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Multiscale assimilation of Advanced Microwave Scanning Radiometer-EOS snow water equivalent and Moderate Resolution Imaging Spectroradiometer snow cover fraction observations in northern Colorado

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Abstract
Eight years (2002–2010) of Advanced Microwave Scanning Radiometer–EOS (AMSR-E) snow water equivalent (SWE) retrievals and Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover fraction (SCF) observations are assimilated separately or jointly into the Noah land surface model over a domain in Northern Colorado. A multiscale ensemble Kalman filter (EnKF) is used, supplemented with a rule-based update. The satellite data are either left unscaled or are scaled for anomaly assimilation. The results are validated against in situ observations at 14 high-elevation Snowpack Telemetry (SNOTEL) sites with typically deep snow and at 4 lower-elevation Cooperative Observer Program (COOP) sites. Assimilation of coarse-scale AMSR-E SWE and fine-scale MODIS SCF observations both result in realistic spatial SWE patterns. At COOP sites with shallow snowpacks, AMSR-E SWE and MODIS SCF data assimilation are beneficial separately, and joint SWE and SCF assimilation yields significantly improved root-mean-square error and correlation values for scaled and unscaled data assimilation. In areas of deep snow where the SNOTEL sites are located, however, AMSR-E retrievals are typically biased low and assimilation without prior scaling leads to degraded SWE estimates. Anomaly SWE assimilation could not improve the interannual SWE variations in the assimilation results because the AMSR-E retrievals lack realistic interannual variability in deep snowpacks. SCF assimilation has only a marginal impact at the SNOTEL locations because these sites experience extended periods of near-complete snow cover. Across all sites, SCF assimilation improves the timing of the onset of the snow season but without a net improvement of SWE amounts.
Keywords
VARIABILITY, DEPTH, CLIMATE, MODIS, INFORMATION-SYSTEM, DEPLETION CURVES, PASSIVE MICROWAVE, LAND-SURFACE MODEL, ENSEMBLE KALMAN FILTER, UNCERTAINTY

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Citation

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Chicago
De Lannoy, Gabriëlle, Rolf Reichle, Kristi R Arsenault, Paul R Houser, Sujay Kumar, Niko Verhoest, and Valentijn Pauwels. 2012. “Multiscale Assimilation of Advanced Microwave Scanning Radiometer-EOS Snow Water Equivalent and Moderate Resolution Imaging Spectroradiometer Snow Cover Fraction Observations in Northern Colorado.” Water Resources Research 48 (1).
APA
De Lannoy, G., Reichle, R., Arsenault, K. R., Houser, P. R., Kumar, S., Verhoest, N., & Pauwels, V. (2012). Multiscale assimilation of Advanced Microwave Scanning Radiometer-EOS snow water equivalent and Moderate Resolution Imaging Spectroradiometer snow cover fraction observations in northern Colorado. WATER RESOURCES RESEARCH, 48(1).
Vancouver
1.
De Lannoy G, Reichle R, Arsenault KR, Houser PR, Kumar S, Verhoest N, et al. Multiscale assimilation of Advanced Microwave Scanning Radiometer-EOS snow water equivalent and Moderate Resolution Imaging Spectroradiometer snow cover fraction observations in northern Colorado. WATER RESOURCES RESEARCH. 2012;48(1).
MLA
De Lannoy, Gabriëlle, Rolf Reichle, Kristi R Arsenault, et al. “Multiscale Assimilation of Advanced Microwave Scanning Radiometer-EOS Snow Water Equivalent and Moderate Resolution Imaging Spectroradiometer Snow Cover Fraction Observations in Northern Colorado.” WATER RESOURCES RESEARCH 48.1 (2012): n. pag. Print.
@article{1995670,
  abstract     = {Eight years (2002--2010) of Advanced Microwave Scanning Radiometer--EOS (AMSR-E) snow water equivalent (SWE) retrievals and Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover fraction (SCF) observations are assimilated separately or jointly into the Noah land surface model over a domain in Northern Colorado. A multiscale ensemble Kalman filter (EnKF) is used, supplemented with a rule-based update. The satellite data are either left unscaled or are scaled for anomaly assimilation. The results are validated against in situ observations at 14 high-elevation Snowpack Telemetry (SNOTEL) sites with typically deep snow and at 4 lower-elevation Cooperative Observer Program (COOP) sites. Assimilation of coarse-scale AMSR-E SWE and fine-scale MODIS SCF observations both result in realistic spatial SWE patterns. At COOP sites with shallow snowpacks, AMSR-E SWE and MODIS SCF data assimilation are beneficial separately, and joint SWE and SCF assimilation yields significantly improved root-mean-square error and correlation values for scaled and unscaled data assimilation. In areas of deep snow where the SNOTEL sites are located, however, AMSR-E retrievals are typically biased low and assimilation without prior scaling leads to degraded SWE estimates. Anomaly SWE assimilation could not improve the interannual SWE variations in the assimilation results because the AMSR-E retrievals lack realistic interannual variability in deep snowpacks. SCF assimilation has only a marginal impact at the SNOTEL locations because these sites experience extended periods of near-complete snow cover. Across all sites, SCF assimilation improves the timing of the onset of the snow season but without a net improvement of SWE amounts.},
  articleno    = {W01522},
  author       = {De Lannoy, Gabri{\"e}lle and Reichle, Rolf and Arsenault, Kristi R and Houser, Paul R and Kumar, Sujay and Verhoest, Niko and Pauwels, Valentijn},
  issn         = {0043-1397},
  journal      = {WATER RESOURCES RESEARCH},
  keyword      = {VARIABILITY,DEPTH,CLIMATE,MODIS,INFORMATION-SYSTEM,DEPLETION CURVES,PASSIVE MICROWAVE,LAND-SURFACE MODEL,ENSEMBLE KALMAN FILTER,UNCERTAINTY},
  language     = {eng},
  number       = {1},
  pages        = {17},
  title        = {Multiscale assimilation of Advanced Microwave Scanning Radiometer-EOS snow water equivalent and Moderate Resolution Imaging Spectroradiometer snow cover fraction observations in northern Colorado},
  url          = {http://dx.doi.org/10.1029/2011WR010588},
  volume       = {48},
  year         = {2012},
}

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