You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
This Python module contains a collection of different scale- and distribution-based bias adjustment techniques for climatic research (see `/examples/examples.ipynb` for help).
21
22
22
-
### 📍 For the application of bias corrections on _lage data sets_ it is recomanded to use the C++ tool [BiasAdjustCXX](https://github.com/btschwertfeger/Bias-Adjustment-Cpp) since bias corrections are complex statistical transformation which are very slow in Python compared to the C++ implementation.
23
+
The documentation is available at: [https://python-kraken-sdk.readthedocs.io/en/stable/](https://python-kraken-sdk.readthedocs.io/en/stable/)
24
+
25
+
> ⚠️ For the application of bias corrections on _lage data sets_ it is recomanded to use the command-line tool [BiasAdjustCXX](https://github.com/btschwertfeger/BiasAdjustCXX) since bias corrections are complex statistical transformation which are very slow in Python compared to the C++ implementation.
23
26
24
27
---
25
28
@@ -42,7 +45,7 @@ These programs and data structures are designed to help minimize discrepancies b
42
45
43
46
<figure>
44
47
<img
45
-
src="images/biasCdiagram.png?raw=true"
48
+
src="docs/images/biasCdiagram.png?raw=true"
46
49
alt="Schematic representation of a bias adjustment procedure"
- When using the `adjust_3d` method you have to specify the method by name.
126
128
- For the multiplicative linear scaling and the delta method as well as the variance scaling method a maximum scaling factor of 10 is defined. This can be changed by the parameter `max_scaling_factor`.
127
129
128
-
## Examples (see repository on [GitHub](https://github.com/btschwertfeger/Bias-Adjustment-Python))
130
+
## Examples (see repository on [GitHub](https://github.com/btschwertfeger/python-cmethods))
129
131
130
132
Notebook with different methods and plots: `/examples/examples.ipynb`
- Computation in Python takes some time, so this is only for demonstration. When adjusting large datasets, its best to use the C++ tool [BiasAdjustCXX](https://github.com/btschwertfeger/Bias-Adjustment-Cpp).
158
+
- Computation in Python takes some time, so this is only for demonstration. When adjusting large datasets, its best to use the C++ tool [BiasAdjustCXX](https://github.com/btschwertfeger/BiasAdjustCXX).
157
159
- Formulas and references can be found in the implementations of the corresponding functions.
158
160
159
161
### Space for improvements:
160
162
161
-
Since the scaling methods implemented so far scale by default over the mean values of the respective months, unrealistic long-term mean values may occur at the month transitions. This can be prevented either by selecting `group='time.dayofyear'`. Alternatively, it is possible not to scale using long-term mean values, but using a 31-day interval, which takes the 31 surrounding values over all years as the basis for calculating the mean values. This is not yet implemented in this module, but is available in the C++ implementation [here](https://github.com/btschwertfeger/Bias-Adjustment-Cpp).
163
+
Since the scaling methods implemented so far scale by default over the mean values of the respective months, unrealistic long-term mean values may occur at the month transitions. This can be prevented either by selecting `group='time.dayofyear'`. Alternatively, it is possible not to scale using long-term mean values, but using a 31-day interval, which takes the 31 surrounding values over all years as the basis for calculating the mean values. This is not yet implemented in this module, but is available in the C++ tool [BiasAdjustCXX](https://github.com/btschwertfeger/BiasAdjustCXX).
162
164
163
165
---
164
166
165
167
<aname="references"></a>
166
168
167
169
## 6. References
168
170
169
-
- Schwertfeger, Benjamin Thomas (2022) The influence of bias corrections on variability, distribution, and correlation of temperatures in comparison to observed and modeled climate data in Europe (https://epic.awi.de/id/eprint/56689/)
170
-
- Linear Scaling and Variance Scaling based on: Teutschbein, Claudia and Seibert, Jan (2012) Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods (https://doi.org/10.1016/j.jhydrol.2012.05.052)
171
-
- Delta Method based on: Beyer, R. and Krapp, M. and Manica, A.: An empirical evaluation of bias correction methods for palaeoclimate simulations (https://doi.org/10.5194/cp-16-1493-2020)
172
-
- Quantile and Detrended Quantile Mapping based on: Alex J. Cannon and Stephen R. Sobie and Trevor Q. Murdock Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes? (https://doi.org/10.1175/JCLI-D-14-00754.1)
173
-
- Quantile Delta Mapping based on: Tong, Y., Gao, X., Han, Z. et al. Bias correction of temperature and precipitation over China for RCM simulations using the QM and QDM methods. Clim Dyn 57, 1425–1443 (2021). (https://doi.org/10.1007/s00382-020-05447-4)
171
+
- Schwertfeger, Benjamin Thomas and Lohmann, Gerrit and Lipskoch, Henrik (2023) _"Introduction of the BiasAdjustCXX command-line tool for the application of fast and efficient bias corrections in climatic research"_, SoftwareX, Volume 22, 101379, ISSN 2352-7110, (https://doi.org/10.1016/j.softx.2023.101379)
172
+
- Schwertfeger, Benjamin Thomas (2022) _"The influence of bias corrections on variability, distribution, and correlation of temperatures in comparison to observed and modeled climate data in Europe"_ (https://epic.awi.de/id/eprint/56689/)
173
+
- Linear Scaling and Variance Scaling based on: Teutschbein, Claudia and Seibert, Jan (2012) _"Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods"_ (https://doi.org/10.1016/j.jhydrol.2012.05.052)
174
+
- Delta Method based on: Beyer, R. and Krapp, M. and Manica, A.: _"An empirical evaluation of bias correction methods for palaeoclimate simulations"_ (https://doi.org/10.5194/cp-16-1493-2020)
175
+
- Quantile and Detrended Quantile Mapping based on: Alex J. Cannon and Stephen R. Sobie and Trevor Q. Murdock _"Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes?"_ (https://doi.org/10.1175/JCLI-D-14-00754.1)
176
+
- Quantile Delta Mapping based on: Tong, Y., Gao, X., Han, Z. et al. _"Bias correction of temperature and precipitation over China for RCM simulations using the QM and QDM methods"_. Clim Dyn 57, 1425–1443 (2021). (https://doi.org/10.1007/s00382-020-05447-4)
0 commit comments