Bosong Zhang

Forcing and Feedback • Radiative Feedbacks

Journal of Climate (2024)

Nonlinear Radiative Response to Patterned Global Warming due to Convection Aggregation and Nonlinear Tropical Dynamics

Targeted SST perturbation experiments test Green’s-function additivity and show where nonlinear cloud-convection responses limit linear TOA-radiation reconstruction.

SST Additivity Test Green's Function Limits Convection Aggregation DOI: 10.1175/JCLI-D-23-0539.1
Figure from Quan et al. 2024 showing nonlinear SST additivity diagnostics
Figure from the paper highlighting nonlinear deviations from linear Green's-function superposition.

GF Overestimation

Linear superposition overestimates multipatch TOA radiative responses for large SST perturbations

Nonadditive Dynamics

Convection aggregation and circulation-induced moisture transport responses are sublinear

Sensitivity Bias Risk

Longwave cooling can be overestimated, implying underestimated effective climate sensitivity

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Paper Citation

Quan, H., B. Zhang, C. Wang, and S. Fueglistaler, 2024: Nonlinear Radiative Response to Patterned Global Warming due to Convection Aggregation and Nonlinear Tropical Dynamics. Journal of Climate, 37, 5675-5693. https://doi.org/10.1175/JCLI-D-23-0539.1

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Scientific Logic

  • Question: When and why does linear SST Green’s-function additivity fail in top-of-atmosphere radiation response?
  • Method: Finite-area and larger-amplitude SST perturbation experiments testing superposition skill for global and regional radiative diagnostics.
  • Mechanism: Nonlinear convection-cloud adjustments and state-dependent circulation reorganizations violate strict linear additivity, especially locally in the tropics.
  • Main Findings: Global-mean reconstruction is more robust than regional fields, but nonlinear residuals remain central for patterned-warming attribution.

Scientific Question

When does the Green's-function linear-superposition framework fail for patterned SST warming, and what physical mechanism drives the nonadditivity in TOA radiative response?

Methods

  • AM4 perturbation experiments with localized tropical Pacific SST patches (plus1 K and plus4 K).
  • Pairwise and multipatch additivity tests comparing true responses against linear superposition predictions.
  • Diagnostics linking TOA LW/SW response errors to precipitation Gini index and moisture-transport changes.

Key Findings

  • Linear superposition performs better for global-mean diagnostics than for regional tropical structure.
  • Nonlinear residuals are strongest where convective organization and cloud regimes shift.
  • Pattern-effect attribution should combine GF diagnostics with explicit nonlinearity assessment.

Figures from the Study

Rendered from Quan et al. (2024), Journal of Climate, https://doi.org/10.1175/JCLI-D-23-0539.1.

Figure A

Quantification of nonlinear additivity error in SST perturbation experiments
Demonstration of where linear superposition diverges from explicitly simulated multipatch SST responses.

Figure B

Regional diagnostics of cloud and convection contributions to nonlinearity
Regional diagnostics showing that cloud-convection regime transitions are major sources of nonlinear residuals.

Figure C

Comparison of reconstructed and simulated radiative responses under larger perturbations
Comparison between reconstructed and simulated TOA responses illustrating scale-dependent limits of additivity.

Interpretation

The study provides a mechanistic explanation for why pattern-effect reconstructions can appear accurate in weak-perturbation or historical-like regimes but break under larger future-warming perturbations: tropical aggregation and circulation responses are not linearly additive.

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