Preparing a Climate Data Time Series from PRISM Rasters This is the cover art for the album The Dark Side of the Moon by the artist Pink Floyd. The cover.

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Presentation transcript:

Preparing a Climate Data Time Series from PRISM Rasters This is the cover art for the album The Dark Side of the Moon by the artist Pink Floyd. The cover art copyright is believed to belong to the label, Harvest / Capitol, or the graphic artist(s), Designed by Storm Thorgerson, drawn by George Hardie. This presentation has nothing to do with Pink Floyd, and Pink Floyd didn’t create the algorithm for PRISM Climate Data. But you’ve got to admit, this is one really awesome graphic.

Jane Schafer-Kramer Research Analyst II (GIS) Modeling Support Branch, Bay-Delta Office

PRISM – PARAMETER-ELEVATION REGRESSIONS ON INDEPENDENT SLOPES MODEL Spatially interpolating climate data since 1993!

PRISM Overview “PRISM uses point data, a digital elevation model (DEM), and other spatial data sets to generate estimates of annual, monthly and event-based climatic elements that are gridded and GIS- compatible. PRISM is not a static system of equations; rather, it is a coordinated set of rules, decisions, and calculations, designed to accommodate the decision-making process an expert climatologist would invoke when creating a climate map.”

Yes, there is metadata.

/index.cfm

FIND the DATA HERE \\nasgispr\EntGIS\GIS\BDO\PRISM_Climate

About the Data Data Type: Stored as.tif rasters in file folders Resolution: 30 arc-second; approximately 800 meters Spatial Extent: State of California Pixel Data Type: signed integer Parameters - Precipitation: cell values are expressed as millimeters times 100 Temperature (Maximum, Mean, Minimum, Dew Point): cell values are expressed as degrees Celsius times 100 Vapor Pressure: cell values are expressed in pascals Time Extent: Monthly from 1895 through 2011, with annual summaries (We plan to purchase data for subsequent years as they become available!) Projected Coordinate System: NAD 1983 UTM Zone 10.5N CaTM for short Use Restrictions! For internal DWR use only – Do not share raster files outside DWR. Any derivative products may be distributed freely.

Data Preparation Decide on a projection: all input files should be in the same projection Keep original file names Keep in chronological order Organize your workspaces Clear a Temporary workspace on a local drive (Don’t try to do geoprocessing over the network.) File geodatabases work well (plays nice with geoprocessing tools) (But there are exceptions!) Import the raster files needed for your analysis (check the dates) Break it up into manageable chunks for better performance and quality control

Sample Workflow Create Time-Series of Mean Monthly Precipitation by Model Study Area Spatial Analyst Toolbox > Zonal Statistics As Table Tool Run in ModelBuilder with Iterator Data Management Toolbox > Joins Toolset > Join Field Tool Run in ModelBuilder with Iterator Export joined attribute table to Microsoft Excel for formatting as Time Series

Spatial Analyst Toolbox > Zonal Statistics As Table Tool Run in ModelBuilder with Iterator Inline variable substitution

Check the Results! Understand the attribute table Check for no data, incorrect zero values, weird numbers, etc.

Data Management Toolbox > Joins Toolset > Join Field Tool Run in ModelBuilder with Iterator

So, what if Zonal Statistics isn’t going to work for me? Plan B: Resample rasters? – logical but inefficient Plan C: Convert rasters to polygons, Dissolve, Intersect, Dissolve again, and export to Excel.

The Excel Part

This is not the only way to do this! If you have another method, let’s discuss: Python script to share, anyone?

Learning Resources Working with Iterators in ModelBuilder - Tutorials B2-2F32E993AFE8 ArcGIS Help (online) About performing analysis with the ArcGIS Spatial Analyst extension with_the_ArcGIS_Spatial_Analyst_extension/ / “Esri Virtual Campus” Web Course Building Models for GIS Analysis Using ArcGIS 10 To enroll in any Esri Web Course (for DWR employees): STUDY+GIS+TRAINING

Thanks for the Help! Michael Mehrdadi, Student Intern and Metadata Wrangler Ruppert Grauberger, Chief of Mapping & Photogrammetry, Geospatial Data Playground Monitor Mike Mullen, The Best LAN Administrator In The Universe Tariq Kadir, The Best Supervisor a GIS Analyst in DWR Could Ever Wish For

California Natural Resources Agency GIS DAY 2013 Tuesday November 19, 2013 Resources Building Auditorium CALL FOR PRESENTATIONS (deadline September 13, 2013) CALL FOR MAPS AND POSTERS (deadline October 31, 2013)

Thank You for your Attention