The Weather.csv and Radiation.csv are from Baltimore, MD, Baltimore-Washington Intl AP
USAF	WBAN	YEAR
724060 	93721 	2018

The LCScale_12x12_alt_3 test case considers Flag_Scenario_CoolAir_LandCover = 3 & TreeCanopyCover_overImpervious_frac = 0.45, and ...
... Scenario_CoolAir_Base_TCI_to_TC_frac = 0.15, Scenario_CoolAir_Alternative_TC_Min_frac = 0.0,  Scenario_CoolAir_Alternative_TC_Max_frac = 0.3, and ...
... Scenario_CoolAir_Alternative_IC_replacing_TC_frac = 0.5, and Scenario_CoolAir_Alternative_IC_Max_frac = 0.9

This scenario will create additional impervious cover to go under trees, but only to the extent of the Scenario_CoolAir_Base_TCI_to_TC_frac, and ...
... will make tree cover between the minimum and maximum value of Scenario_CoolAir_Alternative_TC_Min_frac and Scenario_CoolAir_Alternative_TC_Max_frac, and ...
... any removed tree cover will be replaced with impervious cover based on Scenario_CoolAir_Alternative_IC_replacing_TC_frac = 0.5, and ...
... will make impervious cover to the maximum of Scenario_CoolAir_Alternative_IC_Max_frac for land cover in the NLCD Class 21 to 24. 

It generates z_map_ImperviousNoTree.asc, z_map_ShortVegCover.asc, z_map_SoilCover.asc, z_map_TreeOnImpervious.asc, z_map_TreeOnPervious.asc. 

The 12 x 12 array for the map inputs of imperviouscover.txt and treecover.txt span the range of 0 to 100% with 144 unique cases.  

Typically, tree cover and impervious cover increment from 0, 1, 10, 20, .., 90, 100% or from 0, 10, 20, .., 90, 99, 100%. 
This progression can capture distinct changes near the extreme land cover values when Flag_UrbanCanyon = 1. 

Use a BlockGroupMap.txt file that contains 144 distinct values to obtain temperature outputs across these 144 cases. 
Use the <PrintBlockGroupRange>1,144</PrintBlockGroupRange> to generate BlockGroup1.txt or BlockGroupDaily1.txt.

To graph and envision the change of temperature across these 144 cases, run the Python script z_Map_CoolAirTair_TC-IC_combinations.py.
The script should be stored in the folder \TestingFilesAndScript\. This Python script takes command line input of the path to the output folder. 
A successful run typically requires at least 5 days of output. 
After launching the script in the Xterm window, there will be a prompt for array size (11 or 12) and inputs options (daily or hourly).
You can rotate the plot while viewing. 
Once the script is complete, graphic files are stored in the output subfolder, called Daily_Metrics (or Hourly_Metrics). 

This stored version of the test case has not been run for the full 144 cases in order to save storage space and decrease SVN transfer time. 


This case is also used to test the 32618 WGS 84 / UTM zone 18N projection, specifically for a location of Baltimore, MD, Baltimore-Washington Intl AP, using the following map parameters:

The reference weather station is placed outside the map:
<Flag_refStation_CoordinateFormat> = GCS
<MapProjection_WKID> = 32618 
<RefWeatherLocationLongitude_dd> = -76.684
<RefWeatherLocationLatitude_dd> = 39.173
<RefWeatherLocationElevation_m> = 42

Map title:
xllcorner = 352401
yllcorner = 4339760

Using an external projection tool, the corresponding WKID 3034 coordinates are: Easting = 354530.97186 m, Northing = 4337325.42988 m
✅ When the model runs correctly, the following debug output should appear in the command prompt:
Reference station (GCS): Longitude = -76.684, Latitude = 39.173 -> Projected (PCS): Easting = 354531 m, Northing = 4337325 m