# Numerical Fit Modeling for Temperature Mitigation in
## 5 Conclusions  
The goal was to show that numerical fit can be an alternative to more complex analysis. This was needed because only a few cases had been developed, and they were all in humid regions.  
Key results were that (1) the numerical fit procedure discussed in Section 2 can model air temperature changes when plumes of calcite are placed above cities, (2) the numerical fit procedure and the supercomputer model of the previous work produce similar results, but the supercomputer results show lower changes in temperature, (3) the differences in temperatures between the methods are due to variations in how advection is handled, and (4) both methods have advantages with the supercomputer method representing an average and the numerical fit representing the peak benefit in the core urban area of the city.  
Calcite reflects shortwave radiation more efficiently than longwave radiation, so as an aerosol it is effective at cooling the ground surface. Plumes of calcite can reduce temperatures in cities.  
Placing calcite in the atmosphere in any region will reduce solar radiation. The amount of reduction may be lower in humid areas.  
A numerical fit model was created that estimated temperatures with simple equations for heating and cooling rates. The model needed tuning whenever a new air mass entered the study area because the properties of the air changed. The fit model produced results similar to those of a SCAM6 model by [PERSON] [6] but with bigger temperature changes expected. A benefit of the numerical fit method is that it uses actual temperatures, so it can be used for weather forecasting during a mitigation. Accounting for advection in the numerical fit model makes it similar to the results from SCAM6, but the results vary geographically. Further, under the plume of calcite, the temperatures become less affected by advection and so would approach the results from the numerical fit model.  
In arid regions, there is much less interaction of aerosols with clouds, so the analysis of temperature changes can be more simply modeled. The SCAM6 cases are not available in arid regions, so the numerical fit model should be applied. To apply this to humid regions, existing data about cloud interaction are necessary.  
For each city where this is applied, a new model must be created. The heating and cooling rates vary by geography. The methods are generalizable to other arid cities, but the results are not. Section 3.1 illustrates that this method can be applied to humid cities. However, it was necessary to have extensive data about the clouds that were present. This is more data than are found in weather reports. Therefore, to apply this to humid cities requires a modification to account for clouds such as CONCLD or other equivalent data.  
Several economic, health, social, and ecological issues should be considered. Those are outside of the scope of this paper.  
This research received no external funding.  
Not applicable.  
Data Availability Statement: Data are available at DOI: [[http://doi.org/10.17632/n5](http://doi.org/10.17632/n5) kkn59j7h.1]([http://doi.org/10.17632/n5](http://doi.org/10.17632/n5) kkn59j7h.1) and by contacting the author. Data includes instructions to modify SCAM6, code, input data, output data, analysis of output and numerical models.  
The author declares no conflicts of interest.