HJ Andrews
Temperature Mapping Project
PRODUCTS AND
UNIQUE CHARACTERISTICS OF METHODS
Primary products:
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.
Secondary products:
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.