Search Results
locations (gray dots) with validation sites indicated (black dots). Soil matric potential measurements from the Oklahoma Mesonet heat dissipation sensors are often converted to estimates of soil moisture (i.e., volumetric water content; e.g., Collow et al. 2012 ). That conversion is based on the site- and depth-specific soil water retention curve. The van Genuchten (1980) equation is used to represent the unique water retention curve for each site and depth: The parameters include θ r (cm 3 cm −3
locations (gray dots) with validation sites indicated (black dots). Soil matric potential measurements from the Oklahoma Mesonet heat dissipation sensors are often converted to estimates of soil moisture (i.e., volumetric water content; e.g., Collow et al. 2012 ). That conversion is based on the site- and depth-specific soil water retention curve. The van Genuchten (1980) equation is used to represent the unique water retention curve for each site and depth: The parameters include θ r (cm 3 cm −3
the amount of water available for aquifer recharge. Thus, soil moisture observations are being utilized by water resource managers in their long- and short-term management of water storage facilities (i.e., dams and reservoirs). Our ability to make accurate long-term observations of soil moisture on regional scales can also have a large impact on our ability to understand the impact of global climate change on our water supply. Providing timely weather, hydrological, and climatological forecasts
the amount of water available for aquifer recharge. Thus, soil moisture observations are being utilized by water resource managers in their long- and short-term management of water storage facilities (i.e., dams and reservoirs). Our ability to make accurate long-term observations of soil moisture on regional scales can also have a large impact on our ability to understand the impact of global climate change on our water supply. Providing timely weather, hydrological, and climatological forecasts
1. Introduction Soil moisture is an important forcing variable in terrestrial environments ( Vereecken et al. 2008 ; Robinson et al. 2008 ; Seneviratne et al. 2010 ; Legates et al. 2011 ). Soil moisture significantly influences weather and climate, plant growth and productivity, hydrology, and soil ecology (i.e., carbon/nitrogen dynamics, and trace gas emissions). As such, the need for compilation of extensive and intensive soil moisture information has been recognized for several decades (e
1. Introduction Soil moisture is an important forcing variable in terrestrial environments ( Vereecken et al. 2008 ; Robinson et al. 2008 ; Seneviratne et al. 2010 ; Legates et al. 2011 ). Soil moisture significantly influences weather and climate, plant growth and productivity, hydrology, and soil ecology (i.e., carbon/nitrogen dynamics, and trace gas emissions). As such, the need for compilation of extensive and intensive soil moisture information has been recognized for several decades (e
rainfall-induced changes in the surface conditions. In particular, over land, the actual (attenuation-free) surface backscattering cross sections (denoted by σ e 0 ) increase in the presence of rainfall. This behavior is called the soil moisture effect. In general, the increase in the surface soil moisture causes an increase in the dielectric constant; as the dielectric constant is larger for water than that for soil particle, this leads to an increase in σ e 0 . Several studies including Oki et al
rainfall-induced changes in the surface conditions. In particular, over land, the actual (attenuation-free) surface backscattering cross sections (denoted by σ e 0 ) increase in the presence of rainfall. This behavior is called the soil moisture effect. In general, the increase in the surface soil moisture causes an increase in the dielectric constant; as the dielectric constant is larger for water than that for soil particle, this leads to an increase in σ e 0 . Several studies including Oki et al
1. Introduction Convective systems of tropical or midlatitudes are thermodynamic machines in which heat and moisture, first concentrated in the lower atmospheric layers, are progressively transported to higher altitudes during the system evolution. With variable efficiency these systems transform the convective available potential energy into kinetic energy. This transformation is operated in particular by means of (i) latent heat through microphysical mechanisms, which lead to cloud and
1. Introduction Convective systems of tropical or midlatitudes are thermodynamic machines in which heat and moisture, first concentrated in the lower atmospheric layers, are progressively transported to higher altitudes during the system evolution. With variable efficiency these systems transform the convective available potential energy into kinetic energy. This transformation is operated in particular by means of (i) latent heat through microphysical mechanisms, which lead to cloud and
, airlines do not achieve an immediate operational benefit from adding moisture observations to their existing sensor suites. Therefore, only planes that are specially equipped with moisture sensors can monitor moisture conditions; approximately 150 aircraft, mainly in the United States, are capable of providing moisture data ( Petersen 2016 ). The second and current generation of the Water Vapor Sensing System (WVSS) uses a laser diode that directly measures the water vapor mixing ratio by counting the
, airlines do not achieve an immediate operational benefit from adding moisture observations to their existing sensor suites. Therefore, only planes that are specially equipped with moisture sensors can monitor moisture conditions; approximately 150 aircraft, mainly in the United States, are capable of providing moisture data ( Petersen 2016 ). The second and current generation of the Water Vapor Sensing System (WVSS) uses a laser diode that directly measures the water vapor mixing ratio by counting the
.7–15.5 μ m, with a spectral resolution of 0.25 cm −1 ( Blumstein et al. 2004 ). Observed hyperspectral measurements are routinely used to produce atmospheric temperature and moisture profiles over both the land and the ocean, with a very high vertical resolution, by applying various retrieval algorithms ( Li et al. 2000 ; Aires et al. 2002 ; Goldberg et al. 2003 ; Susskind et al. 2003 ; Carissimo et al. 2005 ; Smith et al. 2005 ; Liu et al. 2009 ). The retrieved high-resolution atmospheric
.7–15.5 μ m, with a spectral resolution of 0.25 cm −1 ( Blumstein et al. 2004 ). Observed hyperspectral measurements are routinely used to produce atmospheric temperature and moisture profiles over both the land and the ocean, with a very high vertical resolution, by applying various retrieval algorithms ( Li et al. 2000 ; Aires et al. 2002 ; Goldberg et al. 2003 ; Susskind et al. 2003 ; Carissimo et al. 2005 ; Smith et al. 2005 ; Liu et al. 2009 ). The retrieved high-resolution atmospheric
1. Introduction For decades now, scientists have estimated SWE and, to some extent, soil moisture content ( M ) by measuring the attenuation of natural soil gamma radiation through the snowpack ( Carroll and Schaake 1983 ; Maxson et al. 1996 ; Grasty 1982 ). Airborne surveys of SWE are routinely conducted by NOAA’s National Operational Hydrologic Remote Sensing Center using this technique. The basic concepts and data analysis algorithms used are described in detail by Fritzsche (1982
1. Introduction For decades now, scientists have estimated SWE and, to some extent, soil moisture content ( M ) by measuring the attenuation of natural soil gamma radiation through the snowpack ( Carroll and Schaake 1983 ; Maxson et al. 1996 ; Grasty 1982 ). Airborne surveys of SWE are routinely conducted by NOAA’s National Operational Hydrologic Remote Sensing Center using this technique. The basic concepts and data analysis algorithms used are described in detail by Fritzsche (1982
similar standards as the Soil Climate Analysis Network ( Schaefer et al. 2007 ) for soil temperature and soil moisture observations. As part of the ongoing expansion, detailed characterization of the soil profile of the new 13 stations was made by NRCS personnel and a new online platform was created for data dissemination ( http://mesonet.k-state.edu ). The third phase of the network spans the period from 2013 to the present time. During this period the network underwent major organizational and
similar standards as the Soil Climate Analysis Network ( Schaefer et al. 2007 ) for soil temperature and soil moisture observations. As part of the ongoing expansion, detailed characterization of the soil profile of the new 13 stations was made by NRCS personnel and a new online platform was created for data dissemination ( http://mesonet.k-state.edu ). The third phase of the network spans the period from 2013 to the present time. During this period the network underwent major organizational and
1. Introduction One of the most important variables related to convective-scale forecasting is the near-surface moisture field. The timing and location of convective initiation (CI) is often highly sensitive to moisture within the boundary layer (BL). Variations as small as 1 g kg −1 in specific humidity, which are typical of boundary layer moisture ( Weckwerth et al. 1996 ), can make the difference in whether or not storm initiation occurs. Xue and Martin (2006a , b ) performed a high
1. Introduction One of the most important variables related to convective-scale forecasting is the near-surface moisture field. The timing and location of convective initiation (CI) is often highly sensitive to moisture within the boundary layer (BL). Variations as small as 1 g kg −1 in specific humidity, which are typical of boundary layer moisture ( Weckwerth et al. 1996 ), can make the difference in whether or not storm initiation occurs. Xue and Martin (2006a , b ) performed a high