Beth Ebert

Group: Weather and Environmental Prediction

Beth Ebert
Beth Ebert

Contact Details:

  • Fax: 9669 4660
  • Phone: 03 9669 4688
  • Address:
    Bureau of Meteorology
    GPO Box 1289
    Melbourne, 3001

Personal Data:


  • B.S. Atmospheric Sciences, University of California, 1981
  • M.S. Meteorology, University of Wisconsin, Madison, 1984
  • Ph.D. Meteorology, University of Wisconsin, Madison, 1987


Research Program Leader of the CAWCR Weather and Environmental Prediction (WEP) Program

Interests and Research:

Validation of satellite precipitation estimates:

Rainfall products from operational satellite precipitation algorithms are easily obtainable via the web or FTP, and are being used for many diverse meteorological, climate, hydrological, agricultural, and other applications. It is therefore important to have an idea of their accuracy and expected error characteristics. The Australian gridded rain gauge analysis is being used to intercompare and validate several operational and semi-operational satellite precipitation algorithms on daily and longer time scales. These include several products from NASA GSFC, NOAA NESDIS, NOAA CPC, Naval Research Laboratory, UC Irvine, and JAXA. A few NWP models are included for comparison. The validation results are updated on a daily basis, and results are displayed on the SatRainVal web site.

 Forecast verification:

In order to improve the accuracy of quantitative precipitation forecasts (QPFs) from the Bureau's numerical weather prediction (NWP) models, I developed an interactive verification tool called RAINVAL that produces maps, time series, and statistics to show the skill of the QPFs when compared to the rainfall analysis and to each other. It is currently used to monitor the daily rainfall forecasts over Australia from a large number of local and overseas NWP models, and to assess new model versions.

I have worked on spatial verification using two complementary approaches. The object-based Contiguous Rain Area (CRA) method uses pattern matching of forecast and observed rain areas to estimate errors in forecast rain location, magnitude, and pattern (Ebert and McBride 2000). This strategy can diagnose systematic errors related to weaknesses in model dynamics, physical parameterisations, surface topography, etc. The forecast for the event inself can be classified as a "hit", "miss", etc., using this object-based technique. The IDL code can be downloaded by clicking here.

Neighborhood (a.k.a. fuzzy) verification approaches reward closeness by relaxing the requirement for exact matches between forecasts and observations within a spatial and/or temporal neighborhood surrounding the forecast and observed points. Computing verification results for varying neighborhood sizes reveals which scales have useful forecast skill. Ebert (2008) describes a framework for neighborhood verification that incorporates several neighborhood verification methods appearing in the literature over recent years. The IDL code can be downloaded by clicking here.

The WWRP has conducted several Forecast Demonstration Projects to demonstrate the skill and utility of advanced nowcasting systems. I have been part of the verification effort for the Sydney 2000 and Beijing 2008 Olympics FDPs, and for the latter I developed a real-time nowcast verification system that was used by forecasters and scientists. In additional to the "usual" visual and statistical verification, it included some advanced spatial verification techniques.

I am a member of the WWRP/WGNE Joint Working Group on Forecast Verification Research (JWGFVR) established in 2003. One of our activities is to maintain a Forecast Verification web page that describes standard and advanced verification methods, answers FAQs, links to verification tools and test datasets, and tries to keep an updated reference list. The JWGFVR also runs a successful series of WMO verification tutorials and workshops, the latest of which was held in 2014 in New Delhi.

 Probabilistic forecasting:

The Bureau runs a poor man's ensemble called Operational Consensus Forecasts (OCF) in which output from several operational NWP models is bias-corrected and combined to give deterministic and probabilistic forecasts. This approach is cheap and efficient, and gives forecasts that are more accurate, on average, than any of the component models. OCF forecasts provide input to the Bureau's Next Generation Forecast and Warning System and the Water And The Land (WATL) rainfall site.

Observations-based nowcasts also benefit from quantitative uncertainty estimates. I collaborate with a team at NOAA/NESDIS working on ensemble Tropical Rainfall Potential (eTRaP), which combines satellite rainfall estimates from multiple sensors to generate deterministic and probabilistic forecasts of heavy rain in landfalling tropical cyclones. I am also part of the team developing the Thunderstorm Environment Strike Probability Algorithm (THESPA) for enhancing radar-based thunderstorm nowcasts.

Positions and Committees:

  • WWRP High Impact Weather Project Task Team, 2013-2014
  • Australian National Fire Danger Rating Science Sub-group, 2010-present
  • WGNE/WGCM Climate Metrics Panel, 2009-present
  • AMS Committee on Probability and Statistics, 2007-2009
  • WWRP Beijing 2008 FDP Team, 2005-2009
  • GIFS-TIGGE Working Group, 2005-2011
  • GPM GV Steering Committee, 2003-2010
  • WWRP/WGNE Joint Working Group on Verification (JWGV), 2003-2014; co-chair 2008-2014
  • International Precipitation Working Group (IPWG), 2002-present
  • WWRP Sydney 2000 FDP Verification Team, 2001-2002
  • Science Advisory Team, Global Precipitation Climatology Project (GPCP), 1998-2001
  • Atmospheric and Oceanic Sciences Committee of the Australian Academy of Science, 1997-2000

Refereed publications:

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