Change in the magnitude and mechanisms of global temperature variability with warming

Revealing climatic and groundwater impacts on the spatiotemporal variations in vegetation coverage in marine sedimentary basins of the North China Plain, China

The North China Plain (NCP) is one of the three great plains in China and also serves as a vital region for grain, cotton, and oil production. Under the influence of regional hydrothermal changes, groundwater overexploitation, and seawater intrusion, the vegetation coverage is undergoing continuous alterations. However, a comprehensive assessment of impacts of precipitation, temperature, and groundwater on vegetation in marine sedimentary regions of the NCP is lacking. Heilonggang Basin (HB) is located in the low-lying plain area in the east of NCP, which is part of the NCP. In this study, the HB was chosen as a typical area of interest. We collected a series of data, including the Normalized Difference Vegetation Index (NDVI), precipitation, temperature, groundwater depth, and Total Dissolved Solids (TDS) from 2001 to 2020. Then the spatiotemporal variation in vegetation was analyzed, and the underlying driving mechanisms of vegetation variation were explored in this paper. The results show that NDVI experiences a rapid increase from 2001 to 2004, followed by stable fluctuations from 2004 to 2020. The vegetation in the HB has achieved an overall improvement in the past two decades, with 76% showing improvement, mainly in the central and eastern areas, and 24% exhibiting deterioration in other areas. From 2001 to 2020, NDVI correlates positively with precipitation, whereas its relationship with temperature fluctuates between positive and negative, and is not statistically significant. There is a threshold for the synergistic change of NDVI and groundwater depth. When the groundwater depth is lower than 3.8 m, NDVI increases sharply with groundwater depth. However, beyond this threshold, NDVI tends to stabilize and fluctuate. In the eastern coastal areas, NDVI exhibits a strong positive correlation with groundwater depth, influenced by the surface soil TDS controlled by groundwater depth. In the central regions, a strong negative correlation is observed, where NDVI is primarily impacted by soil moisture under the control of groundwater. In the west and south, a strong positive correlation exists, with NDVI primarily influenced by the intensity of groundwater exploitation. Thus, precipitation and groundwater are the primary driving forces behind the spatiotemporal variability of vegetation in the HB, while in contrast, the influence of temperature is uncertain. This study has elucidated the mechanism of vegetation response, providing a theoretical basis for mitigating adverse factors affecting vegetation growth and formulating rational water usage regulations in the NCP.

Increasing sensitivity of dryland water use efficiency to soil water content due to rising atmospheric CO2

Examining the intricate interplay between ecosystem carbon-water coupling and soil moisture sensitivity serves as a crucial approach to effectively assess the dilemma arising from escalating global carbon emissions and concomitant water scarcity. Using the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ), this study investigated the potential effects of climate change and soil water content (SWC) on terrestrial ecosystem water use efficiency (WUE) across China from 1982 to 2060. The results revealed that: (1) WUE was higher in South China and Northeast China, but lower in Northwest China and it had shown a significant upward trend in the past 40 years, especially in Northwest China where grasslands were widely distributed. The increase in WUE was mainly closely related to the greening of vegetation. In the past 40 years, the area of net primary productivity (NPP), evapotranspiration (ET), and WUE showing an upward trend accounted for 85.85 %, 63.66 %, and 83.88 % of the total area of the country, respectively. Although ET also showed an increasing trend nationwide, the increase of NPP was more obvious; (2) The control experiment showed that WUE showed a significant increase trend in arid and semi-arid areas of Northwest China with the increase of CO2 concentration, while SWC showed a significant drying trend, but both WUE and SWC showed an increasing trend in humid areas. The sensitivity of WUE to SWC was enhanced in arid and semi-arid areas, and the effect of soil drought was partially offset by the increase of WUE; (3) Future climate projections also indicated that the CO2 fertilization effect will contribute to an increase in WUE while causing drier soil moisture conditions in the arid and semi-arid regions. Especially under the SSP5-8.5 scenario, CO2 fertilization in Northwest China contributed more than 14 % to WUE from 2015 to 2060, while the impact on SWC depletion exceeded 3 %. This highlights the potential implications of rising atmospheric CO2 concentration, as it may promote a significant rise in WUE and exacerbate the drying of soil moisture in these areas. These findings emphasize the need for careful attention and consideration in managing water resources in arid and semi-arid regions in the face of future climate change.

Dynamic Response of Surface Water Temperature in Urban Lakes under Different Climate Scenarios-A Case Study in Dianchi Lake, China

Lake surface water temperature is a fundamental metabolic indicator of lake ecosystems that affects the exchange of material and energy in lake ecosystems. Estimating and predicting changes in lake surface water temperature is crucial to lake ecosystem research. This study selected Dianchi Lake, a typical urban lake in China, as the research area and used the Air2water model combined with the Mann-Kendall mutation statistical method to analyze the temporal and spatial variation in the surface water temperature of Dianchi Lake under three climate models. The research results show that, under the RCP 5-8.5 scenario model, the surface water temperature change rate for Dianchi Lake from 2015 to 2100 would be 0.28 ℃/10a, which was the largest change rate among the three selected scenarios. The rate of change during 2015-2100 would be 9.33 times higher than that during the historical period (1900-2014) (0.03 °C/10a). Against the background of Niulan River water diversion and rapid urbanization, the surface water temperature of Dianchi Lake experienced abrupt changes in 1992, 2016, 2017, and 2022. Against the background of urbanization, the impact of human activities on the surface water temperature of urban lakes will become greater.

Quantifying the contributions of climate change and human activities to vegetation dynamic in China based on multiple indices

Distinguishing the respective roles of climate change and anthropogenic activities can provide crucial information for sustainable management of the environment. Here, using the residual trend method (RESTREND), which measures the residue of the actual and potential trends of vegetation, we quantified the relative contributions of human activities (e.g., ecological restoration, overgrazing, and urbanization) and climate change (the warmer and wetter trend) to vegetation dynamics in China during 1988-2018 based on multiple vegetation indices, including the vegetation optical depth (Ku-VOD, C-VOD), normalized difference vegetation index (NDVI), and gross primary productivity (GPP). The results showed that the VOD, NDVI, and GPP exhibited overall increasing trends during 1988-2018. Human activities contributed >70% to the increases in NDVI and GPP in China, whereas a counterbalanced contribution of human activities and climate change was identified for the VOD dynamics (51% vs. 49%). Regions with high contributions from human activities to NDVI, GPP, and VOD were located in northeastern, southern, central, and northwestern China. In northern China, the positive impacts of human activities on NDVI (78%) and BEPS-GPP (83%) were greater than those of climate change. In contrast, human activities contributed 96% to the decrease in Ku-VOD over the same period. Before 2000, climate change promoted increases in GPP and NDVI in most regions of southern China. The increasing rates of GPP and NDVI accelerated after 2000 due to afforestation. However, human activities like overgrazing and urbanization have led to decreases in Ku-VOD in northern and southwestern China, and in C-VOD in northeastern, eastern, central, southwestern, and southern China. In all, the relative roles of climate and human factors varied in different regions when NDVI, GPP, or VOD were individually considered. Our results highlighted that the regional-scale vegetation conditions should be taken into full account to achieve sustainable management of ecosystems.

The Dominant Driving Force of Forest Change in the Yangtze River Basin, China: Climate Variation or Anthropogenic Activities?

Under the combined effect of climate variations and anthropogenic activities, the forest ecosystem in the Yangtze River Basin (YRB) has experienced dramatic changes in recent decades. Quantifying their relative contributions can provide a valuable reference for forest management and ecological sustainability. In this study, we selected net primary productivity (NPP) as an indicator to investigate forest variations. Meanwhile, we established eight scenarios based on the slope coefficients of the potential NPP (PNPP) and actual NPP (ANPP), and human-induced NPP (HNPP) to quantify the contributions of anthropogenic activities and climate variations to forest variations in the YRB from 2000 to 2015. The results revealed that in general, the total forest ANPP increased by 10.42 TgC in the YRB, and forest restoration occurred in 57.25% of the study area during the study period. The forest degradation was mainly observed in the Wujiang River basin, Dongting Lake basin, and Poyang Lake basin. On the whole, the contribution of anthropogenic activities was greater than climate variations on both forest restoration and degradation in the YRB. Their contribution to forest restoration and degradation varied in different tributaries. Among the five forest types, shrubs experienced the most severe degradation during the study period, which should arouse great attention. Ecological restoration programs implemented in YRB have effectively mitigated the adverse effect of climate variations and dominated forest restoration, while rapid urbanization in the mid-lower region has resulted in forest degradation. The forest degradation in Dongting Lake basin and Poyang Lake basin may be ascribed to the absence of the Natural Forest Conservation Program. Therefore, we recommend that the extent of the Natural Forest Conservation Program should expand to cover these two basins. The current research could improve the understanding of the driving mechanism of forest dynamics and promote the effectiveness of ecological restoration programs in the YRB.

Large-scale emergence of regional changes in year-to-year temperature variability by the end of the 21st century

Global warming is expected to not only impact mean temperatures but also temperature variability, substantially altering climate extremes. Here we show that human-caused changes in internal year-to-year temperature variability are expected to emerge from the unforced range by the end of the 21st century across climate model initial-condition large ensembles forced with a strong global warming scenario. Different simulated changes in globally averaged regional temperature variability between models can be explained by a trade-off between strong increases in variability on tropical land and substantial decreases in high latitudes, both shown by most models. This latitudinal pattern of temperature variability change is consistent with loss of sea ice in high latitudes and changes in vegetation cover in the tropics. Instrumental records are broadly in line with this emerging pattern, but have data gaps in key regions. Paleoclimate proxy reconstructions support the simulated magnitude and distribution of temperature variability. Our findings strengthen the need for urgent mitigation to avoid unprecedented changes in temperature variability.

Meteorology and climatology of historical weekly wind and solar power resource droughts over western North America in ERA5

Wind and solar electricity generation is projected to expand substantially over the next several decades due both to rapid cost declines as well as regulation designed to achieve climate targets. With increasing reliance on wind and solar generation, future energy systems may be vulnerable to previously underappreciated synoptic-scale variations characterized by low wind and/or surface solar radiation. Here we use western North America as a case study region to investigate the historical meteorology of weekly-scale “droughts” in potential wind power, potential solar power and their compound occurrence. We also investigate the covariability between wind and solar droughts with potential stresses on energy demand due to temperature deviations away human comfort levels. We find that wind power drought weeks tend to occur in late summer and are characterized by a mid-level atmospheric ridge centered over British Columbia and high sea level pressure on the lee side of the Rockies. Solar power drought weeks tend to occur near winter solstice when the seasonal minimum in incoming solar radiation co-occurs with the tendency for mid-level troughs and low pressure systems over the U.S. southwest. Compound wind and solar power drought weeks consist of the aforementioned synoptic pattern associated with wind droughts occurring near winter solstice when the solar resource is at its seasonal minimum. We find that wind drought weeks are associated with high solar power (and vice versa) both seasonally and in terms of synoptic meteorology, which supports the notion that wind and solar power generation can play complementary roles in a diversified energy portfolio at synoptic spatiotemporal scales over western North America.

Identifying vegetation restoration effectiveness and driving factors on different micro-topographic types of hilly Loess Plateau: From the perspective of ecological resilience

Vegetation restoration is an important way to improve the sustainability of the ecosystem in the hilly Loess Plateau. The variation of vegetation coverage, caused by the combined effects of meteorological factors and human activities, reflects the succession trend of regional ecosystems. Given the complexity and the diversity of landform in the hilly Loess Plateau, vegetation restoration is more affected by topographic factors. Nevertheless, few studies have considered the characteristics and trends of vegetation restoration under different micro-topographic types in the long-time series. From the perspective of ecological resilience based on the fractional vegetation cover (FVC), the trend, the hurst exponent, and the geographical spatial research were used to analyze the variation and future sustainability of vegetation restoration on different micro-topographic types for 20 years. Besides, the spatial autocorrelation, principal component analysis (PCA) and geographically weighted regression (GWR) were applied to identify the driving factors of vegetation restoration. The results showed: (1) the average of the overall regional vegetation coverage was 61.32%, and only 0.95% of the regional vegetation was degraded in the past 20 years. However, in the future, 69.87% of the area would be degraded from improvement, and 0.52% would be significantly decreased; (2) the vegetation coverage in descending order was as follows: ridge area with shady and steep slope, gully area with shady and steep slope, ridge area with sunny and steep slope, gully area with sunny and steep slope, gully area with shady and gentle slope, ridge area with shady and gentle slope, ridge area with sunny and gentle slope, gully area with sunny and gentle slope, valley area; (3) the difference of vegetation degradation among micro-topography was remarkable, and the valley area and gully area with sunny and steep slope have the greatest decrease; (4) the primary factors affecting vegetation restoration in the hilly Loess Plateau were temperature, moisture, soil quality, and social economical condition, and the dominant factors were various under different micro-topographic types and villages. Therefore, it is necessary to adjust ecological engineering measures by comprehensively considering the regional differences among dominant factors of vegetation restoration.

Temperature variation and preterm birth among live singleton deliveries in Shenzhen, China: A time-to-event analysis

OBJECTIVE

Ambient temperature extremes due to heat exposure was an established risk factor for preterm birth (<37 gestational weeks). However, there is insufficient epidemiological evidence on the effects of temperature variation(TV), although TV is also associated with heat exposure and can influence human health risk. This study aimed to investigate the relationship between inter- and intraday TV and preterm birth (PTB).

METHOD

A total of 1,388,994 live singleton births were collected from January 2003 to December 2012, from the Shenzhen Birth registry system. Daily temperature range (DTR) was defined as the difference between the highest and lowest recorded daily temperature. Intraday TV was defined as the maximum daily diurnal temperature range in a given week (Max-DTR). Inter-day TV was defined as the maximum increase or decrease in daily mean temperature between days t and t-1in a given week; either an increase (Temp-inc) or a decrease (Temp-dec). We used Cox proportional hazards models to estimate TV-related PTB risks during the first trimester, the second trimester, and in late pregnancy.

RESULTS

The maximum values for DTR, Temp-inc, and Temp-dec were 17 °C, 8 °C and 11 °C, respectively. The greatest TV-related PTB risk occurred in the second trimester, with 5.8% (95%CI: 3.3%, 8.3%), 23.7% (95%CI: 19.6%, 27.9%), and 4.4% (95%CI: 1.8%, 7.1%) differences per 1 °C increase in Max-DTR, Temp-inc, and Temp-dec, respectively. Greater TV was associated with elevated PTB risk during the warm season. The association between TV and PTB was modified by seasons, maternal education and chronic conditions.

CONCLUSIONS

Sharp TV is a likely risk factor for PTB. Policy makers and clinicians should recognize the potential role of TV in the etiology of PTB so that interventions can be designed to protect pregnant women and their fetuses against extreme temperatures.

More accurate quantification of model-to-model agreement in externally forced climatic responses over the coming century

Separating how model-to-model differences in the forced response (U_MD) and internal variability (U_IV) contribute to the uncertainty in climate projections is important, but challenging. Reducing U_MD increases confidence in projections, while U_IV characterises the range of possible futures that might occur purely by chance. Separating these uncertainties is limited in traditional multi-model ensembles because most models have only a small number of realisations; furthermore, some models are not independent. Here, we use six largely independent single model initial-condition large ensembles to separate the contributions of U_MD and U_IV in projecting 21st-century changes of temperature, precipitation, and their temporal variability under strong forcing (RCP8.5). We provide a method that produces similar results using traditional multi-model archives. While U_MD is larger than U_IV for both temperature and precipitation changes, U_IV is larger than U_MD for the changes in temporal variability of both temperature and precipitation, between 20° and 80° latitude in both hemispheres. Over large regions and for all variables considered here except temporal temperature variability, models agree on the sign of the forced response whereas they disagree widely on the magnitude. Our separation method can readily be extended to other climate variables.

Uncertainty in estimates of future climate arises not only from internal variability, but also from model-to-model differences. Here, the authors use a new set of single model initial-condition large ensembles to quantify the contribution of model differences to the overall uncertainty in temperature and precipitation projections.

Spatiotemporal Variation of Land Surface Temperature and Vegetation in Response to Climate Change Based on NOAA-AVHRR Data over China

The dynamics of land surface temperature (LST) and its correlation with vegetation are crucial to understanding the effects of global climate change. This study intended to retrieve the LST of China, based on the NOAA-AVHRR images, by using a split-window algorithm. The spatiotemporal variation of LST, Normalized difference vegetation index (NDVI), and the correlation between the two was investigated in China from 1982–2016. Moreover, eight scenarios were established to explore the driving forces in vegetation variation. Results indicated that the LST increased by 0.06 °C/year in nearly 81.1% of the study areas. The NDVI with an increasing rate of 0.1%/year and occupied 58.6% of the study areas. By contrast, 41.4% of the study areas with a decreasing rate of 0.7 × 10−3/year, was mainly observed in northern China. The correlation coefficients between NDVI and LST were higher than that between NDVI and precipitation, and the increase in LST could stimulate vegetation growth. Most regions of China have experienced significant warming over the past decades, specifically, desertification happens in northern China, because it is getting drier. The synergy of LST and precipitation is the primary cause of vegetation dynamics. Therefore, long-term monitoring of LST and NDVI is necessary to better understand the adaptation of the terrestrial ecosystem to global climate change.

Quantifying the Impacts of Anthropogenic Activities and Climate Variations on Vegetation Productivity Changes in China from 1985 to 2015

Accurate assessment of vegetation dynamics provides important information for ecosystem management. Anthropogenic activities and climate variations are the major factors that primarily influence vegetation ecosystems. This study investigates the spatiotemporal impacts of climate factors and human activities on vegetation productivity changes in China from 1985 to 2015. Actual net primary productivity (ANPP) is used to reflect vegetation dynamics quantitatively. Climate-induced potential net primary productivity (PNPP) is used as an indicator of climate change, whereas the difference between PNPP and ANPP is considered as an indicator of human activities (HNPP). Overall, 91% of the total vegetation cover area shows declining trends for net primary productivity (NPP), while only 9% shows increasing trends before 2000 (base period). However, after 2000 (restoration period), 78.7% of the total vegetation cover area shows increasing trends, whereas 21.3% of the area shows decreasing trends. Moreover, during the base period, the quantitative contribution of climate change to NPP restoration is 0.21 grams carbon per meter square per year (gC m−2 yr−1) and to degradation is 2.41 gC m−2 yr−1, while during the restoration period, climate change contributes 0.56 and 0.29 gC m−2 yr−1 to NPP restoration and degradation, respectively. Human activities contribute 0.36 and 0.72 gC m−2 yr−1 during the base period, and 0.63 and 0.31 gC m−2 yr−1 during the restoration period to NPP restoration and degradation, respectively. The combined effects of climate and human activities restore 0.65 and 1.11 gC m−2 yr−1, and degrade 2.01 and 0.67 gC m−2 yr−1 during the base and restoration periods, respectively. Climate factors affect vegetation cover more than human activities, while precipitation is found to be more sensitive to NPP change than temperature. Unlike the base period, NPP per unit area increases with an increase in the human footprint pressure during the restoration period. Grassland has more variability than other vegetation classes, and the grassland changes are mainly observed in Tibet, Xinjiang, and Inner Mongolia regions. The results may help policy-makers by providing necessary guidelines for the management of forest, grassland, and agricultural activities.

Past warming trend constrains future warming in CMIP6 models

Future global warming estimates have been similar across past assessments, but several climate models of the latest Sixth Coupled Model Intercomparison Project (CMIP6) simulate much stronger warming, apparently inconsistent with past assessments. Here, we show that projected future warming is correlated with the simulated warming trend during recent decades across CMIP5 and CMIP6 models, enabling us to constrain future warming based on consistency with the observed warming. These findings carry important policy-relevant implications: The observationally constrained CMIP6 median warming in high emissions and ambitious mitigation scenarios is over 16 and 14% lower by 2050 compared to the raw CMIP6 median, respectively, and over 14 and 8% lower by 2090, relative to 1995-2014. Observationally constrained CMIP6 warming is consistent with previous assessments based on CMIP5 models, and in an ambitious mitigation scenario, the likely range is consistent with reaching the Paris Agreement target.

Less sensitive of urban surface to climate variability than rural in Northern China

In this study, the relationships between interannual variations of surface urban heat islands (SUHIs) and climate variability were studied in 31 cities of China for the period 2001-2016. For cold and dry Northern China, it was found that the interannual variations of SUHI intensity (SUHII, land surface temperature (LST) in urban minus rural) in urban cores was significantly (p<0.05) and negatively correlated with rural LST in 9 (in summer days (SDs)) and 8 (in winter days (WDs)) of the 15 northern cities, respectively. In addition, the daytime LST differences between hot summers and other summers and between cold winters and other winters were generally lower in urban cores (1.141°C for SDs and 2.535°C for WDs) than in rural areas (1.890°C for SDs and 3.377°C for WDs). The standard deviation was further used to reflect the interannual stabilities of LST, enhanced vegetation index (EVI) and white sky albedo (WSA). Interestingly, the standard deviations of LST across 2001-2016 were generally lower in urban cores (0.994°C for SDs and 1.577°C for WDs) than in rural areas (1.431°C for SDs and 2.077°C for WDs). Similar results were observed for EVI and WSA (winter). The results suggested that the urban surface is less sensitive to climate variability than rural areas in Northern China. Comparatively, most findings were less evident in hot and humid Southern China. Despite the whole world would become warmer or colder in future, the insensitivity of urban surface may mitigate its impacts in cold and dry Northern China. However, it does not mean that urbanization is totally good due to its environmental problem.

Mortality burden of diurnal temperature range and its temporal changes: A multi-country study

Although diurnal temperature range (DTR) is a key index of climate change, few studies have reported the health burden of DTR and its temporal changes at a multi-country scale. Therefore, we assessed the attributable risk fraction of DTR on mortality and its temporal variations in a multi-country data set. We collected time-series data covering mortality and weather variables from 308 cities in 10 countries from 1972 to 2013. The temporal change in DTR-related mortality was estimated for each city with a time-varying distributed lag model. Estimates for each city were pooled using a multivariate meta-analysis. The results showed that the attributable fraction of total mortality to DTR was 2.5% (95% eCI: 2.3-2.7%) over the entire study period. In all countries, the attributable fraction increased from 2.4% (2.1-2.7%) to 2.7% (2.4-2.9%) between the first and last study years. This study found that DTR has significantly contributed to mortality in all the countries studied, and this attributable fraction has significantly increased over time in the USA, the UK, Spain, and South Korea. Therefore, because the health burden of DTR is not likely to reduce in the near future, countermeasures are needed to alleviate its impact on human health.