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

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.

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Automated Quality Control Procedure for the "Water Equivalent of Snow on the Ground" Measurement

Journal of Applied Meteorology ◽

10.1175/1520-0450-34.1.143 ◽

1995 ◽

Vol 34 (1) ◽

pp. 143-151 ◽

Cited By ~ 13

Author(s):

Thomas W. Schmidlin ◽

Daniel S. Wilks ◽

Megan McKay ◽

Richard P. Cember

Keyword(s):

Quality Control ◽

Snow Water Equivalent ◽

Data Entry ◽

The United States ◽

Control Procedure ◽

Quality Control Procedure ◽

Ground Measurement ◽

Snow Water ◽

Automated Quality Control ◽

High Winds

Abstract Snow water equivalent (SWE) has been measured daily by the United States National Weather Service since 1952, whenever snow depth is 2 in. (5 cm) or greater. These data are used to develop design snow loads for buildings, for hydrological forecasting, and as an indicator of climate change. To date they have not been subjected comprehensively to quality control. An automated quality control procedure for these data is developed here, which checks daily SWE values for common data entry errors, values beyond reasonable limits, and consistency with daily precipitation and estimated melt. Potential effects of drifting in high winds and of the intrinsic microscale variability of SWE are also considered. An SWE measurement is declared suspicious if a sufficient discrepancy is found with respect to the expected SWE. Data values flagged as potential errors are checked manually. Results of applying the procedure to available SWE data from the northeastern UnitedStates are also summarized.

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Global Automated Quality Control of In Situ Soil Moisture Data from the International Soil Moisture Network

Vadose Zone Journal ◽

10.2136/vzj2012.0097 ◽

2013 ◽

Vol 12 (3) ◽

pp. vzj2012.0097 ◽

Cited By ~ 198

Author(s):

W.A. Dorigo ◽

A. Xaver ◽

M. Vreugdenhil ◽

A. Gruber ◽

A. Hegyiová ◽

...

Keyword(s):

Quality Control ◽

Soil Moisture ◽

Soil Moisture Data ◽

Automated Quality Control

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Quality Control and Evaluation of the Observed Daily Data in the North American Soil Moisture Database

Journal of Meteorological Research ◽

10.1007/s13351-019-8121-2 ◽

2019 ◽

Vol 33 (3) ◽

pp. 501-518 ◽

Cited By ~ 1

Author(s):

Weilin Liao ◽

Dagang Wang ◽

Guiling Wang ◽

Youlong Xia ◽

Xiaoping Liu

Keyword(s):

Quality Control ◽

Soil Moisture ◽

North American ◽

The North ◽

Daily Data

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The North American Soil Moisture Database: Development and Applications

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-13-00263.1 ◽

2016 ◽

Vol 97 (8) ◽

pp. 1441-1459 ◽

Cited By ~ 54

Author(s):

Steven M. Quiring ◽

Trent W. Ford ◽

Jessica K. Wang ◽

Angela Khong ◽

Elizabeth Harris ◽

...

Keyword(s):

Soil Moisture ◽

North American ◽

Land Surface ◽

The United States ◽

Important Variable ◽

Climate System ◽

Drought Monitoring ◽

Multiple Sources ◽

The North

Abstract Soil moisture is an important variable in the climate system that integrates the combined influence of the atmosphere, land surface, and soil. Soil moisture is frequently used for drought monitoring and climate forecasting. However, in situ soil moisture observations are not systematically archived and there are relatively few national soil moisture networks. The lack of observed soil moisture data makes it difficult to characterize long-term soil moisture variability and trends. The North American Soil Moisture Database (NASMD) is a new high-quality observational soil moisture database. It includes over 1,800 monitoring stations in the United States, Canada, and Mexico, making it the largest collections of in situ soil moisture observations in North America. Data are collected from multiple sources, quality controlled, and integrated into an online database (soilmoisture.tamu.edu). Here we describe the development of the database, including quality control/quality assurance, standardization, and collection of metadata. The utility of the NASMD is demonstrated through an analysis of the inter- and intraannual variability of soil moisture from multiple networks. The NASMD is a useful tool for drought monitoring and forecasting, calibrating/validating satellites and land surface models, and documenting how soil moisture influences the climate system on seasonal to interannual time scales.

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Evaluation of distributed soil moisture simulations through field observations during the North American monsoon in Redondo Creek, New Mexico

Ecohydrology ◽

10.1002/eco.23 ◽

2008 ◽

Vol 1 (3) ◽

pp. 271-287 ◽

Cited By ~ 14

Author(s):

Taufique H. Mahmood ◽

Enrique R. Vivoni

Keyword(s):

Soil Moisture ◽

New Mexico ◽

North American ◽

North American Monsoon ◽

Field Observations ◽

The North

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

Ecohydrology ◽

10.1002/eco.11 ◽

2008 ◽

Vol 1 (3) ◽

pp. 225-238 ◽

Cited By ~ 53

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

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Expanding HadISD: quality-controlled, sub-daily station data from 1931

10.5194/gi-2016-9 ◽

2016 ◽

Author(s):

Robert J. H. Dunn ◽

Kate M. Willett ◽

David E. Parker ◽

Lorna Mitchell

Keyword(s):

Quality Control ◽

Wind Speed ◽

Time Range ◽

Underlying Structure ◽

Control Procedure ◽

Future Projections ◽

Quality Control Procedure ◽

Temporal Coverage ◽

Extremes Of Temperature ◽

Selection Of

Abstract. HadISD is a sub-daily, station-based, quality-controlled dataset designed to study past extremes of temperature, pressure and humidity and allow comparisons to future projections. Herein we describe the first major update to the HadISD dataset. The temporal coverage of the dataset has been extended to 1931 to present, doubling the time range over which data are provided. Improvements made to the station selection and merging procedures result in 7677 stations being provided in version 2.0.0.2015p of this dataset. The selection of stations to merge together making composites has also been improved and made more robust. The underlying structure of the quality control procedure is the same as for HadISD.1.0.x, but a number of improvements have been implemented in individual tests. Also, more detailed quality control tests for wind speed and direction have been added. The data will be made available as netCDF files at www.metoffice.gov.uk/hadobs/hadisd and updated annually.

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