Background/Question/Methods According to climate change projections for the southwest United States, temperatures will be warmer in the future and snowpack is likely to decrease. It is important to understand how land surface variables such as snowpack interact with the atmosphere. Snowpack influences vegetative growth and the partitioning of latent and sensible heat fluxes through enhanced soil moisture, which can cause surface temperature changes and precipitation feedbacks. Soil moisture anomalies are generally considered to provide a local positive feedback on precipitation. In the southwest, however, several studies have found a negative feedback between spring snowpack and subsequent summer precipitation from the North American monsoon. Consideration of spring season land-atmosphere feedbacks on interannual fluctuations of the current climate may provide a means of assessing possible long-term changes in summer precipitation associated with decreasing snowpack.
The study area includes mountainous regions of the southwest United States, for which observations of surface energy budget (SEB) variables are limited. We will use assimilated data from the high resolution (32 km) National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) and compare these data with available observations including flux tower measurements. To assess vegetative response we will use normalized difference vegetation index (NDVI) data.
Results/Conclusions
Preliminary results from the NARR suggest that soil moisture remembers an anomalously high snowpack for a month after snow disappearance in late spring. Summer rainfall then overrides soil moisture memory from snowpack. Air temperature in a high snowpack year remains suppressed throughout the spring. In the high snowpack circumstance, the Bowen ratio remains higher relative to a low snowpack year until monsoon onset. The NARR includes fixed, prescribed ecosystem types, causing albedo after snow disappearance to vary spatially but not temporally. Since vegetation in the NARR does not interact with the hydrologic cycle, this makes the NARR a useful control dataset for assessing the real role of vegetation in the surface energy budget.
From our initial results, we conclude that there is land surface memory of snowpack between the time of snow disappearance and monsoon onset. Future analysis will focus on more complete characterization of the seasonal cycle of the SEB using modeled and observational data, and assessment of vegetation as a memory variable. This study has implications for understanding how decreasing snowpack and plant community changes could alter atmospheric feedbacks and affect warm season precipitation.
