Atmospheric and Oceanic Science Letters最新文献

Based on multiple reanalysis data, the authors investigated the distinct impacts of central Pacific (CP) and eastern Pacific (EP) El Niño events on precipitation over West Antarctica and the Antarctic Peninsula in austral spring (September–November). The results demonstrate that EP and CP events have similar impacts on precipitation over the Amundsen–Bellingshausen seas, but opposite impacts on that over the Weddell Sea, especially the Antarctic Peninsula. Mechanistically, the tropical heat sources associated with EP events drive two branches of Rossby wave trains, causing an anomalous anticyclone and cyclone over the Ross–Amundsen–Bellingshausen seas and the Weddell Sea, respectively. Anomalous southerly winds to the east (west) of the anomalous anticyclone (cyclone) advect colder and drier air into the Bellingshausen–Weddell seas and the Antarctic Peninsula, which jointly result in negative precipitation anomalies there. CP events, however, trigger only one weak and westward-shifted Rossby wave train, which induces an anomalous anticyclone and cyclone in the Ross–Amundsen seas and Bellingshausen–Weddell seas, respectively, both 20°–30° west of those generated by EP events. Consequently, anomalous northerly (southerly) winds to the east (west) of the anomalous cyclone cause an increase (a decrease) in precipitation over the Weddell Sea (Amundsen–Bellingshausen seas).

摘要

本文基于多种再分析资料, 研究了中部型 (CP) 和东部型 (EP) El Niño事件对南半球春季 (9–11月) 西南极和南极半岛降水的不同影响. 结果显示, EP和CP事件对阿蒙森-别林斯高晋海的降水具有相似影响, 而对威德尔海, 特别是南极半岛的降水影响相反. 由于EP事件激发两支罗斯贝波列, 分别引起罗斯-阿蒙森-别林斯高森海和威德尔海上空的异常反气旋和气旋, 从而导致别林斯高晋-威德尔海和南极半岛受到干冷的异常偏南风影响, 降水减少. 然而, CP事件仅激发一支相对较弱且偏西的罗斯贝波列, 分别引起罗斯-阿蒙森海和别林斯高晋-威德尔海上空的异常反气旋和气旋, 从而导致南极半岛以西 (东) 受异常偏南 (北) 风影响, 降水减少 (增加).

China's demand for solar energy has been growing rapidly to meet energy transformation targets. However, the potential of solar energy is affected by weather conditions and is expected to change under climate warming. Here, the authors project the photovoltaic (PV) power potential over China under low and high emission scenarios by the 2060s, taking advantage of meteorological variables from 24 CMIP6 models and 4 PV models with varied formats. The ensemble mean of these models yields an average PV power of 277.2 KWh m⁻² yr⁻¹ during 2004–2014, with a decreasing tendency from the west to east. By 2054–2064, the national average PV power potential is projected to increase by 2.29% under a low emission scenario but decrease by 0.43% under a high emission scenario. The emission control in the former scenario significantly enhances surface solar radiation and promotes PV power in the east. On the contrary, strong warming causes inhibitions to PV power generation under the high emission scenario. Extreme warming events on average decrease the PV power potential by 0.28% under the low emission scenario and 0.44% under the high emission scenario, doubling and tripling the present-day loss, respectively. The projections reveal large benefits of controlling emissions for the future solar energy in China due to both the clean atmosphere and the moderate warming.

Investigating the variation in tropical cyclone (TC) activity over the western North Pacific (WNP) in past warm periods helps to better understand TC behaviors in a warming future. In this study, the authors analyze the changes in large-scale TC genesis factors and the associated mechanisms over the WNP during the Last Interglacial (LIG), based on multimodel outputs from the Paleoclimate Modelling Intercomparison Project Phase 4. The results show that potential intensity exhibits a general decrease over the WNP during the LIG in the storm season, dominated by a weakened thermodynamic disequilibrium. The moist entropy deficit shows an overall increase over the WNP, arising from the decreased mid-tropospheric moisture and weakened vertical temperature contrast. Vertical wind shear enhances over the central WNP but weakens over the southwestern WNP, which is induced by the changes in the meridional tropospheric temperature gradient and hence high-level zonal winds. The absolute vorticity shows a general decrease over the WNP, partially linked with the decreased SST over the western tropical Pacific. Based on a genesis potential index, the authors suggest a decrease in genesis potential over the WNP during the LIG, indicating unfavorable conditions for TC genesis. The results highlight the important role of Earth's orbit in regulating TC activity, which may shed light on TC behaviors in a warmer climate.

Hazardous weather events are often accompanied by subseasonal processes, but the forecast skills of subseasonal prediction are still limited. To assess the skill improvement of the constantly updated model version in ECMWF subseasonal-seasonal (S2S) prediction from 2016 to 2022, the performance of yearly updated reforecasts was evaluated against ERA5 reanalysis data using the temporal anomaly correlation coefficient (TCC) as a metric. The newly updated reforecasts exhibit stable superiority at the weather scale of the first two weeks, regardless of whether the 2-m temperature or precipitation forecast is being considered. At the subseasonal time scale starting from the third week, some slight improvements in prediction skills are only found in several tropical regions. Generally, the week-3 TCC values averaged over global land grids still reflect an advancement in prediction skills for updated reforecasts. For the Madden–Julian Oscillation (MJO), reforecasts can reproduce the characteristics of eastward propagation, but there are deviations in the intensity and propagation range of convection anomalies for reforecasts of all seven years. Based on an evaluation of MJO prediction skill using the bivariate anomaly correlation coefficient and bivariate root-mean-square error, some differences are apparent in the MJO prediction skills among the updated reforecasts, but the improvements do not increase monotonically year by year. Despite the inherent limitation of S2S prediction, positive progress has already been achieved via the constantly updated S2S prediction in ECMWF, which reinforces the confidence in further collaboratively improving S2S prediction in the future.

摘要

在2016年至2022年间, ECMWF次季节预测系统不断升级并逐年完成新的回报试验. 本文考察该预测系统逐年升级带来的预测技巧提升潜力. 从2米气温和降水来看, 在起报之后的前两周内天气尺度上预测技巧表现出逐年稳定提升的趋势; 在从第三周开始的次季节时间尺度上, 预测技巧的提升仅限于热带部分区域. MJO预测技巧并不随着模式升级而逐年单调提升. 尽管目前S2S预测技巧存在局限性, 但目前已有的进展增强了在未来深入合作以提高S2S预测技术的信心.

Based on the simulations of 30 CMIP6 models, this paper evaluates their performance in simulating the linkage between the winter Asian-Pacific Oscillation (APO) and precipitation over southern China (SC). Results show that 12 out of the 30 models can reproduce well the observed inverse relationship featuring a positive APO phase corresponding to a decrease in SC precipitation. Associated with the positive APO phase, an anomalous anticyclonic circulation dominates the southern part of Asia in the upper troposphere, and an anomalous cyclonic circulation prevails particularly in the lower troposphere of the South China Sea and the Malay Archipelago. Accordingly, the East Asian westerly jet (EAWJ) shifts northward, and low-level northeasterly anomalies appear over SC, which yield anomalous descending motion and water vapor flux divergence in SC, respectively, hence decreasing the in-situ precipitation. Using the ensemble of the 12 models, the future relationship between the winter APO and SC precipitation under the SSP5-8.5 scenario was further projected. The projection indicates that the APO connection with SC precipitation will still be significant, but weakened slightly, during the second half of the 21st century as compared to the present. Such a weakening may result from the weaker linkage between SC precipitation and the meridional displacement of the EAWJ.

Using all available simulations performed by climate models participating in PMIP4 (Paleoclimate Modelling Intercomparison Project – Phase 4), the authors quantify the seasonality change of surface air temperature over China during the mid-Holocene (6000 years ago) and the associated physical mechanisms. Relative to the preindustrial period, all 16 models consistently show an enhanced temperature seasonality (i.e., summer minus winter temperature) across China during that interglacial period, with a nationally averaged enhancement of 2.44 °C or 9% for the multimodel mean. The temperature seasonality change is closely related with the seasonal contrast variation of surface energy fluxes mainly due to the mid-Holocene orbital forcing. Specifically, the summer–winter increase in surface net shortwave radiation dominates the intensified temperature seasonality at the large scale of China during the mid-Holocene; the surface net longwave radiation has a minor positive contribution in most of the Tibetan Plateau and eastern China; and both the surface latent and sensible heat fluxes show partial offset effects in most of the country. There are uncertainties in the reconstructed temperature seasonality over China during the mid-Holocene based on the proxy data that can reflect seasonal signals.

摘要

利用PMIP4多模式试验数据, 作者量化了中全新世 (距今约6000年) 中国温度季节性变化. 结果表明: 相对于工业革命前期, 所有16个模式一致模拟显示中全新世我国温度季节性 (即夏季与冬季温差) 增强, 平均增幅9%; 这与该时期轨道强迫引起的地表能量通量的季节对比变化密切相关, 其中净短波辐射起主导作用, 净长波辐射作用次之, 感热和潜热为负贡献; 与模拟不同, 重建结果存在不确定性.

The co-occurrence of day and night compound heat extremes has attracted much attention because of the amplified socioeconomic and human health impacts. Based on ERA5 hourly reanalysis data, this study characterized and compared extreme day–night compound humid-heat/high-temperature events (CHHEs/CHTEs) in China as well as the associated impacts. Results indicated that the spatial patterns of summer mean extreme CHHEs are consistent with those of extreme CHTEs, except in northwestern China. A greater magnitude of these two types of events dominates over southern China, but the high-frequency centers are mainly observed over northern China. Significant increasing trends in frequency are captured nationwide, but with much stronger trends detected in northern and western China. Further analysis shows that the anomalies of humidity play a more important role than those of temperature in the occurrence of extreme CHHEs in most parts of China, but particularly in eastern regions. Since 1961, the human population and land areas of China have experienced strongly increasing compound heat extremes, with a faster rate of exposure to extreme CHHEs than to extreme CHTEs. This study highlights the importance of understanding regional changes in humidity when considering heat stress in the future.

Subseasonal reversal of the warm Arctic–cold Eurasia pattern (WACE) could trigger an extreme cold/warm transition in winter and sandstorms in spring over eastern China. An associated subseasonal transition of the sea-ice anomaly also occurs in the Barents–Kara seas (BKS) driven by such remarkable high-latitude atmospheric pattern reversals. Under a warm Arctic and enhanced Ural high, abnormal downward turbulent heat flux and increased downward infrared radiation in the BKS are conducive to sea ice melting. The surface southerly wind drives the sea ice to drift from the thin to perennial ice area and further enlarges the open ocean surface. The opposite mechanism occurs in the opposite phase of WACE, causing positive BKS sea-ice anomalies. When WACE reverses on the subseasonal scale, the above mechanisms occur in early and late winter, respectively, resulting in a significant subseasonal transition of BKS sea-ice anomalies. More importantly, in the last decade, with a more frequent reversal of WACE, the subseasonal transition between early winter and late winter in BKS sea ice has enhanced. The findings of this study establish a comprehensive schematic of the subseasonal reversal of WACE and contribute to better understanding and predicting extreme climate in eastern China.

This study evaluated the capability of 32 models of phase 6 of the Coupled Model Intercomparison Project in modeling the influence of the preceding August Asian–Pacific Oscillation (APO) on subsequent early autumn (September) precipitation over Southeast China and associated atmospheric anomalies, as well as its future projection during 2021–2040 (near-term), 2041–2060 (mid-term), and 2081–2100 (long-term) under different Shared Socioeconomic Pathways (SSPs: SSP2-4.5 and SSP5-8.5). Results indicated that two-thirds of the individual models yielded positive correlations between the APO and Southeast China precipitation that conformed to the observations. On the basis of the capability to reproduce the significantly positive relationship between the APO and Southeast China precipitation, three models were chosen as the “best” model ensemble (BMME). The BMME effectively simulated both the APO-associated precipitation and the atmospheric anomalies, and outperformed the ensemble of the remaining 29 models in terms of the positive correlation between the APO and Southeast China precipitation, and the negative correlations between the meridional displacement of the East Asian jet (EAJ) and the APO and Southeast China precipitation. In general, during three future time periods under both SSPs, the BMME projected persistent negative correlations between the APO and EAJ, and the APO–Southeast China precipitation and EAJ–Southeast China precipitation relationships were projected to weaken. However, considerable discrepancies were evident among the changes projected by the individual models; only the projected changes in the APO–EAJ relationship showed good model agreement.

摘要

本文对32个CMIP6模式对8月亚洲–太平洋涛动 (APO) 与我国东南初秋 (9月) 降水及大气环流联系的模拟能力进行了评估, 并就SSP2-4.5和SSP5-8.5情景下, 未来2021–2040年 (近期) , 2041–2060 (中期) 和2081–2100 (长期) 期间二者联系的变化进行了预估. 基于模式对APO与我国东南初秋降水之间显著正相关关系的再现能力, 选取3个模式作为“最优”模式集合 (BMME) . 研究表明, BMME较好地模拟了与APO相关的我国东南初秋降水和大气环流异常, 且在再现APO与我国东南部降水的正相关关系, 以及东亚高空急流 (EAJ) 经向位移与APO和我国东南部初秋降水之间的负相关关系方面均优于单个模式. 总体而言, 未来不同SSP情景下尽管APO与EAJ之间仍呈负相关关系, 但APO与我国东南初秋降水以及EAJ与我国东南降水的关系将呈减弱确实. 此外, 不同模式预估结果之间存在明显差异, 仅对未来APO-EAJ关系的预估表现出较好的一致性.

A machine learning approach is proposed to identify temperature outliers from Argo float profiles as a complementary procedure to current Argo quality control. A machine learning unsupervised classification (i.e., the Gaussian mixture model, GMM) is applied to cluster the Argo data into classes to construct convex hulls with the smallest polygons encompassing all the data points. Good or bad temperature data are identified as within or outside the polygons based on point-in-polygon analysis implemented by the ray casting algorithm. The South China Sea was selected as an example and results showed that the proposed approach could identify more than 70% of the profiles containing the outliers and mark the outliers automatically at the same time. This highlights the potential of the proposed methodology to be a good complementary quality control method.

摘要

本文提出了一种基于机器学习的Argo浮标温度异常值检测方法. 该方法采用机器学习无监督算法高斯混合模型对Argo浮标数据进行聚类分析, 并构建包围所有数据点的最小多边形的凸包. 基于射线投影算法实现点在多边形内分析, 通过自动识别数据点位于凸包内外来判断该数据点数据质量的好坏. 本文采用南海区域Argo浮标数据对该方法进行测试, 结果表明该方法可以识别70%以上的包含异常值的温度剖面, 同时自动标记出各异常值点.