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Glen E. Liston, Daniel L. Birkenheuer, Christopher A. Hiemstra, Donald W. Cline, and Kelly Elder

development at ESRL utilizes a 10-km horizontal grid (125 × 105) with 21 isobaric vertical levels and an hourly temporal resolution. The purpose of a system such as LAPS is to not only provide an up-to-date atmospheric state representation for nowcasting and assessment but also serve as a mechanism to initialize local-scale mesoscale weather forecast models. LAPS makes use of a wide range of observational datasets as part of its analyses, including 1) surface observations from regional surface networks

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Rafał Wójcik, Konstantinos Andreadis, Marco Tedesco, Eric Wood, Tara Troy, and Dennis Lettenmeier

described in section 3 . The BMA scheme is briefly described below. a. Problem statement Let y be a scalar quantity to be forecast, and let f k be the forecast of y produced by model k . The forecast f k is then characterized by a conditional probability density function (pdf), g k ( y|f k ), which can be interpreted as the pdf of y conditional on f k , given that f k is the best forecast in the ensemble. The BMA predictive pdf for the k -member ensemble of forecasts can be written as

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Kelly Elder, Don Cline, Glen E. Liston, and Richard Armstrong

1. Introduction Snowpack measurements have been taken in North America for nearly 100 years, with the objective of increasing our ability to forecast runoff from snow-covered regions. Point measurements have been the norm, although short transects from snow courses provide a limited representation of the variability of the spatial nature of snow water equivalent (SWE). The snowpack telemetry (SNOTEL) system of the Natural Resources Conservation Service (NRCS) gives regional SWE information in a

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Glen E. Liston, Christopher A. Hiemstra, Kelly Elder, and Donald W. Cline

could also be applied to other cold regions and cold season landscapes to help understand snow-distribution characteristics and features in those areas. Acknowledgments The authors thank Dan Birkenheuer for kindly providing the LAPS datasets. This work was supported by NASA Grants NAG5-11710, NNG04GP59G, and NNG04HK191, and NOAA Grant NA17RJ1228. REFERENCES Albers, S. C. , 1995 : The LAPS wind analysis. Wea. Forecasting , 10 , 342 – 352 . 10.1175/1520-0434(1995)010<0342:TLWA>2.0.CO;2 Albers

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Glen E. Liston and Christopher A. Hiemstra

forecast error statistics. J. Geophys. Res. , 99 , 10143 – 10162 . 10.1029/94JC00572 Fan, Y. , Van den Dool H. M. , Lohmann D. , and Mitchell K. , 2006 : 1948–98 U.S. hydrological reanalysis by the Noah land data assimilation system. J. Climate , 19 , 1214 – 1237 . 10.1175/JCLI3681.1 Fisher, M. , Leutbecher M. , and Kelly G. A. , 2005 : On the equivalence between Kalman smoothing and weak-constraint four-dimensional variational data assimilation. Quart. J. Roy. Meteor. Soc

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D. Marks, A. Winstral, G. Flerchinger, M. Reba, J. Pomeroy, T. Link, and K. Elder

already limited water resources in the western United States ( Barnett et al. 2005 ) and will require improved monitoring ( Schaefer and Werner 1996 ; Abramovich and Pattee 1999 ). Furthermore, as empirical methods calibrated on past climate conditions become less reliable, a more physically based spatially explicit approach to forecasting melt from the seasonal snow cover across the region ( Garen and Marks 1998 , 2005 ) is essential. A number of studies have focused on both measuring and modeling

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Susan Frankenstein, Anne Sawyer, and Julie Koeberle

approximations, climate-feedback research, remote sensing applications, and hydrological modeling and forecasting ( Hinzman and Kane 1991 ; Shook et al. 1993 ; Baral and Gupta 1997 ; Harms and Chanasyk 1998 ; Liston, 1999 ; Cline et al. 2003 ). Because it is impossible to physically measure the full extent and characteristics of the snowpack, numerical models are needed to help estimate the water content of the snow [snow water equivalent (SWE)] and melt-out dates. In this paper, we investigate how well

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