soil moisture south americamauritania pronunciation sound

For more information about sharing your work with Kudos, please visit our Centro de Investigaciones del Mar y la Atmósfera, Consejo Nacional de Investigaciones Científicas y Técnicas–Universidad de Buenos Aires, UMI–Instituto Franco–Argentino sobre Estudios de Clima y sus Impactos/CNRS, Buenos Aires, Argentina Search for other works by this author on: Search for other works by this author on: A first alternative could be to compare GLDAS soil moisture variability against a well-known proxy of the water deficit/excess over land, like the standardized precipitation index (SPI). Similar results were obtained by comparing the surface soil moisture anomalies from the GLDAS land surface model (LSM) against the satellite estimations for a shorter period of time. Our underlying hypothesis is that, if GLDAS soil moisture variability corresponds well with other proxies and/or measurements—generally accepted to describe soil conditions worldwide—then this dataset can be further employed to complement other descriptions of soil moisture at the regional level, where there is a lack of reliable measurements.The evaluation of GLDAS soil moisture anomalies is carried out through their comparison with the SPI and SM-MW. For example, Given our interest to assess GLDAS over South America, where a direct and long-term validation with in situ measurements is unfeasible, we confront the following question. (Click for actual conditions) Comparing the results obtained from GLDAS-1 and GLDAS-2 (v1 and v2), it is clear that the precipitation dataset used to force the LSMs is of major relevance, followed by the impact of using different LSMs with equal atmospheric forcing. Skill and global trend analysis of soil moisture from reanalyses and microwave remote sensingLand-surface–atmosphere coupling in observations and modelsThe land surface climatology of the Community Land Model coupled to the NCAR Community Climate ModelModeling of land-surface evaporation by four schemes and comparison with FIFE observationsThe ERA-Interim reanalysis: Configuration and performance of the data assimilation systemGSWP-2: Multimodel analysis and implications for our perception of the land surfaceThe International Soil Moisture Network: A data hosting facility for global in situ soil moisture measurementsEvaluating global trends (1988–2010) in harmonized multi-satellite soil moisture dataThe Lincoln Declaration on Drought Indices: Universal meteorological drought index recommendedDrought indicators based on model assimilated GRACE terrestrial water storage observationsAnalysis of model-calculated soil moisture over the United States (1931–1993) and applications to long-range temperature forecastsAssessing vegetation response to drought in the northern Great Plains using vegetation and drought indicesThe predictability of soil moisture and near-surface temperature in hindcasts of the NCEP seasonal forecast modelSensitivity of land surface simulations to model physics, parameters, and forcings, at four CEOP sitesClimatology of water excess and shortages in the La Plata basinEvaluation of reanalysis soil moisture simulations using updated Chinese soil moisture observationsA simple hydrologically based model of land surface water and energy fluxes for GSMsOne-dimensional statistical dynamic representation of subgrid spatial variability of precipitation in the two-layer Variable Infiltration Capacity modelTrend-preserving blending of passive and active microwave soil moisture retrievalsHot days induced by precipitation deficits at the global scaleFuture changes in drought characteristics over southern South America projected by a CMIP5 ensembleThe CLARIS LPB database: Constructing a long-term daily hydro-meteorological dataset for La Plata basin, southern South AmericaToward global drought early warning capability: Expanding international cooperation for the development of a framework for monitoring and forecastingProspects for dynamical prediction of meteorological droughtForty-five years of observed soil moisture in the Ukraine: No summer desiccation (yet)Using the standardized precipitation index for flood risk monitoringInvestigating soil moisture–climate interactions in a changing climate: A reviewGlobal trends and variability in soil moisture and drought characteristics, 1950–2000, from observation-driven simulations of the terrestrial hydrologic cycleEvaluation of multi-model simulated soil moisture in NLDAS-2Evaluation of the Global Land Data Assimilation System using global river discharge data and a source-to-sink routing scheme

(Click for actual conditions) We chose this dataset because it is the only one that encompasses the whole region and is consistent in terms of statistical properties. Correlation (significant at 0.01 level; shaded) between SSMA from (left) GLDAS-2 v1 (Noah v2.7), (middle) GLDAS-1 Noah v2.7, and (right) GLDAS-1 Mosaic against SPI3 for (first row) summer [December–February (DJF)], (second row) autumn [March–May (MAM)], (third row) winter (JJA), and (fourth row) spring (SON). As the SPI does not consider important processes affecting soil moisture, like evapotranspiration or gravity drainage, a complementary multisatellite soil moisture estimation product (SM-MW) was used to improve the analysis.While doing so, it is implied that only modeled soil moisture anomalies would be evaluated against the SPI and SM-MW, since there is no possibility to compare soil moisture amounts.After validating precipitation fields used to force the LSMs, it has been shown that GLDAS-2 precipitation is in better agreement with the observations. To address this question, GLDAS-1 and GLDAS-2 precipitation fields are compared with GPCC data.

Walmart Employee Benefits Website, Used Lund 189 Pro V Gl For Sale, Le Chef Translate, Zell Am See Weather Forecast 14 Days, Pr Agency France, Woman Lake Fishing Report, ,Sitemap