Climate Data Analysis John Gross NPS I&M Program GIS / Data Management Conference 3 April 2008.
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Transcript of Climate Data Analysis John Gross NPS I&M Program GIS / Data Management Conference 3 April 2008.
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Climate Data Analysis
John GrossNPS I&M Program
GIS / Data Management Conference 3 April 2008
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National Park Service
Parks and climate change
National Park Service
• Relatively undisturbed• Protected for the future• Broad geographic distribution• Large environmental gradients• Many observations
People really care about Parks
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IPCC 2007 Working Group 4 FAQ 3.1.
Projected temperature change
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"For us the discussion around climate change is not just a theory; it is a very stark and harsh reality.”
Patricia Cochran – Inuit Circumpolar Conference
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Observation (T)
Station summary of day (SOD)
Station month summary
Atmospheric Index – SOI, PDO
Climate indices (PDSI)
Climate Divisions
Spatial Scale
TimeInvestigator-defined area of interest
minutes
Months to years
points regions
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“Climate tells you what clothes to buy …
weather tells you what to wear today!”
• Climate is determined by the properties of the Earth system that define the normal range of variation in observation.
• Weather responds sensitively to local conditions. Weather forecasts are only useful for short periods into the future.
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Observation (T)
Daily station summary (SOD)
Monthly station summary
Atmospheric Index – SOI, PDO
Many indices (PDSI)
Climate Divisions
Spatial Scale
Time(roll-your-own area of interest)
minutes
Months to years
points regions
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Individual station data is essential
This is the basis of our understanding and extrapolation
For long-term value, QA/QC and metadata are CRITICAL
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Communicating climate
• Consider the reference period– 30 year ‘normals’ (often 1971-2000)– Life of station– Since 1895
http://www.wcc.nrcs.usda.gov/snow/
Climates always change – use a thoughtful reference period
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• Highly subject to:– Micrometeorological phenomena– Instrument issues – calibration, changes, etc.– Station relocation and site-specific effects
• Rigorous QA/QC difficult and time-consuming – Missing values difficult to handle and accomodate– McEachern CHIS report (2007) good example
• Metadata is essential– Almost surely need data from an established network
Individual Station Data and Climate Evaluation
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Observation (T)
Daily station summary (SOD)
Monthly station summary
Atmospheric Index – SOI, PDO
Many indices (PDSI)
Climate Divisions
Spatial Scale
Time(roll-your-own area of interest)
minutes
Months to years
points regions
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Describing climate of an area
• Exemplar or ‘indicator’ station(s)
• Relatively easy, once stations are selected
• Station data – local effects, reliant on single sensor, single-station bias
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Multiple-station index or aggregation• Broader inference
• Strength in numbers• More complex analysis problem
California Climate Tracker - WRCC
Describing climate of an area
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NCDC Climate Divisions – To the rescue?
http://www7.ncdc.noaa.gov/CDO/CDODivisionalSelect.jsp
• Monthly data from 1895 - present
• Temperature, precipitation, heating/cooling degree days
• Palmer drought index and related
• Standardized precipitation indices
• Simple data output to text file or (limited) plots
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Mapped by climate division
With apologies to Hawaii and Alaska …
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Temperatures in Northwest Wisconsin
Apostle Islands National Lakeshore Established
From http://www.wrcc.dri.edu/spi/divplot1map.htmlRed line – 12 month averageBlue line – 10 year running mean
1970 19901950 201019301910
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Correlation in precipitation between station and climate division Jan-Mar.
(K. Wolter and D. Allured 2007)
Red = GoodGreen = badBlue = Really bad!
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See: www.cdc.noaa.gov/people/klaus.wolter/ClimateDivisions/
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Large-scale climate drivers are important
• Climate station inventory reports• Regional Climate Centers papers (WRCC for western states)
NEON process: http://web.utk.edu/~jweltzin/SAPOZEO/Hayden090805.htm
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Consider regional indices – these may better predict ecological characteristics than local
data!
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• Data and analyses– NPClime and climate inventory reports– Climate learning modules – www.meted.ucar.edu– ROMN protocol (in draft) for miscellaneous data handling – National Climatic Data Center (NCDC) – many products– Gridded data – PRISM– NRCS SnoTel, National Drought Mitigation Center, USGS
stream flow
Selected Resources and Activities