Investigating bias in impact observation sources and implications for impact-based forecast evaluation
Bibliographic Data
| ID | 22028210 |
|---|---|
| Authors | Faye Wyatt (0000-0001-7562-3411, Met Office, corresponding author), Joanne Robbins (0000-0003-2225-0548, Met Office), Rebecca Beckett (Met Office) |
| Year | 2023 |
| Volume | 90 |
| Pages | 103639 |
| Publication date | 2023-05-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Disaster Risk Reduction (JOURNAL) |
| Journal identifiers | ISSN: 2212-4209 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.ijdrr.2023.103639 |
| OpenAlex | W4327568733 |
| Language | EN |
| Citations received | 5 |
| References cited | 21 |
Data collection · Data science · Geography · Hydrometeorology · Impact assessment · Meteorology · Precipitation · Statistics · Computer Science · Disaster Management and Resilience · Engineering · Environmental Science · Flood Risk Assessment and Management · Tropical and Extratropical Cyclones Research
Quantifying the added value of impact-based warnings for flash flood monitoring using innovative multi-source impact data
Judgment and decision strategies used by weather scientists in southeast Asia to classify impact severity
Research gaps and challenges for impact-based forecasts and warnings
Implementing a routine and standard approach for the automatic collection of socio-economic impact observations for impact-based forecasting and warning
Perceptions, hopes, and concerns regarding the possibilities of artificial intelligence in weather warning contexts
| Unique citing works | 5 |
|---|---|
| Citations per year | 2.5 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 5 |