First Results The figure below shows a snapshot of wind data from mid December 2009 to mid February 2010, the period with the densest data coverage. All.

Slides:



Advertisements
Similar presentations
TRAMM HYDROSYS SENSORSCOPE GSN SENSORMAP BIGLINK RECORD APUNCH EXTREMES MOUNTLAND COGEAR HYDROMON PERMASENSE Swiss Experiment Interdisciplinary Environmental.
Advertisements

World Meteorological Organization Working together in weather, climate and water Snowfall Measurement Challenges WMO SPICE Solid Precipitation Intercomparison.
Development of Bias-Corrected Precipitation Database and Climatology for the Arctic Regions Daqing Yang, Principal Investigator Douglas L. Kane, Co-Investigator.
“OLYMPEX” Physical validation Precipitation estimation Hydrological applications Field Experiment Proposed for November-December th International.
Climate Research in Nepal Himalayas Saraju K. Baidya (Department of Hydrology & Meteorology) “Mountains, witnesses of global changes. Research in the Himalaya.
Eidgenössisches Departement des Innern EDI Bundesamt für Meteorologie und Klimatologie MeteoSchweiz Application of WIGOS principles at MeteoSwiss Bertrand.
NOAA Hydrology Program Geoff Bonnin Office of Hydrologic Development NOAA National Weather Service x103 Geoff Bonnin.
IRWIN IRWIN Improved winter index for maintenance and climate scenarios Torbjörn Gustavsson Pirkko Saarikivi, Dave Rayner, Jörgen Bogren, Caroline Tengroth.
Global Terrestrial Networks : The Hydrological Network.
Terrain and drift influences on snow surface aerodynamics A. Clifton 1, K. C. Leonard 1, C. Manes 2, M. Lehning 1. 1.SLF Davos, Switzerland 2.Politecnico.
Precipitation in the Olympic Peninsula of Washington State Robert Houze and Socorro Medina Department of Atmospheric Sciences University of Washington.
Alpine3D: an alpine surface processes model Mathias Bavay WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland.
1 G EOSS A nd M AHASRI E xperiment in T ropics (GaME-T) Taikan Oki and Shinjiro.
Session 131 Hazard Mapping and Modeling Supporting Emergency Response Operations using GIS and Modeling.
1 Modelled Meteorology - Applicability to Well-test Flaring Assessments Environment and Energy Division Alex Schutte Science & Community Environmental.
Developing Tools to Enable Water Resource Managers to Plan for & Adapt to Climate Change Amy Snover, PhD Climate Impacts Group University of Washington.
A New Technique to Forecast Arizona Summer Thunderstorms Michael Leuthold Lecturer Department of Atmospheric Sciences University of Arizona.
Ensemble Post-Processing and it’s Potential Benefits for the Operational Forecaster Michael Erickson and Brian A. Colle School of Marine and Atmospheric.
Wind Energy Forecaster A Web-based Wind Energy Prediction Tool Aditya Trivedi ’16 Advisor: Dr. Eric Larson.
An Instrumented Coastal Process Modeling Test Bed US Army Corps of Engineers BUILDING STRONG ® Jeff Hanson U. S. Army Engineer Research and Development.
Disaster Reduction & Climate Change Adaptation by Fengmin Kan, UN-ISDR Africa Nairobiwww.unisdr.org.
CARPE DIEM Centre for Water Resources Research NUID-UCD Contribution to Area-3 Dusseldorf meeting 26th to 28th May 2003.
Centre for Earth Systems Engineering Research Infrastructure Transitions Research Consortium (ITRC) David Alderson & Stuart Barr What is the aim of ITRC?
Geostatistical approach to Estimating Rainfall over Mauritius Mphil/PhD Student: Mr.Dhurmea K. Ram Supervisors: Prof. SDDV Rughooputh Dr. R Boojhawon Estimating.
From Rain into Water Peter Ewins Chief Executive Met Office.
Application of a rule-based system for flash flood forecasting taking into account climate change scenarios in the Llobregat basin EGU 2012, Vienna Session.
Summary of MAP D-PHASE Strategy and Requirements MAP D-PHASE / Olympics Project Meeting 6 February 2006 Prepared by: Ron McTaggart-Cowan.
Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss High-resolution data assimilation in COSMO: Status and.
EGU General Assembly C. Cassardo 1, M. Galli 1, N. Vela 1 and S. K. Park 2,3 1 Department of General Physics, University of Torino, Italy 2 Department.
Forecasting Streamflow with the UW Hydrometeorological Forecast System Ed Maurer Department of Atmospheric Sciences, University of Washington Pacific Northwest.
Impact Of Surface State Analysis On Estimates Of Long Term Variability Of A Wind Resource Dr. Jim McCaa
Office of Science Office of Biological and Environmental Research DOE Workshop on Community Modeling and Long-term Predictions of the Integrated Water.
The IEM-KCCI-NWS Partnership: Working Together to Save Lives and Increase Weather Data Distribution.
WWRP OUTCOME OF CASXV (November 2009) David Burridge and Gilbert Brunet WWRP & THORPEX IPO CASXV report – ftp://ftp.wmo.int/Documents/PublicWeb/mainweb/meetings/
Weather Predicting Weather forecasting is a prediction of what the weather will be like in an hour, tomorrow, or next week. Weather forecasting involves.
Understanding hydrologic changes: application of the VIC model Vimal Mishra Assistant Professor Indian Institute of Technology (IIT), Gandhinagar
Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss Local Probabilistic Weather Predictions for Switzerland.
A Decision Support Tool for Highway Maintenance: A First Principle Thermal Mapping Model & Edward E. Adams WTI / MSU Bozeman, MT Allen R. Curran ThermoAnalytics.
New Fire Weather System Bernard Miville Manager of Operational Forecasting.
Advanced interpretation and verification of very high resolution models National Meteorological Administration Rodica Dumitrache, Aurelia LUPASCU,
Travis Smith Hazardous Weather Forecasts & Warnings Nowcasting Applications.
Application of DHSVM to Hydrologically Complex Regions as Part of Phase 2 of the Distributed Model Intercomparison Project Erin Rogers Dennis Lettenmaier.
The Canadian Climate Impacts Scenarios (CCIS) Project is funded by the Climate Change Action Fund and provides climate change scenarios and related information.
TECO Upgrade and new developments of the automatic weather stations network in Austria Ernest Rudel, Martin Mair & Kurt Zimmermann ZAMG.
Doppler Lidar Winds & Tropical Cyclones Frank D. Marks AOML/Hurricane Research Division 7 February 2007.
The DEWETRA platform An advanced Early Warning System.
3-D rendering of jet stream with temperature on Earth’s surface ESIP Air Domain Overview The Air Domain encompasses a variety of topic areas, but its focus.
Proposed THORPEX/HEPEX Hydrologic Ensemble Project (THEPS) Presentation for 3 rd THORPEX Science Symposium September 14-18, 2009 Prepared by John Schaake,
Philippe Steiner, MeteoSwiss COSMO General Meeting September 22th, 2005 Plans of MeteoSwiss for next year.
India has multiple hazards that it must combat namely: 1.Drought 2. Floods 3.Cyclone 4.Earthquake While previous disasters form the basis of developing.
Computational Fluid Dynamics - Fall 2007 The syllabus CFD references (Text books and papers) Course Tools Course Web Site:
Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss Plans of MeteoSwiss for 2007/ th September 2007.
Overview of CBRFC Flood Operations Arizona WFOs – May 19, 2011 Kevin Werner, SCH.
Grupo de Meteorologia e Climatologia na Universidade de Aveiro Alfredo Rocha, Tiago Luna, Juan Ferreira, Ana Carvalho and João.
Tayba Buddha Tamang Meteorology/Hydromet Services Division Department of Energy Ministry of Economic Affairs South Asian Climate Outlook Forum (SASCOF-1)‏
UERRA User Workshop Toulouse, 4 th Feb 2016 Questions to the users.
EC-PHORS GCW YOPP The WMO Global Cryosphere Watch (GCW) is an international mechanism for supporting all key cryospheric in-situ and remote sensing observations.
V. Vionnet1, L. Queno1, I. Dombrowski Etchevers2, M. Lafaysse1, Y
Postprocessing NWP model output for the
European Wind Energy Conference and Exhibition 2009, Marseille, France
Climate Change & Environmental Risks Unit Research Directorate General
Be The Weather Guy Presented to UCALL on October 14, 2009
Validation Working Group
Stefano Grassi WindEurope Summit
University of Washington Center for Science in the Earth System
Stochastic Storm Rainfall Simulation
Verification of COSMO-LEPS and coupling with a hydrologic model
Gabriel Mannah Kpaka Deputy Director General/Head of Operations
(6-8 November 2018, Beijing, China)
Status of the Regional OSSE for Space-Based LIDAR Winds – Feb01
Presentation transcript:

First Results The figure below shows a snapshot of wind data from mid December 2009 to mid February 2010, the period with the densest data coverage. All of this data has been extracted from the SwissEx archives using tools developed for SwissEx. WFJ1 is the most exposed site, and illustrates the synoptic forcing – N and NW storms are a common part of the regional climate. DAV3 shows reduced wind speeds and a change in wind direction, likely from local terrain sheltering, while the DAV1 site shows the impact of the occasional Fohn storms coming from the SW. FLU2 and the Fluela mast show the strong localised valley winds that develop in the Fluela pass. Work continues on coupling COSMO and ARPS. This data (and others from the area) will be used to validate those simulations. Research Platforms: SwissEx Science Observing and modelling Winds and Precipitation in Mountainous Terrain Andrew Clifton 1, Megan Daniels 2, Nicholas Dawes 1, Michael Lehning 1 1. WSL Institute for Snow and Avalanche Research, SLF 2. Laboratory of Environmental Fluid Mechanics and Hydrology (EFLUM), EPFL Contact: Michael Lehning, WSL/SLF Davos, Fluelstrasse 11, 7260 Davos Dorf, Switzerland WWW: SwissEx Science Goals The SwissEx Science project is a collaborative project bringing together data from WSL, EPFL and Metoswiss to address fundamental questions relating to mountain meteorology. Our major goal is to assess the redistribution of precipitation by wind in the region around Davos – a task that demonstrates how the SwissEx infrastructure could be used to help provide hazard warning and also addresses important research questions. Redistribution of snow by wind is a significant contribution to avalanche hazard, while redistribution of rain by wind may contribute to risk of debris flows or flooding. In both cases, better resolution modelling and observations means more accurate spatial and temporal warnings. We aim to show how a project running at EPFL and SLF in Davos can collaborate using web-based tools, particularly the SwissEx wiki ( and the advanced data storage and retrieval tools in the GSN database, also developed in SwissEx. Methods We aim to downscale 2 km COSMO forecast data to points using the Advanced Regional Prediction System, ARPS. We will compare this data to automated weather station (AWS observations, and then use SLF’s Alpine3D blowing snow code to forecast redistribution of blowing snow. Our validation data comes from the 20+ AWS around Davos, including SwissEx sensorscope stations and fixed IMIS sites, as well as the EPFL precipitation RADAR and a temporary wind energy survey mast in the Fluela pass. Downscaling with ARPS Downscaling with ARPS Regional wind and precipitation forecast COSMO Data CSCS) COSMO Data CSCS) AWS observations GSN database Quality scores Models Snow redistribution with Alpine3D Observations compare Validation Sites 20+ AWS around Davos, including RADAR Current Status A dense network of measurement sites was developed around Davos during the first phase of SwissEx. During the winter of 2009/2010 this was supplemented with data from an 80m mast in the Fluela pass. In the first few months of SwissEx Science we have developed tools to extract data from the SwissEx databases, and bring in other data from external sources such as MeteoSwiss COSMO model and run ARPS-based downscaling. This work continues, and we expect to have high resolution data (25m grids) available by the start of The next stage of our work is to validate the simulations against the field observations and quantify uncertainty. We will then move on to coupling the ARPS output with Alpine3D to produce information about redistribution of snow by wind. We intend to make this available as a datastream that can be brought into the SwissEx databases, automaticaclly compared to AWS observations and presented through the web portal to a controlled group of test users. Acknowledgements Elektrizitätswerk Davos AG generously allowed us space on their wind survey mast during the winter 2009 /2010. Sonic anemometers at 36, 54 and 75 m in the Fluela pass Stability measurements in the Fluela Pass Wind roses around Davos 15 December 2009 to 15 February 2010