🚀 AstroPlanner: Adverse Weather Likelihood Engine

Challenge: Will It Rain On My Parade? (Earth Science Division)

💡 Project Summary

AstroPlanner is a personalized web application built with HTML, CSS (Tailwind), and JavaScript that helps users quantify the statistical likelihood of adverse weather conditions for a specific location and time of year. Unlike a short-term forecast, AstroPlanner analyzes decades of historical Earth Observation (EO) data patterns to provide a long-range risk assessment for event planning.

⚙️ How It Works (Focusing on Data)

The application simulates a rigorous historical analysis process based on NASA Earth Observation data to calculate probabilities for five adverse conditions.

1. The Personalized Query

The user inputs two critical parameters:

• Location: Latitude and Longitude (to target a specific geographical grid point).
• Time: Month of the year (to target a specific seasonal historical dataset).

2. The Historical Data Engine (Simulation)

For hackathon expediency, the core JavaScript engine (getMockHistoricalProbability) simulates querying and processing NASA's vast historical EO archive.

The data variables simulated (and the source data they represent) include:

Adverse Condition	Simulated NASA EO Variable	Definition of "Very Adverse"
Very Hot	Daily Maximum Temperature ($T_{max}$)	$\ge 90^{th}$ Percentile Historical $T_{max}$ for that month/location.
Very Cold	Daily Minimum Temperature ($T_{min}$)	$\le 10^{th}$ Percentile Historical $T_{min}$ for that month/location.
Very Wet	Precipitation Rate/Total	$\ge 95^{th}$ Percentile Historical Precipitation (e.g., from GPM data).
Very Windy	Surface Wind Speed	$\ge 95^{th}$ Percentile Historical Wind Speed (e.g., from MERRA-2 Reanalysis).
Very Uncomfortable	Composite Discomfort Index (Heat/Humidity)	Derived from a weighted average of historical $T_{max}$ and Humidity data, indicating risk of heat stress.

3. Likelihood Calculation

The engine calculates the $\text{Likelihood}$ ($\text{Probability}$) for each condition based on the historical frequency of that condition meeting the "Very Adverse" threshold:

$$\text{Likelihood} = \frac{\text{Number of Adverse Days (Historical)}}{\text{Total Number of Historical Days}} \times 100%$$

The resulting percentage is displayed on a color-coded risk gauge.

🛠️ Technology Stack

• Frontend: HTML5, CSS3
• Styling: Tailwind CSS (for rapid, responsive design)
• Logic: Vanilla JavaScript

🌐 Quick Start Guide

AstroPlanner is a single-page application and does not require a server or complex dependencies.

1. Clone the Repository (or Save the File): Save the provided code as index.html.
2. Open in Browser: Double-click index.html to run the application locally in any modern web browser.
3. Test Coordinates: Try coordinates for different seasons:
   • Los Angeles, CA: Lat: 34.05, Lon: -118.25
   • Antarctica (Simulated Winter): Lat: -80, Lon: 0

🏆 How AstroPlanner Meets the Challenge Criteria

Criteria	AstroPlanner Feature
Personalized Interface	User-defined Latitude, Longitude, and Month creates a customized query.
NASA Data Utilization	The core logic is structured to represent the analysis of historical NASA Earth Observation data (GPM, MERRA-2, etc.).
Adverse Conditions	Directly addresses all five conditions: Very Hot, Very Cold, Very Windy, Very Wet, and the composite Very Uncomfortable.
Likelihood Output	The results are provided as clear, color-coded probability percentages, fulfilling the requirement for a likelihood assessment, not a forecast.