Climate Data Analysis John Gross NPS I&M Program GIS / Data Management Conference 3 April 2008

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

IPCC 2007 Working Group 4 FAQ 3.1. Projected temperature change

"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

Observation (T) Station summary of day (SOD) Station month summary Atmospheric Index – SOI, PDO Climate indices (PDSI) Climate Divisions Spatial Scale Time Investigator-defined area of interest minutes Months to years points regions

“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.

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

Individual station data is essential This is the basis of our understanding and extrapolation For long-term value, QA/QC and metadata are CRITICAL

Communicating climate Consider the reference period –30 year ‘normals’ (often ) –Life of station –Since Climates always change – use a thoughtful reference period

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

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

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

Multiple-station index or aggregation Broader inference Strength in numbers More complex analysis problem California Climate Tracker - WRCC Describing climate of an area

NCDC Climate Divisions – To the rescue? Monthly data from present Temperature, precipitation, heating/cooling degree days Palmer drought index and related Standardized precipitation indices Simple data output to text file or (limited) plots

Mapped by climate division With apologies to Hawaii and Alaska …

Temperatures in Northwest Wisconsin Apostle Islands National Lakeshore Established From Red line – 12 month average Blue line – 10 year running mean

Correlation in precipitation between station and climate division Jan-Mar. (K. Wolter and D. Allured 2007) Red = Good Green = bad Blue = Really bad!

See:

Large-scale climate drivers are important Climate station inventory reports Regional Climate Centers papers (WRCC for western states) NEON process:

Consider regional indices – these may better predict ecological characteristics than local data!

Data and analyses –NPClime and climate inventory reports –Climate learning modules – –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