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This study investigates the interannual variations in regional mean sea levels (MSLs) of the northeast Asian marginal seas (NEAMS) during August, focusing on the role of typhoon activity from 1993 to 2019. The NEAMS are connected to the Pacific through the East China Sea (ECS) and narrow, shallow straits in the east, where inflow from the southern boundary (ECS), unless balanced by eastern outflow, leads to significant convergence or divergence, as well as subsequent changes in regional MSLs. Satellite altimetry and tide-gauge data reveal that typhoon-induced Ekman transport plays a key role in MSL variability, with increased inflow raising MSLs during active typhoon seasons. In contrast, weak typhoon activity reduces inflow, resulting in lower MSLs. This study’s findings have significant implications for coastal management, as the projected changes in tropical cyclone frequency and intensity due to climate change could exacerbate sea level rise and flooding risks. Coastal communities in the NEAMS region will need to prioritize enhanced flood defenses, early warning systems, and adaptive land use strategies to mitigate these risks. This is the first study to link typhoon frequency directly to NEAMS MSL variability, highlighting the critical role of wind-driven processes in regional sea level changes.

This study scrutinizes interannual (2003–2023) variations in coastal upwelling along the Guangdong Province during summers (June–August) in the northeastern South China Sea (NESCS) by comprehensively applying the moderate-resolution imaging spectroradiometer (MODIS) remote sensing sea surface temperature (SST) and chlorophyll concentration (CHL) data and the model reanalysis product. The results show that SST and upwelling intensity in the sea area have significant (p < 0.05) rising trends in the last 21 years. The CHL shows an upward but insignificant trend, which is affected simultaneously by the rise in SST and the enhancement of upwelling. Further analysis reveals that the interannual variations in upwelling are robustly related to the wind fields’ variations in the coastal region. A clockwise/counter-clockwise anomaly in the wind field centered on the NESCS facilitates alongshore/onshore winds near the Guangdong coast, which can strengthen/weaken coastal upwelling. Based on the correlation between wind field variations and large-scale climate factors, long-term variations in the upwelling intensity can be primarily predicted by the Oceanic Niño Index.

Ulva prolifera (U. prolifera) green tide outbreaks have occurred in the Yellow Sea of China for many years, causing serious losses to marine ecology and the marine economy. The monitoring and tracking of U. prolifera green tide is a crucial aspect of marine ecological disaster prevention and control management. This paper aims to investigate the spatiotemporal distribution changes in U. prolifera green tide in the Yellow Sea throughout its life cycle. A survey of the Yellow Sea from 2008 to 2023 was conducted using multi-source remote sensing images. Long-term monitoring and analysis of U. prolifera revealed the evolution process of the green tide, including the early development, outbreak, decline, and extinction stages, considering time, space, and frequency of occurrence. Additionally, this study examined peak coverage change patterns over the past 16 years and analyzed the influence of environmental factors such as sea surface temperature and sea surface wind field on the development of U. prolifera. The research results serve as a valuable reference for the monitoring, early warning, and scientific prevention and control of U. prolifera green tide in the Yellow Sea, as well as other similar marine disaster areas.

Rivers in arid regions serve as crucial freshwater resources for local communities and play an essential role in global hydrological and biogeochemical cycles. The Aral Sea Basin (ASB) in Central Asia is characterized by an arid climate and river dynamics that are sensitive to climate change and human activities. Monitoring the spatiotemporal variations in river water extent in the ASB is essential to maintain an ecological balance and ensure water security. In this study, we extracted data regarding monthly river water bodies in the ASB from 2017 to 2022 by synthesizing monthly Sentinel-2 images. The water extents on the Sentinel images were automatically mapped using the Otsu method, and the river widths for all river channels were calculated using the RivWidth algorithm. We investigated the relationships between the river dynamics and the geomorphology, climatic change, human activities, and the annual and interannual variations in the river width in different reaches of the basin. The results show a seasonal variability in the river width, with most rivers reaching the largest width in the warm season and a few rivers in the middle and lower areas reaching the valley value in the warm season. Compared to their tributaries, the mainstem in the middle/lower regions showed less seasonal variability. According to interannual analysis, most of the rivers in the ASB significantly narrowed between 2017 and 2022, a phenomenon which is generally impacted by temperature and evapotranspiration variations. Comparisons show that our results provide improved information about the narrow river reaches and denser river networks compared to the previous global dataset, demonstrating the advantageous properties of high spatial resolution in Sentinel-2 imagery.

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.

The presence of yessotoxins (YTXs) was analyzed in 10,757 samples of Galician bivalves from 2014 to 2022. Only YTX and 45-OH YTX were found. YTX was detected in 31% of the samples, while 45-OH YTX was found in 11.6% of them. Among the samples containing YTX, 45-OH YTX was detected in 37.3% of cases. The maximum recorded levels were 1.4 and 0.16 mg of YTX-equivalentsg−1, for YTX and 45-OH YTX, respectively, which are well below the regulatory limit of the European Union. The YTX and 45-OH YTX toxicities in the raw extracts and extracts subjected to alkaline hydrolysis were strongly and linearly related. Due to the lack of homo-YTX in Galician samples, the effect of alkaline hydrolysis on homo-YTX and 45OH-Homo-YTX was only checked in 23 additional samples, observing no negative effect but a high correlation between raw and hydrolyzed extracts. Hydrolyzed samples can be used instead of raw ones to carry out YTXs determinations in monitoring systems, which may increase the efficiency of those systems where okadaic acid episodes are very frequent and therefore a higher number of hydrolyzed samples are routinely analyzed. The presence of YTX in the studied bivalves varied with the species, with mussels and cockles having the highest percentages of YTX-detected samples. The presence of 45-OH YTX was clearly related to YTX and was detected only in mussels and cockles. Wild populations of mussels contained proportionally more 45-OH YTX than those that were raft-cultured. Spatially, toxin toxicities varied across the sampling area, with higher levels in raft-cultured mussels except those of Ría de Arousa. Ría de Ares (ARE) was the most affected geographical area, although in other northern locations, lower toxin levels were detected. Seasonally, YTX and 45-OH YTX toxicities showed similar patterns, with higher levels in late summer and autumn but lower toxicities of the 45-OH toxin in August. The relationship between the two toxins also varied seasonally, in general with a minimum proportion of 45-OH YTX in July–August but with different maximum levels for raft-cultured and wild mussel populations. Interannually, the average toxicities of YTX decreased from 2014 to 2017 and newly increased from 2018 to 2021, but decreased slightly in 2022. The relationship between 45-OH YTX and YTX also varied over the years, but neither a clear trend nor a similar trend for wild and raft mussels was observed.

The Meiyu season is a typical rainy season in East Asia that is controlled by summer monsoon. Despite extensive research on its impact, it is unclear how urbanization modifies precipitation during the Meiyu season in the background of the monsoon influence. To address this gap, this study investigated the effects of urbanization and monsoon on the modification of precipitation during the Meiyu season (PDM) in the megacity of Shanghai, China. Through homogenization analysis of the original observational data, we assessed the temporal and spatial variation in PDM in Shanghai during two stages of urbanization. Our findings revealed that both total precipitation and extreme daily precipitation during the Meiyu season in Shanghai have significantly increased since 1961. The spatial heterogeneity of PDM has also enhanced during the rapid urban process that has occurred since 1986. The long-term trend of increasing precipitation in Shanghai showed a synchronous variation with the East Asian subtropical summer monsoon (EASM) in 1961–2021. Over the interannual time scale, the significant positive correlation between PDM and EASM during the slow urbanization period (Stage 1: 1961–1985) changed to a non-significant correlation during the rapid urbanization period (Stage 2: 1986–2021), which was associated with the enhanced convective precipitation in Shanghai during the Meiyu season. Urbanization induced more convective precipitation and further weakened the association between PDM and EASM over the central city and nearby areas during Stage 2. The rapid urbanization process also resulted in increased differences in near-surface wind between urban and non-urban areas, which facilitated more PDM over the central city due to the urban friction effect and wind shear in Stage 2. Furthermore, our analysis suggests that the increase in precipitation may be associated with the enhanced coupling of cold air intrusion with the warmer climate background due to the urban heat effect occurring in Stage 2. These findings contribute to a better understanding of how urbanization and monsoons affect PDM in East Asian megacities and serve as a unique reference for climate prediction in this region.

Landfast ice has undergone a dramatic decline in recent decades, imposing potential effects on ice travel for coastal populations, habitats for marine biota, and ice use for industries. The mapping of landfast ice deformation and the investigation of corresponding causes of changes are urgent tasks that can provide substantial data to support the maintenance of the stability of the Arctic ecosystem and the development of human activities on ice. This work aims to investigate the time-series deformation characteristics of landfast ice at multi-year scales and the corresponding influence factors. For the landfast ice deformation monitoring technique, we first combined the small baseline subset approach with ascending and descending Sentinel-1 images to obtain the line-of-sight deformations for two flight directions, and then we derived the 2D deformation fields comprising the vertical and horizontal directions for the corresponding periods by introducing a transform model. The vertical deformation results were mostly within the interval [−65, 23] cm, while the horizontal displacement was largely within the range of [−26, 78] cm. Moreover, the magnitude of deformation observed in 2019 was evidently greater than those in 2020 and 2021. In accordance with the available data, we speculate that the westerly wind and eastward-flowing ocean currents are the dominant reasons for the variation in the horizontal direction in Cambridge Bay, while the factors causing spatial differences in the vertical direction are the sea-level tilt and ice growth. For the interannual variation, the leading cause is the difference in sea-level tilt. These results can assist in predicting the future deformation of landfast ice and provide a reference for on-ice activities.

Proteases, catalysing protein hydrolysis, and arylsulfatases, catalysing sulfate-ester hydrolysis, are key microbial enzymes for N and S mineralization in soil. However, knowledge gaps remain regarding the effect of crop successions and seasonal and interannual meteorological variations on microbial communities responsible for those activities. Here, we compared the effect of six cropping sequences on the abundance and activity of microbial communities involved in proteolysis and sulfate-ester hydrolysis in northern France over four years, with two sampling dates per year. Crop sequences impacted soil microbial communities involved in proteolysis but not those involved in sulfate-ester hydrolysis. Oilseed rape following wheat presented a higher abundance of fungal 18S rDNA, culturable bacteria and alkaline metalloprotease genes and higher protease activity than other crop sequences (wheat following oilseed rape or pea, barley following wheat and pea following barley). Net N and S mineralization was not impacted by the cropping sequence. However, interannual variability of microbial parameters was large, and largely overcame the effect of crop sequences. Precipitation variability between years was the likely cause of this effect. In conclusion, the interaction between current crop, previous crops and yearly meteorology can strongly impact the soil microbial communities in agroecosystems.

For the frequent occurrence of harmful algal blooms (HABs) in the Qinhuangdao coastal sea (QCS) of the Bohai Sea in summer, we tested the hypothesis that high-biodiversity HAB species exist in the area, and a series of censuses of HAB species were conducted in the QCS in the summers of 2014–2019. Through morphological identification, we found 100 algae species representing 42 genera in 3 phytoplankton phyla in this study, among which Bacillariophyta was the most dominant phylum. We also found that the population density of Dinoflagellata increased from 2016 to 2019. In total, 59 HAB species were annotated in this study, including 39 of Bacillariophyta, 18 of Dinoflagellata and 2 of Ochrophyta, of which 13 HAB species were reported in the Bohai Sea for the first time, and most HAB species were widely distributed in the QCS in summer. Notably, four dominant HAB species displayed unique temporal and spatial distribution characteristics, while their distribution ranges and population densities increased from 2014 to 2019. The distributions of five environmental factors were different in the QCS, while the temperature, salinity, and dissolved inorganic nitrogen might be the key environmental factors influencing the distribution of dominant HAB species in the summer. In conclusion, this study provides a detailed evaluation of phytoplankton diversity and interannual variation in the QCS. The existence of a high level of biodiversity of algal bloom species suggests the need for long-term monitoring in order to further study and prevent potential HABs.

Based on Moderate Resolution Imaging Spectoradiometer (MODIS) remote sensing data, meteorological observation data, multisource atmospheric circulation, and sea surface temperature (SST) data from NCEP/NCAR reanalysis, we estimated the net primary productivity (NPP) of terrestrial natural vegetation in China according to the CASA model and analyzed the linear trend and interannual fluctuation of NPP, as well as the spatial distribution characteristics of the annual NPP response to climatic factors. The obtained results revealed the impact of air–sea interaction on interannual NPP variability in key climatic areas. In China, the annual NPP of natural vegetation, linear NPP trend, and interannual NPP fluctuation showed significant regional characteristics. The annual NPP exhibited a significant increasing trend and interannual fluctuation in North China and Northeast China, with spatially consistent responses from NPP to precipitation and temperature. On the seasonal time scale, NPP in the key climatic area (105~135° E, 35~55° N) exhibited a strong response to both summer precipitation and mean temperature. In the summer atmospheric circulation, the circulation anomaly area is mainly distributed in the northeast cold vortex area in the middle- and high-latitude westerlies in East Asia and in the Sea of Okhotsk with dipole circulation. In the SST of the preceding winter and spring, the key SST anomaly area was the Kuroshio region, with an impact of the Kuroshio SST anomaly on the interannual variation in annual NPP in the key climatic area. The cold vortex in Northeast China played a pivotal role in the influence of the SST anomaly in the Kuroshio region on atmospheric circulation anomalies, resulting in abnormal summer precipitation in the key climatic region and affecting the annual accumulation of NPP of natural vegetation.

Agricultural nitrogen (N) non-point source pollution in the North China Plain is a major factor that affects water quality and human health. The characteristics of N leaching under different N application conditions should be further quantified accurately in winter wheat (Triticum aestivum L.) and summer maize (Zea mays L.) rotation farmland in North China, and a basis for reducing the risk and evaluation of N leaching in this area. A three-year field experiment was conducted using an in situ leakage pond method at a typical farmland in Henan in 2017–2020. Crop yield, soil nitrate N residues, and N utilization were also studied during the study period. Five N fertilizer rates were established with 0 (CK), 285 (LN), 465 (MN), 510 (MNO), and 645 (HN) kg N ha−1 for one rotation cycle. MNO was applied with chemical and organic fertilizers. The concentration of nitrate N in the soil leaching solution of CK, LN, MN, MNO, and HN was 0.81-, 1.49-, 3.65-, 5.55-, and 7.57-fold that of the World Health Organization’s standard for underground drinking water. The exponential relationship between the N application rate and leaching was obtained when the annual N input exceeded 300 kg ha−1, and the N leaching rate increased greatly. The leaching rate of nitrate N in the total N was 50.6–82.4% under different treatments of N application. The combination of chemical and organic fertilizers treatment (MNO) reduced the amount of N that was leached in dry years. The nitrate leaching amount of summer maize accounts for 83.0%, 49.4%, and 72.0% of the total nitrate leaching amount of the whole rotation cycles in 2017–2020. LN and MN were recommended as the optimized N application here (285–465 kg N ha−1) with the two-season rotation grain yield of 17.2 ton ha−1 (16.5–17.9 ton ha−1) and nitrate N leaching of 21.6 kg ha−1 (12.6–30.5 kg ha−1).

To investigate the main modes of interannual variation of chlorophyll-a (Chla) with seasonal evolution and its variation cycle in the North Indian Ocean based on satellite-derived products during 1998–2016, a season-reliant empirical orthogonal function (S-EOF) analysis and power spectrum analysis based on Fourier transform are applied in the study. The first three dominate modes reveal distinct Chla variability, as the S-EOF1 features by one dipole pattern have a negative anomaly in the central western Indian Ocean and a positive anomaly off the Java–Sumatra coasts, which is mainly synchronously associated with the climate indices of the positive Indian Ocean dipole (IOD) and eastern Pacific El Nino (EP-El Niño). The S-EOF2 indicates a tripolar structure with positive anomalies located in the central Indian Ocean surrounded by two negative anomalies, which is one year behind a positive IOD and EP-El Niño event. The S-EOF3 exhibits a different dipole distribution, with a positive anomaly in the central west and a negative anomaly in the southeast, synchronized or lagging behind the central Pacific El Nino (CP-El Niño). Moreover, regarding the correlation between the main modes of interannual variation and the IOD and El Nino events, the dynamic parameters (such as SST, SLA, rain, and wind) of the tropical Indo-Pacific Ocean are discussed using time-delay correlation and linear regression analysis to explain the key factors and possible influencing mechanism of the joint seasonal and interannual variations of Chla in the northern Indian Ocean.

Thailand is located in the Southeast Asian region, where the summer rainfall exhibits strong interannual variability, and the successful simulation of rainfall variation in Thailand by current climate models remains a challenge. Therefore, this paper evaluates the capability of the state-of-the-art Atmospheric GCM of the Institute of Atmospheric Physics (IAP-AGCM) in simulating summer rainfall over Thailand by comparing the model’s results with ground-truth observation during 1981–2012. Generally, the model shows a certain skill in reproducing the observed spatial distribution of the summer rainfall climatology and its interannual variability over Thailand, although the model underestimated both rainfall amount and its variability. Using Empirical Orthogonal Function (EOF) analysis, it is found that the IAP climate model reproduced creditably the spatial patterns of the first three dominant modes of summer rainfall in Thailand, whereas it underestimated the explained variance of the observed EOF-1 and overestimated the explained variance of the observed EOF-2 significantly. It was further found that the correlation between the observed rainfall anomalies in Thailand and the Niño3.4 index can be reproduced by the IAP model. However, the observed negative correlation is largely underestimated by the IAP climate model, and this could be the reason for the underestimation of explained variance of the EOF-1 by the IAP model. The evaluation results would be of great importance for further model improvement and thus potential application in seasonal prediction in the region.

The surface energy balance algorithm for land (SEBAL) is a commonly used method for estimating evapotranspiration (ET) at a regional scale; however, the cloudy and rainy characteristics of subtropical monsoon regions pose a greater challenge for estimating paddy field ET based on remote sensing technology. To this end, a typical subtropical climate region in southern China (Ganfu Plain irrigation system) was selected as the study area. Subsequently, we evaluated the applicability of the SEBAL model for estimating the ET of paddy fields at the daily scale; derived the interannual variation (2000–2017) characteristics of early, middle, and late rice ET; and finally analyzed the spatial distribution patterns of rice in different hydrological years. The results demonstrated that: (1) the SEBAL model estimated ET accurately on a daily scale, with R2, NSE, and RMSE values of 0.85, 0.81, and 0.84 mm/day, respectively; (2) the ET of paddy fields in the irrigated area was higher in July and August and the interannual trend of ET of early rice was not obvious, with a declining trend observed in middle rice and late rice from 2000 to 2009, which was followed by an increasing trend from 2009 to 2017; and (3) variations in the spatial distribution of ET were significant for early and late rice at different precipitation levels and less obvious for middle rice in wet years but significant in dry years. Overall, this study verified the applicability of the SEBAL model for estimating ET in paddy fields in subtropical regions and provided a basis and reference for the rational allocation of water resources at a regional scale.

Long-lived species are particularly interesting for investigation of trade-offs that shape reproductive allocation and the effective contribution to the next generations. Life history theory predicts that these species will buffer environmental stochasticity via changes in the reproductive investment, while maintaining high adult survival rates. The spur-thighed tortoise was selected as a case study in order to investigate the relationship between the linked maternal characteristics (size and age) and related traits in their hatchlings. We tracked naturally emerging hatchlings from young and old females under semi-natural conditions to test variations in hatchling numbers, body mass, size and survival over two years. We used linear mixed-effect models to analyze variations in hatchling body mass and size, and a mark–release–recapture framework to model their survival. Our study illustrates that old females of long-lived species have greater offspring numbers, greater survival and smaller size when compared with those of young females. The interannual variability evidenced the reduced offspring number and survival in the lower autumn rainfall and spring mean temperature year. Our results highlight the role of maternal age and climatic conditions in the population dynamics and the need for long-term studies of reproduction traits for designating adequate conservation strategies.

Central Asia is prone to wildfires, but the relationship between wildfires and climatic factors in this area is still not clear. In this study, the spatiotemporal variation in wildfire activities across Central Asia during 1997–2016 in terms of the burned area (BA) was investigated with Global Fire Emission Database version 4s (GFED4s). The relationship between BA and climatic factors in the region was also analyzed. The results reveal that more than 90% of the BA across Central Asia is located in Kazakhstan. The peak BA occurs from June to September, and remarkable interannual variation in wildfire activities occurs in western central Kazakhstan (WCKZ). At the interannual scale, the BA is negatively correlated with precipitation (correlation coefficient r = −0.66), soil moisture (r = −0.68), and relative humidity (r = −0.65), while it is positively correlated with the frequency of hot days (r = 0.37) during the burning season (from June to September). Composite analysis suggests that the years in which the BA is higher are generally associated with positive geopotential height anomalies at 500 hPa over the WCKZ region, which lead to the strengthening of the downdraft at 500 hPa and the weakening of westerlies at 850 hPa over the region. The weakened westerlies suppress the transport of water vapor from the Atlantic Ocean to the WCKZ region, resulting in decreased precipitation, soil moisture, and relative humidity in the lower atmosphere over the WCKZ region; these conditions promote an increase in BA throughout the region. Moreover, the westerly circulation index is positively correlated (r = 0.53) with precipitation anomalies and negatively correlated (r = −0.37) with BA anomalies in the WCKZ region during the burning season, which further underscores that wildfires associated with atmospheric circulation systems are becoming an increasingly important component of the relationship between climate and wildfire.

Monthly mean sea-levels have annual maxima in August in the northeast Asian marginal seas (NEAMS). Based on satellite altimetry data, the rising rate of the August NEAMS sea-level (ANS, 4.2 mm∙yr−1) is greater than those of the NEAMS (3.6 mm∙yr−1) and global (3.4 mm∙yr−1) annual mean sea-levels. Thus, the interannual variations of ANS are classified as relatively high (period H) and low (period L) years and have been analysed because of the high risk of sea-level fluctuation to the coastal regions in August. In period H, there are large atmospheric pressure gradients between the high pressure zone in the Kuroshio Extension (KE) and the low pressure zone in the west of Taiwan (WT). In period L, the atmospheric pressure gradients are small between the above-mentioned zones. Large atmospheric pressure gradients induce strong west-northwestward wind stresses and more Ekman transport from the northwest Pacific Ocean into the NEAMS. The correlation coefficient between August NEAMS sea-level index (ANSI), which is the difference of atmospheric pressure anomalies between the KE and the WT, and the August NEAMS sea-level anomaly (ANSA) is 0.73. Although there is a significant correlation (coefficient: 0.64) between ANSA and the East Asian summer monsoon index (EASMI), ANSI might be more useful in estimating the variability of ANSA.

This study presents the climatological characteristics and physical mechanisms of Guinea Coast precipitation in June. Traditionally, the low-tropospheric air temperature and equivalent potential temperature ( θ e ) play crucial roles in the generation of monsoon precipitation through the following mechanisms: 1. Near-surface atmospheric front, depicted by steep ∂ θ e ∂ y , corresponds to the vertical motion in the lower troposphere. 2. Strong easterly wind in the middle troposphere (600–500 hPa), generated by a steep ∂ T ∂ y near the surface at 12° N, induces a positive vorticity to the south and vertical motion over the Guinea Coast (~5° N). Meanwhile, the strong Guinea Coastal precipitation, in association with the interannual variability, is mainly determined by the sea-surface temperature (SST) anomaly in the eastern equatorial Atlantic Ocean. In years of warm SST in the eastern equatorial Atlantic, ∂ θ e ∂ y in the lower troposphere is less pronounced than in normal years. However, the atmospheric buoyancy (moist static instability) increases, owing to a strong vertical θ e gradient ( ∂ θ e ∂ p ) arising from the increase in moisture and warm temperature in the lower troposphere over the warm SST area. Consequently, the eastern equatorial Atlantic warm SST modulates the Guinea Coastal thermodynamic structure, causing deep convection that increases precipitation south of the Guinea Coast. Forced by the eastern equatorial Atlantic warm SST anomaly, the strong precipitation and corresponding atmospheric structures are successfully simulated from the Geophysical Fluid Dynamics Laboratory global atmosphere model 2.1.

As the carbon monoxide (CO) total column over Asia is among the highest in the world, it is important to characterize its variations in space and time. Using Measurements of Pollution in the Troposphere (MOPITT) and Atmospheric InfraRed Sounder (AIRS) satellite data, the variations and trends in CO total column over Asia and its seven subregions during 2003−2017 are investigated in this study. The CO total column in Asia is higher in spring and winter than in summer and autumn. The seasonal maximum and minimum are in spring and summer respectively in the regional mean over Asia, varying between land and oceans, as well as among the subregions. The CO total column in Asia shows strong interannual variation, with a regional mean coefficient of variation of 5.8% in MOPITT data. From 2003 to 2017, the annual mean of CO total column over Asia decreased significantly at a rate of (0.58 ± 0.15)% per year (or −(0.11 ± 0.03) × 1017 molecules cm−2 per year) in MOPITT data, resulting from significant CO decreases in winter, summer, and spring. In most of the subregions, significant decreasing trends in CO total column are also observed, more obviously over areas with high CO total column, including eastern regions of China and the Sichuan Basin. The regional decreasing trends in these areas are over 1% per year. Over the entire Asia, and in fire-prone subregions including South Siberia, Indo-China Peninsula, and Indonesia, we found significant correlations between the MOPITT CO total column and the fire counts from the Moderate Resolution Imaging Spectroradiometer (MODIS). The variations in MODIS fire counts may explain 58%, 60%, 36%, and 71% of the interannual variation in CO total column in Asia and these three subregions, respectively. Over different land cover types, the variations in biomass burning may explain 62%, 52%, and 31% of the interannual variation in CO total column, respectively, over the forest, grassland, and shrubland in Asia. Extremes in CO total column in Asia can be largely explained by the extreme fire events, such as the fires over Siberia in 2003 and 2012 and over Indonesia in 2006 and 2015. The significant decreasing trends in MODIS fire counts inside and outside Asia suggest that global biomass burning may be a driver for the decreasing trend in CO total column in Asia, especially in spring. In general, the variations and trends in CO total column over Asia detected by AIRS are similar to but smaller than those by MOPITT. The two datasets show similar spatial and temporal variations in CO total column over Asia, with correlation coefficients of 0.86−0.98 in the annual means. This study shows that the interannual variation in atmospheric CO in Asia is sensitive to biomass burning, while the decreasing trend in atmospheric CO over Asia coincides with the decreasing trend in MODIS fire counts from 2003 to 2017.

Bioassessment assumes that ecological conditions remain stable in the absence of environmental changes. Evidence suggests this assumption may hold for reference streams, but knowledge gaps remain for impacted streams. Our study quantified interannual variation of benthic macroinvertebrate communities, monitored for at least 14 years in eight impacted streams in the Upper Thames River watershed in Ontario, Canada. Benthic communities exhibited moderate interannual variation in relative abundance of EPT (Ephemeroptera, Plecoptera and Trichoptera) and Chironomidae taxa. Year-to-year changes were reflected in lower community persistence than that observed in studies of reference streams. In contrast, tolerance-based metrics showed minimal interannual variation, suggesting compositional changes were because of taxonomic substitutions, in which one tolerant taxon replaced another. Analyses indicated limited directionality in temporal variation for most bioassessment metrics. An exception was taxa richness, which increased at most sites, possibly because of changes in subsampling. However, no associations between calculated bioassessment metrics and measured environmental factors (stream flow and water chemistry) or sampling procedures were observed. We conclude interannual variation in ecological conditions can be substantial and may not be associated with deterministic factors routinely measured in stream assessments. We recommend increased sampling frequency and traits-based assessment as options for limiting effects of interannual variation on assessment results.

In this study, we use the long-term satellite data to investigate seasonal and interannual variation of low-cloud fraction (LCF) and the associated controlling factors over the eastern and western North Pacific. On the seasonal time scale, the enhanced LCF over the eastern North Pacific in summer is actively coupled with strong estimated inversion strength (EIS) and 700-hPa relative humidity, and the LCF over the western North Pacific in winter is large and mainly caused by increased sensible heat flux and tropospheric low-level cold advection. On the interannual time scale, the increased LCF over the eastern North Pacific in summer is associated with increased EIS and decreased sea surface temperatures, in which the El Niño plays an important role; the enhanced LCF over the western North Pacific in spring and winter has a positive correlation with enhanced sensible heat flux (SHF) and tropospheric low-level cold advection, which can be partly explained by the subpolar frontal zone (SPFZ) intensity.

In addition to the impact of pollutant emissions, haze pollution is connected with meteorology and climate change. Based on the interannual change analyses of meteorological and environmental observation data from 1981 to 2010, we studied the relationship between the winter haze frequency in central-eastern China (CEC) and the interannual variations of sea surface temperature (SST) over Western Pacific Warm Pool (WPWP) and its underlying mechanism to explore the thermal effect of WPWP on haze pollution variation in China. The results show a significant positive correlation coefficient reaching up to 0.61 between the interannual variations of SST in WPWP and haze pollution frequency in the CEC region over 1981–2010, reflecting the WPWP’s thermal forcing exerting an important impact on haze variation in China. The anomalies of thermal forcing of WPWP could induce to the changes of East Asian winter monsoonal winds and the vertical thermal structures in the troposphere over the CEC region. In the winter with anomalously warm SST over the WPWP, the near-surface winds were declined, and vertical thermal structure in the lower troposphere tended to be stable over the CEC-region, which could be conducive to air pollutant accumulation leading to the more frequent haze occurrences especially the heavy haze regions of Yangtze River Delta (YRD) and Pearl River Delta (PRD); In the winter with the anomalously cold WPWP, it is only the reverse of warm WPWP with the stronger East Asian winter monsoonal winds and the unstable thermal structure in the lower troposphere, which could attribute to the less frequent haze pollution over the CEC region. Our study revealed that the thermal forcing of the WPWP could have a modulation on air environment change in China.