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Forecast Applications
EXPERIMENTAL FORECASTING
NOAA Hazardous Weather Testbed
Scientists and forecasters at the NOAA Hazardous Weather Testbed facility
focus on developing new applications from operational data sets and transferring
new technologies from research into forecast operations. The annual Spring
Experiments, begun in 2000, explore experimental
forecasting strategies, including investigations of new
physical process representations in numerical models, ensemble approaches
to numerical modeling, and applications of high-resolution model predictions
in routine severe-weather forecasts. The NOAA Hazardous Weather
Testbed will
foster a broader collaboration between researchers and practitioners in multiple
areas, particularly shorter-timescale forecasting challenges. More
about the Hazardous Weather Testbed »
Thunderstorm Complexes with Severe Surface
Winds
Drs. Michael Coniglio and Harold Brooks of NSSL
collaborated with the Storm
Prediction Center during the 2005 SPC/NSSL Summer Experiment to
find ways to improve the prediction of thunderstorm complexes that
produce severe surface winds. This research focuses on improving the
prediction of the forward speed of these systems and where and when
these systems will begin to dissipate. More
about thunderstorm complex modeling »
NUMERICAL MODELS
Forecast model MCS
Mesoscale Convective Systems
Dr. Michael Coniglio
is looking at innovative ways to incorporate high-resolution radar observations
into computer models to improve the short-term prediction of mesoscale convective
systems (MCSs), which often produce widespread severe winds and heavy rainfall. More
about MCS modeling »
WEATHER RESEARCH and FORECASTING MODEL
The Weather Research and Forecast (WRF) model is the product of a unique collaboration between the meteorological research and forecasting communities. Its level of sophistication is appropriate for cutting edge research, yet it operates efficiently enough to produce high resolution guidance for front-line forecasters in a timely manner. Working at the interface between research and operations, NSSL scientists have been major contributors to WRF development efforts and continue to provide leadership in the operational implementation and testing of WRF:
- An NSSL scientist developed the fundamental numerical methods that allow WRF to provide an unprecedented combination of accuracy and efficiency in time integration for high resolution models.
- NSSL scientists played integral roles in WRF development as members of various developmental working groups, including groups focusing on model physics, model post-processing, ensemble forecasting, and verification.
- NSSL scientists strongly influenced decisions regarding the operational implementation of WRF by organizing collaborative experimental forecasting and evaluation exercises within the NOAA HWT annual Spring Experiments (2004, 2005)
- NSSL scientists continue to provide a leadership role in the development and implementation of the WRF model by generating and evaluating daily forecasts and serving on the WRF Program Planning Board and WRF Research Applications Board.
SNOW DENSITY
NSSL scientists are collaborating with scientists from the University of Wisconsin-Milwaukee to improve our ability to forecast the density of freshly fallen snow. The density affects the total depth of new snow, and can be difficult to forecast. Their collaboration resulted in a web-based forecasting tool for predicting the probability of snow density falling in one of three categories (light, average, or heavy) based on an artificial neural network approach. This approach was evaluated at the Hydrometeorological Prediction Center during the 2005-2006 winter.
