SPATIOTEMPORAL VARIABILITY OF HUMIDITY ACROSS THE CONTIGUOUS UNITED STATES AND SOUTHERN CANADA USING REGIONAL NETWORKS

The objective of this dissertation was to show that there is now enough observed humidity data available so that estimates of humidity, along with their necessary assumptions, can be replaced by measured humidity data. The range of applications that depend on humidity data is huge, ranging from water use efficiency of plants and plant stress to human health and agricultural practices. Biases due to the use of estimated humidity can be expected to have short and long impacts, decreasing the accuracy and precision of these, and many other, applications. Data from local, regional, and national observation networks was gathered, and custom quality control routines were written to remove bad data points from over 45000 stations, leaving 12533 usable stations. While still not at the same number of observations as temperature or precipitation, this number is nearly ten times as high as two decades ago. The work I performed consists of three major components, corresponding to the three main chapters of this dissertation. In chapter one, I describe data sources and quality control methods, along with some basic statistics of humidity, describing which geographic variables often used to predict temperature and precipitation can be used to do the same for humidity. Chapter two defines specific diurnal patterns (or “types”) of dew point across the United States, including their attributes, causes, and potential influences. Chapter three analyzes biases in evapotranspiration, heat indices, and relative humidity levels that are a direct result of using estimated humidity data. Chapter four discusses contributions this work makes to the scientific community, and potential further research to build on what is presented here. While it may seem that the science of humidity should be well beyond data gathering and bias analysis, the fact remains that humidity is still very commonly estimated through the use of minimum temperature, and diurnal changes in dew point are often ignored. My hope is that this work makes a dent in often deeply entrenched practices, leading others to make the effort to incorporate measured humidity data into their work and study