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FY 16-17: Agency Priority Goal
Improve Forecasting Accuracy and Lead Times for High-Impact and Extreme Weather
Priority Goal
Goal Overview
Major weather events continue to demonstrate the importance of hazard preparedness and response in the United States.
The Department of Commerce’s Strategic Plan Strategic Objective 3.2, Build a Weather-Ready Nation, and the National Weather Service’s (NWS) Weather-Ready Nation goal focus on building community resilience in the face of increasing vulnerability to extreme weather and water events and providing timely and useful information to the emergency management community. A strong link exists between achieving the Department’s mission to create the conditions for economic growth and opportunity, and mitigating the economic impacts of weather events on businesses and communities. The Nation is becoming more dependent on weather prediction capabilities. Industries are demanding more weather information to make informed business decisions.
Becoming a Weather-Ready Nation involves the ability to prepare for, respond to, and recover from weather and water events. To ensure that the United States has a Weather Service that is second-to-none, and meet the demands for more accurate and reliable forecasts and warnings, we need to advance our weather models faster.
More lead time for the prediction of weather events allows people and businesses to make informed choices and enables better protection of life, property and enhancement of the National economy. Knowing that a major snow storm is coming 20 hours before the first snowflake is useful. Knowing with a good level of confidence that a storm is coming in 5 days vastly improves the response. Evacuations for hurricanes require 3 full days. An accurate, consistent forecast 4-7 days in advance is invaluable to people who have to make critical evacuation decisions. Travel-related evacuation costs can exceed $1 million for every 10,000 people evacuated.1
Events such as the unprecedented drought conditions in California, repeated flooding in the Ohio Valley, and massive snow storms across the Northeast (which caused a shut down during the winter of 2015) further demonstrate the need for improved forecasting accuracy and lead times for high impact and extreme weather. Severe weather can lead to massive traffic jams, stranded vehicles, and shutdowns of airports, mass transit systems, roads, schools, and businesses. It prompted the issuance of states of emergency declarations in major cities across the Northeast during the winter of 2015. Shutdown of air and sea transportation routes, construction delays, and the late deliveries of goods and services, impact the wages and the economic health of our nation in both the short and long term.
Increased lead time means more time to take the necessary actions to prepare for and protect individuals from high impact and extreme weather events. For example, the Federal Aviation Administration (FAA) will have more time to make critical decisions regarding rerouting or grounding of planes. Federal Emergency Management Agency (FEMA) will have more time to coordinate evacuation planning and contingency plans supporting Federal, State, and local efforts. Likewise, businesses will have more time to make better decisions necessary to protect their employees and customers and lessen potential economic impacts. Ultimately, this leads to lives saved, property protected and reduction in negative weather impacts to the economy.
Our FY 14-15 Agency Priority Goal (APG), Improve Forecasting Accuracy and Lead Times for Severe Weather, used a deterministic approach based on the performance of a single model. The FY16-17 goal is based on an approach using an ensemble system of global model output, which provides more robust model guidance including estimates of forecast uncertainty and reliability. The ensemble enables forecasters to communicate both the severity and likelihood of predicted weather impacts. Since December 1992, global ensemble forecasts have been part of NWS’ operational suite of forecast model guidance and use of this approach is highlighted in the reports of the National Academy of Sciences, Weather Services for the Nation: Becoming Second to None and the National Academy of Public Administration, Forecast for the Future: Assuring the Capacity of the National Weather Service. The atmosphere is a chaotic system with a significant uncertainty in each forecast. Ensemble weather forecast model guidance entails running a numeric weather prediction model multiple times, with perturbations in the initial conditions and/or model settings, to estimate inherent uncertainty in atmospheric conditions and provide a better estimate for the range of future states of the atmosphere. Use of ensemble weather forecast model guidance provides more useful forecast information that quantifies the uncertainty used to communicate risk for more informed decision making in response to incoming extreme weather events.
Over the next two years, NWS will continue to extend the useful lead time3 of its ensemble weather forecast model guidance out to 9.5 days through:
- Increasing Computing Capacity
- Achieving Higher Model Resolution and improved Physics.
- Improving Data Assimilation Methodology.
- Incorporating New Satellite Observations into NWP Models.
Improving our global weather prediction skill facilitates improvements to our regional, local scale models that provide accurate information about the formation and movement of high impact storms in the right place at the right time. Our goal is to see farther into the future and enable the American public to make the right choices when extreme weather threatens.
1CENTREC. “An Investigation of the Economic and Social Value of Selected NOAA Data and Products for Geostationary Operational Environmental Satellites (GOES)” February 2007. Figures updated by NOAA to reflect 2015 price levels.
2 Laurens M. Bouwer, “Reply to Neville Nichols Comments on ‘Have Disaster Losses Increased Due to Anthropogenic Climate Change?,’” Bulletin of the American Meteorological Society (June 2011), notes that anthropogenic changes have been established for smaller-scale weather extremes such as heat waves, droughts and heavy precipitation events but states that there has not been a demonstrated trend for larger events.
3 Useful lead time is showing skillful model performance as indicated by anomaly correlation score greater than 0.6 (see Indicator Overview section for more details)
Strategies
National Oceanic and Atmospheric Administration (NOAA) overall strategy is to improve useful global ensemble weather forecast model guidance out to 9.5 days, to improve the accuracy of regional predictions and provide forecasters with better information to support stakeholder’s decisions.
One way to measure improvements in model performance is to examine how far into the future numerical weather prediction (NWP) model guidance retains skill (accuracy). Model outputs cease to have useful skill at predicting the weather at longer forecast lengths. Large scale weather patterns that affect the local weather that each of us experience on a daily basis are driven by features in the mid-levels of the atmosphere. This APG focuses on the GEFS model that has useful skill at forecasting the mid-levels of the atmosphere across the globe out to about 9.0 days in 2015. With the increase in computing capacity and model upgrades discussed in the next section, NWS expects to extend this out to 9.5 days.
To achieve the goal of seeing farther into the future, NWS will use a combination of increased computing capacity, higher model resolutions and physics, improved data assimilation methodology, and incorporate new satellite observations into NWP models.
- Increase Computing Capacity: The WCOSS provides NOAA with reliable High Performance Computing capacity essential to processing of complex weather prediction models, data assimilation, data analysis, product generation, and prediction capabilities. Increasing the capacity of the WCOSS will provide more accurate and specific forecasting model guidance critical to help build a Weather-Ready Nation.
- Achieve Higher Model Resolution and Physics: NWS will improve model resolution and the underlying physics upon which the model is built. This means NWS’ weather forecasts will be more specific and accurate for extreme weather. This will be achieved by implementing upgrades to the Global Forecast System (GFS) and the GEFS.
- Improve Data Assimilation Methodology: Improvements in numerical model prediction have been due to in part to improvements in data assimilation. Further, advances in data assimilation and the upgrade of the Ensemble Kalman Filter will improve global forecast models.
- Incorporate New Satellite Observations into NWP Models: Timely and accurate forecasts and warnings depend on data from the integrated global observing systems for initialization. Satellites are central to providing observations with global coverage, frequent refresh, and resolution to meet the requirements of state-of-the-art NWP modeling systems. Applying advanced data assimilation techniques to incorporate the vast increase in quality, frequency, and coverage of measurements to be provided by new satellites to be launched (such as GOES-R, COSMIC- 2A, Joint Polar Satellite System (JPSS)) improves the analysis of current conditions that drive each cycle of GEFS prediction. For instance, GOES-R data will improve Atmospheric Motion Vectors available for the models, and incorporating JPSS and COSMIC-2A data will provide more accurate information about the distribution of moisture and the temperature structure of the atmosphere, as well as the state of the land, sea, and ice surface boundaries.
Progress Update
There were no milestones for Q4 FY16.
The Agency Priority Goal (APG) is on target for completion by September 30, 2017 and we are at our planned stage of process. The advanced satellite observations will be tested and incorporated into scheduled upgrades of the data assimilation system.
Note that the Forecasting Lead Time is calculated based on a calendar year, and the current score is 9.25 days as of January 2016. The score will be updated in January 2017.
Next Steps
Next steps include:
FY17 Q1:
- Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC-2A) launch*
- Geostationary Operational Environmental Satellite R-Series (GOES-R) launch*
FY17 Q3:
- Implement Global Data Assimilation System/GLobal Forecast System (GDAS/GFS) upgrade to help improve forecast skill.
* These are the current public launch dates. If there is further change in these launch dates, those will be reflected before the fiscal year begins.
Contributing Programs & Other Factors
- National Environmental Satellite, Data, and Information Service/Geostationary Operational Environmental Satellites
- National Environmental Satellite, Data, and Information Service/Joint Polar Satellite System
- National Environmental Satellite, Data, and Information Service/Office of Systems Development
- National Weather Service/National Centers of Environmental Prediction/Environmental Modeling Center
- National Weather Service/National Centers of Environmental Prediction/National Center of Operations
- National Weather Service/Science and Technology Integration Office
- National Weather Service/Central Processing Office
- National Weather Service/Analyze Forecast, and Support Office
No Data Available
