Upload
rane
View
40
Download
0
Tags:
Embed Size (px)
DESCRIPTION
NASA and NAAPS products for Air Quality decision-making . Douglas L. Westphal Naval Research Laboratory, Monterey, CA Rudolf B. Husar Washington University, St. Louis, MO Shawn E. McClure CIRA, Colorado State University, Ft. Collins, CO. Background. - PowerPoint PPT Presentation
Citation preview
1
NASA and NAAPS products for Air Quality decision-making
Douglas L. WestphalNaval Research Laboratory, Monterey, CA
Rudolf B. HusarWashington University, St. Louis, MO
Shawn E. McClure
CIRA, Colorado State University, Ft. Collins, CO
Project Summary: Quantify the impact of Non-CONUS emissions on US AQ using NASA and NAAPS data provided to AQ Decision-Makers through DataFed and VIEWS.
Baseline:1. Exceptional events flagging
• No standard information sources as evidence for EEs• Ad hoc flagging and reporting by the States
2. Background conditions for EPS Regional Haze Rule• No modeling studies of international influences were
used to determine the default natural condition values• States lack standard method for quantifying impact
3. AQ Forecasting and sampling• LRT forecasts not freely available in a quantitative way
Background
1. Exceptional events flagging• Distribute NAAPS via standard protocol through
DataFed2. Background conditions for EPS Regional Haze Rule
• Use 10-year NAAPS reanalysis to identify background on 20% best and worst haze days
• Use NAAPS sensitivity runs to estimate impact of projected emissions (e.g. HTAP scenarios)
3. AQ Forecasting and sampling• LRT forecasts distributed• NAAPS made available for boundary conditions for
regional models• NAAPS forecasts used to guide measurements in field
missions
Approach
Earth System ModelsNAAPS - Operational global aerosol forecast model; six-day forecasts of aerosol plumes; 1996-present retrospective databaseFLAMBE Operational fire locating and emission systemNAVDAS-AOD – Operational aerosol data assimilation system
Value & Benefitsto Society Better estimates of
natural background conditions will lead to better implementation of the RHR and better visibility conditions in our National Parks in the future.
More accurate EE Rule implementation will make for a more accurate and less costly EE claim process and lead to faster attainment of the NAAQS.
Better daily AQ forecasts from local, regional and state agencies will lead to a better health and reduced fatalities.
More efficient and effective field studies will increase our understanding of our nation’s air quality issues and lead to scientifically sound regulations and faster attainment.
Predictions/Forecasts
Observations, Parameters & Products
Earth ObservationsCurrently used:MODIS MOD04 AOD dataset for data assimilation by NAVDAS-AODMODIS and GOES data used in FLAMBE smoke emissionsCALIPSO climatology used for data assimilationCALIPSO overpasses used for validation. Underway:MODIS Deep Blue over-land AOD running at NRL; to be used in NAVDAS-AODMODIS Dust Enhancement Product and TOMS AI used to identify dust sourcesMISR-derived height, composition and AOD used in data assimilation and model validation. Future:AVHRR, METOP and other non-NASA AOD products in data assimilationNPP and NPOESS AOD used in data assimilation
ROSES-2008 Air Quality: NASA and NAAPS Products for AQ Decision-making (PI Westphal)
NAAPS – Operational 6-day forecasts and 10-year database of 3-d distributions of aerosol species (sulfate, smoke, dust, salt), as concentrations, meridional and zonal fluxes, emissions, deposition and wet removal fluxesFLAMBE – hourly, global, biomass emission fluxes in real-time and archived since 2000NAVDAS-AOD – 6-hourly, global 3-d distributions of aerosol species (sulfate, smoke, dust, salt), in real-time and back to 2000
Decision Support Systems, Assessments, Management ActionsNAAPS will provide an integrated way of improving on existing but questionable estimates of “natural background” conditions at IMPROVE sites as States develop SIPs in response to the Regional Haze Rule.NAAPS estimates of non-US source impacts on episodic US PM 2.5 concentrations, combined with the AQ data available on VIEWS and DataFed, will be extremely valuable for the EPA’s new “Exceptional Event” Rule, and provide information which is simply not available elsewhere.NAAPS served through VIEWS and DataFed will provide the first operational estimates of PM impacts from Non-US sources and will complement existing regional forecast models such as AIRPACT-3 and enable more accurate AQ forecasts.Combining NAAPS with other graphical products on the DSSs will support decision-making regarding sampling, data analysis, and risk assessment during field studies of particulate matter from international sources.
What is NAAPS?Navy Aerosol Analysis and Prediction System
Purpose: Forecast of global concentrations for EO propagation, scene and radiance correction, with focus on lower tropospheric phenomena
Method: Solve the advection-diffusion equation at each grid point for each species m :
Advection and turbulent mixing: Controlled by dynamical model NOGAPSSources and sinks: Dependent on dynamics and remote sensingInitial State: Based on previous forecast and remote sensing
September 11, 2011Key:Smoke = blueDust = greenSulfate = red
NASA Data for NAAPS Sources
Sources: Global sources are estimated for each species. Source estimates incorporate weather, remote sensing, and anthropogenic activityExample: Smoke released (kg) in each grid box is the sum of individual fires:
Al area burned: Updated in near real time using GOES and MODIS satelliteswk vertical weights: Fixed, uniform in lowest kilometer
GOES and MODISFIRE DETECTION SMOKE FLUX (Ssmoke)
5-daySMOKE AOD FORECAST
Sep 7 2011
NASA Data for NAAPS Initialization
Forecasting is an initial value problem: Requires the 3-D distribution of aerosol concentration at the start of the forecast:
: Assimilation of previous forecast + information from remote sensing of aerosolsCurrent capabilities:
Aerosol Optical Depth (AOD; 2-D) (MODIS and MISR)Extinction (3-D) (CALIPSO)
AOD
+ Ocean MODIS+ Ocean MODIS+ land/Ocean MISR
Multi-sensor assimilation is critical to aerosol assimilation.
NASA Data for NAAPS Initialization
Natural run + Land/Ocean MODIS+ Land/Ocean MISR
NA
APS
AO
D
AERONET AOD
NAAPS Component Assimilated Data
FLAMBE – Hourly, global, biomass emission fluxes in real-time and archived since 2000
DSD – Global dust source database
NAVDAS-AOD – data assimilation, produces 6-hourly, global 3-d distributions of aerosol species (sulfate, smoke, dust, salt), in real-time and back to 2000
NAAPS Validation
Overview of NASA Data Usage in NAAPS
MODIS and GOES data used to produce gridded smoke emissions (FLAMBE, WF-ABBA)
MODIS Dust Enhancement Product and TOMS AI used to identify dust sources
NRL Level 3 version of MODIS AODAERONET and CALIPSO climatology used for speciationR&D: CALIPSO used for 3-d var data assimilation and validation Unused: MODIS Deep Blue, MISR, AVHHR AOD
AERONET – AOD, absorption, sizeCALIPSO and MISR - Altitude
10
72h Forecast of Dust AOD, Valid 00Z 10 September, 2011
NAAPS Ensemble Forecast of Saharan Dust Transport to the Americas
11
NAAPS data integrated with visualization and exploration tools and DSS applications.
NAAPS and other data combined for Exceptional Event analysis with
EPA and States
Surface aerosol chemical data and back trajectories confirm the
Asian origin of dust
NAAPS dust AOD indicates transport from Asia over the Pacific
Vertical profile at any location, time or
integrated
Time series at any location, time or integrated
DataFed and VIEWS: Provide NAAPS Products for Exceptional Event Analysis
Key Developments: Partnerships
– Washington University - Center for Air Pollution Impact and Trend Analysis (CAPITA)
Make available NAAPS analyses to the AQ community via the Federated Data System (DataFed)
– Colorado State University: Visibility Information Exchange Web System (VIEWS) run by Cooperative Institute for Research of the Atmosphere (CIRA)
NAAPS analyses of dust and smoke that originate outside the U.S. are incorporated in the DSS for implementation of the Regional Haze Rule (RHR) and distributed by VIEWS
– National Oceanic and Atmospheric Administration (NOAA) – CIRA, Monitoring of long-range transport of pollution
– Texas Commission on Environmental Quality Saharan dust effects on PM in eastern Texas
NAAPS Data Delivery Case: Sahara Dust Impact on Texas Air Quality, 2006
1. A NOAA-TCEQ project needs LRT (NAAPS) for their analysis2. NOAA data request forwarded to the NAAPS data archive at DataFed 3. The data are extracted and delivered as standard CF-netCDF files
Dust surface concentration, vert. profile, AOD along the research ship track Gridded 4D NAAPS for TX-Mex and the ship track regions, May-Sep 2006
Dust AOD along ship track
Dust surface concentration
NAAPS dust AODJul 31, 2006
NAAPS Data Delivery Case: Sahara Dust Impact on Texas Air Quality, 2006
In DataFed, NAAPS data can be extracted along multiple dimensions
Layer Concentration
Surface Concentration
Layer ConcentrationMay-Sep 2006
Surface ConcentrationMay-Sep 2006
Spatial pattern at specified height, time
Time series at given height and location
The data extraction domain is defined by the DataFed GUI interfaceBased on the data extraction, the 4D pattern can be exploredThe user can then combine the NAAPS data subset with other data
Key Developments - Metrics
1. Exceptional events flagging• NAAPS distributed via standard protocol through DataFed
for analysis and flagging of Exceptional Events2. Background conditions for EPS Regional Haze Rule
• Use 10-year NAAPS reanalysis to identify background on 20% best and worst haze days
• Use NAAPS sensitivity runs to estimate impact of projected emissions (e.g. HTAP scenarios)
3. AQ Forecasting and sampling• LRT forecasts distributed• NAAPS made available for boundary conditions for regional
models• NAAPS forecasts used to guide measurements in field
missions
ARL Review/Description
ARL 4 Justification from Estimator:
Components of eventual application system brought together and technical integration issues worked out:NAAPS data were transferred to Wash U. on a daily basis. NAAPS post processing code wastransferred to WU and implemented there. The native NAAPS data files are transformed to sigmaand pressure coordinates. The 6-hourly NAAPS have been accumulated for years 2007-2011 and now accessible through the DataFed browser. Facilities to extract data subsets have also beenimplemented and tested with several application areas.
Organizational challenges and human process issues identified and managed:The NAAPS data products were harmonized with the DataFed service-oriented data system.Interaction between NRL and WashU resolved the issues with formatting, routine data transfer,decoding as well as differences in operating systems. Interaction with users has shown the diversity of user needs for different formats, data subsetting and parameter aggregation. These were resolved by iterative consultation-testing cycles with the users.
Starting ARL :3 Projected Ending ARL : 7
Reported (Dec 2011) ARL:4
ARL cont.
ARL 5 Justification from Estimator:
Application components integrated into a prototype system:The data products are integrated into DataFed where users can browse, extract subsets and aggregate NAAPS data.
The application system's potential to improve the decision-making activity has been determined and articulated (e.g., projected impacts on cost, functionality, delivery time, etc.):The NAAPS data delivery is in real time, service based, so it can be incorporated into decision systems.
Starting ARL :3 Projected Ending ARL : 7
Reported (Dec 2011) ARL:4 Current (08/23/2012) ARL: 7
∆ (ARL) = 4
ARL cont.
ARL 6 Justification from Estimator
Prototype application system beta-tested in a simulated operational environment: The NAAPS data in DataFed were tested by users in the US and internationally for exceptional aerosol events and model-observation comparison.
Projected improvements in performance of decision-making acitivity demonstrated in a simulated operational environment:The addition of NAAPS has been shown to improve exceptional event analysis and also general aerosol forecasting
ARL 7 Justification from Estimator:
Prototype application system has been integrated into the end-user's operational environment:NAAPS data were incorporated in the data pool used by AQ forecasters in the Northeastern US.
Prototype application's functionality has been tested and demonstrated in decision-making activity: Air quality forecasts are made primarily for informing the Public, who then make decisions on their daily activities.
Obligations and Cost Status
PY12 money arrived in April and May 2012. Unused PY11 money at CIRA was lost in their system. This glitch has been fixed, the funds retrieved, and there should be no further issues.
PY12Institution WBS Budget Obligated Unobligated Costed Uncosted
Naval Res. Lab. 389018.02.15.04.83 90,609 90,609 - 90,609
CSU - CIRA 389018.02.15.04.84 66,679 66,679 - - 66,679 Wash. Univ 389018.02.15.04.85 169,203 - 169,203 - 169,203
PY11
Institution WBS Budget Obligated Unobligated Costed Uncosted
Naval Res. Lab. 389018.02.15.04.83 91,450 91,450 - 91,378 72
CSU - CIRA 389018.02.15.04.84 49,157 49,157 - - 49,157 Wash. Univ 389018.02.15.04.85 166,557 166,557 - 166,557 -
PY10Institution WBS Budget Obligated Unobligated Costed Uncosted
Naval Res. Lab. 389018.02.15.04.83 - - - 90,609 -
CSU - CIRA 389018.02.15.04.84 - - - 66,679 - Wash. Univ 389018.02.15.04.85 - - - 169,203 -
Upcoming Plans• Complete the 10-year data set at the DSS to allow investigation of
past events and development of event climatologies.• Demonstrate use of NAAPS as boundary conditions for CMAQ model
• Users of models have a variety of data needs: latitude, longitude, altitude, parameter, units, etc. Simply providing a standard data package is not adequate. DataFed now allows most of this variety.
• Funding problem at CIRA has been solved. Funds will be costed this PY.
Issues/Concerns/Lessons Learned
1. We have applied an operational global aerosol forecasting system to AQ problems.
2. Developed distribution of NAAPS via existing DSS DataFed and VIEWS. Available back to 2006.
3. NAAPS data have been delivered to AQ analysts and forecasters.
4. Suitable for quantifying impact of LRT to CONUS.5. Successfully demonstrated as evidence for several
exceptional smoke and dust events.6. System is operational, data are ported daily and are
available for use.
END
Summary
Schedule/Milestones
AR AR