SERVICE ORIENTED ATMOSPHERIC RADIANCES (SOAR): A SYSTEM OF SERVICES DELIVERING MULTI-SENSOR GRIDDED...
-
date post
18-Dec-2015 -
Category
Documents
-
view
213 -
download
0
Transcript of SERVICE ORIENTED ATMOSPHERIC RADIANCES (SOAR): A SYSTEM OF SERVICES DELIVERING MULTI-SENSOR GRIDDED...
SERVICE ORIENTED ATMOSPHERIC RADIANCES (SOAR): A SYSTEM OF SERVICES DELIVERING MULTI-SENSOR GRIDDED
DATA RECORDS AND APPLIED SCIENTIFIC ANALYSES
Overview
• Rationale for SOAR as SOS• Architecture• SOAR system walk through • Examples of climate analysis services• Summary
What is SOAR?Service Oriented Atmospheric Radiances
• A web-based service oriented framework to improve access and use of satellite acquired atmospheric IR radiance data
• Maps multi-sensor radiance data from orbital coordinates stored at distributed archives onto lat-lon grids of arbitrary resolution on-demand
• Serves up fundamental data records in image and/or structured data formats
• Provides observation-based analysis services for the study and intercomparison of long historical IR data records
• Currently serves up AIRS and MODIS data and selected periods of HIRS3, VTPR and AVHRR3
What makes SOAR a system of services?• SOAR includes a general ’Downloader’ for accessing multi-sensor
instrument data from distributed archives from multiple satellites
• SOAR contains a generalized ‘Gridder’ that incorporates the sensor’s spatial response function to accurately calibrate the emitted radiance from each observed footprints portion of a grid cell
• SOAR is based on an SOA architecture that employs a cloud computing paradigm for efficient data intensive processing
• SOAR provides a set of analysis tools application specific to the geometry of the respective instrument data sets
• Maps level 1B granules into gridded level 3 radiances
• Increases accessibility and usability by scientists• Most op’n’l forecast centers assimilate gridded radiances• Provides analysis services based directly on observations • Greatly reduces data volume (lossy compression)• A common framework for gridding multi instruments• No level 3 gridded radiance products available from AIRS
and MODIS or HIRS/AVHRR instrument teams
Why we need SOAR?
SOAR Web Service Architecture
Web Service
Lookup
Publish Services
WSDL
URLS
Web Service ProviderWeb Service Client
SOAP
UDDIDirectory
HTML
HTTP
SOARClient Server
User (Browser)
SOARWeb
ProcessServices
File Share (Binary
Data/Images)
Bluegrit Supercomputer
Cluster
GDAACMODAPSNCDCNCAR
SOAR Downloader
• A C++ based application for each sensor
• Downloading formats tailored to each sensors data files as a separate service on UDDI
• Sensor access invoked by soap message specified through client server pull down window
• Accesses on-line data sets over internet using protocols such as ftp, http, etc.
AIRS Visible Image (1 day)
Download of HIRS 3 Orbit
SOARs Generic GridderSOARs Generic Gridder• Philosophy: Philosophy: -- Common gridding algorithms for many instruments.-- Common gridding algorithms for many instruments.
– Spatial calibration with recursive ray casting algorithmSpatial calibration with recursive ray casting algorithm
– Spectral response functions for calibrating multi-sensorsSpectral response functions for calibrating multi-sensors
– Orbital drift calibrations with neural network algorithm.Orbital drift calibrations with neural network algorithm.
• Framework developed for gridding radiances from many Framework developed for gridding radiances from many
scanning instruments.scanning instruments.– Currently implemented for AIRS, MODIS, AIRS VisibleCurrently implemented for AIRS, MODIS, AIRS Visible
-- Extending to HIRS2/3, HIRS4 and VTPR-- Extending to HIRS2/3, HIRS4 and VTPR
– Incorporating artificial neural network algorithm into Gridder.Incorporating artificial neural network algorithm into Gridder.
Cloud ComputingCloud Computing
SOAR System of Services
SO
AR
We
b S
ystem
System Services• Query & Request Instrument Data• Transactions recorded in database• Analysis Routines• NCAR Graphics Visualization• Real-time Data Gridding• Subset by resolution (1°x 0.5° native)• Subset by geographic region• Remote Data Acquisition
Downloader Engine
Gridder Engine
Data Visualization Engine
Analysis Routines
Data Query Web Application
Transactions
Pre
-Grid
de
d d
ata
AIRSMODIS
HIRS
Staged Gridded Radiance Data• MODIS gridded data (Nov’04 – Oct’08)• AIRS gridded data (Sep’02 – Oct’08)• Placing new datasets into production: HIRS, VTPR, SIRS, AVHRR, SBUV, OMI
AVHRR VTPR
One Month 1/1/2005-1/31/2005 AIRS VIS Ch1
HIRS3 Ch 8 (12um) AIRS 528 ch 528 (12um)Jan. 1-14, 2005
SOAR Home Page
SOAR Request Page
SOAR Results Page
Some Analysis Routines•Monthly, Seasonal, Yearly Averages and Anomalies
•Tracking monthly shifts in Inter Tropical Convergence Zone
• Madden Julian Oscillations (EEOFs)
• EL Nino Southern Oscillation (ENSO)
• Outgoing Long Wave Radiation (OLR) and Latitudinal OLR
•AIRS-MODIS Intercomparisons by Grid cell or Region
•Quasi-Bienneial Oscillation
AIRS Monthly average 0.5ox1o at 12.18 µm
AIRS Monthly anomaly 0.5ox1o at 12.18 µm
• Year to year variances• Cold radiances Feb 05 (strong El Nino
year) convective cloud, Warm radiances Feb 07 cloud clear surface in Western Pacific
• Similar in Indian Ocean and West Pacific area
• Feb 05 warmer than other 2 year in East US (hurricanes)
• Variances in Intertropical Convergence Zone
Feb 2006 anomaly
Feb 2005 anomaly Feb 2007 anomaly
MJO- results
C)
Variances color code
BT color code
Variances color codeDec1506
Dec1706
Dec1906
Dec2106
Dec2306
Dec2506
Dec2706
Dec2906
Jan0107
Jan0307
Jan0507
Jan0707
Jan0907
Jan1107
Jan1307
Jan1507
Jan1707
lag1
lag2
lag3
lag4
lag5
The first EOF explaining about explaining about 14.3% variance14.3% variance
B)
2 day running mean of MODIS channel 2 day running mean of MODIS channel 3232 (Surface/Cloud Temperature) (Surface/Cloud Temperature) at 0.5at 0.5oox1 11.7 x1 11.7 µmµm -12.2 -12.2 µmµm 5S-5N 0-180E Brightness Temperature 5S-5N 0-180E Brightness Temperature descending orbit from Dec 15 2006 to descending orbit from Dec 15 2006 to Jan 17 2007.Jan 17 2007.
A)The extended EOF The extended EOF captures the captures the dynamics using a temporal lag dynamics using a temporal lag of 2 day running mean.of 2 day running mean.
AIRS/MODIS total OLR 0.5ox1o
• AIRS/MODIS total OLR• isentropic assumption • Compare with CERES/ERBE OLR Feb. 2005 vs April 1985
Summary• SOAR SOS provides transparent access, gridding and visualization on demand
of the following multi- sensor IR radiance data sets: AIRS, MODIS, AIRS VIS, HIRS3, VTPR;
• SOAR incorporates a variety of analysis tools that provide multi- year monthly and seasonal anomalies, MJO, ENSO, OLR and statistics within a grid
cell as well as regional and global;
• SOAR system provides multiple gridding options for arbitrary spatial/spectral resolutions for multi sensor intercomparisons;
• SOAR Scientific Findings: AIRS and MODIS IR spectral radiance measurements have not degraded in
over 6 years AIRS and MODIS gridded IR spectral radiances have potential to provide
long term (>10 year) Fundamental Decadal Data Record MJO can be tracked directly from raw observations with fewer uncertainties
Back Up Slides
SOAR Service Interaction Diagram
User Client Web Service Bluegrit
New Request
Submit New Request FormGet radiance data() :sessionKey
login()Submit login
Session Key
Get login page
Welcome Page/Recent Results
New Request Form
Request Status :requestID
Login Page (HTML)
Result List
Get user results() :sessionKey
Science Image File
Request Status Page :requestID
Get Results(requested) :sessionKey
Get raw dataRaw Data File Handle
Subset/Average Data
Condensed Data File Handle
Render Data as Image
Get Request Results
Request Results
File URL(s)
Set Status
Results Display
Image/Animation/Data URL(s)
What is SOAR?• A web based system with an interface for accessing and
invoking gridding and analysis services on level 1B Infra-red radiance data
• Employs SOA technologies to discover and select services for use of multi -sensor infra-red radiances
• Serves up pre-gridded (lat-lon) AIRS and MODIS IR spectral radiances on-demand and requested image and/or structured data formats
• Provides a platform for users to exploit IR data for climate analysis with traditional methodologies
Gridding MODIS/AIRS in SOAR system(SOAR- Service Oriented Atmospheric Radiances)
NASA GSFC archived Servers
Processor Server(Bluegrit)
10Gbps
Schedule jobs
Gridding routines
Bluegrit, IBM Blade CenterJS20 Blades & JS21 blades
http://bluegrit.cs.umbc.edu/soar/http://bluegrit.cs.umbc.edu/soar/
Web Server(Bluegrit)
Requests display
• Gridding routines• Subset, images• Simple statistic tools• Convolution routines• Climate applications
Sensor’s datasets
• requests• visualize • analysis• download
SOAR Technologies Used• Apache Tomcat – application server• Apache – web server• C/C++ – data processing utilities• Java – application programming• Apache AXIS – SOAP protocol library• PHP – web client programming• PostGRESQL – application database• Apache ANT – build and deployment scripting• Subversion – configuration management