Tropical cyclone (TC) forecast verification techniques have traditionally focused on track and intensity, as these are some of the most important characteristics of TCs and are often the principal verification concerns of operational forecast centers. However, there is a growing need to verify other aspects of TCs as process-based validation techniques may be increasingly necessary for further track and intensity forecast improvements as well as improving communication of the broad impacts of TCs including inland flooding from precipitation. Here we present a set of TC-focused verification methods available via the Model Evaluation Tools (MET) ranging from traditional approaches to the application of storm-centric coordinates and the use of feature-based verification of spatially defined TC objects. Storm-relative verification using observed and forecast tracks can be useful for identifying model biases in precipitation accumulation in relation to the storm center. Using a storm-centric cylindrical coordinate system based on the radius of maximum wind adds additional storm-relative capabilities to regrid precipitation fields onto cylindrical or polar coordinates. This powerful process-based model diagnostic and verification technique provides a framework for improved understanding of feedbacks between forecast tracks, intensity, and precipitation distributions. Finally, object-based verification including land masking capabilities provides even more nuanced verification options. Precipitation objects of interest, either the central core of TCs or extended areas of rainfall after landfall, can be identified, matched to observations, and quickly aggregated to build meaningful spatial and summary verification statistics.
- Home
- Search Results
- Page 1 of 1
Search for: All records
-
Total Resources3
- Resource Type
-
00000030000
- More
- Availability
-
30
- Author / Contributor
- Filter by Author / Creator
-
-
Gotway, John Halley (3)
-
Abatan, Abayomi A. (1)
-
Ammann, Caspar M. (1)
-
Beck, Jeff (1)
-
Bernardet, Ligia (1)
-
Biswas, Mrinal (1)
-
Blank, Lindsay (1)
-
Brown, Barbara (1)
-
Brown, Barbara G. (1)
-
Buja, Lawrence (1)
-
Bullock, Randy (1)
-
Fowler, Tressa (1)
-
Gallus, Jr., William A. (1)
-
Gilleland, Eric (1)
-
Gutowski, Jr., William J. (1)
-
Harrold, Michelle (1)
-
Jensen, Tara (1)
-
Kaatz, Laurna (1)
-
Nance, Louisa (1)
-
Newman, Kathryn M. (1)
-
- Filter by Editor
-
-
& Spizer, S. M. (0)
-
& . Spizer, S. (0)
-
& Ahn, J. (0)
-
& Bateiha, S. (0)
-
& Bosch, N. (0)
-
& Brennan K. (0)
-
& Brennan, K. (0)
-
& Chen, B. (0)
-
& Chen, Bodong (0)
-
& Drown, S. (0)
-
& Ferretti, F. (0)
-
& Higgins, A. (0)
-
& J. Peters (0)
-
& Kali, Y. (0)
-
& Ruiz-Arias, P.M. (0)
-
& S. Spitzer (0)
-
& Sahin. I. (0)
-
& Spitzer, S. (0)
-
& Spitzer, S.M. (0)
-
(submitted - in Review for IEEE ICASSP-2024) (0)
-
-
Have feedback or suggestions for a way to improve these results?
!
Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher.
Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
-
Abstract -
Gallus, Jr., William A. ; Wolff, Jamie ; Gotway, John Halley ; Harrold, Michelle ; Blank, Lindsay ; Beck, Jeff ( , Weather and Forecasting)
Abstract A well-known problem in high-resolution ensembles has been a lack of sufficient spread among members. Modelers often have used mixed physics to increase spread, but this can introduce problems including computational expense, clustering of members, and members that are not all equally skillful. Thus, a detailed examination of the impacts of using mixed physics is important. The present study uses two years of Community Leveraged Unified Ensemble (CLUE) output to isolate the impact of mixed physics in 36-h forecasts made using a convection-permitting ensemble with 3-km horizontal grid spacing. One 10-member subset of the CLUE used only perturbed initial conditions (ICs) and lateral boundary conditions (LBCs) while another 10-member ensemble used the same mixed ICs and LBCs but also introduced mixed physics. The cases examined occurred during NOAA’s Hazardous Weather Testbed Spring Forecast Experiments in 2016 and 2017. Traditional gridpoint metrics applied to each member and the ensemble as a whole, along with object-based verification statistics for all members, were computed for composite reflectivity and 1- and 3-h accumulated precipitation using the Model Evaluation Tools (MET) software package. It is found that the mixed physics increases variability substantially among the ensemble members, more so for reflectivity than precipitation, such that the envelope of members is more likely to encompass the observations. However, the increased variability is mostly due to the introduction of both substantial high biases in members using one microphysical scheme, and low biases in other schemes. Overall ensemble skill is not substantially different from the ensemble using a single physics package.
-
Abatan, Abayomi A. ; Gutowski, Jr., William J. ; Ammann, Caspar M. ; Kaatz, Laurna ; Brown, Barbara G. ; Buja, Lawrence ; Bullock, Randy ; Fowler, Tressa ; Gilleland, Eric ; Gotway, John Halley ( , Journal of Hydrometeorology)