The Paradigm of Radiative-Convective Equilibrium (RCE)

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Presentation transcript:

Radiative-Convective Equilibrium and its Instability: Implications for Weather and Climate

The Paradigm of Radiative-Convective Equilibrium (RCE) One-dimensional statistical equilibrium state in which radiation and convection are the only processes that transport energy Oldest and simplest representation of climate states Interactive hydrologic cycle not introduced until early 1990s Good first-order representation of tropical and global climate Easily run on a laptop

Radiative-Moist Convective Equilibrium Vertical profile nearly neutral to moist convection Strongly-two way interaction: Radiation drives profile toward instability, convection lofts water that strongly affects radiative transfer

MIT Single Column Model IPCC Estimate: 2-4.5 oC

Explicit Simulation of Radiative-Convective Equilibrium (Work of EAPS PhD student Allison Wing)

Approach: Idealized modeling of convective organization in radiative-convective equilibrium using a cloud resolving model System for Atmospheric Modeling (SAM) of Khairoutdinov and Randall (2003) 768 km 28 km Rigid Lid Fixed SST 297-312 K Constant solar insolation: 413.98 W/m2 Horizontal Resolution: 3km Vertical Resolution: 64 levels Periodic lateral boundaries Initial sounding from domain average of smaller domain run in RCE Fully interactive RRTM radiation and surface fluxes. Three-dimensional cloud resolving model Anelastic equations of motion RRTM radiation scheme SAM 1-moment microphysics scheme Prognostic thermodynamic variables: Liquid water/ice moist static energy: hL = cpT + gz – Lc(qc+qr)-Ls(qi+qs+qg) Total nonprecipitating water Total precipitating water

Evolution of Vertically Integrated Water Vapor Day 1 is pretty homogeneous. By day 10 small area has become drier.

Evolution of Vertically Integrated Water Vapor Over next 20 days, small dry patch amplfies and expands. By day 30 covers nearly a quarter of the domain.

Evolution of Vertically Integrated Water Vapor Process continues and by day 50 areas of the domain not in dry patch have become moister than they were initially.

Evolution of Vertically Integrated Water Vapor Now the expanding dry region has confined all the moist area (which is now moister than anywhere earlier in the simulation) to one band. This band evolves

Evolution of Vertically Integrated Water Vapor Evolves into a single circular cluster in which high tpw values are concentrated. Outside the moist cluster, the rest of the domain has very low values of tpw.

Monsoonal Thunderstorms, Bangladesh and India, July 1985

Surface Temperature Dependence Speculated that high SST simulations required a larger domain size, perhaps because of the large values of dry static stability that occur at high temperature. Larger domain needed for high SSTs to aggregate

Analysis of Feedback Terms Framework: Budget for spatial variance of column integrated frozen moist static energy Consider anomalies from the horizontal mean (primes) Surface fluxes. Column shortwave heating, column longwave cooling. FMSE conserved, convection can’t change column integral. Advantages: not just det by removing processes, actually can compare magnitudes within given simulation, calc a number that is relevant. Feedback term: FMSE anom * Diabatic term anom Positive Feedback: Process increases FMSE of already moist region Negative Feedback: Process decreases FMSE of moist region

Total Diabatic Feedback Term All terms normalized by Black line: Explain axes, black line. When does cluster form? Point out pos fb (red) in dry region, beginning, shifting to moister regions as progresses. Strong pos fv developing in moist regions ~day 60. Point out blue (neg fb) in dry days 30-60, but h’ still increasing in magnitude there. Colors -> magnitude UNITS J/m^2 W/m^2 DRY MOIST

Column Shortwave Flux Convergence SW: mostly a positive feedback. Magnitude indicates not trivial, important. DRY MOIST

Column Longwave Flux Convergence LW is sometimes pos fb, sometimes neg. magnitude comparable to sw. point out super strong in moistest regions – LW cloud fb maintaining cluster. DRY MOIST

Surface Enthalpy Flux Partitioning Partition surface enthalpy flux anomalies into part due to U’ part due to Δq’ or ΔT’ part due to U’Δq’ or U’ΔT’

Surface Flux – Wind Feedback Term This is WISHE term. Conflicting results. Here it is primarly a positive fb--- and a strong wrong. But main role is to counteract…. DRY MOIST

Surface Flux –Air-Sea Disequilibrium Feedback Term …strong neg disequilibrium fb. DRY MOIST

Total Surface Flux Feedback Term Sfc flux: mostly negative fb. DRY MOIST

Convergence Term DRY MOIST

MIT Single-Column Model Fouquart and Bonnel shortwave radiation, Morcrette longwave Emanuel-Zivkovic-Rothman convection Bony-Emanuel cloud scheme 25 hPa level spacing in troposphere; higher resolution in stratosphere Run into RCE state with fixed SST, then re- initialized in WTG mode with T fixed at 850 hPa and above; small perturbations to w in initial condition

Results No drift from RCE state when SST <~ 32 C Migration toward states with ascent or descent at higher SSTs These states correspond to multiple equilibria in two-column models by Raymond and Zeng (2000) and by several others since (e.g. Sobel et al., 2007; Sessions et al. 2010)

Perturbation shortwave (red), longwave (blue), and net (black) radiative heating rates in response to an instantaneous reduction of specific humidity of 20% from the RCE states for (left) SST525C and (right) 40C. Note the different scales on the abscissas.

Perturbation net radiative heating rates in response to an instantaneous reduction of specific humidity of 20% from the RCE states for SSTs ranging from 25 to 45C.

3. Two-Layer Model Temperatures held constant, IR emissivities depend on q, convective mass fluxes calculated from boundary layer QE, w’s calculated from WTG

Results of Linear Stability Analysis of Two-Layer Model: Criterion for instability: Dry static stabilities emissivities Precipitation efficiency Radiative-convective equilibrium becomes linearly unstable when the infrared opacity of the lower troposphere becomes sufficiently large, and when precipitation efficiency is large

Interpretation Ordinary Radiative-Convective Equilibrium Introduce local downward vertical velocity

Note: Once cluster forms, it is strongly maintained by intense negative OLR anomaly associated with central dense overcast. But cloud feedbacks are NOT important in instigating the instability. This leads to strong hysteresis in the radiative-convective system

Hypothesized Subcritical Bifurcation Clustering metric

Consequences

Aggregation Dramatically Dries Atmosphere!

Variation of tropical relative humidity profiles with a Simple Convective Aggregation Index (SCAI). Courtesy Isabelle Tobin, Sandrine Bony, and Remy Roca Tobin, Bony, and Roca, J. Climate, 2012

Hypothesis At high temperature, convection self-aggregates →Horizontally averaged humidity drops dramatically →Reduced greenhouse effect cools system →Convection disaggregates →Humidity increases, system warms →System wants to be near phase transition to aggregated state

Recipe for Self-Organized Criticality (First proposed by David Neelin, but by different mechanism) System should reside near critical threshold for self-aggregation: Regulation of tropical sea surface temperature! Convective cluster size should follow power law distribution

Self-Aggregation on an f-plane

Self-Aggregation on an f-plane Vincent Van Gogh: Starry Night

Hurricane-World Scaling Modified thermodynamic efficiency: Angular velocity of earth’s rotation: Saturation water concentration of sea surface: Net top-of-atmosphere upward radiative flux: Net upward surface radiative flux: Potential intensity:

Hurricane-World Scaling Radius of maximum winds: Distance between storm centers: Number density:

Summary Radiative-Convective Equilibrium remains an interesting problem in climate science At high temperature, RCE is unstable, owing to the particular dependencies of convection and radiation on atmospheric water vapor and clouds Aggregation of convection may have profound effects on climate Physics of aggregation may not operate well, if at all, in today’s climate models