| Atmospheric moisture is an important factor in moderating air temperature, at all scales, and is critical to human comfort, vegetation growth, climate classification, and climate change. Atmospheric moisture records are relatively scarce across both space and time, while maximum and minimum temperature are the two most commonly measured climate variables, with records going back over 100 years at thousands of locations around the world. In humid regions, moisture can be estimated from temperature with good results, but those models do not work well in arid regions, as the minimum temperature rarely approaches the dew point. Since arid regions exist at the margins of sustainability and are undergoing rapid development, it is important to extend the moisture record back in time as far as possible. This research created a linear regression model to estimate mean daily dew point temperature from daily minimum temperature and diurnal temperature range in an arid region (Arizona). The model performed significantly better than previous models for arid locations, with an average mean absolute error of 4.76°C for agricultural sites, 4.46°C for urban sites, 4.96°C for remote high elevation sites, and 4.13°C for Phoenix airport.; Eight years of daily data at 83 weather stations in Arizona were used to develop the regression model. The generalized version of this model has an average of 3°C less error, both systematic and unsystematic, than two previous models, for the arid region. The model was generalized by interpolating the regression coefficients from the development stations, using the ordinary kriging, and extracting regression coefficients from the raster grid at other test locations. The model is simple, objective, retains most of the natural variability of the data, requires no special calibration, and can be applied to any location. Although this study found a high spatial correlation for temperature and humidity between sites, the diurnal temperature-dew point relationship varied widely, due to the microclimate characteristics, and more importantly, as a result of the extreme variability of humidity in arid regions. |
