gis for atmospheric sciences and hydrology
DESCRIPTION
GIS for Atmospheric Sciences and Hydrology. By David R. Maidment University of Texas at Austin. National Center for Atmospheric Research, 6 July 2005. GIS for Atmospheric Science and Hydrology. Space-time data models Hydrologic observations data Weather and climate data Common data model. - PowerPoint PPT PresentationTRANSCRIPT
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GIS for Atmospheric Sciences and Hydrology
By David R. Maidment
University of Texas at Austin
National Center for Atmospheric Research, 6 July 2005
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GIS for Atmospheric Science and Hydrology
• Space-time data models
• Hydrologic observations data
• Weather and climate data
• Common data model
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Atmospheric science – hydrology
• Weather and climate fields are the drivers – continuous in space and time across the nation
• Hydrologic flows in watersheds are the reactors – behaving according to watershed location and characteristics
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Issues
• Atmospheric science describes a fluid domain continuous in space and time, globally connected
• The earth’s surface is a static, highly spatially varied domain whose water properties vary continuously in time, where water is concentrated in flow paths (streams and rivers)
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Issues
• Atmospheric science data are spatially extensive (e.g. North America), involve many variables, are “thin” in time (one day, one forecast period, one month), and use UTC time coordinates
• Hydrologic data are spatially localized (e.g. my watershed), involve few variables (precipitation, evaporation, runoff), are “deep” in time (many decades), and use local time coordinates
This space-time recompositing problem Is not trivial!
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Issues
• Atmospheric science data are stored in vary large binary files with specialized formats (Grib, netCDF, XMRG, ….) whose georeferencing may not be strong
• Hydrologic data are stored in tables in GIS and relational databases, and accessed using GIS spatial and SQL queries
How do we connect these very different data worlds?
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Space, L
Time, T
Variables, V
D
Data Cube
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Continuous Space-Time Data Model -- NetCDF
Space, L
Time, T
Variables, V
D
Coordinate dimensions
{X}
Variable dimensions{Y}
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Space, FeatureID
Time, TSDateTime
Variables, TSTypeID
TSValue
Discrete Space-Time Data Model-- Arc Hydro
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Geospatial Time Series
Value
Time
Shape
Time SeriesProperties
(Type)A Value-Time array
A time series that knows what geographic feature it describes and what type of time series it is
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GIS for Atmospheric Science and Hydrology
• Space-time data models
• Hydrologic observations data
• Weather and climate data
• Common data model
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Data Model for Hydrologic Observations
Relationships
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USGS National Water Information System
Access is rapid enough that it is as if NWIS is a local disk on your computer
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CUAHSI Data Portal
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CUAHSI Data Portal
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Plot from the Hydrology Data PortalProduced using a CUAHSI Hydrology Web Service: getDailyStreamflowChart
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Applications and Services
Web ServicesLibrary
Web application: Data PortalYour application• Excel, ArcGIS, Matlab• Fortran, C/C++, Visual Basic• Hydrologic model• …………….
Your operating system• Windows, Unix, Linux, Mac
Internet
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GIS for Atmospheric Science and Hydrology
• Space-time data models
• Hydrologic observations data
• Weather and climate data
• Common data model
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http://wwwt.emc.ncep.noaa.gov/mmb/rreanl/
A retrospective study of weather and climate made by the National Centers for Environmental Prediction’s (NCEP)
numerical weather prediction model and observations from 1979 to 2003 to make 3 hour forecasts. 3 hour, daily and
monthly data are available on a 32 km grid over North America.
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Using IDV and THREDDS to access NARR
NARR.xml
Get NARR.xml from NARR home page
NARR at Asheville, NC
IDV in Austin, TX
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Precipitable Water and Specific Humidity over Gulf
0.005 0.020 Specific humidity (kg/kg)
Alti
tude
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Precipitable Water and Specific Humidity over Texas
0.005 0.020 Specific humidity (kg/kg)
Alti
tude
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Precipitation
July 2003, 1800Z
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Surface evaporation
July 2003, 1800Z
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GIS for Atmospheric Science and Hydrology
• Space-time data models
• Hydrologic observations data
• Weather and climate data
• Common data model
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NetCDF-Java version 2.2 Common Data Model
John Caron
Unidata/UCAR
Dec 10, 2004
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NetcdfDataset
Application
Scientific Datatypes
Grid Station Image
NetCDF-Java version 2.2 architecture
ADDEOpenDAPTHREDDS
Catalog.xml NetCDF-3
HDF5
I/O service provider
GRIB
GININIDS
NetcdfFile
NetCDF-4
…NexradDMSP
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File Format#N
File Format#2
File Format#1
CDM
Visualization&Analysis
Goal: N + M instead of N * M things on your TODO List
NetCDF file
Data Server
Web Service
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ArcGIS ModelBuilder Application for Automated Water Balancing
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Conclusions
• Data access through web services can mask the variations in data structure between relational databases and data file systems
• We need a “Common, common” data model to better integrate GIS and weather and climate information
• We need tools for space-time recompositing of weather and climate information to make it suitable for hydrology