Mark Branson

Intraseasonal Variability in Coupled GCMs: The Roles of Ocean Feedbacks and Model Physics

AbstractThe interaction of ocean coupling and model physics in the simulation of the intraseasonal oscillation (ISO) is explored with three general circulation models: the Community Atmospheric Model, versions 3 and 4 (CAM3 and CAM4), and the superparameterized CAM3 (SPCAM3). Each is integrated coupled to an ocean model, and as an atmosphere-only model using sea surface temperatures (SSTs) from the coupled SPCAM3, which simulates a realistic ISO. For each model, the ISO is best simulated with coupling. For each SST boundary condition, the ISO is best simulated in SPCAM3.Near-surface vertical gradients of specific humidity, (temperature, ), explain ~20% (50%) of tropical Indian Ocean latent (sensible) heat flux variance, and somewhat less of west Pacific variance. In turn, local SST anomalies explain ~5% (25%) of variance in coupled simulations, and less in uncoupled simulations. Ergo, latent and sensible heat fluxes are strongly controlled by wind speed fluctuations, which are largest in the coupled simul...

Statistical analyses of satellite cloud object data from ceres. Part II Tropical convective cloud objects during 1998 El Niño and evidence for supporting the fixed anvil temperature hypothesis

Abstract Characteristics of tropical deep convective cloud objects observed over the tropical Pacific during January–August 1998 are examined using the Tropical Rainfall Measuring Mission/Clouds and the Earth’s Radiant Energy System Single Scanner Footprint (SSF) data. These characteristics include the frequencies of occurrence and statistical distributions of cloud physical properties. Their variations with cloud object size, sea surface temperature (SST), and satellite precession cycle are analyzed in detail. A cloud object is defined as a contiguous patch of the earth composed of satellite footprints within a single dominant cloud-system type. It is found that statistical distributions of cloud physical properties are significantly different among three size categories of cloud objects with equivalent diameters of 100–150 (small), 150–300 (medium), and >300 km (large), except for the distributions of ice particle size. The distributions for the larger-size category of cloud objects are more skewed towa...

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

MJO Intensification with Warming in the Superparameterized CESM

AbstractThe Madden–Julian oscillation (MJO) is the dominant mode of tropical intraseasonal variability, characterized by an eastward-propagating envelope of convective anomalies with a 30–70-day time scale. Here, the authors report changes in MJO activity across coupled simulations with a superparameterized version of the NCAR Community Earth System Model. They find that intraseasonal OLR variance nearly doubles between a preindustrial control run and a run with 4×CO2. Intraseasonal precipitation increases at a rate of roughly 10% per 1 K of warming, and MJO events become 20%–30% more frequent. Moist static energy (MSE) budgets of composite MJO events are calculated for each scenario, and changes in budget terms are used to diagnose the physical processes responsible for changes in the MJO with warming. An increasingly positive contribution from vertical advection is identified as the most likely cause of the enhanced MJO activity. A decomposition links the changes in vertical advection to a steepening of...

Role of deep soil moisture in modulating climate in the Amazon rainforest

Received 28 December 2009; accepted 19 January 2010; published 2 March 2010. [1] Both local and large‐scale processes affect the Amazon hydrologic cycle. We investigate the impact of deep soils on the atmosphere through local feedbacks. The Simple Biosphere model, version 3 (SiB3), is coupled to a single column model. Historically, land surface schemes parameterize soil moisture stress based on shallow soils and incorrectly capture seasonal cycles in the Amazon. Following observations, SiB3 is updated to allow deep roots to access soil moisture at depth. The new (“Unstressed”) version of SiB3 has a stronger hydrologic cycle, with increased evapotranspiration and moisture export during the dry season. The boundary layer responds through changes in its depth, relative humidity, and turbulent kinetic energy, and these changes feed back to influence wet season onset and intensity. Differences in atmospheric latent heating could affect circulation in a global model. The results have important consequences for modeling the Amazon hydrologic cycle and climate in global climate models. Citation: Harper, A. B., A. S. Denning, I. T. Baker, M. D. Branson, L. Prihodko, andD.A.Randall (2010),Roleof deepsoil moistureinmodulatingclimateintheAmazonrainforest,Geophys.Res.Lett.,

Clouds and Snowball Earth deglaciation

Neoproterozoic, and possibly Paleoproterozoic, glaciations represent the most extreme climate events in post-Hadean Earth, and may link closely with the evolution of the atmosphere and life. According to the Snowball Earth hypothesis, the entire ocean was covered with ice during these events for a few million years, during which time volcanic CO 2 increased enough to cause deglaciation. Geochemical proxy data and model calculations suggest that the maximum CO 2 was 0.01―0.1 by volume, but early climate modeling suggested that deglaciation was not possible at CO 2 = 0.2. We use results from six different general circulation models (GCMs) to show that clouds could warm a Snowball enough to reduce the CO 2 required for deglaciation by a factor of 10―100. Although more work is required to rigorously validate cloud schemes in Snowball-like conditions, our results suggest that Snowball deglaciation is consistent with observations.

Effects of explicit atmospheric convection at high CO2

Significance The representation of clouds and convection has an enormous impact on simulation of the climate system. This study addresses concerns that conventional parameterizations may bias the response of climate models to increased greenhouse gases. The broadly similar response of two models with parameterized and nonparameterized convection and clouds suggests that state-of-the-art predictions, based on parameterized climate models, may not necessarily be strongly biased in either direction (too strong or too weak warming). At the same time, large differences in simulated tropical variability and Arctic sea ice area suggest that improvement in convection and cloud representations remains essential. The effect of clouds on climate remains the largest uncertainty in climate change predictions, due to the inability of global climate models (GCMs) to resolve essential small-scale cloud and convection processes. We compare preindustrial and quadrupled CO2 simulations between a conventional GCM in which convection is parameterized and a “superparameterized” model in which convection is explicitly simulated with a cloud-permitting model in each grid cell. We find that the global responses of the two models to increased CO2 are broadly similar: both simulate ice-free Arctic summers, wintertime Arctic convection, and enhanced Madden–Julian oscillation (MJO) activity. Superparameterization produces significant differences at both CO2 levels, including greater Arctic cloud cover, further reduced sea ice area at high CO2, and a stronger increase with CO2 of the MJO.

Impact of Evapotranspiration on Dry Season Climate in the Amazon Forest

Moisture recycling can be an important source of rainfall over the Amazon forest, but this process relies heavily upon the ability of plants to access soil moisture. Evapotranspiration (ET) in the Amazon is often maintained or even enhanced during the dry season, when net radiation is high. However, ecosystem models often over predict the dry season water stress. The authors removed unrealistic water stress in an ecosystem model [the Simple Biosphere Model, version 3 (SiB3)] and examined the impacts of enhanced ET on the dry season climate when coupled to a GCM. The ‘‘stressed’’ model experiences dry season water stress and limitations on ET, while the ‘‘unstressed’’ model has enhanced root water access and exhibits strong drought tolerance. During the dry season in the southeastern Amazon, SiB3 unstressed has significantly higher latent heat flux (LH) and lower sensible heat flux (SH) than SiB3 stressed. There are two competing impacts on the climate in SiB3 unstressed: cooling resulting fromlower SHand moistening resulting fromhigher LH. During the average dry season, the cooling plays a larger role and the atmosphere is more statically stable, resulting in less precipitation than in SiB3 stressed. During dry season droughts, significantly higher LH in SiB3 unstressed is a necessary but not sufficientcondition for stronger precipitation. The moistening effect of LHdominates when the Bowen ratio (BR 5 SH/LH) is .1.0 in SiB3 stressed and precipitation is up to 26% higher in SiB3 unstressed. Animplication of thisanalysis isthatforest conservationcould enabletheAmazontocopewith drying conditions in the future.

Vertically resolved weak temperature gradient analysis of the Madden‐Julian Oscillation in SP‐CESM

The collective effects of convection can influence large-scale circulations that, in turn, act to organize convective activity. Such scale interactions may play an important role in moisture-convection feedbacks thought to be important to both convective aggregation and the Madden-Julian Oscillation, yet such interactions are not fully understood. New diagnostics based on tropical weak temperature gradient (WTG) theory have begun to make this problem more tractable, and are leveraged in this study to analyze the relationship between various apparent heating processes and large-scale vertical moisture advection in SP-CESM. WTG theory provides a framework for accurately diagnosing intraseasonal variations in large-scale vertical motion from apparent heating, allowing large-scale vertical moisture advection to be decomposed into contributions from microphysical processes, subgrid scale eddy fluxes, and radiative heating. This approach is consistent with the column moist static energy (MSE) budget approach, and has the added benefit of allowing the vertical advection term of the column MSE budget to be quantitatively partitioned into contributions from the aforementioned apparent heating processes. This decomposition is used to show that the MJO is an instability strongly supported by radiative feedbacks and damped by horizontal advection, consistent with the findings of previous studies. Periods of low, moderate, and high MJO amplitude are compared, and it is shown that changes in the vertical structure of apparent heating do not play a dominant role in limiting the amplitude of the MJO in SP-CESM. Finally, a diagnostic approach to scale analysis of tropical dynamics is used to investigate how the governing dynamics of various phenomena differ throughout wavenumber-frequency space. Findings support previous studies that suggest the governing dynamics of the MJO differ from those of strongly divergent convectively coupled equatorial waves.

A Surface Flux Parameterization Based on the Vertically Averaged Turbulence Kinetic Energy

Abstract A new bulk transfer formulation for the surface turbulent fluxes of momentum, heat, and moisture has been developed by using the square root of the vertically averaged turbulent kinetic energy (TKE) in the atmospheric boundary layer as a velocity scale, in place of the mean wind speed. The new parameterization utilizes the surface radiative (skin) temperature instead of the temperature at a “roughness height.” Field observations and large-eddy simulation (LES) results were used to develop the parameterization. It has been tested using an independent dataset from the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE). The predicted surface momentum flux compares very well with the observations, despite the fact that the data used for developing the new parameterization have a very different roughness length from the independent FIFE data. This shows that the parameterization can represent a wide range of surface roughness boundary conditions. The predic...