update on ecmwf forecast performance · 2016. 6. 7. · october 29, 2014 summary 33 • upper-air...
TRANSCRIPT
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© ECMWF October 12, 2015
Update on ECMWF forecast performance
Thomas Haiden, Martin Janousek
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October 29, 2014
Contents
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• Upper-air performance
• Surface parameters
• Model upgrade 2016 (cycle 41r2)
• High-impact weather
• Scale-dependence of skill
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October 29, 2014
Upper-air forecast skill
3
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Upper-air forecast skill
4
ERA-Interim
HRES
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October 29, 2014
Upper-air forecast skill
5
HRES - ERA-Interim
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Model intercomparison
6
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Forecast skill: vertical correlation
7
Geer (2015)
← 500 hPa height
850 hPa temperature →
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Upper-air ensemble forecast skill
8
𝐶𝑅𝑃𝑆𝑆 = 1 −𝐶𝑅𝑃𝑆𝐸𝑁𝑆𝐶𝑅𝑃𝑆𝐶𝐿𝐼𝑀
60%
40%
25%
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Upper-air ensemble forecast skill
9
CRPS
D+4
D+6
D+8
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Wave forecast: verification against buoys
10
Wave height Wind speed
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Wave height – model intercomparison
11
DJF 2015-16
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10 m wind speed
12
SDEV
BIAS
D+3
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2 m temperature
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SDEV
BIAS
D+3
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2 m temperature bias at 00 UTC (DJF)
14
Winter 2014-15 Winter 2015-16
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Precipitation
15
Simbach, Germany, 2 June 2016
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Performance during individual events
16
Large-scale events that actually happened
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Headline score for HRES precipitation: SEEPS
17
Skill in discriminating
between
• Dry
• Light
• Moderate-to-
heavy
Adapted to local
climatology
HRES
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HRES precipitation
18
Skill in discriminating
between
• Dry
• Light
• Moderate-to-
heavy
Adapted to local
climatology
ERA-Interim
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HRES precipitation
19
Skill in discriminating
between
• Dry
• Light
• Moderate-to-
heavy
Adapted to local
climatology
DIFFERENCE
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HRES precipitation – other centres
20
Skill (ETS)
Frequency
bias
D+5
Extra-tropics
Thr=10mm/24h
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ENS precipitation
21
CRPSS=10%
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ENS precipitation – other centres
22
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Model upgrade in March 2016 (Cycle 41r2)
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Nhem Shem Tropics Europe N-Atl N-Amer N-Pac E-Asia Aust/NZ Arctic Antarctic
Upper-air: improvements 2-3%
Surface: up to 5% in the medium range
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Improvements in surface parameters
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uniform resolution
HRES 10 m wind speed ENS 2 m temperature
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High-impact weather
25
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Monitoring of forecast skill for extremesTropical cyclones
2m temperature 10m wind speed
24-h precipitation
Extreme forecast index (EFI), D+4
D+3
D+5
Position
Intensity
Speed
Position
spread/error
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Heavy precipitation
ECMWF Newsletter 144 (Summer 2015)
Largest gains in skill at days 4-7
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EFI for severe convection (CAPE, CAPESHEAR)
28
Verification against severe weather reports
(tornadoes, large hail, severe wind gusts)
Summer 2015, United States
65%
35%
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29
Forecast skill horizon (schematic)
ECMWF Newsletter No. 145 (2015)
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30
Forecast skill horizon: 500 hPa geopotential
Buizza and Leutbecher (2015)
Temporal averaging →
Spatial
averaging
↓
T120 T30
T7
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Precipitation verification against gridded data (NEXRAD)
31
Frequency bias (Oct 2014 – April 2015) Fractions skill score FSS (April - Aug 2014)
16km16km
…1 2 n
i
j
Forecast Fn=5/25
Observed On=3/25
MSEn = (Fn-On)2
FSS concept
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32
Total cloud cover forecast skill
ECMWF Newsletter No. 143 (2015)
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Summary
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• Upper-air performance continues to increase
• ECMWF maintains overall lead among global centres
• Challenge of 2 m temperature biases
• Significant improvements from Cycle 41r2
• Increased focus on verification of high-impact weather
• Forecast skill horizon: scale-dependent predictability
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34
Deadline: 31 October 2016
Price: Invited keynote and paid attendance at the
7th International Verification Methods Workshop in
May 2017 (Berlin, Germany)
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Model intercomparison DJF
35
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Potential economic value of extreme wind forecasts
36
moderately
strong
extreme
extreme and
large-scale
see also ECMWF Newsletter No. 139 (2014)
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EFI for severe convection (CAPE, CAPESHEAR)
37
Verification against severe weather reports
(tornadoes, large hail, severe wind gusts)
Summer 2015, United States
65%
35%
I. Tsonevsky (2016)