JHM manuscript · in preparation

An Exact Decomposition of Accumulated Precipitation into
Occurrence, Intensity, Area, and Coupling

Songkun Yan  ·  Xiaodong Chen
University of Oklahoma

V = Δt·T · fw · Iw · Aw · Kw

IMERG V07 vs GV-MRMS · 5°×5° southeastern U.S. · 2022–2023

The problem

The same rainfall total can be built in different ways

  • Total accumulation is an incomplete summary. Two products can agree on the total while differing in how often it rains, how hard, over how much area, and whether those vary together.
  • Pixel scores answer a different question. Categorical and grid-based metrics assess detection and collocation; displaced-but-realistic features get penalized twice.
  • The classical fix is incomplete for fields. Climate diagnostics factor amount as P = fw·Iw — frequency × conditional intensity — which is pointwise. A gridded field also has an instantaneous raining area, and intensity and area co-vary.
Goal. Factor the accumulated amount itself — exactly — into pieces a product developer can act on.
classical, pointwise
P̄ = fw · Iw
↓ spatial field
this work
V = Δt·T · fw · Iw · Aw · Kw

Two new factors are exactly what a spatial field adds: the extent of rain when it occurs, and whether intense frames are also the extensive ones.

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The decomposition

Four factors, exact by construction

V = Δt·T · fw · Iw · Aw · Kw exact — no residual, no fitting
fw
Occurrence
Fraction of half-hourly frames with rain somewhere in the domain. Domain-scale, not point frequency.
Iw
Wet-frame intensity
Mean frame intensity given rain occurs — area-weighted over active pixels.
Aw
Wet-frame area
Mean raining area given rain occurs. The spatial extent the pointwise form loses.
Kw
Within-wet coupling
1 + ρw·CVI,w·CVA,w. >1 when intense frames are also extensive.
DV = Df + DIw + DAw + DKw DX = ln(Xproduct / Xreference)

Taking logs turns the product into an additive budget: the total difference is apportioned exactly among four interpretable causes, so compensation is displayed, not inferred.

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Data & sampling

One data-rich domain, strictly paired sampling

Study domain and GV-MRMS availability
  • Products. IMERG V07 Final: IR → Uncal → Cal — three fields of one processing chain.
  • Reference. GV-MRMS 30MGCP, conservatively remapped to the 0.1° IMERG grid. A reference, not truth.
  • Domain. 5°×5° SE U.S., 50×50 cells, 2022–2023, half-hourly.
  • Symmetric masking. MRMS quality control blanks 5.3% of pixel-times; those pixels are masked in IMERG too, so every product is summed over an identical pixel set. T = 33,769 paired times.

Without this, a product's raining area would include places the reference never had a chance to observe.

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How it works · 1

A 3-day window: occurrence excess hidden inside an equal total

Four-factor decomposition on a 3-day window
MRMS rains in 60% of frames, Cal in 78% — yet the two totals agree to 0.3%. The budget says why: Df = +0.26 is cancelled almost exactly by −0.05 −0.08 −0.13. Equal totals, opposite structure.
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How it works · 2

A single event: the fw = 1 limit

Event-domain special case
  • Every frame is wet, so fw = 1 and occurrence drops out: the framework reduces to Δt·T·IwAwKw.
  • Same volume (2.14×106 mm km²) from a visibly different storm: Cal is weaker (−0.27), broader (+0.18), more coupled (+0.09).
  • The It–At trajectories occupy different parts of the plane.
The two windows together show which factors carry the compensation depends on the domain — and that the same algebra covers both.
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Main result

Two years: same total, three different pathways

Two-year four-factor budget and stage transitions
Shared by all three fields: rain registered more often (+0.11 to +0.17) and 27–32% weaker when it rains. Neither is removed along the chain.
They differ spatially: IR is 27% broader with MRMS-like coupling; Uncal/Cal are area-neutral but more strongly coupled (+0.14 to +0.16).
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Main result · the numbers

The budget closes exactly, row by row

FieldDfDIw DAwDKw= DVtotal vs MRMS
IMERG IR+0.113−0.385+0.237+0.024−0.012−1%
IMERG Uncal+0.155−0.363−0.001+0.158−0.052−5%
IMERG Cal+0.166−0.317+0.009+0.142+0.000+0.03%
Bold = 95% bootstrap interval excludes zero (paired moving-block, 5,000 replicates; robust to 1/2/5-day blocks).
Cal matches the MRMS total to 0.1% — not by agreeing on any factor set, but because a large occurrence excess and coupling excess offset a large intensity deficit.

MRMS reference: fw = 0.61, Iw = 1.74 mm hr⁻¹, Aw = 26.4×10³ km² (≈10% of the domain), Kw = 1.46 (ρw = 0.44).

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Algorithm stages

Each step of the chain moves a different factor

IR → Uncal  adds PMW, morphing, combination
Wet-frame area −0.24 (removes almost the whole IR area excess)  ·  coupling +0.13 (introduces a new excess)  ·  occurrence and intensity barely move.
Redistributes the spatial contrast rather than removing it.
Uncal → Cal  gauge calibration
Wet-frame intensity +0.05  ·  occurrence, area, coupling all |ΔD| ≤ 0.02.
That single change is what brings the total back to MRMS.
The chain redistributes differences among the four factors; it does not reduce them uniformly. The occurrence excess and most of the intensity deficit survive both steps.

Why this matters for development. A total-volume score would rate Cal as "fixed." The budget shows the calibration acted on one factor only — the other three differences are still there, and they happen to cancel in this domain and period.

These are contrasts between diagnostic fields of one system, not controlled single-factor experiments.

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Time variability

Which differences are persistent, which fluctuate

Monthly four-factor differences
  • Occurrence excess — positive in 17–22 of 24 months (p ≤ 0.002).
  • Intensity deficit — negative in 23 of 24 months for every field (p < 0.001). The most robust signal in the study.
  • Coupling excess — consistent for Uncal/Cal (20–21 of 24); variable for IR.
  • Wet-frame area — the exception: large and positive for IR, but oscillating around zero for Uncal/Cal.
DV is the noisiest row. Its monthly median is indistinguishable from zero for every field — the total hides everything the components reveal.
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Seasons

Area neutrality is a cancellation, not an agreement

Warm vs cool season pooled differences
Warm season: occurrence nearly matches; the contrast is intensity (−0.35 to −0.47) and broader area (+0.13 to +0.43).
Cool season: IMERG rains far more often (+0.23 to +0.25), the intensity deficit halves, and Uncal/Cal become narrower than MRMS (−0.12, −0.13).

The two-year wet-frame area neutrality of Uncal/Cal is a seasonal sign reversal — broader in warm, narrower in cool. A single aggregate number would have reported "no area difference."

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Robustness

What survives every analysis choice — and what does not

Threshold and resolution sensitivity
  • Robust signs across thresholds 0.1–1.0 mm hr⁻¹, windows 3 d–season, sub-domains 0.5–5°, grids 0.1–1°: occurrence excess, intensity deficit, multisatellite coupling excess.
  • Scale dependent: raising the threshold shifts signal from occurrence into area — the area neutrality is specific to p₀ = 0.1.
  • A process clue: coarsening to 0.5–1° removes most of the Uncal/Cal intensity deficit (−0.36 → −0.07) but not IR's (−0.26). The multisatellite deficit lives below ~0.5° — consistent with smoothing of intense cores.

Also checked: block length (1/2/5 d), coverage threshold, symmetric vs one-sided masking, co-wet frames only.

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Summary

What the decomposition buys us

1 · Exact, not fitted. V = Δt·T·fwIwAwKw closes to machine precision, so DV = Df+DIw+DAw+DKw is an accounting identity. Compensation is displayed, not inferred.
2 · It generalizes the classical amount decomposition from a point to a spatial field, adding the two terms a field actually has: raining extent and intensity–area coupling.
3 · It changes the IMERG story. "Weak and broad" is right for IR only. For the multisatellite fields the apparent area excess is an occurrence effect; what is really elevated is the coupling.
4 · Calibrated IMERG matches the MRMS total to 0.1% by compensation — more frequent, weaker, more strongly coupled wet frames — not by agreeing on the factors.
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Status & next steps

For discussion

Manuscript status

  • Full draft complete — Methods, Results, Discussion, 7 figures, 6 supplementary tables.
  • Robustness suite done: bootstrap CIs, block length, threshold, window, domain size, grid resolution, masking, co-wet frames.
  • Framed explicitly as a methodological demonstration on one domain.

Open questions for you

  • Scope: submit as a single-domain method paper, or add 3–4 contrasting CONUS regions first? (Great Plains / Gulf / Midwest / Northeast already computed — available on request.)
  • Framing: is "occurrence–intensity–area–coupling" the right headline, or lead with the compensation result?
  • To do before submission: funding acknowledgment, Zenodo DOI for the code.
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