Conditional verification of all COSMO countries: first results

Federal Department of Home Affairs FDHAFederal Office of Meteorology and Climatology MeteoSwiss

Conditional verification of all COSMO countries:

first results

COSMO General Meeting, September 2012, Lugano

by the members of WG Verification

2 Conditional Verification | COSMO-GM 2012, LuganoVanessa Stauch, [email protected]

Objectives of conditional verification

Contribute to COSMO model development

Improve the understanding of forecast errors

Identify possible sources of errors in COSMO

Contribute to guidelines on how to use COSMO forecasts


Feedback loop within COSMO


Common conditional verification results

T2M for overcast conditions T2M for clear sky conditions

Spring 2012, ME and RMSE for many COSMO modelsAutumn 2011, ME and RMSE for many COSMO models

RMSE

ME

• Cloud cover clearly stratifies the COSMO forecast error of T2M (no matter which diagnostic)

• Under observed clear sky conditions, the mean error has a pronounced daily cycle:

All models underestimate daytime T2M and overestimate nighttime T2M

• Under observed overcast conditions, this behaviour is not observed


Searching for clues…

• Additional stratification to look at cases with stable boundary layer → distinguish between dynamical and radiation dominated processes

COSMO-ME Conditional Verification T2m when observed TCC ≤ 25%

COSMO-ME Conditional Verification T2m when observed TCC ≤ 25% & wind speed ≤ 2 m/s

COSMO-7 Conditional Verification T2m when forecast TCC ≤ 25%

COSMO-7 Conditional Verification T2m when forecast TCC ≤ 25% & wind speed ≤ 2.5 m/s


Searching for clues…

• Additional stratification to look at cases with stable boundary layer → distinguish between dynamical and radiation dominated processes

→ in calm wind conditions, the underestimation of the daily temperature amplitude is even more pronounced→ overestimated thermal mixing (minimal diffusion coefficient?)

Nighttime overestimation from insufficient radiative cooling? Thermal conductivity of the soil?

Daytime underestimation from underestimated sensible heat flux? Impact of soil moisture?


T2M with fcst soil moisture condition

ME, RMSE dry conditions

ME, RMSE wet conditions

ME, RMSE no conditions

Similar systematic error properties as for cloud cover conditions, but phase slightly shifted and different data sample → new box opened…

WG5 COSMO General Meeting, Lugano 2012

Overestimation of preci amount for lower thresholds in high CAPE cases and ETS a bit

reduced

FBI

ETS

Unstable (CAPE>=50J/kg) Stable (CAPE<50J/kg)

Precipitation with CAPE conditions


Precipitation with CAPE conditions

FBI

ETS



Precipitation with CAPE

FBI

ETS


Higher performance (in terms of ETS, also POD) in stable conditions, but CAPE condition displaced

→ find appropriate time period, other condition


Conclusions

Conditional verification provides us with tools for analysing rather complex COSMO model errors

Use of intensive measurement sites (e.g. sensible and latent fluxes for clear sky temperature error, soil moisture for temperature and dewpoint error) and radiosoundings

Identify suitable stratifications for precipitation (e.g. appropriate time integrations for CAPE or convective time scale, so far no success with weather classes)

Tight interaction with WG3 and others

CAPE>50

CAPE<50

Very high POD values for unstable conditions, FAR not

so differentWG5 COSMO General Meeting, Lugano 2012

2mT, Td with dry or wet soil conditions

WG5 COSMO General Meeting, Lugano 2012

W_SO Water content of first soil layer(kg/m2) 1cm.

Td: Higher error in dry soil and larger underestimation2mT: Higher error in wet soil and larger understimation

Winter SpringFall

Winter SpringFall


TD2M with soil moisture condition

ME, RMSE dry conditions

ME, RMSE wet conditions

ME, RMSE no conditions


FF10M with grid point height

ME, RMSE all stations

ME, RMSE gp height > 800m

ME, RMSE gp height < 800m


FF10M scatter plot

Winter 2012

Conditional verification of all COSMO countries: first results

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