ECMWF snow data assimilation: Use of snow cover products and In situ snow depth data for NWP

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1 snow data assimilation: Use of snow cover products and In situ snow depth data for NWP Patricia de Rosnay Thanks to: Ioannis Mallas, Gianpaolo Balsamo, Philippe Lopez, Anne Fouilloux, Mohamed Dahoui, Lars Isaksen, Erik Andersson and Jean-Noël Thépaut GCW Snow Watch Workshop, Toronto, January 2013 Slide 1

2 Land Surface Analysis Operational NWP Objective of high quality surface and near surface weather products Land Surface Model: H-TESSEL (Balsamo et al., J. Hydromet. 2009) Land Surface Data Assimilation (de Rosnay et al. Survey Geophysics 2012) - Snow depth analysis New 2D Optimal Interpolation (OI) (operational) Ground data (SYNOP and other NRT data) High resolution NESDIS/IMS snow cover data (de Rosnay et al., Surv. Geophys., 2012) ASCAT - Soil Moisture analysis Simplified Extended Kalman Filter (EKF) de Rosnay et al. QJRMS (2012) SMOS NESDIS/IMS snow cover (16 Jan. 2012) January 2010 METOP-A/B ASCAT de Rosnay et al., QJRMS 2012 SMOS Sabater et al., TGRSL 2011 Validation: Albergel et al. RSE 2012, and JHM 2012 GCW Snow Watch Workshop, Toronto, January 2013 Slide 2

3 Snow Analysis Snow Model variables: - Snow depth S (m) - Snow water equivalent SWE (m), ie snow mass - Snow Density ρ s, between 100 and 400 kg/m 3 SWE = S. ρs 1000 [m] Observations types used: - Conventional snow depth data: SYNOP and National networks Prognostic variables 16km resol (T1279) - Snow cover extent: NOAA/NESDIS IMS daily product GCW Snow Watch Workshop, Toronto, January 2013 Slide 3

4 NOAA/NESDIS IMS Snow extent data Interactive Multisensor Snow and Ice Mapping System - Time sequenced imagery from geostationary satellites - AVHRR, - SSM/I - Station data Northern Hemisphere product - Daily, no time stamp - Polar stereographic projection Information content: Snow/Snow free Data used at : - 24km product in Grib (used for ) - 4 km product in Ascii Revised pre processing (used from Nov 2010) More information at: GCW Snow Watch Workshop, Toronto, January 2013 Slide 4

5 IMS data Pre-Processing at Altitude of the observation needed for data assimilation Conversion to BUFR, and add land-sea mask, and orography interpolated from the T3999 (5km) model orograpghy on the IMS 4km grid (use T799, ie 25 km orography for the 24km IMS product) Orography (m) included in the BUFR used in the snow analysis GCW Snow Watch Workshop, Toronto, January 2013 Slide 5

6 NESDIS/IMS 24km vs 4km product IMS Products after pre-processing at - Coast mask applied in the 24km product (lack of geoloc information in the grib product) - Data thinning (1/36) of the 4km product -> same data quantity, improved quality 4km product provides more local information than 24km product consistent with the way IMS is used in the data assimilation system GCW Snow Watch Workshop, Toronto, January 2013 Slide 6

7 Use of SYNOP and National Network data TAC 2010: Member States requested to improve availability of Snow depth data SYNOP at 06 UTC National snow data GCW Snow Watch Workshop, Toronto, January 2013 Slide 7

8 Use of SYNOP and National Network data TAC 2010: Member States requested to improve availability of Snow depth data - Dec 2010: New data from Sweden on the GTS (more than 300 stations) - New BUFR template from - update of acquisition and DA to use additional snow data: March Status today: GTS: Sweden, Romania, The Netherlands, Denmark, Finland FTP: Hungary SYNOP at 06 UTC National snow data GCW Snow Watch Workshop, Toronto, January 2013 Slide 8

9 Use of SYNOP data -Not much SYNOP reports in North America, particularly in the US - Would be valuable to have more snow depth data on the GTS GCW Snow Watch Workshop, Toronto, January 2013 Slide 9

10 Snow Analysis at Pre-Processing: - SYNOP reports converted into BUFR files. - IMS converted to BUFR (and orography added) - SYNOP BUFR data is put into the ODB (Observation Data Base) Snow depth analysis in two steps: (Drusch et al., J. Appl. Meteo. 2004) 1- NESDIS IMS data (once per day): - IMS snow free used as a SYNOP snow free data - IMS has snow & First Guess snow free put 0.1m snow in First Guess 2- Snow depth analysis at 00, 06, 12, 18 UTC : - Cressman interpolation: Operations: Still used in ERA-Interim - Optimal Interpolation (OI): Operational since November 2010 (de Rosnay et al; SG 2012) GCW Snow Watch Workshop, Toronto, January 2013 Slide 10

11 Validation data: NWS/COOP - NWS Cooperative Observer Program - Independent data relevant for validation - Used to validate a set of numerical experiments considering different assimilation approaches and IMS snow cover Numerical Experiments Bias (cm) R RMSE (cm) Cressman, IMS 24 km OI, IMS 24 km Oper until Nov ERA-Interim OI, IMS 4km OI, IMS 4km <1500m Oper since Nov 2010 Validation against ground data Main improvement due to the OI compared to Cressman GCW Snow Watch Workshop, Toronto, January 2013 Slide 11

12 Validation data: NWS/COOP - NWS Cooperative Observer Program - Independent data relevant for validation - Used to validate a set of numerical experiments considering different assimilation approaches and IMS snow cover RMSE (cm) for the new snow analysis (OI, IMS 4km except in mountainous areas) GCW Snow Watch Workshop, Toronto, January 2013 Slide 12

13 Impact on the Atmospheric Forecasts RMS 1000hPa Geopotential height Northern Hemisphere DJF OI vs Cressman impact (both use IMS 24km) Positive means OI improves Overall impact New OI,IMS 4km vs Cressman, IMS 24km Positive means new analysis improves Validation with atmospheric forecasts Main improvement due to the IMS 4km and pre-processing GCW Snow Watch Workshop, Toronto, January 2013 Slide 13

14 New snow Analysis in Operations From Nov 2010 Old: Cressman IMS 24km New: OI IMS 4km & new preprocessing FC impact (East Asia) RMSE 500 hpa Geopot H Cressman +24km NESDIS OI Brasnett km NESDIS New snow analysis improves both the snow depth patterns and the atmospheric forecasts GCW Snow Watch Workshop, Toronto, January 2013 Slide 14

15 Snow depth analysis Operational Snow Depth Analysis departure (Observations minus Analysis ) RMS from 2007 to January 2010 Resolution increase (16km) Major improvement in the Operational Snow Depth analysis From November 2010 Consistent Improvement for the entire winters and GCW Snow Watch Workshop, Toronto, January 2013 Slide 15

16 Summary and discussion ERA-Interim: Relies on Cressman, uses SYNOP snow depth &IMS 24km Operational: Relies on OI, uses SYNOP, national snow depth &IMS 4km Improved used of observations in the past few years: analysis approach and availability of national data from six MS in NRT (valid at 06UTC, provided within 3h). More data available from other countries would be valuable. BUFR template available. products available to Member states and other users (space agencies, projects, etc ) Snow not in list of products for non-commercial use by the National Met services of WMO members; would be available to a larger community. Needs to be requested by WMO and approved by council. GCW Snow Watch Workshop, Toronto, January 2013 Slide 16

17 Summary and discussion IMS snow cover data: daily, no precise knowledge of obs time Can cause problems for short time scale events/snow line. Improving timeliness and observations time stamp of snow cover products would be highly relevant for NWP For some stations, lack of in situ reports in snow free conditions, (would be very valuable for short time scale events!) Regions with sparse SYNOP data: - But National networks exist in some areas (eg USA) Interest in having access to the data on the GTS - Regions with sparse SYNOP snow depth stations (Siberia, China) Operational monitoring of snow observations under development Acquisition of the NOAA NESDIS Automated product Future snow dedicated satellites (eg CoreH2O) of high interest for snow analysis GCW Snow Watch Workshop, Toronto, January 2013 Slide 17