1 RTP, NC 1 Gregory Leptoukh & Frank Lindsay, AQ Data Summit Goddard Interactive Online Visualization ANd aNalysis Infrastructure NASA Goddard Space Flight

1 RTP, NC 1 Gregory Leptoukh & Frank Lindsay, AQ Data Summit

Goddard Interactive Online Visualization ANd aNalysis Infrastructure

NASA Goddard Space Flight Center

http://giovanni.gsfc.nasa.gov/

Assessing U.S Air Quality with Remote Sensing Data via


Content

•What is Giovanni?•Giovanni for Air Quality•Trace gases in Giovanni• Interoperability of Giovanni•Case studies•Giovanni and Google Earth


About Giovanni

• Giovanni is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC).

• Giovanni provides a simple and easy way to explore, visualize, analyze, and access vast amounts of Earth science remote sensing and model data.

http://giovanni.gsfc.nasa.gov/


Aerosol from MODIS and GOCART modelParticulate Matter (PM 2.5) from AIRNow

Ozone Hole from OMI

Aerosol from GOCART model10-6 ppmv

Carbon Monoxide from AIRS

Water Vapor from AIRS MODIS vs SeaWiFS Chlorophyll

Giovanni Instances

CloudSat

HIRDLS

MLS

OMI

TRMM

SeaWiFS

AMSR-E

HALOE

TOMS

Models

Parasol

CALIOP

Data Inputs

MODIS

AIRS

MISR

and more…


CapabilitiesBasic (one-parameter):• Area plot – averaged or accumulated over any data period for any rectangular

area (various map projections)• Time plot – time series averaged over any rectangular area• Hovmöller plots –longitude-time or latitude-time cross sections• ASCII output – for all plot types (can be used with GIS apps)• Image animation – for area plot• Vertical profiles • Vertical cross-sections, zonal means

Beyond basics:• Area plot - geographical intercomparison between two parameters• Time plot - an X-Y time series plot of several parameters• Scatter plot of parameters in selected area and time period • Scatter plot of area averaged parameters - regional (i.e., spatially averaged)

relationship between two parameters• Temporal correlation map - relationship between two parameters at each grid

point in the selected spatial area• Temporal correlation of area averaged parameters - a single value of the

correlation coefficient of a pair of selected parameters• Difference plots• Anomaly plots • Acquiring parameter and spatial subsets in a batch mode through Giovanni

htt

p:/

/gio

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The Power of Simplicity

Only a Web browser is needed.

No need to learn data formats and programming.

No need to download large amounts of data.

Customized data and analyses can be obtained with only a few mouse clicks.

Caution: Giovanni is an exploration tool!

htt

p:/

/gio

van

ni.

gsfc

.nasa.g

ov/


AOT for June 2006

Terra MODIS

Aqua MODIS Envisat MERIS

Parasol POLDER


AOT Differences for June 2006

Terra MODIS – Aqua MODIS Aqua MODIS - POLDER

Terra MODIS – MERIS MERIS – POLDER


Scatter plots


Time series


Maps of NO2


Maps of CO


Profile Data ComparisonsHIRDLS MLS

HIRDLS and MLSozone (top) and temperature (bottom) profiles acquired March 12, 2007, over France during the passage of a weather front. Note the tropopause fold (arrow) in the ozone profiles.

MLS vertical resolution is ~3 km, HIRDLS vertical resolution is ~1 km.


California fires by MODIS


PM2.5 from AirNow in Giovanni

16

RTP, NC 16 Gregory Leptoukh & Frank Lindsay, AQ Data Summit

Visualizing California’s Wildfires from Space

Tropospheric NO2

UV Aerosol Index

Total Column CO

Aerosol Small Mode

Fraction

Cloud Optical

Thickness

Aerosol Mass over

Land

OMI OMI AIRS

MODIS

MODIS

MODIS

23-27 October 2007Data from NASA’s Aura OMI (Tropospheric NO2 and UV Aerosol Index), Aqua AIRS (Total Column CO) and

Terra MODIS (Aerosol Small Fraction, Cloud Optical Thickness and Aerosol Mass Concentration Over Land)

17 RTP, NC 17 Gregory Leptoukh & Frank Lindsay, AQ Data SummitDust event, May 23, 2007

Data Fusion (prototype) in

Terra

Aqua

Terra +

Aqua


Interoperability


20

WCS OpenDAP

WMS

Proto-cols

RTP, NC 20 Gregory Leptoukh & Frank Lindsay, AQ Data Summit

TOMS

OMI SeaWIFS

CALIPSO

MODIS

SATs inGiovanni

Aerosol Data

NASA GES DISC

NetCDF

HDF4/5

IDLetc.

MATLAB

KML

ASCII

Binary

Format

already in Giovanni 3.06


OGC and other m2m protocols • WMS:

– Via Map Server– Via Giovanni

• WCS:– Via WebGIS– Via Giovanni

• OPeNDAP Hyrax 4 serving data on 12 machines. Sample URLs:http://acdisc.sci.gsfc.nasa.gov/opendap/http://atrain.sci.gsfc.nasa.gov/opendap/

• WMS sample URL to get WMS data for 'LAYER=AIRX3STD_TOTO3_A‘:http://g0hep12u.ecs.nasa.gov/mapserv-bin/wms_ogc?TARGET_SRS=EPSG:4326&Service=WMS&VERSION=1.1.1&REQUEST=GetMap&SRS=EPSG:4326&WIDTH=768&HEIGHT=512&BBOX=-180,-90,180,90&LAYERS=AIRX3STM_TOTO3_A,coastline

• GDS (Grads-DODS):http://agdisc.gsfc.nasa.gov/dods/

http://acdisc.sci.gsfc.nasa.gov/opendap/

http://atrain.sci.gsfc.nasa.gov/opendap/

http://g0hep12u.ecs.nasa.gov/mapserv-bin/wms_ogc?TARGET_SRS=EPSG:4326&Service=WMS&VERSION=1.1.1&REQUEST=GetMap&SRS=EPSG:4326&WIDTH=768&HEIGHT=512&BBOX=-180,-90,180,90&LAYERS=AIRX3STM_TOTO3_A,coastline




http://agdisc.gsfc.nasa.gov/dods/


WMS and WCS in

Serving MODIS data via WMS: Maps (decorated and undecorated), time-series, Hovmoller, time-averaged maps, difference maps

Example of Maps:

http://giovanniplus-ts1.sci.gsfc.nasa.gov/daac-bin/G3/giovanni-wms.cgi?SERVICE=WMS&WMTVER=1.0.0&REQUEST=GetMap&SRS=EPSG:4326&EXCEPTIONS=INIMAGE&FORMAT=GIF&BBOX=-130,24,-60,52&TIME=2006-02-01T00:00:00Z&WIDTH=800&HEIGHT=400&LAYERS=MOD08_D3.005::Optical_Depth_Land_And_Ocean_Mean

Serving data via WCS:

Here is a get capabilities url:

http://giovanniplus-ts1.sci.gsfc.nasa.gov/daac-bin/G3/giovanni-wcs.cgi?SERVICE=WCS&WMTVER=1.0.0&REQUEST=GetCapabilities




WCS support outside of

OMI NO2 (Level 3):getCapabilities and describeCoverage requests http://acdisc.sci.gsfc.nasa.gov/daac-bin/wcsNO2?service=wcs&version=1.0.0&request=describeCoveragehttp://acdisc.sci.gsfc.nasa.gov/daac-bin/wcsNO2?service=wcs&version=1.0.0&request=getCapabilities

• getCoverage example request:http://acdisc.sci.gsfc.nasa.gov/daac-bin/wcsNO2?service=WCS&version=1.0.0&request=getCoverage&CRS=WGS84&resx=0.5&resy=0.5&coverage=NO2Total&bbox=-179.75,-89.75,179.75,89.75&TIME=2006-08-01/2006-08-04&format=netCDF

AIRS X2RET (Level 2 collection 5):getCapabilities and describeCoverage requests http://g0dup05u.ecs.nasa.gov/cgi-bin/ceopAIRX2RET?service=wcs&version=1.0.0&request=getCapabilitieshttp://g0dup05u.ecs.nasa.gov/cgi-bin/ceopAIRX2RET?service=wcs&version=1.0.0&request=describeCoverage

• getCoverage request:http://g0dup05u.ecs.nasa.gov/cgi-bin/ceopAIRX2RET?service=WCS&version=1.0.0&request=getCoverage&coverage=H2OMMRStd&crs=WGS84&bbox=-179.75,-89.75,179.75,89.75&resX=0.5&resY=0.5&time=2004-07-28&format=netCDF

• The server now supports 28 variables, including both 2D and 3D fields: TSurfAir, TAirStd, GP_Height, GP_Surface, PSurfStd, TSurfStd, totH2OStd, H2OMMRStd, H2OMMRSat, H2OMMRSat_liquid, O3VMRStd, totO3Std, PCldTopStd, TCldTopStd, olr, clrolr, CO_total_column, CO_VMR_eff, CO_eff_press, CH4_total_column, CH4_VMR_eff, CH4_eff_press, GP_Height_MWOnly, sfcTbMWStd, EmisMWStd, totH2OMWOnlyStd, totCldH2OStd, and numCloud.

• OMI UVB and O3 (Level 3) coming shortly

http://acdisc.sci.gsfc.nasa.gov/daac-bin/wcsNO2?service=wcs&version=1.0.0&request=describeCoverage


Air Quality Tools and Datasetson aerosols

Available Science Data Sets (examples)• PM2.5 station data - EPA AirNow (via WCS) DataFed

(aggregated and gridded) (via WCS) Giovanni• MODIS TERRA and AQUA total and Fine mode Aerosol Optical

Depth • CALIOP Aerosol Feature Mask curtain plots

• OMI NO2 Tropospheric column and Aerosol Index

Useful Tools for Air Quality Applications• AOD/ PM2.5 scatter plots, correlation maps, time series and

difference plots

• AOD and PM2.5 loops for examining long range transport of aerosols


PM2.5 (EPA DataFed Giovanni) Deep Blue MODIS Aerosol Optical Depth

The standard MODIS AOT GOCART AOT

Prototyping PM25 data in


Giovanni Air Quality Data (July 7th, 2006) Level-3 MODIS AQUA AODEPA AirNow PM2.5 (ug/m3)

• MODIS and OMI imagery show smoke aerosols over the northeast, southeast and Great Lakes.

• CALIOP Aerosol Flag (yellow) confirms that aerosols are above the boundary layer

• EPA AirNow PM2.5 doesn’t show anything around Great Lakes, i.e. aerosols are primarily above the boundary layer

OMI Aerosol Index

CALIOP Aerosol Flag (yellow)


Giovanni Air Quality Services: AOD/PM2.5 Correlation Maps and Time Series

May 2007 AOD/PM2.5 correlation map over the U.S

Moderate to good correlation in the eastern U.S

No significant differences were found when using the Fine Mode MODIS AOD.

May 2007- AOD and PM2.5

Time series over the southeast


CALIPSO: Elevated Smoke Layers over the US Midwest

Smoke

Giovanni MODIS Terra AOD mapGiovanni PM2.5 Map

Smoke in Great Lakes region moving east


Level-3 MODIS AOD

EPA PM2.5 (ug/m3)

May 22nd, 2007: Smoke over North Carolina. High AOD and low PM2.5 (r=0.54). There is also haze in the southeast

• Improved correlation over this region when excluding smoke areas (r=0.80)

• Giovanni data sets and tools help provide a more complete understanding of the origin, evolution, and vertical distribution of aerosol pollution over the continental U.S.

Giovanni Air Quality tools: Understanding AOD/PM2.5 correlations


Level-3 MODIS AOD

EPA PM2.5 (ug/m3)

• CALIOP Aerosol Flag (yellow) for examining the vertical aerosol distribution.

• Aerosols in Georgia and Alabama from the surface to 4 km, AOD/PM2.5 correlation is moderately good

• Aerosols in the northeast are above boundary layer, AOD/PM2.5 correlation is poor

Giovanni Air Quality tools: Understanding AOD/PM2.5 correlations


July 31st, 2007

In Canada and the north-central US, MODIS and OMI show thick aerosols plumes. CALIOP overpass has a plume above the boundary layer


July 31, 2007: Haze over the south eastern US

• In the southeast (Tennessee, Mississippi, Alabama and Arkansas) MODIS and PM2.5 show good spatial agreement and have moderately good correlation (see scatter plot)

• Low OMI Aerosol Index and CALIPSO Aerosol flag (see previous slide) also indicate aerosols are primarily confined to the boundary layer in these states


July 31, 2007: Haze over the south eastern US

OMI contours over MODIS AOD. White lines indicated CALIPSO overpass



Importing Giovanni Data into Google Earth


A-Train in Google Earth via Giovanni: Calipso Lidar


• Examined AOD and PM2.5 maps, correlation maps and time series plots. Fine Mode AOD also available

• High AOD/PM2.5 correlation indicates the MODIS algorithm is capturing aerosols at the surface in addition to elevated aerosols (if any)

• High AOD and low PM2.5 may indicate the presence of aerosol plumes above the boundary layer

• CALIPSO overpass (if available) together with AOD/PM2.5 correlations and scatter plots to qualitatively assess the vertical distribution of aerosols

• OMI measurements are less sensitive to aerosols in the boundary layer, so if OMI doesn’t show high aerosol while MODIS does, it may indicate aerosol being in the boundary layer

• MODIS algorithm issues (e.g. retrieval problems over bright surfaces) may affect correlations

Analysis of U.S Air Quality Via

Test Case - NO2 Air Pollution Data from Aura OMI

Iamges Courtesy of Mark O. Wenig, Eric J. Bucsela, Edward A. Celarier, James F. Gleason, NASAJ. Pepijn Veefkind, K. Folkert Boersma, Ellen Brinksma, KNMI

Documents

1 RTP, NC 1 Gregory Leptoukh & Frank Lindsay, AQ Data Summit Goddard Interactive Online Visualization ANd aNalysis Infrastructure NASA Goddard Space Flight