Assessing the Influence of Decadal Climate Variability and Climate Change on Snowpacks in the Pacific Northwest JISAO/SMA Climate Impacts Group and the Department of Civil and Environmental Engineering, University of Washington Alan F. Hamlet Philip W. Mote Dennis P. Lettenmaier Overview Decadal and interannual climate variability and (at longer timescales) global warming all affect trends in snowpack in the Pacific Northwest. The figure below, for example, shows the effects of the Pacific Decadal Oscillation (PDO) and the El Niño Southern Oscillation (ENSO) on summer streamflow in the Columbia River, which is highly correlated with winter snowpack. Here we analyze trends in snow water equivalent (SWE) on April 1 (commonly the spring peak) over the Pacific Northwest using a high quality long-term data set of precipitation and temperature and the VIC macro- scale hydrologic model (Liang et al, 1994; see schematic below) implemented at 1/8 th degree resolution. Separate runs are made holding either temperature or precipitation fixed for each month, which allows us to isolate the effects of trends in temperature and precipitation. In addition, the results are composited according to warm PDO epochs to examine the role of decadal scale climate variability in the overall trends. Linear trends are extracted from the model simulations of SWE for each grid cell. For cells with more than 25 mm of average SWE, relative trends (i.e. [raw trend]/ [lt mean]) are then summarized in the plots shown to the right. April 1 SWE (mm) Description of Experiment 1: Temperature and precipitation are unperturbed and the results are not composited. These results are a continuous time series from and reflect observed trends in the forcings over that time period. Discussion:: Modest positive trends dominate at higher elevations, suggesting increasing trends in precipitation. These values are consistent with observed trends in PNW precipitation. At lower elevations (and in some high elevation areas in the southern portion of the basin), trends are predominantly negative, suggesting that temperature effects are the dominant driver in these locations. Relative Trend in April 1 SWE (% per year) Relative Trend in April 1 SWE (% per year) Elevation (m) Description of Experiment 2: Precipitation for each month is held constant at the climatological value for each grid cell. Temperature varies as in the unperturbed time series. These results reflect the SWE trends attributable to temperature trends only. Description of Experiment 3: Temperature for each month is held constant at the climatological value for each grid cell. Precipitation varies as in the unperturbed time series. These results reflect the SWE trends associated with precipitation trends only. Cool Warm Description of Experiment 4: Data used in Experiment 1 is composited for warm PDO epochs ( and ). Relative trends are based on this new 41-year time series. Relative Trend in April 1 SWE (% per year) Elevation (m) Relative Trend in April 1 SWE (% per year) Elevation (m) Relative Trend in April 1 SWE (% per year) Elevation (m) Relative Trend in April 1 SWE (% per year) Relative Trend in April 1 SWE (% per year) Relative Trend in April 1 SWE (% per year) Discussion:: With precipitation variability removed from the analysis, temperature variability becomes the primary determinant of trends. Note that although many high elevation cells do not experience strong trends in SWE (as expected), almost all of the trends are negative in sign. This reflects the general warming trends experienced by the entire region over the period of analysis. Lower elevation cells are more sensitive to warming than high elevation cells. Discussion:: With temperature variability removed from the analysis, precipitation variability becomes the primary determinant of trends. Note that the majority of cells have experienced increasing precipitation over the period of analysis. Elevation dependence in the results is not strongly evident. It is important to note, however, that no primary station data from high elevation sites is used in constructing the gridded precipitation data sets used to drive the hydrologic model, so differences in precipitation trends in high and low elevation areas are not explicitly represented. Discussion:: The results above show much larger relative trends (partly due to lower average snowpacks during warm PDO periods). Trends are mostly negative. High elevation areas show small trends, suggesting small trends in precipitation. Because the two periods are climatologically similar, the influence of decadal variability on the trends is reduced. The trends shown are therefore estimates of the trends associated with other sources of variability, such as global warming. The results show that the period from was warmer than the period from despite similar North Pacific ocean variability. Compare with the scatter plot in Experiment 1. P2.8 Liang, X., Lettenmaier, D.P., Wood, E.F. and Burges, S. J., 1994, A Simple Hydrologically Based Model of Land Surface Water and Energy Fluxes for General Circulation Models, J. Geophys. Res., 99, D7, pp14,415-14,428