Sun spectrum model — contributor reference

The Light & Sun lens reconstructs solar spectral irradiance and convolves it through published action spectra to derive per-channel doses. This page documents the model, the action spectra, and the calibration choices for anyone touching js/sun-spectrum.js or js/sun-uvdata.js.

Pipeline

Atmosphere (UV index, ozone, cloud cover, temperature, altitude)
        │  via js/sun-uvdata.js — multi-source ladder:
        │     selfhost (CAMS-mirrored) → CAMS direct → NOAA NWS → Open-Meteo
        │     → offline zenith-angle fallback → manual entry
        ▼
Solar zenith angle (NOAA solar position algorithm, ±1° accuracy)
        │  js/sun-uvdata.js → solarZenithAngle(date, lat, lon)
        ▼
Bird-Riordan-style clear-sky reconstruction
        │  js/sun-spectrum.js → reconstructSpectrum()
        │  280-2500 nm at 5 nm resolution (89 bands)
        │  Extraterrestrial × Rayleigh × Ozone (Bass-Paur) × Aerosol × Cloud
        ▼
Per-channel convolution with action spectra
        │  js/sun-spectrum.js → computeChannelDoses()
        │  8 channels × 89 bands × 5nm bandwidth
        ▼
Dose accumulator (channel-au, internal unit)
        │  Mapped to qualitative tier (none/low/moderate/good/strong)
        │  via channelTier() vs CHANNEL_DISPLAY[k].dailyTarget
        ▼
UI (channel pills, channel cards, AI context)

Wavelength grid

WAVELENGTHS = [280, 285, 290, ..., 2495, 2500]  // 89 bands at 5nm

5 nm matches CAMS UV index forecast resolution and is fine enough for the action-spectrum convolutions. Coarser grids would lose the sharp UVB peak; finer grids would oversample without improving accuracy.

Action spectra (per channel)

Each channel has a closed-form action spectrum function returning a 0–1 weighting per nm. Defined in js/sun-spectrum.js:

Channel	Function	Reference	Peak	Bandwidth
`vitamin_d`	`vitaminDAt(nm)`	CIE 174:2006 previtamin-D3 (MacLaughlin 1982)	297 nm	~252–330 nm
`pomc`	`erythemalAt(nm)`	CIE S 007 / ISO 17166:1999 (McKinlay-Diffey 1987)	297 nm	~250–400 nm
`no_cv`	`noReleaseAt(nm)`	Liu 2014 / Oplander 2009	345 nm	300–410 nm Gaussian
`violet_eye`	`opn5At(nm)`	OPN5/neuropsin — Buhr 2019, Yoshikawa 2019	380 nm + 471 nm	320–540 nm
`circadian`	`melanopicAt(nm)`	CIE S 026:2018 (ipRGC / melanopsin)	490 nm	380–720 nm Gaussian
`nir_solar`	`nirSolarAt(nm)`	Optical tissue window (Jacques 2013)	900 nm	600–1400 nm
`pbm_red`	`pbmRedAt(nm)`	Karu 2010 / Hamblin 2018 (cytochrome c oxidase band)	660 nm	600–700 nm
`pbm_nir`	`pbmNirAt(nm)`	Karu 2010 / Hamblin 2018 (cytochrome c oxidase band)	850 nm	700–1100 nm

The CCO action spectrum (ccoAt) in the file is an unused helper that sums Karu’s four absorption bands; PBM channels use the simpler narrowband Gaussians for cleaner therapy-device dose math. The citation registry is duplicated in data/sun-action-spectra.json for AI context grounding.

Bird-Riordan reconstruction

Implemented as reconstructSpectrum() with these terms per wavelength:

E(λ) = E0(λ) × T_Rayleigh × T_O3 × T_aerosol × cloudT

Where:

E0(λ) — extraterrestrial spectral irradiance, hardcoded fit to ASTM E490 reference at sample points 280, 300, 320, 340, 360, 380, 400, 420, 450, 500, 550, 600, 650, 700, 800, 900, 1000, 1200, 1500, 2000, 2500 nm with linear interpolation between
T_Rayleigh — exp(-tauR × airMass / 1000) with tauR = (115.6406 / (nm/1000)^4 - 1.335 / (nm/1000)^2) × altScale and altScale = exp(-altitudeM / 8000)
T_O3 — exp(-ozoneAbsorption(nm) × airMass × ozoneDU/1000) with Bass-Paur cross-section approximation peaking in the Hartley band (~250 nm)
T_aerosol — exp(-tauA × airMass) with tauA = 0.27 × (nm/500)^-1.14
cloudT — 1 - 0.75 × cloudCover (linear cloud transmission)
airMass — 1 / max(cos(zenithDeg × π/180), 0.001)

Honest accuracy: ±25% relative for our use case (correlation against biomarkers). Not a radiometer. The full Bird-Riordan model has aerosol single-scattering, multiple scattering, and direct/diffuse separation that we deliberately drop for code simplicity. If the lens grows toward research-grade radiometry, re-implement against SMARTS-2.

Channel dose calculation

computeChannelDoses({ spectrum, durationMin, bodyExposureFraction, eyeExposure }) → {
  vitamin_d: number,
  pomc: number,
  no_cv: number,
  violet_eye: number,
  circadian: number,
  nir_solar: number,
  pbm_red: number,
  pbm_nir: number,
}

Per channel:

dose = Σ_λ E(λ) × W(λ) × dλ × duration × gain

Where gain is:

Skin channels (vitamin_d, pomc, no_cv, nir_solar, pbm_*) → bodyExposureFraction (0–1)
Eye channels (circadian, violet_eye) → eyeMultiplier(eyeExposure):
- direct + clear → 1.0
- clear-glasses → 0.85 (blocks UV, passes visible)
- glass-window → 0.4 (passes most visible, blocks NIR + UV)
- polarized → 0.5
- photochromic → 0.3
- blue-blocker → 0.4
- amber/red → 0.2
- sunglasses → 0.05
- closed-eyes, indoor → 0

Eye-channel doses go to zero when eyeExposure is null (no eye exposure logged). Skin channels are unaffected by eye-mode.

Genetic vitamin D context

geneticVitaminDMultiplier(genetics) reads four catalog calls and returns a compound multiplier plus an auditable contributor list:

SNP	Catalog locus	Genotype multipliers
`rs2282679`	`GC` / VDBP marker	`TT: 1.00`, `GT: 0.95`, `GG: 0.85`
`rs10741657`	`CYP2R1`	`AA: 1.00`, `AG: 0.95`, `GG: 0.88`
`rs12785878`	`NADSYN1/DHCR7` region	`TT: 1.00`, `GT: 0.95`, `GG: 0.92`
`rs6013897`	`CYP24A1` region	`TT: 1.00`, `AT: 0.97`, `AA: 0.92`

vitaminDIURaw() multiplies the channel result by this compound value before the per-session and daily caps are applied. Missing or reference calls contribute 1.0. These are conservative heuristic weights for associations with circulating 25-OH vitamin D. They are not genotype-specific intervention responses and do not directly measure skin synthesis, transport, hydroxylation, or personal blood response. The UI therefore describes an effective serum response per modeled UV dose, not genetically calculated vitamin D production. VDR rs2228570 and CYP27B1 rs10877012 remain in the public Genome catalog as informational/mechanistic context but are intentionally excluded from the multiplier because their cited studies do not establish a change in circulating 25-OH vitamin D or UV response. Claim scopes and publication links live in data/snp-health.json.

Safety counters

Two safety counters are computed alongside the channel doses:

Erythemal SED

erythemalSED({ spectrum, durationMin, bodyExposureFraction }) → number

Standard Erythemal Dose, defined as 100 J/m² of CIE-erythemal-weighted irradiance. Converted to a Fitzpatrick-fraction via:

fractionOfMED({ sed, fitzpatrick }) → ratio

With per-Fitzpatrick MED values from Diffey 1991 / GrassrootsHealth (in SED units): { I: 2, II: 2.5, III: 3, IV: 4.5, V: 6, VI: 10 }. Burn-risk is cumulativeMEDToday() (sum across all sessions today).

Retinal UV

retinalUVdose({ spectrum, eyeExposure }) → J/m²

Only counts when eyeExposure.mode === 'direct'. Sums irradiance for λ ≤ 400 nm × duration. Used as a pure safety counter — never recommended to maximize. Sun-gazing protocols are deliberately not supported.

Daily targets

CHANNEL_DISPLAY[k].dailyTarget defines the literature-rough target for “a meaningful healthy daily dose”:

Channel	Daily target (channel-au)
vitamin_d	300
pomc	80
no_cv	5000
violet_eye	8000
circadian	20000
nir_solar	30000
pbm_red	8000
pbm_nir	10000

These map to the qualitative tier function:

ratio = dose / dailyTarget
dose ≤ 0      → 'none'      // tier 0
ratio < 0.20  → 'low'       // tier 1
ratio < 0.55  → 'moderate'  // tier 2
ratio < 1.00  → 'good'      // tier 3
ratio ≥ 1.00  → 'strong'    // tier 4

weeklyChannelTier() uses the same ratios but multiplies the daily target by 7 — keeps a 7-day rollup from being scored against a 1-day expectation (a value that scores “moderate” against daily would otherwise score “low” against weekly). Targets are deliberately rough. They’re not normative — they’re a translation layer so the UI doesn’t show channel-au integers. The AI sees raw dose; users see tiers.

Adding a new channel

Add an entry to CHANNEL_DISPLAY in js/sun.js with icon, label, dailyTarget, and what (user-facing tooltip)
Add an action-spectrum function to js/sun-spectrum.js
Append to the CHANNELS array in the same file with { id, key, fn, label }
Add a row to data/sun-action-spectra.json’s channels block with the citation
Add to the dashboard pill order in js/views.js and the page/detail render order in js/light-channel-view.js
Update js/sun-correlations.js if the channel should be biomarker-correlated
Update tests/test-sun-spectrum.js — assert the channel is in SUN_CHANNELS and has non-zero dose at noon

UV data source

js/sun-uvdata.js resolves the active UV data provider via providerOrder(cfg):

`cfg.mode`	Order
`auto` (default)	selfhost (if URL set) → CAMS hosted relay → Open-Meteo → offline zenith
`selfhost`	selfhost → Open-Meteo
`open-meteo`	Open-Meteo only
`manual`	none (always returns null, manual entry required)

Legacy cams and noaa modes (from earlier v1.7.x dev iterations) auto-migrate to auto on load via getMeteoConfig() so users with stored configs from a pre-shipping build don’t get stuck. CAMS hosted relay is implemented by the public getbased-uvdata companion service. The browser talks only to the same-origin /api/proxy route; the server-side deployment injects any required upstream credential and returns Open-Meteo-shaped atmosphere data. Self-hosters can run the same relay and point Settings → Light & Sun → Sun data source → Self-hosted at their own URL. We deliberately don’t pull CAMS-McRad surface UV — that product is queue-based with pre-registered locations, structurally incompatible with synchronous per-coord serving. The /spectrum endpoint on the relay runs Bird-Riordan reconstruction server-side fed by real CAMS atmosphere, which collapses the model uncertainty band from ±20–45% to ±10–15% in the UV sweet-spot. Source confidence is computed at read time via computeUVConfidence({source, snapshotAgeSec, cloudCover, zenithDeg, uvIndex, isStale, manualOverridden}) — no longer a static per-source number. Stale grid (>24 h) halves the confidence; heavy cloud (>0.8), low sun (zenith >80°), and below-threshold UVI (<2) each multiplicatively discount further. Manual UV-meter readings lock to 1.0; everything else caps at 0.99.

Validation

tests/test-sun-spectrum.js covers ~120 assertions:

Spectrum shape (wavelength array, 5nm grid, 280–2500 nm bounds, non-negative irradiance)
Sun-below-horizon → all-zero spectrum
Atmospheric attenuation (zenith / ozone / cloud / altitude) — directional checks
Channel dose calculation (all channels, body fraction scaling, eye-mode gating, sunglasses → near-zero circadian)
Safety counters (SED scales linearly with duration, Fitzpatrick I burns faster than VI, retinal-UV only in direct mode)
Edge cases (night spectrum, zero-duration session)

Quarterly validation against published clear-sky measurement campaigns (NREL SRRL, NOAA SURFRAD) is the next-tier rigour. Keep that report in the developer docs when it exists; do not treat it as part of the current verified test suite.

Core project

Data model & sync

AI & agents

Feature internals

Security architecture

Operations & release

Sun spectrum model

Sun spectrum model — contributor reference

Pipeline

Wavelength grid

Action spectra (per channel)

Bird-Riordan reconstruction

Channel dose calculation

Genetic vitamin D context

Safety counters

Erythemal SED

Retinal UV

Daily targets

Adding a new channel

UV data source

Validation

​Sun spectrum model — contributor reference

​Pipeline

​Wavelength grid

​Action spectra (per channel)

​Bird-Riordan reconstruction

​Channel dose calculation

​Genetic vitamin D context

​Safety counters

​Erythemal SED

​Retinal UV

​Daily targets

​Adding a new channel

​UV data source

​Validation

Sun spectrum model — contributor reference

Pipeline

Wavelength grid

Action spectra (per channel)

Bird-Riordan reconstruction

Channel dose calculation

Genetic vitamin D context

Safety counters

Erythemal SED

Retinal UV

Daily targets

Adding a new channel

UV data source

Validation