Abstract

The leading interannual mode of winter surface air temperature over the North American (NA) sector, characterized by a “warm Arctic, cold continents” (WACC) pattern, exerts pronounced influences on NA weather and climate, while its underlying mechanisms remain elusive. In this study, the relative roles of surface boundary forcing versus internal atmospheric processes for the formation of the WACC pattern are quantitatively investigated using a combined analysis of observations and large-ensemble atmospheric global climate model simulations. Internal atmospheric variability is found to play an important role in shaping the year-to-year WACC variability, contributing to about half of the total variance. An anomalous SST pattern resembling the North Pacific mode is identified as a major surface boundary forcing pattern in driving the interannual WACC variability over the NA sector, with a minor contribution from sea ice variability over the Chukchi and Bering Seas. Findings from this study not only lead to improved understanding of underlying physics regulating the interannual WACC variability, but also provide important guidance for improved modeling and prediction of regional climate variability over NA and the Arctic region.

Abstract

The Madden–Julian oscillation (MJO) provides an important source of subseasonal-to-seasonal (S2S) predictability. Improved MJO prediction can be beneficial to S2S prediction of global climate and associated weather extremes. In this study, hindcasts based on an atmosphere–ocean coupled general circulation model (CGCM) are compared to those based on atmosphere general circulation models (AGCMs) to investigate influences of air–sea interactions on MJO prediction. Our results suggest that MJO prediction skill can be extended about 1 week longer in the CGCM hindcasts than AGCM-only experiments, particularly for boreal winter predictions. Further analysis suggests that improved MJO prediction in the CGCM is closely associated with improved representation of moistening processes. Compared to the AGCM experiments, the CGCM better predicts the boundary layer moisture preconditioning to the east of MJO convection, which is generally considered crucial for triggering MJO deep convection. Meanwhile, the widely extended east–west asymmetric structure in free-tropospheric moisture tendency anomalies relative to the MJO convection center as seen in the observations is also well predicted in the CGCM. Improved prediction of MJO moisture processes in CGCM is closely associated with better representation of the zonal scale of MJO circulation and stronger Kelvin waves to the east of MJO convection, both of which have been recently suggested to be conducive to MJO eastward propagation. The above improvements by including air–sea coupling could be largely attributed to the realistic MJO-induced SST fluctuations through the convection–SST feedback. This study confirms a critical role of atmosphere–ocean coupling for the improvement of MJO prediction.

Abstract

Key processes associated with the leading intraseasonal variability mode of wintertime surface air temperature (SAT) over Eurasia and the Arctic region are investigated in this study. Characterized by a dipole distribution in SAT anomalies centered over north Eurasia and the Arctic, respectively, and coherent temperature anomalies vertically extending from the surface to 300 hPa, this leading intraseasonal SAT mode and associated circulation have pronounced influences on global surface temperature anomalies including the East Asian winter monsoon region. By taking advantage of realistic simulations of the intraseasonal SAT mode in a global climate model, it is illustrated that temperature anomalies in the troposphere associated with the leading SAT mode are mainly due to dynamic processes, especially via the horizontal advection of winter mean temperature by intraseasonal circulation. While the cloud–radiative feedback is not critical in sustaining the temperature variability in the troposphere, it is found to play a crucial role in coupling temperature anomalies at the surface and in the free atmosphere through anomalous surface downward longwave radiation. The variability in clouds associated with the intraseasonal SAT mode is closely linked to moisture anomalies generated by similar advective processes as for temperature anomalies. Model experiments suggest that this leading intraseasonal SAT mode can be sustained by internal atmospheric processes in the troposphere over the mid- to high latitudes by excluding forcings from Arctic sea ice variability, tropical convective variability, and the stratospheric processes.

Abstract

African easterly waves (AEWs) exert significant influence on local and downstream high-impact weather including tropical cyclone (TC) genesis over the Atlantic. Accurate representation of AEWs in climate and weather prediction models therefore is necessary for skillful predictions. In this study, we examine simulated AEWs, including their evolution, vertical structure, and linkage to tropical cyclone genesis, in the NASA Goddard Earth Observing System Model, version 5 (GEOS-5) atmospheric global climate model. Identified by the leading empirical orthogonal function mode of time-filtered precipitation, the observed westward propagating AEWs along the southern track over the Atlantic are largely captured in GEOS-5, but with a slower phase speed and significantly weaker amplitude downstream off the West Africa coast. The weak downstream development of AEWs in GEOS-5 is accompanied by much reduced TC genesis over the main development region. Further analyses suggest that the slow westward propagation and weaker AEW amplitude downstream can be ascribed to a weak African easterly jet, while overestimated negative (positive) meridional potential vorticity (PV) gradients appear to the north (south) of 10°N in GEOS-5. The greatly overestimated positive meridional PV gradient to the south of 10°N is expected to generate strong horizontal stretching in the AEW wave pattern in the model, which hinders organization of convection and its feedback to sustain the AEW development. Persistent and vigorous AEW precipitation in the Guinea Highlands of the West Africa coast could also be responsible for reduced westward propagation of AEWs in the model.

Abstract

A model diagnosis has been performed on the nocturnal Great Plains low-level jet (LLJ), which is one of the key elements of the warm season regional climate over North America. The horizontal–vertical structure, diurnal phase, and amplitude of the LLJ are well simulated by an atmospheric general circulation model (AGCM), thus justifying a reevaluation of the physical mechanisms for the formation of the LLJ based on output from this model. A diagnosis of the AGCM data confirms that two planetary boundary layer (PBL) processes, the diurnal oscillation of the pressure gradient force and of vertical diffusion, are of comparable importance in regulating the inertial oscillation of the winds, which leads to the occurrence of maximum LLJ strength during nighttime. These two processes are highlighted in the theories for the LLJ proposed by Holton (1967) and Blackadar (1957). A simple model is constructed in order to study the relative roles of these two mechanisms. This model incorporates the diurnal variation of the pressure gradient force and vertical diffusion coefficients as obtained from the AGCM simulation. The results reveal that the observed diurnal phase and amplitude of the LLJ can be attributed to the combination of these two mechanisms. The LLJ generated by either Holton’s or Blackadar’s mechanism alone is characterized by an unrealistic meridional phase shift and weaker amplitude.

It is also shown that the diurnal phase of the LLJ exhibits vertical variations in the PBL, more clearly at higher latitudes, with the upper PBL wind attaining a southerly peak several hours earlier than the lower PBL. The simple model demonstrates that this phase tilt is due mainly to sequential triggering of the inertial oscillation from upper to lower PBL when surface cooling commences after sunset. At lower latitudes, due to the change of orientation of prevailing mean wind vectors and the longer inertial period, the inertial oscillation in the lower PBL tends to be interrupted by strong vertical mixing in the following day, whereas in the upper PBL, the inertial oscillation can proceed in a low-friction environment for a relatively longer duration. Thus, the vertical phase tilt initiated at sunset is less evident at lower latitudes.

Abstract

Practical predictability of tropical cyclogenesis over the North Atlantic is evaluated in different synoptic flow regimes using the NCEP Global Ensemble Forecast System (GEFS) reforecasts with forecast lead time up to two weeks. Synoptic flow regimes are represented by tropical cyclogenesis pathways defined in a previous study based on the low-level baroclinicity and upper-level forcing of the genesis environmental state, including nonbaroclinic, low-level baroclinic, trough-induced, weak tropical transition (TT), and strong TT pathways. It is found that the strong TT and weak TT pathways have lower predictability than the other pathways, linked to the lower predictability of vertical wind shear and midlevel humidity in the genesis vicinity of a developing TT storm. Further analysis suggests that stronger extratropical influences contribute to lower genesis predictability. It is also shown that the regional and seasonal variations of the genesis predictive skill in the GEFS can be largely explained by the relative frequency of occurrence of each pathway and the predictability differences among pathways. Predictability of tropical cyclogenesis is further discussed using the concept of the genesis potential index.

Abstract

Despite an urgent demand for reliable seasonal prediction of precipitation in California (CA) due to the recent recurrent and severe drought conditions, our predictive skill for CA winter precipitation remains limited. October hindcasts by the coupled dynamical models typically show a correlation skill of about 0.3 for CA winter (November–March) precipitation. In this study, an attempt is made to understand the underlying processes that limit seasonal prediction skill for CA winter precipitation. It is found that only about 25% of interannual variability of CA winter precipitation can be attributed to influences by El Niño–Southern Oscillation (ENSO). Instead, the year-to-year CA winter precipitation variability is primarily due to circulation anomalies independent from ENSO, featuring a circulation center over the west coast United States as a portion of a short Rossby wave train pattern over the North Pacific. Analyses suggest that dynamical models show nearly no skill in predicting these ENSO-independent circulation anomalies, thus leading to limited predictive skill for CA winter precipitation. Low predictability of these ENSO-independent circulation anomalies is further demonstrated by a large ensemble of atmospheric-only climate model simulations. While low predictability of the ENSO-independent circulation anomalies could be due to chaotic internal atmospheric processes over the mid- to high latitudes, possible underexploited predictability sources for CA precipitation in models are also discussed. This study pinpoints an urgent need for improved understanding of the formation mechanisms of ENSO-independent circulation anomalies over the U.S. West Coast for a breakthrough in seasonal prediction of CA winter precipitation.

Abstract

June–October east Pacific warm pool intraseasonal variability (ISV) is assessed in eight atmospheric general circulation simulations. Complex empirical orthogonal function analysis is used to document the leading mode of 30–90-day precipitation variability in the models and Tropical Rainfall Measuring Mission observations. The models exhibit a large spread in amplitude of the leading mode about the observed amplitude. Little relationship is demonstrated between the amplitude of the leading mode and the ability of models to simulate observed north-northeastward propagation.

Several process-oriented diagnostics are explored that attempt to distinguish why some models produce superior ISV. A diagnostic based on the difference in 500–850-hPa averaged relative humidity between the top 5% and the bottom 10% of precipitation events exhibits a significant correlation with leading mode amplitude. Diagnostics based on the vertically integrated moist entropy budget also demonstrate success at discriminating models with strong and weak variability. In particular, the vertical component of gross moist stability exhibits a correlation with amplitude of −0.9, suggesting that models in which convection and associated divergent circulations are less efficient at discharging moisture from the column are better able to sustain strong ISV.

Several other diagnostics are tested that show no significant relationship with leading mode amplitude, including the warm pool mean surface zonal wind, the strength of surface flux feedbacks, and 500–850-hPa averaged relative humidity for the top 1% of rainfall events. Vertical zonal wind shear and 850-hPa zonal wind do not appear to be good predictors of model success at simulating the observed northward propagation pattern.

Abstract

The Madden–Julian oscillation (MJO) represents a primary source of predictability on the intraseasonal time scales and its influence extends from seasonal variations to weather and extreme events. While the last decade has witnessed marked improvement in dynamical MJO prediction, an updated estimate of MJO predictability from a contemporary suite of dynamic models, in conjunction with an estimate of their corresponding prediction skill, is crucial for guiding future research and development priorities. In this study, the predictability of the boreal winter MJO is revisited based on the Intraseasonal Variability Hindcast Experiment (ISVHE), a set of dedicated extended-range hindcasts from eight different coupled models. Two estimates of MJO predictability are made, based on single-member and ensemble-mean hindcasts, giving values of 20–30 days and 35–45 days, respectively. Exploring the dependence of predictability on the phase of MJO during hindcast initiation reveals a slightly higher predictability for hindcasts initiated from MJO phases 2, 3, 6, or 7 in three of the models with higher prediction skill. The estimated predictability of MJO initiated in phases 2 and 3 (i.e., convection in Indian Ocean with subsequent propagation across Maritime Continent) being equal to or higher than other MJO phases implies that the so-called Maritime Continent prediction barrier may not actually be an intrinsic predictability limitation. For most of the models, the skill for single-member (ensemble mean) hindcasts is less than the estimated predictability limit by about 5–10 days (15–25 days), implying that significantly more skillful MJO forecasts can be afforded through further improvements of dynamical models and ensemble prediction systems (EPS).

Abstract

The eastern Pacific (EPAC) warm pool is a region of strong intraseasonal variability (ISV) during boreal summer. While the EPAC ISV is known to have large-scale impacts that shape the weather and climate in the region (e.g., tropical cyclones and local monsoon), simulating the EPAC ISV is still a great challenge for present-day global weather and climate models. In the present study, the predictive skill and predictability of the EPAC ISV are explored in eight coupled model hindcasts from the Intraseasonal Variability Hindcast Experiment (ISVHE). Relative to the prediction skill for the boreal winter Madden–Julian oscillation (MJO) in the ISVHE (~15–25 days), the skill for the EPAC ISV is considerably lower in most models, with an average skill around 10 days. On the other hand, while the MJO exhibits a predictability of 35–45 days, the predictability estimate for the EPAC ISV is 20–30 days. The prediction skill was found to be higher when the hindcasts were initialized from the convective phase of the EPAC ISV as opposed to the subsidence phase. Higher prediction skill was also found to be associated with active MJO initial conditions over the western Pacific (evident in four out of eight models), signaling the importance of exploring the dynamic link between the MJO and the EPAC ISV. The results illustrate the possibility and need for improving dynamical prediction systems to facilitate more accurate and longer-lead predictions of the EPAC ISV and associated weather and short-term climate variability.