HUT snow emission model and its applicability to snow water equivalent retrieval

Pulliainen, Jouni; Grandell, J.; Hallikainen, M.

doi:10.1109/36.763302

Cited by 349 publications

(251 citation statements)

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“…Since EF is nearly constant during daylight hours [Shuttleworth et al, 1989;Crago, 1996], it can be used for scaling instantaneous satellite observations to longer time periods (daily or daytime for snow parameters [Pulliainen et al 1999;Macelloni et al 2003], and found that the EDVI V has the greatest correlation coefficients. Thus, we will mainly use the EDVI V in the following analysis.…”

Section: Resultsmentioning

confidence: 99%

“…The emissivity observed at longer wavelengths with a weaker attenuation by the canopy generally represents an effectively thicker layer than those observed at shorter and stronger attenuation wavelengths. Some studies even found that the brightness temperature difference at two microwave wavelengths has certain capability to classify land surface type and to determine forest characteristics [Neale et al 1990;Pulliainen et al 1999;Macelloni et al 2003]. Thus, a new parameter based on the microwave land surface emissivity difference between two wavelengths is introduced to indicate VWC and other vegetation properties of the canopy with a minimal influence of the soil emission underneath vegetation canopy.…”

Section: Microwave Emissivity Difference Vegetation Index (Edvi)mentioning

confidence: 99%

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Remote sensing of evapotranspiration and carbon uptake at Harvard Forest

Min

Lin

2006

Remote Sensing of Environment

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Section: Resultsmentioning

confidence: 99%

Section: Microwave Emissivity Difference Vegetation Index (Edvi)mentioning

confidence: 99%

Remote sensing of evapotranspiration and carbon uptake at Harvard Forest

Min

Lin

2006

Remote Sensing of Environment

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“…Using the method described in Pulliainen (2006), the HUT (Helsinki University of Technology) microwave snow emission model (Pulliainen et al 1999) is used to relate the brightness temperature values of the satellites to the snow properties and snow depth. HUT is a radiative transfer model for calculating the microwave emission of a snowpack (assumed homogeneous) for given SWE, grain size and snow density.…”

Section: Globsnowmentioning

confidence: 99%

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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“…Additionally, other auxiliary datasets required by CMEM, e.g., the percentages of sand and clay and the fraction of vegetation, were provided from the surface datasets of CLM3 (Oleson et al, 2004). Kirdyashev et al (1979) Atmosphere Atmospheric optical depth Pellarin et al (2003) Snow Snow reflectivity Pulliainen et al (1999) (2)…”

Section: The Cmem-clm Experimentsmentioning

confidence: 99%