This measure tracks the number of protected species stocks for which adequate assessments are available. Assessments are vital to determine the scientific basis for supporting and evaluating the impact of management actions. To be deemed adequate, assessments must be based on recent quantitative or qualitative analysis sufficient to determine current stock status based on a variety of data category levels (e.g., life history, threats, stock structure, assessment quality, assessment frequency, and abundance), and conservation status. Stock status projections are highly dependent on survey frequencies, assessment time frames, and fiscal constraints. This measure covers the protected species stocks covered by the Marine Mammal Protection Act (MMPA) or listed under the Endangered Species Act (ESA). The number of such stocks continues to increase as new species are listed and as new stocks of listed species and marine mammals are identified— the latter typically indicates increased knowledge about population stock structure.

This measure tracks the percentage of Fish Stock Sustainability Index (FSSI) fish stocks for which adequate assessments are available. Assessments are vital to determine the scientific basis for supporting and evaluating the impact of fishery management actions. To be deemed adequate, assessments must be based on recent quantitative information sufficient to determine current stock status (abundance and mortality) relative to established reference levels and to forecast stock status under different management scenarios

This measure tracks Sea Grant’s success in assisting industry personnel with the adoption of responsible harvesting and processing techniques that improve social, economic, and ecological sustainability. Industry personnel include recreational, commercial (wild and cultured), and subsistence fishery participants, processors, and retailers. Practices include techniques, technologies and best management practices adopted. Fisheries sustainability and seafood safety refers to any combination of the ability of the ecosystem to remain diverse and productive; the social, cultural, and economic resilience of the fishing community; personal or crew safety; and quality and safety of the seafood product.

The measure is a proxy for the useful forecast lead time of the GFS beyond the current forecasts skill and is computed as a three-year moving average over the range of forecast days into the future. It is defined as the day (including fractional day) that the value drops below 0.6 in the deterministic GFS forecast. Dropping below 0.6 indicates the point at which a forecast loses useful skill. Extending lead time in prediction of future weather events allows people to make informed choices and enables protection of life, property, and enhancement of the National economy. Target is measured in days.

Temperature outlooks are used by sectors of the U.S. economy, such as energy, agriculture, transportation, etc. as one factor in resource decision making. Temperature outlooks are reported as the probability of temperature being above normal or below normal or, where no definite guidance can be provided, equal chances. This is the cumulative skill calculated for regions where predictions are made.

This measure tracks a range of contributions to address coastal community risk, vulnerability, and resilience to coastal hazards. It does this by using an index that incorporates a range of NOAA-sponsored activities, including training and technical assistance that communities have engaged in to mitigate their susceptibility to coastal hazards. This measure illuminates how NOAA is improving integration of its coastal programs and the Nation's capacity for end to end preparedness, response, recovery and resilience to hazards.

The lower this measure is the better, so being below the target is exceeded and above the target is not met. Visibility and cloud ceiling forecasts are critical for aircraft safety and efficient operations. When visibility or cloud ceilings are low, pilots rely on instruments to navigate instead of visual reconnaissance. The Federal Aviation Administration establishes Instrument Flight Rule (IFR) thresholds—visibility less than three statute miles and/or cloud ceilings at, or below, 1000 feet—for safety. NWS assesses the quality of IFR threshold forecasts in response to these requirements. Fundamental statistical metrics, specifically Probability of Detection (POD) and False Alarm Ratio (FAR), are used to track IFR forecast performance. Probability of Detection (POD), also known as Accuracy, is a ratio that describes the number of times IFR is correctly forecasted compared to the total number of IFR occurrences. FAR is a ratio that describes the number of IFR forecasts when IFR was not observed compared to the total number of forecast attempts. These two metrics must always be used in conjunction, as one can be improved at the expense of the other. Greater accuracy and a minimized FAR result in safer flights and fewer flight delays; conversely, poorer accuracy and an increased FAR result in a greater incidence of unnecessary flight delays.

*Please also note that a FAR is is the number of false alarms per the total number of warnings. So if a FAR actual is higher than the target, then the target has not been met. If the actual is the same number or less, then it has been met or exceeded.

A winter storm warning provides NOAA customers and partners advanced notice of a hazardous winter weather event that endangers life or property, or provides an impediment to commerce. Winter storm warnings are issued for winter weather phenomena like blizzards, ice storms, heavy sleet, and heavy snow. This performance indicator measures the advance warning lead time in hours of winter storm events. Improving the accuracy and advance warnings of winter storms enables the public to take the necessary steps to prepare for disruptive winter weather conditions.

Weather information users are surveyed continuously by means of a web-based, pop-up survey on NWS web pages throughout the Nation. A sample size of approximately 6,000 responses is collected quarterly for a maximum of 24,000 annual responses. The Customer Satisfaction Index (CSI) score is calculated as a weighted average of three survey questions that measure different facets of satisfaction with NWS services. American Customer Satisfaction Index (ACSI) researchers use proprietary software technology to estimate the weighting. The three questions include the overall satisfaction of NWS services, expectations of service, and a comparison to an ideal organization. Indexes are reported on a 0 to 100 scale. The CSI was started in the United States in 1994 by researchers at the University of Michigan, in conjunction with the American Society for Quality in Milwaukee, Wisconsin, and CFI Group in Ann Arbor, Michigan. The Index was developed to provide information on satisfaction with the quality of products and services available to consumers. The survey data serve as inputs to an econometric model that benchmarks customer satisfaction with more than 300 companies in 43 industries and 10 economic sectors, as well as various services of federal and local government agencies.

Metric calculated as the percent of Climate Prediction Center extended (outlooks out to 14 days) and long range (monthly and seasonal outlooks) temperature and precipitation outlooks exceeding Heidke Skill Score (HSS) of 10 (10% better than a climatological forecast). Due to the scarcity of long range outlooks (six per month), scores are smoothed over a three year period. To better track results, three individual metrics are tracked – 1) All forecasts combined, 2) Temperature only, and 3) Precipitation only.