Activity of SMHI(Swedish Meteorological and Hydrological Institute)

Presentation for CARPE DIEM kick-off meeting,DLR-GERMANY, 28-29 January 2002.

Contact person:Magnus.Lindskog@smhi.se

Structure

•SMHI general information•Research activities at SMHI•SMHI CARPE DIEM work

SMHI General InformationSMHI operates under the Swedish Ministry of the Environment. The main office is situated in the city of Norrköping. Around 550 employees organised into divisions:

•Government•Media and Business•Environment and Energy•Transport •Research (55 persons)

The HIRLAM 3D-Var

.

. .

..

Radar Meteorology

http://www.smhi.se/brdc/

MESAN - an Operational Mesoscale Analysis System

Methods

• Optimal interpolation• HIRLAM or statistics for first guess• Quality control by cross validation• Advanced structure functions• Variable first guess error

Parameters

• Temperature at 2 m• RH at 2 m• Visibility at 2 m

Input data•Topography and orography•HIRLAM data•Synop

Precipitation structure functions

•Radar data (left)•Satellite data (right)

• Wind at 10 m• Wet bulb temperature

• Accumulated precipitation • Cloud cover

lake

soil moisture

snow

saturated zone

saturated zone

The HBVhydrologicalmodel

Distribution of the HBV model

SMHI CARPE DIEM Contribution

SMHI contributes with 50 person-months (pm):

•Area 1: Data assimilation and NWP improvements (37 pm)•Area 3:Flood forecasting (12 pm)•End-Users level of service requirements•Project results dissemination (1 pm)

SMHI AREA 1 Contribution (Part I)

Scientific rapporteur AREA 1 (2 pm):Work:•Quality assurance and global co-ordination.Deliverables:•Set up of TSC, report of kick-off meeting (month 2).•TSC reports (month 13-36).•Final report (month 36).

WP 2: Extraction of information from Doppler winds (10 pm):Work:•Generate radar radial wind superobservations.Deliverables:•Superobservation data set (month 12).

SMHI AREA 1 Contribution(Part II)

WP 3: Data assimilation (35 pm):•Implementation of observation operator for radial winds in the HIRLAM 3D- and 4D-Var. Quality control and ambiguity removal. Estimation of observation error statistics, case studies and OSE.•Software modules for 4D-Var (month 24).•Impact studies of radar radial winds and assesment for suitability of use in operational NWP (month 30).

WP 4: Assessment of improvements in NWP (5 pm):•Investigate the possibilities for online estimation of forecast error standard deviations in variational data assimilation by using techniques demonstrated by Partner 2.•Report on benefits arising from improved data assimilation (month 36).

SMHI AREA 3 Contribution (Part I)

WP 9: Assessment of the bias in the different sources of areal precipitation estimates (6 pm):Work:•Investigate the error characteristics of different sources of precipitation estimates, including NWP forecasts. MESAN useful.•Use different precipitation estimates to drive the hydrological HBV model.Deliverables:•Comparison of precipitation estimates with mesoscale analysis and other methods (month 12).•Comparison of flood estimates and forecasts using the HBV model over the area of Torpshammar (month 18).•Assessment of precipitation errors (month 36).

Swedish Case Study Basin

runoff area:4216 km2

Flooding - 2000

SMHI AREA 3 Contribution (Part II)

WP 10: Incorporating gauges and radar rainfall in NWP for improving flood forecasting in urban and rural catchments (6 pm):

Work:•Develop techniques for statistical downscaling of HIRLAM NWP forecasts. The statistical downscaling will utilise radar precipitation estimates (among others).Deliverables:•Methods for optimal combined use of precipitation estimates (month 36).•Assessments of relationship between flood forecast lead-time, accuracy and reliability (month 36).