Monograph A · NASA Space Apps Challenge 2026 · Campinas, SP, Brazil

42 Years of NASA POWER Trends Across Brazilian Biomes: Seasonal Mann-Kendall + Theil-Sen Attribution of Surface Solar Brightening (1984–2025)

Author: Luiz Antonio Gois Junior (Team Curva do Pato) · Platform: Cockpit-OMNI (www.curveofduck.xyz) · Source Code: github.com/SunLuiz/Curva_do_Pato (MIT)

Abstract (Answer-First Summary): Over 42 continuous years of monthly NASA POWER (MERRA-2 / CERES) observations (1984-01 to 2025-12, n = 504 months per series), Cockpit-OMNI evaluates seven Earth system variables across three contrasting Brazilian biomes using Seasonal Mann-Kendall (period = 12, α = 0.05) and deseasonalized Theil-Sen regression (95% CI). All three stations warmed significantly (Campinas-SP +0.4091 °C/dec, Petrolina-PE +0.3012 °C/dec, Manaus-AM +0.3065 °C/dec) and lost rainfall, while surface shortwave solar irradiance increased everywhere. Crucially, the exact same statistical engine delivers opposite physical causal verdicts: solar brightening in Petrolina-PE (-0.9647 %/dec cloud attenuation, p = 2.833e-09; clear-sky null p = 0.2901) and Manaus-AM (-0.8552 %/dec cloud attenuation, p = 3.015e-08; clear-sky null p = 0.7686) is cloud-driven, whereas Campinas-SP exhibits stationary clouds (p = 0.9476) alongside surging clear-sky irradiance (+0.1897 MJ/m²/day/dec, p < 1e-16), isolating an aerosol / clear-sky atmospheric transparency shift. Monthly 2m wind speed (WS2M) shows zero significant trend at any station (p = 0.4890 / 0.1734 / 0.4512) and is explicitly barred from sub-hourly ramp claims.

1. How does Cockpit-OMNI compute non-parametric climate trends without seasonal distortion?

Direct Answer: Cockpit-OMNI computes trends deterministically in both Python (pymannkendall + scipy.stats.theilslopes) and pure browser JavaScript (frontend/src/engine/trend.js) by comparing matching calendar months across 42 years (Seasonal Mann-Kendall, period = 12), removing NASA POWER annual summary rows (YYYY13) and -999.0 sentinel values prior to estimating median deseasonalized Theil-Sen slopes.

Ordinary least-squares regression fails on multi-decade climatology because single El Niño spikes skew the slope and regular summer-winter oscillations mask secular change. For example, in Campinas-SP all-sky irradiance (ALLSKY_SFC_SW_DWN), an ordinary un-seasonalized Mann-Kendall test produces p = 0.1968 (falsely labeling the series "no trend"), whereas Seasonal Mann-Kendall isolates the true decadal signal at p = 0.0008616 (τ = +0.103, +0.1621 MJ/m²/day/dec).

2. Complete 21-Metric Empirical Benchmark (NASA POWER, 1984–2025, n = 504 Months)

Direct Answer: Every metric below is stored in the open zero-key cache of www.curveofduck.xyz/cockpit and verified automatically by scripts/verify_answers.mjs against the frozen 2026-11-14T15:04 UTC snapshot.

2.1 Campinas-SP (-22.90, -47.06) — Atlantic Forest / Cerrado Transition (Aerosol / Clear-Sky Driven)

Variable Unit Slope / Decade 95% Confidence Interval 42-yr Total Seasonal τ Seasonal p-value Verdict (α = 0.05)
T2M°C+0.4091[+0.3329, +0.4891]+1.718+0.293< 1e-16Increasing
PRECTOTCORRmm/day-0.2724[-0.3881, -0.1559]-1.144-0.1491.59e-06Decreasing
RH2M%-1.6601[-1.9845, -1.3400]-6.972-0.296< 1e-16Decreasing
ALLSKY_SFC_SW_DWNMJ/m²/day+0.1621[+0.0591, +0.2667]+0.681+0.1030.0008616Increasing
CLRSKY_SFC_SW_DWNMJ/m²/day+0.1897[+0.1577, +0.2232]+0.797+0.322< 1e-16Increasing
CLOUD_ATTEN_PCT%+0.0378[-0.3877, +0.4698]+0.159+0.0020.9476Null (no trend)
WS2Mm/s-0.0042[-0.0191, +0.0103]-0.018-0.0210.4890Null (no trend)

2.2 Petrolina-PE (-9.39, -40.50) — Caatinga Semi-Arid Solar Corridor (Cloud-Driven)

Variable Unit Slope / Decade 95% Confidence Interval 42-yr Total Seasonal τ Seasonal p-value Verdict (α = 0.05)
T2M°C+0.3012[+0.2314, +0.3710]+1.265+0.2424.663e-15Increasing
PRECTOTCORRmm/day-0.0721[-0.1265, -0.0250]-0.303-0.0680.0291Decreasing
RH2M%-0.8932[-1.2997, -0.4790]-3.751-0.1255.157e-05Decreasing
ALLSKY_SFC_SW_DWNMJ/m²/day+0.2558[+0.1624, +0.3496]+1.075+0.1789.384e-09Increasing
CLRSKY_SFC_SW_DWNMJ/m²/day+0.0127[-0.0093, +0.0350]+0.053+0.0330.2901Null (no trend)
CLOUD_ATTEN_PCT%-0.9647[-1.2794, -0.6302]-4.052-0.1842.833e-09Decreasing
WS2Mm/s-0.0138[-0.0433, +0.0168]-0.058-0.0420.1734Null (no trend)

2.3 Manaus-AM (-3.10, -60.02) — Central Amazon Rainforest (Cloud-Driven)

Variable Unit Slope / Decade 95% Confidence Interval 42-yr Total Seasonal τ Seasonal p-value Verdict (α = 0.05)
T2M°C+0.3065[+0.2543, +0.3593]+1.287+0.381< 1e-16Increasing
PRECTOTCORRmm/day-0.4673[-0.5989, -0.3344]-1.963-0.2044.238e-11Decreasing
RH2M%-0.5149[-0.7309, -0.3099]-2.163-0.1331.645e-05Decreasing
ALLSKY_SFC_SW_DWNMJ/m²/day+0.2413[+0.1690, +0.3120]+1.013+0.1981.738e-10Increasing
CLRSKY_SFC_SW_DWNMJ/m²/day+0.0289[0.0000, +0.0582]+0.121+0.0090.7686Null (no trend)
CLOUD_ATTEN_PCT%-0.8552[-1.1442, -0.5651]-3.592-0.1723.015e-08Decreasing
WS2Mm/s-0.0007[-0.0034, +0.0013]-0.003-0.0230.4512Null (no trend)

3. Multi-Vector Attribution & Verified NASA Dataset Provenance

Direct Answer: Cockpit-OMNI pairs NASA POWER decadal trends with near-real-time thermal fire anomalies (NASA FIRMS VIIRS_NOAA21_NRT, CMR Concept ID C3264430167-LANCEMODIS), space weather alerts (NASA DONKI), and cataloged InSAR/thermal surface deformation products (NASA Earthdata CMR MCP: NISAR_L2_GUNW_PROVISIONAL_V1 and ECO_L2T_LSTE, honestly labeled roadmap).

Machine-Readable Verification Endpoints: