scholarly journals Impact of bias correction to reanalysis products on simulations of North American soil moisture and hydrological fluxes

2003 ◽  
Vol 108 (D16) ◽  
pp. ACL 2-1-ACL 2-15 ◽  
Author(s):  
Aaron A. Berg
Keyword(s):  
Soil Moisture ◽  
North American ◽  
Bias Correction ◽  
Hydrological Fluxes

scholarly journals Potential of bias correction for downscaling passive microwave and soil moisture data

2015 ◽  
Vol 120 (13) ◽  
pp. 6460-6479 ◽  
Author(s):  
Kurt C. Kornelsen ◽  
Michael H. Cosh ◽  
Paulin Coulibaly
Keyword(s):  
Soil Moisture ◽  
Bias Correction ◽  
Passive Microwave ◽  
Soil Moisture Data

Vegetation controls on soil moisture distribution in the Valles Caldera, New Mexico, during the North American monsoon

Ecohydrology ◽  
2008 ◽  
Vol 1 (3) ◽  
pp. 225-238 ◽  
Author(s):  
Enrique R. Vivoni ◽  
Alex J. Rinehart ◽  
Luis A. Méndez-Barroso ◽  
Carlos A. Aragón ◽  
Gautam Bisht ◽  
...  
Keyword(s):  
Soil Moisture ◽  
New Mexico ◽  
North American ◽  
Moisture Distribution ◽  
North American Monsoon ◽  
Valles Caldera ◽  
The North ◽  
Soil Moisture Distribution

Observed relation between evapotranspiration and soil moisture in the North American monsoon region

2008 ◽  
Vol 35 (22) ◽  
Author(s):  
Enrique R. Vivoni ◽  
Hernan A. Moreno ◽  
Giuseppe Mascaro ◽  
Julio C. Rodriguez ◽  
Christopher J. Watts ◽  
...  
Keyword(s):  
Soil Moisture ◽  
North American ◽  
North American Monsoon ◽  
Monsoon Region ◽  
The North

scholarly journals Automated Quality Control of In Situ Soil Moisture from the North American Soil Moisture Database Using NLDAS-2 Products

2015 ◽  
Vol 54 (6) ◽  
pp. 1267-1282 ◽  
Author(s):  
Youlong Xia ◽  
Trent W. Ford ◽  
Yihua Wu ◽  
Steven M. Quiring ◽  
Michael B. Ek
Keyword(s):  
Quality Control ◽  
Soil Moisture ◽  
North American ◽  
Soil Layer ◽  
Control Procedure ◽  
Multiple Model ◽  
Quality Control Procedure ◽  
The North ◽  
Automated Quality Control

AbstractThe North American Soil Moisture Database (NASMD) was initiated in 2011 to provide support for developing climate forecasting tools, calibrating land surface models, and validating satellite-derived soil moisture algorithms. The NASMD has collected data from over 30 soil moisture observation networks providing millions of in situ soil moisture observations in all 50 states, as well as Canada and Mexico. It is recognized that the quality of measured soil moisture in NASMD is highly variable because of the diversity of climatological conditions, land cover, soil texture, and topographies of the stations, and differences in measurement devices (e.g., sensors) and installation. It is also recognized that error, inaccuracy, and imprecision in the data can have significant impacts on practical operations and scientific studies. Therefore, developing an appropriate quality control procedure is essential to ensure that the data are of the best quality. In this study, an automated quality control approach is developed using the North American Land Data Assimilation System, phase 2 (NLDAS-2), Noah soil porosity, soil temperature, and fraction of liquid and total soil moisture to flag erroneous and/or spurious measurements. Overall results show that this approach is able to flag unreasonable values when the soil is partially frozen. A validation example using NLDAS-2 multiple model soil moisture products at the 20-cm soil layer showed that the quality control procedure had a significant positive impact in Alabama, North Carolina, and west Texas. It had a greater impact in colder regions, particularly during spring and autumn. Over 433 NASMD stations have been quality controlled using the methodology proposed in this study, and the algorithm will be implemented to control data quality from the other ~1200 NASMD stations in the near future.

Long-Term Climate and Derived Surface Hydrology and Energy Flux Data for Mexico: 1925–2004

2007 ◽  
Vol 20 (9) ◽  
pp. 1936-1946 ◽  
Author(s):  
Chunmei Zhu ◽  
Dennis P. Lettenmaier
Keyword(s):  
Soil Moisture ◽  
North American ◽  
Land Surface ◽  
Surface Fluxes ◽  
The Other ◽  
Shortwave Radiation ◽  
Infiltration Capacity ◽  
Time Step ◽  
Downward Longwave Radiation

Abstract Studying the role of land surface conditions in the Mexican portion of the North American monsoon system (NAMS) region has been a challenge due to the paucity of long-term observations. A long-term gridded observation-based climate dataset suitable for forcing land surface models, as well as model-derived land surface states and fluxes for a domain consisting of all of Mexico, is described. The datasets span the period of January 1925–October 2004 at 1/8° spatial resolution at a subdaily (3 h) time step. The simulated runoff matches the observations plausibly over most of the 14 small river basins spanning all of Mexico, which suggests that long-term mean evapotranspiration is realistically reproduced. On this basis, and given the physically based model parameterizations of soil moisture and energy fluxes, the other surface fluxes and state variables such as soil moisture should be represented reasonably. In addition, a comparison of the surface fluxes from this study is performed with North American Regional Reanalysis (NARR) data on a seasonal mean basis. The results indicate that downward shortwave radiation is generally smaller than in the NARR data, especially in summer. Net radiation, on the other hand, is somewhat larger in the Variable Infiltration Capacity (VIC) hydrological model than in the NARR data for much of the year over much of the domain. The differences in radiative and turbulent fluxes are attributed to (i) the parameterization used in the VIC forcings for solar and downward longwave radiation, which links them to the daily temperature and temperature range, and (ii) differences in the land surface parameterizations used in VIC and the NCEP–Oregon State University–U.S. Air Force–NWS/Hydrologic Research Lab (Noah) land scheme used in NARR.

scholarly journals A comparison of methods for a priori bias correction in soil moisture data assimilation

2012 ◽  
Vol 48 (3) ◽  
Author(s):  
Sujay V. Kumar ◽  
Rolf H. Reichle ◽  
Kenneth W. Harrison ◽  
Christa D. Peters-Lidard ◽  
Soni Yatheendradas ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Bias Correction ◽  
A Priori ◽  
Comparison Of Methods ◽  
Soil Moisture Data
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