Long-term trends of precipitation verification results for GME, COSMO-EU and COSMO-DE

Deutscher Wetterdienst

Long-term trends of precipitation verification results for GME, COSMO-EU and

COSMO-DE Ulrich Damrath

Long-term Trends of Precipitation Verification Results for COSMO-EU: Ulrich Damrath COSMO GM 2010 @ Moscow

Overview

Verification using „Fuzzy“ methods

Example for the FSS and he upscaling HSS for January and July

Time series for special thresholds and window sizes

Consisency of precipitation forecasts using the CRA method (update)

current state


Fuzzy verification January 2008: Accumulated frequency distribution of precipitation, observation and GME


Fuzzy verification January 2008: Accumulated frequency distribution of precipitation, observation and CEU


Fuzzy verification January 2008: Accumulated frequency distribution of precipitation, observation and CDE


Fuzzy verification January 2008: FSS

Monthly average of precipitation: 68 mm





Fuzzy verification January 2010:Frequency distribution of precipitationObservation, GME, CEU and CDE





Accumulated frequency distribution of precipitation

July 2007 (Observation and GME)



July 2007 (Observation and CEU)



July 2007 (Observation and CDE)


Fuzzy verification July 2007: FSS









Fuzzy verification July 2010:Frequency distribution of precipitationObservation, GME, CEU and CDE





Fuzzy verification January 2008: HSS(UPS)






Fuzzy verification January 2010:Frequency distribution of precipitationObservation, GME, CEU and CDE





Fuzzy verification July 2007: HSS(UPS)









Fuzzy verification July 2010:Frequency distribution of precipitationObservation, GME, CEU and CDE





Fuzzy verification: Time series, choice of windows and thresholds


Fuzzy verification: Time series, ETS UPS GME VV:06-30


Fuzzy verification: Time series, ETS UPS CEU VV:06-30


Fuzzy verification: Time series, ETS UPS GME VV:06-18


Fuzzy verification: Time series, ETS UPS CEU VV:06-18


Fuzzy verification: Time series, ETS UPS CDE VV:06-18


Fuzzy verification: Time series, FSS GME VV:06-30


Fuzzy verification: Time series, FSS CEU VV:06-30


Fuzzy verification: Time series, FSS GME VV:06-18


Fuzzy verification: Time series, FSS CEU VV:06-18


Fuzzy verification: Time series, FSS CDE VV:06-18

Entity-based QPF verification (rain “blobs”) by E. Ebert (BOM Melbourne)Verify the properties of the forecast rain system against the properties of

the observed rain system:

• location• rain area• rain intensity

(mean, maximum)

Observed Forecast

CRA error decompositionThe total mean squared error (MSE) can be written as:

MSEtotal = MSEdisplacement + MSEvolume + MSEpattern

Configuration for the current study:

- “Observations”: forecasts: 06-30 hours

- Forecasts : forecasts: 30-54 hours and

forecasts: 54-78 hours


Consistency of precipitation forecasts: Parts of error decomposition Autumn 2009

Dark :forecasts 30-54 hLight:forecasts 54-78 h


Consistency of precipitation forecasts: Parts of error decomposition Winter 2009/10



Consistency of precipitation forecasts: Parts of error decomposition Spring 2010



Consistency of precipitation forecasts: Parts of error decomposition Summer 2010



Consistency of precipitation forecasts: Parts of error decomposition Summer 2010



Summary

Fraction skill score and upscaling ETS are considered. Both scores are relatively high correlated.

Fuzzy verification in general shows best results for low precipitation values and large window sizes

For some months best results can be seen for precipitation amounts around 2 mm (12 h)-1

CEU and CDE models have nearly the same quality and are better than GME especially during summer times.

A positive long term trend of precipitation quality can be seen for low precipitation values and large window sizes. No clear trend is visible for high precipitation values for any window size.

Results for the check of consistency of precipitation forecasts lead to the expected (but proved) results that for high thresholds the inconsistency is most obvious. During winter time pattern errors are dominant. During summer times displacement errors are prevailing.


One conclusion

Forecasters sometimes really like CDE.

But the future is CDE-EPS!

Documents

Long-term trends of precipitation verification results for GME, COSMO-EU and COSMO-DE