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Activity of SMHI (Swedish Meteorological and Hydrological Institute)

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.

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Activity of SMHI (Swedish Meteorological and Hydrological Institute)

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  1. 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

  2. Structure • SMHI general information • Research activities at SMHI • SMHI CARPE DIEM work

  3. SMHI General Information • SMHI 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)

  4. The HIRLAM 3D-Var . . . . .

  5. Radar Meteorology http://www.smhi.se/brdc/

  6. MESAN - an Operational Mesoscale Analysis System Input data • Topography and • orography • HIRLAM data • Synop • Radar data (left) • Satellite data (right) • 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 • Wind at 10 m • Wet bulb temperature Precipitation structure functions • Accumulated precipitation • Cloud cover

  7. The HBV hydrological model snow soil moisture saturated zone saturated zone lake

  8. Distribution of the HBV model

  9. 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)

  10. 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).

  11. 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).

  12. 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).

  13. Swedish Case Study Basin runoff area: 4216 km2

  14. Flooding - 2000

  15. 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).

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