Deep Convection: Onset, Diurnal Cycle, and Role in Climate Variability and Sensitivity

Principal Investigator(s):
Anthony Del Genio, NASA - Goddard Institute for Space Studies

The ASR Southern Great Plains (SGP) testbed for continuous modeling offers new opportunities to improve global climate model (GCM) parameterizations. We propose an ASR investigation of convective and cloud microphysical processes that uses existing ARM data as a testing ground for meaningful approaches to model evaluation and sets the stage for later strategic use of the testbed to improve cumulus parameterizations and better understand deep convective cloud feedback. Our proposed research consists of the following tasks:

  1. Diurnal cycle of continental convection
  2. Deep convection at the SGP occurs in two forms: Organized mesoscale convection that originates upstream and produces peak precipitation at night; and local shallow convection that develops into deep convection that peaks in late afternoon. Local transitions are a logical next step from the shallow convection that will be the early focus of the testbed. This transition constrains entrainment and cold pools, since GCMs produce a continental rain peak near noon. We will study ARSCL-observed transition cases using the WRF, determine the sources of SCM diurnal cycle errors and make parameterization changes as appropriate. We will identify similar cases when the testbed is operational, document the cloud field using ARM scanning radar data, and use the continuous modeling framework for out-of-sample tests to further understand the physics of the transition and what is needed to model it realistically.

  3. Factors controlling convective detrainment and anvil evolution
  4. Convective detrainment is a major source of high cloud ice water content and cloud forcing. The GISS GCM diagnoses a convective updraft speed profile, assumes a particle size distribution (PSD), and uses size-fallspeed relations to determine the fraction of condensate carried upward vs. precipitating. We will use SCM case studies for TWP-ICE and MC3E for which vertical velocity has been retrieved to test whether entrainment improvements produce realistic updraft speeds and then re-examine the updraft parameterization as needed. We will then compare detrained ice water contents and fall speeds to ASR retrievals to refine the GCM’s fall speed and PSD assumptions. The state dependence will be evaluated using SGP testbed cases, taken initially from the shallow-deep transition events studied in task 1.

  5. Role of convective cloud radiative processes in the Madden-Julian Oscillation (MJO)
  6. Changes in entrainment and rain evaporation and a cold pool parameterization have produced an MJO in the GISS GCM for the first time and allowed us to reproduce the KAZR dependence of convection depth on humidity during AMIE-Gan. We will determine whether model changes that improve the continental diurnal cycle improve or degrade the MJO and make adjustments accordingly. We will also address the hypothesis that the MJO utilizes anvil cloud-radiative heating anomalies as its energy source. Convective detrainment improvements will be tested to determine whether they change MJO strength, and we will also vary parameters that affect the vertical velocity, fall speed, and PSD to see whether MJO strength scales with the magnitude and profile of cloud radiative heating anomalies.

  7. Contribution of convective cloud feedback to climate sensitivity

Recent “emergent constraints” imply that climate sensitivity is high because of positive low cloud feedbacks. However inferences from the observed late-20th Century temperature record and paleoclimate proxies suggest a sensitivity closer to 3°C. Our research will produce an improved GCM parameterization of high cloud properties associated with convection in which processes are more closely coupled to atmospheric state. We will use this to perform 2xCO2 GCM simulations to test the hypothesis that increases in high clouds of sufficient optical thickness can shield some regions of low cloud decrease and thereby limit climate sensitivity and reconcile observed temperature trends with emergent constraints.