Weather stations in mountainous areas are too sparsely distributed to measure accurately the complexity of the surface temperature distribution, which varies with elevation, aspect, and convexity of terrain. Climate-quality stations are even sparser. For hydrologic modeling and high-resolution gridding of weather observations in complex terrain, it is common to assume that the surface lapse rate (that is, rate of change of mean surface temperature with altitude) is -6.5C/km, with the justification that this is approximately the moist adiabatic lapse rate and that the primary control of surface temperature in mountainous terrain is in contact with the (presumably moist adiabatic) atmosphere. The true surface lapse rate, however, may under some conditions be quite far from -6.5C/km.

In this study we combine long records of surface weather at sparsely distributed stations in the Washington Cascades with radiosonde observations, NCEP reanalysis, a mesoscale numerical weather prediction model, and a temporary network of temperature sensors to provide a fuller picture of the temporal and spatial variability of the surface lapse rate and its dependence on large-scale atmospheric flow. Lapse rates are most extreme in summer with maximum temperatures varying by approximately -7C/km and minimum temperatures by -2.5C/km; the rest of the year both lapse rates are closer to -5C/km. We will discuss the consequences of these findings for hydrologic modeling and the estimation of the sensitivity to climate change.