Joyce E. Meyerson

North American Climate in CMIP5 Experiments. Part I: Evaluation of Historical Simulations of Continental and Regional Climatology*

AbstractThis is the first part of a three-part paper on North American climate in phase 5 of the Coupled Model Intercomparison Project (CMIP5) that evaluates the historical simulations of continental and regional climatology with a focus on a core set of 17 models. The authors evaluate the models for a set of basic surface climate and hydrological variables and their extremes for the continent. This is supplemented by evaluations for selected regional climate processes relevant to North American climate, including cool season western Atlantic cyclones, the North American monsoon, the U.S. Great Plains low-level jet, and Arctic sea ice. In general, the multimodel ensemble mean represents the observed spatial patterns of basic climate and hydrological variables but with large variability across models and regions in the magnitude and sign of errors. No single model stands out as being particularly better or worse across all analyses, although some models consistently outperform the others for certain variab...

North American Climate in CMIP5 Experiments: Part III: Assessment of Twenty-First-Century Projections*

AbstractIn part III of a three-part study on North American climate in phase 5 of the Coupled Model Intercomparison Project (CMIP5) models, the authors examine projections of twenty-first-century climate in the representative concentration pathway 8.5 (RCP8.5) emission experiments. This paper summarizes and synthesizes results from several coordinated studies by the authors. Aspects of North American climate change that are examined include changes in continental-scale temperature and the hydrologic cycle, extremes events, and storm tracks, as well as regional manifestations of these climate variables. The authors also examine changes in the eastern North Pacific and North Atlantic tropical cyclone activity and North American intraseasonal to decadal variability, including changes in teleconnections to other regions of the globe. Projected changes are generally consistent with those previously published for CMIP3, although CMIP5 model projections differ importantly from those of CMIP3 in some aspects, inc...

California Winter Precipitation Change under Global Warming in the Coupled Model Intercomparison Project Phase 5 Ensemble

AbstractProjections of possible precipitation change in California under global warming have been subject to considerable uncertainty because California lies between the region anticipated to undergo increases in precipitation at mid-to-high latitudes and regions of anticipated decrease in the subtropics. Evaluation of the large-scale model experiments for phase 5 of the Coupled Model Intercomparison Project (CMIP5) suggests a greater degree of agreement on the sign of the winter (December–February) precipitation change than in the previous such intercomparison, indicating a greater portion of California falling within the increased precipitation zone. While the resolution of global models should not be relied on for accurate depiction of topographic rainfall distribution within California, the precipitation changes depend substantially on large-scale shifts in the storm tracks arriving at the coast. Significant precipitation increases in the region arriving at the California coast are associated with an ...

North American Climate in CMIP5 Experiments. Part II: Evaluation of Historical Simulations of Intraseasonal to Decadal Variability

AbstractThis is the second part of a three-part paper on North American climate in phase 5 of the Coupled Model Intercomparison Project (CMIP5) that evaluates the twentieth-century simulations of intraseasonal to multidecadal variability and teleconnections with North American climate. Overall, the multimodel ensemble does reasonably well at reproducing observed variability in several aspects, but it does less well at capturing observed teleconnections, with implications for future projections examined in part three of this paper. In terms of intraseasonal variability, almost half of the models examined can reproduce observed variability in the eastern Pacific and most models capture the midsummer drought over Central America. The multimodel mean replicates the density of traveling tropical synoptic-scale disturbances but with large spread among the models. On the other hand, the coarse resolution of the models means that tropical cyclone frequencies are underpredicted in the Atlantic and eastern North Pa...

Sensitivity of Tropical Tropospheric Temperature to Sea Surface Temperature Forcing

During El Nino, there are substantial tropospheric temperature anomalies across the entire tropical belt as- sociated with the warming of sea surface temperatures (SSTs) in the central and eastern Pacific. The quasi- equilibrium tropical circulation model (QTCM) is used to investigate the mechanisms for tropical tropospheric temperature response to SST forcing. In both observations and model simulations, the tropical averaged tro- pospheric temperature anomaly ^T ˆ9& is approximately linear with the tropical mean SST anomaly ^& for observed T9 SST forcing. Regional SST anomaly experiments are used to estimate regional sensitivity measures and quantify the degree of nonlinearity. For instance, SST anomalies of 38C in the central Pacific would give a nonlinear ^T ˆ9& response about 15% greater than a linear fit to small SST anomaly experiments would predict, but for the maximum observed SST anomaly in this region the response differs by only 5% from linearity. Nonlinearity in ^T ˆ9& response is modest even when local precipitation response is highly nonlinear. While temperature anomalies have large spatial scales, the main precipitation anomaly tends to be local to the SST anomaly regions. The tropical averaged precipitation anomalies ^P9& do not necessarily have a simple relation to tropical averaged tropospheric temperature anomalies or SST forcing. The approximate linearity of the ^T ˆ9& response is due to two factors: 1) the strong nonlinearities that occur locally tend to be associated with the transport terms, which become small in the large-area average; and 2) the dependence on temperature of the top-of-atmosphere and surface fluxes has only weak nonlinearity over the range of ^T ˆ9& variations. Analytical approximations to the QTCM suggest that the direct impact of climatological SST, via flux terms, contributes modestly to regional variations in the sensitivity a of ^T9& to ^& . Wind speed has a fairly strong effect on a but tends to oppose T9 s the direct effect of SST since cold SST regions often have stronger climatological wind, which would yield larger slopes. A substantial contribution to regional variation in a comes from the different reaction of moisture to SST anomalies in precipitating and nonprecipitating regions. Although regions over climatologically warm water have a slightly higher sensitivity, subregions of El Nino SST anomalies even in the colder eastern Pacific contribute substantially to tropospheric temperature anomalies.

Considerations for parameter optimization and sensitivity in climate models

Climate models exhibit high sensitivity in some respects, such as for differences in predicted precipitation changes under global warming. Despite successful large-scale simulations, regional climatology features prove difficult to constrain toward observations, with challenges including high-dimensionality, computationally expensive simulations, and ambiguity in the choice of objective function. In an atmospheric General Circulation Model forced by observed sea surface temperature or coupled to a mixed-layer ocean, many climatic variables yield rms-error objective functions that vary smoothly through the feasible parameter range. This smoothness occurs despite nonlinearity strong enough to reverse the curvature of the objective function in some parameters, and to imply limitations on multimodel ensemble means as an estimator of global warming precipitation changes. Low-order polynomial fits to the model output spatial fields as a function of parameter (quadratic in model field, fourth-order in objective function) yield surprisingly successful metamodels for many quantities and facilitate a multiobjective optimization approach. Tradeoffs arise as optima for different variables occur at different parameter values, but with agreement in certain directions. Optima often occur at the limit of the feasible parameter range, identifying key parameterization aspects warranting attention—here the interaction of convection with free tropospheric water vapor. Analytic results for spatial fields of leading contributions to the optimization help to visualize tradeoffs at a regional level, e.g., how mismatches between sensitivity and error spatial fields yield regional error under minimization of global objective functions. The approach is sufficiently simple to guide parameter choices and to aid intercomparison of sensitivity properties among climate models.

Mechanisms for lagged atmospheric response to ENSO SST forcing

The mechanism and sensitivity of the lagged response of tropical tropospheric temperature to El Nino– Southern Oscillation (ENSO) SST forcing are examined using the Quasi-Equilibrium Tropical Circulation Model (QTCM) coupled to a slab mixed layer ocean model, along with a simple analytical model. It is found that the lag and amplitude of tropospheric temperature response depend on mixed layer depth (MLD), ENSO SST forcing period, areal fraction of the mixed layer ocean, and the strength of Tropics to midlatitude transports. The phase lag is not a monotonic function of mixed layer depth. It maximizes at moderate MLD and, thus, is not very sensitive to MLD in the realistic range. The phase lag asymptotes to values determined by free-atmospheric time scales, between 1 and 2 months, for small or large values of MLD. The amplitude of the tropospheric temperature response decreases with increasing MLD. The phase lag and amplitude of tropospheric temperature both increase as a specified ENSO SST forcing period increases and they appear to be rather insensitive to the seasonal cycle of SST. On the other hand, the phase lag and amplitude of mixed layer ocean SST change monotonically with MLD and ENSO forcing period, with a deeper mixed layer producing longer lag and smaller amplitude of SST anomalies. Longer ENSO SST forcing periods correspond to longer lag and larger amplitude of mixed layer ocean SST anomalies. While the ENSO region convective heating (precipitation) anomalies are closely tied to SST anomalies, the tropical mean precipitation seems best viewed as a complex by-product of the response rather than as a driver. One useful parameter determining the lag of tropospheric temperature to ENSO SST is the freedecay time scale of the coupled system. This parameter combines the effects of surface flux exchanges, heat loss at the top of the atmosphere and from the Tropics to midlatitudes, and finite ocean heat capacity. It is indicative of the extent to which the lagged response of tropical tropospheric temperature to ENSO SST is a coupled phenomenon. Overall, the contribution of coupling to SST outside the ENSO region substantially increases the amplitude and lag of the tropospheric temperature response to ENSO.

Tropical Tropospheric Temperature and Precipitation Response to Sea Surface Temperature Forcing

During an El Nino event, there are substantial tropospheric temperature anomalies across the tropics associated with sea surface temperature (SST) warming in the central and eastern Pacific. The typical spatial scale for teleconnection response of tropospheric temperature tends to be large. On the other hand, the precipitation response exhibits strong compensation between positive response over warm SST anomalies and a complex negative response remotely. The tropical spatial averages of tropospheric temperature and precipitation thus yield an interesting contrast in behavior. Anomalies of tropical averaged precipitation for 3-month averages appear quite scattered in relation to tropical SST anomalies, while the tropical mean tropospheric temperature obeys an approximately linear relationship to SST. This different behavior of tropical mean precipitation and tropospheric temperature in relation to SST is examined in detail using observational data, GCM simulations and idealized experiments with the quasi-equilibrium tropical circulation model (QTCM). Theoretical understanding is provided through a simple analytical model, which suggests that the integral constraint on tropical average precipitation is dominated by dry static energy transport into or out of the tropics. Convection acts to keep tropospheric temperature in quasi-equilibrium (QE) with boundary layer moist static energy, which is in turn held toward SST by surface fluxes. To maintain QE, the tropical average convective heating (i.e., precipitation) anomalies react to oppose any processes that tend to cool the tropical troposphere. Thus, while tropical average tropospheric temperature is closely related to SST, unrelated heating or cooling anomalies such as those due to the tropical-midlatitude transports can create large scatter in tropical average precipitation anomalies.