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Climate and Weather Projects at the NWCC to Support USDA-NRCS Activities
Climate Mapping Time Series Development Weather Generator Research (GEM) Serially Complete Dataset Snow Climate Monitoring & Analysis Soil Climate Monitoring & Analysis Internet Technologies for Climate Delivery
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Climate Mapping Collaborative effort between NRCS National Water and Climate Center (NWCC) and the Spatial Climate Analysis Service (SCAS) at Oregon State University Goal is to produce new maps and digital GIS layers of climate elements needed by the NRCS and others
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A Spatial Climate Modeling System
PRISM (Parameter-elevation Regressions on Independent Slopes Model) Statistical/Dynamical/Topographic approach Uses point data, a DEM and a coordinated set of rules, decisions and calculations, designed to mimic an “expert” climatologist For good reference see PRISM Guide Book under Technical Papers at the OSU PRISM web site
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PRISM Originally developed for precipitation only, now expanded to temperature, dewpoint, solar radiation and many derived variables such as HDD’s/CDD’s, GDD’s, frost dates, snowfall, snow water equivalent, etc. Most commonly applied in monthly or annual time increments, but also applied to events
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PRISM Model from OSU’s Spatial Climate Analysis Service
Funded primarily by the NRCS-NWCC since 1993 for development of spatial climate products for the U.S. 4 km horizontal resolution raster data, and ARC polygon coverages both available Most commonly applied in monthly or annual time increments, but also applied to events
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PRISM Any given grid cell value is determined by a linear regression of station values against elevation Stations assigned weights Combined weight of a station is a function of many factors
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PRISM-derived Products
Mean Mon. and Ann. Precipitation Mean Mon. and Ann. Temps (mx/mn) Frost Dates and Freeze-free Season Extreme Winter Min. Temps & Probs. Growing, Heating, Cooling degree days Snow-Water Equivalent & Snowfall Rainfall Erosivity (‘R-factor’ for RUSLE), Intensity-Duration-Frequency
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Other PRISM-derived Climate Map Products for the NRCS:
New Soil Climate Maps, including mean annual soil temperature, soil taxonomic regions Precipitation Efficiency, Climatic Index, and other “older” Thornthwaite products New Plant Hardiness Map of the U.S.
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Cartographic-quality Map of Mean Annual Precipitation for Idaho Produced at the USDA-NRCS NCGC
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Annual Precipitation Map of Elmore County, Idaho Produced by the NRCS NCGC
“Cut-out” of State Map
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July normal precipitation
(top) vs. July 1993 precipitation (bottom)
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PRISM - SWE Map - Oregon
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New Precipitation Frequency Maps Needed in the NRCS
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TP-40 100 Yr 24-hour pcpn. (in.) from SCS TR-55, 1986
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100 Year, 24-hour NOAA Atlas 2 Values (inches)
Northwest Colorado (1973)
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Ft. Collins CO Rainfall (in.), 5:30 -11 pm, July 28, 1997
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PRISM Product Dissemination
Web Sites: OSU (Raster and polygon coverages of practically everything produced to date (Arc, GRASS); documentation; metadata; DEM’s) NRCS (U.S., Regional and State mean annual precipitation cartographic products)
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Cartographic state mean annual precipitation maps Full repository of “official” NRCS PRISM layers
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PRISM Product Dissemination
Compact Discs: All precipitation layers for all of the U.S CD’s (East, Central, West) of the lower 48 states. Includes Arc Explorer viewing software, and all documentation. Available from the NRCS-NCGC:
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PRISM Product Dissemination
Hardcopy maps: Cartographic-quality, walls-size maps of mean annual precipitation for each state Available from the NRCS Climate Data Liaison in each state
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Wind Mapping to Support NRCS Air Quality Program
Need high resolution mean and event wind speeds and directions for whole U.S. Atmospheric model needed for this: Sue Ferguson at USFS Research Seattle Mean monthly winds of U.S. at 5 km resolution now nearly complete
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Time Series Development: Weather Generator Research and Integration
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Ultimate Question: What is really needed
Ultimate Question: What is really needed? (for applications needing point-serial data) A continuous time series of weather data of sufficient length to make reasonable assessments for planning decisions, of sufficient temporal resolution to match the time step in process models, and of sufficient spatial resolution and accuracy to have confidence in its application in any location in the U.S.
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What are our choices? Observed data -or- Model-generated data
Observed data: Point, “truth”, missing values, limited record, one realization, only 1 or 2 elements at many stations Generated data: Point, only an approximation of the “true” climate, serially-complete, easy to generate
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Why Stochastic Weather Generation Programs?
Easily accessible, serially-complete data sets are produced Easily modified outputs to match other modeling requirements Weather/Climate scenarios for locations with limited or no observed data Ability to adjust model parameters for playing “What If ?” games; risk assessments
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ARS-NRCS Weather Simulation Team (WST)
Formed in response to need for updated, more dynamic weather simulation tool Comprised of 5-10 ARS and NRCS scientists Major focus areas include storm generation (generating sub-daily time steps), GEM as a predictive tool (linkage to large-scale forcings), generation of all needed weather elements, and spatial distribution of generator parameters
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GEM: Generation of weather Elements for Multiple applications
Known as WGEN (Richardson, 1984) and USCLIMATE (Hanson et al., 1994) Preservation of serial and cross correlations Basic version is a point model, and delivers daily time series of precipitation, max/min temperature, solar radiation, average dewpoint and average wind speed
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Distributing GEM Model Parameters Using the PRISM (Parameter-elevation Regressions on Independent Slopes Model) system at Oregon State University Goal: To generate accurate climatic time series at any point in the U.S., regardless of the availability of historical climate information, for input to models, scenario development, and many other uses
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Annual mean of Tmin for wet/dry days from PRISM
-9 -3 2 oC
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Time Series Development: Serially Complete Dataset Project
To produce accurate historical climate time series, with no missing records, from NOAA climate stations nationwide (precipitation and temperature)
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Serially Complete Dataset
40+ years of daily pcpn. and max/min temps ( ) Approximately 11,000 precipitation and 7,300 temperature station records now available for all 48 conterminous states Generating an ASCII file of estimates for NCDC and UCAN Unique flags for estimates Journal of Applied Meteorology paper Sept. 2000
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Snow Climate Monitoring & Analysis: SNOTEL
Large Automated Climate Network Began in 1978 Over 650 remote site Generally in high elevation areas Located in the 12 Western States and Alaska Utilizes meteor burst communication technology to telemeter data
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SNOTEL Coverage
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SNOTEL Typical Remote Site Sensor Array
Snow Pillow used to measure snow water content Snow Depth All Season Precipitation Gage Air Temperature Includes current, 24 hour: maximum, minimum, and average
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SNOTEL Other Sensor Relative Humidity Solar Radiation
Wind Speed and Direction Barometric Pressure Water Level Soil Moisture and Temperature
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Typical SNOTEL Site
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Soil Climate Monitoring and Analysis: SCAN
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SCAN (Soil Climate and Analysis Network)
Nationwide Soil Moisture & Temperature Network Background A pilot project was started in 1991 Pilot project objectives were to: Develop technical expertise in monitoring Soil-Climate interface Demonstrate the technical feasibility for a nationwide system Precursor to SCAN
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SCAN Currently 42 SCAN sites, located in 30 states
Uses meteor burst or cellular telephone technology to transmit data Data are delivered to the National Water and Climate Center in Portland, Oregon Real-time data validation Data are computer accessible in near real-time Danger of losing 20+ SCAN sites without additional funding
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SCAN USA as of August 2000
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Typical SCAN Site
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Internet Technologies for Climate Delivery
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Unified Climate Access Network
Climate Data Now for the 21st Century 1
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UCAN Goals Make climate data and analyses available to a broad user community Tailor products to the needs of users Provide a flexible interface to satisfy programmatic needs Integrate climate resources across agencies Pretty self-explanatory…….. 2
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