Update README.md

README.md

@@ -140,23 +140,22 @@ validation period.
 ### Preprocessing
 
 The preprocessing of climate datasets ERA5 and CERRA, extracted from the Climate Data Store (CDS), is a critical step before their utilization in training models. 
-This section defines the preprocessing steps undertaken to homogenize these datasets into a common format. 
-The steps include unit standardization, coordinate system rectification, and grid interpolation. 
-The rationale and methodologies employed in each step are discussed comprehensively, setting a robust foundation for the subsequent training procedure.
+This section defines the preprocessing steps undertaken to homogenize these datasets into a common format. The steps include unit standardization, coordinate system 
+rectification, and grid interpolation. The methodology employed in each step is discussed comprehensively in the following paragraphs:
 
-1. Unit Standardization: A preliminary step in the preprocessing pipeline involved the standardization of units across both datasets.
-  This was imperative to ensure a uniform unit system, facilitating a seamless integration of the datasets in later stages.
-  The units in both datasets were scrutinized and amended to adhere to a common unit system, thereby eliminating any discrepancies that could hinder the analysis.
+- Unit Standardization: A preliminary step in the preprocessing pipeline involved the standardization of units across both datasets.
+  This was imperative to ensure a uniform unit system, facilitating a seamless integration of the datasets in later stages. 
 
-2. Coordinate System Rectification: The coordinate system of the datasets was rectified to ensure a coherent representation of geographical information. 
-  Specifically, the coordinates and dimensions were renamed to a standardized format with longitude (lon) and latitude (lat) as designated names. 
-  The longitude values were adjusted to range from -180 to 180 instead of the initial 0 to 360 range, while latitude values were ordered in ascending order, 
+- Coordinate System Rectification: The coordinate system of the datasets was rectified to ensure a coherent representation of geographical information.
+  Specifically, the coordinates and dimensions were renamed to a standardized format with longitude (lon) and latitude (lat) as designated names.
+  The longitude values were adjusted to range from -180 to 180 instead of the initial 0 to 360 range, while latitude values were ordered in ascending order,
   thereby aligning with conventional geographical coordinate systems.
 
-3. Grid Interpolation: The ERA5 dataset is structured on a regular grid with a spatial resolution of 0.25º, whereas the CERRA dataset inhabits a curvilinear
-   grid with a Lambert Conformal projection of higher spatial resolution (0.05º). To overcome this disparity, a grid interpolation procedure was initiated.
-  This step was crucial to align the datasets onto a common regular grid (with different spatial resolution), thereby ensuring consistency in spatial representation.
-  The interpolation transformed the CERRA dataset to match the regular grid structure of the ERA5 dataset, keeping its initial spatial resolution of 0.05º (5.5 km).
+- Grid Interpolation: The ERA5 dataset is structured on a regular grid with a spatial resolution of 0.25º, whereas the CERRA dataset inhabits a curvilinear grid with
+  a Lambert Conformal projection of higher spatial resolution (0.05º). To overcome this disparity in the grid system, a grid interpolation procedure is performed.
+  This step is crucial to align the datasets onto a common format, a regular grid (with different spatial resolutions), thereby ensuring consistency in spatial
+  representation. The interpolation transformed the CERRA dataset to match the regular grid structure of the ERA5 dataset, keeping its initial spatial resolution
+  of 0.05º (5.5 km).
 
 ### Speeds, Sizes, Times