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The Tarim Basin is a large inland arid basin in the arid region of northwest China and has been experiencing significant "warming and wetting" since 1987. As a result, the purpose of this paper is to determine whether the climate transition phenomenon occurred in the Tarim Basin as well as the role of atmospheric circulation in this process. We use meteorological data and atmospheric circulation indexes to study the seasonal trends of climate change in this region from 1987 to 2020 to understand how they are affected by atmospheric circulation. The findings show that, from 1987 to 2020, the Tarim Basin experienced significant warming and wetting; with the exception of the winter scale, all other seasonal scales exhibited a clear warming and wetting trend. From the perspective of spatial distribution, most of the areas showed a significant warming trend, and the warming amplitude around the basin is greater than that in the central area of the basin. However, there are significant regional differences in precipitation change rates. Meanwhile, wavelet analysis shows that there is a significant oscillation period of 17–20 years between climate change and the atmospheric circulation index during 1987–2020. The correlation analysis shows that the Pacific decadal oscillation (PDO) and El Niño-Southern Oscillation (ENSO) are the main influencing factors of climate change in the Tarim Basin at different seasonal scales, while the teleconnection of the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) is low and the PDO dominates the summer and autumn temperature changes in the Tarim Basin. The research results of this paper show that, despite the warming and wetting trends since 1987 in the Tarim Basin, the climate type did not change. From 1987 to 2020, the main teleconnection factors of climate change in the Tarim Basin were PDO and ENSO. [ABSTRACT FROM AUTHOR]

The westerly circulation and the monsoon circulation are the two major atmospheric circulation systems affecting the middle latitudes of the Northern Hemisphere (NH), which have significant impacts on climate and environmental changes in the middle latitudes. However, until now, people's understanding of the long-term paleoenvironmental changes in the westerly- and monsoon-controlled areas in China's middle latitudes is not uniform, and the phase relationship between the two at different time scales is also controversial, especially the exception to the "dry gets drier, wet gets wetter" paradigm in global warming between the two. Based on the existing literature data published, integrated paleoenvironmental records, and comprehensive simulation results in recent years, this study systematically reviews the climate and environmental changes in the two major circulation regions in the mid-latitudes of China since the Middle Pleistocene, with a focus on exploring the phase relationship between the two systems at different time scales and its influencing mechanism. Through the reanalysis and comparative analysis of the existing data, we conclude that the interaction and relationship between the two circulation systems are relatively strong and close during the warm periods, but relatively weak during the cold periods. From the perspective of orbital, suborbital, and millennium time scales, the phase relationship between the westerly and Asian summer monsoon (ASM) circulations shows roughly in-phase, out-of-phase, and anti-phase transitions, respectively. There are significant differences between the impacts of the westerly and ASM circulations on the middle-latitude regions of northwest China, the Qinghai–Tibet Plateau, and eastern China. However, under the combined influence of varied environmental factors such as BHLSR (boreal high-latitude solar radiation), SST (sea surface temperature), AMOC (north Atlantic meridional overturning circulation), NHI (Northern Hemisphere ice volume), NAO (North Atlantic Oscillation), ITCZ (intertropical convergence zone), WPSH (western Pacific subtropical high), TIOA (tropical Indian Ocean anomaly), ENSO (El Niño/Southern Oscillation), CGT/SRP (global teleconnection/Silk Road pattern), etc., there is a complex and close coupling relationship between the two, and it is necessary to comprehensively consider their "multi-factor's joint-action" mechanism and impact, while, in general, the dynamic mechanisms driving the changes of the westerly and ASM circulations are not the same at different time scales, such as orbital, suborbital, centennial to millennium, and decadal to interannual, which also leads to the formation of different types of phase relationships between the two at different time scales. Future studies need to focus on the impact of this "multi-factor linkage mechanism" and "multi-phase relationship" in distinguishing the interaction between the westerly and ASM circulation systems in terms of orbital, suborbital, millennium, and sub-millennium time scales. [ABSTRACT FROM AUTHOR]

Atmosphere clearness is the single most essential parameter determining surface solar radiation. However, few studies have investigated the interannual variations in China's atmosphere clearness and the impacts of El Niño–Southern Oscillation on it. This study aims to fill the knowledge gap by calculating the clearness index using the China Meteorological Forcing Dataset version 1.7 and then analyzing the correlations between the interannual anomaly and the Niño-3.4 index. The results show that there is a significantly negative correlation in the southeastern coastal regions, northern Xinjiang, northeastern Xizang, and areas from northern Hebei to middle Inner Mongolia. In these areas, the higher the ENSO index, the lower the clearness index, and, coincidingly, positive precipitation anomalies are reported in previous studies. The impacts of El Niño and La Niña vary with seasons. The ENSO events have generally opposite impacts in the seasons other than summer. El Niño tends to decrease the clearness index, while La Niña tends to decrease the atmosphere clearness in most territories of China. The impacts are different in the places of statistical significance. The negative impacts of El Niño are significant in the southeastern coastal regions of China in winter and in northeast China in autumn. The positive impacts of La Niña are significant in the southwestern and northeastern China in the autumn. In these seasons, ENSO's impacts scale with the strength of the event. Stronger events amplify the magnitude of the anomalies, while the spatial patterns of the anomalies are kept almost invariant. In summer, ENSO's impacts exhibit different characteristics than in the other seasons and between the El Niño and La Niña events. For the El Niño events, the impacts are insignificant in most territories of China, even for the strong ones. La Niña has a larger influence on the summertime clearness than El Niña, and the spatial pattern of the La Niña's impacts varies with the event strength. The anomalies during strong La Niña events have a tripolar pattern with a positive anomaly in south and north China and a negative anomaly in between. The pattern suggests that the relationship between the clearness index and precipitation is different during strong La Niña events. These findings would provide valuable insights into the interannual variations of atmosphere clearness in China and could be clues to further investigation. The revealed impacts of El Niño–Southern Oscillation should be important for developing solar energy. [ABSTRACT FROM AUTHOR]

Based on the 30-year global hourly sea surface temperature (SST) dataset (MLSST) produced by the National Marine Environmental Forecasting Center, Ministry of Natural Resources of China, we analyzed the variability of diurnal sea surface temperature amplitude (DSST) of the tropical Indian Ocean at multiple time scales, as well as its influencing factors. The results show that the DSST in the Arabian Sea, Bay of Bengal, and equatorial Indian Ocean exhibits a bimodal seasonal variation with a semi-annual cycle, while the DSST in the southern Indian Ocean shows an annual cycle. The seasonal variation of DSST is mainly influenced by factors such as sea surface wind speed, shortwave solar radiation, and precipitation. The DSST in the equatorial Indian Ocean is generally higher during El Niño years compared to La Niña years. At the intraseasonal scale, the large standard deviation of DSST in boreal winter is mainly distributed in the southern hemisphere, while the large standard deviation of DSST in boreal summer shifts northward. The intraseasonal variation amplitude of DSST in boreal winter of the tropical Indian Ocean is greater than that in boreal summer. The DSST in the tropical Indian Ocean exhibits significant variation characteristics at multi-time scales. This study provides reference for numerical simulation of air-sea interaction patterns in the tropical Indian Ocean, as well as improvement of short-term climate prediction. [ABSTRACT FROM AUTHOR]

In recent years, more and more record-breaking extreme weather/climate events have been reported from the Asian monsoon region, which have caused tremendous loss of property and lives. In this paper, we analyzed the Asian summer monsoon (ASM) variability during the Holocene and evaluated future climate extremes in monsoonal China from a paleoclimatic view. We found a significant regime transition to more chaotic fluctuations, with enhanced decadal variability of the ASM since 6.6 ka BP. We suggested the gradual intensification of ENSO was responsible for enhancing the ASM variability since the late mid-Holocene. If the observed relationship of monsoon mean intensity, ENSO and decadal variability of the ASM in the past 11.2 ka continue to exist, enhanced decadal variability of ASM in the future warming world will be expected. As a result, the intensification of daily precipitation extremes, superimposed on enhanced decadal variability of ASM, might make the record-breaking extremes more frequent in the future, increasing the risk of climate-related disasters in China. [ABSTRACT FROM AUTHOR]

In this work, we studied the influence of spring (SP) and summer (SU) El Niño events on the landfalling tropical cyclones (TCs) in China. The results showed that compared to SU El Niño years, the average latitude of the landfalling TCs in SP El Niño years shifted significantly southward and that the average TC intensity was significantly stronger, especially in the post-landfall period. Additionally, more severe tropical storm-level TCs generated over the South China Sea made landfall in China. Meanwhile, in SP El Niño years, landfalling TCs in southern China had a greater landfall intensity, but landfalling TCs in eastern China were the opposite. These changes in TC intensity during the SP El Niño years could be attributed to more favorable dynamical and thermodynamical conditions, which are beneficial for maintaining TC intensity and duration after landfall. These results could have important implications for an in-depth understanding of TC activities, as well as TC disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

Based on 35-year (1981–2015) ensemble (24 members) hindcasts of the IAP/LASG global seasonal prediction system named FGOALS-f2 V1.0 (FGOALS-f2), the tropical cyclone (TC) seasonal prediction skills over the South China Sea (SCS) during the TC peak season (July–November) are evaluated. Starting the prediction from June 20th, FGOALS-f2 can well capture the seasonal mean characteristics for both the genesis location and track of TCs over the SCS. For seasonal anomalous TC numbers, FGOALS-f2 underestimates the maximum and minimum of the TC number compared to the observation. The temporal correlation coefficients (TCCs) between FGOALS-f2 and the observation are 0.39 for the TC number and 0.51 for accumulated cyclone energy (ACE) over the SCS, respectively, which are both above the 95% significant level. Additionally, FGOALS-f2 has acceptable prediction skill for the seasonal mean number of TCs landing on three areas (coastal southeastern China, Indochina Peninsula, and Philippines) surrounding the SCS. The skillful prediction of SCS TCs could be ascribed to the well-predicted tropical anomaly of sea surface temperature (SSTA), TC and El Niño-Southern Oscillation (TC-ENSO) relations, and Genesis potential index (GPI). [ABSTRACT FROM AUTHOR]

The El Niño Southe58rn Oscillation (ENSO) is a typical oscillation affecting climate change, and its stable periodicity, long-lasting effect, and predictable characteristics have become important indicators for regional climate prediction. In this study, we analyze the Standardized Precipitation Evapotranspiration Index (SPEI), the Niño3.4 index, the Southern Oscillation Index (SOI), and the Multivariate ENSO Index (MEI). Additionally, we explore the spatial and temporal distribution of the correlation coefficients between ENSO and SPEI and the time lag between ENSO events of varying intensities and droughts. The results reveal that the use of Nino3.4, MEI, and SOI produces differences in the occurrence time, end time, and intensity of ENSO events. Nino3.4 and MEI produce similar results for identifying ENSO events, and the Nino3.4 index accurately identifies and describes ENSO events with higher reliability. In China, the drought-sensitive areas vulnerable to ENSO events include southern China, the Jiangnan region, the middle and lower reaches of the Yangtze River, and the arid and semi-arid areas of northwestern China. Droughts in these areas correlate significantly with meteorological drought, and time-series correlations between ENSO events and droughts are significantly stronger in regions close to the ocean. Drought occurrence lags ENSO events: when using the Niño3.4 index to identify ENSO, droughts lag the strongest and weakest El Niño events by 0–12 months. However, when using the MEI as a criterion for ENSO, droughts lag the strongest and weakest El Niño events by 0–7 months. The time lag between the strongest ENSO event and drought is shorter than that for the weakest ENSO event, and droughts have a wider impact. The results of this study can provide a climate-change-compatible basis for drought monitoring and prediction. [ABSTRACT FROM AUTHOR]

A tree-ring width chronology was developed from the Chinese pine (Pinus tabuliformis) in northern North China. To acquire a long-term perspective on the history of droughts in this region, the Standardized Precipitation Evapotranspiration Index (SPEI) from August of the previous year to February of the current year was reconstructed for the period of 1903–2012 AD. The reconstruction explained 46.6% of the instrumental records over the calibration period of 1952–2012. Five dry periods (1916–1927, 1962–1973, 1978–1991, 1994–1999 and 2002–2005) and three wet periods (1908–1915, 1928–1961 and 1974–1977) were found in the reconstructed period, and most of the dry years (periods) in the reconstruction were supported by historical records. Comparisons between the reconstruction and other nearby dryness/wetness indices and precipitation reconstructions demonstrated a good repeatability and high reliability in our reconstruction. Spatial correlation implied that the reconstruction could represent regional hydroclimatic characteristics on a larger regional scale. Significant periodicities and correlations were observed between the reconstructed data and the quasi-biennial oscillation (QBO), El Niño–Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO), which suggested that the hydroclimatic variation in northern North China may be closely connected to remote oceans. The significant and high correlation between the reconstructed series and sea surface temperatures (SSTs) in the eastern equatorial and Southeast Pacific Ocean indicated that ENSO may be the main factor influencing the regional climate. [ABSTRACT FROM AUTHOR]

With the aggravation of the ocean–atmosphere cycle anomaly, understanding the potential teleconnections between climate indices and drought/flood conditions can help us know natural hazards more comprehensively to better cope with them. This study aims at exploring the spatiotemporal patterns of drought and its multi-scale relations with typical climate indices in the Huaihe River Basin. First, the spatial patterns were identified based on the seasonal Standardized Precipitation Index (SPI)-3 during 1956–2020 by means of the Empirical Orthogonal Function (EOF). The two leading sub-regions of spring and winter droughts were determined. Then, we extracted the periodicity of spring and winter SPI-3 series and the corresponding seasonal climate indices (Arctic Oscillation (AO), Bivariate El Niño–Southern Oscillation (ENSO)Timeseries (BEST), North Atlantic Oscillation (NAO), Niño3, and Southern Oscillation Index (SOI)) and the sunspot number by using the Continuous Wavelet Transform (CWT). We further explored the teleconnections between spring drought, winter drought, and climate indices and the sunspot number by using Cross Wavelet Transform (XWT) and Wavelet Coherence (WTC) analyses. The results show that there are in-phase multi-scale relations between spring/winter PC1 and AO, BEST, and Niño3, of which the climate indices lead spring PC1 by 1.5–2 years and the climate indices lag winter PC1 by 1.5–3 years. Anti-phase relations between spring PCs and SOI and the sunspot number were observed. NAO mainly affects the interdecadal variation in spring drought, while AO and Niño3 focus on the interannual variation. In addition, Niño3 and SOI are more related to the winter drought on interdecadal scales. Moreover, there is a positive correlation between the monthly average precipitation/temperature and Niño3 with a lag of 3 months. The results are beneficial for improving the accuracy of drought prediction, considering taking NAO, AO, and Niño3 as predictors for spring drought and Niño3 and SOI for winter drought. Hence, valuable information can be provided for the management of water resources as well as early drought warnings in the basin. [ABSTRACT FROM AUTHOR]

Skillful sub-seasonal precipitation forecasts can provide valuable information for both flood and drought disaster mitigations. This study evaluates both deterministic and probabilistic sub-seasonal precipitation forecasts of ECMWF, ECCC, and UKMO models derived from the Sub-seasonal to Seasonal (S2S) Database at various spatiotemporal scales over China during the boreal summer monsoon. The Multi-Source Weighted-Ensemble Precipitation, version 2 (MSWEP V2), is used as the reference dataset to evaluate the forecast skills of the models. The results suggest that skillful deterministic sub-seasonal precipitation forecasts are found when the lead time is within 2 weeks. The deterministic forecast skills reduce quickly when the lead time is beyond 2 weeks. Positive ranked probability skill scores (RPSS) are only found when the lead time is within 2 weeks for probabilistic forecasts as well. Multimodel ensembling helps to improve forecast skills by removing large negative skill scores in northwestern China. The forecast skills are also improved at larger spatial scales or longer temporal scales. However, the improvement is only observed for certain regions where the predictable low frequency signals remain at longer lead times. The composite analysis suggests that both the El Niño–Southern Oscillation (ENSO) and Madden–Julian Oscillation (MJO) have an impact on weekly precipitation variability over China. The forecast skills are found to be enhanced during active ENSO and MJO phases. In particular, the forecast skills are found to be enhanced during active MJO phases. [ABSTRACT FROM AUTHOR]