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The PRISM Approach to Mapping Climate in Complex Regions

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Title: The PRISM Approach to Mapping Climate in Complex Regions


1
The PRISM Approach to Mapping Climate in Complex
Regions
  • Christopher Daly
  • Director, PRISM Group
  • Northwest Alliance for Computational Science and
    Engineering
  • Department of Geosciences
  • Oregon State University
  • Corvallis, Oregon, USA

2
  • PRISM Group Facts
  • 5-FTE applied research team at Oregon State
    University, 100 externally funded
  • The PRISM Group is the only center in the world
    dedicated solely to the spatial analysis of
    climate
  • PRISM climate mapping technology has been
    continuously developed, and repeatedly
    peer-reviewed, since 1991
  • The PRISM Group is the de facto climate mapping
    center for the US
  • The PRISM Group is advancing Geospatial
    Climatology as an emerging discipline

3
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4
Oregon Annual Precipitation
5
Oregon Annual Precipitation
6
Oregon Annual Precipitation
7

Oregon Annual Precipitation
8
Oregon Annual Precipitation
9
Rationale
  • Observations are rarely sufficient to directly
    represent the spatial patterns of climate
  • Human-expert mapping methods often produce the
    best products, but are slow, inconsistent, and
    non-repeatable
  • Purely statistical mapping methods are fast and
    repeatable, but rarely provide the best accuracy,
    detail, and realism
  • Therefore
  • The best method may be a statistical approach
    that is automated, but developed, guided and
    evaluated with expert knowledge


10
Knowledge-Based System KBS
  • Knowledge acquisition capability Elicit expert
    information
  • Knowledge base Store of knowledge
  • Inference Engine Infer solutions from stored
    knowledge
  • User interface Interaction and explanation
  • Independent verification Knowledge refinement


11
PRISM
Parameter-elevation Regressions on Independent
Slopes Model
  • Generates gridded estimates of climatic
    parameters
  • Moving-window regression of climate vs. elevation
    for each grid cell
  • Uses nearby station observations
  • Spatial climate knowledge base weights stations
    in the regression function by their physiographic
    similarity to the target grid cell

12
Oregon Annual Precipitation
Interface
13
PRISM
Knowledge Base
  • Elevation Influence on Climate

14
1961-90 Mean January Precipitation, Sierra
Nevada, CA, USA
Oregon Annual Precipitation
15
1961-90 Mean August Max Temperature, Sierra
Nevada, CA, USA
Oregon Annual Precipitation
16
1963-1993 Mean November Precipitation, Puerto Rico
17
1963-93 Mean June Maximum Temperature, Puerto Rico
18
1971-90 Mean February Precipitation, European Alps
19
1961-90 Mean September Max Temperature, Qin Ling
Mountains, China
Oregon Annual Precipitation
20
PRISM Moving-Window Regression Function
Oregon Annual Precipitation
1961-90 Mean April Precipitation, Qin Ling
Mountains, China
Weighted linear regression
21
Governing Equation
  • Moving-window regression of climate vs
    elevation
  • y ß1x ß0
  • Y predicted climate element
  • x DEM elevation at the target cell
  • ß0 y-intercept
  • ß1 slope
  • x,y pairs - elevation and climate observations
    from nearby climate stations

22
Station Weighting
  • Combined weight of a station is
  • W f Wd Wz Wc Wf Wp Wl Wt We
  • Distance
  • Elevation
  • Clustering
  • Topographic Facet (orientation)
  • Coastal Proximity
  • Vertical Layer (inversion)
  • Topographic Index (cold air pooling)
  • Effective Terrain Height (orographic profile)

23
PRISM
Knowledge Base
  • Elevation Influence on Climate
  • Terrain-Induced Climate Transitions (topographic
    facets, moisture index)

24
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25
Rain Shadow 1961-90 Mean Annual
Precipitation Oregon Cascades
Portland
Mt. Hood
Eugene
Dominant PRISM KBS Components Elevation Terrain
orientation Terrain steepness Moisture Regime
Mt. Jefferson
2500 mm/yr
2200 mm/yr
Sisters
Three Sisters
350 mm/yr
Redmond
N
Bend
26
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27
1961-90 Mean Annual Precipitation, Cascade Mtns,
OR, USA
28
1961-90 Mean Annual Precipitation, Cascade Mtns,
OR, USA
29
Olympic Peninsula, Washington, USA
Flow Direction
30
Topographic Facets
? 4 km

? 60 km

31
Mean Annual Precipitation, 1961-90
Oregon Annual Precipitation
Max 7900 mm
Full Model
3452 mm 3442 mm 4042 mm
Max 6800 mm
32
Mean Annual Precipitation, 1961-90
Max 4800 mm
3452 mm 3442 mm 4042 mm
Facet Weighting Disabled
33
Mean Annual Precipitation, 1961-90
Oregon Annual Precipitation
Max 3300 mm
3452 mm 3442 mm 4042 mm
Elevation 0
34
Mean Annual Precipitation, 1961-90
Oregon Annual Precipitation
Max 7900 mm
Full Model
3452 mm 3442 mm 4042 mm
Max 6800 mm
35
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36
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37
PRISM
Knowledge Base
  • Elevation Influence on Climate
  • Terrain-Induced Climate Transitions (topographic
    facets, moisture index)
  • Coastal Effects

38
Coastal Effects 1971-00 July Maximum
Temperature Central California Coast 1 km
Sacramento
Stockton
Dominant PRISM KBS Components Elevation
Coastal Proximity Inversion Layer
34
San Francisco
Oakland
Fremont
San Jose
Preferred Trajectories
Santa Cruz
27
Pacific Ocean
20
Hollister
Monterey
Salinas
N
39
1961-90 Mean July Maximum Temperature, Central
California, USA
Coastal Proximity Weighting OFF
Coastal Proximity Weighting ON
40
PRISM
Knowledge Base
  • Elevation Influence on Climate
  • Terrain-Induced Climate Transitions (topographic
    facets, moisture index)
  • Coastal Effects
  • Two-Layer Atmosphere and Topographic Index

41
1971-2000 January Temperature, HJ Andrews Forest,
Oregon, USA
TMAX-Elevation Plot for January
Layer 1 Layer 2
TMIN-Elevation Plot for January
Layer 1 Layer 2
42
Mean Annual Precipitation, Hawaii
43
United States Potential Winter Inversion
44
Western US Topographic Index
45
Central Colorado Terrain and Topographic Index
Gunnison
Gunnison
Terrain
Topographic Index
46
January Minimum Temperature Central Colorado
Gunnison
Gunnison
Valley Bottom Elev 2316 m Below Inversion Lapse
5.3C/km T -16.2C
47
January Minimum Temperature Central Colorado
Gunnison
Mid-Slope Elev 2921 m Above Inversion Lapse
6.9C/km T -12.7C
48
January Minimum Temperature Central Colorado
Gunnison
Ridge Top Elev 3779 m Above Inversion Lapse
6.0C/km T -17.9C
49
Inversions 1971-00 January Minimum
Temperature Central Colorado
N
Dominant PRISM KBS Components Elevation
Topographic Index Inversion Layer
Taylor Park Res.
Crested Butte
-18
Gunnison
-13
-18C
Lake City
50
PRISM 1971-2000 Mean January Minimum Temperature,
800-m
Banana Belt
Cold air drainage
Snake Plain
51
Inversions 1971-00 July Minimum
Temperature Northwestern California
Pacific Ocean
N
Willits
9
Dominant PRISM KBS Components Elevation
Inversion Layer Topographic Index Coastal
Proximity
Ukiah
Lake Pilsbury.
10
17
16
Cloverdale
Lakeport
12
Clear Lake
17
52
PRISM
Knowledge Base
  • Elevation Influence on Climate
  • Terrain-Induced Climate Transitions (topographic
    facets, moisture index)
  • Coastal Effects
  • Two-Layer Atmosphere and Topographic Index
  • Orographic Effectiveness of Terrain (Profile)

53
United States Effective Terrain
United States Orographically Effective Terrain
54
Oregon Annual Precipitation
55
PRISM
Knowledge Base
  • Elevation Influence on Climate
  • Terrain-Induced Climate Transitions (topographic
    facets, moisture index)
  • Coastal Effects
  • Two-Layer Atmosphere and Topographic Index
  • Orographic Effectiveness of Terrain (Profile)
  • Persistence of climatic patterns
    (climatologically-aided interpolation)

56
Oregon Annual Precipitation
Leveraging Information Content of High-Quality
Climatologies to Create New Maps with Fewer Data
and Less Effort
Climatology used in place of DEM as PRISM
predictor grid
57
PRISM Regression of Climate vs Climate or
Weather vs Climate
20 July 2000 Tmax vs 1971-2000 Mean July Tmax
58
Recent Projects
  • Updated 1971-2000 mean monthly P, Tmax, Tmin maps
    for the US at 800-m resolution (USDA-NRCS, NPS,
    USFS)
  • Spatial-Probabilistic QC system for SNOTEL
    observations (NRCS)
  • 1971-2000 monthly precipitation climatologies for
    NW Oregon conditional on 700-mb flow direction
    (NWS Western Region)
  • Extended monthly time series maps of P, Tmax,
    Tmin, Tdew for climate monitoring (USFS)


59
Future Directions
  • Engage in collaborative projects to develop the
    use of PRISM and PRISM climatologies for
    downscaling numerical weather prediction models
  • Continue to develop technology to move to smaller
    time steps and towards real time operation
  • Explore using remotely-sensed data to improve
    PRISM accuracy in under-sampled areas (and
    vice-versa)
  • Continue to develop PRISMs Spatial Climate
    Knowledge Base

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