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CMAQ vs ggcorrplot

A side-by-side editorial comparison of CMAQ and ggcorrplot — release velocity, themes, recent moves, and the top alternatives to consider.

CMAQ vs ggcorrplot: at a glance

FeatureCMAQggcorrplot
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesair-quality, atmospheric-modeling, epa, scientific-computingcorrelation, r, ggplot2, visualization
Last editorial update1h ago8h ago
WebsiteVisit →Visit →

What is CMAQ?

CMAQ went global in v5.5, and has been patching that surface ever since.

CMAQ is the EPA's Community Multiscale Air Quality modeling system, used for regulatory and research air quality simulation. Its release rhythm is strictly two-tier: numbered major versions carry new science and fresh benchmark datasets, while the x.y.z.n updates carry bug fixes against documentation and benchmarks that stay pinned to the parent version. The current line is v5.5, which introduced CRACMM2 chemistry and coupling to MPAS-A meteorology, followed by three patch rollups.

Read the full CMAQ trajectory →

What is ggcorrplot?

ggcorrplot came back after four years and found its significance markers had been lying

ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.

Read the full ggcorrplot trajectory →

CMAQ vs ggcorrplot: editorial side-by-side

C
CMAQ
ANALYTICS
0.0

CMAQ went global in v5.5, and has been patching that surface ever since.

◆ Current state

CMAQ is the EPA's Community Multiscale Air Quality modeling system, used for regulatory and research air quality simulation. Its release rhythm is strictly two-tier: numbered major versions carry new science and fresh benchmark datasets, while the x.y.z.n updates carry bug fixes against documentation and benchmarks that stay pinned to the parent version. The current line is v5.5, which introduced CRACMM2 chemistry and coupling to MPAS-A meteorology, followed by three patch rollups.

◆ Where it's heading

The v5.5 patches cluster around the newest and most sensitive components. ISAM source apportionment and DDM-3D sensitivity analysis account for corrections in every one of the three updates, and CRACMM2 needed fixes within months of release. That is the expected shape after a major version lands: the science is stable, the instrumentation built on top of it is not. Parallel I/O work in the latest patch suggests the global configurations are now being run at scales that expose throughput limits.

◆ Prediction

The next major version will fold these fixes in with new science, documentation and benchmark data — the release notes state this explicitly each time. Until then, expect further ISAM and DDM-3D corrections, which have appeared in every patch so far.

G
ggcorrplot
ANALYTICS
2.5

ggcorrplot came back after four years and found its significance markers had been lying

◆ Current state

ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.

◆ Where it's heading

Both releases chase the same target: parity with the older corrplot package inside a ggplot2 object. Significance stars appended to coefficient labels, circle scaling, decimal control, then boxed cells and glyphs sized by absolute correlation — these are corrplot's visual vocabulary reimplemented where they can be composed with other ggplot2 layers. The bug fixes point the other way, at foundations: p-values matched to cells by name rather than row position, clustering computed on the unrounded matrix, tl.col actually applied.

◆ Prediction

With the corrplot look largely reproduced and the correctness backlog cleared, the remaining gap is the mixed upper/lower display corrplot supports; that is the natural next argument if the current release pace holds.

Alternatives to CMAQ and ggcorrplot

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either CMAQ or ggcorrplot.

See all CMAQ alternatives → · See all ggcorrplot alternatives →

Recent activity from CMAQ and ggcorrplot

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 22d agoggcorrplotggcorrplot 0.3.0 adds boxed cells and correlation-sized squares
  2. 1mo agoggcorrplotggcorrplot 0.2.0 fixes significance markers broken by hc.order
  3. 1y agoCMAQCMAQ 5.5.0.3 enables parallel I/O, fixes DDM-3D control files
  4. 1y agoCMAQCMAQ 5.5.0.2 corrects ISAM aerosol and cloud processing
  5. 1y agoCMAQCMAQ 5.5.0.1 fixes SAPRC mechanism runs and NLCD mapping
  6. 1y agoCMAQCMAQ 5.5 adds global simulation coupled to MPAS-A
  7. 1y agoCMAQCMAQ 5.4.0.5: minor ELMO output fixes
  8. 2y agoCMAQCMAQ 5.4.0.4 fixes RBSTATS under ROS3, corrects a molecular weight
  9. 3y agoggcorrplotggcorrplot 0.1.4
  10. 6y agoggcorrplotggcorrplot 0.1.3
  11. 7y agoggcorrplotggcorrplot 0.1.2
  12. 10y agoggcorrplotggcorrplot's first release: correlograms in ggplot2

Frequently asked questions

What is the difference between CMAQ and ggcorrplot?

They serve adjacent needs but don't currently overlap on shipped themes. ggcorrplot is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is CMAQ better than ggcorrplot?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggcorrplot is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to CMAQ?

Top CMAQ alternatives in Analytics are ranked by recent ship velocity. Browse the "CMAQ alternatives" section above for the current picks, or visit /alternatives/cmaq for the full list with editorial commentary on each.

What are the best alternatives to ggcorrplot?

Top ggcorrplot alternatives in Analytics are ranked by recent ship velocity. Browse the "ggcorrplot alternatives" section above for the current picks, or visit /alternatives/ggcorrplot for the full list with editorial commentary on each.