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Attributing sources of tropical cyclogenesis (TCG) bias to large‐scale circulation in global circulation models is challenging. Here, we propose the use of empirical orthogonal functions as an approach to understand model bias of TCG. Two leading modes of large‐scale wind circulations in the West Pacific can explain the TCG frequency and location in both climate reanalysis and the MetUM model. In the reanalysis, the two modes distinguish the summer monsoon trough position and the strength of the north Pacific subtropical high. However, in the model, the wind circulations are biased toward the positive phase of simulated modes thus overestimating TCG in the entire Main Development Region. This bias is further related to the north‐eastward shifted monsoon trough and a weakened subtropical high, and overly strong tropics‐subtropics connections. This approach could be deployed more widely to other basins and models to diagnose the causes of TCG bias. Plain Language Summary: General Circulation Models (GCMs) have bias in tropical cyclogenesis (TCG). This bias largely reduces the credibility of GCMs. In this study, we suggest an empirical orthogonal function‐based approach to trace the sources of TCG bias in the western North Pacific more rigorously back to large‐scale wind circulation patterns. We find that TCG bias in both basin‐wide and regional scales is a combination of the two biased circulation patterns, associated with too strong tropics‐subtropics connections. The two biased circulation patterns are also featured with a north‐eastward shifted monsoon trough and a weakened subtropical high. We choose the Met Office climate models to demonstrate the approach. But, it can be applied to other GCMs and basins to better understand TCG bias and inform further model development. Key Points: Multivariate empirical orthogonal functions are used to diagnose model bias of tropical cyclogenesis (TCG) in the West PacificTwo leading modes of large‐scale wind circulations can explain most of TCG variability in both ECMWF fifth generation climate reanalysis and MetUMIn MetUM, positive TCG bias is related to large‐scale wind circulations biased toward the positive phase of the simulated modes [ABSTRACT FROM AUTHOR]

This study presents an analysis of the equatorial waves in the ERA5 reanalysis and forecasts of the Met Office Global Seasonal Forecast System version 5 (GloSea5), by projecting dynamical fields onto theoretical equatorial wave modes. The seasonal and interannual variation of equatorial wave activity in GloSea5 is evaluated against ERA5 waves. We find that in ERA5 the seasonal and spatial variations of eastward‐moving Kelvin wave activity are mainly determined by the ambient zonal flow, with wave activity being stronger in easterlies than westerlies. For the westward‐moving mixed Rossby–gravity waves and equatorial Rossby waves, the seasonal and spatial variations of the upper‐tropospheric wave activity are determined by both the ambient flow and extratropical forcing with stronger wave activity generally in the westerlies, whilst the lower‐tropospheric wave activity is related to the ambient flow and tropical convection. In GloSea5, the Kelvin wave activity is not well simulated in the upper troposphere, and in general the wave activity and wave‐related convective signal are too weak. In contrast, GloSea5 performs better for the westward‐moving equatorial waves, including their Doppler‐shifted eastward‐moving components, despite a significant overestimation in the Atlantic and African region. The phase of ENSO has a substantial impact on equatorial waves in both ERA5 and GloSea5. The mechanism of the impact is through changes in the ENSO‐related ambient flow, upper‐tropospheric extratropical forcing, and tropical convection. GloSea5 can capture the low‐level Kelvin wave–ENSO relationship reasonably well, with stronger wave activity over the eastern Pacific in El Niño, although the ENSO‐driven variation is too weak. The wave–ENSO relationship for westward‐moving waves is well represented in GloSea5, especially in the upper‐level eastern‐Pacific westerly duct region in the extended boreal winter and the low‐level Indo‐Pacific in all seasons. We conclude that in GloSea5 the representation of the wave–ENSO teleconnection is the key driver for the performance of interannual variability in the wave activity. [ABSTRACT FROM AUTHOR]

Predicting the peak‐season (July–September) tropical cyclones (TCs) in Southeast Asia (SEA) several months ahead remains challenging, related to limited understanding and prediction of the dynamics affecting the variability of SEA TC activity. Here, we introduce a new statistical approach to sequentially identify mutually independent predictors for the occurrence frequency of peak‐season TCs in the South China Sea (SCS) and east of the Philippines (PHL). These predictors, which are identified from the preseason (April‐June) environmental fields, can capture the interannual variability of different clusters of peak‐season TCs, through a cross‐season effect on large‐scale environment that governs TC genesis and track. The physically oriented approach provides a skillful seasonal prediction in the 41‐year period (1979–2019), with r = 0.73 and 0.54 for SCS and PHL TC frequency, respectively. The lower performance for PHL TCs is likely related to the nonstationarity of the cross‐season TC‐environment relationship. We further develop the statistical approach to a hybrid method using the predictors derived from dynamical seasonal forecasts. The hybrid prediction shows a significant skill for both SCS and PHL TCs, for lead times up to four or 5 months ahead, related to the good performance of models for the sea surface temperatures and low‐level winds in the tropics. The statistical and hybrid predictions outperform the dynamical predictions, showing the potential for operational use. Plain Language Summary: Tropical cyclones (TCs) have huge impact in Southeast Asia (SEA). Seasonal forecasts of SEA peak‐season (July–September) TCs remains challenging for both statistical and dynamical models. In this paper, we introduce a novel statistical approach to sequentially identify independent predictors tailored for the frequency of SEA peak‐season TCs. The predictors are routinely constructed from far‐field sea surface temperatures and low‐level winds in the preceding‐season. The main concept in this approach is that each predictor represents a unique cluster of TC formation and propagation in the peak‐season. We also develop the approach to a hybrid prediction method by building the predictors from dynamical seasonal forecasts. The seasonal predictions based on the new approach perform much better than the current statistical and dynamical models. Such predictions can provide useful warning service for SEA TC activity 4–5 months ahead. Key Points: A new approach to identify independent predictors of Southeast Asia (SEA) tropical cyclone (TC) frequency is introducedThe preceding‐season predictors represent different clusters of TC formation and propagation through a cross‐season effectThe new method outperforms existing statistical and dynamical predictions for SEA TCs [ABSTRACT FROM AUTHOR]

Sea levels in the Western North Pacific (WNP) are presented with anomalous intraseasonal variations. This study examines the response of sea level in the WNP to the atmospheric Intraseasonal Oscillation modes, namely the Madden–Julian Oscillation (MJO) and the Boreal Summer Intraseasonal Oscillation (BSISO), using the 25 years (1993–2017) of satellite altimetry and barotropic model output. In winter, the MJO has significant effects on the component of sea level due to the instant wind and atmospheric pressure effects (high‐frequency), showing an eastward propagation pattern in most regions, with the strongest effects in the western marginal seas. The MJO‐associated pattern of dynamical (low‐frequency) component of sea level propagates southward, with the significant effects mostly in the tropics. In summer, the BSISO‐associated pattern of the high‐frequency component of sea level moves from southwest to northeast, with the largest anomalies in the middle of WNP (20°N‐30°N), while the strongest BSISO effects on the low‐frequency component are detectable mostly in the coasts of China and east of the Philippines. The MJO and BSISO can also modulate the probability of extreme sea level events. In winter, during phases 2–5, MJO increases the chance of extreme high events in the high‐frequency component of sea level by 100%–200% in the western coasts and the tropics. In summer, in BSISO phases 6–7, the chance of extreme high events in the high‐frequency component of sea level is enhanced by >300% in the South China Sea and east of the Philippines. Plain Language Summary: The coastal regions of the Western North Pacific (WNP) are densely populated areas, which are exposed to tremendous oceanic hazards. The intraseasonal variability of sea level may alter the occurrence of extreme sea level events when superimposing on other factors under extreme conditions. Thus, understanding the variations of sea level in the WNP on intraseasonal timescales is helpful for marine disaster prevention and mitigation. The atmospheric Intraseasonal Oscillation (ISO) is one of the dominant modes of climate variability on intraseasonal timescales, including the Madden–Julian Oscillation (MJO) and the Boreal Summer Intraseasonal Oscillation (BSISO). In this study, we investigate the relationship between the atmospheric ISO and WNP sea level over the satellite era (1993–2017) using observational data. Our analysis suggests that the atmospheric ISO significantly modulates the intraseasonal variations of WNP sea level both in winter and summer seasons, including the probability of extreme sea level events, through altering the convection and surface wind circulations associated with, or originated from, the atmospheric ISO. These findings imply the potential for developing a statistical approach to predict the intraseasonal variability of sea level extremes. Key Points: Madden–Julian Oscillation (MJO) strongly affects intraseasonal variation of sea level over the Western North Pacific (WNP) in winter, with the largest effects in the tropicsBoreal Summer Intraseasonal Oscillation (BSISO) has significant effects on sea level over the WNP in summer, with the strongest impacts in the subtropics of WNPMJO and BSISO can largely alter the occurrence of extreme sea level events [ABSTRACT FROM AUTHOR]

We examine the merit of atmosphere–ocean coupled models for tropical cyclone (TC) predictions in the western North Pacific (WNP), where accurate TC predictions remain challenging. The UK Met Office operational atmospheric global numerical weather prediction (NWP) model is compared with two trial coupled configurations, in which the operational atmospheric model is coupled to a one‐dimensional mixed‐layer ocean model and a three‐dimensional dynamical ocean model. Reforecasts for the 2016 TC season show that the coupled models outperform the NWP model for TC location predictions, with a systematic improvement of 50–100 km over the seven‐day forecasts, but the coupled models amplify the underestimation of TC intensity in the NWP model. Nearly identical TC predictions (for both location and intensity) are found in the two coupled models, indicating the dominance of thermodynamic processes at the air–sea interface for TC predictions on these timescales. The improved prediction of the TC position in the coupled models is associated with an enhanced Western North Pacific Subtropical High (WNPSH), which introduces an anticyclonic steering flow anomaly that shifts TC tracks further west in the southern part of the region and further east in the northern part. Based on sensitivity experiments, we show that these improvements in the coupled models are due mainly to colder initial sea‐surface temperatures (SSTs). Air–sea feedbacks do not change the WNPSH or TC tracks noticeably. Apart from the effect of the initial SSTs, tropical ocean warming due to air–sea interaction in the coupled forecasts can also reduce the predicted TC intensity, presumably due to a stronger regional Hadley circulation with increased subtropical subsidence. [ABSTRACT FROM AUTHOR]

The European Centre for Medium-range Weather Forecasts (ECMWF) has produced the ocean-atmosphere coupled reanalysis for the twentieth century, CERA-20C, following on from the similar but atmosphere-only reanalysis ERA-20C. Here we demonstrate the capability of CERA-20C in producing more physically consistent ocean and atmosphere boundary conditions, by focusing on sea surface temperature (SST)-precipitation intraseasonal relationships. CERA-20C reproduces well the observed SST-precipitation correlations, while these relationships are poorly represented in ERA-20C, with the greatest discrepancies in the early 1900s. The improved relationships in CERA-20C are due to intraseasonal improvements in SST that are not present in the external HadISST2 product. In CERA-20C, SST-precipitation relationships are slightly weaker in the 1900s than in the 2000s, mainly due to differences in the assimilated observation density. We also find that the coupled model initialized from CERA-20C in the 2000s realistically simulates these relationships, while relaxing SST toward HadISST2 tends to damp these relationships. CERA-20C has improved mean and variance in precipitation over ERA-20C, but these are mostly due to improvements in the atmospheric model and not due to coupled feedbacks. [ABSTRACT FROM AUTHOR]

ABSTRACT This study investigates the relationship between the wind wave climate and the main climate modes of atmospheric variability in the North Atlantic Ocean. The modes considered are the North Atlantic Oscillation ( NAO), the East Atlantic ( EA) pattern, the East Atlantic Western Russian ( EA/ WR) pattern and the Scandinavian ( SCAN) pattern. The wave dataset consists of buoys records, remote sensing altimetry observations and a numerical hindcast providing significant wave height ( SWH), mean wave period ( MWP) and mean wave direction ( MWD) for the period 1989-2009. After evaluating the reliability of the hindcast, we focus on the impact of each mode on seasonal wave parameters and on the relative importance of wind-sea and swell components. Results demonstrate that the NAO and EA patterns are the most relevant, whereas EA/ WR and SCAN patterns have a weaker impact on the North Atlantic wave climate variability. During their positive phases, both NAO and EA patterns are related to winter SWH at a rate that reaches 1 m per unit index along the Scottish coast ( NAO) and Iberian coast ( EA) patterns. In terms of winter MWD, the two modes induce a counterclockwise shift of up to 65° per negative NAO (positive EA) unit over west European coasts. They also increase the winter MWP in the North Sea and in the Bay of Biscay (up to 1 s per unit NAO) and along the western coasts of Europe and North Africa (1 s per unit EA). The impact of winter EA pattern on all wave parameters is mostly caused through the swell wave component. [ABSTRACT FROM AUTHOR]

Heterogeneous catalysts with single‐atom active sites offer a means of expanding the industrial application of noble metal catalysts. Herein, an atomically dispersed Pt1‐Co3O4 catalyst is presented, which exhibits an exceptionally high efficiency for the total oxidation of methanol. Experimental and theoretical investigations indicate that this catalyst consists of Pt sites with a large proportion of occupied high electronic states. These sites possess a strong affinity for inactive Co2+ sites and anchor over the surface of (111) crystal plane, which increases the metal–support interaction of the Pt1‐Co3O4 material and accelerates the rate of oxygen vacancies regeneration. In turn, this is determined to promote the coadsorption of the probe methanol molecule and O2. Density functional theory calculations confirm that the electron transfer over the oxygen vacancies reduces both the methanol adsorption energy and activation barriers for methanol oxidation, which is proposed to significantly enhance the dissociation of the CH bond in the methanol decomposition reaction. This investigation serves as a solid foundation for characterizing and understanding single‐atom catalysts for heterogeneous oxidation reactions. [ABSTRACT FROM AUTHOR]