First THORPEX International Science Symposium, Montreal

Transcription

1 Courtesy of Mel Shapiro Ladies and Gentlemen, The Rossby wave train you can find in the Thorpex Science Plan reached Europe on August 11, An upper level trough induced the development of a low pressure system over the Adria in the mediterranean sea. 1

2 August 2002, Saxonia Ilse This system moved northeast around the Alps. This so-called Vb weather situation is usally a matter of concern because huge amounts of humidity are transported from the mediterrenean to eastern Europe. And indeed due to strong vertical lifting of the air masses, heavy precipitation occured demonstrated by this rain rate retrieval provided by Franz Berger, DWD. But then two other unfortunate effects happened. The low pressure was blocked and got stationary. The increase of the pressure gradient at the northern part caused a strong wind from northwest. This resulted in strong enhancement of the precipitation in the Erzgebirge, a lowmountain range in eastern Germany. Welche Werte traten denn bei der Flutkatastrophe auf und wie vergleichen sich diese mit den mittleren Ergebnissen? 1. Development of upper level low pressure system over gulf of Genua 2. Dynamic lifting on east side 3. Vb low pressure system over adria 4. Moved northeast, strong humidity transport from mediterreanean 5. Northern and western side, large area of lifting due to upper level divergence 6. Western side strong pressure gradient, strong northwest wind 7. Orographic lifting in Erzgebirge 8. Blocking by high pressure systems over east and western Europe 2

3 Precipitation amount in August 2002 Largest ever measured precipitation in Germany: Zinnwald-Georgenfeld 312 mm/24h German Meteorological Service (DWD), Klimastatusbericht 2002 Important example for the interaction between large and small-scale processes The results was the strongest precipitation ever measured in Germany. Important example of interaction. If the low has moved 100 km more to the east, we would not have had a flooding event in Germany. Findet man sonst höchstes in den Tropen während des Monsuns. Wiederholwahrscheinlichkeit: mehr als 100 Jahre 3

4 Flood disaster, Saxonia, August 2002 Economic loss: about US$ (Annual Report 2002, Munich Reinsurance Company) Historic district of Dresden. How did the models perform? 4

5 Performance of Local Model of DWD DWD, Klimastatusbericht 2003 Left panel: obs. precip between , 6 UTC, right panel: LM forecast Area-averaged precipitation was predicted reasonably well. However, prediction of location and intensity of precip maximum was not accurate enough for supporting hydrological models. In connection with Thorpex, these small-scale effects due to orography have to be taken into account, so that the precipitation fields can be predicted down to the size of the river catchment areas. This event was one of our motivations to launch a QPF program in Germany. 5

6 The German Priority Program 1167 Quantitative Precipitation Forecast Volker Wulfmeyer Institute of Physics and Meteorology (IPM), University of Hohenheim, Stuttgart, Germany Gerhard Adrian German Meteorological Service (DWD) Andreas Hense, Clemens Simmer Meteorological Institute, University of Bonn, Germany Christoph Kottmeier Institute of Meteorology and Climate Research (IMK), Karlsruhe, Germany 1. Goals and structure of Priority Program PQP 2. PQP Experiments 3. The relation between PQP and THORPEX Coauthors. PQP Aufbau 6

7 1. Goals and structure of PQP Improve QPF by the identification of the physical and chemical processes responsible for deficits exploration and application of existing and new data sets for improved representation of relevant processes determination of the predictability of precipitation using statistical-dynamical analyses Very similar to Thorpex goals. Ask correct critical science questions, we can to similar statements. 7

8 PP 1167 Information Year Staff Exp. GOP IOP April M April Period 1 2 M Preparation Preparation April M 0.2M April Period 2 2 M 1.2M One year Performance: Summer 2007 GOP: General Observations Period IOP: Intensive Observations Period April M 0.2M April Period 3 2 M Data analysis Data analysis Participants: - 11 universities - 3 research centers - 2 weather services Projects: - 3 Verification - 2 Theory, numerics - 3 Nowcasting - 2 Orography - 3 Microphysics - 2 Parameterization - 6 Data assimilation - 3 GOP, IOP First SPP since 18 years 8

9 GOP and IOP 2) Assimilation and stat. dyn. methods 1) Data base and retrievals 3) Processes and model physics VALIDATION DFG Priority Program 4) Operational test environment Universities and research institutes NWP models DWD Common structure for coordination. There is still something missing important for a success of this program. Enhancement of data base 9

10 IOP COPS (Convective and Orographically-induced International collaboration Precipitation Study) and coordination A field experiment within the Priority Program 1167 PQP IPY Goal: Advance forecasts of orographically-induced convective precipitation by 4-d observations of its life cycle Region: Southwestern Germany, eastern France Duration: 3 months Date: Summer 2007 Features: Severe thunderstorm activity but low QPF skill Information: EUMETSAT special satellite operation modes and data COPS Natural convection laboratory THORPEX Regional Campaign Suggested area (270 x 150 km 2 ) General Observations Period (GOP) region, duration: 1 year in 2007 Transport and Chemistry in Convective Systems (TRACKS) region Intensive observations period (IOP) region SFB 641 Tropospheric Ice Phase Mesoscale Alpine Programme (MAP) Forecast Demonstration Project (FDP) region Supersite 10

11 1. Pre-convection: 3. Life cycle of precipitation: - Targeted observation within a TReC -- Dedicated Aircraft tracking, radar observations measurements of upstream flow Investigation of cloud and precipitation Boundary-layer measurements using a synergy dynamics and instrumentation microphysics of 3-d scanning Turbulence closure inobservations heterogeneous terrain Impact of targeted Investigation of the interaction between large- and small-scale processes 2. Initiation of convection: - Dedicated measurements of upstream flow - Impact of targeted observations Investigation of the interaction between large- and small-scale processes - Adaptation of scanning modes Investigation of the development and parameterization of convection Large effort, can only be achieved by international collaboration Successful proposal for Priority Program Initial conditions + parameterization Science Overview Document in preparation Collaboration with NASA, NOAA, NCAR, CNRS, weather services in Germany and other countries 11

12 Sensitivity on initial conditions: Case study during IHOP_2002: May 24 LASE flight tracks 18:15UT 20:30UT 18:00UT 19:00UT 20:00UT 20:20UT 20:50UT 19:30UT 18:35UT 18:45UT NASA Langley Research Center (LaRC) Lidar Atmospheric Sensing Experiment (LASE) on board of NASA DC-8 Initiation of convection Assimilation of new observing system in mesoscale and global models will be a central aspect of COPS, on example We used data of the IHOP campaign. IHOP, we selected May 24, 2002: Cold front, dry line triple point, high probability of convection, upper air trough Flight pattern were designed so that the preconvective water vapor field was measured Lase was upstream and downstream there was development of deep convection 12

13 4DVAR using MM5: Comparison of water vapor fields Huge impact on the water vapor field by data assimilation, probably due to better placement of dryline Explain carefully the labels. 13

14 Results: Comparison of precipitation fields Significant positive impact on the precipitation field by first 4DVAR of water vapor lidar data (Wulfmeyer et al., submitted to MWR 2004) In principle, we cannot expect a detailed agreement due to the complex processes but also due to the fact that information content of LASE only influenced the western part of Oklahoma. Therefore any improvement of precipitation would be a large success. In the following, I am showing the precipitation field modeled without and with data assimilation as well as the corresponding radar reflectivity field. Obviously, strong impact indicating problems with the initial fields. Prof. Dr. Hartmut Graßl: Numerical models are only as good as the data sets used for their validation and initialization Prof. Dr. Volker Wulfmeyer: Data sets are only good insofar as they are able to directly close the gaps the models and the real state of the atmosphere. We showed that this case for lidar data. 14

15 3. Relations to THORPEX 2. High-resolution, advanced models IOP, GOP features 3. Data assimilation, ensemble forecasts, reanalyses Minimizing the gap between models and data 1. Previously unachieved data sets: Synergy of 3-d scanning, airborne and satellite instrumentation Big picture approach: Initiation of convection Formation of clouds Formation of precip. Separate and quantify QPF errors due to initial fields and parameterizations, study their effect on predictability Why now? Better data and synergies, better models, coordination with international projects, high-resolution models, better data assimilation tools (real-time), separation of errors due to initialization and parameterization Focus for collaboration 15