The Hydrometeorological Testbed at NOAA/NWS/NCEP Weather Prediction Center (WPC) is a naturalistic decision-making environment, a physical space, a collaboration space, and an insight-generating laboratory. We explore observations and models (Numerical Weather Prediction, Machine Learning and statistical models) in order to evaluate, validate and verify weather-forecasting procedures, tools, and techniques.
We recently wrapped up our season long Virtual Winter Weather Experiment (WWE) 2020-2021 during which we evaluated eight experimental Unified Forecast System (UFS) convection-allowing models (CAMs) and one machine learned snow to liquid equivalent technique (in the western US only) for snowfall forecasting using an immersive forecasting activity. We asked participants to view model information and draw their own forecasts, rank models in a pre and post evaluation survey (both subjectively and objectively), and discuss how such guidance might influence their forecasts or forecast process. Participants enjoyed the immersive forecasting activity and appreciated the opportunity to explore these experimental data sets in a pseudo-operational way. We learned that predictability for the most common events was hit or miss, large-scale predictability, at time scales of 60-84 h, was still uncertain, and CAMs could not correct for this very well. However, the information contained in such forecasts was still useful and could be brought to bear in the forecast process, and thus could be meaningful in Impact Decision Support Services (IDSS). We continued to explore the predictability challenges by designing case studies focused on Days 3 and 2 in our retrospective, intensive forecasting sessions. This aspect of the forecast process was also considered valuable because we can begin to explore notions of forecast consistency between model cycles and interactions with the forecast strategies, processes, and procedures in future experiments. For more information on the WWE, contact Dr. Kirstin Harnos (kirstin.harnos at noaa.gov).
A large part of our success comes from the participation of a large number of NWS Weather Forecast Offices, regional centers, Environmental Modeling Center, Physical Sciences Laboratory, and our academic partners as shown below:
Participant locations and number of sessions attended by Weather Forecast Offices, River Forecast Centers, National Centers, Academic Institution, Cooperative Institutes, National Labs, Region, or NOAA entity.
Our immersive forecasting activities will continue into the warm season for our Virtual Flash Flood and Intensive Rainfall Experiment (FFaIR). We will continue to utilize CAMs provided by the Center for the Analysis and Prediction of Storms, Environmental Modeling Center, and the Global Systems Laboratory for the purpose of detecting and forecasting heavy and significant precipitation that may lead to flash flooding. We will do so through an operational product lens (i.e., Excessive Rainfall Outlook) and a hybrid forecast product for 6-hour rainfall, which bridges the traditional Quantitative Precipitation Forecast guidance from WPC with the Mesoscale Precipitation Discussion product. We will forecast rainfall accumulations, rainfall rates, durations, and flooding in the Day 1 period synthesizing many operational and experimental deterministic and ensemble CAM systems. We will continue to extract meaningful information from these systems under a variety of real-time forecasting scenarios during the peak of the warm season. For more information on FFaIR, contact Dr. Sarah Trojniak (sarah.trojniak at noaa.gov).
We are looking forward to expanding the breadth of our knowledge as we seek collaboration with the social-science community. The information we produce informs the public we serve, from the methods we employ to solve physical science problems, to how we equip and prepare forecasters. Only through many different perspectives can we hope to capture a wide-angle view of forecast challenges to improve the predictions of precipitation that empower all of us to save lives and protect property.
We encourage researchers, forecasters, and emergency-support function personnel to reach out so we can work together and appreciate each other's challenges to better apply our various sciences, techniques, and approaches to empower life-saving and protective action against hazards, local and national.
NOAA/NWS/NCEP Weather Prediction Center
Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder