DATA SCIENCE

Project Title: Regional Analysis (INDIA) of Radiative Cooling Performance in Varying Atmospheric Transparency Windows

Project Description:

We are seeking a skilled and proactive freelancer to conduct a comprehensive study on the performance of our radiative cooling paints in different regions across India, considering the variations in Atmospheric Transparency Windows (ATW) caused by varying water vapor content in the atmosphere. The objective is to analyze how the radiative cooling performance of our paints is influenced by these regional and seasonal variations.

**Project Objectives:**

1. **Water Vapor Data Extraction:**

Utilize satellite data, particularly from Landsat, and tools like Google Earth Engine to extract region-wise humidity and water vapor data, focusing on different seasons. The objective is to compile an extensive dataset for analysis.

2. **ATW Variation Analysis:**

Utilize the extracted humidity and water vapor data to plot the variations in the Atmospheric Transparency Window (ATW) across different regions in India. Understand how ATW fluctuates based on water vapor content and its implications on radiative cooling performance.

3. **Atmospheric Transmittance Data:**

Utilize MODTRAN or similar tools to calculate atmospheric transmittance data, leveraging the knowledge of local humidity levels obtained from satellite data. This will enable a detailed understanding of how transmittance affects radiative cooling potential.

4. **Performance Mapping:**

Calculate the steady-state temperature of the radiative cooling film in different regions based on the transmittance data. Plot the performance of radiative cooling paints across various regions in India, correlating it with the ATW variations and seasonal changes.

**Desired Skills and Qualifications:**

- Proficiency in utilizing satellite data and tools like Google Earth Engine for extracting relevant environmental data.

- Familiarity with MODTRAN or similar tools for atmospheric transmittance calculations.

- Strong data analysis and visualization skills to effectively present the findings in a clear and insightful manner.

- Background in environmental science, remote sensing, climate studies, or related fields would be highly beneficial.

**Deliverables:**

- Comprehensive dataset of region-wise humidity/water vapor data extracted from satellite imagery.

- Detailed analysis and visual representation of ATW variations across different regions in India.

- Calculations of atmospheric transmittance data based on humidity levels.

- Performance mapping of radiative cooling paints in correlation with ATW variations.

- ML model which shows performance forecast of the paint over multiple years and how to optimize it properly

Google Earth Engine open-source code for LST (for water vapor data)

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Datatiede Tilastoanalyysi Kaukotunnistus Ilmastotieteet Machine Learning (ML)

Projektin tunnus: #37245983

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