Umfang:
Online-Ressource
ISSN:
1684-9981
Inhalt:
Abstract km down to 8 km. For even lower resolutions, the skill is diminished again. In contrast, for grapevine, decreasing model resolution below 1 km tends to reduce skill, which is attributed to the different spatial distribution of field crops and grapevine in the landscape. It is shown that identifying a suitable MESHS thresholds to model damage footprints always involves trade-offs. For the lowest possible MESHS threshold (20 mm) the model predicts damage about twice as often as observed (high frequency bias and false alarm ratio), but it also has a high probability of detection (80 %). The frequency bias decreases for larger thresholds and reaches an optimal value close to 1 for MESHS thresholds of 30–40 mm. However, this comes at the cost of a substantially lower probability of detection (around 50 %), while overall model skill, as measured by the Heidke skill score (HSS), remains largely unchanged (0.41–0.44). We argue that, ultimately, the best threshold therefore depends on the relative costs of a false alarm versus a missed event. Finally, the frequency of false alarms is substantially reduced and skill is improved (HSS = km resolution for field crops and 1 km for grapevine.
In:
volume:24
In:
number:7
In:
year:2024
In:
pages:2541-2558
In:
extent:18
In:
Natural hazards and earth system sciences, Katlenburg-Lindau : European Geophysical Society, 2001-, 24, Heft 7 (2024), 2541-2558 (gesamt 18), 1684-9981
Sprache:
Englisch
DOI:
10.5194/nhess-24-2541-2024
URN:
urn:nbn:de:101:1-2408061447226.318293528769
URL:
https://doi.org/10.5194/nhess-24-2541-2024
URL:
https://nbn-resolving.org/urn:nbn:de:101:1-2408061447226.318293528769
URL:
https://d-nb.info/1338067613/34
URL:
https://nhess.copernicus.org/articles/24/2541/2024/nhess-24-2541-2024.pdf
URL:
https://nhess.copernicus.org/articles/24/2541/2024/
