Ensures that NOAA provides real time (or near real time) availability of critical satellite data and products without gaps to users (NWS and other NOAA line offices, US military and operational partners). On time data and imagery provided increases timeliness and accuracy of public warnings and forecasts of climate and weather events.

Seasonal outlooks are reported as the probability of temperature being above normal, near normal, below normal or, where no definite seasonal guidance can be provided, equal chances. The seasonal outlooks are the cumulative skill calculated for regions where predictions are made. These forecasts are verified using a 48 month running mean of Heidke Skill score computed for seasonal outlooks for each 3-month seasonal mean (e.g., January-February-March mean; February-March-April mean; March-April-May mean; and so on). The previous dataset used to verify the CPC seasonal temperature outlook has developed a cold bias across a large portion of the western United States during the past 5-10 years. CPC has developed a new dataset which consists of Synoptic and Metar stations only, which is consistent throughout the historical and real time periods. This change will not impact the measure itself, nor how it is reported, but will remove biases identified in the old verification dataset, resulting in a more accurate performance indicator.

The NWS Partnership Strategy aims to improve the overall NWS partnership experience, enhance and develop new ways of leveraging and using partnership capabilities to help realize the NWS vision for a Weather-Ready Nation and understand the landscape of NWS partnerships and develop a clear strategic vision of which key partnerships we are looking to enhance or develop. To that end, the NWS will convene at least 3 national-level stakeholder/partner meetings to help meet the goals of the NWS Partnership strategy.

The Argo program is responsible for providing real-time data for the upper 2000m of ocean heat content globally and for important regions like the Tropical Pacific for detection of El Nino.

Reducing bias in OAR’s Earth System Model is an indicator of the improved skill of precipitation simulation. Bias is defined as the long-term mean (or average over time) difference between a simulated (model generated) value and the observed value. This performance measure will track the reduction in bias (e.g., percent reduction of the current FY21 bias) in U.S. seasonal precipitation simulations in OAR Earth System models based on a percentage of bias in past Earth System models.

The measure captures the count of significant and discrete NOAA research and development products that have transitioned to application at operational U.S. weather services and in the U.S. weather commercial sector. In addition, these weather products support NOAA contributions to the Weather Research and Forecasting Innovation Act of 2017.

Key activities for the development and launch of weather satellites and products are identified and tracked using a project management system.

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.

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 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.

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