Two distinctly different forms of tropical Pacific Ocean warming are shown to have substantially different impacts on the frequency and tracks of North Atlantic tropical cyclones. The eastern Pacific warming (EPW) is identical to that of the conventional El Niño, whereas the central Pacific warming (CPW) has maximum temperature anomalies located near the dateline. In contrast to EPW events, CPW episodes are associated with a greater-than-average frequency and increasing landfall potential along the Gulf of Mexico coast and Central America. Differences are shown to be associated with the modulation of vertical wind shear in the main development region forced by differential teleconnection patterns emanating from the Pacific. The CPW is more predictable than the EPW, potentially increasing the predictability of cyclones on seasonal time scales.

[1] This study assesses the CMIP5 decadal hindcast/ forecast simulations of seven state-of-the-art oceanatmosphere coupled models. Each decadal prediction consists of simulations over a 10 year period each of which are initialized every five years from climate states of 1960/1961 to 2005/2006. Most of the models overestimate trends, whereby the models predict less warming or even cooling in the earlier decades compared to observations and too much warming in recent decades. All models show high prediction skill for surface temperature over the Indian, North Atlantic and western Pacific Oceans where the externally forced component and low-frequency climate variability is dominant. However, low prediction skill is found over the equatorial and North Pacific Ocean. The Atlantic Multidecadal Oscillation (AMO) index is predicted in most of the models with significant skill, while the Pacific Decadal Oscillation (PDO) index shows relatively low predictive skill. The multi-model ensemble has in general better-forecast quality than the single-model systems for global mean surface temperature, AMO and PDO.

Tropical Pacific Ocean warming has been separated into two modes based on the spatial distribution of the maximum sea surface temperature (SST) anomaly: an east Pacific warming (EPW) and a central Pacific warming (CPW). When combined with east Pacific cooling (EPC), these three regimes are shown to have different impacts on tropical cyclone (TC) activity over the North Pacific by differential modulation of both local thermodynamic factors and large-scale circulation patterns. In EPW years, the genesis and the track density of TCs tend to be enhanced over the southeastern part and suppressed in the northwestern part of the western Pacific by strong westerly wind shear. The extension of the monsoon trough and the weak wind shear over the central Pacific increases the likelihood of TC activity to the east of the climatological mean TC genesis location. In CPW years, the TC activity is shifted to the west and is extended through the northwestern part of the western Pacific. The westward shifting of CPW-induced heating moves the anomalous westerly wind and monsoon trough through the northwestern part of the western Pacific and provides a more favorable condition for TC landfall. The CPW, on the other hand, produces a large suppression of TC activity in the eastern Pacific basin. In EPC years, all of the variables investigated show almost a mirror image of the EPW.

The seasonal prediction skill for the Northern Hemisphere winter is assessed using retrospective predictions from the ECMWF System 4 (Sys4) and National Center for Environmental Prediction (NCEP) CFS version 2 (CFSv2) coupled atmosphere-ocean seasonal climate prediction systems. Sys4 shows a cold bias in the equatorial Pacific but a warm bias is found in the North Pacific and part of the North Atlantic. The CFSv2 has strong warm bias from the cold tongue region of the eastern Pacific to the equatorial central Pacific and cold bias in broad areas over the North Pacific and the North Atlantic. A cold bias in the Southern Hemisphere is common in both reforecasts. In addition, excessive precipitation is found in the equatorial Pacific, the equatorial Indian Ocean and the western Pacific in Sys4, and in the South Pacific, the southern Indian Ocean and the western Pacific in CFSv2. A dry bias is found for both modeling systems over South America and northern Australia. The mean prediction skill of 2 meter temperature (2mT) and precipitation anomalies are greater over the tropics than the extra-tropics and also greater over ocean than land. The prediction skill of tropical 2mT and precipitation is greater in strong El Nino Southern Oscillation (ENSO) winters than in weak ENSO winters. Both models predict the year-to-year ENSO variation quite accurately, although sea surface temperature trend bias in CFSv2 over the tropical Pacific results in lower prediction skill for the CFSv2 relative to the Sys4. Both models capture the main ENSO teleconnection pattern of strong anomalies over the tropics, the North Pacific and the North America. However, both models have difficulty in forecasting the year-to-year winter temperature variability over the US and northern Europe.

The authors examine the predictability and prediction skill of the Madden-Julian oscillation (MJO) of two ocean-atmosphere coupled forecast systems of ECMWF [Variable Resolution Ensemble Prediction System (VarEPS)] and NCEP [Climate Forecast System, version 2 (CFSv2)]. The VarEPS hindcasts possess five ensemble members for the period 1993-2009 and the CFSv2 hindcasts possess three ensemble members for the period 2000-09. Predictability and prediction skill are estimated by the bivariate correlation coefficient between the observed and predicted Wheeler-Hendon real-time multivariate MJO index (RMM). MJO predictability is beyond 32 days lead time in both hindcasts, while the prediction skill is about 27 days in VarEPS and 21 days in CFSv2 as measured by the bivariate correlation exceeding 0.5. Both predictability and prediction skill of MJO are enhanced by averaging ensembles. Results show clearly that forecasts initialized with (or targeting) strong MJOs possess greater prediction skill compared to those initialized with (or targeting) weak or nonexistent MJOs. The predictability is insensitive to the initial MJO phase (or forecast target phase), although the prediction skill varies with MJO phases.A few common model issues are identified. In both hindcasts, the MJO propagation speed is slower and the MJO amplitude is weaker than observed. Also, both ensemble forecast systems are underdispersive, meaning that the growth rate of ensemble error is greater than the growth rate of the ensemble spread by lead time.

An atmospheric river (AR) event is a strong poleward moisture transport that is composed of a series of spatiotemporally connected instantaneous AR objects. A new object‐based tracking algorithm is developed in this study, which aims to identify an AR event and investigate its life cycle from origin to termination. The algorithm identifies duration, intensity, propagation speed and direction, and the traveled distance throughout the life cycle of the AR event. The tracking algorithm is applied to 6‐hourly column‐integrated water vapor flux from November to March during the period of 1979–2017, with a focus on the North Pacific. Most North Pacific AR events originate in the subtropics over the Northwest Pacific and terminate at higher latitudes over the Northeast Pacific including western North America. On average, long AR events that last more than 72 hrs travel 7 times longer in distance and have stronger intensity than short AR events that last less than 24 hrs. Finally, a new accumulated AR intensity index is developed, which summarizes the overall impact of AR events over a given domain during a certain period by incorporating number, lifetime, and intensities of AR events.

In this study, the intraseasonal variations in storm-track activity, surface air temperature, and precipitation over North America associated with the Madden–Julian oscillation (MJO) in boreal winter (November–April) are investigated. A lag composite strategy that considers different MJO phases and different lag days is developed. The results highlight regions over which the MJO has significant impacts on surface weather on intraseasonal time scales. A north–south shift of storm-track activity associated with the MJO is found over North America. The shift is consistent with the MJO-related surface air temperature anomaly over the eastern United States. In many regions over the western, central, and southeastern United States, the MJO-related precipitation signal is also consistent with nearby storm-track activity. An MJO-related north–south shift of precipitation is also found near the west coast of North America, with the precipitation over California being consistent with the MJO-related storm-track activity over the eastern Pacific. MJO-related temperature and storm-track anomalies are also found near Alaska. Further analyses of streamfunction anomalies and wave activity flux show clear signatures of Rossby wave trains excited by convection anomalies related to MJO phases 3 and 8. These wave trains propagate across the Pacific and North America, bringing an anticyclonic (cyclonic) anomaly to the eastern part of North America, shifting the westerly jet to the north (south), thereby modulating the surface air temperature and storm-track activity over the continent. Rossby waves associated with phases 2 and 6 are also found to impact the U.S. West Coast.

No abstract