Evaluation of the MODIS snow cover fraction product

2012 ◽  
Vol 28 (3) ◽  
pp. 980-998 ◽  
Author(s):  
Kristi R. Arsenault ◽  
Paul R. Houser ◽  
Gabriëlle J. M. De Lannoy
Keyword(s):  
Snow Cover ◽  
Snow Cover Fraction ◽  
Fraction Product

scholarly journals Satellite observations of changes in snow-covered land surface albedo during spring in the Northern Hemisphere

2015 ◽  
Vol 9 (5) ◽  
pp. 1879-1893 ◽  
Author(s):  
K. Atlaskina ◽  
F. Berninger ◽  
G. de Leeuw
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Air Temperature ◽  
Land Surface ◽  
Surface Albedo ◽  
Vegetation Index ◽  
Precipitation Amount ◽  
Snow Cover Fraction ◽  
Air Temperatures ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Thirteen years of Moderate Resolution Imaging Spectroradiometer (MODIS) surface albedo data for the Northern Hemisphere during the spring months (March–May) were analyzed to determine temporal and spatial changes over snow-covered land surfaces. Tendencies in land surface albedo change north of 50° N were analyzed using data on snow cover fraction, air temperature, vegetation index and precipitation. To this end, the study domain was divided into six smaller areas, based on their geographical position and climate similarity. Strong differences were observed between these areas. As expected, snow cover fraction (SCF) has a strong influence on the albedo in the study area and can explain 56 % of variation of albedo in March, 76 % in April and 92 % in May. Therefore the effects of other parameters were investigated only for areas with 100 % SCF. The second largest driver for snow-covered land surface albedo changes is the air temperature when it exceeds a value between −15 and −10 °C, depending on the region. At monthly mean air temperatures below this value no albedo changes are observed. The Enhanced Vegetation Index (EVI) and precipitation amount and frequency were independently examined as possible candidates to explain observed changes in albedo for areas with 100 % SCF. Amount and frequency of precipitation were identified to influence the albedo over some areas in Eurasia and North America, but no clear effects were observed in other areas. EVI is positively correlated with albedo in Chukotka Peninsula and negatively in eastern Siberia. For other regions the spatial variability of the correlation fields is too high to reach any conclusions.

scholarly journals Evaluation of snow cover fraction for regional climate simulations in the Sierra Nevada

2014 ◽  
Vol 35 (9) ◽  
pp. 2472-2484 ◽  
Author(s):  
Melissa L. Wrzesien ◽  
Tamlin M. Pavelsky ◽  
Sarah B. Kapnick ◽  
Michael T. Durand ◽  
Thomas H. Painter
Keyword(s):  
Snow Cover ◽  
Sierra Nevada ◽  
Regional Climate ◽  
Snow Cover Fraction ◽  
Climate Simulations

scholarly journals Improvement of the Snow Depth in the Common Land Model by Coupling a Two-Dimensional Deterministic Ensemble Model with a Variational Hybrid Snow Cover Fraction Data Assimilation Scheme and a New Observation Operator

2017 ◽  
Vol 18 (1) ◽  
pp. 119-138 ◽  
Author(s):  
Jianhui Xu ◽  
Feifei Zhang ◽  
Hong Shu ◽  
Kaiwen Zhong
Keyword(s):  
Data Assimilation ◽  
Snow Cover ◽  
Snow Depth ◽  
Cloud Cover ◽  
Two Dimensional ◽  
Observation Operator ◽  
Snow Cover Fraction ◽  
Depletion Curve ◽  
Common Land Model ◽  
The Common

Abstract During snow cover fraction (SCF) data assimilation (DA), the simplified observation operator and presence of cloud cover cause large errors in the assimilation results. To reduce these errors, a new snow cover depletion curve (SDC), known as an observation operator in the DA system, is statistically fitted to in situ snow depth (SD) observations and Moderate Resolution Imaging Spectroradiometer (MODIS) SCF data from January 2004 to October 2008. Using this new SDC, a two-dimensional deterministic ensemble–variational hybrid DA (2DEnVar) method of integrating the deterministic ensemble Kalman filter (DEnKF) and a two-dimensional variational DA (2DVar) is proposed. The proposed 2DEnVar is then used to assimilate the MODIS SCF into the Common Land Model (CoLM) at five sites in the Altay region of China for data from November 2008 to March 2009. The analysis performance of the 2DEnVar is compared with that of the DEnKF. The results show that the 2DEnVar outperforms the DEnKF as it effectively reduces the bias and root-mean-square error during the snow accumulation and ablation periods at all sites except for the Qinghe site. In addition, the 2DEnVar, with more assimilated MODIS SCF observations, produces more innovations (observation minus forecast) than the DEnKF, with only one assimilated MODIS SCF observation. The problems of cloud cover and overestimation are addressed by the 2DEnVar.

An empirical formula to compute snow cover fraction in GCMs

2004 ◽  
Vol 21 (4) ◽  
pp. 529-535 ◽  
Author(s):  
Tongwen Wu ◽  
Guoxiong Wu
Keyword(s):  
Snow Cover ◽  
Empirical Formula ◽  
Snow Cover Fraction

scholarly journals Assimilation of MODIS Snow Cover Fraction Observations into the NASA Catchment Land Surface Model

2018 ◽  
Vol 10 (2) ◽  
pp. 316 ◽  
Author(s):  
Ally M. Toure ◽  
Rolf H. Reichle ◽  
Barton A. Forman ◽  
Augusto Getirana ◽  
Gabrielle J. M. De Lannoy
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Snow Cover Fraction

scholarly journals Impacts of snow cover fraction data assimilation on modeled energy and moisture budgets

2013 ◽  
Vol 118 (14) ◽  
pp. 7489-7504 ◽  
Author(s):  
Kristi R. Arsenault ◽  
Paul R. Houser ◽  
Gabriëlle J. M. De Lannoy ◽  
Paul A. Dirmeyer
Keyword(s):  
Data Assimilation ◽  
Snow Cover ◽  
Snow Cover Fraction
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