missing carbon sink on land over the boreal latitudes The SMAP mission concept will utilize L-band radar and radiometer instruments sharing a rotating 6-m mesh reflector antenna to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days In addition, the SMAP project will use these observations with advanced modeling and data assimilation to provide deeper root-zone soil moisture and net ecosystem exchange of carbon SMAP is scheduled for launch in the 2014-2015 time frame
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TL;DR: The International Soil Moisture Network (ISMN) as discussed by the authors is a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users.
Abstract: . In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu ) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status May 2011), the ISMN contains data of 19 networks and more than 500 stations located in North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.
914 citations
TL;DR: A retrieval algorithm to deliver global soil moisture (SM) maps with a desired accuracy of 0.04 m3/m3 is given, discusses the caveats, and provides a glimpse of the Cal Val exercises.
Abstract: The Soil Moisture and Ocean Salinity (SMOS) mission is European Space Agency (ESA's) second Earth Explorer Opportunity mission, launched in November 2009. It is a joint program between ESA Centre National d'Etudes Spatiales (CNES) and Centro para el Desarrollo Tecnologico Industrial. SMOS carries a single payload, an L-Band 2-D interferometric radiometer in the 1400-1427 MHz protected band. This wavelength penetrates well through the atmosphere, and hence the instrument probes the earth surface emissivity. Surface emissivity can then be related to the moisture content in the first few centimeters of soil, and, after some surface roughness and temperature corrections, to the sea surface salinity over ocean. The goal of the level 2 algorithm is thus to deliver global soil moisture (SM) maps with a desired accuracy of 0.04 m3/m3. To reach this goal, a retrieval algorithm was developed and implemented in the ground segment which processes level 1 to level 2 data. Level 1 consists mainly of angular brightness temperatures (TB), while level 2 consists of geophysical products in swath mode, i.e., as acquired by the sensor during a half orbit from pole to pole. In this context, a group of institutes prepared the SMOS algorithm theoretical basis documents to be used to produce the operational algorithm. The principle of the SM retrieval algorithm is based on an iterative approach which aims at minimizing a cost function. The main component of the cost function is given by the sum of the squared weighted differences between measured and modeled TB data, for a variety of incidence angles. The algorithm finds the best set of the parameters, e.g., SM and vegetation characteristics, which drive the direct TB model and minimizes the cost function. The end user Level 2 SM product contains SM, vegetation opacity, and estimated dielectric constant of any surface, TB computed at 42.5°, flags and quality indices, and other parameters of interest. This paper gives an overview of the algorithm, discusses the caveats, and provides a glimpse of the Cal Val exercises.
846 citations
Cites background from "The Soil Moisture Active Passive (S..."
...L-Band seemed the best way to go, and as soon as tractable solutions became possible for the antenna, the SMOS [27], [28], Aquarius [29], and SMAP [30], [31] concepts emerged....
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Vienna University of Technology1, Centre national de la recherche scientifique2, European Centre for Medium-Range Weather Forecasts3, National Research Council4, ETH Zurich5, Finnish Meteorological Institute6, Nanjing University of Information Science and Technology7, Ghent University8, VU University Amsterdam9, University College Cork10, Starlab11
TL;DR: The European Space Agency (ESA) released the first multi-decadal, global satellite-observed soil moisture (SM) dataset as part of its Climate Change Initiative (CCI) program.
756 citations
Princeton University1, Utrecht University2, Goethe University Frankfurt3, University of California, Irvine4, National Center for Atmospheric Research5, Delft University of Technology6, George Mason University7, University of Bonn8, McGill University9, University of Washington10, Goddard Space Flight Center11, University of Illinois at Urbana–Champaign12, University of Reading13, University of Oxford14
TL;DR: In this article, the authors discuss the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles, and they call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.
Abstract: Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface-subsurface interactions due to fine-scale topography and vegetation; improved representation of land-atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.
704 citations
TL;DR: In this article, the authors presented an approach for combining four passive microwave products from the VU University Amsterdam/National Aeronautics and Space Administration and two active microwave items from the Vienna University of Technology.
637 citations
References
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TL;DR: In this article, a change detection algorithm has been developed in order to obtain high-resolution soil moisture estimates from future Soil Moisture Active and Passive (SMAP) L-band radar and radiometer observations.
Abstract: A change detection algorithm has been developed in order to obtain high-resolution soil moisture estimates from future Soil Moisture Active and Passive (SMAP) L-band radar and radiometer observations. The approach combines the relatively noisy 3-km radar backscatter coefficients and the more accurate 36-km radiometer brightness temperature into an optimal 10-km product. In preparation for the SMAP mission, an observation system simulation experiment (OSSE) and field experimental campaigns using the Passive and Active L- and S-band Airborne Sensor (PALS) have been conducted. We use the PALS airborne observations and OSSE data to test the algorithm and develop an error budget table. When applied to four-month OSSE data, the change detection method is shown to perform better than direct inversion of the radiometer brightness temperatures alone, improving the root mean square error by 2% volumetric soil moisture content. The main assumptions of the algorithm are verified using PALS data from the soil moisture experiments held during June-July 2002 (Soil Moisture Experiment 2002) in Iowa. The algorithm error budget is estimated and shown to meet SMAP science requirements.
136 citations
TL;DR: A simple parameterization that is based on a single roughness parameter was calibrated in order to account for this angular and polarization dependencies and is suitable for soil moisture retrieval from Soil Moisture and Ocean Salinity data.
Abstract: A simple reflectivity model of a bare soil at L-band is developed to account for the effects of soil roughness at different angles and polarizations. This model was developed using a long-term dataset acquired over the bare soil in the framework of the Surface Monitoring Of the Soil Reservoir EXperiment (SMOSREX). It is shown that the roughness effects are different depending on the measurement configuration, in terms of incidence angle and polarization. However, in this paper, a simple parameterization that is based on a single roughness parameter was calibrated in order to account for this angular and polarization dependencies. This parameter was found to be dependent on soil moisture: drier conditions were associated to higher ldquoroughnessrdquo conditions. The root-mean-square error between the measured and modeled reflectivities on days when no precipitation events were detected at vertical polarization (V-pol) is 0.0275, and at horizontal polarization (H-pol), the rmse is 0.0237; all incidence angles were considered. When all data are considered, the rmsd for V-pol is 0.0350, and for H-pol, the rmse is 0.0373. This new simple model is suitable for soil moisture retrieval from Soil Moisture and Ocean Salinity data. By means of this simple parameterization, almost two years of soil moisture data were retrieved with a good accuracy. The SMOSREX dataset allowed to ensure a long-term suitability of the proposed parameterization.
126 citations
"The Soil Moisture Active Passive (S..." refers methods in this paper
...Corrections for surface roughness are performed as rp smooth 1⁄4 rp rough= expð hÞ where the parameter h is a function of the root mean square (rms) surface heights [31]....
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TL;DR: In this paper, the authors used an imaging microwave radiometer operating at a frequency of 1.42 GHz to study the drydown of the soil following heavy rain and to map its spatial variation.
Abstract: HAPEX (Hydrologic Atmospheric Pilot Experiment), FIFE (First ISLSCP Field Experiment) and MONSOON 90 which used an imaging microwave radiometer operating at a frequency of 1.42 GHz are reported. For FIFE and MONSOON 90, a wide range of moisture conditions were present and it was possible to observe the drydown of the soil following heavy rain and to map its spatial variation. The quantitative agreement of microwave observations and ground measurements was very good. In HAPEX there were no significant rains and conditions were generally rather dry, however, moisture variations due to irrigation were observed.
118 citations
"The Soil Moisture Active Passive (S..." refers background in this paper
...[13] T....
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...In the 1980s and early 1990s, an instrument called the Push Broom Microwave Radiometer (PBMR) provided the capability to map larger domains, which facilitated the observation of a wider range of conditions [13]....
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TL;DR: In this paper, the performance of the passive and active L and S band sensor (PALS) along with physical variables measured by in situ sampling have been used to demonstrate the sensitivity of the instrument to soil moisture and perform soil moisture retrieval using statistical regression and physical modeling techniques.
114 citations
"The Soil Moisture Active Passive (S..." refers background in this paper
...[20] U....
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...These include SGP99 [19], SMEX02 [20], CLASIC [21], and SMAPVEX08....
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TL;DR: In this paper, the authors used a temporal change detection analysis of NSCAT daily radar backscatter measurements to characterize the 1997 seasonal spring thaw transition period across the 106 km2 BOREAS study region of central Canada.
96 citations