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Hui Zhou
,
Dongliang Yuan
,
Lina Yang
,
Xiang Li
, and
William Dewar

Abstract

The meridional geostrophic transport (MGT) in the interior tropical North Pacific Ocean is estimated based on global ocean heat and salt content data. The decadal variations of the zonally and vertically integrated MGT in the tropical North Pacific Ocean are found to precede the Pacific decadal oscillation (PDO) by 1–3 years. The dynamics of the MGT are analyzed based on Sverdrup theory. It is found that the total meridional transport variability (MGT plus Ekman) is dominated by the MGT variability having positive correlations with the PDO index. The Sverdrup transports differ from the total meridional transport significantly and have insignificant correlations with PDO index, suggesting that the MGT variability is not controlled by the Sverdrup dynamics. In comparison, the simulated meridional transport variability in the models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and the Ocean General Circulation Model for the Earth Simulator are dominated by the Sverdrup transports, having insignificant correlations with the simulated PDO indices. The comparison suggests that the non-Sverdrup component in the MGT is important for the predictability of PDO and that significant deficiencies exist in these models in simulating a realistic structure of the tropical ocean gyre variability and predicting the decadal climate variations associated with it.

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Chenxi Li
,
Xihui Gu
,
Louise J. Slater
,
Jianyu Liu
,
Jianfeng Li
,
Xiang Zhang
, and
Dongdong Kong

Abstract

Heavy precipitation (HP) events can be preceded by moist heatwaves (HWs; i.e., hot and humid weather), and both can be intensified by urbanization. However, the effect of moist HWs on increasing urban HP remains unknown. Based on statistical analyses of daily weather observations and ERA5 reanalysis data, we herein investigate the effect of moist HWs on urban-intensified HP by dividing summer HP events into NoHW- and HW-preceded events in the Yangtze River delta (YRD) urban agglomeration of China. During the period 1961–2019, the YRD has experienced more frequent, longer-lasting, and stronger intense HP events in the summer season (i.e., June–August), and urbanization has contributed to these increases (by 22.66%–37.50%). In contrast, urban effects on HP are almost absent if we remove HW-preceded HP events from all HP events. Our results show that urbanization-induced increases in HP are associated with, and magnified by, moist HWs in urban areas of the YRD region. Moist HWs are conducive to an unstable atmosphere and stormy weather, and they also enhance urban heat island intensity, driving increases in HP over urban areas.

Significance Statement

The contribution of urbanization to increases in heavy precipitation has been widely reported in previous studies. HP events can be preceded by moist heatwaves (hot and humid extremes); however, it is unknown whether moist HWs enhance urban effects on HP. We choose the Yangtze River delta urban agglomeration to explore this question and find that urbanization contributes to the increasing frequency, duration, maximum intensity, and cumulative intensity of HP events in the summer season. However, this urban signal is not detectable if we remove HW-preceded events from all HP events. In other words, moist HWs play a key role in magnifying urbanization-induced increases in HP. Given that urban areas are projected to continue expanding and moist HWs are projected to occur with increasing frequency and intensity in the future, the role of HWs in the urban water cycle merits further investigation.

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Baoqiang Xiang
,
Bin Wang
,
Juan Li
,
Ming Zhao
, and
June-Yi Lee

Abstract

Understanding the change of equatorial Pacific trade winds is pivotal for understanding the global mean temperature change and the El Niño–Southern Oscillation (ENSO) property change. The weakening of the Walker circulation due to anthropogenic greenhouse gas (GHG) forcing was suggested as one of the most robust phenomena in current climate models by examining zonal sea level pressure gradient over the tropical Pacific. This study explores another component of the Walker circulation change focusing on equatorial Pacific trade wind change. Model sensitivity experiments demonstrate that the direct/fast response due to GHG forcing is to increase the trade winds, especially over the equatorial central-western Pacific (ECWP) (5°S–5°N, 140°E–150°W), while the indirect/slow response associated with sea surface temperature (SST) warming weakens the trade winds.

Further, analysis of the results from 19 models in phase 5 of the Coupled Model Intercomparison Project (CMIP5) and the Parallel Ocean Program (POP)–Ocean Atmosphere Sea Ice Soil (OASIS)–ECHAM model (POEM) shows that the projected weakening of the trades is robust only in the equatorial eastern Pacific (EEP) ( 5°S–5°N, 150°–80°W), but highly uncertain over the ECWP with 9 out of 19 CMIP5 models producing intensified trades. The prominent and robust weakening of EEP trades is suggested to be mainly driven by a top-down mechanism: the mean vertical advection of more upper-tropospheric warming downward to generate a cyclonic circulation anomaly in the southeast tropical Pacific. In the ECWP, the large intermodel spread is primarily linked to model diversity in simulating the relative warming of the equatorial Pacific versus the tropical mean sea surface temperature. The possible root causes of the uncertainty for the trade wind change are also discussed.

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Liudan Ding
,
Tim Li
,
Baoqiang Xiang
, and
Melinda Peng

Abstract

Hurricane Sandy (2012) experienced an unusual westward turning and made landfall in New Jersey after its northward movement over the Atlantic Ocean. The landfall caused severe casualties and great economic losses. The westward turning took place in the midlatitude Atlantic where the climatological mean wind is eastward. The cause of this unusual westward track is investigated through both observational analysis and model simulations. The observational analysis indicates that the hurricane steering flow was primarily controlled by atmospheric intraseasonal oscillation (ISO), which was characterized by a pair of anticyclonic and cyclonic circulation systems. The anticyclone to the north was part of a global wave train forced by convection over the tropical Indian Ocean through Rossby wave energy dispersion, and the cyclone to the south originated from the tropical Atlantic through northward propagation. Hindcast experiments using a global coupled model show that the model is able to predict the observed circulation pattern as well as the westward steering flow 6 days prior to Sandy’s landfall. Sensitivity experiments with different initial dates confirm the important role of the ISO in establishing the westward steering flow in the midlatitude Atlantic. Thus the successful numerical model experiments suggest a potential for extended-range dynamical tropical cyclone track predictions.

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Yuhang Xiang
,
Juan Li
,
Bin Wang
,
Libin Ma
, and
Zhiwei Zhu

Abstract

Eastward propagation is an essential feature of the Madden–Julian oscillation (MJO). Yet, it remains a challenge to realistically simulate it by global climate system models, and the reasons are not fully understood. This study evaluates the capability of 20 Coupled Model Intercomparison Project phase 6 (CMIP6) models in simulating MJO’s eastward propagation and its intrinsic links with the dynamic–thermodynamic structures and the background mean states, aiming at better understanding the sources of the simulation errors. The metrics to evaluate the MJO internal dynamics consists of six parameters: 1) the east–west asymmetry in the low-level circulation, 2) the boundary layer moisture convergence propagation, 3) the vertical tilt of equivalent potential temperature or moist static energy, the vertical structures of 4) diabatic heating and 5) available potential energy generation, and 6) upper-level diabatic heating and divergence. We also gauge the performance of three MJO-related background mean-state fields, including precipitation, sea surface temperature, and low-level moist static energy. It is argued that these parameters are relevant internal and external factors that could affect MJO eastward propagation. We find that the boundary layer moisture convergence is most tightly coupled with the eastward propagation of MJO and controls the premoistening, destabilization, and the leading low-level diabatic heating and available potential energy generation. The CMIP6 models exhibit significant improvements against CMIP5 models in simulating MJO dynamic–thermodynamic structures and the mean states. The diagnostics in this study could help to identify the possible processes related to CMIP6 models’ shortcomings and shed light on how to improve simulation of MJO eastward propagation in the future.

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Cheng-Dong Xu
,
Jin-Feng Wang
,
Mao-Gui Hu
, and
Qing-Xiang Li

Abstract

Some climate datasets are incomplete at certain places and times. A novel technique called the point estimation model of Biased Sentinel Hospitals-based Area Disease Estimation (P-BSHADE) is introduced to interpolate missing data in temperature datasets. Effectiveness of the technique was empirically evaluated in terms of an annual temperature dataset from 1950 to 2000 in China. The P-BSHADE technique uses a weighted summation of observed stations to derive unbiased and minimum error variance estimates of missing data. Both the ratio and covariance between stations were used in calculation of these weights. In this way, interpolation of missing data in the temperature dataset was improved, and best linear unbiased estimates (BLUE) were obtained. Using the same dataset, performance of P-BSHADE was compared against three estimators: kriging, inverse distance weighting (IDW), and spatial regression test (SRT). Kriging and IDW assume a homogeneous stochastic field, which may not be the case. SRT employs spatiotemporal data and has the potential to consider temperature nonhomogeneity caused by topographic differences, but has no objective function for the BLUE. Instead, P-BSHADE takes into account geographic spatial autocorrelation and nonhomogeneity, and maximizes an objective function for the BLUE of the target station. In addition to the theoretical advantages of P-BSHADE over the three other methods, case studies for an annual Chinese temperature dataset demonstrate its empirical superiority, except for the SRT from 1950 to 1970.

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Baoqiang Xiang
,
Ming Zhao
,
Xianan Jiang
,
Shian-Jiann Lin
,
Tim Li
,
Xiouhua Fu
, and
Gabriel Vecchi

Abstract

Based on a new version of the Geophysical Fluid Dynamics Laboratory (GFDL) coupled model, the Madden–Julian oscillation (MJO) prediction skill in boreal wintertime (November–April) is evaluated by analyzing 11 years (2003–13) of hindcast experiments. The initial conditions are obtained by applying a simple nudging technique toward observations. Using the real-time multivariate MJO (RMM) index as a predictand, it is demonstrated that the MJO prediction skill can reach out to 27 days before the anomaly correlation coefficient (ACC) decreases to 0.5. The MJO forecast skill also shows relatively larger contrasts between target strong and weak cases (32 versus 7 days) than between initially strong and weak cases (29 versus 24 days). Meanwhile, a strong dependence on target phases is found, as opposed to relative skill independence from different initial phases. The MJO prediction skill is also shown to be about 29 days during the Dynamics of the MJO/Cooperative Indian Ocean Experiment on Intraseasonal Variability in Year 2011 (DYNAMO/CINDY) field campaign period. This model’s potential predictability, the upper bound of prediction skill, extends out to 42 days, revealing a considerable unutilized predictability and a great potential for improving current MJO prediction.

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Shuyun Feng
,
Xihui Gu
,
Sijia Luo
,
Ruihan Liu
,
Aminjon Gulakhmadov
,
Louise J. Slater
,
Jianfeng Li
,
Xiang Zhang
, and
Dongdong Kong

Abstract

Drylands play an essential role in Earth’s environment and human systems. Although dryland expansion has been widely investigated in previous studies, there is a lack of quantitative evidence supporting human-induced changes in dryland extent. Here, using multiple observational datasets and model simulations from phase 6 of the Coupled Model Intercomparison Project, we employ both correlation-based and optimal fingerprinting approaches to conduct quantitative detection and attribution of dryland expansion. Our results show that spatial changes in atmospheric aridity (i.e., the aridity index defined by the ratio of precipitation to potential evapotranspiration) between the recent period 1990–2014 and the past period 1950–74 are unlikely to have been caused by greenhouse gas (GHG) emissions. However, it is very likely (at least 95% confidence level) that dryland expansion at the global scale was driven principally by GHG emissions. Over the period 1950–2014, global drylands expanded by 3.67% according to observations, and the dryland expansion attributed to GHG emissions is estimated as ∼4.5%. Drylands are projected to continue expanding, and their populations to increase until global warming reaches ∼3.5°C above preindustrial temperature under the middle- and high-emission scenarios. If warming exceeds ∼3.5°C, a reduction in population density would drive a decrease in dryland population. Our results for the first time provide quantitative evidence for the dominant effects of GHG emissions on global dryland expansion, which is helpful for anthropogenic climate change adaptation in drylands.

Significance Statement

In the past decades, global drylands have been reported to show changes in space and time, based on atmospheric aridity (i.e., aridity index defined by the ratio of precipitation to potential evapotranspiration). Using two detection and attribution methods, the spatial change patterns of atmospheric aridity between 1990–2014 and 1950–74 are unlikely to be driven by greenhouse gas (GHG) emissions, whereas the temporal expansion of global drylands (i.e., 3.67% from 1950 to 2014) is principally attributed to GHG emissions (contribution: ∼122%). Quantitative evidence from the detection and attribution analysis supports the dominant role of greenhouse gas emissions in global dryland expansion, which will increase the population suffering from water shortages under future warming unless climate adaptation is adopted.

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Lihong Wei
,
Xihui Gu
,
Louise J. Slater
,
Yangchen Lai
,
Dongdong Kong
,
Jianyu Liu
,
Jianfeng Li
, and
Xiang Zhang

Abstract

Precipitation induced by tropical cyclones (TCs) over cities is associated with both TC duration and urbanization; however, observational evidence of the impacts of TC duration and urbanization on precipitation in megalopolises is limited. In this study, the Yangtze River Delta (YRD) of eastern China is taken as a typical region because this region has been experiencing both rapid urbanization processes and frequent TC attacks. During 1979–2018, we find reduced translation speed and increased meandering of TCs over the YRD, resulting in increased TC duration and the proportion of TC stalling in this region. The correlation between TC duration and TC-induced precipitation amount is significant across the YRD region but is relatively weak in areas with faster urbanization expansion rates. Long-term increases in TC-induced precipitation are found in both rural and urban areas but are larger for urban areas. Urbanization plays an important role in enhancing TC-induced precipitation over urban areas of the YRD region. Areas with faster urbanization expansion rates and longer TC durations have larger TC-induced precipitation, suggesting that urban expansion and TC duration jointly amplify TC-induced precipitation. Our findings suggest that urban planners, in areas potentially affected by TCs, should consider adaptation measures to mitigate the impacts of urban rainstorms amplified by the combined effects of TCs and urbanization.

Significance Statement

The combined impacts of tropical cyclone (TC) duration and urbanization on precipitation have received limited attention, especially in populated urban areas. Here, we focus on the Yangtze River Delta (YRD) of eastern China, an urban agglomeration frequently impacted by TCs. We find that slowed translation and increased meandering of TCs have led to longer TC duration and stalling over the 500-km YRD buffer during 1979–2018. Significant positive correlation between TC duration and TC-induced precipitation indicates that longer-lasting TCs trigger greater precipitation. The greater TC-induced precipitation due to increased TC duration is further amplified by urban expansion.

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Xianan Jiang
,
Baoqiang Xiang
,
Ming Zhao
,
Tim Li
,
Shian-Jiann Lin
,
Zhuo Wang
, and
Jan-Huey Chen

Abstract

Motivated by increasing demand in the community for intraseasonal predictions of weather extremes, predictive skill of tropical cyclogenesis is investigated in this study based on a global coupled model system. Limited intraseasonal cyclogenesis prediction skill with a high false alarm rate is found when averaged over about 600 tropical cyclones (TCs) over global oceans from 2003 to 2013, particularly over the North Atlantic (NA). Relatively skillful genesis predictions with more than 1-week lead time are only evident for about 10% of the total TCs. Further analyses suggest that TCs with relatively higher genesis skill are closely associated with the Madden–Julian oscillation (MJO) and tropical synoptic waves, with their geneses strongly phase-locked to the convectively active region of the MJO and low-level cyclonic vorticity associated with synoptic-scale waves. Moreover, higher cyclogenesis prediction skill is found for TCs that formed during the enhanced periods of strong MJO episodes than those during weak or suppressed MJO periods. All these results confirm the critical role of the MJO and tropical synoptic waves for intraseasonal prediction of TC activity. Tropical cyclogenesis prediction skill in this coupled model is found to be closely associated with model predictability of several large-scale dynamical and thermodynamical fields. Particularly over the NA, higher predictability of low-level relative vorticity, midlevel humidity, and vertical zonal wind shear is evident along a tropical belt from the West Africa coast to the Caribbean Sea, in accord with more predictable cyclogenesis over this region. Over the extratropical NA, large-scale variables exhibit less predictability due to influences of extratropical systems, leading to poor cyclogenesis predictive skill.

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