Joseph Tribbia

The Seasonal Cycle over the Tropical Pacific in Coupled Ocean–Atmosphere General Circulation Models

Abstract The seasonal cycle over the tropical Pacific simulated by 11 coupled ocean–atmosphere general circulation models (GCMs) is examined. Each model consists of a high-resolution ocean GCM of either the tropical Pacific or near-global means coupled to a moderate- or high-resolution atmospheric GCM, without the use of flux correction. The seasonal behavior of sea surface temperature (SST) and eastern Pacific rainfall is presented for each model. The results show that current state-of-the-art coupled GCMs share important successes and troublesome systematic errors. All 11 models are able to simulate the mean zonal gradient in SST at the equator over the central Pacific. The simulated equatorial cold tongue generally tends to be too strong, too narrow, and extend too far west. SSTs are generally too warm in a broad region west of Peru and in a band near 10°S. This is accompanied in some models by a double intertropical convergence zone (ITCZ) straddling the equator over the eastern Pacific, and in others...

The North American Multimodel Ensemble: Phase-1 Seasonal-to-Interannual Prediction; Phase-2 toward Developing Intraseasonal Prediction

The recent U.S. National Academies report, Assessment of Intraseasonal to Interannual Climate Prediction and Predictability, was unequivocal in recommending the need for the development of a North American Multimodel Ensemble (NMME) operational predictive capability. Indeed, this effort is required to meet the specific tailored regional prediction and decision support needs of a large community of climate information users. The multimodel ensemble approach has proven extremely effective at quantifying prediction uncertainty due to uncertainty in model formulation and has proven to produce better prediction quality (on average) than any single model ensemble. This multimodel approach is the basis for several international collaborative prediction research efforts and an operational European system, and there are numerous examples of how this multimodel ensemble approach yields superior forecasts compared to any single model. Based on two NOAA Climate Test bed (CTB) NMME workshops (18 February and 8 April 2...

Dynamical Seasonal Prediction

Abstract Dynamical Seasonal Prediction (DSP) is an informally coordinated multi-institution research project to investigate the predictability of seasonal mean atmospheric circulation and rainfall. The basic idea is to test the feasibility of extending the technology of routine numerical weather prediction beyond the inherent limit of deterministic predictability of weather to produce numerical climate predictions using state-of-the-art global atmospheric models. Atmospheric general circulation models (AGCMs) either forced by predicted sea surface temperature (SST) or as part of a coupled forecast system have shown in the past that certain regions of the extratropics, in particular, the Pacific-North America (PNA) region during Northern Hemisphere winter, can be predicted with significant skill especially during years of large tropical SST anomalies. However, there is still a great deal of uncertainty about how much the details of various AGCMs impact conclusions about extratropical seasonal prediction an...

A Decadal Prediction Case Study: Late Twentieth-Century North Atlantic Ocean Heat Content

An ensemble of initialized decadal prediction (DP) experiments using the Community Climate System Model, version 4 (CCSM4) shows considerable skill at forecasting changes in North Atlantic upper-ocean heat content and surface temperature up to a decade in advance. Coupled model ensembles were integrated forward from each of 10 different start dates spanning from 1961 to 2006 with ocean and sea ice initial conditions obtained from a forced historical experiment, a Coordinated Ocean-Ice Reference Experiment with Interannual forcing (CORE-IA), which exhibits good correspondence with late twentieth-century ocean observations from the North Atlantic subpolar gyre (SPG) region. North Atlantic heat content anomalies from the DP ensemble correlate highly with those from the CORE-IA simulation after correcting for a drift bias.In particular, theobservedlarge,rapid rise in SPGheatcontentin themid-1990sis successfullypredicted in the ensemble initialized in January of 1991. A budget of SPG heat content from the CORE-IA experiment sheds light on the origins of the 1990s regime shift, and it demonstrates the extent to which low-frequency changes in ocean heat advection related to the Atlantic meridional overturning circulation dominate temperature tendencies in this region. Similar budgets from the DP ensembles reveal varying degrees of predictive skill in the individual heat budget terms, with large advective heat flux anomalies from the south exhibiting the highest correlation with CORE-IA. The skill of the DP in this region is thus tied to correct initialization of ocean circulation anomalies, while external forcing is found to contribute negligibly (and for incorrect reasons) to predictive skill in this region over this time period.

Tropical air-sea interaction in general circulation models

An intercomparison is undertaken of the tropical behavior of 17 coupled ocean-atmosphere models in which at least one component may be termed a general circulation model (GCM). The aim is to provide a taxonomy—a description and rough classification—of behavior across the ensemble of models, focusing on interannual variability. The temporal behavior of the sea surface temperature (SST) field along the equator is presented for each model, SST being chosen as the primary variable for intercomparison due to its crucial role in mediating the coupling and because it is a sensitive indicator of climate drift. A wide variety of possible types of behavior are noted among the models. Models with substantial interannual tropical variability may be roughly classified into cases with propagating SST anomalies and cases in which the SST anomalies develop in place. A number of the models also exhibit significant drift with respect to SST climatology. However, there is not a clear relationship between climate drift and the presence or absence of interannual oscillations. In several cases, the mode of climate drift within the tropical Pacific appears to involve coupled feedback mechanisms similar to those responsible for El Niño variability. Implications for coupled-model development and for climate prediction on seasonal to interannual time scales are discussed. Overall, the results indicate considerable sensitivity of the tropical coupled ocean-atmosphere system and suggest that the simulation of the warm-pool/cold-tongue configuration in the equatorial Pacific represents a challenging test for climate model parameterizations.

Optimal Prediction of Forecast Error Covariances through Singular Vectors

Abstract Optimal perturbations, also referred to as singular vectors (SVs), currently constitute an important guideline for the generation of initial ensembles to be used for ensemble prediction. The optimality of these perturbations refers to their property of maximizing prespecified quadratic measures of error growth, given that tangent-linear error evolution is assumed. The goal of ensemble prediction is the accurate prediction of the uncertainty of forecasts made with dynamical numerical weather prediction models. In the present paper the theoretical justification for the use of SVs in ensemble prediction systems is investigated. It is shown that, in a tangent-linear framework, SVs—constructed using covariance information valid at the initial time—evolve into the eigenvectors of the forecast error covariance matrix valid for the end of the optimization interval. As such, SVs represent the most efficient means for predicting the forecast error covariance matrix, given a prespecified number of allowable...

Diurnal Coupling in the Tropical Oceans of CCSM3

Abstract New features that may affect the behavior of the upper ocean in the Community Climate System Model version 3 (CCSM3) are described. In particular, the addition of an idealized diurnal cycle of solar forcing where the daily mean solar radiation received in each daily coupling interval is distributed over 12 daylight hours is evaluated. The motivation for this simple diurnal cycle is to improve the behavior of the upper ocean, relative to the constant forcing over each day of previous CCSM versions. Both 1- and 3-h coupling intervals are also considered as possible alternatives that explicitly resolve the diurnal cycle of solar forcing. The most prominent and robust effects of all these diurnal cycles are found in the tropical oceans, especially in the Pacific. Here, the mean equatorial sea surface temperature (SST) is warmed by as much as 1°C, in better agreement with observations, and the mean boundary layer depth is reduced. Simple rectification of the diurnal cycle explains about half of the sh...

An evaluation of neutral and convective planetary boundary-layer parameterizations relative to large eddy simulations

This paper compares a number of one-dimensional closure models for the planetary boundary layer (PBL) that are currently in use in large-scale atmospheric models. Using the results of a large-eddy simulation (LES) model as the standard of comparison, the PBL models are evaluated over a range of stratifications from free convective to neutral and a range of surface shear stresses. Capping inversion strengths for the convective cases range from weakly to strongly capped. Six prototypical PBL models are evaluated in this study, which focuses on the accuracy of the boundary-layer fluxes of momentum, heat, and two passive scalars. One scalar mimics humidity and the other is a top-down scalar entrained into the boundary layer from above. A set of measures based on the layer-averaged differences of these fluxes from the LES solutions is developed. In addition to the methodological framework and suite of LES solutions, the main result of the evaluation is the recognition that all of the examined PBL parameterizations have difficulty reproducing the entrainment at the top of the PBL, as given by the LES, in most parameter regimes. Some of the PBL models are relatively accurate in their entrainment flux in a subset of parameter regimes. The sensitivity of the PBL models to vertical resolution is explored, and substantive differences are observed in the performance of the PBL models, relative to LES, at low resolution typical of large scale atmospheric models.

Research Needs and Directions of Regional Climate Modeling Using WRF and CCSM

In final form 12 September 2006 ©2006 American Meteorological Society limate varies across a wide range of temporal and spatial scales. Yet, climate modeling has long been approached using global models that can resolve only the broader scales of atmospheric processes and their interactions with land, ocean, and sea ice. Clearly, large-scale climate determines the environment for mesoscale and microscale processes that govern the weather and local climate, but, likewise, processes that occur at the regional scale may have significant impacts on the large-scale circulation. Resolving such scale interactions will lead to a muchimproved understanding of how climate both influences and is influenced by human activities. Since October 2003, the National Center for Atmospheric Research (NCAR) has supported an effort to develop regional climate modeling capability using the Weather Research and Forecasting (WRF) model (see information online at www.wrfmodel.org/index.php) and the Community Climate System Model (CCSM) (information online at www. ccsm.ucar.edu/models). The goal is to develop a next-generation community Regional Climate Model (RCM) that can address both downscaling and upscaling issues in climate modeling. Downscaling is the process of deriving regional climate information based on large-scale climate conditions. Both dynamical and statistical downscaling methods have been used to produce regional climate change scenarios; however, their resolution and physical fidelity are considered inadequate. Hence, the global change community has expressed a strong demand for improved regional climate information to explore the implications of adaptation and mitigation and assess climate change impacts (see information online at www.climatescience. gov/events/workshop2002/). Upscaling encapsulates the aggregate effects of small-scale physical and dynamical processes on Research Needs and Directions of Regional Climate Modeling Using WRF and CCSM

The Spectral Element Atmosphere Model (SEAM): High-Resolution Parallel Computation and Localized Resolution of Regional Dynamics

Abstract Fast, accurate computation of geophysical fluid dynamics is often very challenging. This is due to the complexity of the PDEs themselves and their initial and boundary conditions. There are several practical advantages to using a relatively new numerical method, the spectral-element method (SEM), over standard methods. SEM combines spectral-method high accuracy with the geometric flexibility and computational efficiency of finite-element methods. This paper is intended to augment the few descriptions of SEM that aim at audiences besides numerical-methods specialists. Advantages of SEM with regard to flexibility, accuracy, and efficient parallel performance are explained, including sufficient details that readers may estimate the benefit of applying SEM to their own computations. The spectral element atmosphere model (SEAM) is an application of SEM to solving the spherical shallow-water or primitive equations. SEAM simulated decaying Jovian atmospheric shallow-water turbulence up to resolution T10...