Playa Soil Moisture and Evaporation Dynamics During the MATERHORN Field Program

Hang, Chaoxun; Nadeau, Daniel F.; Jensen, Derek D.; Hoch, Sebastian W.; Pardyjak, Eric R.

doi:10.1007/s10546-015-0058-0

Cited by 27 publications

(32 citation statements)

References 62 publications

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“…(at each pixel from the TIR imagery):

a^{*} false(x, y false) = ({, \begin{matrix} array a (1 - \frac{\overset{true¯}{T} ⊡}{〈 \overset{true¯}{T} 〉} f) & array \overset{true¯}{T} (x, y) 〈 〈 \overset{true¯}{T} 〉, \\ array \\ array a (1 + \frac{\overset{true¯}{T} ⊡}{〈 \overset{true¯}{T} 〉} f) & array \overset{true¯}{T} (x, y) > 〈 \overset{true¯}{T} 〉 . \end{matrix})

In this expression,

〈 \overset{T}{true} 〉

is the spatial‐temporal mean of the entire TIR time series, T ¯⊡ is the temporally averaged difference between the instantaneous pixel temperature and the spatial‐temporal mean, which produces the long‐term temperature heterogeneities for the TIR time series (Christen et al , 2012 gives further information), and f is the weight given to a pixel relative to the ratio of T ¯⊡ to

〈 \overset{T}{true} 〉

(allowing patches colder than the spatial mean to receive less radiation, and conversely for warmer patches). The weight has been determined a posteriori ensuring a good match with the experimental data of (Hang et al , 2016). Hence, the weighting function could be considered a tunable parameter without sufficient supporting data to constrain it.…”

Section: Seb‐tir Flux Measurement Methodsmentioning

confidence: 99%

“…For this experiment, the soil near the Playa surface was mostly clay, silty clay or silty clay loam. The density, thermal conductivity, and specific heat were determined in Hang et al (2016) and Jensen et al (2016) during the MATERHORN spring field campaign and were 1426.2 kg m −3 , 0.77 W m −1 K −1 , and 1.472×10 3 J kg −1 K −1 respectively. Note that these values lead to a thermal admittance (

= \sqrt{ρ c_{p} k}

) of 1270 J m −2 K −1 s −1/2 .…”

Section: Seb‐tir Flux Measurement Methodsmentioning

confidence: 99%

“…Due to the arid climate of the Dugway Proving Grounds (Hang et al , 2016), latent heat fluxes are very weak. Measurements of water vapour fluxes were carried out at the MATERHORN Playa site using a Campbell Scientific (Logan, Utah) EC150 (infrared gas analyser) and CSAT3 (sonic anemometer‐thermometer) at a height of 10.4 m (Jensen et al , 2016) give a detailed methodology).…”

Section: Seb‐tir Flux Measurement Methodsmentioning

confidence: 99%

“…Measurements were taken at a flat desert Playa site at the US Army Dugway Proving Ground located near the southern extreme of the Great Salt Lake Basin, about 137 km southwest of Salt Lake City, Utah (40°8

^{'}

5.9

^{'^{'}}

N, 113°27

^{'}

7.8

^{'^{'}}

W). The playa region stretches ∼130 km north–south and spans ∼65 km east–west with an elevation of 1296 m and a variation less than 1 m km −1 (Hang et al , 2016). The annual temperature of the site is ∼13.7 °C, with an annual rainfall and evaporation of ∼100 and ∼170 mm respectively (Malek, 2003; Hang et al , 2016).…”

Section: Methodsmentioning

confidence: 99%

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A methodology for computing spatially and temporally varying surface sensible heat flux from thermal imagery

Morrison

Calaf

Fernando

et al. 2017

Quart J Royal Meteoro Soc

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Thermal infrared imagery provides a measure of surface temperature by quantifying the thermal emission of radiation from objects. In this work, we propose a novel approach for computing surface sensible heat fluxes from a time series of thermal imagery sampled at 20 Hz. The approach consists of using a surface energy budget, where the ground heat flux is easily computed from limited measurements using a force–restore‐type methodology, the latent heat fluxes are neglected, and the energy storage is computed using a lumped capacitance model. Preliminary validation of the method is presented using experimental data acquired at a desert playa in western Utah from an intensive observation period during the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Program. The sensible heat fluxes computed from thermal imagery show encouraging agreement (≈4% difference for 1 h averaged fluxes computed with the force–restore method) compared to heat fluxes obtained using the eddy‐covariance technique, however additional evaluation is required to confirm the method's validity. Further, the technique illustrates the richness of surface heat flux spatio‐temporal structure even over very smooth surfaces.

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“…(at each pixel from the TIR imagery):

a^{*} false(x, y false) = ({, \begin{matrix} array a (1 - \frac{\overset{true¯}{T} ⊡}{〈 \overset{true¯}{T} 〉} f) & array \overset{true¯}{T} (x, y) 〈 〈 \overset{true¯}{T} 〉, \\ array \\ array a (1 + \frac{\overset{true¯}{T} ⊡}{〈 \overset{true¯}{T} 〉} f) & array \overset{true¯}{T} (x, y) > 〈 \overset{true¯}{T} 〉 . \end{matrix})

In this expression,

〈 \overset{T}{true} 〉

〈 \overset{T}{true} 〉

Section: Seb‐tir Flux Measurement Methodsmentioning

confidence: 99%

= \sqrt{ρ c_{p} k}

) of 1270 J m −2 K −1 s −1/2 .…”

Section: Seb‐tir Flux Measurement Methodsmentioning

confidence: 99%

Section: Seb‐tir Flux Measurement Methodsmentioning

confidence: 99%

^{'}

5.9

^{'^{'}}

N, 113°27

^{'}

7.8

^{'^{'}}

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

A methodology for computing spatially and temporally varying surface sensible heat flux from thermal imagery

Morrison

Calaf

Fernando

et al. 2017

Quart J Royal Meteoro Soc

Self Cite

View full text Add to dashboard Cite

show abstract

“…alkaline sediments (Boettinger, 2009). It is characterized by high albedo, low roughness 161 length (see Table SI 2) and seasonally changing moisture and albedo (Hang et al, 2015). were operated continuously.…”

Section: Introductionmentioning

confidence: 99%

The MATERHORN: Unraveling the Intricacies of Mountain Weather

Fernando

Pardyjak

Sabatino

et al. 2015

Bulletin of the American Meteorological Society

159

116

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Emerging application areas such as air pollution in megacities, wind energy, urban security, and operation of unmanned aerial vehicles have intensified scientific and societal interest in mountain meteorology. To address scientific needs and help improve the prediction of mountain weather, the U.S. Department of Defense has funded a research effort—the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Program—that draws the expertise of a multidisciplinary, multi-institutional, and multinational group of researchers. The program has four principal thrusts, encompassing modeling, experimental, technology, and parameterization components, directed at diagnosing model deficiencies and critical knowledge gaps, conducting experimental studies, and developing tools for model improvements. The access to the Granite Mountain Atmospheric Sciences Testbed of the U.S. Army Dugway Proving Ground, as well as to a suite of conventional and novel high-end airborne and surface measurement platforms, has provided an unprecedented opportunity to investigate phenomena of time scales from a few seconds to a few days, covering spatial extents of tens of kilometers down to millimeters. This article provides an overview of the MATERHORN and a glimpse at its initial findings. Orographic forcing creates a multitude of time-dependent submesoscale phenomena that contribute to the variability of mountain weather at mesoscale. The nexus of predictions by mesoscale model ensembles and observations are described, identifying opportunities for further improvements in mountain weather forecasting.

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The effect of long‐term aerial exposure on intertidal mudflat erodibility

Nguyen

Bryan

Pilditch

2020

Earth Surf Processes Landf

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Intertidal zones by definition are exposed to air at low tide, and the exposure duration can be weeks (e.g. during neap tides) depending on water level and bed elevation. Here we investigated the effect of varying exposure duration (6h to 10 days) on intertidal mudflat erosion (measured using the EROMES device), where the effects of water content and biofilm biomass (using chlorophyll-a content as a proxy, Chl-a μgg À1) were taken into account. Sediments were collected between spring and summer

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Playa Soil Moisture and Evaporation Dynamics During the MATERHORN Field Program

Cited by 27 publications

References 62 publications

A methodology for computing spatially and temporally varying surface sensible heat flux from thermal imagery

A methodology for computing spatially and temporally varying surface sensible heat flux from thermal imagery

The MATERHORN: Unraveling the Intricacies of Mountain Weather

The effect of long‐term aerial exposure on intertidal mudflat erodibility

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