HJ Andrews Temperature Mapping Project
UNIQUE CHARACTERISTICS OF METHODS
1. Radiation-adjusted maximum/minimum mean monthly temperature maps with the effects of vegetation minimized.
2. Maximum/minimum mean monthly temperature maps (and average annual means) with the effects of vegetation removed, but not corrected for incoming monthly solar radiation.
1. Radiation maps explicitly taking into account the effects of topography as well as monthly cloudiness and its effects on proportion of direct to diffuse radiation.
2. Regression functions relating incoming solar radiation to maximum temperature and sky view factor to minimum temperature, applicable for research in other mountainous forested areas.
3. Improved historical daily temperature datasets, quality-checked and consistently formatted.
4. Monthly mean maximum and minimum temperature datasets, quality-checked and adjusted to 30-year period of record.
5. Hemispherical fisheye photographs for every site in the HJA, past and present.
6. Comprehensive and detailed site descriptions (summaries of radiation regimes, canopy covers, etc).
7. Comprehensive list of site sensor specifications and heights for the period of record.
8. Improved site locations and reference map.
*** All products readily available by downloading from website ***
Characteristics of project methods that make it unique:
1. The local scale of the study (a small mountain watershed) differentiates it from other mapping studies on larger scales.
2. Explicitly taking into account topographic effects on solar radiation such as terrain shading, slope, aspect and elevation and mapping their effects on temperatures at this scale has not been done before.
3. Quantifying the effects of forest canopy and topography on both direct and diffuse solar radiation to make temperature corrections by using fisheye photography has not been done before.
4. Average monthly attenuation due to cloudiness is taken into account in a more comprehensive manner than other studies.
5. The solid 30-year HJA dataset, with a high spatial density of sites and reliable year-round data, is a treasure trove of data matched by few other spatial climate studies.
6. A spatial temperature interpolator (PRISM) is employed that uses a two-layer atmosphere model (i.e., explicitly taking into account temperature inversions, a common phenomenon in the HJA) and topographic facet weighting.
Thus we have a golden opportunity to improve upon previous temperature mapping work at the HJA with an improved dataset and more comprehensive tools at our disposal. Our final maps will represent the temperature regime of the HJA in the absence of vegetation, which is also unique and allows our results to be applicable in a wide range of fields requiring temperature data in their analyses. We seek to combine all of these unique methods to create the most spatially accurate set of temperature maps of the HJA possible with existing resources.