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Explicit arguments in TropCyclone.apply_climate_scenario_knu #991

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Explicit arguments in TropCyclone.apply_climate_scenario_knu #991

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trop_cyclone.apply_climate_scenario_knu: make yearly_steps argument e…
emanuel-schmid Jan 13, 2025
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changelog
emanuel-schmid Jan 13, 2025
6983678
readthedocs: explicit configuration file
emanuel-schmid Jan 13, 2025
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Merge branch 'develop' into feature/apply_climate_scenario_knu-signature
emanuel-schmid Jan 14, 2025
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1 change: 1 addition & 0 deletions CHANGELOG.md
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Original file line number Diff line number Diff line change
Expand Up @@ -125,6 +125,7 @@ CLIMADA tutorials. [#872](https://github.com/CLIMADA-project/climada_python/pull
- `Impact.from_hdf5` now calls `str` on `event_name` data that is not strings, and issue a warning then [#894](https://github.com/CLIMADA-project/climada_python/pull/894)
- `Impact.write_hdf5` now throws an error if `event_name` is does not contain strings exclusively [#894](https://github.com/CLIMADA-project/climada_python/pull/894)
- Split `climada.hazard.trop_cyclone` module into smaller submodules without affecting module usage [#911](https://github.com/CLIMADA-project/climada_python/pull/911)
- `yearly_steps` parameter of `TropCyclone.apply_climate_scenario_knu` has been made explicit [#991](https://github.com/CLIMADA-project/climada_python/pull/991)

### Fixed

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9 changes: 6 additions & 3 deletions climada/hazard/trop_cyclone/trop_cyclone.py
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Expand Up @@ -380,7 +380,7 @@ def apply_climate_scenario_knu(
percentile: str = "50",
scenario: str = "4.5",
target_year: int = 2050,
**kwargs,
yearly_steps: int = 5,
):
"""
From current TC hazard instance, return new hazard set with future events
Expand Down Expand Up @@ -422,6 +422,9 @@ def apply_climate_scenario_knu(
'8.5' for RCP 8.5
target_year : int
future year to be simulated, between 2000 and 2100. Default: 2050.
yearly_steps : int
yearly resolution at which projections are provided. Default is 5 years.

Returns
-------
haz_cc : climada.hazard.TropCyclone
Expand Down Expand Up @@ -450,11 +453,11 @@ def apply_climate_scenario_knu(
for basin in np.unique(tc_cc.basin):
scale_year_rcp_05, scale_year_rcp_45 = [
get_knutson_scaling_factor(
percentile=percentile,
variable=variable,
percentile=percentile,
basin=basin,
baseline=(np.min(years), np.max(years)),
**kwargs,
yearly_steps=yearly_steps,
).loc[target_year, scenario]
for variable in ["cat05", "cat45"]
]
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