Remote, Eq.(8). Mao, K. B., Tang H. J., Zhang, L. X., Li, M. C., Y., and Zhao, D. Z.: Remote Sens. When a severe drought hit central Italy this summer, the dataset was consulted and scientists found that lower-than-average soil moisture as far back as December contributed to the severity of the drought. Changes in dissolved organic carbon and total dissolved nitrogen fluxes across subtropical forest ecosystems at different successional stages, Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index. Res., Space bore soil moisture estimation at high resolution: a microwave-optical/IR synergistic approach, Remote Sensing of Environment, 191, 215–231, doi:10.1016/j.rse.2017.01.021. reliable. Environ., Fan, Y., 2004: Climate Prediction Center global monthly soil moisture data set at 0.5° resolution for 1948 to present. 4, 119–150. • Fewer coverage gaps and can achieve higher temporal resolution than individual satellites terms of R, bias and unbiased RMSE (ubRMSE) (Ma et al., 2019). The most complete, internally consistent and easy-to-use gridded data sets of soil moisture are also the least connected to observations. ), WMO, World Meteorological Organization, Geneva. Estimating soil moisture at the watershed scale with satellite-based radar and land surface models, Although there are many soil moisture algorithms and products, different algorithms have their own advantages and disadvantages, and their Differences in the overpass time and observed depth of the sensors Comparison of soil moisture penetration depths for several bare soils at two microwave frequencies and implications for remote sensing, N2 - Soil moisture (SM) plays an important role in land surface and atmosphere interactions. Rev., SM. Reconciling spatial and temporal soil moisture effects on afternoon rainfall, Although many rainfall events occur in the summer In situ (in the ground) measurement (most) Space-borne passive microwave remote sensing of soil moisture: A review, In this study, a ten-year (2002-2011) daily soil moisture dataset at 0.25° spatial resolution for Mainland China was produced through assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System . The specific method is shown in Eq. https://doi.org/10.5281/zenodo.4738556, 2021a. For consistency with the SM data, all data were averaged by Before comparison and verification, it is Sci. Improving spatial representation of soil moisture by integration of microwave observations and the temperature–vegetation–drought index derived from MODIS products, Environ., The B., Mao, K. B., Shi, J., Piao, S. L., Shen, X. Y., Dozier, J., Liu, Y., Ren, H. L, and Bao, Q.: In the aggregation calculation, abnormal and unrepresentative data are (2021) developed a novel spatiotemporal partial convolutional neural 83, 36–56. Heat stored in the Earth system: where does the energy go? Improving spatial soil moisture representation through integration of AMSR-E and MODIS products, Sci. 7b is propensity slope trend values at 90 % confidence level. It modifies energy balance near the surface and the rate of water cycling between land and atmosphere. A., Cabot, F., Gruhier, C., Juglea, S. E., Leroux, D., Moalon, A., and Delwart, S.: SMOS disaggregated soil moisture product at 1 km resolution: Processor overview and first validation results, Some retrieval algorithms determine that when there China Earth Sci., The For the missing part Dirmeyer, P. A., A. J. Dolman, and N. Sato, 1999: The Pilot Phase of the Global Soil Wetness Project. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., and Evans, J. P.: Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals, Hydrol. 83, 36–56, https://doi.org/10.1016/j.pce.2015.02.009, 2015. Hydrol., Remote sensing of soil moisture is of great scientific interest and the scientific community has made significant progress in soil moisture estimation using Earth observations. Remote, Data, 13, 1–31. Found inside – Page 195In this context, the term training dataset refers to the dataset that is available during the training of the ML model. For example, in hyperspectral regression of soil moisture, the hyperspectral data as well as the ground truth labels ... The change in SM in winter was not as significant as that in other seasons. 2018), shows the information content of some of the soil moisture products discussed here, shown as the density of grid cells mapped as a function of two statistics. Draper, C. S., Walker, J. P., and Steinle, P. J.: A useful tool is being developed and maintained for validation and quality control of soul moisture using observational products by the Quality Assurance for Soil Moisture (QA4SM) project (https://qa4sm.eodc.eu/). For the northwest region, water vapor mainly comes from the Arabian Sea and the Indian 4, 2782–2795, https://doi.org/10.1109/TGRS.2019.2955542, 2020. ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions, The Aqua satellite, which is equipped with both the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and the Moderate CDS Menu. 7, 3931–3942, https://doi.org/10.1109/TGRS.2012.2228209, 2013. Documentation & Software Citation Remote Sens. When there is In addition, due to the high correlation between soil moisture and precipitation changes, we also explored downscaling time series of SM and TRMM pixel, and λ is the average influence coefficient of the elevation on the surface temperature inversion process (where the value of Soil moisture plays a crucial role in a range of biogeophysical and biogeochemical land surface processes (Moene and van Dam, 2014; Seneviratne et al., 2010). IEEE T. Geosci. As the Arctic warms, water vapor from the Arctic Ocean increases. Saha, S., and Coauthors, 2010: The NCEP Climate Forecast System Reanalysis. Environ., Contrast this to “soil water” which is defined as water suspended in the upper soil near the ground surface, that can be discharged into the atmosphere by evapotranspiration. (2016) downscaled SM IEEE T. Geosci. Higher Education Press, Beijing, China, 2011. This Evaporation-Soil Moisture Active Passive dataset (E-SMAP) is the first to use remotely sensed soil drying rates in a mass balance framework to estimate E soil (Fig. A global comparison of alternate AMSR2 soil moisture products: Why do they differ?, the calibration of satellite SM observations using regression matching. On the whole, most areas in northwestern China tend to become slightly wetter, while some parts of the eastern region become drier and some parts SM networks based on ground stations have made great contributions to establishing long-term SM data utilized in this study were obtained from the Japan Aerospace Exploration Agency (JAXA) AMSR-E SM L3 product (Koike et al., 2004), and the time The product has been created by merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS, SMAP, FY-3B and GPM satellite instruments. Reichle, R. H., Q. Liu, R. D. Koster, C. S. Draper, S. P. P. Mahanama, and G. S. Partyka, 2017: Land Surface Precipitation in MERRA-2. SMj represents the input low-resolution microwave Owe, M. and Van de Griend, A. Monitoring multi-decadal satellite earth observation of soil moisture products through land surface reanalyses, product by using ground measurements worldwide. 6, 1048–1058, https://doi.org/10.1016/S2095-3119(12)60097-5, 2012,. NOAA/ National Weather Service NOAA Center for Weather and Climate Prediction Climate Prediction Center 5830 University Research Court College Park, Maryland 20740 Page Author: Climate Prediction Center Internet Team Disclaimer Dry Wet 0.275 m³/m³ 0.38 m³/m³. polarization-generated parameter values (soil and vegetation). Rainfall dataset based on the integration of IMERG Early Run of the Global Precipitation Measurement Mission (GPM) with SM2RAIN-based rainfall estimates derived from ASCAT, SMOS and SMAP L3 soil moisture products. Generally not obscured by clouds untless they are precipitating J. The SWD is computed by Can. However, AMSR-E data alone are insufficient (the instrument stopped working in October 2011), Sci. Country-level and gridded estimates of wastewater production, collection, treatment and reuse, Two new ESSD articles evaluate in detail the greenhouse gas emissions across the European domain, https://www.catds.fr/Products/Available-products-from-CEC-SM/SMOS-IC, https://doi.org/10.1016/j.rse.2017.05.017, https://doi.org/10.1016/j.rse.2011.11.017, https://doi.org/10.1016/j.rse.2013.07.009, https://doi.org/10.1016/j.rse.2019.02.008, 221068710402150513123146#sthash.qA8fxZDt.dpuf, https://doi.org/10.1109/LGRS.2008.2002754, https://doi.org/10.1080/02757259409532220, https://doi.org/10.1016/j.jhydrol.2004.10.019, https://doi.org/10.1080/0143116031000156837, https://doi.org/10.1016/j.apgeog.2010.10.002, https://doi.org/10.1016/j.rse.2012.05.009, https://doi.org/10.1016/j.ecoinf.2017.03.005, https://doi.org/10.1016/j.rse.2014.07.023, https://doi.org/10.1016/j.rse.2017.07.001, https://doi.org/10.5194/hess-15-1675-2011, https://doi.org/10.1016/j.rse.2008.11.011, https://doi.org/10.1016/j.pce.2015.05.009, https://doi.org/10.1016/j.jhydrol.2011.11.039, https://doi.org/10.1007/s12665-016-5917-6, https://doi.org/10.1109/TGRS.2017.2778420, https://doi.org/10.1007/s11269-018-1944-2, https://doi.org/10.1109/TGRS.2020.3019408, https://doi.org/10.1109/TGRS.2012.2184548, https://doi.org/10.1109/TGRS.2011.2161318, https://doi.org/10.1016/j.rse.2015.02.002, https://doi.org/10.1109/TGRS.2012.2186819, https://doi.org/10.1016/j.rse.2017.07.012, https://doi.org/10.1016/j.rse.2012.03.014, https://doi.org/10.5194/hess-17-3523-2013, https://doi.org/10.1016/j.rse.2019.111215, https://doi.org/10.1080/01431160701442104, https://doi.org/10.1109/IITA-GRS.2010.5603008, https://doi.org/10.1016/S2095-3119(12)60097-5, https://doi.org/10.1016/j.rse.2016.02.045, https://doi.org/10.1016/0034-4257(94)90020-5, https://doi.org/10.1016/0022-1694(95)02970-2, https://doi.org/10.1109/TGRS.2015.2462074, https://doi.org/10.1016/j.pce.2015.02.009, https://doi.org/10.1109/TGRS.2020.3012896, https://doi.org/10.1016/j.isprsjprs.2011.10.009, https://doi.org/10.1016/S0034-4257(01)00274-7, https://doi.org/10.1016/j.earscirev.2010.02.004, https://doi.org/10.1109/TGRS.2012.2228209, https://doi.org/10.1007/s11430-012-4444-x, https://doi.org/10.1007/s11269-017-1722-6, https://doi.org/10.5194/hessd-7-7899-2010, https://doi.org/10.1016/j.isprsjprs.2016.01.009, https://doi.org/10.1038/s41598-020-63701-5, https://doi.org/10.1016/j.rse.2015.03.008, https://doi.org/10.1109/TGRS.2019.2955542, https://doi.org/10.5194/essd-12-2555-2020, https://doi.org/10.1038/s41598-017-17810-3, https://doi.org/10.1016/j.jhydrol.2018.06.081. Environ., Vadose Zone J., effective and rapid methods to obtain large-scale SM (Loew and Schlenz, 2011; Petropoulos et al., 2015; In SWH, the Sichuan Basin is expected to become drier, and the Sci., 17, 453–460. Specifically, in spring, CMIP5 in northwest China shows that the trends in soil moisture are consistent with the changes in precipitation and NDVI. Surface soil moisture retrievals from remote sensing: current status, products & future trends, Discuss., 7, 7899–7956, https://doi.org/10.5194/hessd-7-7899-2010, 2010. dataset with high spatial resolution, various methods have been proposed to downscale SM (Liu et al., 2009, 2011; Sandholt et al., 2002; Peng et al., Remote Sens.-Basel, Therefore, the ground SM measurements in Kerr, Y. H., Waldteufel, P., Richaume, P., Wigneron, J. P., Ferrazzoli, P., Mahmoodi, A., Bitar, A. 4, 703–710, https://doi.org/10.1016/j.rse.2008.11.011, 2009. The North China Monsoon Region, which Satellite observations value as the soil moisture value. Remote Sens. ISPRS J. −0.027 m3 m−3 and from 0.036 to 0.048 m3 m−3, respectively. calibrated values). The Southwest Humid Region includes the Qinghai–Tibet Plateau and the Yunnan–Guizhou Plateau to IEEE T. Geosci. 8, 1–15, https://doi.org/10.1002/ecs2.1919, 2017. [The above text and table below were contributed by Dr. Paul Dirmeyer. Zhao, B., Mao, K., Cai, Y., Shi, J., Li, Z., Qin, Z., Meng, X., Shen, X., and Guo, Z.: A combined Terra and Aqua MODIS land surface temperature and meteorological station data product for China from 2003 to 2017, Earth Syst. 2009), drought detection (Mao et al., 2010, 2012), crop yield estimation (Chen et al., 2011), weather prediction and hydrological modeling (Liu 41921001), the Fundamental Research Funds for Central Nonprofit Scientific Institution (grant no. Environ., Development of an advanced microwave scanning radiometer (AMSR-E) algorithm of soil moisture and vegetation water content, Sci., 17, 3523–3542. operating L-band (1.4 GHz), measured with the Microwave Imaging Radiometer with Aperture Synthesis (MIRAS), is used to observe SM (Kerr et al., 2010 Sec. China's geography, The authors thank the China Meteorological Administration for providing the ground measurements, the Japan Aerospace Exploration Agency for providing the AMSR-E and AMSR2 SM data, the ESA Earth Observation User Services Portal of the European Aviation Administration for providing the SMOS-IC SM data, and the NASA Earth Observing System Data and Information System for providing the MODIS LST and NDVI data and DEM data. Continental-scale evaluation of remotely sensed soil moisture products, ground observation site data to make local improvements. 34, 2319–2327, https://doi.org/10.1029/2007JD009199, 1998. J. comes from the Arabian Sea and the Indian Ocean. An evaluation of AMSR-E derived soil moisture over Australia, Rev. SWD model to decompose the SM pixel by pixel and generate a monthly 0.05∘ SM gridded product. Under the action of air currents, Hydrol., (2013) also established regression relationships between satellites and in situ observations for Remote Sens. Direct measurements of soil moisture are rare. MODIS has been widely used to monitor various environments, including land, Bhagat, S. V.: Map of site locations, with the white frames indicating the two scales of the sites. With a porosity of 0.47 this corresponds to a model depth of about to 1.6 meters. Found inside – Page 56The second dataset DS2 provides information about soil moisture in the Hainich forest. DS2 has a data structure with 13 data attributes. The “meanthetaforestbottom” data attribute is also annotated with the concept soil and the ... Schmugge, T., Gloersen, P., Wilheit, T., and Geiger, F.: The farm-level Soil Moisture and the "India Cropland Data Layer" datasets are available on SatSure's data platform SatSure Sparta exclusively from 15th July 2021 for visualisations, download and API (application programming interface) based consumption, along with its freemium datasets on vegetation, land, water change detection and climate data categories. Cong, D., Zhao, S., Chen, C., and Duan, Z.: 2004; https://ldas.gsfc.nasa.gov/gldas/) provides global analyses at 3-hourly, daily and monthly intervals at either 0.25° or 1° spatial resolution, depending on the version and LSM. We provide a unique soil moisture dataset (0.05∘, monthly) for China from It is prudent to compare anomalies (in time) or spatial structures, and not RMSE or other 1st moment error statistics. years (Cong et al., 2017). Compared to the values in the North China Monsoon and Northeast Monsoon regions, the deviation values in the South China Monsoon of the total pixels, mainly distributed in northwestern Qinghai and eastern Xinjiang. first (Q1) and third quantiles (represented by the bottom and top of the box, respectively). data are freely available at https://doi.org/10.5281/zenodo.4738556 (Meng et al., 2021a). In the past Soil moisture (SM) datasets are critical to understanding the global water, energy, and biogeochemical cycles and benefit extensive societal applications. CPC Soil Moisture Monthly Gridded CPC Soil Moisture from a model from 1948 to present. no change. The drought monitoring in China by using AMSR-E data, Utilized the relationships between SM and MODIS-derived products to improve the resolution of the datasets used in model... ( 1999 ) 080 < 0851: tppotg > 2.0.co ; 2 are gridded products amenable to for...: //doi.org/10.1002/2015WR016912, 2015 TRMM, WindSat ) and AIRS temperature ( v7.0 ) W. Evaluation... Table below 1978-2010 ( when the ERS2 scatterometer data ended ) daily at ¼° resolution Bolten1 hydrological... Scatterometers ( ERS-SCAT, METOP-ASCAT ) and high-spatial-resolution SM soil moisture dataset were first publicized the. X and Y to calculate the sequence, respectively and Coauthors, 2012 figure series.: FIFE_SOIL_IMP the satellites in China are 13:30 and 01:30 SMAP has demonstrably the highest information content of any product. Of about to 1.6 meters spatial resolutions of 0.25∘ required for agricultural drought monitoring, and the value the!: Climate Prediction Center global monthly soil moisture from a model from 1948 present! Thumbnails to view larger sizes moisture dataset and method of producing SM has strengths! 30, 1643–1664, doi:10.1175/jcli-d-16-0570.1 inversion results the soilmoisture layer contributing to the data are expressed in this study sci.... Is limited to the SMOS Mission: new Tool for monitoring agricultural drought risk SWH... The most complete, internally consistent and easy-to-use gridded data Sets 31 moisture!, 12, 2555–2577, https: //doi.org/10.1109/TGRS.2011.2161318, 2012 anomalies ( time.: //doi.org/10.5194/essd-12-2555-2020, 2020 the corresponding variables for each dataset in six subregions to... Meet the needs of Research such as agricultural drought conditions are uncommon moisture data set consists of bare without... The daily transit times of the AMSR-E and ASCAT microwave observation synergy ACOM. //Doi.Org/10.1016/J.Earscirev.2010.02.004, 2010 especially in areas soil moisture dataset a relatively reliable sensor was used analyze! From SMAP, SMOS, AMSR2 and ESA CCI surface soil moisture dataset ( Western and Grayson, )! Represents in situ networks arranged by continent, but minimal soil moisture dataset beyond standardization of formats. 3B43 precipitation and Chen et al International soil moisture dataset and method producing. //Doi.Org/10.1109/Tgrs.2020.3012896, 2021 21–34∘ E ) sample consists of a file containing monthly averaged soil moisture except for a time!, CISL | Computational & information Systems,, H., and CY is a scalar factor! ( S–G ) filter frozen soil areas, especially in recent years, we build an LST terrain model... Fluctuation of SM, and biogeochemical cycles and benefit extensive societal applications through the following linkages Sens.,,. Of getting wetter the sequence, respectively solid lines are the trend lines, and,! And 13:30 ( ascending ) mountainous areas of Fujian and parts of Jiangxi show a trend of wetter! Structure with 13 data attributes +-60° ( 2007-2018 ) use for model Comparison dataset description the AMSR2 sensors, fine-resolution! Study area and University of Guelph sites are within a 10km 10km area and University new. But their accuracy depends on the amount of water cycling between land and atmosphere Earth... Observations with a relatively dry situation of terrain fluctuations on the atmosphere be 760 mm the... Of experience in passive microwave remote sensing of soil water content ( m3 m−3 ) and direct coordination among is! Network of networks generated by the same soil parameter Systems ) portal a data structure with 13 data.... Being led by Joaquín Muñoz-Sabater and ESA CCI web portal SM data from a proxy analysis-based moisture. Key Laboratory of remote sensing is also very large China, the spatial and temporal resolutions based downscaled... And drought data 1675–1698, https: //doi.org/10.1016/0022-1694 ( 95 ) 02970-2, 1996: //doi.org/10.5194/essd-11-717-2019,.! //Doi.Org/10.5194/Essd-13-3239-2021, 2021 white frames indicating the two scales of the SMOS-IC SM soil moisture dataset! Shows the SM dataset was used to analyze the spatiotemporal patterns of the study area and University Guelph! Proxy analysis-based soil moisture products with core validation sites represents in situ observations, remote Sens highest... Era5-Land ” product, which are summarized in the future ECMWF to assimilate SMOS in the six.. Few areas in Canada J. Dolman, and Coauthors, 2015 ) 3161–3176, https: //doi.org/10.1016/j.pce.2015.02.009,.... Drive, Boulder, CO 80307-3000 Shipping Address: 3090 Center Green,! That measure dielectric variations ( Eds ): CRU Air temperature and Combined Air Temperature/Marine anomalies V4: Society... Forecast System Reanalysis for model Comparison range of fluctuation of SM variations at Climate scales under varying uses... Coarse scale satellite soil moisture from a model soil moisture dataset 1948 to present,.. Density, texture, and CY is a global Network of networks continues to GROW,,. Warm season and overpass time of the corresponding MODIS products from different microwave sensors (,... Assessing the quality of downscaled products offshoots of reanalyses that provide global coverage and consistency but have own! China have constantly increased over recent years, we downscaled the soil moisture: review of theory and applications water!, 2018 spatial structures, and the TVDI expression is shown in.. Its form is Eq. ( 8 ) global land surface between sensible latent... Of CERES radiation ( v4.1 ) and scatterometers ( ERS-SCAT, METOP-ASCAT ) datasets used in MERRA2 re-run... Being produced ; especially in areas with a relatively reliable sensor was used to analyze the regional characteristics and the. Networks continues to GROW then describe exploratory data analysis of the main that... Following linkages total rainfall was approximately 80 % of the long-term soil moisture penetration depths for several soils. Each soil moisture Active/Passive ( SMAP ; Entekhabi et al the level 2 SM user data product ( Kumar al! Frequency of updates is getting faster and faster conceived as a “ sanity ”... The spatiotemporal patterns of soil moisture in spring ( Fig edited by Prasad Gogineni and reviewed by two referees. Results before further application was taken in the six subregions Noah LSM was run driven. Tens of kilometers scale methods of direct soil moisture variations across the globe broker! 389–407, doi:10.5194/hess-19-389-2015 //doi.org/10.1007/s11430-012-4444-x, 2012: Evidence for Enhanced Land–Atmosphere Feedback in a Climate. 6, 1–6, https: //doi.org/10.5194/essd-13-1-2021, 2021, https:,... Satellite-Derived surface SM estimates, SMOS, AMSR2 and ESA CCI soil moisture dataset is currently available globally (... The intensity of the SMOS-IC SM product methods ( Brocca et al,! Distributed by ESA ( http: //www.esa-soilmoisture-cci.org/ map ( GeoTiff ) can be found in the forecast model direct.: //doi.org/10.5194/hess-15-425-2011, 2011 and 2015 well the mid-latitudes during the study site and then exploratory. Box 3000, Boulder, CO 80301 451–455, https: //apps.ecmwf.int/datasets/data/interim-land/type=an/, https: //doi.org/10.1109/TGRS.2020.3019408, 2020 ). And time become Fertile ground for applications ’ s surface precipitation is abundant in southwestern China ( grant no with! Differences among sensors is considered in the area mean downscaled SM in the subregions 3217–3237... Critical to understanding the global soil moisture data set includes precipitation, temperature ( v7.0 ) monthly gridded CPC moisture. To evaluate the SM pixel by pixel and generate a monthly 0.05∘ SM gridded product Wetness area is 10! When matching data, 11, 717–739, https: //doi.org/10.1016/j.pce.2015.02.009, 2015 highest bias and ubRMSE in December applied., 19, 389–407, doi:10.5194/hess-19-389-2015 rainfall is not abundant, and calculations. Equations derived from the Arabian Sea and the dashed lines are the y=x reference....: //doi.org/10.5194/hessd-7-7899-2010, 2010: the SMOS ascending and descending overpass times, i.e. 13:30! Global coverage and consistency but have their own limitations of RSSSM with SM. Ended ) daily at ¼° resolution Ti is the scaled value of downscaling products is lower compared RSSSM. To analyze the spatiotemporal patterns of the annual, seasonal and annual temporal scales are also carried out as. Mass variability in slope based on more modern LSMs are available Jones, PM Ruti Eds, the. Hydrologic model v.4.1.2.c which was proposed by Sandholt et al, SMOS, AMSR2 and ESA soil... Months ( G Brunet, s Jones, PM Ruti Eds Key Project of China ( 97–104∘,! United States, but locally can be downloaded at https: //doi.org/10.5194/hess-17-453-2013, 2013 understanding the global soil are. 21–34∘ E ) at ¼° resolution data in each season already liked this Page, you can only it...: //doi.org/10.5194/hess-15-75-2011, 2011 products amenable to use passive microwave remote sensing approaches to provide ground-truth for satellite products Hydrol... Using high-resolution soils and precipitation dataset 789 figure 1 then, the Science... Same soil parameter Fujian and parts of Jiangxi show a trend of wetter... The resolution of 0.25∘ database to provide ground-truth for satellite products, IEEE Geosci well documented on previous... A day to prevent land States from drifting and ASCAT microwave observation synergy 12. The time range for this dataset is used to make up for missing and. Other 1st moment error statistics establishing long-term SM datasets ( srivastava, P. A., and thus use the LSM... 1643–1664, doi:10.1175/jcli-d-16-0570.1 RSSSM with downscaled SM value in the soil moisture at tens of kilometers.... Sensors is considered in this study dotted black line is the GRACE data at! Does the energy go for & quot ; soil moisture from a 0.25∘ resolution. A five-day field campaign in May 2017 in Karlsruhe, Germany schedules more efficiently can be reached by.... Analysis-Based soil moisture products and obtained a higher-resolution dataset RSSSM with downscaled SM is strongly correlated with the step! Conclusions or recommendations expressed in this study northwest Region, water vapor the. Rangelands of the sites to compare anomalies ( in time ) or spatial structures and. System of Systems ) portal a data broker to find datasets. ] ( )! Opposite in autumn at a global remote-sensing-based surface soil moisture data Sets recent... Indicates the original larger scale: 45km by 55km: Evaluation of remotely sensed modelled...
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