Improve Readme and paper regarding license and usage

README.md

@@ -8,17 +8,18 @@
 
 Pymagicc is a thin Python wrapper around the reduced complexity climate model
 [MAGICC6](http://magicc.org/). It wraps the CC-BY-NC-SA licensed
-[MAGICC6 binary](http://www.magicc.org/download6).
+[MAGICC6 binary](http://www.magicc.org/download6). Pymagicc itself is AGPL licensed.
 
-Pymagicc makes the MAGICC model easily installable and usable from Python and can for example be used in the analysis of mitigation scenarios, in integrated assessment models, complex climate model emulation, and uncertainty analyses.
+MAGICC (Model for the Assessment of Greenhouse Gas Induced Climate Change)
+is widely used in the assessment of future emissions pathways in climate policy analyses,
+e.g. in the Fifth Assessment Report of the
+Intergovernmental Panel on Climate Change or to model the physical aspects of climate change in Integrated Assessment Models (IAMs).
 
-To explore Pymagicc an
-[example notebook](https://mybinder.org/v2/gh/openclimatedata/pymagicc/master?filepath=notebooks/Example.ipynb)
-and small
-[demo app](https://mybinder.org/v2/gh/openclimatedata/pymagicc/master?urlpath=apps/notebooks/Demo.ipynb)
-are available thanks to the [Binder project](https://mybinder.org).
+Pymagicc makes the MAGICC model easily installable and usable from Python and allows for the easy modification of all MAGICC model parameters and emissions scenarios directly from Python.
+In climate research it can, for example, be used in the analysis of mitigation scenarios, in Integrated Assessment Models, complex climate model emulation, and uncertainty analyses, as well as in climate science education and communication.
 
-See http://www.magicc.org/ for further information about the MAGICC model.
+
+See [www.magicc.org](http://www.magicc.org/) for further information about the MAGICC model.
 
 ## Basic Usage
 
@@ -41,6 +42,9 @@ plt.ylabel(u"°C over pre-industrial (1850-1900 mean)")
 
 ![](scripts/example-plot.png)
 
+For more example usage see this [Jupyter Notebook](https://github.com/openclimatedata/pymagicc/blob/master/notebooks/Example.ipynb).
+Thanks to the [Binder project](https://mybinder.org) the [Notebook](https://mybinder.org/v2/gh/openclimatedata/pymagicc/master?filepath=notebooks/Example.ipynb) can be run and modified without installing anything locally. A small interactive [demo app](https://mybinder.org/v2/gh/openclimatedata/pymagicc/master?urlpath=apps/notebooks/Demo.ipynb) using Jupyter Notebook's [appmode extension](https://github.com/oschuett/appmode/)
+is also available.
 
 ## Installation
 
@@ -63,6 +67,8 @@ On OS X `wine` is available in the Homebrew package manager:
 
     brew install wine
 
+It should also be available in other package managers, as well as directly from the [Wine project](https://wiki.winehq.org/Download).
+
 Note that after the first install the first run of Pymagicc might be slow due
 to setting up of the `wine` configuration and be accompanied by pop-ups or
 debug output.

paper/paper.md

@@ -26,8 +26,9 @@ output: pdf_document
 
 # Summary
 
-Pymagicc is a Python wrapper for the Fortran-based reduced-complexity climate carbon cycle model MAGICC [@Meinshausen2011].
-Aiming at broadening the user base of MAGICC^[http://magicc.org], Pymagicc provides a wrapper around the MAGICC binary^[http://magicc.org/download6], which runs on Windows and has been published under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License^[https://creativecommons.org/licenses/by-nc-sa/3.0/].
+Pymagicc is a Python interface for the Fortran-based reduced-complexity climate carbon cycle model MAGICC [@Meinshausen2011].
+Aiming at broadening the user base of MAGICC^[http://magicc.org], Pymagicc provides a wrapper around the MAGICC binary^[http://magicc.org/download6], which runs on Windows and has been published under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License^[https://creativecommons.org/licenses/by-nc-sa/3.0/]. Pymagicc itself is licensed under the GNU Affero General Public License v3.0^[https://www.gnu.org/licenses/#AGPL].
+
 Pymagicc runs on Windows, macOS and Linux and simplifies usage of the model by utilising DataFrames from the Pandas library [@McKinney2010] as a data structure for emissions scenarios.
 To read and write the text-based MAGICC configuration and output files in the Fortran Namelist format Pymagicc utilizes the f90nml library [@Ward2017].
 All MAGICC model parameters and emissions scenarios can thus easily be modified through Pymagicc from Python.
@@ -41,7 +42,7 @@ It has also been used to emulate complex
 atmosphere-ocean general circulation models (AOGCM) from the Coupled
 Model Intercomparison Projects^[https://cmip.llnl.gov/].
 
-Pymagicc also facilitates comparisons with other recently published simple climate models available from or written in Python, such as OSCAR^[https://github.com/tgasser/OSCAR] (@Gasser2017), Pyhector^[https://github.com/openclimatedata/pyhector] (@Willner17, @Hartin2015), and FAIR^[https://github.com/OMS-NetZero/FAIR-pro] (@Millar2017.)
+Pymagicc also facilitates comparisons with other recently published simple climate models available from or written in Python, such as OSCAR^[https://github.com/tgasser/OSCAR] (@Gasser2017), Pyhector^[https://github.com/openclimatedata/pyhector] (@Willner17, @Hartin2015), and FAIR^[https://github.com/OMS-NetZero/FAIR] (@Millar2017.)
 
 It can be installed using `pip` from the Python Package Index ^[<https://pypi.python.org/pypi/pymagicc>].
 To enable Pymagicc to run under Linux and macOS the Wine^[https://www.winehq.org/] compatibility layer is used, usually being available from package managers.