'Forecast skill' diaporamas de présentation

Ensemble Forecasting

Ensemble Forecasting. Yuejian Zhu Ensemble & Probabilistic Guidance Team Environmental Modeling Center December 7 th 2010 Acknowledgment for: Jun Du, Dingchen Hou, Geoff DiMego, John Ward, Hendrik Tolman Bill Lapenta and Steve Lord. Outline. Service for users

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A Brief History of Weather Forecasting

A Brief History of Weather Forecasting. The Beginning: Weather Sayings. "Red Sky at night, sailor's delight. Red sky in the morning, sailor take warning." "Mare's tails and mackerel scales make tall ships take in their sails." "Clear moon, frost soon." .

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Continuation of Lecture 1

Continuation of Lecture 1. Corrections/Clarifications from Day 1. 1. Lin-Rood scheme stability comes about because it is equivalent to a Semi-Lagrangian scheme not using implicit differencing. (Thanks to Ravi for pointing this out).

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Probabilistic QPFs for the Indian Monsoon using Reforecasts

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Part 5. Human Activities

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Introduction to the HWRF-based Ensemble Prediction System

Introduction to the HWRF-based Ensemble Prediction System. Zhan Zhang and HWRF Team. 2014 Hurricane WRF Tutorial, NCWCP, MD. January 16. Outline. Introduction to ensemble prediction system (EPS) What and why ensemble prediction Approaches to ensemble prediction

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A holistic review informing the Thorpex legacy Gilbert Brunet WWRP/JSC Chair

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A Coordinated Field Experiment on Severe Thunderstorm Observations and Regional Modeling over the SAARC Region

SAARC STORM A Coordinated Field Experiment on Severe Thunderstorm Observations and Regional Modeling over the SAARC Region SAARC Someshwar Das* SAARC Meteorological Research Centre, Dhaka, Bangladesh *Permanent Affiliation:

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Better Defining the Flood Threat Flood Inundation Mapping from the National Weather Service

Better Defining the Flood Threat Flood Inundation Mapping from the National Weather Service. 2009 Severe Storms and Hydrology Conference Shreveport, LA Gregory P. Shelton NWS/West Gulf River Forecast Center. Advanced Hydrologic Prediction Service. State of the science forecasting

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WGNE MJO Task Force : Current Activities and Next Steps

WGNE MJO Task Force : Current Activities and Next Steps. Steve Woolnough on Behalf of the WGNE MJO Task Force. MJO Task Force : Background. Renewed in early 2013 for a term of 3 years, extend in Dec 2015 for a further 3 years Sponsor: Working Group on Numerical Experimentation (WGNE)

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Optimization of mooring observations in the Arctic Ocean

Optimization of mooring observations in the Arctic Ocean. G. Panteleev, International Arctic Research Center, UAF M. Yaremchuk, Naval Research Laboratory, Stennis Space Center D. Nechaev, Department of Marine Science, USM T.Kikuchi, Jamstec, Japan

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Next Generation of NR

Next Generation of NR. Michiko Masutani January 2009. Joint OSSE will be concentrate on existing T511 and T799 Nature run produced by ECMWF for next few years. There are several global meso scale models are being developed. Atmosphere and Ocean coupled model is becoming mature

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Renewed in early 2013 for a new term of 3 years

WGNE MJO Task Force: Understanding MJO Dynamics and Aiding Subseasonal Prediction Matthew Wheeler WGNE MJO Task Force co-chair CAWCR/Bureau of Meteorology. MJO Task Force : Background. Renewed in early 2013 for a new term of 3 years Sponsor: Working Group on Numerical Experimentation (WGNE)

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T he NOAA Hydrometeorology Testbed

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50 th Anniversary of Operational Numerical Weather Prediction

50 th Anniversary of Operational Numerical Weather Prediction. John Jones Deputy Assistant Administrator for Weather Services June 15, 2004 University of Maryland College Park. Overview. Forecasting 60 years ago: before Numerical Weather Prediction

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Long-term Trends in Water Supply Forecast Skill

Tom.Pagano@por.usda.gov. Long-term Trends in Water Supply Forecast Skill. Are there any long-term trends in April 1 st water supply forecast skill? If so, where, when and why?. Average skill of all sites over 20-yr moving window For the West, as a whole,

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Validation of US Navy Polar Ice Prediction (PIPS) Model using Cryosat Data

Validation of US Navy Polar Ice Prediction (PIPS) Model using Cryosat Data. Kim Partington 1 , Towanda Street 2 , Mike Van Woert 2 , Ruth Preller 3 and Pam Posey 3 1 Vexcel UK, Newbury, United Kingdom 2 US National Ice Center, Washington DC, USA 3 Naval Research Laboratories, MS, USA.

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Representing Model Uncertainty: A Case Study in Seamless Prediction Tim Palmer University of Oxford European Centre for

Representing Model Uncertainty: A Case Study in Seamless Prediction Tim Palmer University of Oxford European Centre for Medium-Range Weather Forecasts. Why is it so difficult to simulate climate accurately ? What, fundamentally, is the source of model error ?

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