Photo credit: A. Rees, WLU

The challenge of evaluating RCM snow cover simulations over

northern high latitudes

Ross D. Brown, Climate Research Division, Environment Canada @ Ouranos, Montréal

The problem…

Snow cover extent variations over high latitudes are difficult to monitor for a number of reasons…

• Strong local controls on snow cover (wind, topography, vegetation, proximity to open water…)

• Patchy spring snow cover (scaling and sensor resolution issues)

• Frequent cloud cover during snow cover onset and melt periods

• Large gaps in surface observing network; unrepresentative sites

• Snowpack structure and lake ice pose challenges for passive m/w

• Confusion of lake ice and snow cover during melt season

• Historical operational products such as NOAA weekly product include changes in analysis procedures, spatial resolution and the amount and resolution of available satellite imagery over time (re-charting work by Dave Robinson attempting to address this)

• Relatively small area of snow cover during melt season in Arctic; errors potentially large % of mean SCE

What snow information exists over the Arctic and how good is it?

1. In situ:

daily snow depths, bi-weekly snow surveys, snow pillows

sparse data coverage over Arctic especially northern Canada

daily depths are point observations take at open locations and may not be representative especially in regions with high winds and frequent drifting snow

can obtain longer length scales with derived snow cover variables such as snow cover duration and start/end dates of snow cover

NO pan-Arctic dataset… Russia and Scandinavian countries have a merged SWE dataset but is not public; Canada and FSU data published to 2004; US data dispersed over a number of agencies

MSC snow sampler Oct Nov Dec Jan Feb Mar Apr May

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io

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All data

Ratio of snow stake measurements to adjacentforested area snow course (forest transect)

Oct Nov Dec Jan Feb Mar Apr May0.5

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All data

Ratio of snow stake measurements to adjacentforested area snow course (forest transect)

Spatial distribution of daily snow depth observations in the Global Summary of the Day dataset

Spatial distribution of March SWE obs from Canada and FSU, 1966-1990.

Not a data gap… high density of SWE obs exist over Scandinavia

Current snow survey network for Alaska

2. Satellite sources with continuous snow cover information over Arctic:

Data source Variable Period Resoln. Source

CCRS AVHRR Snow-off date 1982-2004 5 km Zhao and Fernandes (2009)

IMS daily 24 km Daily snow-no snow

1997-2008 24 km NSIDC [Ramsey (1998)]

IMS daily 4 km Daily snow-no snow

2004-2008 4 km NSIDC [Helfrich et al., 2007]

MODIS monthly 0.05° (MOD10CM Version 5)

Snow cover fraction

2000-2008 ~5 km NSIDC [Hall et al., (2006)]

NOAA Weekly snow-no snow

1966-2008 190.5 km

Rutgers U. [Robinson et al., 1993]

Passive m/w SWE, snow cover extent

1978-2008 24 km NSIDC [Armstrong and Brodzik(2005)]

QSCAT Snow-off date 2000-2008 ~5 km Wang et al. (2008)

Data source Variable Period Resolution Source

CMC Analysis Daily snow depth (estimated SWE)

1998-2008 ~35 km Canadian Met. Centre [Brasnett, 1999]

CRCM4.1driven with ERA-40 over North America

Daily snow depth, SWE, snow cover fraction

1958-2000 ~50 km Ouranos Climate Simulation Group [Caya and Laprise, 1999]

ERA-40 Reanalysis snow depths

Daily snow depth 1958-2003 ~275 km ECMWF [Uppala et al, 2005]

ERA-40 reconstructed snow cover

Daily snow depth 1958-2003 ~275 km (with 5 km elevation adjustment)

Reconstructed snow depth from 6-hourly temp and precip

NCEP Reanalysis spring thaw date

Snow-off date 1948-2008 ~275 km 0°C crossing date used as proxy for snow cover melt date

3. Other sources:

1949 1954 1959 1964 1969 1974 1979 1984 1989 1994 1999 2004

NOAA

NCEP

ERA-40

ERA-40 rec

CCRS

CRCM4

PMW

MODIS

QSCAT

IMS-24

IMS-4

CMC

Temporal distribution of NH snow cover data sets (CRCM4 only available for North America)

Problem that dataset temporal coverage is quite variable…

Large differences in mean SCE between datasets over the Arctic

June SCE, North America N60

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1959 1963 1967 1971 1975 1979 1983 1987 1991 1995 1999 2003 2007

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E (

mill

ion

km

^2) NOAA

NCEP

ERA-40

ERA-40 rec

CCRS

CRCM4

PMW

40% 0% 0% 0% 0%

40% 40% 40% 0% 0%

50% 50% 40% 0% 0%

80% 80% 40% 0% 0%

100% 80% 40% 0% 0%

25 km

25 km

IMS-24 SCE = 0

IMS-4 SCE = 150 km2

MODIS SCE = 180 km2

Amount of snow cover “seen” depends on threshold and resolution…

Mean % error in NH SCE from IMS 4km, 2004-2008

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% e

rro

r

NOAA

IMS-24km

Error in Arctic ablation season SCE > ± 10% when resolution falls below ~ 25 km

June NOAA NCEP PMW QSCAT MODIS IMS-24 IMS-4 CMC

Average 4.8 2.8 1.2 3.4 2.3 5.1 4.7 3.0

Stdev 0.7 0.9 0.4 0.5 0.3 0.6 0.6 0.7

Mean SCE seen by various data sets over NH north of 60° (excl Greenland) for the period 2004-2008

May NOAA NCEP PMW QSCAT MODIS IMS-24 IMS-4 CMC

Average 11.6 10.2 7.2 10.2 9.6 11.0 10.6 9.0

Stdev 0.6 1.2 0.9 1.0 0.7 0.5 0.6 0.7

May Average NH SCE (excl PMW) 2004-2008 = 10.3 ± 0.9 million km2

June Average NH SCE (excl PMW) 2004-2008 = 3.7 ± 1.1 million km2

Development of reliable gridded SWE information is particularly problematic over the Arctic :

sparse obs, problems of data representativeness

PMW has not yet shown it can provide reliable SWE estimates over Arctic

CMC analysis affected by data biases and excessive melt from degree-day melt algorithm

snow depth estimates available from laser and radar altimetry but not enough in time and space for circumpolar RCM evaluation

SWE estimates from GRACE could be used for basin-averaged analysis of snow water storage

downscaled snow cover information from reanalyses with snow/hydrological models including key Arctic processes (blowing snow, sublimation) is a potential solution but then how reliable is the precipitation?

Mean annual maximum SWE estimated from CMC snow depth analysis, 1999-2006

Mean annual maximum SWE from 14 AR4 GCMs, 1970-1999

Comparison of CMC est mean monthly max SWE for 1999-2006 with the average model values for the 1970-1999 reference period. On average the models overestimate annual maximum monthly SWE by 16 mm over NH land areas north of 30N.

Difference (mm)

Conclusions:

• Evaluation of RCM snow simulations in the Arctic is a challenge!

• Are in good shape for evaluating snow-off dates with new CCRS dataset, Quikscat and PMW (snow-on dates more of challenge)

• Also in good shape for evaluating monthly snow cover fraction with MODIS monthly and IMS 24-km products (but only have ~10 years data)

• Snow depth and SWE are more problematic - downscaling with high resolution Arctic snow process models is one approach e.g. PBSM Pomeroy et al., SnowTran-3D Liston and Sturm

2000 2001 2002

2003 2004 2005

Application of QuikSCAT for monitoring pan-Arctic melt onset, 2000 - 2005

Source: L. Wang, ECJulian Day

Spring SCD (days)

Application of QuikSCAT for mapping spring snow cover – mean spring (MAMJJ) snow cover duration, 2000-2004.

Source: Brown et al., 2007

Sample of Canada Centre for Remote Sensing circumpolar dataset of snow disappearance date from Arctic Polar Pathfinder AVHRR data, 1982-2004

Source: H. Zhao and R. Fernandes, CCRS (JGR, 2009)