1. Predictability of 2-m temperature
Thomas Haiden, Zied Ben Bouallegue, Martin Leutbecher, Martin Janousek
European Centre for Medium-Range Weather Forecasts
Reference period is
(March 2017 anomalies)

2. 2-m temperature error growth: DJF 2016-17
RMSE
against SYNOP
NH Extratropics, 12 UTC

3. 2-m temperature error growth: DJF 2016-17
RMSE
against SYNOP
against analysis
NH Extratropics, 12 UTC

4. 2-m temperature error growth: DJF 2016-17
MSE
against SYNOP
against analysis
(2.8 K)2
NH Extratropics, 12 UTC

5. 2-m temperature error growth: DJF 2016-17
MSE
against SYNOP
against analysis
T850
NH Extratropics, 12 UTC

6. 2-m temperature error growth: DJF 2016-17
MSE
against SYNOP
against analysis
diurnal mean
T850
NH Extratropics, 12 UTC

7. Regional variations
RMSE

8. Regional variations
RMSE
Stations excluded where ∆z>150m

9. Regional variations
SDEV

10. Europe
SDEV

11. Estimating representativeness mismatch
Error averaged over 1-deg boxes
SDEV

12. Estimating representativeness mismatch
Error of up-scaled forecast and obs
SDEV

13. Estimating representativeness mismatch
SDEV difference
Ranging from 0.5 to 2.0 K
Average value ~1 K (consistent with other studies)
Short-range forecast error ~2 K

14. T2m forecast skill evolution (ENS)
Horizontal resolution upgrades
CRPS
P(CRPS > 5 K)
All errors
Percentage of large errors
CRPS decreased by ~10%
Frequency of large errors decreased by ~20%

15. Upscaling to ~400 km (4 deg) Day 5 SDEV 12 UTC
Small difference → larger scale issue
Problem: strong surface inversions over snow

16. Large difference → smaller scale issue
Upscaling to ~400 km (4 deg)
Day 5
SDEV
12 UTC
Large difference → smaller scale issue
Problem: low stratus boundaries and persistence

17. TIGGE: forecasts from different centres
Day 5
SDEV
12 UTC
ECMWF
JMA
NCEP
UKMO

18. Predictability of period means
3-day mean
5-day mean
instantaneous
NH Extratropics, 12 UTC, RMSE skill

19. Probabilistic T2m skill: weeks 2 to 4
Based on temperature anomalies (terciles)
Week 2
Week 3
Week 4
Vitart (2014)

20. Forecast skill horizon and large-scale predictability
Temporal averaging →
T120
Spatial averaging ↓
T30
Buizza and Leutbecher (2015) T7
Skill beyond week 4 in predicting weekly averages of large-scale 850 hPa temperature anomalies

21. T2m forecast skill - summary
Day 1-4
Day 5-10
Day 11-15
Week 3 and 4
Useful for 5-day or weekly means
Marginal for weekly means
Forecast skill:
High
Useful
Mainly representativeness
Predictability and representativeness
Mainly atmospheric predictability
Earth-system predictability
Limited by:
Improve:
Model resolution
Stable boundary-layer vertical mixing
Low cloudiness (especially inversion-capped stratus)
Soil moisture
Representation of surface characteristics