2_use_case_name: LightningCast: AI for lightning prediction
3_agency: Department of Commerce
3_abr: DOC
4_bureau: NOAA - National Oceanic and Atmospheric Administration
8_topic_area: Other
8_question_type: Hazard Prediction
10_commercial_ai: None of the above.
11_purpose_benefits: LightningCast provides prognostic information on lightning, before the threat is realized, thereby allowing for actions that protect life and property
12_outputs: Probability that lightning will be observed at a given location in the next 60 minutes
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 9/1/2019
19_date_acq_dev_began: 9/1/2020
20_date_implemented: Scheduled for FY2025
22_dev_method: Developed in-house.
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: No
31_data_catalog: No
33_agency_data: Data from the Geostationary Operational Environmental Satellites
34_data_docs: Documentation is widely available: Documentation is not only complete, but is widely accessible within the agency, and has an owner and a regular update cadence.
37_custom_code: Yes
38_code_access: Yes – source code is publicly available.
39_code_link: https://cimss.ssec.wisc.edu/csppgeo/lightningcast_v1.0b1.html 
40_has_ato: No
42_dev_tools_wait: More than 12 months
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: Yes
49_existing_reuse: Re-use production level code and/or data products: This use case re-uses production level code as well as data products that have been published or made widely available for data science teams for within the agency.
50_internal_review: Documentation has been developed: Complete documentation detailing model performance across a range of benchmarks, architecture, relevant features and information regarding the appropriate use of the model for predictive tasks has been created.
51_extension_request: No – Agency did not request an extension for this use case.
52_impact_assessment: Planned or in-progress.
53_real_world_testing: Impact evaluation in operational environment: The AI use case has been tested in an operational environment before being fully implemented as a solution and has utilized randomized experiments with a control group or other counterfactual, social systems analysis, or other rigorous research methodologies to evaluate impact and identify potential harm to users as well as broader groups of people.
55_independent_eval: Yes – by another appropriate agency office that was not directly involved in the system’s development
56_monitor_postdeploy: Intermittent and Manually Updated: A plan for monitoring the AI use case is in place, and requires data science teams to work with DevOps engineers to manually update models at scheduled intervals, and create metrics to detect data distribution shifts between the operational environment and the training data for the model. 
57_autonomous_impact: No - Some individual decisions or actions require direct human oversight.
59_ai_notice: Online - in the terms or instructions for the service.
61_adverse_impact: No
63_stakeholder_consult: Direct user testing
65_appeal_process: No – it is not operationally practical to offer this.
66_no_appeal_reason: The AI does not provide a service. It provides guidance.
67_opt_out: Other
67_question_type: This AI is a decision-support tool used by meteorologists. Utilization is completely optional.