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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. GIS for Atmospheric Science and Hydrology. Space-time data models Hydrologic observations data Weather and climate data Common data model.

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Gis for atmospheric sciences and hydrology

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
GIS for Atmospheric Science and Hydrology

  • Space-time data models

  • Hydrologic observations data

  • Weather and climate data

  • Common data model


Atmospheric science hydrology
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


Issues
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)


Issues1
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!


Issues2
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 GISspatial and SQL queries

How do we connect these very different data worlds?


Data cube

Time, T

D

Space, L

Variables, V

Data Cube


Continuous space time data model netcdf
Continuous Space-Time Data Model -- NetCDF

Time, T

Coordinate

dimensions

{X}

D

Space, L

Variable dimensions

{Y}

Variables, V


Discrete space time data model arc hydro
Discrete Space-Time Data Model-- Arc Hydro

Time, TSDateTime

TSValue

Space, FeatureID

Variables, TSTypeID


Geospatial time series

Value

Time

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


Gis for atmospheric science and hydrology1
GIS for Atmospheric Science and Hydrology

  • Space-time data models

  • Hydrologic observations data

  • Weather and climate data

  • Common data model



Usgs national water information system
USGS National Water Information System

Access is rapid enough that it is as if NWIS is a local disk on your computer




Plot from the hydrology data portal
Plot from the Hydrology Data Portal

Produced using a CUAHSI Hydrology Web Service: getDailyStreamflowChart


Applications and services
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


Gis for atmospheric science and hydrology2
GIS for Atmospheric Science and Hydrology

  • Space-time data models

  • Hydrologic observations data

  • Weather and climate data

  • Common data model


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.

http://wwwt.emc.ncep.noaa.gov/mmb/rreanl/


Using idv and thredds to access narr
Using IDV and THREDDS to access NARR 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.

NARR at Asheville, NC

IDV in Austin, TX

NARR.xml

Get NARR.xml from NARR home page


Precipitable Water and 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.Specific Humidity over Gulf

Altitude

0.005 0.020

Specific humidity (kg/kg)


Precipitable water and specific humidity over texas
Precipitable Water and 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.Specific Humidity over Texas

Altitude

0.005 0.020

Specific humidity (kg/kg)


Precipitation
Precipitation 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.

July 2003, 1800Z


Surface evaporation
Surface evaporation 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.

July 2003, 1800Z


Gis for atmospheric science and hydrology3
GIS for Atmospheric Science and Hydrology 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.

  • Space-time data models

  • Hydrologic observations data

  • Weather and climate data

  • Common data model


Netcdf java version 2 2 common data model

NetCDF-Java version 2.2 Common Data Model 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.

John Caron

Unidata/UCAR

Dec 10, 2004


Scientific Datatypes 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.

Grid

Station

Image

THREDDS

Catalog.xml

Application

NetCDF-Java version 2.2 architecture

NetcdfDataset

NetcdfFile

OpenDAP

ADDE

HDF5

I/O service provider

NetCDF-3

NetCDF-4

GRIB

NIDS

GINI

Nexrad

DMSP


CDM 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.

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



Conclusions
Conclusions Balancing

  • 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


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