Eidgenssisches Departement des Innern EDI Bundesamt fr Meteorologie

Eidgenössisches Departement des Innern EDI Bundesamt für Meteorologie und Klimatologie Meteo. Schweiz Automatic weather classification at Meteo. Swiss Tanja Weusthoff / Pierre Eckert COSMO GM 05. 09. 2011

“A weather situation represents the state of the atmosphere over a certain region and at a certain time. The weather situation determines the local weather elements of the day. ” (to a certain extent, personal note) W SE L Mean distributions of pressure, precipitation and temperature anomaly for the given weather class and for the time range 1958 – 2001. Automatic weather classifications| COSMO GM 2011 Tanja Weusthoff / Pierre Eckert 2

New (automatic) weather classifications The old manual weather classifications are replaced with new automated weather classifications. Ma til nu 31 al, . 12. 20 10 Alpenwetterstatistik AWS Perret un Zala-Klassifikation Automatic weather classifications| COSMO GM 2011 Tanja Weusthoff / Pierre Eckert Sin a ce uto Ca Ja ma t n un lcula uar ed y til t 01 ed b 201. 09 ac 1, . 19 k 57 NEW OLD GWT & CAP/PCACA 3

• “Harmonisation and Applications of Weather Type Classifications for European regions“ (2005 -2010) • Among others 1. Catalogue of computed classifications cost 733 cat-1 original classifications of the various authors cost 733 cat-2. 0 classifications recalculated with the cost 733 class software 2. Software for computation of own classifications cost 733 class (still under development) http: //geo 21. geo. uni-augsburg. de/cost 733 wiki Automatic weather classifications| COSMO GM 2011 Tanja Weusthoff / Pierre Eckert 4

1. Neue (automatisierte) Wetterlagenklassifikationen COST 733@MCH Classes chosen at MCH: • GWT (10, 18, 26 classes) • Weather classes are predefined according to fixed rules and threshold (Quasi-objective). • Explains precipitations rather well, except GWT 10. • Explains also other parameters (SLP, 2 m. T) not badly in the alpine region. • PCACAC (9, 18, 27 classes) neu: CAP • Weather classes are derived following a optimisation procedure. • Explains precipitation fluctuations best in the alpine region. Already good with 9 classes, except in summer. • Explains also other parameters (SLP, 2 m. T) not badly in the alpine region • PCACAC 18: In summer, 2/3 of the days come from 4 classes. Automatic weather classifications| COSMO GM 2011 Tanja Weusthoff / Pierre Eckert 5

1. Neue (automatisierte) Wetterlagenklassifikationen Methods 10 classifications are computed every day, based on two different kind of methods: 1. CAP = Cluster Analysis of Principal Component STEP 1: Derivation of weather classes by using principal component analysis and clustering on ERA 40 -data. STEP 2: Attribution of other days to these predefined classes. 2. GWT = Gross. Wetter. Types • Correlation with „Prototype“ patterns • Attribution to the predefined classes using correlations. • Wind directions, high and low pressure. 3. GWTWS = adapted GWT • Wind at 500 h. Pa for distinguishing convective / advective Automatic weather classifications| COSMO GM 2011 Tanja Weusthoff / Pierre Eckert 6

1. Neue (automatisierte) Wetterlagenklassifikationen Methods 10 classifications are computed every day, based on two different kind of methods 1. CAP = Cluster Analysis of Principal Component CAP 9, CAP 18 and CAP 27 based on MSLP 2. GWT = Gross. Wetter. Types GWT 10, GWT 18 and GWT 26 based on (1) MSLP and (2) Z 500 3. GWTWS = adapted GWTWS with 11 classes based on GWT 8 for Z 500, mean wind at 500 h. Pa and mean MSLP Automatic weather classifications| COSMO GM 2011 Tanja Weusthoff / Pierre Eckert 7

1. Neue (automatisierte) Wetterlagenklassifikationen Database • Classifications computed back using ECMWF reanalyses 01. 09. 1957 -31. 08. 2002 01. 09. 2002 -31. 12. 2010 ERA 40 ERA interim • For daily computation (since 01. 2011), use of the operational IFS 12 z run from ECMWF; Analysis and forecasts out to 10 days are classified • Domain: alpine region 41 N - 52 N (12 pts) 3 E - 20 E (18 pts) Automatic weather classifications| COSMO GM 2011 Tanja Weusthoff / Pierre Eckert 8

Operational aspects Daily computation at 9 pm IFSData Europe, 1° horizontal res. 12 UTC run Conversion to net. CDF (CDO) CLIMAP cost 733 class retrieve_dwh (Version 0. 31_07, Mai 2010) Output as ASCII file, 1 File per parameter Automatic weather classifications| COSMO GM 2011 Tanja Weusthoff / Pierre Eckert DWH Users 9

3. Auswertungen Trends in CAP 9 Year Winter Increase of cold, dry high pressure situations, mainly in Winter. Year Spring Decrease of warm, wet northeast situations, mainly in spring. Automatic weather classifications| COSMO GM 2011 Tanja Weusthoff / Pierre Eckert 10

• Verification (for the moment GWTWS) COSMO-7 minus Radar, for each class W SE L „Neighbourhood“ verification Automatic weather classifications| COSMO GM 2011 Tanja Weusthoff / Pierre Eckert 12

• COSMO-MOS (GWTWS) (postponed) Weather classes can be used as potential predictors for the statistical correction of NWP models. • Dust (PM 10) concentration (GWT 26_MSL) Usefulness of the GWT 26_MSL classification for predicting the concentration of dust (PM 10). Comparison with neural classification. Automatic weather classifications| COSMO GM 2011 Tanja Weusthoff / Pierre Eckert 13