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

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

Use of Remote Sensing, Hydrologic Tree-Ring Reconstructions, and Forecasting for Improved Water Resources Planning and Management

Uncertainties were analyzed in three areas (remote sensing, dendroclimatology, and climate modeling) relevant to current water resources management. First, the research investigated the relationships between remotely sensed and in situ Snow Water Equivalent (SWE) datasets in three western U.S. basins. Agreement between SWE products was found to increase in lower elevation areas and later in the snowpack season. Principal Components Analysis (PCA) revealed two distinct snow regions among the datasets and Singular Value Decomposition (SVD) was used to link both data products with regional streamflow. Remotely sensed SWE was found to be sufficient to use in statistically based forecast models in which magnitude did not affect results. Second, the research investigated the dendroclimatic potential of a critical flood control and hydropower region in the southeastern U.S. (Tennessee Valley) using climate division precipitation and regional tree-ring chronology datasets. Tennessee Valley May–July precipitation was reconstructed from 1692 to 1980 (289 years) using a stepwise linear regression model (R2 = 0.56). Weibull analysis illustrated that the Tennessee Valley reconstruction model developed generally underestimated extreme precipitation and overestimated average precipitation. The longest May–July drought occurred over 10 consecutive years (1827–1836). Instrumental records indicated that the two most recent droughts (1985–1988 and 2006–2008) ranked second and third in severity in the past three centuries. Third, past, present, and future patterns and extremes in streamflow within the North Platte River Basin were investigated. A streamflow reconstruction dating back to 1383 using tree rings was created to provide a proxy for the long-term variability in the region. Projected streamflow datasets from the Community Climate System Model (CCSM) were gathered to acquire future insight of the hydroclimatic variability within the North Platte River Basin (NRPB). Drought analysis revealed that 2002–2008 was one of the driest periods in the past 600 years. Multiple CCSM projections suggest that in the future, drier (5th percentile) years will become wetter relative to 1970–1999 CCSM hindcasts. Future average (50th percentile) and wet (95th percentile) years may yield statistically higher streamflow compared to those seen in the historical (1383–1999) record, suggesting potential anthropogenic influence beyond the historic natural variability