Snow and Albedo as Essential Climate Variables

Transcription

1 Snow and Albedo as Essential Climate Variables Jason E. Box Geological Survey of Denmark and Greenland Copenhagen, Denmark current (alphabetical) national collaboration 1.Liège, Belgium 2.Copenhagen, Denmark 3.Grenoble, France 4.Oslo, Norway 5.Zurich, Switzerland 6.Aberystwyth, Wales ESRIN Italy ESA Colocation ECV CCI

2 NASA MODIS

3 NASA MODIS

4 bare ice snow line snow land sea NASA MODIS

5 Sea ice, ponds, leads Tschudi, M.

6 ablation leads to 1.8x to 3.6x increased absorbed sunlight 60-86% 30-50% Snow 14-40% Bare Ice 50-70%

7 ablation leads to 2.1x to 4.3x increased absorbed sunlight 60-86% 15-40% Snow 14-40% Land 60-85%

8 ablation leads to 1.4x to 4.6x increased absorbed sunlight 35-80% 8-15% snow on sea ice, ponding 20-65% Sea 85-92%

9 75% increase in solar heating of Arctic ocean Perovich et al. 2007, Increasing solar heating of the Arctic Ocean and adjacent seas, : Attribution and role in the ice-albedo feedback, Geophys. Res. Lett., 34, L19505, doi: /2007GL

10 Tschudi, J. M. J. Maslanik D. Perovich, Recent Arctic Summer Sea Recent Arctic Summer Sea Ice Albedo Trends and their Ice Albedo Trends and their Relationship to Sea Ice Relationship to Sea Ice Conditions

11 Arctic Amplification of Warming zonal average anomalies

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13 MODIS on Terra

14 MODIS on Terra

15 MODIS on Terra

16 no data, yet

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19 polarportal.dk outreach NASA

20 Greenland Climate Network 1995-present Petermann Humboldt Tunu-N GITS NASA-E NGRIP NASA-U Summit CP1&2 Swiss Camp JAR1,2,3 KAR DYE-2 NASA-SE Saddle South Dome

21 PROMICE 2007-present Petermann Humboldt Tunu-N GITS NASA-E NGRIP NASA-U Summit CP1&2 Swiss Camp JAR1,2,3 KAR DYE-2 NASA-SE Saddle South Dome

22 Albedo Validation MODIS MOD10A1 Albedo GC-Net MODIS Greenland snow albedo validation studies 1.Stroeve, Box, et. al RSE 2.Stroeve, Box, et. al RSE 3.Liang, Stroeve, Box, et.al Box, et. al TC 5.Stroeve, Box, et. al RSE Box, J. E., X. Fettweis, J.C. Stroeve, M. Tedesco, D.K. Hall, and K. Steffen Greenland ice sheet albedo feedback: thermodynamics and atmospheric drivers, The Cryosphere, 6, doi: /tc

23 14 years of ground and MODIS MOD10 albedo

24 MOD10 Albedo Validation using PROMICE vs PROMICE MODIS

25 MCD43 Albedo Validation using PROMICE vs PROMICE MODIS

26 August 2015 survey of Greenland ice ice thickness Dash6 Twin Otter (POF) 2015 repeat of 2007 and 2011 surveys 2015 without ice sounding radar profiles of ~20 major glaciers in addition to ~1700 m elevation contour 2015 with spectral imager and laser ranger Height above surface 305 m (1,000 ft) nominal ground speed 69 m/s (135 knots, 250 km/hr) profiles of 20 major glaciers 1700 m elevation contour

27 POF belly port, photographed from below laser scanner 7.8 x 11 cm available space OCI 6 cm diameter optical sensors (scaled to actual size)

28 OLCI chan nel OLCI (nm) OLCI - MODIS overlap low limit, nm high limit, nm overlap with MODIS overlap with OLCI MODIS (nm) tetracam filter name center, nm width, nm mean overlap MODIS channel center, nm % 83% 67% % 95% 95% FS % 80% 80% % 10% 10% FS % 75% 50% % 30% 10% FS % 80% 80% % 64% 55% % 35% 30% % 76% 87% % 67% 33% % 75% 100% % 70% 40% FS low limit, nm high limit, nm width, nm

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32 successful 32 km missions. 0 airframe losses successful 140 km missions. 2 airframe losses. Aberystwyth University Johnny Ryan and the albedo drone August, 2014.

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34 UAV bottom tail nose Sony NEX5n camera Apogee Intruments SP-110 pyranometers UAV top 34

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38 ESA snow/ice ECVs: haves & have nots Maturity area (SE), 1km, GlobSnow ESA DUE * mass (SWE), 25 km, GlobSnow ESA DUE high albedo (land, sea ice, land ice) snowline ( bare ice area) surface temperature (IST) H2020 EUSTACE snow mass on land ice snow mass on land in mountainous regions snow mass on sea ice, lake ice melt rate (a.k.a. ablation, melt intensity) low exploiting ERB, albedo, cloud CCI products, CMUG * Data User Element

39 Snowline land ice ECV MODIS-based snowline retrieval end of melt season 2013 after Box, in prep.

40 Snow/Ice Albedo Applications CDRs change indication transient climate model evaluation data assimilation into melt models DMI HIRHAM5 * Data User Element

41 surface melting dominates Greenland ice cumulative total mass anomaly anomaly vs

42 photo J Box

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44 melt energy Clear Cloudy 26% 2% 6% 2% 3% 34% 71% 54% absorbed sunlight, S (1-α) L Condensation Turbulent Sensible Flux Rain

45 Flanner, M. G., K. M. Shell, M. Barlage, D. K. Perovich, and M. A. Tschudi (2011), Radiative forcing and albedo feedback from the Northern Hemisphere cryosphere between 1979 and 2008, Nat. Geosci., 4, , doi: /ngeo1062.

46 GlobSnow European Space Agency (ESA) Data User Element (DUE) snow extent (SE) ~1km, 17+ years; , i.e. the sensor record spanning Envisat AATSR and ERS-2, ATSR-2 semi-empirical SCAmod-algorithm (Metsämäki et al. 2012) snow water equivalent (SWE) 25 km, non-mountainous regions of N Hem., excluding glaciers and Greenland Pulliainen 2006, Takala et al pmw radiometers (SMMR, SSM/I and SSMIS) and ground-based weather station data, spanning years 1979 to 2013.

47 Albedo land ice ECV MODIS-based snowline retrieval end of melt season 2013 after Box, in prep.

48 US Bureau of Land Management

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50 Eicken, H., T. C. Grenfell, D. K. Perovich, J. A. Richter-Menge, and K. Frey (2004), Hydraulic controls of summer Arctic pack ice albedo, J. Geophys. Res., 109, C08007, doi: /2003jc

51 Riihelä, A., T. Manninen, and V. Laine, (2013) Observed changes in the albedo of the Arctic sea-ice zone for the period 1982 to Nature Climate Change, doi: /nclimate1963 Eicken, H., T. C. Grenfell, D. K. Perovich, J. A. Richter-Menge, and K. Frey (2004), Hydraulic controls of summer Arctic pack ice albedo, J. Geophys. Res., 109, C08007, doi: /2003jc Hudson, S. R. (2011), Estimating the global radiative impact of the sea ice albedo feedback in the Arctic, J. Geophys. Res., 116, D16102, doi: /2011jd Perovich, D. K., B. Light, H. Eicken, K. F. Jones, K. Runciman, and S. V. Nghiem (2007), Increasing solar heating of the Arctic Ocean and adjacent seas, : Attribution and role in the ice-albedo feedback, Geophys. Res. Lett., 34, L19505, doi: /2007gl

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53 Hudson, S. R. (2011), Estimating the global radiative impact of the sea ice albedo feedback in the Arctic, J. Geophys. Res., 116, D16102, doi: /2011JD

54 Climate Application Takala, M., Luojus, K., Pulliainen, J., Derksen, C., Lemmetyinen, J., Kärnä, J.-P., Koskinen, J. and Bojkov, B. (2011): Estimating northern hemisphere snow water equivalent for climate research through assimilation of space-borne radiometer data and ground-based measurements. Remote Sensing of Environment, Vol. 115 no. 12, December 2011, pp , doi: /j.rse

55 Climate Application Metsämäki, S., Mattila, O.-P., Pulliainen, J., Niemi, K., Luojus, K., Böttcher, K., "An optical reflectance model-based method for fractional snow cover mapping applicable to continental scale" Remote Sensing of Environment, Vol. 123, August 2012, Pages , /j.rse

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