Interannual Trends Research Articles

Photoperiod alone does not explain the variations of leaf senescence onset across Europe

The onset of autumnal leaf senescence (TLSO) plays a crucial role in understanding and modeling how plants prepare for winter dormancy, but it has remained under-explored. Previous research, based on limited in situ observations, have proposed that the year-to-year invariant photoperiod is the primary trigger of TLSO, indicating potential insensitivity to climate change. This study verifies this hypothesis using high spatial resolution satellite data and ground-based observations throughout the European continent. Surprisingly, our findings reveal a widespread delay in TLSO during 2001–2019 (approximately 73 %, significant in 19 % of the continent, p < 0.05), closely aligned with delayed leaf senescence end (TLSD) as reported in previous studies. Moreover, as the delaying trend was larger for TLSO than for TLSD, it is apparent that climate change does not only postpone the onset of the leaf senescence process but also shortens its duration across the continent. This finding indicates that a reduced duration for plants to get ready for dormancy could potentially undermine their resilience to cold and other winter stresses. Contrary to the hypothesized photoperiodic control, TLSO exhibited opposing inter-annual temporal trends along temperature gradients, despite similar daylengths. Ground based observations failed to support photoperiodic influence either, highlighting the substantial spatial variation in TLSO responses to climate change. Intriguingly, complex climate-TLSO interactions were observed, with radiation dominating TLSO changes in 37.0 % of the study area. This analysis underscores the necessity of considering multiple variables to comprehend the patterns of TLSO at continental and vegetation scales.

Interannual Variation and Trend of Carbon Budget Observed for More Than Two Decades at Takayama in a Cool‐Temperate Deciduous Forest in Central Japan

AbstractLong‐term carbon dioxide (CO2) flux measurements between the atmosphere and the ecosystem have been made since 1993 at a cool‐temperate deciduous forest site (Takayama) in Japan influenced by the Asian Monsoon, constituting the longest data set among all the AsiaFlux sites. Interannual variations (IAVs) and trends in the annual carbon budget components and related environmental factors were examined. Annual net ecosystem production (NEP) (mean ± 1σ) during the period of eddy covariance measurements in 1999–2021 was 265 ± 86 gC m−2 yr−1, and its IAV was dependent more on gross primary production (GPP) than on ecosystem respiration. The annual NEP and GPP were correlated with the monthly mean NEP, GPP and leaf area index from June to September, as well as with the length of the net carbon uptake period. Significantly increasing and decreasing trends in the annual NEP and GPP were detected during 2004–2013 and 2013–2021, respectively. The increasing trends were mainly caused by the vegetation recovery from typhoon disturbances. On the other hand, although the cause of the decreasing trends was not clearly identified, recent extreme weather events and/or forest succession might be related to the trends. Significant positive correlations between the start and the end of the net carbon uptake period, and between the leaf expansion and leaf fall were found. These may be attributed to phenological characteristics and negative correlation between air temperature in spring and solar radiation in early fall associated with ENSO events that can also influence IAVs in annual NEP and GPP.

Agricultural drought-driven mechanism of coupled climate and human activities in the karst basin of southern China.

Timely and accurate agricultural drought monitoring and drought-driven mechanism analysis in karst basins in the context of global warming are highly important for drought disaster monitoring and sustainable ecological development in a basin. In this study, based on MODIS data, meteorological and topographic data and land use data from 2001 to 2020, we used the Sen slope, the Mann-Kendall test and a geographic detector to explore the driving mechanisms of agricultural drought caused by climate change and human activities in the karst basin of southern China from 2001 to 2020. The results showed that (1) the spatial distribution of the TVDI in the karst basin in southern China has obvious regional characteristics, showing a decreasing trend from west to east. (2) According to the interannual trend of drought, the degree of drought in the South China karst basin exhibited a weakening trend over the last 20 years, with the most severe drought occurring in 2003. Regarding the seasonal change in the TVDI, drought in spring, summer and autumn exhibited a decreasing trend, while that in winter exhibited an increasing trend, and the drought intensity decreased in the following order: spring (0.58) > autumn (0.53) > summer (0.5) > winter (0.48). (3) Single-factor detection the results showed that rainfall, temperature and elevation were the main factors driving aridification in the study area; multifactor coupling (mean) drove drought in descending order: rainfall (q = 0.424) > temperature (q = 0.340) > elevation (q = 0.219) > land use (q = 0.188) > population density (q = 0.061) > slope (q = 0.057). Therefore, revealing the mechanism of agricultural drought in karst basins through the study of this paper has important theoretical significance and provides technical guidance for drought relief in karst areas.

Analysis of Spatial Differentiation of NDVI and Climate Factors on the Upper Limit of Montane Deciduous Broad-Leaved Forests in the East Monsoon Region of China

The vertical transition zone of mountain vegetation is characterized by high species diversity, and the width of the transition zone may serve as an indirect indicator of climate change. However, research into the differential characteristics of vegetation response to climate changes at the boundary of vertical transition zones has been limited. This study employs MODIS and climate data spanning 2001 to 2018 to investigate spatiotemporal trends in precipitation (PRE), temperature (TMP), radiation (RAD), and Normalized Difference Vegetation Index (NDVI) across nine montane deciduous broad-leaved forests in the eastern monsoon region of China. It explores the time-lag and -accumulation effects of climatic variables on NDVI, quantifying their relative contributions to both its short-term and interannual variations. Results show that, notably, with the Qinling-Daba Mountains as a demarcation, northern regions exhibit significant increases in RAD (0.874–2.047 W m−2/a), whereas southern regions demonstrate notable rises in TMP (0.59–0.73 °C/10a). Areas of lower annual PRE correspond to the most rapid increases in annual average NDVI (5.045 × 10−3/a). NDVI’s lag time and cumulative duration responses to TMP are the shortest (0 and 2~4 periods), while its correlation with RAD is the strongest (0.815–0.975), generally decreasing from higher to lower latitudes. TMP significantly affects NDVI variations, impacting both short-term and interannual trends, with PRE driving short-term fluctuations and RAD dictating long-term shifts. This research provides critical data and a theoretical framework that enhances our understanding of how regional vegetation’s vertical zonation responds to climate change, thereby making a substantial contribution to the study of mountain vegetation’s diverse adaptability to climatic variations.

Mutual inhibition effects of elevated CO2 and climate change on global forest GPP

The impact of CO2 fertilization on enhancing global forest gross primary productivity (GPP) is acknowledged, but its interaction with climate factors—air temperature (Tem), precipitation (Pre), vapor pressure deficit (VPD), and radiation (Rad)—remains unclear. In this study, global forest GPP trends from 1982 to 2018 were examined using BEPS, NIRv, FLUXCOM, and revised EC-LUE datasets, with interannual trends of 5.618 (p < 0.01), 5.831 (p < 0.01), 0.227, and 6.566 g C m−2 yr−1 (p < 0.01), respectively. Elevated CO2 was identified as the primary driver of GPP trends, with the dominant area ranging from 51.11% to 90.37% across different GPP datasets. In the NIRv and revised EC-LUE datasets, the positive impact of CO2 on GPP showed a decrease of 0.222 g C m−2 yr−1, while the negative impact of Rad increased by 0.007 g C m−2 yr−1. An inhibitory relationship was found between the actual effects of elevated CO2 and climate change on GPP in most forest types. At lower latitudes, Tem primarily constrained CO2 fertilization, while at higher latitudes, VPD emerged as the key limiting factor. This was mainly attributed to the potential trade-off or competition between elevated CO2 and climate change in influencing GPP, with strategic resource allocation varying across different forest ecosystems. This study highlights the significant inhibitory effects of elevated CO2 and climate change on global forest GPP, providing insights into the dynamic responses of forest ecosystems to changing environments.

Changes in Surface Runoff and Temporal Dispersion in a Restored Montane Watershed on the Qinghai–Tibetan Plateau

Surface runoff is a major component of the hydrological cycle, and it is essential for supporting the ecosystem services provided by grassland and forest ecosystems. It is of practical importance to understand the mechanisms and the dynamic processes of runoff in a river’s basin, and in this study, we focused on the restored montane Pailugou Basin in the Qilian Mountains, Gansu Province, China, since its water status is extremely important for the large arid area and local economies therein. Our purpose was to determine the annual variation in the surface runoff in the Pailugou Basin because it is important to understand the influence of climate fluctuations on surface water resources and the economy of the basin. In addition, little is known about the annual variations in precipitation and runoff in this region of the world. Daily atmospheric precipitation, air temperature and runoff data from 2000 to 2019 were analyzed by the calculation of the uneven annual distribution of surface runoff, the calculation of the complete adjustment coefficient, and the vector accumulation expressed by the concentration degree. We also used the cumulative anomaly approach to determine the interannual variation trend of runoff, while the change trend was quantified by the sliding average method. Finally, we used the Mann–Kendall mutation test method and regression analysis to establish the time-series trend for precipitation and runoff and to determine the period of abrupt runoff changes. The results indicated concentrated and positive distributions of surface runoff on an annual basis, with a small degree of dispersion, and an explicit concentration of extreme flows. The relative variation ranges exhibited a decreasing trend, and the distribution of the surface runoff gradually was uniform over the year. The runoff was highest from July to September (85% of the annual total). We also determined that annual surface runoff in the basin fluctuated over the 20-year period but showed an overall increasing trend, increasing by 3.94 × 105 m3, with an average increase rate of 0.42 × 105 m3 every ten years. From 2005 to 2014, the annual runoff and the proportion of runoff in the flood season (July to September) to the annual runoff fluctuated greatly. The correlation between the runoff and precipitation was significant (r = 0.839, p &lt; 0.05), whereas the correlation between air temperature and surface runoff was low (r = 0.421, p &lt; 0.05).

Recent-year variations in O3 pollution with high-temperature suppression over central China

By analyzing environmental and meteorological monitoring data over recent years of 2015–2022, the Twain-Hu Basin (THB) in central China was identified as a regional O3 pollution center over China with the highest increasing trend at 1.10 %⸱yr−1 in interannual variations of O3 concentrations with deteriorating O3 pollution over recent years. We explored the spatiotemporal variations in O3 pollution in the THB with ozone suppression (OS) under high air temperature over metropolitan, small urban, and mountainous areas. The bipolarized interannual trends in interannual O3 variations in urban and mountainous areas over central China were characterized with the increasing and decreasing 90th percentiles of the daily maximum 8-h (MDA8-90) O3 concentrations respectively in polluted urban areas and clean mountainous areas over recent eight years. The changes of the near-surface O3 concentrations with air temperature exhibited the inflection points of OS from increasing to decreasing O3 at air temperature of 30.5 °C in mountainous areas, 32.5 °C in small urban areas, and 34.5 °C in metropolitan areas, and the intensity of OS was estimated in the ranking with mountainous areas (−2.30 μg⸱m−3⸱°C−1) > small urban areas (−1.96 μg⸱m−3⸱°C−1) > metropolitan areas (−1.54 μg⸱m−3⸱°C−1), indicating that the OS was more significant over the lower-O3 mountainous areas. This study has implications for understanding O3 pollution variations with the meteorological drivers.

Sustained Reductions of Bay Area CO2 Emissions 2018-2022.

Cities represent a significant and growing portion of global carbon dioxide (CO2) emissions. Quantifying urban emissions and trends over time is needed to evaluate the efficacy of policy targeting emission reductions as well as to understand more fundamental questions about the urban biosphere. A number of approaches have been proposed to measure, report, and verify (MRV) changes in urban CO2 emissions. Here we show that a modest capital cost, spatially dense network of sensors, the Berkeley Environmental Air Quality and CO2 Network (BEACO2N), in combination with Bayesian inversions, result in a synthesis of measured CO2 concentrations and meteorology to yield an improved estimate of CO2 emissions and provide a cost-effective and accurate assessment of CO2 emissions trends over time. We describe nearly 5 years of continuous CO2 observations (2018-2022) in a midsized urban region (the San Francisco Bay Area). These observed concentrations constrain a Bayesian inversion that indicates the interannual trend in urban CO2 emissions in the region has been a modest decrease at a rate of 1.8 ± 0.3%/year. We interpret this decrease as primarily due to passenger vehicle electrification, reducing on-road emissions at a rate of 2.6 ± 0.7%/year.

Monitoring and influencing factors of grassland livestock overload in Xinjiang from 1982 to 2020.

It is crucial to estimate the theoretical carrying capacity of grasslands in Xinjiang to attain a harmonious balance between grassland and livestock, thereby fostering sustainable development in the livestock industry. However, there has been a lack of quantitative assessments that consider long-term, multi-scale grass-livestock balance and its impacts in the region. This study utilized remote sensing and empirical models to assess the theoretical livestock carrying capacity of grasslands. The multi-scale spatiotemporal variations of the theoretical carrying capacity in Xinjiang from 1982 to 2020 were analyzed using the Sen and Mann-Kendall tests, as well as the Hurst index. The study also examined the county-level grass-livestock balance and inter-annual trends. Additionally, the study employed the geographic detector method to explore the influencing factors. The results showed that: (1) The overall theoretical livestock carrying capacity showed an upward trend from 1982 to 2020; The spatial distribution gradually decreased from north to south and from east to west. In seasonal scale from large to small is: growing season > summer > spring > autumn > winter; at the monthly scale, the strongest livestock carrying capacity is in July. The different grassland types from largest to smallest are: meadow > alpine subalpine meadow > plain steppe > desert steppe > alpine subalpine steppe. In the future, the theoretical livestock carrying capacity of grassland will decrease. (2) From 1988 to 2020, the average grass-livestock balance index in Xinjiang was 2.61%, showing an overall increase. At the county level, the number of overloaded counties showed an overall increasing trend, rising from 46 in 1988 to 58 in 2020. (3) Both single and interaction factors of geographic detectors showed that annual precipitation, altitude and soil organic matter were the main drivers of spatiotemporal dynamics of grassland load in Xinjiang. The results of this study can provide scientific guidance and decision-making basis for achieving coordinated and sustainable development of grassland resources and animal husbandry in the region.

Vegetation and Evapotranspiration Responses to Increased Atmospheric Vapor Pressure Deficit across the Global Forest

A forest is vulnerable to drought and plays important roles in the regulation of carbon and water cycling in a terrestrial ecosystem. Atmospheric vapor pressure deficit (VPD) has been identified as an increasingly major factor in plant functioning and has been established as a main contributor to recent drought-induced plant mortality, independent of other drivers associated with climate change. However, most previous studies have focused on the effects of climate warming and CO2 enrichment on vegetation growth, without considering the effects of an increased VPD on vegetation growth and evapotranspiration (ET) in forest ecosystems. This could lead to a large uncertainty in estimating the variability in forest carbon sinks. Based on the long-term satellite data, we investigated the response of the leaf area index (LAI) and ET to the VPD via a partial correlation analysis in this study. We also examined the temporal variability in the partial coefficients within a ten-year moving window. The results showed that over 50% of the region displayed a negative partial correlation between the LAI, ET, and VPD, and those pixels were mainly concentrated in North America and the plains of Eastern Europe. Regions with a negative trend of partial correlation in both the LAI and ET are mostly located in the plains of Eastern Europe and the Siberian Plain of western Russia, while the positive trend is mainly in South America. The plains of Eastern Europe are becoming drier, which was proved by the interannual trend of the Standardized Precipitation Evapotranspiration Index (SPEI) and soil water content (SWC). Additionally, the LAI and ET in those areas exhibited a significant positive correlation with the SWC based on the moving window average. This study suggests that the role of the VPD on vegetation will become increasingly prominent in the context of future climate change for the forest ecosystem.

Analysis of Changes in Runoff and Sediment Load and Their Attribution in the Kuye River Basin of the Middle Yellow River Based on the Slope Change Ratio of Cumulative Quantity Method

Climate change and human activities exert significant influence on the water–sediment relationship in arid and semi-arid regions. Therefore, comprehending the underlying mechanisms is crucial for the effective management of water and soil resources, as well as integrated watershed management. This research focuses on the Kuye River watershed (KYH_W) in the middle reaches of the Yellow River in China, along with its sub-watersheds Wangdaohengtazi (WDHT_SW) and Xinmiaosi (XM_SW). This paper utilizes the Mann–Kendall non-parametric test and the double cumulative curve method to examine the interannual trends of runoff, sediment transport, precipitation, temperature, and NDVI factors. Furthermore, the method of the slope change ratio of cumulative quantity (SCRCQ) is utilized to quantitatively evaluate the impacts and contribution rates of climate change and human activities on water–sediment changes within each watershed. The results are as follows: (1) From 1969 to 2019, the entire watershed experienced a significant decrease in both runoff and sediment transport, with 1997 marking the year of abrupt change. However, following 2012, the KYH_W and WDHT_SW exhibited a noticeable rebound in runoff. (2) Human activities predominantly contribute to the reduction in water and sediment in the watershed. (3) After the abrupt change, between 1998 and 2011, the contribution rates of climate change and human activities to the annual runoff reduction in the entire KYH_W reached 33% and 64%, respectively. Moreover, these rates for sediment transport reduction reached 26% and 74%, respectively. Subsequently, after 2012, the contribution rates of both factors to the increase in watershed runoff reached 29% and 71%, respectively. Factors other than the NDVI, within human activities, played a dominant role in augmenting the watershed’s runoff. (4) Prior to 2011, changes in vegetation cover resulting from the Grain for Green Program, as measured by the NDVI, emerged as the primary factor responsible for reduced runoff in the watershed. Conversely, factors other than the NDVI assumed dominance in reducing sediment transport. The SCRCQ method offers a quantitative approach to assessing water–sediment changes. Based on this method, the study further underscores the substantial impacts of climate change and human activities on variations in runoff and sediment transport within the KYH_W in the middle reaches of the Yellow River. Notably, the water–sediment changes in the KYH_W exhibit distinct stage-wise and spatial discrepancies, which warrant increased attention in future research endeavors.

The Impact of Quality Control Methods on Vegetation Monitoring Using MODIS FPAR Time Series

Monitoring vegetation dynamics (VD) is crucial for environmental protection, climate change research, and understanding carbon and water cycles. Remote sensing is an effective method for large-scale and long-term VD monitoring, but it faces challenges due to changing data uncertainties caused by various factors, including observational conditions. Previous studies have demonstrated the significance of implementing proper quality control (QC) of remote sensing data for accurate vegetation monitoring. However, the impact of different QC methods on VD results (magnitude and trend) has not been thoroughly studied. The fraction of absorbed photosynthetically active radiation (FPAR) characterizes the energy absorption capacity of the vegetation canopy and is widely used in VD monitoring. In this study, we investigated the effect of QC methods on vegetation monitoring using a 20-year MODIS FPAR time series. The results showed several important findings. Firstly, we observed that the Mixed-QC (no QC on the algorithm path) generally produced a lower average FPAR during the growing season compared to Main-QC (only using the main algorithm). Additionally, the Mixed-QC FPAR showed a very consistent interannual trend with the Main-QC FPAR over the period 2002–2021 (p &lt; 0.05). Finally, we found that using only the main algorithm for QC generally reduced the trend magnitude (p &lt; 0.1), particularly in forests. These results reveal differences in FPAR values between the two QC methods. However, the interannual FPAR trends demonstrate greater consistency. In conclusion, this study offers a case study on evaluating the influence of different QC methods on VD monitoring. It suggests that while different QC methods may result in different magnitudes of vegetation dynamics, their impact on the time series trends is limited.

Multiple-Time-Scale Variations of the Record-Breaking Pre-Summer Rainfall over South China in 2022

Abstract South China encountered an exceptionally heavy pre-summer rainy season in 2022 with the regional precipitation ranking first in the past 44 years. This study aims to analyze the multiple-time-scale variations of precipitation in this pre-summer rainy season to shed light on the complex dynamics influencing pre-summer precipitation over South China. The findings reveal that the variation of precipitation was dominated by the 10–20-day oscillation during April–May, while interannual variation and trend during May–June. The 10–20-day oscillation of precipitation in pre-summer rainy season in South China demonstrates a strong association with cold-air activity, which can be traced back to the propagation of disturbances along a teleconnection, which represents the dominant mode of intraseasonal atmospheric circulation over Eurasia in high latitudes during April–May. This teleconnection plays a crucial role in facilitating cold-air invasion and triggering precipitation over East China and South China. The interannual component of abnormal precipitation is strong during May–June of 2022. It is primarily attributed to the abnormal highs in the lower troposphere over the subtropical western North Pacific and Japan. These abnormal highs are likely stimulated by the combined influences of Eurasian teleconnection propagation and cooling sea surface temperature anomalies (SSTAs) over the tropical central and eastern Pacific in the third year of a consecutive La Niña event. However, the universality of the impact of Eurasian teleconnection propagation on the abnormal high over Japan on interannual scale necessitates further investigation. Furthermore, there is a significant upward trend in pre-summer rainfall over South China, accounting for 38% of the total anomaly observed in 2022.

Sea ice cover in the Copernicus Arctic Regional Reanalysis

Abstract. The Copernicus Arctic Regional Reanalysis (CARRA) is a novel regional high-resolution atmospheric reanalysis product that covers a considerable part of the European Arctic including substantial amounts of ice-covered areas. Sea ice in CARRA is modelled by means of a one-dimensional thermodynamic sea ice parameterisation scheme, which also explicitly resolves the evolution of the snow layer over sea ice. In the present study, we assess the representation of sea ice cover in CARRA and validate it against a wide set of satellite products and observations from ice mass balance buoys. We show that CARRA adequately represents general interannual trends towards thinner and warmer ice in the Arctic. Compared to ERA5, sea ice in CARRA shows a reduced warm bias in the ice surface temperature. The strongest improvement was observed for winter months over the central Arctic and the Greenland and Barents seas where a 4.91 °C median ice surface temperature error in ERA5 is reduced to 1.88 °C in CARRA on average. Over Baffin Bay, intercomparisons suggest the presence of a cold winter-time ice surface temperature bias in CARRA. No improvement over ERA5 was found in the ice surface albedo with spring-time errors in CARRA being up to 0.08 higher on average than those in ERA5 when computed against the CLARA-A2 satellite retrieval product. Summer-time ice surface albedos are comparable in CARRA and ERA5. Sea ice thickness and snow depth in CARRA adequately resolve the annual cycle of sea ice cover in the Arctic and bring added value compared to ERA5. However, limitations of CARRA indicate potential benefits of utilising more advanced approaches for representing sea ice cover in next-generation reanalyses.

Trend of Ostreopsis cf. ovata (Dinophyceae) along the Conero Riviera (northern Adriatic Sea) over two decades

ABSTRACT Harmful blooms of the toxic dinoflagellate Ostreopsis cf. ovata have been a recurrent phenomenon along the Mediterranean coasts in the last decades. Since first recorded, there has been a widespread belief that the extension of this dinoflagellate, well-known in tropical areas, to higher latitudes was due to global warming and the general rise of seawater temperature. Blooms of O. cf. ovata along the Conero Riviera (northern Adriatic Sea) occur between the end of the summer and the beginning of the autumn since 2006. The Ostreopsis cf. ovata abundances collected from its first record to today were analysed to better define the interannual trend of this phenomenon and its possible linking to certain climate change predictors. A significant increasing trend in the magnitude of Ostreopsis phenomenon was observed up to year 2012, then a stabilization at relatively low values was observed. This trend does not follow the incessant increase in water temperature observed during the last three decades in the Adriatic Sea, but rather recalls patterns seen in invasive species, although the provenience of O. cf. ovata in the Mediterranean Sea is still unresolved. Even if the Ostreopsis bloom in this area seems to slightly lessen in the last decade, Ostreopsis abundances still reach values of up to 103 cells cm−2 which could be harmful to human health.

Drought‐Induced Vertical Displacements and Water Loss in the Po River Basin (Northern Italy) From GNSS Measurements

AbstractWe study vertical ground displacement time series from Global Navigation Satellite System (GNSS) stations to measure deformation associated with hydrological drought in the Po river basin. Focusing on interannual trend changes, rather than seasonal (annual) components, we found a clear spatially correlated deformation signal that is temporally (anti)correlated with changes in the Po river level and the SPEI‐12 drought index, with stations moving upward during periods of river/index level decrease and vice versa. In the 2021–2022 time span, which culminated in the most severe drought of the last two centuries, we estimate the amount and spatial distribution of water loss in the basin and its surroundings. Excluding the seasonal signals, between January 2021 and August 2022, the GNSS stations underwent uplift, up to 7 mm, which corresponds to ∼70 Gtons of water loss. Compared to Global Land Data Assimilation System and Gravity Recovery and Climate Experiment estimates, GNSS results show a similar temporal evolution of water content but a more heterogeneous distribution of values. We show that continuous GNSS networks provide an effective way to monitor multiannual trend changes in water storage even in small water basins and serve as a reliable indicator of drought severity.

Exacerbating water shortage induced by continuous expansion of surface artificial water bodies in the Yellow River Basin

Aggravated water shortage limits high-quality and sustainable development in the Yellow River Basin (YRB), an important strategic region with a dense population in China. Surface water area (SWA) and terrestrial water storage (TWS) are two crucial indicators of the overall status of water resources in the region, so monitoring their dynamics and drivers is extremely important for sustainable water management under a changing climate and anthropogenic disturbances. Here, we examined the interannual variabilities and trends of SWA and TWS in the YRB during 1990–2021 utilizing all Landsat-5/7/8 surface reflectance observations, Gravity Recovery and Climate Experiment mascon data, a robust water mapping algorithm based on spectral indices and thresholds, and the Google Earth Engine (GEE) cloud computing platform. We found that SWA continuously and substantially expanded (49.67 ± 9.73 km2/yr) in the YRB. The most rapid expansion of SWA occurred in Shandong Province (20.24 ± 1.00 km2/yr), next in the provinces of Henan (15.09 ± 1.16 km2/yr), Shanxi (13.21 ± 1.11 km2/yr), and Shaanxi (4.11 ± 1.07 km2/yr). Quantitative attribution analysis showed that anthropogenic factors, including constructing and extending artificial reservoirs/lakes (42.4 %) and aquaculture ponds (26.5 %), were the major contributors to increased SWA. However, TWS had a significant downward trend (-6.82 ± 0.99 mm/yr) across the entire YRB. Using water evaporation data, we found that evaporation consistently increased (0.07 ± 0.01 km3/yr or 0.16 ± 0.02 mm/yr), which was mainly caused by SWA expansion in Shandong, Henan, Shanxi, Shannxi, Inner Mongolia. We also identified the hotspots with the most rapid increases in evaporative loss, which were in the provinces of Shandong (0.026 ± 0.002 km3/yr) and Henan (0.018 ± 0.001 km3/yr). These losses resulted in a decline of TWS by 1.37 ± 0.11 mm/yr and 0.5 ± 0.05 mm/yr, respectively. Our findings warn that the expanding surface water bodies were not only an illusion of increased freshwater resources in the YRB but also exacerbated the water crisis by accelerating TWS loss through evaporation.

Effects of land surface temperatures on vegetation phenology along urban–rural local climate zone gradients

ContextUrbanization and local urban climate have multiple impacts on vegetation phenology in urban and suburban areas. Understanding these effects and their interactions with the surface urban heating effect remains limited.ObjectiveWe employed a time series of Earth observation data to analyze land surface phenology (LSP) dynamics and related environmental drivers in the highly urbanized Pearl River Delta (PRD) region.MethodsFirst, local climate zone (LCZ) maps were generated from Earth observation datasets of 2000 and 2019. Second, LSP (i.e., start, end, and length of season) were extracted from vegetation indices for 2000–2019. Thirdly, land surface temperature (LST) was used as an explanatory variable based on the LCZ of cities. Finally, interannual trends of LSP and their association with LST were analyzed, depending on the distance gradient of vegetation to compact high-rise buildings.ResultsUrban surface characteristics showed that LSP in regions dominated by compact and high-rise urban areas presented significant spatiotemporal variation at the start and end of season than those dominated by open, mid-rise, and low-rise areas. The impacts of spring and autumn LST in the daytime on LSP were slightly more substantial than those in the nighttime. The association of decreasing spring LST in the daytime with a delayed start of season is especially pronounced in urban domains.ConclusionsThe results indicate that vegetated areas adjacent to urban domains presented greater spatiotemporal dynamics than suburban and rural regions. Our study emphasizes the dependence of spatiotemporal changes in vegetation phenology on the effects of urban surface warming.

Multi-timescale variation characteristics of PM2.5 in different regions of China during 2014–2022

Over the past decade, China has achieved a significant reduction in PM2.5 concentrations. Due to the diversity of natural and artificial factors, regional differences are remarkable in the variation characteristics and have not been well addressed in previous studies. Based on hourly observed PM2.5 concentrations from 2014 to 2022, this study conducted a comprehensive analysis of variation characteristics on annual, seasonal, and diurnal scales, with a special focus on differences across major regions. Driving factors of the variations, the effectiveness of air pollution control efforts as well as future priorities were discussed. The annual PM2.5 concentrations in all regions showed an overall downward trend from 2014 to 2022, but the decline rates differed notably across the regions, with the maximum value nearly two times higher than the minimum value. The seasonal decline rates also differ from region to region, which could be partially attributed to the burning of crop residues and dust events. Northeast China was significantly affected by the burning of crop residues and experienced a big drop in the number of fire points in autumn, but a remarkable increase in spring. The spring dust events may greatly contribute to PM2.5 concentrations in northern and western China. For diurnal variation, nighttime concentrations were generally greater than daytime concentrations, and the nighttime concentrations were likely to increase in eastern regions and decrease in western regions. Furthermore, the daytime and nighttime ratios (calculated by daytime/nighttime concentration divided by the daily-mean concentration) exhibited different interannual trends, with the daytime ratios decreasing and nighttime ratios increasing, especially in the northeastern and western regions. The findings indicate that the air pollution control efforts have been generally successful, but with large regional disparities, and highlight the importance of controlling crop residue burning, dust events, and nighttime emissions for specific seasons and regions.

Interannual variations and trends of gross primary production and transpiration of four mature deciduous broadleaf forest sites during 2000–2020

The interannual variations of gross primary production (GPP) and transpiration (T) in deciduous broadleaf forests reflect how the forest responds to climate change. However, our knowledge remains limited due to lack of multi-decadal data. In this study, we selected four mature deciduous broadleaf forest sites in the United States of America and Canada from 2000 to 2020 to investigate decadal trends in atmospheric CO2 concentrations, climate, vegetation indices, phenology, and carbon and water fluxes. The Vegetation Photosynthesis Model (VPM v3.0) and the Vegetation Transpiration Model (VTM, v2.0) were used to estimate GPP and T at the four sites. The GPP from the VPM simulations (GPPVPM) is highly consistent with that from the eddy flux tower sites (GPPEC) (R2 range from 0.77 to 0.89). The interannual trends of carbon and water fluxes during the period from 2000 to 2020 varied by sites, ranging from increases (CA-Cbo) to no trend (US-Ha1, US-MMs, US-WCr sites), dependent upon the temporal changes in atmospheric CO2 concentration and climate. Spring phenology at these sites had no significant trends due to the lack of an interannual trend of air temperature during 2000–2020. In those years with hotter winter and early spring season (WESS), the start of the season (SOS) advanced and the growing season length (GSL) extended, but there were little changes in the end of the season (EOS) and annual GPP. This study highlights the value of long-term measurements at forest eddy flux tower sites and the skill of VPM v3.0 and VTM v2.0 models and the ERA5 climate dataset for simulations over the past two decades, which could be used to do regional and global simulations of deciduous broadleaf forests and assess their responses to climate change.