GIS for Atmospheric Sciences and Hydrology

1
GIS for Atmospheric Sciences and Hydrology
By David R. Maidment University of Texas at
Austin
National Center for Atmospheric Research, 6 July
2005
2
GIS for Atmospheric Science and Hydrology

• Space-time data models
• Hydrologic observations data
• Weather and climate data
• Common data model

3
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

4
Issues

• Atmospheric science describes a fluid domain
  continuous in space and time, globally connected
• The earths 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)

5
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!
6
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?
7
Data Cube
8
Continuous Space-Time Data Model -- NetCDF
Time, T
Coordinate dimensions X
D
Space, L
Variable dimensions Y
Variables, V
9
Discrete Space-Time Data Model-- Arc Hydro
Time, TSDateTime
TSValue
Space, FeatureID
Variables, TSTypeID
10
Geospatial Time Series
Time Series Properties (Type)
A Value-Time array
A time series that knows what geographic feature
it describes and what type of time series it is
Shape
11
GIS for Atmospheric Science and Hydrology

• Space-time data models
• Hydrologic observations data
• Weather and climate data
• Common data model

12
Data Model for Hydrologic Observations
Relationships
13
USGS National Water Information System
Access is rapid enough that it is as if NWIS is a
local disk on your computer
14
CUAHSI Data Portal
15
CUAHSI Data Portal
16
Plot from the Hydrology Data Portal
Produced using a CUAHSI Hydrology Web Service
getDailyStreamflowChart
17
Applications and Services
Web application Data Portal

• Your application
• Excel, ArcGIS, Matlab
• Fortran, C/C, Visual Basic
• Hydrologic model
• .

• Your operating system
• Windows, Unix, Linux, Mac

Internet
Web Services Library
18
GIS for Atmospheric Science and Hydrology

• Space-time data models
• Hydrologic observations data
• Weather and climate data
• Common data model

19
A retrospective study of weather and climate made
by the National Centers for Environmental
Predictions (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.
http//wwwt.emc.ncep.noaa.gov/mmb/rreanl/
20
Using IDV and THREDDS to access NARR
NARR at Asheville, NC
IDV in Austin, TX
NARR.xml
Get NARR.xml from NARR home page
21
Precipitable Water and Specific Humidity over
Gulf
Altitude
0.005 0.020 Specific
humidity (kg/kg)
22
Precipitable Water and Specific Humidity over
Texas
Altitude
0.005 0.020 Specific
humidity (kg/kg)
23
Precipitation
July 2003, 1800Z
24
Surface evaporation
July 2003, 1800Z
25
GIS for Atmospheric Science and Hydrology

• Space-time data models
• Hydrologic observations data
• Weather and climate data
• Common data model

26
NetCDF-Java version 2.2 Common Data Model

• John Caron
• Unidata/UCAR
• Dec 10, 2004

27
Application
NetCDF-Java version 2.2 architecture
NetcdfDataset
NetcdfFile
ADDE
OpenDAP
HDF5
I/O service provider
NetCDF-3
NetCDF-4
GRIB
NIDS
GINI
Nexrad

DMSP
28
Goal N M instead of N M things on your TODO
List
File Format 1
Visualization Analysis
NetCDF file
File Format 2
Data Server
File Format N
Web Service
29
ArcGIS ModelBuilder Application for Automated
Water Balancing
30
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