Transcript AVHRR SDS and PATMOS-x

AVHRR Stewardship Project
Pathfinder Atmospheres –
Extended (PATMOS-x)
Andrew Heidinger, Aleksandar Jelenak, Michael
Pavolonis
NOAA/NESDIS/ORA
Objectives
• Improve the AVHRR data quality (notably geolocation and
reflectance calibration)
• Use PATMOS-x mapped data as vehicle to provide improved
AVHRR data and selected climate data records (similar to level 3
MODIS products)
• Use the spectral information and spatial resolution offered by
AVHRR to expand the knowledge available from existing
climatologies (ISCCP and HIRS)
• Develop cloud climate records from the AVHRR that are physically
consistent with those from MODIS and VIIRS
Scientific Rationale (Relevance to Climate)
• The AVHRR provides a unique 25 year record of global data from a
consistent set of sensors. Underutilized for cloud climate research.
• Past attempts (i.e. PATMOS) have shown the need for the data
improvement activities were undertaking.
• Results from existing cloud climatologies differ in some key respects
and the unique information provided by the AVHRR may help bring
consensus.
• The scientific relevance of the cloud climate records from EOS and
NPOESS will be much larger if we can extend selected time series
back in time using the AVHRR data.
Current Internal Capabilities and Activities
• PATMOS – The AVHRR Pathfinder Atmosphere project (1992-1998).
Processed only afternoon AVHRR data (1982-1999) into 1° climate
data records. Included cloud amount, aerosol over ocean and OLR
and planetary albedo. No other cloud products. Data hosted by
SAA/CLASS
• CLAVR-x – NESDIS’s new operational cloud processing system
developed by ORA. Replaces CLAVR with algorithmic and
processing improvements over the last few years. For example,
CLAVR-x algorithms can account for terminator conditions in
morning orbiter AVHRR data. Includes full suite of cloud products
(layered amounts, cloud type, cloud temperature, optical depths,
particle size, LWP, IWP, …).
• PATMOS-x – (an AVHRR reprocessing using CLAVR-x) was
developed as a pilot project funded by ORA. PATMOS-x runs
CLAVR-x in a configuration that uses ancillary data and processing
steps to transition its EDRs into CDRs.
The ORA AVHRR Processing System (as used for PATMOS-x)
INPUT
12 TB of online storage
PROCESSING
10 dual CPU
Linux Workstations
OUTPUT (0.5°)
Orbital pixel-level products
• Used for GVI-x processing
Orbital Mapped Products
•AVHRR GAC Level 1B
from CLASS (65 MB/ 32
TB)*
•Clevernav – new pixel
geolocation (10 MB / 2 TB)
CLAVR-x**
OPTRAN
•NCEP Reanalysis (50 GB)
Mapping
•Clear-sky Ch1 and NDVI
Composites (1 MB / 3 GB)
Averaging
Daily Mapped Files (50 MB / 2TB)
Monthly Averages (50 MB / 45 GB)
•OISST (0.5 MB / 700 MB)
* Size given per orbit (or day) processing and for processing all orbits or days.
**Note, CLAVR-x is same system used by OSDPD but run in different configuration for PATMOS-x
Results – Temporal Sampling (High Cloud Amount )
We have tried to build a system that captures the
needed temporal/spatial resolution for cloud
climate research. One of the big concerns using
AVHRR for climate is orbital drift.
Diurnal Cycle: July 2004 NOAA-15,16,17
•Sensitivity to orbital drift is mitigated by
processing all data (am,pm,terminator)
•Seek algorithmic solutions that are consistent from
satellite to satellite (inter-annual) and for all viewing
geometries (seasonal)
Seasonal Cycle: NOAA-16 Des. 2004
Inter-annual Cycle: July 1982-2004
Results: Comparison of PATMOS-x time series with others (High Cloud Amount)
• Note time series differ in magnitude and signs.
• ISCCP plagued by difficulties high cloud detection at night
•AQUA similar to PATMOS-x but new version of AQUA is forth coming
More Results – Non-cloud PATMOS-x products
•PATMOS-x contains multi-discipline CDRS. For example, PATMOS-x contains
aerosol optical depth and NDVI.
•While we recognize the GVI-x is no doubt a better NDVI time series for climate
studies, having an NDVI produced from PATMOS-x provides a strong
diagnostic tool for the performance of cloud processing (i.e. cloud mask). Also,
the PATMOS-x NDVI product may be sufficient/convenient for many
cloud/surface process studies.
0.63 mm Aerosol Optical Depth
NDVI (Atmos. Corr.)
Monthly Variation from 2004 from NOAA-16
•Using Simultaneous Nadir
Observations (SNO) to derive a
MODIS based AVHRR Reflectance
Calibration.
•SNO’s also used to tie reflectance
calibration of overlapping AVHRRs
together
Ref. Cal. Produces continuous
AOT time series (dark surface).
MODIS Ch1 Reflectance
Results: Contributions of PATMOS-x to AVHRR Data Improvement
AVHRR Ch1 Count
Ref. Cal. produces continuous Greenland
reflectance time series (bright surface).
We are still bothered by difference between MODIS-based and traditional results (N.Rao)
Results: Contributions of PATMOS-x to AVHRR Data Improvement
• Aleksandar Jelenak has developed a tool to reduce the geolocation errors
due to:
• AVHRR clock errors
• Interpolation from the sub sampled anchor points in Level 1B
• This tool produces hdf files meant to accompany the Level 1b data.
BEFORE
AFTER
Issues with current approaches
(Why do we need PATMOS-x given the existing cloud climatologies?)
• ISCCP’s use of a single reflectance and single thermal channel has
introduced large day/night differences in some critical cdrs. While
temporal resolution (3 hrly) is a strength of ISCCP, the day/night
differences in the approaches negate the ability for diurnal sampling
for some products.
• Some of ISCCP’s cloud amount time series show trends not seen in
other climatologies. ISCCP was never designed for long term
studies.
• HIRS based cloud climatologies do not suffer from the day/night
differences but lack sensitivity to low clouds. Low spatial resolution
(20 km) prohibits resolution of some types of cloudiness. Example
HIRS climatologies are the UW-NOAA HIRS CO2 Slicing (Menzel,
Wylie, Bates, Jackson) and Others (Stubenrauch, Susskind).
Recommended Approach (Activities)
Continue to develop the PATMOS-x Cloud Climatology:
• Finish MODIS-based Reflectance calibration. Support
other ORA efforts at FCDR improvement
• Reprocess all AVHRR data through PATMOS-x
• Analyze PATMOS-x data. Reprocess as we learn how to
improve its time-series (leverage off PEATE, GOES-R)
• Participate in GEWEX Cloud Working group and other
collaborations and try to reach a consensus among
members and gain acceptance/build maturity of the
PATMOS-x data.
• Continue to publish core PATMOS-x algorithms to facilitate
confidence in the climate community.
Reducing Uncertainties
• Come to a consensus on the AVHRR calibration and
quality assurance approaches. Use PATMOS-x as a
calibration test-bed.
• Pursue approaches that result in stable long term cloud
climate data records. Use advanced sensors to
characterize performance (CloudSat and CALIPSO).
• Leverage off the validation efforts for MODIS and NPP
which occur while the AVHRR is still flying. Strive to
achieve consistency between analogous products.
External Collaboration
• Participant in recent GEWEX cloud climatology assessment
workshop
• Participant in NPP PEATE which seeks consistent cloud cdrs from
NPP/VIIRS and AVHRR
• Collaborating on Reflectance Calibration with N. Saleous (NASA).
Geolocation improvement method handed to Eumetsat CM-SAF (P.
Albert).
• PATMOS-x cloud property algorithms used by M Uddstrom from
NIWA and leveraging off of his validation.
• Proposal submitted with Steve Platnick to pursue continuous
records in cloud optical thickness and particle size from
AVHRR/MODIS
• PATMOS-x cloud typing routine used by NPOESS contractor
Deliverables
• FY05: An AVHRR local archive in ORA, a
prototype cloud climatology system (PATMOSx), geolocation improvements.
• FY06: A complete reprocessing of the AVHRR
GAC data through PATMOS-x. Analysis of time
series. Completion and validation of new
reflectance calibration (MODIS-based).
• FY07: Validation of time series from PATMOS-x
and algorithm refinements to maximize maturity.
Conduct final reprocessing. Explore merger with
HIRS.