Interdecadal Scales Research Articles

Ley evolutiva de la relación entre el lago Dongting y las tres desembocaduras del río Jingjiang en los últimos 60 años

The Three Gorges Reservoir has begun to play a comprehensive role in power generation, flood control, shipping and other aspects, since June 1, 2003. Using long time series runoff and sediment transport data, the evolution of the relationship of the Dongting Lake and the three outlets of the Jingjiang River after operation of the Three Gorges Project was analyzed using Back Propagation neural networks, Mann-Kendall trend test, and double cumulative curves. The results show that: 1) On interannual and interdecadal scales, the decrease in runoff from Dongting Lake is mainly caused by the sharp decrease in runoff from the three outlets. To some extent, the siltation of the Dongting Lake was alleviated because of the reduction of sediment transport coming from the three outlets; 2) by analyzing the consistency of runoff and sediment transport in and out of Dongting Lake, it was found that the influence of the hydraulic engineering in the Yangtze River on runoff and sediment entering and leaving Dongting Lake is asynchronous. The rate of decay of sediment into the Lake is much greater than the decay rate of sediment out of the Lake; 3) from the trend change of the dried-up days of the three outlets, the three outlets tend to be silted, and the Ouchi River and the Hudu River gradually decline; 4) From the sedimentation process line of Dongting Lake, cumulative sedimentation of Dongting Lake from 2003 to 2018 was -2 829×104 t, and the Dongting Lake changed from siltation state to erosion state; 5) a back propagation neural network model was used to simulate the runoff and sediment transport of Dongting Lake, and the results show that the simulation accuracy met the needs of Dongting Lake runoff and sediment transport prediction.

Spatio-temporal variations and multi-scale correlations of climate, water, land, and vegetation resources over the past four decades in the Heihe River Basin

Study regionHeihe River Basin (HRB), Northwest China. Study focusThe study proposes an analytical scheme to identify trend, periodicity, and scale-correlation in climate, water, land, and vegetation resources over the past four decades using multivariate remote sensing data. New hydrological insights for the regionHeat and precipitation resources in the HRB have increased at rates of 14.27℃ yr−1 and 1.26 mm yr−1, respectively. The glacier area has decreased by 47.47 %. Additionally, the increase in upstream precipitation (2.82 mm yr−1) and glacier meltwater effectively replenishes runoff, soil water, and groundwater. The implementation of the ecological water diversion project (EWDP) in 2000 has contributed to enhancing runoff and lake storage capacity. The 9.28 % increase in vegetation cover (including cropland, forest, grassland, and shrubland) indicates an improvement in the hydrothermal conditions of the HRB. Additionally, the magnitude and direction of interactions among various natural resources vary across multiple spatial scales and time scales. The effect of hydrothermal coupling on vegetation is more prominent at the interdecadal scale. Vegetation growth in the upstream area is primarily influenced by thermal condition, while moisture plays a significant role in the midstream and downstream areas. Knowledge from this study contributes to the informed allocation of natural resources and offer policymakers valuable insights to enhance eco-environmental sustainability.

Interdecadal variability of winter and spring Eurasian snow depth and its impact on Eastern China precipitation

Empirical orthogonal function (EOF) and correlation analyses were employed to investigate the winter and spring snow depth in Eurasia and its relationship with Eastern China precipitation based on the observed and reanalyzed data from 1980 to 2016. The results show that the winter and spring snow cover in Eurasia not only highlights a decreasing trend due to global warming (the first EOF mode, its variance accounted for 24.4% and 22.6% of the total variance) but also exhibits notable interdecadal variation (the second EOF mode, its variance accounted for 10.2% and 11.5% of the total variance). The second EOF mode of winter snow depth in Eurasia is characterized by a west-east dipole pattern. It was observed that the spatial correlation pattern between the EOF2 of Eurasian snow depth and summer precipitation in China closely resembles the meridional quadrupole structure of the third EOF mode of summer precipitation in China. This pattern is characterized by excessive rainfall in Northeast China and the lower-middle reaches of the Yangtze River, and less rainfall over the Yellow River basin and southern China. The EOF mode of spring snow depth not only reflects the declining trend but also regulates precipitation in Eastern China. The possible mechanisms by which snow depth causes changes in soil moisture and subsequently affects atmospheric circulation are then explored from the perspective of the hydrological effects of snow cover. Decreased (Increased) snow depth in Eurasia during the winter and spring directly leads to diminished (increased) soil moisture while increasing (decreasing) net radiation and sensible heat flux at the surface. The meridional distribution of surface temperature also exhibits a dipole pattern, leading to enhanced subtropical westerly jet in the upper troposphere. The Eurasian snow cover anomalies pattern triggered an anomalous mid-latitude Eurasian wave train, which strengthened significantly in the Western Siberian Plain. It then splits into two branches, one continuing to propagate eastward at high latitudes and the other shifting towards East Asia, thereby impacting precipitation in Eastern China. This work indicates that the second EOF mode of Eurasian snow cover can impact the precipitation variability in Eastern China during the same period and in summer on an interdecadal scale.

Spatial diversity of atmospheric moisture transport and climate teleconnections over Indian subcontinent at different timescales

Regional weather and climate are generally impacted by global climatic phenomenon′s. Understanding the impact of global climate phenomenon′s on an atmospheric branch of the hydrological cycle is crucial to make advances in skillful precipitation forecast. The present study adopts a multiscale approach based on wavelets for unravelling the linkages between teleconnections and atmospheric moisture transport over homogeneous regions of Indian sub-continent. We investigated linkages between atmospheric moisture transport quantified as monthly integrated water vapor transport (IVT) during 1951–2022 over selected homogeneous regions and eight large scale climate oscillations using wavelet and global wavelet coherence. Our results indicate significant heterogeneity in linkages across different regions and across multiple timescales. In particular, the Indian Ocean Dipole (IOD) influence monthly IVT at intra-annual to inter-annual scale over all regions. The El Niño–Southern Oscillation (ENSO) have strong connection to monthly IVT at inter-annual scale whereas over west central region both IOD and ENSO strongly influence IVT at inter-decadal scale. While the Atlantic Multi-Decadal Oscillation and Pacific Decadal Oscillation have an impact on IVT in the north-east and southern regions, the Arctic Oscillation and North Atlantic oscillation have a strong inter-annual connection to IVT, majorly in the northwest and hilly regions. Overall, the methodology offers an effective approach for capturing the dynamics of atmospheric moisture transport in time–frequency space and provide a practical reference for prediction of atmospheric moisture transport linked precipitation over different regions of Indian subcontinent.

New characteristics of Meiyu precipitation changes in the middle and lower reaches of the Yangtze River since 2000

This study comprehensively analyzed the long-term changes of Meiyu in the middle and lower reaches of the Yangtze River with regard to precipitation, precipitation threshold, and interdecadal changes in atmospheric circulation. Results revealed obvious new features of Meiyu precipitation since 2000. (1) Meiyu precipitation shows a significant linear increase trend, with an average increment of 73.5 mm every 10 years. The increase in torrential rain is the most significant, accounting for 61% of the total precipitation increase, and its proportion has been increasing, while the proportions of light, moderate, and heavy rain in the total precipitation have been decreasing. (2) At the interdecadal scale, Meiyu precipitation and the local surface average temperature show opposite changes. Meiyu precipitation decreases by approximately 150 mm for every 1°C increase in the average temperature. This inverse correlation was not evident before 2000. (3) The saturated specific humidity in this area shows a significant increasing trend, indicating that precipitation in this area is caused by a higher threshold of atmospheric saturation and condensation, which may be a reason for the low Meiyu precipitation during high-temperature years. (4) The main atmospheric circulation in East Asia associated with Meiyu shows clear interdecadal changes, including the Western North Pacific Subtropical High and South Asian High having become significantly stronger and having extended westward and eastward, respectively, thereby facilitating the occurrence and persistence of Meiyu precipitation. The atmospheric circulation patterns associated with Meiyu, such as the Western North Pacific Subtropical High and South Asian High, have more significant impacts on Meiyu precipitation.

Characteristics of warming and humidification in the Yellow River's upper reaches and their impact on surface water resources

AbstractBased on multi‐source data, including observation, analysis, model calculation, satellite remote sensing, and scenario estimation data, this study has systematically analysed the warming and dry–wet change characteristics of the Yellow River's upper reaches in the last 60 years. The causes and features of the current warming and humidification and their impact on surface water resources are also discussed. This study found that since 1961, the average temperature in the Yellow River's upper reaches has increased at a rate of 0.37°C/10a, which is more significant than the increases observed for the world, China, and even northwest China in the same period. At the beginning of this century, the rate of change in precipitation in the Yellow River's upper reaches reversed direction from decreasing to increasing, with a significant increase (35 mm/10a) since 2000. Therefore, climate change has shown a significant warming and humidification trend in the upper reaches of the Yellow River. From the dynamic change perspective, the Yellow River's upper reaches were warming and drying in each climatic period from 1961 to 2010; however, the tendency towards dryness slowed period by period. In contrast, the region showed consistent warming and humidification from 1991 to 2020. From the perspective of multiple time scales, the change in average temperature is mainly dominated by the multi‐decadal scale. In contrast, precipitation is dominated by interannual change. The increase in the multi‐decadal component in average temperature and precipitation explains the current warming and humidification. Precipitation changes in the upper reaches of the Yellow River Basin are mainly affected by the westerly circulation, the East Asian summer monsoon, and the South Asian summer monsoon circulation systems. However, precipitation was affected by different circulation factors on different time scales. On an interannual scale, it was mainly affected by the South Asian summer monsoon circulation. On an interdecadal scale, it was mainly affected by the westerly wind and the East Asian summer monsoon circulation. On a multi‐decadal scale, it was jointly influenced by the westerly wind, the East Asian summer monsoon, and the South Asian summer monsoon circulation. Under the control of multi‐decadal synergistic enhancement of the westerly, the East Asian summer monsoon, and the South Asian summer monsoon circulations, the vertical field shows an abnormal upward movement. There has been a significant abnormal easterly and southerly airflow that transports water vapour, and cold air is transported along the northwest airflow at the back of the Mongolian cyclone, which makes the climate in the upper reaches of the Yellow River more humid. The warming and humidifying of the upper reaches of the Yellow River has significantly increased runoff and lake area and significantly degraded the frozen soil. The surface water budget in the Yellow River's upper reaches has significantly responded to the current warming and humidification. The actual surface evapotranspiration and surface runoff increased significantly, but the net surface water budget still showed a decreasing trend. The increase in precipitation did not change the surface water deficit.

Changes in Temperature‐Precipitation Compound Extreme Events in China During the Past 119 Years

AbstractThis study analyzes the change characteristics of compound extreme events (CEEs) of temperature and precipitation (including warm‐wet, warm‐dry, cold‐wet and cold‐dry) in China on interannual and interdecadal scales between 1901 and 2019. The results demonstrate a long‐term increasing trend and interdecadal oscillations in CEEs total frequency. However, the frequency of each type of CEEs changes in a different manner compared with total CEEs frequency. There are fewer CEEs but increasing warm‐dry during 1901–1950. The period 1951–1995 are characterized by frequent cold CEEs (cold‐wet and cold‐dry), cold‐wet are largely distributed in most areas except for northeast and coastal areas of China, while cold‐dry are distributed in most areas except for the northwest regions of China. There are frequent warm CEEs (warm‐wet and warm‐dry) and fewer cold CEEs during 1996–2019. Warm‐wet frequently occurs in the Tibetan Plateau and northwest China, and warm‐dry mainly concentrates in southwest and northern China during this period. The frequency of warm‐dry and cold‐wet were higher than that of warm‐wet and cold‐dry over the past 119 years, whereas warm‐wet increased fastest in the northwest region after 1996, consistent with the warming and wetting characteristics in the northwest region of China. Further study show that long‐term change and low frequency oscillations have the greatest impact on CEEs among different time scale factors. Furthermore, the temperature rise caused by climate change affects the interdecadal characteristics of CEEs in China through the changes of circulation fields such as East Asian trough and subtropical high and the configuration between them.

Analysis of the Asymmetric Characteristic of Extreme Rainfall Erosivity in 8 Provinces of Southern China during 1961–2020

The roles of rainfall with various intensities in hydraulic erosion processes are obviously different. In-depth knowledge about the spatiotemporal variation in extreme rainfall erosivity is critical for soil erosion risk assessment and formulation of response measures. In the period of 1961–2020, more than 390,000 erosive rainfall data from 212 meteorological stations were collected to explore the erosion characteristics of different intensities of rainfall erosivity across southern China. The asymmetric characteristic of extreme rainfall erosion was analyzed and expressed by an asymmetric change index (ACI) defined in this study. Correlation analysis was applied to study the impact of global extreme climate events on the ACI. The results showed that different patterns of precipitation had evident asymmetric characteristics in rainfall erosivity, and fewer high-intensity precipitation events contributed to much higher total rainfall erosivity, particularly for rainstorms (≥100 mm). The ACI of the rainfall erosivity exhibited evident spatial heterogeneity; insignificant increasing trends were found in the ACIs for heavy rainfall, torrential, and rainstorm erosivities over the past 60 years. The change rate of ACI varied greatly on both monthly and interdecadal scales, and the ACI of rainstorms showed the maximum linear increasing trend on the long-time scale. There were significantly high correlations between the ACI and erosive rainfall days and the ACI and erosive rainfall (p < 0.01), and the correlation coefficients were relatively higher from May to October, where the precipitation was concentrated. Additionally, the El Niño-Southern Oscillation and tropical cyclones clearly influenced the spatiotemporal distribution of the ACI and rainfall erosivity but were limited to specific periods and regions. These results could provide a reference for extreme soil erosion event monitoring and control in southern China.

Ley evolutiva de la relación entre el lago Dongting y las tres salidas del río Jingjiang en los últimos 60 años

The Three Gorges Reservoir has begun to play a comprehensive role in power generation, flood control, shipping and other aspects, since June 1, 2003. Using long time series runoff and sediment transport data, the evolution of the relationship of the Dongting Lake and the Three Outlets of the Jingjiang River after operation of the Three Gorges Project was analyzed using Back Propagation neural networks, Mann-Kendall trend test, and double cumulative curves. The results show that: (1) On interannual and interdecadal scales, the decrease in runoff from Dongting Lake is mainly caused by the sharp decrease in runoff from the Three Outlets. To some extent, the siltation of the Dongting Lake was alleviated because of the reduction of sediment transport coming from the Three Outlets. (2) By analyzing the consistency of runoff and sediment transport in and out of Dongting Lake, it was found that the influence of the hydraulic engineering in the Yangtze River on runoff and sediment entering and leaving Dongting Lake is asynchronous. The rate of decay of sediment into the Lake is much greater than the decay rate of sediment out of the Lake. (3) From the trend change of the dried-up days of the Three Outlets, the Three Outlets tend to be silted, and the Ouchi River and the Hudu River gradually decline. (4) From the sedimentation process line of Dongting Lake, cumulative sedimentation of Dongting Lake from 2003 to 2018 was -2829×104t, and the Dongting Lake changed from siltation state to erosion state. (5) A Back Propagation neural network model was used to simulate the runoff and sediment transport of Dongting Lake, and the results show that the simulation accuracy met the needs of Dongting Lake runoff and sediment transport prediction.

South drying and north wetting over the Tibetan Plateau modulated by a zonal temperature dipole across timescales

Precipitation over the Tibetan Plateau and surrounding highlands is a crucial process in the hydrological cycle and is very important for local and downstream ecology, and previous research mainly focused on a certain range of timescales. A better understanding of the variability across various timescales, which has been largely ignored, can provide new insight on the regional weather and climate. Here, a north‒south dipole pattern of precipitation shaped by a zonal dipole of the upper-tropospheric temperature is revealed in this region. Both dipole patterns of the precipitation and the accompanied temperature exist from daily to interdecadal scales. The three-dimensional circulation anomalies connecting the temperature and precipitation dipoles are consistent across various timescales. The frequencies of daily events with opposite phases of the temperature dipole modulate the interannual and interdecadal variability in precipitation. The south drying and north wetting pattern over the Tibetan Plateau is an interdecadal manifestation of the precipitation dipole and can be ascribed to the temperature trend favourable for the positive phase of the zonal temperature dipole. The consistent dipole pattern constructs a more complete portrayal of precipitation over the Tibetan Plateau from synoptic scale to climatology.

A 195-Year Growing Season Relative Humidity Reconstruction Using Tree-Ring Cellulose δ13C in the Upper Tarim River Basin, NW China

Reconstruction of relative humidity changes in the upper Tarim River using carbon isotopic tree-ring chronology bridges the gap in historical observations on the Tarim River Basin in Arid Central Asia. Populus euphratica Olivier (P. euphratica), growing in the Tarim River Basin of Xinjiang, is an excellent record of past climate change. Based on precise dating, we analysed alpha-cellulose stable carbon isotopes in four cores of P. euphratica taken from the Alaer region of the upper Tarim River Basin. The four stable carbon isotope series records were corrected by the “pin method” and then combined into a carbon isotopic discrimination (Δ13C) series by the “numerical mix method”. The discrimination (Δ13C) series were clearly correlated with the mean relative humidity (RHAS) in April–September of the growing season (n = 60, r = −0.78, p < 0.001), and according to the climate response analysis, we designed a simple regression equation to reconstruct the mean relative humidity (RHAS) in April–September from 1824 to 2018 on the Alaer region. The reconstructed sequence showed mainly dry periods in the last 195 years, 1857–1866 and 1899–1907, while primarily wet periods from 1985 to 2016. Due to increased global warming and human activities, the climate shifted from “warm–dry” to “warm–wet” in the mid-to-late 1980s, when there were signs of a shift from “warm–wet” to “warm–dry” in the 2010s, with an increasing trend towards aridity. The RHAS series of Alaer compares well to other hydroclimate series’ surrounding the research area, and the spatial correlation analysis indicates that the reconstructed series has good regional representativeness. On an interdecadal scale, the revamped RHAS series is positively correlated with the Atlantic Multidecadal Oscillation (AMO) and negatively correlated with the North Atlantic Oscillation (NAO), reflecting the influence of westerly circulation on regional wet and dry variability. At the same time, the RHAS may also be influenced by The Pacific Decadal Oscillation (PDO).

Comparison Study on Climate Changes between the Guangdong–Hong Kong–Macao Greater Bay Area and Areas around the Baltic Sea

With global warming, coastal areas are exposed to multiple climate-related hazards. Understanding the facts and attribution of regional climate change in coastal communities is a frontier science challenge. In this study, we focus on fact analysis of multi-scale climate changes in the Guangdong–Hong Kong–Macao Greater Bay area (GBA) and around the Baltic Sea area (BSA). We selected three Asian stations from the GBA in South China (Guangzhou, Hong Kong, and Macao) and five European stations around the Baltic Sea (Stockholm, Haparanda A, Vestervig, Poznan, and Frankfurt) from four countries in the BSA as representative stations, which have more than 100- or 150-year datasets. Based on the ensemble empirical mode decomposition (EEMD) and Mann–Kendall methods, this study focuses on the multi-scale temperature and precipitation fluctuation and mutation analysis in the past. The multi-scale analyses show that there are four time-scale changes in both areas. They are the inter-annual scale, inter-decadal scale, centennial scale, and trend, but the lengths of different timescales vary in both regions, especially the inter-decadal scale and centennial scale. For temperature, the inter-annual scales show the same results, with 2–4 and 7–9 a in both the GBA and BSA. In the GBA, the inter-decadal scales are 10–14, 30–50, and 55–99 a, while in the BSA, they are 13–20, 26–50, and 66–99 a. For centennial scales, there are 143–185 and 200–264 a in the BSA and about 100–135 a in the GBA. Temperature trends in the GBA reveal that the coastal area has experienced an upward trend (Hong Kong and Macao), but in the inland area (Guangzhou), the trend fluctuated. Temperature trends in the BSA have risen since 1756. For precipitation, the inter-annual scales are 2–4 and 6–9 a in both the GBA and BSA. The inter-decadal scales are 11–29 and 50–70 a in the GBA and 11–20, 33–50, and 67–86 a in the BSA. For centennial scales, there are about 100 a in the GBA and 100–136 a in the BSA. In the GBA, the precipitation trends show stronger local characteristics, with three different fluctuation types. In the BSA, most stations had a fluctuating trend except Haparanda A and Vestervig station, which experienced an upward trend throughout the whole time range. Overall, there are no unified trends for precipitation in both areas. Temperature mutation tests show that only Vestervig in the BSA changed abruptly in 1987, while the mutation point of Macao in the GBA was 1991. Precipitation mutation points of Stockholm and Vestervig were 1878 and 1918 in the BSA, while only Macao in the GBA changed abruptly in 1917. The results reveal that the regional climate mutation of both areas is not obvious, but the temperature changes with an upward trend as a whole.

Potential Vorticity Dynamics Explain How Extratropical Oceans and the Arctic Modulate Wintertime Land‐Temperature Variations

AbstractTemperature variations across the continental northern hemisphere at the interdecadal scale are thought to be remotely modulated by oceanic internal climate variability and the Arctic. Nevertheless, further elucidating the dynamics is essential for clarifying ongoing debates. We show that potential vorticity (PV) dynamics provide a concise explanation for these teleconnections. Our findings demonstrate that extratropical oceans and the Arctic can remotely modulate the wintertime continental temperature variations by stimulating PV anomalies, which are constrained by climatological PV gradients and jet streams. A causal explanation includes anomalous temperature and precipitation over oceans and the Arctic inducing local PV anomalies via diabatic heating. Subsequently, meridional and downstream advection distributes the anomalous PV to remote land regions where the climatological PV gradients are strong, that is, involving PV fronts, as well as jet streams; therefore, PV fronts and jet streams jointly indicate land regions that are largely and frequently impacted. However, land can also modulate other regions through the same mechanism when variations over land occur in advance. Clear causality depends on which factor is independent, while interactions among those regions may convolute the causality, thereby causing further debates.

Evolution of the Internal Climate Modes under Future Warming

Abstract Climate modes play an important role in weather and climate variability over multiple spatial and temporal scales. This research assesses Earth system model (ESM) projections of the spatiotemporal characteristics of key internal climate modes (NAM, SAM, PNA, ENSO, PDO, and AMO) under high (SSP585) and low (SSP126) radiative forcing scenarios and contextualizes those projections using historical fidelity. Time series analyses are used to assess trends and mode phase characteristics are summarized for the historical period and for the end of the twenty-first century. Spatial patterns are compared to infer morphological changes. Shifts in the power spectra are used to examine changes in variability at subannual, interannual, and interdecadal scales. Changes in time-lagged correlations are used to capture the evolution of first-order interactions. While differences in historical skill are predominantly ESM dependent, changing mode characteristics in a warmer climate also exhibit variability between individual ensemble realizations. NAM, SAM, and ENSO tend to evolve toward increased prevalence of the positive phase up to 2100 across the multimodel ensemble while the PNA and PDO exhibit little trend but increasing phase intensity. AMO characteristics are shown to depend on the method used to remove the external signal. ESMs that show higher historical fidelity tend to show more modest changes in those modes under global nonstationarity. Changes in mode interactions are found to be highly ESM dependent but exhibit broadly similar behavior to historical relationships. These findings have implications for our understanding of internal variability and make clear that the choice of ESM, and even the ESM realization, matters for applications of climate projections. Significance Statement Internal modes of variability are important to understand due to their impact on local, regional, and global weather and climate patterns. Future climate changes will not only be affected by the variability arising from these modes, but the modes will themselves change in response to the changing climate. Spatial and temporal aspects of the modes are assessed from projections of future climate and related to how well they are captured in the historical climate. This yields some measure of confidence in the changes exhibited by the models. In most cases, when historically skillful models exhibit changes that are different from those produced by less skillful models, they tend to produce more modest changes. These results, as well as the variability between model outcomes, mean decisions on which ESM to use for projections of the future climate matter significantly.

Evaluation of the Pacific Decadal Oscillation from 1901 to 2014 in CMIP6 models

The simulation of internal climate variability is key to understanding climate change. Internal fluctuations can fully obscure or amplify the underlying climate-change signal in many fields over years to decades. The Pacific Decadal Oscillation (PDO) is an important mechanism that dominates interdecadal climate variations. Here, the capacity of 36 Coupled Model Intercomparison Project Phase 6 (CMIP6) models for reproducing the PDO during the period 1901-2014 was evaluated across spatial pattern, amplitude, periodicity and phase aspects. The results suggested that approximately 71% of the models were capable of capturing the spatial pattern of the PDO. However, most of the other models underestimated the percentage of the variance explained and the pattern amplitude. CMIP6 models can capture the periodicity over shorter periods (<20 yr), while most CMIP6 models underestimate the periodicity of the PDO on the interdecadal scale (60 yr periods). In particular, the probability distribution functions (PDFs) of the raw PDO index showed that most CMIP6 models could capture the unimodal probability distribution. Some of the models were able to reproduce the bimodal probability distribution of the PDO index filtered by the ensemble empirical mode decomposition method. Moreover, the findings also showed that the multimodel ensemble (MME) for 36 CMIP6 models could effectively capture the spatial pattern and periodicity over a shorter period (<20 yr) of the PDO. Moreover, the MME exhibited higher fidelity to the observation in the PDF of the PDO index, although the positive area was larger than the observation. These findings are crucial because they may help detect simulation gaps and provide valuable references for the design and applicability of future models worldwide.

Multiscale characteristics of the early spring temperature and response to climate indices over the past 179 years in the Qinling Mountains

Examination of the periodic differences in temperature in the Qinling Mountains at different time scales is highly important in research on the long-term evolution of the regional climate system and ecological environment. Based on February-April temperature data from 1835 to 2013 obtained at 27 weather stations in the Qinling Mountains reconstructed through tree rings, the multiscale characteristics of the early spring temperature time series on the southern and northern slopes of the Qinling Mountains and the response to climate signals were analyzed. The results indicate that the early spring temperature in the Qinling Mountains exhibits significant periodic characteristics on multiple time scales. Reconstruction at the different time scales reveals that the interannual scale change in the temperature variation on the northern slope of the Qinling Mountains plays a decisive role. The temperature on the northern slope exhibits a higher amplitude at the interannual and interdecadal scales than does that on the southern slope, and temporal differences occur at the quasi-century scale. The temperature achieves the strongest correlation with the original Atlantic Multidecadal Oscillation (AMO) sequence during the entire study period. In addition, the different time scales reveal that a significant response relationship exists between the temperature at the interannual scale and the May sea temperature in the NINO3.4 area, which lags by one year. At the different time scales and various time ranges, the Qinling early spring temperature responds differently to the climate signals, which is an important factor leading to a lower correlation during the entire study period.

A sub-seasonal oscillation of sea surface temperature in the Southern Indian Ocean during DJF and its excitation mechanism

Southern Indian Ocean dipole (SIOD) is a dipole SST anomaly in the Southern Indian Ocean that plays an important role in tropical climate variability. However, previous studies focused on the interannual and interdecadal scales. In this paper, the characteristics on sub-seasonal scale of SIOD are revealed from December to February (DJF) based on the ERA-Interim reanalysis dataset, and the excitation mechanisms of SIOD are also discussed. The results show that the two dominant modes of SST in the Southern Indian Ocean are the spatial distribution of Southwest-Northeast direction dipole (SIOD) and triple (SIOT) respectively, which has obvious period of quasi 50–60 days. Moreover, the intensity and zonal oscillation of the Mascarene high are conducive to the formation of SIOD (SIOT). The air–sea interaction during the formation process is composed of three stages. In the first stage the atmospheric forces the ocean to result in the Mascarene high westward (eastward) and enhances the abnormal anticyclone in the Southern Indian Ocean. There are abnormal northerly (southerly) flows on the west (east) sides of the abnormal anticyclone respectively, which weakens (enhances) the southeast trade wind in the climatology. The surface latent heat flux release decreases (increases) and SST is warmed (cooled). During the following stage, the ocean feedback the atmosphere. The warm SST continues to increase, resulting in low-level convective enhancement, which weakens the abnormal anticyclone. The third stage is again the atmosphere forcing the ocean. The abnormal anticyclone gradually turns into an abnormal cyclone and the meridional wind direction is reversed. The release of the latent heat flux increases (decreases) significantly which leads to the cooling (warming) of SST on the west (east) sides of an abnormal cyclone. In addition, the formation and extinction of SIOT are easier affected by the southern annular mode (SAM) than SIOD. The abnormal zonal wave train with wavenumber 4 (3) propagates the Southern Indian Ocean by the westerly jet waveguide and results in an SST anomaly of SIOD (SIOT), accompanied by an obvious sub-seasonal meridional variation of the precipitation in Southern Africa.

Impact of Tibetan Plateau vertical heating on the Asian summer monsoon on the interdecadal scale

AbstractThis study investigated the impacts of Tibetan Plateau vertical heating (TPVH) on the Asian summer monsoon (ASM) on the interdecadal scale since the beginning of the 20th century. The ASM, corresponding to TPVH, generally enhances on the interdecadal scale. In the upper troposphere, the upper‐level westerly and easterly jet streams shift northwards in Asia, with two meridional “southern low and northern high” wave‐like patterns dominating in East Asia and India, respectively. In the lower troposphere, the summer monsoonal airflow and convergence zone migrate northwards in Asia, and two meridional “southern high and northern low” patterns appear in East Asia and India, respectively. Thus, TPVH can strengthen the baroclinicity over northern East Asia and northern India, but weaken it over southern East Asia and southern India. Moreover, two anomalous meridional circulation cells are identified in East Asia and India, with ascending branches in their northern parts and descending branches in their southern parts. Eventually, the ASM strengthens, leading to a southern dry and northern wet pattern in East Asia and India.

Wavelet coherence of monsoon and large‐scale climate variabilities with precipitation in Pakistan

AbstractMonsoon and its teleconnection with earth system internal processes affect the spatiotemporal distribution of precipitation and water resources. In this paper, the wavelet coherence analysis has been utilized, a time and frequency domain methodology for comparing the spectral features of two independent time series superior to linear approaches. This technique is used to capture the significant modes of variabilities in the Indian Summer Monsoon Index (ISMI) and large‐scale climate indices (CIs) between ocean–atmosphere oscillations, like Indian Ocean Dipole (IOD), El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), and Arctic Oscillation (AO) over Pakistan. Precipitation time series during 1960–2016 revealed significant interannual coherences with ISMI, whereas the remaining CIs (IOD, ENSO, PDO, SOI, NAO, AMO, and AO) revealed interannual, decadal and interdecadal coherences. However, AO revealed strongest coherences in R‐II, III, and VI at interdecadal scales among all CIs. Overall, the interannual cycles on ISMI are 2.8 years, IOD 1–5.3 years, PDO 0–5.3 years, SOI 1–5.3 years, NAO 0–5 years, AO 0–5 years, and AMO 0–8.3 years. Whereas, the remaining CIs shared interdecadal coherences over particular regions. The ISMI displayed coherences (except in the UIB) with the large‐scale CIs over various homogenous regions on an interannual scale. The dominant influence of ISMI is observed in R‐II and III; the significant coherences in R‐II ranged from ~8 to 32 months (~0.8–2.8 years). The IOD and NAO have major coherences than the remaining large‐scale CIs ranging from ~16 to 64 months (1.3–5.3 years). The AO has the most significant coherences observed in R‐II, III, and VI on the decadal/interdecadal scale from 128 months and above (almost 10–15 years). On a 1.0‐year timescale, all homogenous regions demonstrated strong intermittent coherence with ISMI, IOD, ENSO, PDO, SOI, NAO, AMO, and AO. These findings have substantial implications for decision‐makers and scientists in Pakistan looking to enhance water resource planning and operations in the face of future climate uncertainties.

Reconstructing 6-hourly PM2.5 datasets from 1960 to 2020 in China

Abstract. Fine particulate matter (PM2.5) has altered the radiation balance on Earth and raised environmental and health risks for decades but has only been monitored widely since 2013 in China. Historical long-term PM2.5 records with high temporal resolution are essential but lacking for both research and environmental management. Here, we reconstruct a site-based PM2.5 dataset at 6 h intervals from 1960 to 2020 that combines long-term visibility, conventional meteorological observations, emissions, and elevation. The PM2.5 concentration at each site is estimated based on an advanced machine learning model, LightGBM, that takes advantage of spatial features from 20 surrounding meteorological stations. Our model's performance is comparable to or even better than those of previous studies in by-year cross validation (CV) (R2=0.7) and spatial CV (R2=0.76) and is more advantageous in long-term records and high temporal resolution. This model also reconstructs a 0.25∘ × 0.25∘, 6-hourly, gridded PM2.5 dataset by incorporating spatial features. The results show PM2.5 pollution worsens gradually or maintains before 2010 from an interdecadal scale but mitigates in the following decade. Although the turning points vary in different regions, PM2.5 mass concentrations in key regions decreased significantly after 2013 due to clean air actions. In particular, the annual average value of PM2.5 in 2020 is nearly the lowest since 1960. These two PM2.5 datasets (publicly available at https://doi.org/10.5281/zenodo.6372847, Zhong et al., 2022) provide spatiotemporal variations at high resolution, which lay the foundation for research studies associated with air pollution, climate change, and atmospheric chemical reanalysis.