Snow water equivalent estimation by microwave radiometry

Chang, A. T. C.; Foster, James L.; Hall, Dorothy K.; Rango, A.; Hartline, Beverly Karplus

doi:10.1016/0165-232x(82)90019-2

Cited by 157 publications

(115 citation statements)

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“…It has been shown that snow grain size and SWE dominate the scattering (Chang et al 1982). Snow density has an effect, although this is much smaller.…”

Section: Microwave Measurement Of Snowmentioning

confidence: 99%

“…The larger the snow grains the greater the scattering for a given SWE and so a, in equation 1, is tuned for a particular snow grain size. The value of 1.59 was found by assuming a grain size of 0.35 mm (Chang et al 1982), but as snow grains change through the winter an assumption of constant grain size will cause errors (Kelly et al 2003). Liquid water affects the snow-pack's dielectric constant, increasing attenuation, potentially preventing the retrieval of SWE (Stiles and Ulaby 1980).…”

Section: Microwave Measurement Of Snowmentioning

confidence: 99%

“…Strong thermal gradients will cause large snow grains, of the order of one to several millimetres (Chang et al 1982, Davenport et al 2012, larger than is assumed in the derivation of AMSR-E and SSM/I. Clifford (2010), Brodzik et al (2007) and Boone et al (2006) cited these large grain snow-packs as a potential source of systematic bias in Chang based SWE estimates.…”

Section: Snow Grainsmentioning

confidence: 99%

“…The coordinates for these are given in Foster et al (1980). These were chosen as relatively simple cases (Foster et al 1980, Chang et al 1982) and so may not be representative of the global snow-affected land areas. To test this a selection of surface and meteorological properties were extracted for the three areas and compared to the same values for the 1,381 1 o pixels used here.…”

Section: Chang Algorithm Calibrationmentioning

confidence: 99%

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Evaluating global snow water equivalent products for testing land surface models

Hancock

Baxter

Evans³

et al. 2013

Remote Sensing of Environment

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(2013) 'Evaluating global snow water equivalent products for testing land surface models.', Remote sensing of environment., 128 . pp. 107-117. Further information on publisher's website:http://dx.doi.org/10.1016/j.rse. 2012.10.004 Publisher's copyright statement: NOTICE: this is the author's version of a work that was accepted for publication in Remote sensing of environment. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be re ected in this document. Changes may have been made to this work since it was submitted for publication. A de nitive version was subsequently published in Remote sensing of environment, 128, 2013, 10.1016/j.rse.2012.10.004 Additional information: Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Abstract This paper compares three global snow water equivalent (SWE) products, SSM/I (NSIDC), AMSR-E (NSIDC) and Globsnow (v1.0, ESA) to each other, snow covered area (SCA), ground measures of snow depth and meteorological data in an attempt to determine which might be most suitable for testing and developing land surface models. Particular attention is payed to which gives the most accurate peak accumulation, seasonal SWE changes and first and last dates of snow cover.SSM/I and AMSR-E are pure earth observation (EO) derived products whilst Globsnow is a combination of EO and ground data. The results suggest that the pure EO products can saturate in deeper snow (SWE > 80 -150 mm), can show spurious features during melt and can overestimate SWE due to strong thermal gradients and erroneous forest cover correction factors. Along with the comparison to ground data (only a single point) this suggests that Globsnow is the more accurate product for determining peak accumulation and seasonal SWE cycle.The snow start and end dates of the three SWE products were compared to an optically derived SCA (MOD10C1, taken as truth) and found to give large errors of snow start date (root mean square error of 20+ days, though SSM/I was correct on average). The snow end dates had lower errors (a bias of 1-6 days) although the spread was still on the order of three weeks.During the investigation, occasional abrupt changes in Globsnow were observed (in the v1.0 and v1.2 daily and v1.2 weekly products). These only occurred in around 1% of cases examined and seem to be spurious. Care should be taken to correct or avoid these jumps if using Globsnow to validate land surface models or in an assimilation scheme.

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“…It has been shown that snow grain size and SWE dominate the scattering (Chang et al 1982). Snow density has an effect, although this is much smaller.…”

Section: Microwave Measurement Of Snowmentioning

confidence: 99%

Section: Microwave Measurement Of Snowmentioning

confidence: 99%

Section: Snow Grainsmentioning

confidence: 99%

Section: Chang Algorithm Calibrationmentioning

confidence: 99%

See 2 more Smart Citations

Evaluating global snow water equivalent products for testing land surface models

Hancock

Baxter

Evans³

et al. 2013

Remote Sensing of Environment

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“…Thus, the raw data were first collapsed into a more manageable form. For a given day, the observed snowfall depth was multiplied by a prevalent conversion factor of 0.1 (Chang et al, 1982) to convert the snowfall into its equivalent water depth. The equivalent water depth was added to the observed rainfall on the same day to determine the daily precipitation.…”

Section: Analysis Methodsmentioning

confidence: 99%

Spatio-temporal variations in soil moisture and physicochemical properties of a typical semiarid sand-meadow-desert landscape as influenced by land use

Duan

Liu

Wang

et al. 2011

Hydrol. Earth Syst. Sci.

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Abstract.A good understanding of the interrelations between land cover alteration and changes in hydrologic conditions (e.g., soil moisture) as well as soil physicochemical properties (e.g., fine soil particles and nutrients) is crucial for maintaining the fragile hydrologic and environmental conditions of semiarid land, such as the Horqin Sandy Land in China, but is lacking in existing literature. The objectives of this study were to examine: (1) spatio-temporal variations of soil moisture and physicochemical properties in semiarid land; and (2) how those variations are influenced by land cover alteration. Using the data collected in a 9.71 km 2 well-instrumented area of the Horqin Sandy Land, this study examined by visual examination and statistical analyses the spatio-temporal variations of soil moisture and physicochemical properties. The results indicated that for the study area, the soil moisture and physicochemical properties were dependent on local topography, soil texture, vegetation density, and human activity. Long-term reclamation for agriculture was found to reduce soil moisture by over 23 % and significantly (p-value < 0.05) lower the contents of soil organic matter, fine soil particles, and nutrients.

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Sensor Principles and Remote Sensing Techniques

England

2005

Encyclopedia of Hydrological Sciences

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Model‐derived estimates of water stored in the upper few meters of soil, in vegetation, and in snow packs are the objectives of a new satellite microwave remote sensing technology. The most mature of the alternatives, this technology will use a combination of longer wavelength satellite microwave brightness observations and Soil Vegetation Atmosphere Transfer (SVAT) models, forced by solar and thermal radiation and by weather, to produce a near‐daily global field of stored water. While the near‐daily temporal resolution is a unique strength for hydrometeorology, its likely spatial resolution of tens of kilometers is a serious weakness for land‐surface hydrology. This article is intended as a review of the concept and the investigations that have contributed to it. It also includes brief surveys of some technologies, like aperture synthesis radiometry and combined active passive sensing, that are being explored to improve spatial resolution.

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Snow water equivalent estimation by microwave radiometry

Cited by 157 publications

References 5 publications

Evaluating global snow water equivalent products for testing land surface models

Evaluating global snow water equivalent products for testing land surface models

Spatio-temporal variations in soil moisture and physicochemical properties of a typical semiarid sand-meadow-desert landscape as influenced by land use

Sensor Principles and Remote Sensing Techniques

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