Presentation on theme: "TIGGE research Richard Swinbank GIFS-TIGGE Working Group meeting #9, Aug-Sep 2011."— Presentation transcript:
TIGGE research Richard Swinbank GIFS-TIGGE Working Group meeting #9, Aug-Sep 2011
TIGGE and GIFS TIGGE Objectives TIGGE archive status TIGGE-LAM Research using TIGGE data Use of multi-model ensembles Predictability studies GIFS developments Developing links with CBS/SWFDP Examples of tropical cyclone forecast products
TIGGE THORPEX Interactive Grand Global Ensemble A major component of THORPEX: a World Weather Research Programme to accelerate the improvements in the accuracy of 1-day to 2-week high-impact weather forecasts GEO task WE – TIGGE and the Development of a Global Interactive Forecast System for Weather Objectives: Enhance collaboration on ensemble prediction, both internationally and between operational centres & universities. Facilitate research on ensemble prediction methods, especially methods to combine ensembles and to correct systematic errors Enable evolution towards a prototype operational system, the Global Interactive Forecast System
TIGGE data Ten of the leading global forecast centres are providing regular ensemble predictions to support research on predictability, dynamical processes and the development of probabilistic forecasting methods. TIGGE data is made available for research after a 48-hour delay. Near real-time access may be granted for specific projects through the THORPEX International Project Office.
Summary of TIGGE database (late 2010) Centre Ensemble members Output data resolution Forecast length Forecasts per day Fields (out of 73) Start date BOM*331.50º x 1.50º10 day2553 Sep 07 CMA150.56º x 0.56º10 day26015 May 07 MSC210.9º x 0.9º16 day2563 Oct 07 CPTEC150.94º x 0.94º15 day2551 Feb 08 ECMWF51 N200 (Reduced Gaussian) N128 after day day2701 Oct 06 JMA510.56º x 0.56º9 day1611 Oct 06 KMA*171.00º x 1.00º10 day24628 Dec 07 Météo-France351.50º x 1.50º4.5 day26225 Oct 07 NCEP211.00º x 1.00º16 day4695 Mar 07 UKMO240.83º x 0.55º15 day2721 Oct 06 * Delivery of KMA & BoM data currently suspended
TIGGE Archive Usage (NCAR + ECMWF)
TIGGE-LAM: TIGGE for limited-area models The TIGGE-LAM panel, chaired by Tiziana Paccagnella (ARPA-SIM), supports the coordinated development of the Limited Area Model Ensemble Prediction System component of TIGGE. This Panel works in close coordination with the GIFS-TIGGE WG, in liaison with pre-existing LAM EPS initiatives and in coordination with the THORPEX regional committees. The panel facilitates the interoperability of the different modelling systems contributing to TIGGE and coordinates the archiving of limited-area ensemble forecasts – the three TIGGE archive centres have agreed to host a sub-set of high priority data Highlights: The TIGGE LAM Panel is being restructured in Regional sub-groups to give more emphasis to the regional component of TIGGE LAM and to facilitate the focus on regional activities. European, North America and Asia sub-groups have already been formed. The TIGGE-LAM plan is available from the TIGGE-LAM website
Publicising TIGGE Major Article in BAMS New leaflet to publicise TIGGE to researchers Contribution to GEO book Crafting Geoinformation Tropical cyclone case study in WMO Bulletin Update of TIGGE website
TIGGE Research Following the successful establishment of the TIGGE dataset, the main focus of the GIFS-TIGGE working group has shifted towards research on ensemble forecasting. Particular topics of interest include: a posteriori calibration of ensemble forecasts (bias correction, downscaling, etc.); combination of ensembles produced by multiple models; research on and development of probabilistic forecast products. TIGGE data is also invaluable as a resource for a wide range of research projects, for example on dynamical processes and predictability – for example, see presentations in this meeting. Up to the end of 2010, 43 articles related to TIGGE have been published in the scientific literature
Multi-model ensemble forecasts of T850 Demonstrates benefit of multi-model ensemble, provided that the most skilful models are used. Renate Hagedorn, ECMWF
Multi-model ensemble compared with reforecast calibration Reforecast calibration gives comparable benefit to multi-model ensemble Choice of verification data set (in this case, ERA-Interim) could have subtle but significant effect on relative benefits Calibration could further enhance benefit of multi-model ensemble Renate Hagedorn
Uncalibrated precipitation forecasts Probabilistic verification Based on ECMWF, UKMO, NCEP, 12 hour accumulations, 2 years data (autumn autumn 2009) for UK region. Verified against UKPP composite data; thresholds taken from one-month 5x5 gridpoint ukpp climatologies Multimodel (pfconcat) has consistent slight advantage over single model ensembles in resolution (solid) and reliability penalty (dotted) The overall Brier Skill Score (resolution-reliability) is negative for long lead times and high thresholds Single model ensemblesMultimodel ensemble Jonathan Flowerdew, Met Office
Probability verification - idealised calibration Use model climatology for forecast thresholds Provides upper bound on benefit from calibration Increases BSS resolution and reduces reliability penalty Multi-model ensemble remains superior Single model ensemblesMultimodel ensemble Jonathan Flowerdew, Met Office
Precipitation forecasts over USA 24 hour accumulations, data from 1 July 2010 to 31 October members each from ECMWF, NCEP, UK Met Office, Canadian Meteorological Centre. 80-member, equally weighted, multi-model ensemble verified as well. Verification follows Hamill and Juras (QJ, Oct 2006) to avoid over-estimating skill due to variations in climatology. Conclusions: ECMWF generally most skillful. Multi-model beats all. Tom Hamill
Comparison of extra-tropical cyclone tracks Lizzie Froude, U. Reading Ensemble mean error: Position (verified against ECMWF analyses) Ensemble mean error – Propagation speed Propagation speed bias
Forecasts of cyclone tracks Jana Čampa, Heini Wernli
Spatiotemporal Behaviour of TIGGE forecast perturbations Kipling et al, 2011 M(t) (log) perturbation amplitude V(t) (log) variance Indicates how spatial correlation & localisation vary as perturbations grow.
North Atlantic eddy-driven jet regimes North Atlantic eddy-driven jet profile is taken as vertically/zonally averaged low-level zonal wind in North Atlantic sector (15-75N, E) Split into three clusters S, M, N using K-means clustering Transition probability defined: Tom Frame, John Methven, U. Reading
Brier Skill Score: regime transition probabilities 3 years of TIGGE data for ONDJF ( ), ECMWF, UKMO, MSC
Matsueda (2009) The state-of-the-art NWP models simulate the blocking frequency well. But models still underestimate the (extreme) blocking frequency. +5 days +9 days +15 days Blocking frequency comparison (DJF)
Matsueda and Endo (2011, GRL accepted) - ECMWF and UKMO have a superior performance in simulating MJO. - Predicted phase speed tends to be slower than observed one. - Predicted amplitude tends to be larger than observed one. MJO Forecast comparison
ECMWF (50 members) Sinlaku initiated at 12UTC 10 Sep Dolphin initiated at 00UTC 13 Dec Japan Philippines Taiwan NCEP (20 members) Black line: Best track Grey lines: Ensemble member Munehiko Yamaguchi Tropical cyclone forecasts – ensemble spread contradictions
ECMWFNCEP T+0h T+48h Spread grows with time Does not spread with time SV-based perturbations better capture: Baroclinic energy conversion within a vortex Baroclinic energy conversion associated with mid-latitude waves Barotropic energy conversion within a vortex Munehiko Yamaguchi Steering vector Asymmetric propagation vector
24 Comparisons of TC track forecasts NOAA developing EnKF for eventual operational use in hybrid EnKF/variational data assimilation system. Early June 2010 through end of October 2010; verification against best track information. Out-performs NCEP operational - differences are statistically significant. Also compares well with ECMWF (not shown) Tom Hamill
Global Interactive Forecast System (GIFS) Development of products based on exchange of real- time tropical cyclone predictions using Cyclone XML format.
GIFS concept GIFS will use global- regional-national cascade pioneered by the WMO Severe Weather Forecast Demonstration Project (SWFDP). No single GIFS centre. Further development and evaluation of products will be done in conjunction with SWFDP and other regional pilot projects. Use of web-enabled technology for generation and distribution of products.
GIFS development GIFS-TIGGE WG has initiated a GIFS development project Develop products, based on TIGGE ensembles, focused on forecasts of Tropical cyclones Heavy precipitation Strong winds Collaborate with WMO Severe Weather Forecast Demonstration Project (SWFDP) and other FDPs and RDPs to provide an environment for the evaluation of prototype products, and to ensure that products address needs of operational forecasters and end users.
GIFS development project interactions
GIFS links to other projects NW Pacific TC project TC products on MRI website SWFDP Meteo-France RSMC Reunion TC products website under development MRI willing to make web software available to other projects, e.g. SWFDDP in SW Pacific Proposal for future SE Asia project – Honda-san Also NOAA TC product demonstration website
Tropical cyclone products from MRI/JMA
New tropical cyclone product: Strike probability time-series at a city Tetsuo Nakazawa
Forecasting TC genesis strike probability 5-7 days ahead David Richardson / ECMWF
Warnings of heavy precipitation Prototype product courtesy Mio Matsueda
Summary Since October 2006, the TIGGE archive has been accumulating regular ensemble forecasts from leading global NWP centres. The archive is a tremendous resource for the research community at large, and in particular the science working groups of THORPEX. As the basis of the development of the future Global Interactive Forecast System, products are being developed to enhance the prediction of high-impact weather, starting with tropical cyclones. GIFS products will be developed & evaluated in conjunction with SWFDP and other regional projects. TIGGE website:
How can we further increase impact of TIGGE on research? Publicity New leaflet Website How to publicise better to universities? Scientific publications Conferences/meetings THORPEX symposia & regional meetings Other conference & workshops IAMAS, AMS, EMS, AGU… Communications tiggeusers mailing list hardly used What about social media: facebook, twitter…? How else?
TIGGE – next steps References on website Volunteer required Review Article on TIGGE research When? Additional data Stratospheric Network on Assessment of Predictability (SNAP) – Andrew Charlton. Inviting TIGGE providers to join as partners
Research needs and priorities Current emphasis Calibration and combination methods Bias correction, downscaling Multi-model ensembles; reforecasts Development of probabilistic forecast products – GIFS development Tropical cyclones (CXML-based) Gridded data: heavy precipitation; strong winds Focus on downstream use of ensembles, rather than on improving EPSs
Research needs and priorities But other important areas for EPSs include Initial conditions – link with ensemble data assimilation (DAOS) Representing model error – stochastic physics (PDP, WGNE) Seamless forecasting – links with sub-seasonal forecasting (new project) Convective-scale ensembles (TIGGE-LAM, MWFR) Fragmented approach, across several WGs. But these areas, particularly first two, are important for improving EPS skill and products.
Virtuous Circle Develop, Improve Evaluate, Diagnose Ensemble Forecasts To improve EPSs we need to develop a virtuous circle – best with a single group with focus on ensemble prediction
Evolution of TIGGE & GIFS The initial focus of GIFS-TIGGE WG was on establishing the TIGGE database. We then broadened our scope to include downstream ensemble combination, calibration & product development for GIFS. We should also use the WG as a forum to discuss R&D focused on improving our EPS systems. TIGGE development GIFS Products EPS improvement Time