PHOENIX COLLEGE HIGH-ALTITUDE BALLOONING

MISSION COMMS
MISSION SUPPORT

Frequently Asked Questions

General program answers plus dedicated Spring 2026 data and visualization answers for presentations and technical review.

General Questions

PROGRAM

NASA ASCEND is a near-space STEM research program where students design, build, launch, and recover high-altitude balloon payloads while collecting and analyzing real scientific flight data.

Phoenix College students from multiple STEM disciplines participate, supported by faculty mentors and NASA ASCEND partner resources.

Students gain experience in systems engineering, telemetry interpretation, payload integration, field operations, flight safety planning, and technical communication.

Each launch follows pre-flight checklists, weather review, field-team role assignments, tracking redundancy, and post-recovery procedures with documented chain-of-custody for payload data.

Use the Join Team application on the main site, or contact mission staff at pcnasaascend@gmail.com for onboarding, role options, and next mission cycle dates.

Data & Visuals (13)

SPRING 2026

The dashboard is compiled directly from the raw multisensor CSV collected during Spring 2026 flight operations. This raw file is preserved in docs/raw-data and processed into the telemetry JSON used by the charts.

The compiled Spring 2026 payload dataset contains 737 telemetry rows for altitude and sensor series.

Altitude, PM0.3, PM0.5, PM1.0, PM2.5, PM5.0, PM10 particle counts, CO2 concentration, temperature, and humidity.

Pre-flight calibration and baseline offsets can appear before ascent. The trend and profile still correctly show the full climb, peak, and descent behavior.

The profile reaches approximately 83,661 ft in the compiled dataset used for the visual dashboard.

APRS GPS track products are separated from Geiger payload telemetry to avoid schema conflicts. This ensures each visualization uses the correct data structure.

The Spring 2026 section uses interactive browser-rendered charts, including hover tooltips and responsive resizing for desktop and mobile.

The telemetry JSON is reproducibly generated from raw CSV source files. Verification compares each output array against raw columns to confirm point-by-point alignment.

Displaying all six Geiger payload PM channels (PM0.3, PM0.5, PM1.0, PM2.5, PM5.0, PM10) helps compare particle-size behavior across ascent, peak, and descent altitude bands.

Focus on source traceability (raw file to chart), altitude trend shape, CO2 and PM behavior by altitude, and whether displayed metrics match documented mission telemetry ranges.

For better scientific quality, common methods include baseline correction, moving-average or median filtering to reduce sensor noise, outlier detection using z-scores/IQR thresholds, interpolation for short missing segments, and altitude binning to compare atmospheric layers consistently. These methods improve trend reliability without over-smoothing real flight events.

Core equations include finite-difference vertical rate (Δh/Δt), Haversine great-circle distance for horizontal motion, and standard-atmosphere barometric relations to estimate pressure from altitude. Additional high-value methods are linear/polynomial regression for trend extraction and correlation analysis (r) between altitude and variables like CO2, temperature, and particle channels.

Use uncertainty-aware reporting: document sensor limits, report confidence intervals or error bounds, show before/after filtering criteria, and avoid drawing conclusions from single-point anomalies. Strong reviews also require unit consistency, reproducible assumptions, and sensitivity checks showing how results change if filtering or thresholds are adjusted.