Michael S. Pritchard

Orogenic Propagating Precipitation Systems over the United States in a Global Climate Model with Embedded Explicit Convection

Intheleeofmajormountainchainsworldwide,diurnalphysicsoforganizedpropagatingconvection project onto seasonal and climate time scales of the hydrologic cycle, but this phenomenon is not represented in conventional global climate models (GCMs). Analysis of an experimental version of the superparameterized (SP) Community Atmosphere Model (CAM) demonstrates that propagating orogenic nocturnal convection in the central U.S. warm season is, however, representable in GCMs that use the embedded explicit convection model approach [i.e., multiscale modeling frameworks (MMFs)]. SP-CAM admits propagating organized convective systems in the lee of the Rockies during synoptic conditions similar to those that generate mesoscale convective systems in nature. The simulated convective systems exhibit spatial scales, phase speeds, and propagation speeds comparable to radar observations, and the genesis mechanism in the model agrees qualitatively with established conceptual models. Convective heating and condensate structures are examined on both resolvedscales in SP-CAM, and coherently propagating cloud ‘‘metastructures’’ are shown to transcend individual cloud-resolving model arrays. In reconciling how this new mode of diurnal convective variabilityis admittedin SP-CAMdespite thesevereidealizations in the cloud-resolvingmodel configuration, an updated discussion is presented of what physics may transcend the re-engineered scale interface in MMFs. The authors suggest that the improved diurnal propagation physics in SP-CAM are mediated by large-scale first-baroclinic gravity wave interactions with a prognostic organization life cycle, emphasizing the physical importance of preserving ‘‘memory’’ at the inner resolved scale.

Causal Evidence that Rotational Moisture Advection is Critical to the Superparameterized Madden–Julian Oscillation

AbstractThe authors investigate the hypothesis that horizontal moisture advection is critical to the eastward propagation of the Madden–Julian oscillation (MJO). Consistent diagnostic evidence has been found in recent MJO-permitting global models viewed from the moisture-mode dynamical paradigm. To test this idea in a causal sense, tropical moisture advection by vorticity anomalies is artificially modulated in a superparameterized global model known to produce a realistic MJO signal. Boosting horizontal moisture advection by tropical vorticity anomalies accelerates and amplifies the simulated MJO in tandem with reduced environmental gross moist stability. Limiting rotational horizontal moisture advection shuts the MJO down. These sensitivities are robust in that they are nearly monotonic with respect to the control parameter and emerge despite basic-state sensitivities favoring the opposite response. Speedup confirms what several diagnostic lines of evidence already suggest—that anomalous moisture advecti...

Constraining the influence of natural variability to improve estimates of global aerosol indirect effects in a nudged version of the Community Atmosphere Model 5

Natural modes of variability on many timescales influence aerosol particle distributions and cloud properties such that isolating statistically significant differences in cloud radiative forcing due to anthropogenic aerosol perturbations (indirect effects) typically requires integrating over long simulations. For state-of-the-art global climate models (GCM), especially those in which embedded cloud-resolving models replace conventional statistical parameterizations (i.e., multiscale modeling framework, MMF), the required long integrations can be prohibitively expensive. Here an alternative approach is explored, which implements Newtonian relaxation (nudging) to constrain simulations with both pre-industrial and present-day aerosol emissions toward identical meteorological conditions, thus reducing differences in natural variability and dampening feedback responses in order to isolate radiative forcing. Ten-year GCM simulations with nudging provide a more stable estimate of the global-annual mean net aerosol indirect radiative forcing than do conventional free-running simulations. The estimates have mean values and 95% confidence intervals of −1.19 ± 0.02 W/m2 and −1.37 ± 0.13 W/m2for nudged and free-running simulations, respectively. Nudging also substantially increases the fraction of the worlds area in which a statistically significant aerosol indirect effect can be detected (66% and 28% of the Earths surface for nudged and free-running simulations, respectively). One-year MMF simulations with and without nudging provide global-annual mean net aerosol indirect radiative forcing estimates of −0.81 W/m2 and −0.82 W/m2, respectively. These results compare well with previous estimates from three-year free-running MMF simulations (−0.83 W/m2), which showed the aerosol-cloud relationship to be in better agreement with observations and high-resolution models than in the results obtained with conventional cloud parameterizations.

Robust effects of cloud superparameterization on simulated daily rainfall intensity statistics across multiple versions of the Community Earth System Model

PUBLICATIONS Journal of Advances in Modeling Earth Systems RESEARCH ARTICLE 10.1002/2015MS000574 Key Points: Superparameterization improves the rainfall amount mode and extreme rates relative to TRMM 3B42 Mean rainfall and dry day frequency biases do not improve much with superparameterization Conventional and superparameterized rainfall intensity statistics are similar poleward of 508 Robust effects of cloud superparameterization on simulated daily rainfall intensity statistics across multiple versions of the Community Earth System Model Gabriel J. Kooperman 1 , Michael S. Pritchard 1 , Melissa A. Burt 2 , Mark D. Branson 2 , and David A. Randall 2 Department of Earth System Science, University of California, Irvine, California, USA, 2 Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado, USA Abstract This study evaluates several important statistics of daily rainfall based on frequency and Supporting Information: Supporting Information S1 Correspondence to: G. J. Kooperman, gkooperm@uci.edu Citation: Kooperman, G. J., M. S. Pritchard, M. A. Burt, M. D. Branson, and D. A. Randall (2016), Robust effects of cloud superparameterization on simulated daily rainfall intensity statistics across multiple versions of the Community Earth System Model, J. Adv. Model. Earth Syst., 8, 140–165, doi:10.1002/2015MS000574. Received 28 OCT 2015 Accepted 29 DEC 2015 Accepted article online 2 JAN 2016 Published online 1 FEB 2016 amount distributions as simulated by a global climate model whose precipitation does not depend on convective parameterization—Super-Parameterized Community Atmosphere Model (SPCAM). Three superparameterized and conventional versions of CAM, coupled within the Community Earth System Model (CESM1 and CCSM4), are compared against two modern rainfall products (GPCP 1DD and TRMM 3B42) to discriminate robust effects of superparameterization that emerge across multiple versions. The geographic pattern of annual-mean rainfall is mostly insensitive to superparameterization, with only slight improvements in the double-ITCZ bias. However, unfolding intensity distributions reveal several improvements in the character of rainfall simulated by SPCAM. The rainfall rate that delivers the most accumulated rain (i.e., amount mode) is systematically too weak in all versions of CAM relative to TRMM 3B42 and does not improve with horizontal resolution. It is improved by superparameterization though, with higher modes in regions of tropical wave, Madden-Julian Oscillation, and monsoon activity. Superparameterization produces better representations of extreme rates compared to TRMM 3B42, with- out sensitivity to horizontal resolution seen in CAM. SPCAM produces more dry days over land and fewer over the ocean. Updates to CAM’s low cloud parameterizations have narrowed the frequency peak of light rain, converging toward SPCAM. Poleward of 508, where more rainfall is produced by resolved-scale processes in CAM, few differences discriminate the rainfall properties of the two models. These results are discussed in light of their implication for future rainfall changes in response to climate forcing. 1. Introduction C 2016. The Authors. V This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. KOOPERMAN ET AL. Rainfall is an intrinsic characteristic of a region’s climate, by definition determining whether the region is a desert or rainforest [Peel et al., 2007]. As the Earth warms, global mean precipitation is expected to increase by 1–3% 8C 21 due to radiative constraints [Allen and Ingram, 2002; Pendergrass and Hartmann, 2014a; Ste- phens and Ellis, 2008], but regional changes are much less robust [Dai, 2006; Mahlstein et al., 2012; Stocker et al., 2013]. Regional rainfall is driven over time by changes in circulation, moisture transport, and local evaporation [Trenberth et al., 2003]. These changes can depend on complex interactions between rainfall, large-scale dynamics, and surface sensible and latent heat fluxes, especially over land where soil moisture coupling plays an important role [Seneviratne et al., 2010]. Interactions linked to the second-order statistics of rainfall (e.g., frequency and intensity) can determine whether rain is intercepted by the canopy, infiltrates the soil, or runs off the surface, thus influencing the soil moisture [Lawrence et al., 2011; Ramirex and Senar- ath, 2000]. In turn, the soil moisture effects local evaporation and sensible heat fluxes, which project onto large-scale dynamics and downstream moisture transport [Dirmeyer et al., 2009; Koster et al., 2004; Senevir- atne et al., 2010]. These second-order rainfall characteristics are expected to change even more than the mean, up to 7% 8C 21 on global scales, and even larger on regional scales [O’Gorman, 2015; Trenberth et al., 2003]. For these reasons, and because rainfall frequency and intensity control the prevalence of devas- tating drought or flood conditions, it is critical they be realistically simulated in global climate models (GCMs). RAINFALL INTENSITY STATISTICS IN SPCAM

Vertical structure and physical processes of the Madden-Julian Oscillation: Biases and uncertainties at short range

Abstract An analysis of diabatic heating and moistening processes from 12 to 36 h lead time forecasts from 12 Global Circulation Models are presented as part of the “Vertical structure and physical processes of the Madden‐Julian Oscillation (MJO)” project. A lead time of 12–36 h is chosen to constrain the large‐scale dynamics and thermodynamics to be close to observations while avoiding being too close to the initial spin‐up of the models as they adjust to being driven from the Years of Tropical Convection (YOTC) analysis. A comparison of the vertical velocity and rainfall with the observations and YOTC analysis suggests that the phases of convection associated with the MJO are constrained in most models at this lead time although the rainfall in the suppressed phase is typically overestimated. Although the large‐scale dynamics is reasonably constrained, moistening and heating profiles have large intermodel spread. In particular, there are large spreads in convective heating and moistening at midlevels during the transition to active convection. Radiative heating and cloud parameters have the largest relative spread across models at upper levels during the active phase. A detailed analysis of time step behavior shows that some models show strong intermittency in rainfall and differences in the precipitation and dynamics relationship between models. The wealth of model outputs archived during this project is a very valuable resource for model developers beyond the study of the MJO. In addition, the findings of this study can inform the design of process model experiments, and inform the priorities for field experiments and future observing systems.

Restricting 32–128 km horizontal scales hardly affects the MJO in the Superparameterized Community Atmosphere Model v.3.0 but the number of cloud-resolving grid columns constrains vertical mixing

© 2014. The Authors. The effects of artificially restricting the 32-128 km horizontal scale regime on MJO dynamics in the Superparameterized Community Atmosphere Model v.3.0 have been explored through reducing the extent of its embedded cloud resolving model (CRM) arrays. Two and four-fold reductions in CRM extent (from 128 to 64 km and 32 km) produce statistical composite MJO signatures with spatial scale, zonal phase speed, and intrinsic wind-convection anomaly structure that are all remarkably similar to the standard SPCAMs MJO. This suggests that the physics of mesoscale convective organization on 32-128 km scales are not critical to MJO dynamics in SPCAM and that reducing CRM extent may be a viable strategy for 400% more computationally efficient analysis of superparameterized MJO dynamics. However several unexpected basic state responses caution that extreme CRM domain reduction can lead to systematic mean state issues in superparameterized models. We hypothesize that an artificial limit on the efficiency of vertical updraft mixing is set by the number of grid columns available for compensating subsidence in the embedded CRM arrays. This can lead to reduced moisture ventilation supporting too much liquid cloud and thus an overly strong cloud shortwave radiative forcing, particularly in regions of deep convection. Key Points Physics of MMF MJO are insensitive to near elimination of meso-beta-scale The efficiency of deep convective mixing in MMFs is limited by CRM extent 4x speedup of superparameterized models possible for MJO analysis

The response of US summer rainfall to quadrupled CO2 climate change in conventional and superparameterized versions of the NCAR community atmosphere model

© 2014. American Geophysical Union. All Rights Reserved. Observations and regional climate modeling (RCM) studies demonstrate that global climate models (GCMs) are unreliable for predicting changes in extreme precipitation. Yet RCM climate change simulations are subject to boundary conditions provided by GCMs and do not interact with large-scale dynamical feedbacks that may be critical to the overall regional response. Limitations of both global and regional modeling approaches contribute significant uncertainty to future rainfall projections. Progress requires a modeling framework capable of capturing the observed regional-scale variability of rainfall intensity without sacrificing planetary scales. Here the United States summer rainfall response to quadrupled CO 2 climate change is investigated using conventional (CAM) and superparameterized (SPCAM) versions of the NCAR Community Atmosphere Model. The superparameterization approach, in which cloud-resolving model arrays are embedded in GCM grid columns, improves rainfall statistics and convective variability in global simulations. A set of 5 year time-slice simulations, with prescribed sea surface temperature and sea ice boundary conditions harvested from preindustrial and abrupt four times CO 2 coupled Community Earth System Model (CESM/CAM) simulations, are compared for CAM and SPCAM. The two models produce very different changes in mean precipitation patterns, which develop from differences in large-scale circulation anomalies associated with the planetary-scale response to warming. CAM shows a small decrease in overall rainfall intensity, with an increased contribution from the weaker parameterized convection and a decrease from large-scale precipitation. SPCAM has the opposite response, a significant shift in rainfall occurrence toward higher precipitation rates including more intense propagating Central United States mesoscale convective systems in a four times CO 2 climate. Key Points Large-scale dynamics are critical to regional rainfall climate change responses Superparameterization captures expected increases in rain and storm intensity Extreme rain may be decoupled from key climate change drivers in standard GCMs

Neglecting ice-atmosphere interactions underestimates ice sheet melt in millennial-scale deglaciation simulations

Dynamic and thermodynamic interactions between the atmosphere and underlying ice sheets are generally not represented in the traditional one-way boundary condition forcing used to drive ice sheet models. This shortcoming is investigated through a series of idealized millennial-scale deglaciation simulations designed to isolate the mechanisms regulating the deglaciation timescale of the Laurentide ice sheet. Sensitivity experiments indicate that the conventional use of one-way (non-interactive) atmospheric forcing fields leads to an unrealistically insensitive melt response in the ice sheet model even when atmospheric carbon dioxide is set to modern preindustrial levels and Earths angle of obliquity is set to its early Holocene value. A more realistic deglaciation timescale is obtained only through the application of a new two-way (interactive) asynchronous ice-atmosphere coupling scheme and a seasonal ice albedo parameterization that accounts for the observed darkening of ice in the moist summertime ablation zone.

Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence

Systematic biases in the representation of boundary layer (BL) clouds are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called “ultraparameterization” (UP) is developed, in which the grid spacing of the cloud-resolving models (CRMs) is fine enough (250m × 20m) to explicitly capture the BL turbulence, associated clouds and entrainment in a global climate model capable of multi-year simulations. UP is implemented within the Community Atmosphere Model using 2° resolution (∼14,000 embedded CRMs) with one-moment microphysics. By using a small domain and mean-state acceleration, UP is computationally feasible today and promising for exascale computers. Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere radiation and cloud vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) clouds, due to stronger vertical eddy motions that promote entrainment. Results from 90-day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near-coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy-permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP-GCMs with turbulence parameterizations for studying BL cloud-climate and cloud-aerosol feedback.

Response of the Superparameterized Madden–Julian Oscillation to Extreme Climate and Basic-State Variation Challenges a Moisture Mode View

AbstractThe climate sensitivity of the Madden–Julian oscillation (MJO) is measured across a broad range of temperatures (1°–35°C) using a convection-permitting global climate model with homogenous sea surface temperatures. An MJO-like signal is found to be resilient in all simulations. These results are used to investigate two ideas related to the modern “moisture mode” view of MJO dynamics. The first hypothesis is that the MJO has dynamics analogous to a form of radiative convective self-aggregation in which longwave energy maintenance mechanisms shut down for SST ≪ 25°C. Inconsistent with this hypothesis, the explicitly simulated MJO survives cooling and retains leading moist static energy (MSE) budget terms associated with longwave destabilization even at SST < 10°C. Thus, if the MJO is a form of longwave-assisted self-aggregation, it is not one that is temperature critical, as is observed in some cases of radiative–convective equilibrium (RCE) self-aggregation. The second hypothesis is that the MJO is...