Oklahoma Mesonet Soil Moisture (OKMSOIL) Value-Added Product Report

Remote sensing can provide timely and economical monitoring of large areas. It provides the ability to generate information on a variety of spatial and temporal scales. Generally, remote sensing is divided into passive and active depending on the sensor system. The majority of remote-sensing studies concerned with drought monitoring have involved visible–infrared sensor systems, which are passive and depend on the sun’s illumination. Radar (radio detection and ranging) is an active sensor system that transmits energy in the microwave region of the electromagnetic spectrum and measures the energy reflected back from the landscape target. The energy reflected back is called backscatter. The attraction of radar over visible– infrared remote sensing (chapters 5 and 6) is its independence from the sun, enabling day/night operations, as well as its ability to penetrate cloud and obtain data under most weather conditions. Thus, unlike visible–infrared sensors, radar offers the opportunity to acquire uninterrupted information relevant to drought such as soil moisture and vegetation stress. Drought conditions manifest in multiple and complex ways. Accordingly, a large number of drought indices have been defined to signal abnormally dry conditions and their effects on crop growth, river flow, groundwater, and so on (Tate and Gustard, 2000). In the field of radar remote sensing, much work has been devoted to developing algorithms to retrieve geophysical parameters such as soil moisture, crop biomass, and vegetation water content. In principle, these parameters would be highly relevant for monitoring agricultural drought. However, despite the existence of a number of radar satellite systems, progress in the use of radar in environmental monitoring, particularly in respect to agriculture, has been slower than anticipated. This may be attributed to the complex nature of radar interactions with agricultural targets and the suboptimal configuration of the satellite sensors available in the 1990s (Ulaby, 1998; Bouman et al., 1999). Because most attention is still devoted to the problem of deriving high-quality soil moisture and vegetation products, there have been few investigations on how to combine such radar products with other data and models to obtain value-added agricultural drought products.

Download Full-text

A Modified Framework for Quantifying Land–Atmosphere Covariability during Hydrometeorological and Soil Wetness Extremes in Oklahoma

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-18-0230.1 ◽

2019 ◽

Vol 58 (7) ◽

pp. 1465-1483 ◽

Cited By ~ 2

Author(s):

Ryann A. Wakefield ◽

Jeffrey B. Basara ◽

Jason C. Furtado ◽

Bradley G. Illston ◽

Craig. R. Ferguson ◽

...

Keyword(s):

Soil Moisture ◽

Great Plains ◽

Hot Spot ◽

Extreme Rainfall ◽

Southern Great Plains ◽

Low Level ◽

Oklahoma Mesonet ◽

Humidity Index ◽

Grid Points ◽

Regional Reanalysis

AbstractGlobal “hot spots” for land–atmosphere coupling have been identified through various modeling studies—both local and global in scope. One hot spot that is common to many of these analyses is the U.S. southern Great Plains (SGP). In this study, we perform a mesoscale analysis, enabled by the Oklahoma Mesonet, that bridges the spatial and temporal gaps between preceding local and global analyses of coupling. We focus primarily on east–west variations in seasonal coupling in the context of interannual variability over the period spanning 2000–15. Using North American Regional Reanalysis (NARR)-derived standardized anomalies of convective triggering potential (CTP) and the low-level humidity index (HI), we investigate changes in the covariance of soil moisture and the atmospheric low-level thermodynamic profile during seasonal hydrometeorological extremes. Daily CTP and HI z scores, dependent upon climatology at individual NARR grid points, were computed and compared to in situ soil moisture observations at the nearest mesonet station to provide nearly collocated annual composites over dry and wet soils. Extreme dry and wet year CTP and HI z-score distributions are shown to deviate significantly from climatology and therefore may constitute atmospheric precursors to extreme events. The most extreme rainfall years differ from climatology but also from one another, indicating variability in the strength of land–atmosphere coupling during these years. Overall, the covariance between soil moisture and CTP/HI is much greater during drought years, and coupling appears more consistent. For example, propagation of drought during 2011 occurred under antecedent CTP and HI conditions that were identified by this study as being conducive to positive dry feedbacks demonstrating potential utility of this framework in forecasting regional drought propagation.

Download Full-text

Estimating profile soil moisture and groundwater variations using GRACE and Oklahoma Mesonet soil moisture data

Water Resources Research ◽

10.1029/2007wr006057 ◽

2008 ◽

Vol 44 (1) ◽

Cited By ~ 82

Author(s):

Sean Swenson ◽

James Famiglietti ◽

Jeffrey Basara ◽

John Wahr

Keyword(s):

Soil Moisture ◽

Soil Moisture Data ◽

Oklahoma Mesonet

Download Full-text

Retrieval of an Available Water-Based Soil Moisture Proxy from Thermal Infrared Remote Sensing. Part I: Methodology and Validation

Journal of Hydrometeorology ◽

10.1175/2008jhm1024.1 ◽

2009 ◽

Vol 10 (3) ◽

pp. 665-683 ◽

Cited By ~ 71

Author(s):

Christopher R. Hain ◽

John R. Mecikalski ◽

Martha C. Anderson

Keyword(s):

Soil Moisture ◽

Potential Evapotranspiration ◽

Thermal Infrared ◽

Surface Energy Budget ◽

Rooting Depth ◽

Thermal Infrared Remote Sensing ◽

Water Fraction ◽

Available Water ◽

Oklahoma Mesonet ◽

Moisture Conditions

Abstract A retrieval of available water fraction ( fAW) is proposed using surface flux estimates from satellite-based thermal infrared (TIR) imagery and the Atmosphere–Land Exchange Inversion (ALEXI) model. Available water serves as a proxy for soil moisture conditions, where fAW can be converted to volumetric soil moisture through two soil texture dependents parameters—field capacity and permanent wilting point. The ability of ALEXI to provide valuable information about the partitioning of the surface energy budget, which can be largely dictated by soil moisture conditions, accommodates the retrieval of an average fAW over the surface to the rooting depth of the active vegetation. For this method, the fraction of actual to potential evapotranspiration ( fPET) is computed from an ALEXI estimate of latent heat flux and potential evapotranspiration (PET). The ALEXI-estimated fPET can be related to fAW in the soil profile. Four unique fPET to fAW relationships are proposed and validated against Oklahoma Mesonet soil moisture observations within a series of composite periods during the warm seasons of 2002–04. Using the validation results, the most representative of the four relationships is chosen and shown to produce reasonable (mean absolute errors values less than 20%) fAW estimates when compared to Oklahoma Mesonet observations. Quantitative comparisons between ALEXI and modeled fAW estimates from the Eta Data Assimilation System (EDAS) are also performed to assess the possible advantages of using ALEXI soil moisture estimates within numerical weather predication (NWP) simulations. This TIR retrieval technique is advantageous over microwave techniques because of the ability to indirectly sense fAW—and hence soil moisture conditions—extending into the root-zone layer. Retrievals are also possible over dense vegetation cover and are available on spatial resolutions on the order of the native TIR imagery. A notable disadvantage is the inability to retrieve fAW conditions through cloud cover.

Download Full-text

Benefits and Beneficiaries of the Oklahoma Mesonet: A Multisectoral Ripple Effect Analysis

Weather Climate and Society ◽

10.1175/wcas-d-16-0139.1 ◽

2017 ◽

Vol 9 (3) ◽

pp. 499-519 ◽

Cited By ~ 8

Author(s):

Jadwiga R. Ziolkowska ◽

Christopher A. Fiebrich ◽

J. D. Carlson ◽

Andrea D. Melvin ◽

Albert J. Sutherland ◽

...

Keyword(s):

Public Safety ◽

Agricultural Sector ◽

Wildland Fire ◽

Value Added ◽

Economic Benefits ◽

Decision Makers ◽

Extreme Weather Events ◽

Ripple Effect ◽

Oklahoma Mesonet ◽

K 12

Abstract Since the Oklahoma Mesonet (the state’s automated mesoscale weather station network) was established in 1994, it has served a number of diverse groups and provided public services to foster weather preparedness, education, and public safety, while also supporting decision-making in agricultural production and wildland fire management. With 121 monitoring stations across the state, the Oklahoma Mesonet has developed an array of technologies to observe a variety of atmospheric and soil variables in 5- to 30-min intervals. These consistent observations have been especially critical for predicting and preparing for extreme weather events like droughts, floods, ice storms, and severe convective storms as well as for development of value-added tools. The tools, outreach programs, and mesoscale data have been widely utilized by the general public, state decision-makers, public safety officials, K–12 community, agricultural sector, and researchers, thus generating wide societal and economic benefits to many groups. Based on practical application examples of weather information provided by the Oklahoma Mesonet, this paper analyzes both benefits generated by Oklahoma Mesonet information to the public and decision-makers and ripple effects (spreading amplified outcomes/implications) of those benefits in the short and long term. The paper further details ongoing and anticipated Oklahoma Mesonet innovations as a response to changing needs for weather-related information over time, especially as a result of technological developments and weather variability.

Download Full-text