U53A-0702
Climate Mapping Challenges in Mountainous Regions
Christopher Daly , Wayne Gibson, George Taylor, and Matt Doggett
Spatial Climate Analysis Service
Oregon State University
Corvallis, Oregon
daly@coas.oregonstate.edu
Abstract
Rain Shadows
Cold Air Drainage and Inversions
Mountainous regions encompass some of the most complex climates in the world. The
presence of major topographic features, sometimes interacting with coastal effects, creates a
myriad of spatially complex precipitation and temperature regimes. Typically, only a small
number of these regimes are well-represented by surface observations. Therefore, producing
accurate climate maps for these regions can be quite challenging. PRISM, a knowledgebased climate mapping system, was originally developed in 1991 to map precipitation in the
mountainous western United States. Since then, it has been expanded and refined over time
to model more climate variables and address more climatological processes, and its use has
expanded worldwide. Model improvements have come primarily as a result of lessons
learned through repeated applications of the model and peer-review of the results. This
poster surveys some of the major climatological processes driving temperature and
precipitation patterns in mountainous regions, and how PRISM accommodates these
processes. These include elevational gradients, rain shadows, coastal influences, temperature
inversions, and cold air drainage.
PRISM Basics
PRISM (Parameter-elevation Regressions on Independent Slopes Model) generates gridded
estimates of climate parameters such as temperature and precipitation. The model is a
moving-window regression of climate vs. elevation that is calculated for each grid cell in a
digital elevation grid. Stations surrounding the grid cell provide data points for the
regression.
What makes PRISM unique is the extensive spatial climate knowledge base that calculates
station weights upon entering the regression function. These weights are based on each
station’s climatological similarity to the grid cell being estimated. Physiographic
information such as coastal proximity and terrain orientation are provided to these weighting
functions via additional gridded data. PRISM weighting functions currently account for
spatial variations in climate due to:
Mountains profoundly affect precipitation patterns in two ways: they amplify precipitation on
their windward slopes by forcing moisture-laden air to rise; and limit precipitation on their
leeward slopes by blocking low-level moisture and forcing air to descend. Mountains that
present a steep and bulky profile to the prevailing air flow tend to have the greatest effect on
precipitation patterns, while rolling hills that deviate little from the large-scale terrain pattern
have the least. The Oregon Cascades are a good example of a significant rain shadow; mean
annual precipitation drops from 2200 mm/yr at the crest of the Cascades, to only 350 mm/yr
just down the hill to the east. The components of the PRISM knowledge base that play the
greatest role in station weighting are elevation, terrain orientation, terrain profile, and
moisture regime.
Cold air drainage can occur throughout mountainous regions in all seasons, creating
highly complex spatial patterns of temperature. In summer, minimum temperatures in
sheltered valleys may be several degrees cooler than adjacent ridgetop locations,
especially during clear, calm conditions. In winter, weak solar heating allows cold air
drainage to dominate many areas of the western US, especially the interior, affecting both
minimum and maximum temperatures. The components of the PRISM knowledge base
that play the greatest role in station weighting are elevation, inversion layer, and
topographic position.
Coastal Terrain Effects
• Elevation - digital elevation grid (DEM)
• Terrain orientation - topographic facet (orientation) grids a six different scales
• Terrain profile – effective terrain height grid
• Moisture regime - PRISM straight-line storm trajectory model
• Coastal proximity - PRISM coastal trajectory model
• Inversion layers – potential inversion height grid
• Cold air pooling – topographic index grid (e.g., valley, slope, ridgetop)
Final Thoughts
Example of a PRISM weighted regression function of mean April precipitation vs.
Elevation for a DEM pixel in the Qing Ling Mountains, China.
Mountains play a major role in the distribution of temperature in coastal regions. The central
California coast is well-known for its extreme gradients in maximum temperature in summer,
caused by the interaction of the warm land mass, complex terrain, and the adjacent cool
Pacific Ocean. Terrain presents a significant obstacle to inland penetration of cool marine air,
channeling it through valleys and passes, and sheltering other areas from its effects. The
components of the PRISM knowledge base that play the greatest role in station weighting
here are elevation, coastal proximity, and inversion layer. Coastal proximity is estimated
with the PRISM coastal influence trajectory model.
Accurate mapping of climate in mountainous regions is a complex process, requiring a large
amount of information that defines the physiographic characteristics and similarities of
various locations. Factors that must be accounted for include elevation, terrain orientation
and profile to oncoming winds, topographic position (valley, slope or ridgetop), moisture
regime, coastal proximity, and inversion height..
A new project to map 1971-2000 mean monthly temperature and precipitation at 800-m
resolution over the US is now underway, funded by USDA-NRCS. The goal is for these
maps to represent the current state of knowledge regarding the spatial patterns and
magnitudes of climate in the US. To that end, a review of the draft maps will be performed
before the final maps are produced and released in 2005. If you have station data sets to
contribute or would like to be involved in the review process, please contact us.