3.2 Verification of Convection-Permitting Models (Invited Presentation)

Tuesday, 24 January 2017: 2:00 PM
Conference Center: Chelan 2 (Washington State Convention Center )
Adam Clark, CIMMS/Univ. of Oklahoma, Norman, OK

Convection-permitting models (CPMs) provide dramatic benefits relative to models that parameterize convection.  The benefits include an improved diurnal rainfall cycle depiction, ability to accurate depict convective mode, and better simulation of the statistical properties of convection and heavy rainfall.  Furthermore, storm-attribute based diagnostics like updraft-helicity, which cannot be computed without explicitly depicting convection, have proven invaluable for severe weather forecasting and many other applications.  Although much has been learned about CPMs through research studies and real-time forecasting experiments such as those conducted at NOAA’s Hazardous Weather Testbed, obtaining useful objective assessments of CPM performance is very challenging.  However, these objective assessments are critically important to improving these models, providing forecasters with meaningful diagnostic information, and informing evidence-based decisions on future operational CPM-based ensemble configurations.  Thus, development of useful measures that can be adopted by CPM users and developers and be made available in community tools like the Developmental Testbed Center’s Model Evaluation Tools is a high priority. 

In this talk, I’ll discuss the challenges in verifying CPMs, much of which stems from the fact that traditional verification methods typically applied to larger-scale weather indicators (e. g., precipitation, low-level temperature and moisture) fail at providing useful information when applied to CPMs.  Then, I will provide a review of recent work on new verification strategies for CPMs, such as scale-dependent metrics and object-based methods.  Finally, one of the biggest challenges for verifying CPMs is the availability of relevant observations at the scale of the CPM forecasts.  Thus, I’ll discuss recent work utilizing innovative observational datasets for verification such as the National Severe Storm Laboratory’s “rotation tracks” and MESH (maximum estimated size hail).

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner