Mesoscale Monitoring of Soil Moisture across a Statewide Network

Illston, Bradley G.; Basara, Jeffrey B.; Fisher, Daniel K.; Elliott, Ronald L.; Fiebrich, Christopher A.; Crawford, Kenneth; Humes, K. S.; Hunt, Eric

doi:10.1175/2007jtecha993.1

Cited by 132 publications

(123 citation statements)

References 30 publications

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“…The support to MH for processing the long-term soil temperature dataset from the ARM archive is provided by DOE's Atmospheric System Research (ASR) program. PNNL is op- The Oklahoma Mesonet (Brock et al 1995;Illston et al 2008;McPherson et al 2007) is an Oklahoma-wide network of meteorological stations (Fig. A1).…”

Section: Summary and Discussionmentioning

confidence: 99%

Validation of Noah-Simulated Soil Temperature in the North American Land Data Assimilation System Phase 2

Xia

Sheffield

et al. 2013

Journal of Applied Meteorology and Climatology

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Soil temperature can exhibit considerable memory from weather and climate signals and is among the most important initial conditions in numerical weather and climate models. Consequently, a more accurate longterm land surface soil temperature dataset is needed to improve weather and climate simulation and prediction, and is also important for the simulation of agricultural crop yield and ecological processes. The North American Land Data Assimilation phase 2 (NLDAS-2) has generated 31 years ) of simulated hourly soil temperature data with a spatial resolution of 1 /88. This dataset has not been comprehensively evaluated to date. Thus, the purpose of this paper is to assess Noah-simulated soil temperature for different soil depths and time scales. The authors used long-term observed monthly mean soil temperatures from 137 cooperative stations over the United States to evaluate simulated soil temperature for three soil layers (0-10, 10-40, and 40-100 cm) for annual and monthly time scales. Short-term (1997-99) observed soil temperatures from 72 Oklahoma Mesonet stations were used to validate simulated soil temperatures for three soil layers and for daily and hourly time scales. The results showed that the Noah land surface model generally matches observed soil temperature well for different soil layers and time scales. At greater depths, the simulation skill (anomaly correlation) decreased for all time scales. The monthly mean diurnal cycle difference between simulated and observed soil temperature revealed large midnight biases in the cold season that are due to small downward longwave radiation and issues related to model parameters.

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Section: Summary and Discussionmentioning

confidence: 99%

Validation of Noah-Simulated Soil Temperature in the North American Land Data Assimilation System Phase 2

Xia

Sheffield

et al. 2013

Journal of Applied Meteorology and Climatology

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“…Environmental data included maximum air temperature, minimum relative humidity, maximum wind speed (measured at 10 m), and reference temperature difference (Illston et al, 2008) from heat dissipation sensors (Model 229, Campbell Scientific Inc., Logan, UT) at the 5-and 25-cm soil depths. The reference temperature difference was converted to soil matric potential using a calibration function (Illston et al, 2008). Volumetric water content was then calculated from soil matric potential using van Genuchten parameters obtained from the Rosetta pedotransfer function.…”

Section: Environmental Datamentioning

confidence: 99%

“…Environmental data for each fire were assigned for the day of fire ignition from the Mesonet station nearest the address of the responding fire department. Data from the next nearest station were used to fill missing soil moisture data when necessary because soil moisture is recorded at only 105 of Oklahoma's 120 Mesonet stations (Illston et al, 2008). No attempt was made to fill any remaining missing environmental data, and data existed for 96% of fires.…”

Section: Relating Environmental Conditions To Wildfire Size Classmentioning

confidence: 99%

Soil Moisture Affects Growing-Season Wildfire Size in the Southern Great Plains

Krueger

Ochsner

Engle

et al. 2015

Soil Science Society of America Journal

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The increasing availability of soil moisture data presents an opportunity for its use in wildfire danger assessments, but research regarding the influence of soil moisture on wildfires is scarce. Our objective was to identify relationships between soil moisture and wildfire size for Oklahoma wildfires during the growing (May-October) and dormant seasons (November-April). we hypothesized that soil moisture influences wildfire size when vegetation is growing but is less important when most vegetation is dead or dormant. soil moisture, as fraction of available water capacity (FAw), and commonly measured weather variables were determined for 38,419 wildfires from 2000-2012. wildfires were grouped by size class (<4.05, ³4.05 and <40.5, ³40.5 and <121, ³121 and <405, and ³405 ha), and the Kruskal-wallis test with multiple comparisons was used to identify differences in each variable between wildfire size classes and seasons. Large fires occurred at lower FAw than small fires during both seasons (P < 0.001), but growing-season wildfires ³405 ha occurred over a narrow range of FAw (0.05-0.46) whereas dormant-season fires of this size occurred across the entire range of FAw (0.05-1.05). For growing-season fires ³ 121 ha, 91% occurred at FAw < 0.5 and 77% occurred at FAw < 0.2. Our finding that large growing-season wildfires occurred exclusively under conditions of low soil moisture highlights the need to develop methods to use soil moisture data in wildfire danger assessments.Abbreviations: AWC, available water capacity; FAW, fraction of available water capacity; KBDI, Keetch-Byram Drought Index; LFM, live fuel moisture; PAW, plant available water.

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“…In situ observations of soil moisture are taken from the Oklahoma Mesonet (http://mesonet.org/), comprised of over 100 continuously monitoring stations across the state (Illston et al, 2008). Campbell Scientific 229-L heat dissipation sensors are deployed at four depths (5, 25, 60, 75 cm) in the soil column and measure matric potential, from which volumetric water content is derived.…”

Section: Soil Moisture Datamentioning

confidence: 99%

Soil moisture–precipitation coupling: observations from the Oklahoma Mesonet and underlying physical mechanisms

Ford

Rapp

Quiring

et al. 2015

Hydrol. Earth Syst. Sci.

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Abstract.Interactions between soil moisture and the atmosphere are driven by the partitioning of sensible and latent heating, through which soil moisture has been connected to atmospheric modifications that could potentially lead to the initiation of convective precipitation. The majority of previous studies linking the land surface to subsequent precipitation have used atmospheric reanalysis or model data sets. In this study, we link in situ observations of soil moisture from more than 100 stations in Oklahoma to subsequent unorganized afternoon convective precipitation. We use hourly next generation (NEXRAD) radar-derived precipitation to identify convective events, and then compare the location of precipitation initiation to underlying soil moisture anomalies in the morning. Overall we find a statistically significant preference for convective precipitation initiation over drier than normal soils, with over 70 % of events initiating over soil moisture below the long-term median. The significant preference for precipitation initiation over drier than normal soils is in contrast with previous studies using satellite-based precipitation to identify the region of maximum precipitation accumulation. We evaluated 19 convective events occurring near Lamont, Oklahoma, where soundings of the atmospheric profile at 06:00 and 12:00 LST are also available. For these events, soil moisture has strong negative correlations with the level of free convection (LFC), planetary boundary layer (PBL) height, and surface temperature changes between 06:00 and 12:00 LST. We also find strong positive correlations between morning soil moisture and morning-toafternoon changes in convective available potential energy and convective inhibition. In general, the results of this study demonstrate that both positive and negative soil moisture feedbacks are important in this region of the USA.

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Mesoscale Monitoring of Soil Moisture across a Statewide Network

Cited by 132 publications

References 30 publications

Validation of Noah-Simulated Soil Temperature in the North American Land Data Assimilation System Phase 2

Validation of Noah-Simulated Soil Temperature in the North American Land Data Assimilation System Phase 2

Soil Moisture Affects Growing-Season Wildfire Size in the Southern Great Plains

Soil moisture–precipitation coupling: observations from the Oklahoma Mesonet and underlying physical mechanisms

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