A Mass-Flux Scheme View of a High-Resolution Simulation of a Transition from Shallow to Deep Cumulus Convection

In this paper, an idealized, high-resolution simulation of a gradually forced transition from shallow, nonprecipitating to deep, precipitating cumulus convection is described; how the cloud and transport statistics evolve as the convection deepens is explored; and the collected statistics are used to evaluate assumptions in current cumulus schemes. The statistical analysis methodologies that are used do not require tracing the history of individual clouds or air parcels; instead they rely on probing the ensemble characteristics of cumulus convection in the large model dataset. They appear to be an attractive way for analyzing outputs from cloud-resolving numerical experiments. Throughout the simulation, it is found that 1) the initial thermodynamic properties of the updrafts at the cloud base have rather tight distributions; 2) contrary to the assumption made in many cumulus schemes, nearly undiluted air parcels are too infrequent to be relevant to any stage of the simulated convection; and 3) a simple model with a spectrum of entraining plumes appears to reproduce most features of the cloudy updrafts, but significantly overpredicts the mass flux as the updrafts approach their levels of zero buoyancy. A buoyancy-sorting model was suggested as a potential remedy. The organized circulations of cold pools seem to create clouds with larger-sized bases and may correspondingly contribute to their smaller lateral entrainment rates. Our results do not support a mass-flux closure based solely on convective available potential energy (CAPE), and are in general agreement with a convective inhibition (CIN)-based closure. The general similarity in the ensemble characteristics of shallow and deep convection and the continuous evolution of the thermodynamic structure during the transition provide justification for developing a single unified cumulus parameterization that encompasses both shallow and deep convection

Massflux Budgets of Shallow Cumulus Clouds

The vertical transport by shallow nonprecipitating cumulus clouds of conserved variables, such as the total specific humidity or the liquid water potential temperature, can be well modeled by the massflux approach, in which the cloud field is represented by a top-hat distribution of clouds and its environment. The budget of the massflux is presented and is compared with the vertical velocity variance budget. The massflux budget is computed by conditionally sampling the prognostic vertical velocity equation by means of a Large-Eddy Simulation of shallow cumulus clouds. The model initialization is based on observations made during BOMEX. Several different sampling criteria are applied. The presence of liquid water is used to select clouds, whereas additional criteria are applied to sample cloud updraft, downdraft and core properties. The massflux and vertical velocity variance budgets appear to be qualitatively similar. The massflux is driven by buoyancy in the lower part of the cloud layer, whereas turbulent transport is important in generating massflux in the upper part of the cloud layer. Pressure and subgrid-scale effects typically act to dissipate massflux. The massflux approach is verified for non-conserved variables. The virtual potential temperature flux and the vertical velocity variance according to the the top-hat approximation do not correspond very well to the Reynolds-averaged turbulent flux. The top-hat structure for the virtual potential temperature is degraded by lateral mixing and the subsequent evaporative cooling of cloud droplets which support the development of negatively buoyant cloud downdrafts. Cloudy downdrafts occupy about 20% of the total cloud area in the upper part of the cumulus layer, and are the cause that the vertical velocity variance is not well represented by the massflux approach, either

Final Technical Report for DOE Award DE-FG02-05ER63959

The goals of this work were: (1) to improve the University of Washington shallow cumulus parameterization, first developed by the PI's group for better simulation of shallow oceanic cumulus convection in the MM5 mesoscale model (Bretherton et al., 2004, Mon. Wea. Rev.); (2) to explore its applicability to deep (precipitating) cumulus convection; and (3) to explore fundamental physical issues related to this cumulus parameterization

An analytical theory of moist convection

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 1985.MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE.Bibliography: leaves 208-210.by Christopher Stephen Bretherton.Ph.D

Improving the predictions of ML-corrected climate models with novelty detection

While previous works have shown that machine learning (ML) can improve the prediction accuracy of coarse-grid climate models, these ML-augmented methods are more vulnerable to irregular inputs than the traditional physics-based models they rely on. Because ML-predicted corrections feed back into the climate model's base physics, the ML-corrected model regularly produces out of sample data, which can cause model instability and frequent crashes. This work shows that adding semi-supervised novelty detection to identify out-of-sample data and disable the ML-correction accordingly stabilizes simulations and sharply improves the quality of predictions. We design an augmented climate model with a one-class support vector machine (OCSVM) novelty detector that provides better temperature and precipitation forecasts in a year-long simulation than either a baseline (no-ML) or a standard ML-corrected run. By improving the accuracy of coarse-grid climate models, this work helps make accurate climate models accessible to researchers without massive computational resources.Comment: Appearing at Tackling Climate Change with Machine Learning Workshop at NeurIPS 202

Variability in the Southerly Flow into the Eastern Pacific ITCZ

During boreal summer and fall, there is a strong southerly boundary layer flow across the equator into the east Pacific intertropical convergence zone (ITCZ). The modulation of this flow on synoptic to seasonal time scales is studied using an index of meridional pressure difference between the equator and the ITCZ along 95°W. Two complementary datasets from the East Pacific Investigation of Climate (EPIC) are used to study eastern Pacific variability. Daily measurements of sea level pressure (SLP) from Tropical Atmosphere Ocean (TOA) array buoys from May to November 2001 provide temporal coverage, and eight flights by a C-130 aircraft during September to October 2001 document the associated modulation of lower tropospheric vertical structure. The principal mode of variability of the perturbation SLP along 95°W from 1°S to 12°N, derived by principal component analysis from either the eight flights (PC1C-130) or from daily TAO buoy observations (PC1), explains 77% of the meridional pressure gradient variability. The pressure anomalies at 1.6 km are similar to those at the surface. The time series of the first mode of the TAO observations shows that most of the variance is in the 2–7-day range. Low pressure at 12°N is associated with southerly and westerly surface wind anomalies, and enhanced precipitation in the ITCZ. The depth of ITCZ convection is more strongly correlated to meridional wind above the planetary boundary layer (PBL) than to meridional wind within the PBL. There is little correlation of PBL meridional flow across the equator with ITCZ convection. Regression of PC1C-130 against the 95°W cross sections observed by dropwinsondes released during the eight C-130 flights shows correlations of westerlies to positive PC1C-130 (low pressure at 12°N). Between the equator and 4°N, statistically significant northerlies just above the PBL at 1–2-km height and southerlies at 4 km are correlated with negative PC1C-130, having high SLP at 12°N, an anomalously weak meridional SLP gradient, and suppressed convection in the ITCZ. PC1 is bandpass filtered and correlated with reanalysis fields to identify the structures that modulate meridional pressure gradients along 95°W. Most of the variability at periods less than 15 days is related to easterly waves. Seasonal trends in PC1 during May–October 2001 reflect the seasonal evolution of the sea and land surface temperatures. After the seasonal trend is removed, a geostrophic westerly jet at 12°N—probably related to the Madden–Julian oscillation—dominates PC1 variability on time scales longer than 15 day

CGILS Phase 2 LES Intercomparison of Response of Subtropical Marine Low Cloud Regimes to CO2\u3c/sub\u3e Quadrupling and a CMIP3 Composite Forcing Change

© 2016. The Authors. Phase 1 of the CGILS large-eddy simulation (LES) intercomparison is extended to understand if subtropical marine boundary-layer clouds respond to idealized climate perturbations consistently in six LES models. Here the responses to quadrupled carbon dioxide (“fast adjustment”) and to a composite climate perturbation representative of CMIP3 multimodel mean 2×CO2 near-equilibrium conditions are analyzed. As in Phase 1, the LES is run to equilibrium using specified steady summertime forcings representative of three locations in the Northeast Pacific Ocean in shallow well-mixed stratocumulus, decoupled stratocumulus, and shallow cumulus cloud regimes. The results are generally consistent with a single-LES study of Bretherton et al. () on which this intercomparison was based. Both quadrupled CO2 and the composite climate perturbation result in less cloud and a shallower boundary layer for all models in well-mixed stratocumulus and for all but a single LES in decoupled stratocumulus and shallow cumulus, corroborating similar findings from global climate models (GCMs). For both perturbations, the amount of cloud reduction varies across the models, but there is less intermodel scatter than in GCMs. The cloud radiative effect changes are much larger in the stratocumulus-capped regimes than in the shallow cumulus regime, for which precipitation buffering may damp the cloud response. In the decoupled stratocumulus and cumulus regimes, both the CO2 increase and CMIP3 perturbations reduce boundary-layer decoupling, due to the shallowing of inversion height