Daniel A. Shaevitz

Characteristics of tropical cyclones in high-resolution models in the present climate

The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) fields in two types of experiments, using climatological SST and interannually varying SST. TC tracks and intensities are derived from each models output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TC frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models.

Tracking Scheme Dependence of Simulated Tropical Cyclone Response to Idealized Climate Simulations

AbstractFuture tropical cyclone activity is a topic of great scientific and societal interest. In the absence of a climate theory of tropical cyclogenesis, general circulation models are the primary tool available for investigating the issue. However, the identification of tropical cyclones in model data at moderate resolution is complex, and numerous schemes have been developed for their detection.The influence of different tracking schemes on detected tropical cyclone activity and responses in the Hurricane Working Group experiments is examined herein. These are idealized atmospheric general circulation model experiments aimed at determining and distinguishing the effects of increased sea surface temperature and other increased CO2 effects on tropical cyclone activity. Two tracking schemes are applied to these data and the tracks provided by each modeling group are analyzed.The results herein indicate moderate agreement between the different tracking methods, with some models and experiments showing bet...

Cluster Analysis of Downscaled and Explicitly Simulated North Atlantic Tropical Cyclone Tracks

AbstractA realistic representation of the North Atlantic tropical cyclone tracks is crucial as it allows, for example, explaining potential changes in U.S. landfalling systems. Here, the authors present a tentative study that examines the ability of recent climate models to represent North Atlantic tropical cyclone tracks. Tracks from two types of climate models are evaluated: explicit tracks are obtained from tropical cyclones simulated in regional or global climate models with moderate to high horizontal resolution (1°–0.25°), and downscaled tracks are obtained using a downscaling technique with large-scale environmental fields from a subset of these models. For both configurations, tracks are objectively separated into four groups using a cluster technique, leading to a zonal and a meridional separation of the tracks. The meridional separation largely captures the separation between deep tropical and subtropical, hybrid or baroclinic cyclones, while the zonal separation segregates Gulf of Mexico and Ca...

How Well Do Global Climate Models Simulate the Variability of Atlantic Tropical Cyclones Associated with ENSO

The variability of Atlantic tropical cyclones (TCs) associated with El Nino‐Southern Oscillation (ENSO) in model simulations is assessed and compared with observations. The model experiments are 28-yr simulations forced with the observed sea surface temperature from 1982 to 2009. The simulations were coordinated by the U.S. Climate Variability and Predictability Research Program (CLIVAR) Hurricane Working Group and conducted with five global climate models (GCMs) with a total of 16 ensemble members. The model performance is evaluated based on both individual model ensemble means and multimodel ensemble mean. The latter has the highest anomaly correlation (0.86) for the interannual variability of TCs. Previous observational studiesshowastrongassociationbetweenENSOandAtlanticTCactivity,aswellasdistinctionsduringeastern Pacific (EP) and central Pacific (CP) El Nino events. The analysis of track density and TC origin indicates that each model has different mean biases. Overall, the GCMs simulate the variability of Atlantic TCs well with weaker activity during EP El Nino and stronger activity during La Nina. For CP El Nino, there is a slight increase in the number of TCs as compared with EP El Nino. However, the spatial distribution of track density and TC origin is less consistent among the models. Particularly, there is no indication of increasing TC activity overtheU.S.southeast coastalregionduringCPElNinoasinobservations.Thedifferencebetweenthemodels andobservationsislikelyduetothebiasofthemodelsinresponsetotheshiftoftropicalheatingassociatedwith CP El Nino, as well as the model bias in the mean circulation.

Implementing the Weak Temperature Gradient Approximation with Full Vertical Structure

Abstract A two-column, nonrotating radiative–convective model is formulated in which the free-tropospheric temperature profiles of the two columns are assumed to be identical and steady and the temperature equation is used diagnostically to calculate the vertical velocities [the weak temperature gradient (WTG) approximation]. These vertical velocities and the continuity equation are then used to calculate the horizontal velocities. No horizontal momentum equation is used. This model differs from other two-column models that have used similar formulations in that here both columns are governed by the same laws rather than different dynamical roles being assigned a priori to the “warm” and “cold” columns. The current formulation has the advantage of generalizing trivially to an arbitrary number of columns, a necessity for developing a 3D model under WTG. The two-column solutions compare reasonably well with a reference two-column model that uses a linear, nonrotating horizontal momentum equation and the sam...

Forcings and feedbacks on convection in the 2010 Pakistan flood: Modeling extreme precipitation with interactive large‐scale ascent

Extratropical extreme precipitation events are usually associated with large-scale flow disturbances, strong ascent and large latent heat release. The causal relationships between these factors are often not obvious, however, and the roles of different physical processes in producing the extreme precipitation event can be difficult to disentangle. Here, we examine the large-scale forcings and convective heating feedback in the precipitation events which caused the 2010 Pakistan flood within the Column Quasi-Geostrophic framework. A cloud-revolving model (CRM) is forced with the large-scale forcings (other than large-scale vertical motion) computed from the quasi-geostrophic omega equation with input data from a reanalysis data set, and the large-scale vertical motion is diagnosed interactively with the simulated convection. Numerical results show that the positive feedback of convective heating to large-scale dynamics is essential in amplifying the precipitation intensity to the observed values. Orographic lifting is the most important dynamic forcing in both events, while differential potential vorticity advection also contributes to the triggering of the first event. Horizontal moisture advection modulates the extreme events mainly by setting the environmental humidity, which modulates the amplitude of the convections response to the dynamic forcings. When the CRM is replaced by either a single-column model (SCM) with parameterized convection or a dry model with a reduced effective static stability, the model results show substantial discrepancies compared with reanalysis data. The reasons for these discrepancies are examined, and the implications for global models and theoretical models are discussed.

Tropical Cyclones in the GISS ModelE2

The authors describe the characteristics of tropical cyclone (TC) activity in the GISS general circulation ModelE2 with a horizontal resolution 1°×1°. Four model simulations are analysed. In the first, the model is forced with sea surface temperature (SST) from the recent historical climatology. The other three have different idealised climate change simulations, namely (1) a uniform increase of SST by 2 degrees, (2) doubling of the CO2 concentration and (3) a combination of the two. These simulations were performed as part of the US Climate Variability and Predictability Program Hurricane Working Group. Diagnostics of standard measures of TC activity are computed from the recent historical climatological SST simulation and compared with the same measures computed from observations. The changes in TC activity in the three idealised climate change simulations, by comparison with that in the historical climatological SST simulation, are also described. Similar to previous results in the literature, the changes in TC frequency in the simulation with a doubling CO2 and an increase in SST are approximately the linear sum of the TC frequency in the other two simulations. However, in contrast with previous results, in these simulations the effects of CO2 and SST on TC frequency oppose each other. Large-scale environmental variables associated with TC activity are then analysed for the present and future simulations. Model biases in the large-scale fields are identified through a comparison with ERA-Interim reanalysis. Changes in the environmental fields in the future climate simulations are shown and their association with changes in TC activity discussed.

Dynamic amplification of extreme precipitation sensitivity

Significance Changes in precipitation extremes under climate change are subject to substantial uncertainty. Atmospheric moisture increases alone would make extreme rain events heavier at a well-understood rate of ∼7% K−1, but a component associated with storm dynamics is much less well-understood and can either amplify or reduce that moisture-driven intensification. This paper uses an idealized modeling framework to understand the coupling of these two components, simulating one actual heavy rain event in both the present climate and hypothetical perturbed climates. The increased heating due to increased moisture drives a dynamical increase in large-scale ascent, amplifying the moisture-driven response by as much as a factor of two for warmer climates. A useful starting hypothesis for predictions of changes in precipitation extremes with climate is that those extremes increase at the same rate as atmospheric moisture does, which is ∼7% K−1 following the Clausius–Clapeyron (CC) relation. This hypothesis, however, neglects potential changes in the strengths of atmospheric circulations associated with precipitation extremes. As increased moisture leads to increased precipitation, the increased latent heating may lead to stronger large-scale ascent and thus, additional increase in precipitation, leading to a super-CC scaling. This study investigates this possibility in the context of the 2015 Texas extreme precipitation event using the Column Quasi-Geostrophic (CQG) method. Analogs to this event are simulated in different climatic conditions with varying surface temperature (Ts) given the same adiabatic quasigeostrophic forcing. Precipitation in these events exhibits super-CC scaling due to the dynamic contribution associated with increasing ascent due to increased latent heating, an increase with importance that increases with Ts. The thermodynamic contribution (attributable to increasing water vapor; assuming no change in vertical motion) approximately follows CC as expected, while vertical structure changes of moisture and diabatic heating lead to negative but secondary contributions to the sensitivity, reducing the rate of increase.