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Surface Analysis (I)

M. Drusch

Room 1007, Phone 2759

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The Current Surface Analysis System

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Outline

1. Sea Surface Temperature (SST)2. Sea Ice (CI)3. Snow

1. 2 m Relative Humidity and Temperature2. Soil Moisture

Part 1:

Part 2:

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Overview Part I

1. Sea Surface Temperature (SST)- NCEP / MMAB SST- lake SST

2. Sea Ice

3. Snow- observation types- operational Cressman analysis- revision based on satellite derived snow extent- analyses’ validation against independent satellite

and in-situ observations- impact on the forecast

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Sea Surface Temperature (SST) - AnalysisThe SST analysis is produced by NCEP / MMAB:- daily data set- two dimensional variational interpolation - buoy and ship observations, satellite retrieved SST

Analysis steps:1) Satellite retrieved SST values are averaged within 0.5º grid boxes2) Bias calculation and removal for satellite retrieved SST3) SST from ships and buoys are separately averaged4) The first guess is the prior analysis with one day’s climate adjustment added.5) Where fractional sea ice cover exceeds 50%, surface temperature is

calculated from Millero’s formula for the freezing point of water:

with s the salinity in psu.6) Empirical autocorrelation function has the form:

with d and l in km, grad T K/km

22

3

0002.00017.00575.0)( ssssSST

)/exp( 22 ld

))100,/25.2max(,450min( gradTl

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MMAB SST Data

80°S80°S

70°S 70°S

60°S60°S

50°S 50°S

40°S40°S

30°S 30°S

20°S20°S

10°S 10°S

0°0°

10°N 10°N

20°N20°N

30°N 30°N

40°N40°N

50°N 50°N

60°N60°N

70°N 70°N

80°N80°N

160°W

160°W 140°W

140°W 120°W

120°W 100°W

100°W 80°W

80°W 60°W

60°W 40°W

40°W 20°W

20°W 0°

0° 20°E

20°E 40°E

40°E 60°E

60°E 80°E

80°E 100°E

100°E 120°E

120°E 140°E

140°E 160°E

160°E

ECMWF Analysis VT:Thursday 1 January 2004 12UTC Surface:

270

275

280

285

290

295

300

305

310

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SST – OSTIA Data Sets

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OSTIA-NCEP

[K]

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Lake SST - Data

22 non analysed lakes at T319 resolution, Great Lakes and Caspian Seaare included in the NCEP analysis

Current analysis method was developed using:

• 18,000 observations of mean monthly surface air temperature compiled by Legates and Wilmott (1990)

• ERA15 monthly mean SST based on satellite and in-situ observations (NCEP data set) for the Great Lakes and the Caspian Sea

• Lake temperatures for 4 African Lakes from Spigel and Coulter (1996)

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Lake SST - Methodology

SST Lake(t) = T2m(t-1)

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Sea Ice – ‘Analysis’

Based on SSM/I (Special Sensor microwave / Imager) antenna temperatures.

1. Remapping from scan points to a polar stereographic grid (25km true at 60)2. Conversion to brightness temperatures (Hollinger et al., 1987).3. Weather filter following Gloersen and Cavalieri (1986).4. Sea ice concentration algorithm (Cavalieri et al., 1991).5. Polar gap filling.6. Quality check (100 % maximum ice cover).7. Final filtering based on Reynolds SST (no ice if SST > 2º C).

NCEP’s algorithm (Grumbine, 1996):

ECMWF post-processing:

1. Resampling to model grid using a spatial interpolation (Cressman Analysis).

2. Final quality check.3. Replace sea ice in the Baltic Sea with the high resolution

product from SMHI.

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Sea Ice - AlgorithmSea ice fraction algorithm (Cavalieri et al., 1991)

ocean tie point

multi year sea ice tie point

first year sea ice tie pointSSM/I

channelopenwater

first year sea ice

multi-year sea

ice

19 H 100.8 242.8 203.9

19 V 177.1 258.2 223.2

37 V 201.7 252.8 186.3

2. Northern Hemisphere tie points

HVVV

HVHV

TTTTGR

TTTTPR

37371937

19191919

/

/

1. Calculate polarization ratio &

spectral gradient ratio

MFT

M

F

CCC

GRPRcGRcPRccD

DGRPRbGRbPRbbC

DGRPRaGRaPRaaC

3210

3210

3210

/

/3. Calculate fractional sea ice coverage

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(hhtp://polar.wwb.noaa.gov/seaice)

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Sea Ice – Baltic Sea

Mean sea ice concentration for the period 5-24 January 2004:a) NCEP / ECMWF (CTRL) and b) SMHI / ECMWF (EXP)

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Sea Ice – Baltic Seasensible heat flux latent heat flux

CTRL

EXP - CTRL

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Sea Ice – Baltic Sea

GP1: thin lines, GP2: thick linesCTRL: solid, EXP: dashed grey

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Snow Analysis - Definitions

Definitions - snow extent (binary information 1/0)- fractional snow cover (0 – 100 %) - snow depth SD (m)

- snow water equivalent (SWE)

Observation types - in situ measurements (snow depth and SWE) - remote sensing microwaves (SWE)

- remote sensing visible & infrared (snow extent, aggregation gives fractional snow coverage)

1000SSD

SWE

[m]

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Cressman Analysis (I)

N

n

n

N

n

bOnn

ba

w

SSwSS

1

1

'

1. Cressman spatial interpolation:

with: - SO snow depth from synop reports, - Sb background field estimated from the short-range forecast of snow water equivalent,- Sb‘ background field at observation location, and - wn weight function, which is a function of horizontal distance r and vertical displacement h (model – obs): w = H(r) v(h) with:

,0rr

rrmaxH(r)

22max

22max

2h2maxh

2h2maxh

1 if 0 < h

0 if h < - hmax

if – hmax < h < 0v(h) =

rmax = 250 km

hmax = 300 m

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Cressman Analysis (II)

2. Quality check for every grid point

3. Final analysis using climatological values

cliaa SSS 1(

with: - Scli snow depth from climate data set (Foster and Davy 1988), - relaxation coefficient of 0.02

- If Tb2m < 8 C only snow depth observations below 140 cm are accepted.

- If Tb2m > 8 C only snow depth observations below 70 cm are accepted.

- Observations which differ by more than 50 cm from the background are rejected.

- When only one observation is available within rmax, the snow depth increments are set to 0.

- Snow-depth analysis is limited to 140 cm.

- Snow-depth increments are set to 0 when larger than (160-16Tb2m) mm, where Tb

sm is in C.

- Snow-depth analysis is set to 0 if below 0.04 cm- If there is no snow in the background and in more than half of the observations within a

circle of radius rmax, the snow depth increment is kept to 0.

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Analyses vs Satellite Data

MODIS snow extent 17.-24.1.2002

by NSIDCby NSIDC

MODIS vis image 27.10.2002

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Analyses vs Satellite Data

MODIS 16/02/2002

SWE [cm]

operational analysis

40°N

50°N

60°N

70°N

20°W

20°W

0°

0°

20°E

20°E 40°E

40°E

60°E

60°E

ECMWF Analysis VT:Saturday 16 February 2002 12UTC Surface: snow depth

0.1

0.5

1

2

5

10

20

40

75

125

200

10000

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NOAA / NESDIS Snow Extent

Interactive Multisensor Snow and Ice Mapping System:- time sequenced imagery from geostationary satellites,- AVHRR, - SSM/I, - station data, - previous day‘s analysis

Northern Hemisphere product- real time- polar stereographic projection- 1024 × 1024 elements

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Revision of the Global Snow Depth Analysis using NESDIS snow extent

1) Comparison between first guess and NESDIS: - NESDIS is interpolated to actual model resolution

- fractional snow cover is calculated - snow free f.g. boxes are updated with 10 cm of snow where the NESDIS product has 100% snow cover

2) Cressman Analysis - NESDIS snow free grid boxes are used as observations with

0 cm snow depth. - Observation height is calculated from high resolution ‚ECMWF‘

orography on the corresponding polarstereographic grid. - Climatology is switched off.

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Technical implementation

NOAA NESDIS snow extent: snow present

NOAA NESDIS snow extent: no snow

first guess updated with previous increments

00 UTC 12 UTC

6 hour forecast(first guess)

12 hour forecast(first guess)

SYNOP observations SYNOP observations

06 UTC

Cressman analysis /quality check

(& climatology)

Cressman analysis /quality check

(& climatology)

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6-h cycling in 12 hour 4DVarSWE [cm]

SWE [cm]

SWE [cm]

SWE [cm]

00 UTC 06 UTC

18 UTC12 UTC

first guess:12 hour fc

first guess:6 hour fcobservations

first guess:12 hour fc &update with previous analysisincrements &satellite data

first guess:6 hour fc

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Snow Depth Analyses for 1/3/2002

SWE [cm]

SWE [cm]

NESDIS Snow Cover [%]

MODIS

operational

revised

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Validation and intercomparison

Research Experiments• November 2003 to May 2004 (Cycle 28R1)• March, May and December 2002 (Cycle 26R3)• Satellite Data ingestion at 12:00 UTC / CTRL

National Operational Hydrologic Remote Sensing CenterAnalysis (SNODAS) • November 2003 to May 2004• 1km, re-sampled to T511 reduced Gaussian grid

MODIS snow extent• March, May, and December 2002• 0.05 deg CMG, re-sampled to 0.5 deg

Canadian Met Service daily observations• March, May, December 2002• Heidke Skill Score (2 class contingency table: snow / no snow)

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MODIS ComparisonMarch 2002 May 2002

operational

revised

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Snow Depth Analyses for 2/12/2002

NWS National Operational Hydrologic Remote Sensing Center

Operational Revised

NESDIS

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SNODAS snow extent

01/11/03 01/12/03 01/01/04 01/02/040.0

0.2

0.4

0.6

0.8

1.0

snow

ext

ent

US

CTRLEXPSNODAS

01/11/03 01/12/03 01/01/04 01/02/040.0

0.2

0.4

0.6

0.8

1.0

snow

ext

ent

West

01/11/03 01/12/03 01/01/04 01/02/040.0

0.2

0.4

0.6

0.8

1.0

snow

ext

ent

Central

01/11/03 01/12/03 01/01/04 01/02/040.0

0.2

0.4

0.6

0.8

1.0

snow

ext

ent

East

(-124° W to -105° W)

(-80° W to -60° W)(-105° W to -80° W)

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Impact on the forecast

0 1 2 3 4 5 6 7 8 9 10

Forecast Day

40

50

60

70

80

90

100%

DATE1=20031107/... DATE2=20031107/...

AREA=N.HEM TIME=12 MEAN OVER 144 CASES

ANOMALY CORRELATION FORECAST

500 hPa GEOPOTENTIAL

FORECAST VERIFICATION

CNTL

EICE

MAGICS 6.9 metis - dar Thu Oct 21 16:10:30 2004 Verify SCOCOM

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Fractional snow coverage

SWE [mm]

Fra

ctio

nal s

now

cov

er

SWE [mm]

Fra

ctio

nal s

now

cov

erSNODASat T511

30/11/03 31/1/04

Sellers et al. 1996: SiB2Marshall et al. 1994: CCM2 (NCAR)Yang et al. 1997

z0 : 2 cm; ρ = 300 kg m-3

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Problems and Limitations …

100

100 100

100

100

100

100

200

200

200

200

200

200

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1

0.1 0.1

0.1

0.1

2

2

2

2 2

2

22

10

10

10

10

10

10

25

25

25

25

25

50

50

5050

50

100

100

100

100

100

46°N

48°N

6°E

6°E

8°E

8°E

10°E

10°E

12°E

12°E

14°E

14°E 16°E16°E

00

0

0

00

00

0 0

0

0

0

0

0

0

0

0

0

0

0

00

0

0

0

0

0 0

0

0

0

0

0 0

0

00

0

0

0

0

0

0

00

33

59

81

79

230

310199

285

395

FC field from 2007040712, t + 42 VT: 2007040906 [ cm ]Observations from 2007040900 to 2007040909 [ cm ]

snow depth verification

2 - 10 cm 10 - 25 cm 25 - 50 cm 50 - 160.82 cm

MAGICS 6.11 bee06 - moa Tue Apr 10 05:02:54 2007

285

230395

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Problems and Limitations …

40°N 40°N

50°N50°N

20°E

20°E

0.1

0.5

1

2.5

5

10

25

50

100

250

500

40°N 40°N

50°N50°N

20°E

20°E

0.1

0.5

1

2.5

5

10

25

50

100

250

500

40°N 40°N

50°N50°N

20°E

20°E

0.001

0.1

0.5

1

2.5

5

10

20

30

40

40°N 40°N

50°N50°N

20°E

20°E

0.001

0.1

0.5

1

2.5

5

10

20

30

40

ERA Interim T255 (May 1991)ERA 40 T159 (May 1990-2000)

Operations scaled to T159 (May 2006)Operations T799 (May 2006)