The record-breaking mei-yu in the Yangtze-Huaihe River valley (YHRV) in 2020 was characterized by an early onset, a delayed retreat, a long duration, a wide meridional rainbelt, abundant ...precipitation, and frequent heavy rainstorm processes. It is noted that the East Asian monsoon circulation system presented a significant quasi-biweekly oscillation (QBWO) during the mei-yu season of 2020 that was associated with the onset and retreat of mei-yu, a northward shift and stagnation of the rainbelt, and the occurrence and persistence of heavy rainstorm processes. Correspondingly, during the mei-yu season, the monsoon circulation subsystems, including the western Pacific subtropical high (WPSH), the upper-level East Asian westerly jet, and the low-level southwesterly jet, experienced periodic oscillations linked with the QBWO. Most notably, the repeated establishment of a large southerly center, with relatively stable latitude, led to moisture convergence and ascent which was observed to develop repeatedly. This was accompanied by a long-term duration of the mei-yu rainfall in the YHRV and frequent occurrences of rainstorm processes. Moreover, two blocking highs were present in the middle to high latitudes over Eurasia, and a trough along the East Asian coast was also active, which allowed cold air intrusions to move southward through the northwestern and/or northeastern paths. The cold air frequently merged with the warm and moist air from the low latitudes resulting in low-level convergence over the YHRV. The persistent warming in the tropical Indian Ocean is found to be an important external contributor to an EAP/PJ-like teleconnection pattern over East Asia along with an intensified and southerly displaced WPSH, which was observed to be favorable for excessive rainfall over YHRV.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The detection and prevention strategies for drug control have gained significant attention from the drug control committees globally and need the researchers’ attention to improve these strategies ...worldwide. Hence, this research investigates the impact of the
status quo
(SQ) and resistance to the innovative nature of the drug control committee on the failure of detection and prevention strategies (FDPS) in Malaysia. This article also analyzes the mediating role of poor team performance (PTP) among the SQ and resistance to the innovative nature of the drug control committee and the FDPS in Malaysia. This study has employed the primary data collection ways such as questionnaires to gather the data from selected respondents. The researchers also applied the SPSS-AMOS to check the association among variables and testing of hypotheses. The results revealed that the SQ and resistance to the innovative nature of the drug control committee have a positive association with the FDPS in Malaysia. The findings have also exposed that PTP significantly mediates between the SQ and resistance to the innovative nature of the drug control committee and the FDPS in Malaysia. This study guides the policymakers that they should develop the policies that eliminate the SQ nature and motivate the committee to adopt innovations that enhance the team performance and success of detection and prevention strategies in Malaysia.
The first rainy season (FRS), also known as the presummer rainy season, is the first standing stage of the East Asian summer monsoon when over 40% of the annual precipitation is received over South ...China. Based on the start and end dates of the FRS defined by the China Meteorological Administration, this study investigates the interannual variations of the FRS precipitation over South China and its mechanism with daily mean data. The length and start/end date of the FRS vary year to year, and the average length of the FRS is 90 days, spanning from 6 April to 4 July. Composite analyses reveal that the years with abundant FRS precipitation over South China feature weakened anticyclonic wind shear over the Indochina Peninsula in the upper troposphere, southwestward shift of the western Pacific subtropical high, and anticyclonic wind anomalies over the South China Sea in the lower troposphere. The lower-tropospheric southwesterly wind anomalies are especially important because they help to enhance warm advection and water vapor transport toward South China, increase the lower tropospheric convective instability, and shape the pattern of the anomalous ascent over South China. It is further proposed that a local positive feedback between circulation and precipitation exists in this process. The variability of the FRS precipitation can be well explained by a zonal sea surface temperature (SST) dipole in the tropical Pacific and the associated Matsuno–Gill-type Rossby wave response over the western North Pacific. The interannual variability of both the SST dipole and the FRS precipitation over South China is weakened after the year 2000.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
In this work, the evolution and prediction of the persistent and remarkable warm sea surface temperature anomaly (SSTA) in the northeastern Pacific during October 2013–June 2016 are examined. Based ...on experiments with an atmospheric model, the possible contribution of SSTAs in different ocean basins to the atmospheric circulation anomalies is identified. Further, through verifying the real-time forecasts, current capabilities in predicting such an extreme warm event with a state-of-the-art coupled general circulation model are assessed.
During the long-lasting warm event, there were two warm maxima in the area-averaged SSTA around January 2014 and July 2015, respectively. The warm anomaly originated at the oceanic surface and propagated downward and reached about 300 m. Model experiments forced by observed SST suggest that the long persistence of the atmospheric anomalies in the northeastern Pacific as a whole may be partially explained by SST forcing, particularly in the tropical Pacific Ocean associated with a persistent warm SSTA in 2014/15 and an extremely strong El Niño in 2015/16, via its influence on atmospheric circulation over the North Pacific. Nevertheless, it was a challenge to predict the evolution of this warm event, especially for its growth. That is consistent with the fact that the SSTAs in extratropical oceans are largely a consequence of unpredictable atmospheric variability.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
In the winter of 2018/2019, the lower reach of the Yangtze River (LRYR) of China experienced an excessive amount of precipitation with a long duration. Such an extreme event occurred in the mature ...phase of an El Niño under the background of global warming, and thus, attracted great attention in the society and climate community. Presumably, this extreme event was driven by the El Niño. In this work, based on observational diagnoses and real‐time model forecasts, we investigate the contributions of oceanic forcing and the predictability of this event. It is argued that tropical Atlantic warming, interdecadal variation, and central tropical Pacific warming (associated with Central Pacific CP instead of Eastern Pacific El Niño) are three major factors leading to the extreme event. In addition to the recognized impact from sea surface temperature anomalies (SSTAs) associated with CP El Niño, tropical Atlantic warming makes an important contribution to the Atlantic‐Eurasian circulation change through a global zonal wave pattern extending from the tropical Atlantic to East Asia. Moreover, a climate model successfully predicted the wet pattern in LRYR in short (1–5 month) lead real‐time predictions, and captured the observed statistical relationship between the winter precipitation in LRYR and the SSTA in the central tropical Pacific and equatorial Atlantic Oceans. These results indicate that such an event is predictable to some extent.
Tropical Atlantic warming, interdecadal variation, and central tropical Pacific warming (associated with Central Pacific instead of Eastern Pacific El Niño) are three major factors leading to the extremely wet winter of 2018/2019 in the lower reach of the Yangtze River (LRYR). The real‐time prediction results of successfully captured the observed statistical relationship between the winter precipitation in LRYR and the sea surface temperature anomaly (SSTA) in the central tropical Pacific and equatorial Atlantic Oceans indicates that such an event is predictable to some extent. The figure shows the reconstructions of December–January–February (DJF) 2018/2019 precipitation anomaly based on the linear regression with the detrended (a) central Pacific El Niñoand (b) Atlantic Niño SST indices; (c) the interdecadal change of the DJF precipitation in 1989/1990–2018/2019 and 1951/1952–1988/1989; (d) the sum of (a), (b) and (c)
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
An unprecedented extreme positive Indian Ocean dipole event (pIOD) occurred in 2019, which has caused widespread disastrous impacts on countries bordering the Indian Ocean, including the East African ...floods and vast bushfires in Australia. Here we investigate the causes for the 2019 pIOD by analyzing multiple observational datasets and performing numerical model experiments. We find that the 2019 pIOD was triggered in May by easterly wind bursts over the tropical Indian Ocean associated with the dry phase of the boreal summer intraseasonal oscillation, and it was sustained by the local atmosphere–ocean interaction thereafter. During September–November, warm sea surface temperature anomalies (SSTA) in the central-western tropical Pacific Ocean further enhanced the Indian Ocean's easterly winds, bringing the pIOD to an extreme magnitude. The central-western tropical Pacific warm SSTA was strengthened by two consecutive Madden–Julian oscillation (MJO) events that originated from the tropical Indian Ocean. Our results highlight the important roles of cross-basin and cross-time-scale interactions in generating extreme IOD events. The lack of accurate representation of these interactions may be the root for a short lead time in predicting this extreme pIOD with a state-of-the-art climate forecast model.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
The El Niño–Southern Oscillation (ENSO) is a major source of seasonal climate predictability and a key predictor for East Asian precipitation. However, the impacts of ENSO on East Asian ...precipitation are extremely complex and still controversial. Thus, it is necessary and significant to use various (observational and model) data sources to further examine the robustness of the impacts. This study revisits the evolution of the ENSO‐related seasonal precipitation anomalies in East Asia, including symmetric and asymmetric impacts of El Niños and La Niñas, the differences in the influences of eastern Pacific (EP) and central Pacific (CP) El Niños, and the interdecadal change of ENSO influences. The ENSO impact on East Asian precipitation has weakened (strengthened) in the ENSO's developing (decay) phase in the recent two decades. The ENSO impacts are robust in (i) southern China‐lower reaches of the Yangtze River‐southern Japan around the ENSO's mature phase, (ii) western North China in the developing phase and (iii) southwestern China in the decay phase. The distribution of East Asian precipitation anomalies is asymmetric in El Niño and La Niña years. The model simulations forced with observed sea surface temperature generally reproduce the observed evolution of seasonal precipitation anomalies associated with ENSO and confirm the robust impact of ENSO in East Asia. These results indicate the necessity to consider the asymmetric impact of El Niños and La Niñas, to distinguish the El Niño flavours for their impact on the East Asian climate, and to include the interdecadal variation of ENSO influence in addressing East Asian climate anomalies.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
In this work, the roles of El Niño–Southern Oscillation (ENSO) in the variability and predictability of the Pacific–North American (PNA) pattern and precipitation in North America in winter are ...examined. It is noted that statistically about 29% of the variance of PNA is linearly linked to ENSO, while the remaining 71% of the variance of PNA might be explained by other processes, including atmospheric internal dynamics and sea surface temperature variations in the North Pacific. The ENSO impact is mainly meridional from the tropics to the mid–high latitudes, while a major fraction of the non-ENSO variability associated with PNA is confined in the zonal direction from the North Pacific to the North American continent. Such interferential connection on PNA as well as on North American climate variability may reflect a competition between local internal dynamical processes (unpredictable fraction) and remote forcing (predictable fraction). Model responses to observed sea surface temperature and model forecasts confirm that the remote forcing is mainly associated with ENSO and it is the major source of predictability of PNA and winter precipitation in North America.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The prediction skill and bias of tropical Pacific sea surface temperature (SST) in the retrospective forecasts of the Climate Forecast System, version 2 (CFSv2), of the National Centers for ...Environmental Prediction were examined. The CFSv2 was initialized from the Climate Forecast System Reanalysis (CFSR) over 1982–2010. There was a systematic cold bias in the central–eastern equatorial Pacific during summer/fall. The cold bias in the Niño-3.4 index was about −2.5°C in summer/fall before 1999 but suddenly changed to −1°C around 1999, related to a sudden shift in the trade winds and equatorial subsurface temperature in the CFSR.
The SST anomaly (SSTA) was computed by removing model climatology for the periods 1982–98 and 1999–2010 separately. The standard deviation (STD) of forecast SSTA agreed well with that of observations in 1982–98, but in 1999–2010 it was about 200% too strong in the eastern Pacific and 50% too weak near the date line during winter/spring. The shift in STD bias was partially related to change of ENSO characteristics: central Pacific (CP) El Niños were more frequent than eastern Pacific (EP) El Niños after 2000. The composites analysis shows that the CFSv2 had a tendency to delay the onset phase of the EP El Niños in the 1980s and 1990s but predicted their decay phases well. In contrast, the CFSv2 predicted the onset phase of the CP El Niños well but prolonged their decay phase. The hit rate for both El Niño and La Niña was lower in the later period than in the early period, and the false alarm for La Niña increased appreciably from the early to the later period.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The middle and lower reaches of the Yangtze River in eastern China during summer 2020 suffered the strongest mei-yu since 1961. In this work, we comprehensively analyzed the mechanism of the extreme ...mei-yu season in 2020, with focuses on the combined effects of the Madden-Julian Oscillation (MJO) and the cooperative influence of the Pacific and Indian Oceans in 2020 and from a historical perspective. The prediction and predictability of the extreme mei-yu are further investigated by assessing the performances of the climate model operational predictions and simulations.
It is noted that persistent MJO phases 1−2 during June−July 2020 played a crucial role for the extreme mei-yu by strengthening the western Pacific subtropical high. Both the development of La Niña conditions and sea surface temperature (SST) warming in the tropical Indian Ocean exerted important influences on the long-lived MJO phases 1−2 by slowing down the eastward propagation of the MJO and activating convection related to the MJO over the tropical Indian Ocean. The spatial distribution of the 2020 mei-yu can be qualitatively captured in model real-time forecasts with a one-month lead. This can be attributed to the contributions of both the tropical Indian Ocean warming and La Niña development. Nevertheless, the mei-yu rainfall amounts are seriously underestimated. Model simulations forced with observed SST suggest that internal processes of the atmosphere play a more important role than boundary forcing (e.g., SST) in the variability of mei-yu anomaly, implying a challenge in quantitatively predicting an extreme mei-yu season, like the one in 2020.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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