aft_4_luojus_globsnow_igarss_2011_final.ppt

12.04.23

ESA DUE GLOBSNOW

Investigating Hemispherical Trends in Snow Accumulation Using GlobSnow

Snow Water Equivalent Data

Kari Luojus (Finnish Meteorological Institute)J. Pulliainen, M. Takala, J. Lemmetyinen (FMI)C. Derksen, L. Wang (EC)S. Metsämäki (SYKE), B. Bojkov (ESA)

GlobSnow project consortium:FMI, NR, ENVEO, GAMMA, SYKE, EC, Norut

12.04.23Finnish Meteorological Institute 2

ESA-funded GlobSnow project: Production of hemispherical scale snow extent (SE) and snow water equivalent (SWE) climate data records; along with a demonstration of a near real time processing and data dissemination chain for the products.

Consortium; Finnish Meteorological Institute (FMI) with ENVEO IT GmbH (Austria), GAMMA Remote Sensing (Switzerland), Norwegian Computing Center, Finnish Environment Institute (SYKE), and Environment Canada (EC).

Products and project details: www.globsnow.info

Near-real-time snow map production on-going since: 1 October 2010

ESA GlobSnow

http://www.esa.int/

http://www.enveo.at/

http://www.nr.no/

http://www.gamma-rs.ch/

http://www.environment.fi/

http://www.ec.gc.ca/


GlobSnow: Long term snow products

• SWE (30 years) and SE product (15 years) + NRT demonstration

• Primary products:

• Daily SWE / Daily fractional SE

• Secondary products:

• Weekly SWE / SE (mean and maximum)• Sliding average: data from current day + previous 6 days

• 1 file for every day

• Monthly SWE / SE(mean and maximum)• 12 files per year: January, February, March…

• Spatial coverage: Northern Hemisphere (both SE & SWE)


GlobSnow – SWE ECVA new State-of-the-Art Snow Water Equivalent (SWE) climate data record

• Work initiated at HUT/LST during 1990’s by Profs Pulliainen and Hallikainen• SWE Methodology (main body of work) published 2006 in RSE by Pulliainen• Past 5 years the work has been carried at FMI Arctic research centre

• Shifted in high gear for ESA DUE GlobSnow (T.O. ESA/ESRIN: B.Bojkov)-> Past 3 years of work by an experienced team (key people originally HUT/LST + team at Environment Canada) have resulted in a new SWE climate record (daily, 1979 – 2010, hemispherical SWE record)

• Validation, spanning NH, indicates a new level of accuracy for SWE retrieval• Production of 30+ years SWE data on a (FMI Cray 5 XTm) super computer

Results presented in earlier conferences & a journal article in press (and a project document library for GlobSnow users)


SWE product (development by FMI & EC)

• SWE climate record for 1979 - 2010 (+ NRT demonstration)

• Spaceborne microwave radiometer data

1) AMSR-E data (2003 – present)

2) SSM/I data (1987 – 2002)

3) SMMR data (1979 – 1987)

+ Global weather station data from WMO stations

• Produced in EASE-grid projection ~ 25km resolution

• Product includes error estimates for each SWE value


Overview for the SWE product• Daily maps of hemispherical snow

cover:

- SWE for the permanent seasonal snow area

- Total snow area (Snow Extent)

• Regions with high topograpical variability are masked out

- Alpine regions

- Glaciers

- Greenland

• NRT production of SWE demonstrated in 2010-2011

• NRT to be transferred to EUMETSAT H-SAF late 2011

• Data format HDF4 & NetCDF CF

• Data access through FTP & WWW


Daily SWE product: 15 February 2008

Northern Hemisphere


SWE algorithm selection & retrieval validationDaily SWE estimates acquired with 5 algorithms evaluated for Eurasia (1994-1997)

• FMI Assimilation algorithm (Pulliainen 2006)

• EC SWE suite (Goodison, Walker, Goita, Derksen et al. 1993-2009)

• Chang et al. 1987 (original channel difference algorithm)

• SPD-algorithm (Asbacher 1989)

• Armstrong and Brodzik 2001-algorithm (Improved channel difference)

SWE estimates computed between 09/1994 and 12/1997 (SSM/I data)

• Chang, SPD and Armstrong –algorithms were evaluated for both asc & desc nodes; FMI uses desc node data complemented with asc node data

• Evaluations for North America and Finland were carried out in addition to the analyses for Eurasia


Validation data – INTAS SSCONE data

INTAS SSCONE data (from the former USSR and Russia)• There are 1294 snow path stations with data from the USSR

• Manual ground-based measurements on snow depth

• Used as the validation data for the GlobSnow evaluations

• There were 450 path stations with data for 1994-1997


Overall performance for SWE algorithms

Eurasia 09/1994 – 12/1997Evaluation with 450 INTAS snow courses

Name RMSE bias Corr.coeffUnbiased

RMSESamples

FMI algorithm - (selected for GlobSnow)

43.2 mm -3.1 mm 0.611 43.1 mm 26063

EC algorithm 67.6 mm -28.2 mm 0.210 61.5 mm 18109

Chang et al. 1987 (asc node)Chang et al. 1987 (desc node)

71.6 mm70.7 mm

-8.4 mm1.6 mm

0.0110.029

71.1 mm70.8 mm

2672627521

SPD algorithm (asc node)SPD algorithm (desc node)

67.1 mm63.9 mm

-12.7 mm-3.1 mm

0.0520.121

65.9 mm63.9 mm

2955929451

Armstrong et al. 2001 (asc node)Armstrong et al. 2001 (desc node)

72.3 mm73.7 mm

-44.1 mm-42.9 mm

0.0440.029

57.3 mm59.9 mm

2179624791


SWE<150 mm All SWE

• RMS error and retrieval bias calculated independently for each year• Consistent inter-annual characteristics & minimal difference between sensors

Consistency of GlobSnow SWE retrieval 1980 - 2009

AMSR-EF 13

SSM/IF 11

SSM/IF 8

SSM/ISMMR AMSR-EF 13

SSM/IF 11

SSM/IF 8

SSM/ISMMR

AMSR-EF 13

SSM/IF 11

SSM/IF 8

SSM/ISMMR AMSR-EF 13

SSM/IF 11

SSM/IF 8

SSM/ISMMR


AMSR-E vs. SSM/I evaluations (2003 - 2010)

• GlobSnow SWE PMW sensor changes from SSM/I to AMSR-E at the beginning of 2003

• FPS v1.0 (current sensor set)

• SMMR 1979 – 1987

• SSM/I 1987 – 2002

• AMSR-E 2003 – 2010

• Possible alternative sensor set (e.g. NSIDC sea ice)

• SMMR 1979 – 1987

• SSM/I 1987 - 2010

• Comparisons between for SSM/I and AMSR-E derived SWE datasets (2003-2010) conducted


• Change of bias: DMSP-F13 results in higher snow mass (SWE) than AMSR-E, but DMSP-F17 gives a lower snow mass after summer 2009

2009-2010 DMSP-F172003 – 2008 DMSP-F13

AMSR-E vs. SSM/I evaluations (2003 - 2010)


AMSR-E vs. SSM/I trend (1980 - 2010)


SSMI, -8,2% trend for 30 yearsAMSR-E, -9.6% trend for 30 years

AMSR-E vs. SSM/I trend (1980 - 2010)


Summary on SWE product • Current long term datasets on Global scale: Monthly from 1978, daily from 2002

GlobSnow: Daily 30+ years ( … from launch of SMMR 1978)

• Thematic accuracy

• Current alternative algorithms

• Global scale 40mm – 200mm

• Regional scale 20mm – 50mm (methods typically regionally adjusted)

• GlobSnow algorithm (Global scale):

RMSE of 43.2 mm for Eurasia (diagnostic dataset; > 26 000 samples)

RMSE of 33.5 mm for Eurasia (for SWE < 150mm; >23 000 samples)

Error estimates (error bars)

• Current methods do not provide information on estimation error

GlobSnow SWE algorithm: Error estimates for each SWE estimate

12.04.23Finnish Meteorological Institute 1712.04.23Finnish Meteorological Institute 17

GlobSnow Snow Extent Dataset

• SE retrieval using ERS-2 ATSR-2 and Envisat AATSR data

- Finnish Environment Institute’s SCAmod algorithm.

- Norwegian Linear Reflectance’ (NLR) fractional snow cover (FSC) algorithm;

- 15 years SE data record has been produced using optical imagery from ATSR-2 (1995-) and AATSR (2002-) on a hemispherical scale. yellow – clouds

green – bare groundwhite – snow cover

http://www.esa.int/

http://www.enveo.at/

http://www.nr.no/

http://www.gamma-rs.ch/


Daily, weekly and monthly products

April 2003

19 April 2003

10 April 2003

Optical data ~ 1km spatial resolution


Examples of monthly products, 2003

April 2003

May 2003

June 2003

12.04.23Finnish Meteorological Institute 2012.04.23Finnish Meteorological Institute 20

• 30+ year daily Snow Water Equivalent climate record (25 km resolution)• 30+ year daily Snow Extent (PMW) climate record (25 km resolution)• 15+ year daily Snow Extent (optical) climate record (1km resolution)

- Version 1.0 of low resolution SWE/SE (30 years) and high resolution SE (15 years) are available now

- The extensive validation effort indicates a new level of accuracy for hemispherical scale SWE retrieval for the 30+ year evaluation

- Long term trends indicate a clear decline in hemispherical snow mass

The near-real-time GlobSnow processing system is on-going an operational demonstration phase (ESA GlobSnow -> Eumetsat H-SAF)

Products (freely available) and additional details: www.globsnow.info

GlobSnow - Summary

aft_4_luojus_globsnow_igarss_2011_final.ppt

Technology

years swe data

swe value

globsnow swe ecv

daily swe product

smmr data

desc node data

weekly swe se

swe retrieval production