FASST Soil Moisture, Soil Temperature: Original Versus New

Frankenstein, Susan

doi:10.21236/ada483823

Cited by 9 publications

(10 citation statements)

References 18 publications

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“…To represent the influence of soil moisture on latent and sensible heat fluxes, we developed mean daily near‐surface (0–10 cm depth) soil moisture grids using the Fast All‐Season Soil Strength model (FASST; Frankenstein and Konig, ). FASST is a point‐based energy balance model designed to estimate ground surface properties, including soil moisture, strength and temperature.…”

Section: Methodsmentioning

confidence: 99%

“…In addition, the model is quite flexible, and can be run at sub‐hourly to daily time steps with outputs that can be retrieved at a range of user‐defined depths. Addition details on the physical schemes implemented in the model can be found in Frankenstein and Konig (). Because FASST is a point‐based model and computationally intensive to run daily at fine scale over the entire study domain, we ran the model daily across a systematic grid of 14 830 points and then interpolated predictions using a regression approach.…”

Section: Methodsmentioning

confidence: 99%

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Development of high‐resolution (250 m) historical daily gridded air temperature data using reanalysis and distributed sensor networks for the US Northern Rocky Mountains

Holden

Swanson

Klene

et al. 2015

Intl Journal of Climatology

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Gridded temperature data sets are typically produced at spatial resolutions that cannot fully resolve fine-scale variation in surface air temperature in regions of complex topography. These data limitations have become increasingly important as scientists and managers attempt to understand and plan for potential climate change impacts. Here, we describe the development of a high-resolution (250 m) daily historical temperature data set for the US Northern Rocky Mountains using observations from both long-term weather stations and a dense network of low-cost temperature sensors. Empirically based models for daily minimum and maximum temperature incorporate lapse rates from regional reanalysis data, modelled daily solar insolation and soil moisture, along with time invariant canopy cover and topographic factors. Daily model predictions demonstrate excellent agreement with independent observations, with mean absolute errors of <1.4 ∘ C for both minimum and maximum temperature. Topographically resolved temperature data may prove useful in a range of applications related to hydrology, fire regimes and fire behaviour, and habitat suitability modelling. The form of the models may provide a means for downscaling future temperature scenarios that account for potential fine-scale topographically mediated changes in near-surface temperature.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Development of high‐resolution (250 m) historical daily gridded air temperature data using reanalysis and distributed sensor networks for the US Northern Rocky Mountains

Holden

Swanson

Klene

et al. 2015

Intl Journal of Climatology

View full text Add to dashboard Cite

show abstract

“…Among meteorological phenomena, precipitation and air temperature have the greatest influence on vehicle cross-country mobility, as they directly affect the soil's bearing capacity, freezing point, and moisture level. Vehicle terrain trafficability models contain information of the regarding meteorological phenomena, given after modelling of soil moisture content obtained through structured weather data (Smith and Meyer, 1973;Sullivan et al, 1997;Frankenstein and Koenig, 2004a;2004b;Frankenstein, 2008). Weather forecasts are only used for short-term (up to 72 hours in advance) predictions of vehicle terrain trafficability, because the accuracy of weather forecasts declines over longer periods.…”

mentioning

confidence: 99%

“…Od meteoroloških pojava najveći utjecaj na terensku mobilnost vozila imaju padaline i temperatura zraka, pri čemu one izravno utječu na nosivost tla, odnosno na zamrzavanje i vlažnost tla. Modeli prohodnosti vozila sadržavaju informacije o meteorološkim pojavama nakon modeliranja stanja vlažnosti tla putem strukturiranih podataka meteoroloških prognoza (Smith i Meyer, 1973;Sullivan i dr. 1997;Frankenstein i Koenig, 2004a;2004b;Frankenstein, 2008). Meteorološke prognoze koriste se za kratkoročna (do 72 sata unaprijed) predviđanja prohodnosti tla za vozila zbog nemogućnosti točnoga predviđanja vremena za dulja razdoblja.…”

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