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Joss_Paper/paper.md

@@ -28,20 +28,16 @@ bibliography: paper.bib
 # Summary
 
 AixWeather is a tool for generating weather data for building energy system simulations. 
-It can be used to retrieve, format, enrich and ultimately export weather data in various file formats, 
+It can be used to retrieve, format, enrich, and ultimately export weather data in various file formats, 
 including .epw (EnergyPlus) and .mos (AixLib).
 It addresses the challenges researchers and industry players face in obtaining accurate and 
 formatted weather data by providing a streamlined process.
 
 **Key features of AixWeather**:
 
-*Data retrieval*: AixWeather can directly retrieve data from the German weather provider DWD, and 
-supports historical, recent and forecasted weather data retrieval. It also supports the upload 
-of test reference years (TRY) from the DWD and .epw files from EnergyPlus. A custom weather data 
-upload is also supported, which depending on the data structure, needs to be adjusted by the user.
+*Data retrieval*: AixWeather can directly retrieve data from the German weather provider DWD and supports historical, recent, and forecasted weather data retrieval. It also supports uploading test reference years (TRY) from the DWD and .epw files from EnergyPlus. A custom weather data upload is also supported, but depending on the import structure, the user needs to adjust the transformation code.
 
-*Data conversion*: AixWeather converts this raw weather data from various sources into a 
-defined core format and from there into the desired export format.
+*Data conversion*: AixWeather converts this raw weather data from various sources into a defined core format and, from there, into the desired export format.
 
 *Data accuracy*: AixWeather ensures data accuracy by taking into account critical factors that are 
 often overlooked in custom solutions, including consideration of time zones, 
@@ -54,76 +50,60 @@ from the available weather- and metadata.
 *Flexibility*: AixWeather offers a modular structure that simplifies the addition of new import and
 output formats, and the maintenance of existing formats.
 
-*Modelica ReaderTMY3 compatibility*: A special feature of AixWeather is its support for generating 
-weather data compatible with the Modelica ReaderTMY3 format. This covers a so far unsatisfied need.
-
-[//]: # (AixWeather empowers researchers and professionals working in building energy systems by streamlining )
-
-[//]: # (the weather data generation process. It ensures the availability of high-quality weather data, )
-
-[//]: # (enabling researchers to focus on their essential work in the field of building energy systems.)
+*Modelica ReaderTMY3 compatibility*: A particular feature of AixWeather is its support for generating weather data compatible with the Modelica ReaderTMY3 format. This covers a so far unsatisfied need.
 
 # Statement of need
 
 Building energy simulations, crucial for research in building energy systems, 
 often rely on specific weather data formats. Creating such weather data can be a 
 labor-intensive and error-prone task. AixWeather addresses these challenges by offering 
-a comprehensive solution for pulling, transforming, enriching and exporting weather data from 
+a comprehensive solution for pulling, transforming, enriching, and exporting weather data from 
 various sources and formats.
 
-There are tools that focus on generating typical meteorological year (TMY) data, like the PVGIS [@PVGIS.2023]
-from the European Commission, providing TMY exports as .csv, .json and in the .epw format.
+Some tools focus on generating typical meteorological year (TMY) data, like the PVGIS [@PVGIS.2023] from the European Commission, which provides TMY exports in .csv, .json, and .epw formats.
 EnergyPlus [@EnergyPlus.2017], a widely used building energy simulation tool, also provides a 
 weather data converter to cover the needs of its users, again only supporting the .epw format.
-There exist only limited tools for importing and converting real, historic or forecast, weather 
+Only limited tools exist for importing and converting real, historical, or forecast weather 
 data to building energy simulation formats.
-The same holds true for Test Reference Years (TRY) from the German weather service (DWD). 
+The same holds for Test Reference Years (TRY) from the German Weather Service (DWD). 
 Also, there is a lack of tools supporting conversions to the ReaderTMY3 format.
-The ReaderTMY3 is a modelica model of the well established open source library Buildings
+The ReaderTMY3 is a Modelica model of the well-established open-source library Buildings
 [@WetterZuoNouiduiPang.2014].
-Other libraries such as the open source library AixLib [@Maier.2023] import this model
+Other libraries, such as the open-source library AixLib [@Maier.2023], import this model
 to handle weather data.
-Often user of these libraries, which do not have a TMY3 file at hand, get stuck or invest a lot of 
+Often, users of these libraries, which do not have a TMY3 file at hand, get stuck or invest a lot of 
 time to convert their weather data to the required format.
-Solving this problem, was the initial motivation to develop AixWeather.
-Now, AixWeather is used by users of the open source library AixLib on a regular basis. Due to the 
-recent open source release and the lack of a citable reference, there is no citation yet.
-Though, it does not only cover the needs of the AixLib users, but also those who need real 
+Solving this problem was the initial motivation behind developing AixWeather.
+Now, AixWeather is regularly used by users of the open-source library AixLib. Due to the 
+recent open source release and the lack of a citable reference, there has yet to be a citation.
+However, it does not only cover the needs of the AixLib users but also those who need real 
 weather data, be it historical or forecasted, in a format that can be used in building energy 
 simulations. 
-Now AixWeather also covers the aforementioned needs, making 
-it a valuable tool not only for researchers that work with the ReaderTMY3 format.
+Now, AixWeather also covers the needs mentioned above, making 
+it a valuable tool, not only for researchers who work with the ReaderTMY3 format.
 
 
 # Accessibility
 
-AixWeather can be accessed through the repository itself (https://github.com/RWTH-EBC/AixWeather)
-, e.g. to incorporated in simulation 
-automation workflows.
-For manual weather data generation we recommend our locally hosted web application at 
-https://aixweather.eonerc.rwth-aachen.de, omitting the need to set up an environment.
+AixWeather can be accessed through the GitHub repository itself (https://github.com/RWTH-EBC/AixWeather)
+, e.g., to be incorporated in simulation automation workflows.
+For manual weather data generation, we recommend our locally hosted web application at 
+https://aixweather.eonerc.rwth-aachen.de, which omits the need to set up an environment.
 The web application's source code is open source and hosted in a separate repository at 
 https://github.com/RWTH-EBC/AixWeather-WebApp.
 
 # Structure of AixWeather
 
 \autoref{fig:AixWeatherStructure} shows the current data flow and structure of AixWeather. 
-Starting from the import layer, the imported data is transformed into a core format, and from there 
-into the
-desired export format. The core format is a defined format that allows for easy conversion to
-different export formats. The pass-through handling avoids avoidable interpolation-related 
-smoothing, through storing the original unsmoothed time series and, if the shift sequence 
-allows, overwriting the smoothed time series in the output file.
+First, the data is imported as raw as possible. The imported data is transformed into a core format and, from there, into the desired export format. The core format is a defined format that allows for easy conversion to different export formats. The pass-through handling avoids avoidable interpolation-related smoothing by storing the original unsmoothed time series and, if the shift sequence allows, overwriting the smoothed time series in the output file.
 
 ![Structure of AixWeather.\label{fig:AixWeatherStructure}](Overview_WeatherTool.png)
 
 # Acknowledgements
 
-We acknowledge contributions from Michael Mans, Felix Nienaber and Ana Constantin for providing 
+We acknowledge contributions from Michael Mans, Felix Nienaber, and Ana Constantin for providing 
 some functional base code.
-We also want to thank Firas Drass and Felix Rehmann from the TU Berlin for their support on the 
-WebApp.
-Last but not least, we want to thank Fabian Wüllhorst and David Jansen for their support with the 
-quality management through continuous integration.
+We also want to thank Firas Drass and Felix Rehmann from TU Berlin for their support on the WebApp.
+Lastly, we want to thank Fabian Wüllhorst and David Jansen for their support with quality management through continuous integration.
 
 # References