WEEK 11 DAY 01 CONCEPT & ANALYSIS

Balloonist Weather App

Elevating Balloon Navigation: Laying the foundation for a specialized weather and navigation app for hot-air balloon pilots.

1. Introduction & Core Vision

To meet the highly specialized needs of hot-air balloon pilots, this app offers a synthesis of high-resolution meteorological data, real-time telemetry, and advanced pathfinding algorithms, all presented in an intuitive interface optimized for flight conditions.

Core Pillars of Analysis:

Meteorological Data: High-resolution forecasting and wind analysis.
Trajectory Optimization: Lagrangian physics and A* pathfinding.
Real-Time Telemetry: Sensor integration and ground-truthing.

2. High-Resolution Forecasting

Wind Analysis & NWP Ingestion

Targeted NWP Ingestion

Seamlessly ingest data from high-resolution Numerical Weather Prediction (NWP) models (e.g., HRRR, ECMWF), automatically selecting the best available model based on GPS coordinates.

Vertical Profiling

Fetch wind speed and direction at specific pressure levels (e.g., 1000, 950, 900, 850 hPa) to build a precise vertical wind profile.

Shear and Stability Calculations

Calculate "bulk shear" and "micro-shear", and the Bulk Richardson Number to predict wind shear layer turbulence.

3. Trajectory Optimization

Physics Engine

Lagrangian simulations factoring in inertia, buoyancy, drag, and ascent/descent rates.

Flight Profiles

Adjustable settings for sport vs. commercial balloon types and flight aggressiveness.

A* Pathfinding

Probability ellipses to project likely landing zones across altitudes and time steps.

4. Meteorological Visualizations

Hodographs: Wind vectors showing changes with altitude with interactive data points.

Skew-T Log-P: Dynamic thermodynamic charts for inversion and instability identification.

Density Altitude: Real-time lift calculation based on ambient conditions.

5. User Experience & Safety

Flight Safety Features

VFR and Visibility Alerts
Obstacle & Airspace Awareness

Interface Design

Offline-First Functionality
Night Mode (High Contrast)

App Concept

Click to Enlarge

Initial UI/UX Concept for Balloonist Weather App

WEEK 11 DAY 02 METEOROLOGICAL DATA

Data Ingestion & Planning

Integrating high-resolution wind profiles and NWP models for precise flight planning and real-time situational awareness.

1. High-Resolution Data Sources

NOAA HRRR (USA)

3km resolution, hourly updates. Critical for local wind shear and convective activity during flight windows.

ECMWF IFS (Global)

9km native resolution. The gold standard for medium-range planning and synoptic-scale wind patterns.

2. API Retrieval Strategy

// Example Open-Meteo Request for Wind Profile

GET /v1/forecast?latitude=40.71&longitude=-74.01

&hourly=windspeed_1000hPa,winddirection_1000hPa,

windspeed_950hPa,winddirection_950hPa...

&models=ecmwf_ifs04,hrrr

1

Dynamic Model Selection: The backend automatically selects HRRR for US regions and falls back to ECMWF/GFS globally for optimal resolution.
2

JSON Normalization: Raw model outputs are normalized into a consistent "Wind Profile" object containing speed/direction at 100ft intervals.

3. Planning & In-Transit Display

Planning Mode (T-24h)

Focus on "Launchability" windows. Interactive Skew-T diagrams help identify morning inversions and mid-day gust fronts.

• Window Recommendation Engine
• Multi-model Comparison (Consensus)
• Estimated Landing Zone Probabilities

In-Transit Mode (Active Flight)

Focus on "Immediate Decision Support". High-contrast data overlays and offline-first wind vector maps.

• Real-time Vertical Profile via GNSS
• Forecast vs. Actual Drift Correction
• Proximity Alerts for Hazardous Shear

4. Data Providers & API Access

Open-Meteo (Recommended)

NO KEY REQUIRED

High-resolution HRRR (US) and ECMWF (Global) forecasts.

Steps: Use the API Configurator at open-meteo.com. Select Wind Speed/Direction at pressure levels (1000hPa to 10hPa).

ECMWF

ACCOUNT REQUIRED

The most accurate global wind models (IFS).

Steps: Register at apps.ecmwf.int -> Accept License Terms -> Retrieve API Key from User Profile.

NOAA NWS

USER-AGENT ONLY

Real-time US-specific data and HRRR models.

Steps: Include a unique User-Agent header (e.g., App Name + Contact Email) in your HTTP requests.

Windy.com API

DOMAIN KEY

Rendering beautiful wind maps and particle animations.

Steps: Login to Windy -> Point Forecast API -> Generate key for your domain (52weekchallenges.com).

WEEK 11 DAY 03 TRAJECTORY OPTIMIZATION

Trajectory Optimization

Solving the 4D optimization problem of balloon flight through vertical profiling and advanced pathfinding algorithms.

Trajectory optimization for hot air balloons is a 4D optimization problem involving latitude, longitude, altitude, and time. Because balloons cannot be steered laterally, optimization relies entirely on finding the most advantageous vertical flight profile. Here is how it is done:

1. Lagrangian Physics Engine

A balloon is modeled as a Lagrangian drifter, but because it possesses significant mass and inertia, it does not instantly adapt to the velocity of a new wind layer. A physics engine calculates the balloon's transition through the atmosphere by evaluating three primary forces:

Buoyancy

Based on the envelope's volume and the density difference between the heated air inside and the ambient air outside.

Weight

The total mass of the system, including the envelope, payload, fuel, and ballast.

Drag

The vertical resistance calculated using the Reynolds number for a spherical body moving through a viscous fluid.

Using the user's inputted ascent and descent rates, the engine simulates the craft’s transition through forecast wind layers.

2. A* Pathfinding Algorithm

To find the optimal path to a target, an A* search algorithm is applied to a grid where the "nodes" are altitude layers and time steps.

Cost Functions

The algorithm evaluates flight paths to minimize a cost function. This function considers the Euclidean distance to the goal, combined with the actuation cost, which penalizes the expenditure of finite resources (gas and ballast) required to perform altitude changes.

Admissibility Constraints

At each step, the local wind vector determines which neighboring nodes are realistically reachable, ensuring the algorithm adapts to changing wind fields.

Safety and Uncertainty

The search avoids paths over hazardous areas like large bodies of water or restricted airspace. To account for weather model uncertainty, it can simulate an ensemble of trajectories to output a probability ellipse for the landing zone rather than a single point.

3. HYSPLIT Trajectory Splitting

The HYSPLIT model uses a trajectory splitting method that visualizes potential flow combinations from up to three different starting heights. At specified time intervals, the trajectories split, growing exponentially up to a maximum of 1,024 trajectories. The system then identifies the optimal trajectory that passes closest to the user's desired target, defining the vertical and horizontal flight path the balloonist needs to travel.

Sources and Tools to Achieve This

You can implement or build upon several existing frameworks and open-source tools to achieve trajectory optimization:

NOAA's HYSPLIT Model: A professional atmospheric transport model with a dedicated Balloon Flight Forecasting Tool.

pyBalloon: Open-source Python scripts for simulating tropospheric and stratospheric weather balloons.

ASTRA Simulator: Python-based balloon flight planner developed by the University of Southampton.

BLIiPSim v2: Advanced trajectory prediction system using React and the Open-Meteo API.

Leaflet Predictor (Tawhiri): Web-based tool for predicting flight paths and landing locations.

WEEK 11 DAY 04 REAL-TIME TELEMETRY

Real-Time Telemetry

Turning hot-air balloons into live meteorological sensors for continuous navigation refinement and forecasting.

Real-time telemetry turns a hot-air balloon into a live meteorological sensor, gathering data to continuously refine navigation and forecasting. Here is how this component can be implemented and the tools available to achieve it:

How Real-Time Telemetry is Implemented

Smartphone GNSS and IMU Integration

The most accessible method is leveraging the sensors in off-the-shelf smartphones. By capturing consecutive 3D GNSS positions (longitude, latitude, altitude) and the elapsed time, the app calculates the balloon's displacement to determine wind speed and direction. Furthermore, the app can access the phone’s Inertial Measurement Units (IMUs)—such as accelerometers, gyroscopes, and magnetometers—to record the gondola's attitude, angular velocity, roll, and pitch,.

Data Transmission and Caching

The collected location and sensor data must be transferred to a server via standard telecommunication (cellular) networks to update forecasts in real-time,. Because cellular service is often spotty at higher altitudes or in remote landing areas, the application must be built with offline support, using Service Workers and local storage (such as IndexedDB) to cache data until the network connection is restored.

Dynamic Trajectory Correction (Ground-Truthing)

By comparing the balloon's actual GPS-derived ground track against the initially forecasted wind models, the app can immediately detect discrepancies and adjust its trajectory predictions mid-flight. Additionally, algorithms can analyze the "noise" or short-term fluctuations in the GPS and accelerometer signals to infer micro-scale turbulence, giving the pilot a real-time "ride quality" metric.

PiBal (Pilot Balloon) Tracking

Before launch, pilots often release a small helium balloon to observe the lowest wind layers. The app can facilitate tracking the PiBal's azimuth and elevation over time, allowing the pilot to feed actual launch-site wind profiles into the app to calibrate the model right before taking off.

Available Sources and Tools to Help You Build It

Native Mobile OS APIs: You do not need to build raw sensor processing from scratch. Operating systems like Android process the raw physical signals from built-in inertial units (e.g., Bosch BMI160 and BMM150) through dedicated APIs,.

BFA Wind Explorer: App developed by the Balloon Federation of America designed specifically for profiling real-time wind speed and direction using a helium balloon.

IGRA (Integrated Global Radiosonde Archive): Near-real-time radiosonde observations from ~800 global stations which can serve to validate and ground-truth your regional forecasts,.

ATC Transponder Networks: If a balloon is equipped with a transponder, it can be interrogated by ATC radars and tracked via platforms like luchtballonradar.nl.

Progressive Web App (PWA) Technologies: Use WebSerial API for external serial GPS devices and Protomaps (PMTiles) for offline vector maps stored locally.

Open Source API Insights

Based on the provided sources, there is no single "open source API" explicitly named that is dedicated solely to the transmission of real-time hot-air balloon telemetry. However, the sources outline how you can enable this functionality using native device APIs alongside open-source predictive and weather APIs:

1. Native Mobile OS APIs for Data Collection

To capture real-time telemetry from the balloon, developers rely on the native APIs of mobile operating systems (such as Android) rather than external open-source libraries. The smartphone's operating system automatically processes the raw physical signals from built-in hardware (such as the Bosch BMI160 inertial unit and BMM150 magnetometer). Applications can then use dedicated Java APIs to retrieve ready-to-use 3D coordinates, altitude, orientation, roll, and pitch data directly from the device.

2. Open-Source APIs for Weather and Trajectory Prediction

Once the telemetry is collected via the device's native APIs, you can feed that data into open-source forecasting and prediction tools to dynamically map the flight:

• Open-Meteo API: Provides seamless access to high-resolution weather models like HRRR and ECMWF.
• Tawhiri API: Utilized by the open-source Leaflet Predictor to predict flight paths and landing locations.
• Open-Source Physics Simulators: Integrate engines like pyBalloon or ASTRA Simulator to model behavior based on incoming telemetry.

3. Real-Time Data Validation Sources

To supplement and validate the telemetry coming from your app, you can pull near-real-time radiosonde observations from the Integrated Global Radiosonde Archive (IGRA), which gathers data from approximately 800 worldwide weather balloon stations.

A Future "Crowd-Sourced" Telemetry Protocol

The sources note that decentralized telemetry is the "next frontier" for micro-weather ballooning. Currently, the community still needs to create a standardized "protocol for sharing real-time, anonymized wind data from app users" so that balloons in flight can act as a network of weather stations, updating models for all other pilots in the area.

WEEK 11 DAY 05 PROTOTYPE & DESIGN

MyDriftCast Prototype

Consolidating the mobile design concept and the functional sample programs for the Balloonist Weather App.

Mobile Design Concept

Screen 1: Dashboard

Features a high-level weather summary, VFR status, and quick-action buttons for planning and launch modes.

Screen 2: Planning

Interactive map for target selection and a detailed vertical wind profile table with automated trajectory simulation.

Screen 3: Live Flight

Dark-mode optimized UI displaying live telemetry, ascent rates, and "Ground Truth" wind drift corrections.

mobile_design_concept.html

Sample Program Implementation

The prototype logic is implemented across several modular Python scripts, proving the technical feasibility of the core pillars:

01

Forecasting (1_forecasting.py)

Communicates with the Open-Meteo API to fetch wind speed and direction at specific pressure levels (1000hPa, 900hPa, 850hPa) and calculates vertical wind shear.

02

Trajectory Simulation (2_trajectory.py)

A Lagrangian physics engine that simulates balloon ascent and horizontal drift through multiple atmospheric layers based on forecast data.

03

Visualizations (4_visualizations.py)

Generates mathematical hodographs and trajectory plots using Matplotlib to help pilots visualize the flight path.

Vertical Wind Hodograph

Simulated Flight Path

Interactive Design Prototype

Experience the MyDriftCast interface below. Click the buttons to navigate between screens.

Current Location

Albuquerque, NM

68°F

Clear Skies • Surface Wind: 4kts SE

VFR CLEAR

Launchability

Tomorrow Morning

06:00 AM - 09:30 AM

Good

WEEK 11 DAY 06 INFRASTRUCTURE & SKELETON

Initial Skeleton & Sanity Check

Establishing the core application architecture and validating end-to-end connectivity between mobile and cloud layers.

Infrastructure & Connectivity

Program Skeleton

The initial code skeleton has been established, defining the modular structure for weather ingestion, trajectory calculation, and telemetry handling.

Core Business Logic Layer established
API Service wrappers implemented
Mobile state management scaffolding

Sanity Check Results

Completed a full sanity validation to confirm the integrity of the deployed environment.

GCP Infrastructure Deployment: Verified
Mobile App to GCP Connectivity: Verified
Firebase Real-time Sync: Verified

WEEK 11 DAY 07 FINAL PROTOTYPE & SOURCE

Final Prototype & Source Code

The complete codebase and deployment guide for the MyDriftCast Balloonist navigation system.

Source Code Repository

mydriftcast Repository

Access the final code for the Flutter mobile application, GCP Cloud Functions, and core trajectory physics engine.

Clone via GitLab

Essential Configuration Files

firebase_options.dart

Why it's required: Contains the auto-generated platform identifiers for Android, iOS, and Web. This file is critical for the application's runtime initialization of the Firebase suite.

Generated via: flutterfire configure

GoogleService-Info.plist

Why it's required: The iOS-specific identity file. Used by the native Firebase SDK to link the mobile binary with the cloud project's security rules and services.

Source: Firebase Console App Settings

firebase.json

Why it's required: Instructs the Firebase CLI on deployment paths, hosting behaviors, and global configurations for the cloud-side infrastructure.

Created via: firebase init

Important: These files must be manually added to the project paths before build execution as they are excluded from the repository for security.