A 85-year Retrospective Hydrologic Analysis for the Western US Nathalie Voisin, Hyo-Seok Park, Alan F. Hamlet, Andrew W. Wood, Ned Guttman # and Dennis P. Lettenmaier Department of Civil and Environmental Engineering # National Climatic Data Center University of Washington Boulder, CO Introduction A frequently encountered difficulty in assessing model-predicted land–atmosphere exchanges of moisture and energy is the absence of comprehensive observations to which model predictions can be compared at the spatial and temporal resolutions at which the models operate. Various methods have been used to evaluate the land surface schemes in coupled models, including: comparison of model-predicted energy and radiative fluxes with tower measurements during periods of intensive observations comparison of model-predicted evapotranspiration with values derived from atmospheric balances over large river basins, comparison of (routed) model-predicted runoff with observed streamflow, comparison of model predictions of soil moisture with spatial averages of point observations. While these approaches have provided useful model diagnostic information, the observation-based products used in the comparisons typically are inconsistent with the model variables with which they are compared, due to differences in spatial and temporal resolution. In a previous study (Maurer et al. 2002), a model-derived data set of land surface states and fluxes was derived for the conterminous United States and portions of Canada and Mexico. The data set spans the period 1950–2000, and is at a 3-h time step with a spatial resolution of 1/8 degree. These data allow the evaluation of the interaction of the water balance components over large regions for long periods. The National Climatic Data Center (NCDC) has recently created digital archives of daily climatological data for the continental U.S. going back to the beginning of the period of instrumental records. We describe an extension of the Maurer et al data back to 1916 and forward to 2003, a period for which adequate station density exists to perform hydrologic simulations with the Variable Infiltration Capacity (VIC) model. A particular advantage of this 85-year period is that it includes the droughts of 1930s, which facilitates comparative evaluations with more recent events. Conclusion The derived data (soil moisture, snow water content, runoff) are distinct from reanalysis products in that precipitation is a gridded product derived directly from observations, and both the land surface water and energy budgets balance at every time step. Simulated runoff match observations fairly well, and inter annual variability is well preserved over large river basins. On this basis, and given the physically based model parameterizations, we argue on the basis of closure that other terms in the surface water balance (e.g., soil moisture and evapotranspiration) must be reasonably well represented, at least for the purposes of diagnostic studies such as those in which atmospheric model reanalysis products have been widely used. These characteristics make this dataset useful for a variety of studies, especially where ground observations are lacking. Pre-processing of surface data input The National Climatic Data Center (NCDC) has recently created digital archives of daily climatological data (primarily precipitation and daily temperature maxima and minima) for the continental U.S. going back to the beginning of the period of instrumental records. Previous electronic archives were typically available only back to about 1948, with a few stations digitized back to the 1930's. Using the newly available data merged with the previous archive ( ), we have created a 1/8 degree data set of precipitation, temperature, and derived radiative forcings and other surface variables needed to drive the Variable Infiltration Capacity (VIC) macroscale hydrology model over the western U.S. (soon to be extended to the entire conterminous U.S.). The first step though consists of developing a method, based an carefully quality controlled HCN (Historical Climatology Network; see Easterling et al, “United States Historical Climatology Network (U.S. HCN) Monthly Temperature and Precipitation Data”, ORNL/CDIAC-87, NDP-019/R3. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee) stations to control for drift in the gridded data that otherwise results from changes in the stations included over time. We proceeded as follows: 1/8 Degree VIC Hydrologic Model and Simulated Channel Network The preliminary VIC simulations for the Shasta reservoir, CA, the Dalles, OR and Hoover Dam, NV show a fair agreement with observations. There is a noticeable peak underestimation and phase lag at the Dalles, OR but the interannual variability seems to be well preserved (see e.g. circled drought periods). The selected drought periods of the 1930’s and 1970’s are analyzed below so as to assess the severity of recent western U.S. drought in a centennial context. Validation of VIC Water Balance H22B-0913 Hydrologic simulations – severity of ongoing extreme events relative to the past 1929 Drought 1930 Drought 1931 Drought 1976 Drought 1977 Drought 2002 Drought ( in California ) climatology April 1 st Snow April 1st Snow Anomaly ( > 50 mm) ( 10 mm threshold) (a) August 1 st August 1 st Soil Soil Moisture Moisture Anomaly, ( > 0 mm/day ) 3 layers (mm/day) (b) June Runoff Anomaly ( > 0 mm/day ) (mm/day) (c) ( Columbia River at the Dalles, OR Sacramento River at Shasta reservoir, CA Colorado River at Hoover Dam, NV 3 4 Preprocessing Regridding Lapse Temperatures Correction to Remove Temporal Inhomogeneities HCN/HCCD Monthly Data Topographic Correction for Precipitation Coop Daily Data PRISM Monthly Precipitation Maps Schematic Diagram for Data Processing of VIC Meteorological Driving Data Hydrologic Model The Variable Infiltration Capacity (VIC) hydrologic model (schematic diagram below) has been implemented at 1/8 degree spatial resolution over the study domain. Each grid cell is about 12 km by 12 km. Runs were made in water balance mode using a time step of 24 hours and a snow model time step of 1 hour. Using the station meta data for indexing, the data were gridded to a uniform 1/8 degree grid over the study domain. Precipitation data were then rescaled for each month and each grid location by comparing the long term mean of the raw data from to the PRISM (Daly et al., 1984, J. of Applied Met. (33) pp ) means for the same location and time period. The temporal variability of the precipitation data was directly derived from the station data, but the spatial distribution was forced to match the PRISM results in the long-term mean for each month at each location. Earlier records were corrected by the same scaling fraction, even though the exact group of stations that define the raw precipitation values are not guaranteed to be the same in different periods. No attempt was made in this preliminary analysis to remove temporal inhomogeneities in the precipitation time series. Wind data were gathered from NCAR reanalysis, and the daily climatological mean value for each grid cell was used to define the daily mean wind speed. This approach was used because reanalysis data are not available prior to (a) Black values are under -300 mm snow anomalies, (b) Black values are under -200 mm/day anomalies, (c) Black values are under -1mm/day anomalies 5