diff --git a/README.md b/README.md
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--- a/README.md
+++ b/README.md
@@ -2,12 +2,12 @@
# pyet: Estimation of Potential Evapotranspiration
-
+[](https://github.com/pyet-org/pyet/actions/workflows/ci.yml)
[](https://www.codacy.com/gh/phydrus/pyet/dashboard?utm_source=github.com&utm_medium=referral&utm_content=phydrus/pyet&utm_campaign=Badge_Grade)
[](https://www.codacy.com/gh/phydrus/pyet/dashboard?utm_source=github.com&utm_medium=referral&utm_content=phydrus/pyet&utm_campaign=Badge_Coverage)
-
+
pyet is an open source python package for calculating reference and potential Evapotranspiration (PET) for 1D (pandas.Series)
@@ -37,7 +37,7 @@ and 3D (xarray.DataArrray) data. Currently, eighteen methods for calculating dai
| Oudin | oudin | ✓ | - | - | - | ✓ | - | - |
$^a$ $T_{max}$ and $T_{min}$ can also be provided. $^b$ $RH_{max}$ and $RH_{min}$ can also be provided. $^c$ If actual vapor pressure is provided, RH is not needed. $^d$ Input for radiation can be (1) Net radiation, (2) solar radiation or (3) sunshine hours. If (1), then latitude is not needed. If (1, 3) latitude and elevation is needed. $^e$ One must provide either the atmospheric pressure or elevation. $^f$ The PM method can be used to estimate potential crop evapotranspiration, if leaf area index or crop height data is available. $^g$ The effect of $CO_2$ on stomatal resistance can be included using the formulation of Yang et al. 2019. $^h$ If net radiation is provided, RH and Lat are not needed. $^i$ If method==2, $u_2$, $RH_{min}$ and sunshine hours are required. $^j$ Additional input of $T_{max}$ and $T_{min}$, or $T_{dew}$. $^k$ Input can be $RH$ or actual vapor pressure. $^l$ If method==1, latitude is needed instead of $R_s$. $^m$ $T_{max}$ and $T_{min}$ also needed.
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+
## Examples and Documentation
Examples of using *pyet* can be found in the example folder:
@@ -57,10 +57,10 @@ Examples of using *pyet* can be found in the example folder:
* [Example 6](examples/06_worked_examples_McMahon_etal_2013.ipynb): Worked examples for estimating meteorological
variables and potential evapotranspiration after McMahon et al., 2013
-* [Example 7](examples/07_example_climate_change.ipynb): Example for estimating potential evapotranspiration under
- warming and elevated $CO_2$ concentrations following Yang et al., (2019)
+* [Example 7](examples/07_example_climate_change.ipynb): Example for estimating potential evapotranspiration under
+ warming and elevated $CO_2$ concentrations following Yang et al., (2019)
-* [Example 8](examples/08_crop_coefficient.ipynb): Determining the crop coefficient function with Python
+* [Example 8](examples/08_crop_coefficient.ipynb): Determining the crop coefficient function with Python
* [Example 9](examples/09_CMIP6_data.ipynb): Estimating PET using CMIP data
@@ -87,7 +87,7 @@ made:
* `pyet.makkink` against daily PET estimated with Makkink from The Royal Netherlands Meteorological
Institute ([KNMI](https://www.knmi.nl/over-het-knmi/about)).
-## Dimensions
+## Data dimensions
As of version v1.2., *pyet* is compatible with both Pandas.Series and xarray.DataArray, which means you can now estimate
potential evapotranspiration for both point and gridded data.
@@ -114,8 +114,8 @@ To install in developer mode, use the following syntax:
If you use *pyet* in one of your studies, please cite the *pyet* EGU abstract:
-* Vremec, M., Collenteur, R. A., and Birk, S.: Technical note: Improved handling of potential evapotranspiration in
-hydrological studies with PyEt, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2022-417,
+* Vremec, M., Collenteur, R. A., and Birk, S.: Technical note: Improved handling of potential evapotranspiration in
+hydrological studies with PyEt, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2022-417,
in review, 2023.
```Reference