acsys observation products panelacsys observation products

9/23/99 PoDAG Meeting (K. Steffen) 1

Members

Konrad Steffen, University of Colorado, USA – Chair

Joey Comiso, NASA/GSFC, USA

Ron Kwok, NASA/JPL, USA

Seymour Laxon, University College London, EnglandVladimir Smirnov, AARI, St. Petersburg, Russian Fed.

Bruce Ramsay Tom Carrieres, Canadian Ice Center, Canada

Jinro Ukita, Frontier Research Systems, Japan

Meetings

1st OPP Meeting: Koblenz, Germany, 28 June – 1 July, 1999

Global Runoff Data Center

2nd OPP Meeting: St. Petersburg, Russian Fed., July 2000

Arctic and Antarctic Research Institute

ACSYS Observation Products PanelACSYS Observation Products Panel


Agenda

Initial task: to evaluate and recommend the optimum sea-ice products needed by ACSYS, in particular evaluate products for the ECMWF Re-Analysis (1958 - present).

General: to evaluate current and new techniques for sea-ice concentration and thickness products for ACSYS use and particularly in relation to model verification. Review also other se ice parameters following the initial review (I.g., ice type, IST, SST in marginal IZ).

• Evaluate user requirements for OP obtained by in-situ and remote sensing obs.

• Evaluate techniques by which specified observational products are derived.

• Evaluate data sets derived from the application of these techniques.

• Review new techniques and products for application in ACSYS-relevant climate res.

• Assess accuracy and recommend the best products for ACSYS use

• Liase with other groups (GEWEX and CLIVAR) and external to WCRP

ACSYS Observation Products PanelACSYS Observation Products Panel


NCAR has undertaken a massive program of observational data rehabilitation. The results of these efforts are being made available to ERA-40 and will provide the main component of the archive of pre-1979 conventional data. The US-Navy has made available their de-classified data, and additional data are being provided by the Japan Meteorological Agency.

NCAR have also provided an archive of VTPR and TOVS 1b data for the period 1974 to 1993. Arrangements are being made to acquire the later TOVS 1b data, EUMETSAT re-computed METEOSAT cloud winds, SSM/I radiance data, and other appropriate satellite data.

Data sources for ERA-40 will include most of those used for ERA-15, but with these additional sources:

conventional surface and upper air data pre-1979 from NCAR; declassified US-Navy data; full VTPR and TOVS 1b data; SSM/I radiance;ERS-1 and ERS-2 data; updated COADS; GISST 4 and a new SST data set from NCEP, with compatible sea ice.

ECMWF Re-Analysis (1958-98): ERA-40ECMWF Re-Analysis (1958-98): ERA-40


A campaign of pre-production experimentation has begun to enable the exact details of the production system to be established. Currently it is expected that the production system will use:

spectral TL159 resolution with 60 hybrid vertical levels3 dimensional variational (3D-VAR) analysis incorporating physical retrieval of satellite radiance dataintegrated Forecast System (IFS) version of the ECMWF forecast model coupled wave model with 1.5 degree resolutionanalysis and prediction of stratospheric ozonevarying carbon dioxide and aerosolsSST and sea ice forcing as indicated above

ERA-40 production is expected to begin in the third quarter of 1999. Results of the re-analysis will be made available after each whole year has been completed, and when sufficient validation is complete to give reasonable confidence in the data.

ECMWF Re-Analysis (1958-98): ERA-40ECMWF Re-Analysis (1958-98): ERA-40


National Ice Center Digital Ice MapsNational Ice Center Digital Ice Maps

• Digital maps available since 1997• Currently 19-years of data are digitized• Does cover Arctic and Antarctic regions


International Arctic Buoy Data ProgramInternational Arctic Buoy Data Program

Arctic Ocean buoy data products are 12-hourly interpolated pressure, temperature, position, and ice velocity grids. Buoys deployed on ice floes measure atmospheric pressure and temperature (inside buoy housing) at ocean surface; an average of 15 buoys are in service at any time. Grid is 2 minutes longitude by 10 minutes latitude. Synoptic weather station data have been integrated into pressure field calculations. As of October 1998 gridded data are available for 1979 to 1996.

Data sets are pressure/temperature, position, ice velocity. Data are ASCII (tabular); format is described in annual data reports. Copies of the format description provided on request by NSIDC. An on-line guide is available for this data set. Data are collected and processed as part of the Coordinated Arctic Buoy Program at the University of Washington, Polar Science Center, and are available via FTP.

Spatial Coverage Map: International Arctic Buoy Program, 1992:


SSM/I PM and NOAA VIS derived Ice TypesSSM/I PM and NOAA VIS derived Ice Types


Passive Microwave Ice ConcentrationPassive Microwave Ice Concentration

0 20 40 60 80 100

Landsat Ice Concentration (%)

0

20

40

60

80

100

NA

SA

-Tea

m S

SM

/I Ic

e C

once

ntra

tion

(%)

Linear Fit r=0.967Stand. Dev. =6.6%

Global Tie Points

Beaufort, Chukchi, Weddell and Greenland seas, spring and fall conditions. Statistics of SSM/I ice concentration minus

Landsat ice concentration in percent for local and global tie points.

mean median std dev min max SSM/I pixels

Local TP -1.5% 0.0% ±4.5% -20.3% 7.9% 95

Global TP -3.6% -3.2% ±6.6% -25.3% 13.8% 95

0 20 40 60 80 100


0

20

40

60

80

100

NA

SA

-Tea

m S

SM

/I Ic

e C

once

ntra

tion

(%)

Linear Fit r=0.978Stand. Dev. =4.5%

Local Tie Points


Passive Microwave Ice ConcentrationPassive Microwave Ice Concentration

70 80 90 100


-30

-20

-10

0

10

SS

M/I

- La

ndsa

t Ice

Con

c. (

%)

Global Tie PointsLocal Tiel Points

Spring Ice Conditions

Beaufort Sea, spring 1988. Statistics of SSM/I ice concentrationminus Landsat ice concentration in percent for local and global tiepoints.

mean median std dev min max SSM/I pixelsLocal TP -0.2% 0.0% ±2.6% -7.8% 7.9% 33Global TP -2.1% 1.8% ±3.1% -9.7% 6.0% 33

0 20 40 60 80 100


��

��

�

��

��

��

SS

M/I

- La

ndsa

t Ice

Con

c. (

%)

Summer Ice Conditions

Beaufort and Chukchi seas, summer 1988. Statistics of SSM/I iceconcentration minus Landsat ice concentration in percent for localand global tie points.

mean median std dev min max SSM/I pixelsLocal TP 3.8% 1.5% ±22.3% -24.0% 46.6% 25Global TP 11.0% 13.5% ±22.9% -20.0% 50.1% 25


NOAA/NASA Polar Pathfinder ProgramNOAA/NASA Polar Pathfinder Program

The AVHRR Polar Pathfinder 5 km Data Set provides a time-series overview of each entire pole, and provides for the first time, daily composites of AVHRR-collected variables at a resolution suitable for process studies on a hemispheric scale. Temporal coverage begins in July 1981 and continues through the present. Calibrated channel data from each of the five channels; surface broadband albedo; surface (skin) temperature; and ancillary data including solar zenith angles, relative azimuth angles, satellite elevation angles, time of pixel, cloud mask, orbit masks, and surface-type masks are provided. Also included are ice motionproducts.


NOAA/NASA Polar Pathfinder ProgramNOAA/NASA Polar Pathfinder Program

Ice Motion and Surface Pressure for April 30, 1988

The P-Cube data set is a 100 km resolution subset of many important variables from three Polar Pathfinder Projects in commonprojection (Lambert azimuthal equal-area) and common grid (EASE-Grid). For the first time, data sets from multiple sensors measuring the Arctic region are being distributed in a manner that facilitates study of polar processes and interactions between them. A "data cube" of the Polar Pathfinder Products, hence the name "P-Cube," allows users to access variables derived from three satellite sensors and use them together. The common spatial resolution for P-Cube is dictated by the lowest resolution product (TOVS data). The P-Cube allows browsing of the multi-sensor data and exploring the relationships among the variables. For AVHRR and SSM/I data, the user may turn to the full resolution, single instrument Polar Pathfinder data sets for greater details.


ACSYS OPP Recommandations (Draft)ACSYS OPP Recommandations (Draft)

ENVISAT Data for Arctic Ice MonitoringRADARSAT Geophysical Processor (RGPS) is essential for monitoring sea ice dynamics, seasonal and interannual variations in concentration and thickness. Radarsat-2 SAR satellite date will not be available to the US-lead processing laboratories. We recommend therefore that the ENVISAT satellite data will be made available by the European Space Agency to US investigators to continue monitoring the state of the Arctic sea ice. (contact person: Dr. Ron Kwok, NASA-JPL)



ERA-40 Sea Ice ConcentrationWe recommend using the following sea ice products for the ECMWF re-

analysis1958-72: AARI 10-Day Arctic Ocean EASE-Grid Sea Ice Observations,

Arctic and Southern Oceans sea ice concentrations. All these data sets are available from the WDC-A/NSIDC in Boulder.

1972- 76: ESMR passive microwave derived ice concentrations and ice extent (NSIDC).

1977-78: Analyzed fields from the National Ice Centers (US and Canadian), and Arctic and Southern Oceans sea ice concentrationsdata set (NSIDC).

1979-98: SMMR and SSM/I passive microwave derived ice concentration and ice extent using the Bootstrap algorithm for both hemispheres.

ERA-40 Surface Pressure and Air TemperatureFor the re-analysis project (ECMWF 1958-72) we recommend to use all

available buoys pressure data, and buoy air temperatures after 1994.



Upper Looking Sonar (ULS) Submarine Data SetsThis data set is the only in situ information on the spatial distribution of ice thickness for certain parts in the Arctic, and therefore should be made available to the scientific community as soon as possible. We recommend that: (a) the Arctic Ocean Climate Stations ULS be archived at the WDC-A; (b) release schedule for all historic submarine ULS data (US, UK and others); (c) release schedule for SCICEX data; and (d) we propose that an intercomparison between all archived ULS data sets been coordinated by the archiving centers to reduce possible “off-set errors” which were observed in the past.



Data Assimilation A major challenge to the sea ice research community is how to address the need for a uniform, consistent, gridded data set describing the state of the polar sea-ice and its variability in time and space. This is especially troublesome since most remotely sensed information only provides indirect measurements of the key elements of sea ice dynamics – ice concentration, ice movement, ice thickness, and turbulent energy fluxes through the atmosphere-ice-ocean interfaces. Further compounding this problem, in-situ measurements of ice properties are from temporally and spatially limited case studies. We recommend the use of data assimilation in simple models, and with success at this level, moving to progressively more complex models. Further, we recommend the re-configuration of current remote sensing data to include precise time tags with each pixel needed to assess error statistics and quality control information. The effectiveness of data assimilation techniques is directly linked to the availability of data error statistics.

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