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

Postprocessing of temperature and wind for COSMO-7 and COSMO-2

Vanessa Stauch

Offenbach, September 2009

COSMO General Meeting

2 Statistical PP | COSMO-GM 2009Vanessa Stauch

calibration with Kalman Filter

>> recursive estimation of forecast error (prediction – correction)

>> requires online observations

>> can be used quasi-instantaneously (no large historical database)

>> cannot predict fast changes (assumption of persistent error)

>> suitable for a subset of parameters (normally distributed errors)

3 Statistical PP | COSMO-GM 2009Vanessa Stauch

calibration with Kalman Filter

it

it

it xx 1

Tt

DMOttt

Tt Txxerr 21

itit QN ,0~

tTt RN ,0~error model:

states evolution:

prediction:Tt

DMOttt

Tt Txxerr 11

21

111

with

with

error : tDMOt

Tt OBSTerr

^

^

4 Statistical PP | COSMO-GM 2009Vanessa Stauch

COSMO models

COSMO-7

COSMO-LEPS

COSMO-2

COSMO-LEPS

10km, +132 hours

COSMO-7

6.6km, +72 hours

COSMO-2

2.2km, +24 hours

5 Statistical PP | COSMO-GM 2009Vanessa Stauch

Kalman Filter @ MeteoSwiss

operational:

T2m, TD2m

for

COSMO-LEPS mean

COSMO-7

COSMO-2

IFS

in preparation:

FF10m, TW2m, RH2m

for

COSMO-LEPS mean

COSMO-7

COSMO-2

IFS

6 Statistical PP | COSMO-GM 2009Vanessa Stauch

Swiss met. measurement network

62 stations

7 Statistical PP | COSMO-GM 2009Vanessa Stauch

T2m predictions

COSMO-7

COSMO-2COSMO-2

KFC7

COSMO-7

KFC2

COSMO-7COSMO-7

performance?

8 Statistical PP | COSMO-GM 2009Vanessa Stauch

benefit COSMO-2 vs COSMO-7?

04.04.08 – 31.10.08 RMSE RMSE

All ANETZ stations 11.0 % 4.0 %

Low ANETZ stations8.8 % 5.2 %

High ANETZ stations 13.0 % 3.2 %

04.04.08 – 31.10.08 STD STD

All ANETZ stations 12.3 % 4.0 %

Low ANETZ stations12.7 % 5.2 %

High ANETZ stations 12.6 % 3.2 %

C2 vs C7 C2-KF vs C7-KF

=

9 Statistical PP | COSMO-GM 2009Vanessa Stauch

benefit COSMO-2 vs COSMO-7-KF??

04.04.08 – 31.10.08 RMSE

C2-DMO vs C7-KF

STD

C2-DMO vs C7-KF

All ANETZ stations-25 % -20 %

Low ANETZ stations -22 % -12 %

High ANETZ stations -27 % -20 %

10 Statistical PP | COSMO-GM 2009Vanessa Stauch

Chasseral (CHA)

Evionnaz (EVI)

Gütsch (GUE)

Piz Martegnas (PMA)

Schaffhausen (SHA)

Oron (ORO)

Üetliberg (UEB)

stations for wind speed calibration

SMN station

WKA

11 Statistical PP | COSMO-GM 2009Vanessa Stauch

Station CHA EVI GUE ORO PMA SHA UEB WiCol WiFel WiGue WiCro

Höhe (obs) 1599 480 2287 830 2670 437 1043 450 1020 2331 1230

cosmo7 WiCro WiCol WiGue ORO PMA SHA UEB WiCol WiFel WiGue WiCro

Höhe (mod) 1088 1024 2322 811 2334 432 541 1024 1013 2322 1088

deltaheight_7 (mod-obs) -511 544 35 -19 -336 -4.8 -502 574 -6.8 -8.8 -142

cosmo2 CHA EVI WiGue ORO PMA SHA UEB WiCol WiFel WiGue WiCro

Höhe (mod) 1293 746 2298 805 2520 477 604 796 941 2298 1114

deltaheight_2 (mod-obs) -306 266 11 -25 -150 40 -439 346 -79 -33 -116

CHA/WiCro

EVI/WiCol

WiGue

PMA

SHA

UEB

ORO WiFel

height differences

12 Statistical PP | COSMO-GM 2009Vanessa Stauch

represenativeness of met. station

model prediction representative for (mean) grid box

local point observation (specific conditions)

wind turbine Gütsch

13 Statistical PP | COSMO-GM 2009Vanessa Stauch

COSMO-7 vs COSMO-2

COSMO-7

COSMO-2 (03)

Chasseral (CHA)

56 > 44

Evionnaz (EVI)

90 < 99

Gütsch (GUE) 55 > 45

Oron (ORO) 53 < 59

Piz Martegnas (PMA)

51 > 45

Schaffhausen (SHA)

54 > 52

Uetliberg (UEB)

76 > 69

rRMSE (%) für 1-24h, period 01.09.08 – 31.03.09

CHA

EVI

GUE

PMA

SHA

ORO

UEB

14 Statistical PP | COSMO-GM 2009Vanessa Stauch

effect on MOS-postprocessing

COSMO-7

MOS

COSMO-2 (03) MOS

Chasseral (CHA)

34 > 32

Evionnaz (EVI)

78 > 77

Gütsch (GUE) 45 > 39

Oron (ORO) 59 > 47

Piz Martegnas (PMA)

69 > 42

Schaffhausen (SHA)

85 > 77

Uetliberg (UEB)

59 > 54

rRMSE (%) für 1-24h, period 01.09.08 – 31.03.09

CHA

EVI

GUE

PMA

SHA

ORO

UEB

15 Statistical PP | COSMO-GM 2009Vanessa Stauch

effect on KF-postprocessing

COSMO-7 KF

COSMO-2 (03) KF

Chasseral (CHA)

33 = 33

Evionnaz (EVI)

77 < 83

Gütsch (GUE) 47 > 43

Oron (ORO) 52 > 50

Piz Martegnas (PMA)

48 > 43

Schaffhausen (SHA)

44 = 44

Uetliberg (UEB)

57 > 56

rRMSE (%) für 1-24h, Zeitraum 01.09.08 – 31.03.09

CHA

EVI

GUE

PMA

SHA

ORO

UEB

16 Statistical PP | COSMO-GM 2009Vanessa Stauch

summary

>> statistical postprocessing profits from a better NWP input model

>> „dynamical downscaling“ does not replace statistical adaptation to local

observations (in particular if results being verified against those)