CCI and the Sea Ice ECVT. Lavergne (MET Norway)

ESA Climate Change Initiative / 9th Collocation meeting / 25-28 March 2019

Layout● Sea Ice in GCOS-IP 2016;

● Highlights from CCI;

● The associated SeaIceScape in Europe;

● Plans in CCI+ (Phase 1);

● Cross-ECV considerations.

Sea Ice in GCOS-IP 2016The primary parameters that define the state of sea ice include: concentration, area and extent, ice type, motion, deformation, age, thickness and volume.

The presence of sea ice strongly modifies surface waves and air-sea exchanges of heat, momentum, moisture and gasses. Sea ice also has a distinct influence on the Earth’s albedo. In addition, the water masses and properties below the sea ice are transformed through freezing and melting.

Table: GCOS Product Requirements for the Sea Ice ECV (GCOS-200)

Highlights from CCI

Phase 1:● SIC RRDP (Pedersen et al., 2018)● Intercomparison of 30+ SIC algos.

(Ivanova et al., 2015)

Phase 2:Design new algorithms.(Lavergne et al., 2019)

Better algorithms CCI and OSISAF CDRs documented in Lavergne et al. (2019)

Highlights from CCI

Algorithm developments to bring Envisat and CS2freeboards to 25km [Paul et al. 2018].

At the end of CCI Phase 2: Envisat + CS2 time-series, 2002-2017 (NH + SH).

Also full error propagation.

The associated SeaIceScape (in Europe)

2013-2018R2O

2021

R2O

new CDRICDR

new CDR, ICDR

+

Sea Ice Thickness

Sea IceConcentration

2019-2021

2019-2021

Plans in CCI+● Continued R&D on Sea-ice Concentration and Thickness

● For Thickness:○ Extend with ERS-1 and -2 (1993->);○ Algorithms improvements;○ Better uncertainties.

● For Concentrations:○ Use higher frequency channels (1992->)○ Extend with ESMR Nimbus-5 (1972-77)○ Better uncertainties;

● User Reqs, Validation, and Climate Assessment activities.

SIT in CCI+ : ERS 1 and 2

Envisat + CryoSat-2 inCCI & C3SERS 1&2 in CCI+

S3 in C3S (& CCI+)

SIT in CCI+ : Algorithm improvements

● Focus on ERS 1&2 and the overlap to Envisat (continuity);

● Improve on the propagation of uncertainties, especially to L3 (monthly) : separate the random and systematic contributions.

● Define a Level-4 product, filling the polar observation hole (needed for Sea Ice Volume estimates / indicators).

● Small improvements:○ Ocean swell in MIZ○ Retracking, surface type classification etc.

SIC in CCI+ : high-frequency channels

● GCOS requires “10-15 km” spatial resolution. This is not achieved by the long-term CDRs from US NSIDC, OSI SAF, nor CCI.

● “near 90 GHz” frequency channels provide better resolution (~15km), and are available since 1991 (F10) (soon 30 years).

● BUT: ~90 GHz means (substantially) more retrieval noise: -> new/improved algorithms.

● A “draft” CDR using ~90 GHz was processed in CCI, but considered not mature enough.

30+ years with ~90GHzimagery.

SIC in CCI+ : ESMR Nimbus-5● ESMR was a pre-cursor imaging radiometer flown on U.S.

Nimbus-5 (and -6) missions.

● L1 calibrated Nimbus-5 ESMR data (1972-1977) were recently released (data rescue).

● ESMR is quite different from the later radiometers:○ cross-track scanning (geometry variation);○ single frequency (~19 GHz) blending polarizations.

● In CCI+, we will see what can be achieved with ESMR, aiming first at weekly sea-ice extent (ice/no-ice) maps.

● Why care for just 5 years? e.g. Weddell Sea Polynya (winters 1974-1976).

30+ years with ~90GHzimagery.

Sea Ice and the other ECVs● For most Ocean ECVs, sea ice is just a land mask…. but it moves every day!

● These can/should access to the most recent SIC data record (luckily it starts early, 1978).○ Often used as ice/no-ice mask.○ Sometimes as area fraction?

● Ocean ECVs from Vis/IR sensors (e.g. SST, OC) have higher resolution (~1 km) than the SIC data record (~ 25-50 km). Mismatch in scale (interest for the CCI+ developments, and for ice masks derived directly from Vis/IR data… not a CCI_Sea_Ice task).

● Many Atmosphere retrievals will break over sea ice surface (albedo, emissivity). Here again, is mismatch in spatial scale an issue?

● The Sea Ice ECV team is looking forward to dialogue on this, to help cross-ECV consistency.

ExtraContact:

● Thomas Lavergne (thomas.lavergne@met.no)● Twitter @lavergnetho

References:

Ivanova, N., Pedersen, L. T., Tonboe, R. T., Kern, S., Heygster, G., Lavergne, T., Sørensen, A., Saldo, R., Dybkjær, G., Brucker, L., and Shokr, M.: Inter-comparison and evaluation of sea ice algorithms: towards further identification of challenges and optimal approach using passive microwave observations, The Cryosphere, 9, 1797–1817, https://doi.org/10.5194/tc-9-1797-2015, 2015.

Lavergne, T., Sørensen, A. M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., Bell, L., Dybkjær, G., Eastwood, S., Gabarro, C., Heygster, G., Killie, M. A., Brandt Kreiner, M., Lavelle, J., Saldo, R., Sandven, S., and Pedersen, L. T.: Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records, The Cryosphere, 13, 49-78, https://doi.org/10.5194/tc-13-49-2019, 2019.

Pedersen, L. T., Saldo, R., Ivanova, N., Kern, S., Heygster, G., Tonboe, R., Huntemann, M., Ozsoy, B., Ardhuin, F., and Kaleschke, L.: Reference dataset for sea ice concentration, figshare, https://doi.org/10.6084/m9.figshare.6626549.v3, 2018. 

Paul, S., Hendricks, S., Ricker, R., Kern, S., and Rinne, E.: Empirical parametrization of Envisat freeboard retrieval of Arctic and Antarctic sea ice based on CryoSat-2: progress in the ESA Climate Change Initiative, The Cryosphere, 12, 2437-2460, https://doi.org/10.5194/tc-12-2437-2018, 2018.

Schwegmann, S., Rinne, E., Ricker, R., Hendricks, S., and Helm, V.: About the consistency between Envisat and CryoSat-2 radar freeboard retrieval over Antarctic sea ice, The Cryosphere, 10, 1415-1425, https://doi.org/10.5194/tc-10-1415-2016, 2016.

Sipola, J.: An assessment of an Arctic sea ice thickness reanalysis using ESA Climate Change Initiative product, Master’s thesis, University of Helsinki, 2018