Magnitude Of Warming Research Articles

The decline in tropical land carbon sink drives high atmospheric CO2 growth rate in 2023

Abstract Atmospheric CO2 growth rate (CGR), reflecting the carbon balance between anthropogenic emissions and net uptake from land and ocean, largely determines the magnitude and speed of global warming. CGR at Mauna Loa Baseline Observatory reached record high in 2023. Here we quantified major components of global carbon balance for 2023, by developing a framework which integrated fossil fuel CO2 emissions data, an atmospheric inversion from Global ObservatioN-based system for monitoring Greenhouse GAses (GONGGA) with two artificial intelligence (AI) models derived from dynamic global vegetation models. We attributed the record high CGR increase in 2023 compared to 2022 primarily to the large decline in land carbon sink (1803 ± 197 TgC year−1), with minor contributions from a small reduction in ocean carbon sink (184 TgC year−1) and a slight increase in fossil fuel emissions (24 TgC year−1). At least 78% of the global decline in land carbon sink was contributed by the decline in tropical sink, with GONGGA inversion (1354 TgC year−1) and AI simulations (1578 ± 666 TgC year−1) showing similar declines in the tropics. We further linked this tropical decline to the detrimental impact of El Niño-induced anomalous warming and drying on vegetation productivity in water-limited Sahel and southern Africa. Our successful attribution of CGR increase within the framework combining atmospheric inversion with AI simulations enabled near-real-time tracking of the global carbon budget which had a one-year reporting lag.

Temperature sensitivity quandary of soil microbial community structure in Tibetan alpine grasslands: A meta-analysis and field experiment

Soil microorganisms act as the primary decomposers in global terrestrial ecosystems. Whether climate warming will lead to the convergence of the temperature sensitivity of soil microbial community structure and the convergence of the responses of soil microbial community structure to warming remains controversial. This study explored how warming amplitude affected the temperature sensitivity of soil bacteria and fungi community structures, and how it influenced the responses of soil bacteria and fungi community structures to warming on the Qinghai-Tibet Plateau based on meta-analysis and a single-site warming experiment. The temperature sensitivity of soil microbial community structure did not consistently decline with increasing warming magnitude; instead, it even rose, which might be associated with the nonlinear relationships of the warming magnitude with the temperature sensitivity of ecological processes of soil microbial community assembly or the topological parameters of species co-occurrence network. Meta-analysis indicated that responses of soil microbial community to warming were independent of warming amplitude. However, the single-site warming experiment demonstrated that responses of soil microbial community to warming varied with warming amplitude. These inconsistent results might be attributed to distinct spatial scales, grassland types, climatic conditions and warming magnitudes between the single-site experiment and the meta-analysis. Therefore, the temperature sensitivity of soil microbial community and its response to climate warming cannot be simply characterized as monotonically decreasing or increasing in relation to increasing warming magnitude.

Two Perspectives on Amplified Warming over Tropical Land Examined in CMIP6 Models

Abstract Climate change projections show amplified warming associated with dry conditions over tropical land. We compare two perspectives explaining this amplified warming: one based on tropical atmospheric dynamics and the other focusing on soil moisture and surface fluxes. We first compare the full spatiotemporal distribution of changes in key variables in the two perspectives under a quadrupling of CO2 using daily output from the CMIP6 simulations. Both perspectives center around the partitioning of the total energy/energy flux into the temperature and humidity components. We examine the contribution of this temperature/humidity partitioning in the base climate and its change under warming to rising temperatures by deriving a diagnostic linearized perturbation model that relates the magnitude of warming to 1) changes in the total energy/energy flux, 2) the base-climate temperature/humidity partitioning, and 3) changes in the partitioning under warming. We show that the spatiotemporal structure of warming in CMIP6 models is well predicted by the inverse of the base-climate partition factor, which we term the base-climate sensitivity: conditions that are drier in the base climate have a higher base-climate sensitivity and experience more warming. On top of this relationship, changes in the partition factor under intermediate (between wet and dry) surface conditions further enhance or dampen the warming. We discuss the mechanistic link between the two perspectives by illustrating the strong relationships between lower-tropospheric temperature lapse rates, a key variable for the atmospheric perspective, and surface fluxes, a key component of the land surface perspective. Significance Statement Understanding what conditions give rise to the largest magnitude of warming in response to rising CO2 concentrations is not only scientifically important but also critical from a climate impact standpoint. Two main perspectives, one focusing on atmospheric dynamics and the other focusing on land surface processes, have been proposed to explain the stronger warming associated with drier conditions in the tropics. Here, we compare and contrast these two perspectives. We demonstrate that amplified warming in CMIP6 models can largely be predicted from base-climate dryness alone in both perspectives but is further modified based on changes in the partitioning of energy between temperature and moisture. We highlight the spatiotemporal conditions where assumptions in the two perspectives hold and where deviations occur within CMIP6 climate models.

Eocene maar sediments record warming of up to 3.5 °C during a hyperthermal event 47.2 million years ago

Eocene hyperthermal events reflect profound perturbations of the global carbon cycle. Most of our knowledge about their onset, timing, and rates originates from marine records. Hence, the pacing and magnitude of hyperthermal continental warming remains largely unaccounted for due to a lack of high-resolution climate records. Here we use terrestrial biomarkers and carbon isotopes retrieved from varved lake deposits of the UNESCO World Heritage site ‘Messel Fossil Pit’ (Germany) to quantify sub-millennial to millennial-scale temperature and carbon isotope changes across hyperthermal event C21n-H1 (47.2 million years ago). Our results show maximum warming of ca. 3.5 °C during C21n-H1. We propose that two components are responsible for the warming pattern across the hyperthermal: (1) the massive release of greenhouse gases into the atmosphere-ocean system and (2) half-precession orbital forcing indicated by ~12.000-year temperature cycles. The carbon isotope record of bulk organic matter indicates a sharp, 7‰ decrease at the peak of the hyperthermal, corresponding to increased organic carbon content and a shift in the lake algal community. Collectively, our proxy data reveal the structure of continental temperature response during the hyperthermal event that is characterized by overall warming with a superimposed pattern of sub-orbital scale temperature fluctuations.

Projected rapid response of stratospheric temperature to stringent climate mitigation

Deep, rapid and sustained reductions in greenhouse gas emissions are required to meet the 2015 Paris Agreement climate target. If the world strengthens efforts toward near-term decarbonisation and undertakes major societal transformation, this will be met with requests from policymakers and the public for evidence that our actions are working and there are demonstrable effects on the climate system. Global surface temperature exhibits large internal variability on interannual to decadal timescales, meaning a reduction in the magnitude of surface warming would not be robustly attributable to climate mitigation for some time. In contrast, global stratospheric temperature trends have much higher signal-to-noise ratios and could offer an early indication of the effects of climate mitigation. Here we examine projected near-term global temperature trends at the surface and in the stratosphere using large ensemble climate models following three future emission scenarios. Under rapid, deep emission cuts following SSP1–1.9, modelled middle and upper stratospheric cooling trends show a detectable weakening within 5 years compared to a scenario approximately representing current climate commitments (SSP2–4.5). Therefore, stratospheric temperature trends could serve as an early indicator to policymakers and the public that climate mitigation is taking effect.

Constraining future surface air temperature change on the Tibetan Plateau

Abstract The rapid warming of the Tibetan Plateau (TP) in recent decades has led to severe consequences, including the melting of glaciers and snow cover, which further accelerates warming. Accurately projecting the magnitude of future warming is crucial for effective climate change adaptation. However, the projection of future temperature change is model dependent. In this study, we demonstrate a significant correlation between the historical intermodel warming trend and future temperature change, suggesting this relationship could be used to calibrate the best estimate of projections and reduce the uncertainty by observations. For a high emission scenario, the constraint helps to narrow down the uncertainty range of annual and summer temperature change on the western TP by up to 2 °C and 4 °C, respectively, in the end of this century. The most substantial calibrated increase of future change is in winter up to 2 °C, followed by autumn with an increase of up to about 1 °C. Discrepancies of historical warming trend among different observation datasets expose the largest impact on the constrained best estimate compared with emergent relationship derived from different climate models and historical periods.

Excessive climate warming exacerbates nitrogen limitation on microbial metabolism in an alpine meadow of the Tibetan Plateau: Evidence from soil ecoenzymatic stoichiometry

Soil ecoenzymatic stoichiometry reflects the dynamic equilibrium between microorganism's nutrient requirements and resource availability. However, uncertainties persist regarding the key determinants of nutrient restriction in relation to microbial metabolism under varying degrees of warming. Our long-term and multi-level warming field experiment (control treatment, +0.42 °C, +1.50 °C, +2.55 °C) in a typical alpine meadow unveiled a decline in carbon (C)- and nitrogen (N)-acquired enzymes with escalating warming magnitudes, while phosphorus (P)-acquired enzymes displayed an opposite trend. Employing enzymatic stoichiometry modeling, we assessed the nutrient limitations of microbial metabolic activity and found that C and N co-limited microbial metabolic activities in the alpine meadow. Remarkably, high-level warming (+2.55 °C) exacerbated microbe N limitation, but alleviate C limitations. The structural equation modeling further indicated that alterations in soil extracellular enzyme characteristics (SES) were more effectively elucidated by microbial characteristics (microbial biomass C, N, P, and their ratios) rather than by soil nutrients (total nutrient contents and their ratios). However, the microbial control over SES diminished with higher levels of warming magnitude. Overall, our results provided novel evidence that the factors driving microbe metabolic limitation may vary with the degree of warming in Tibet alpine grasslands. Changes in nutrient demand for microorganism's metabolism in response to warming should be considered to improve nutrient management in adapting to different future warming scenarios.

Anthropogenic influence on altitudinally amplified temperature change in the Tibetan Plateau

As the highest plateau on the Earth, the Tibetan Plateau (TP) has experienced rapid warming in the last decades, affecting natural ecosystem and water resources extending far beyond the plateau itself. A distinctive characteristic known as elevation-dependent warming (EDW) in the high mountain regions was particularly pronounced in the TP, whereby the magnitude of temperature warming was amplified with increasing altitudes. Different mechanisms have been proposed to explain this phenomenon, however, the link between the root cause of warming, human activities, and the EDW remains poorly understood. Here we used the homogenized observation and simulations by the newest climate models to discern human influence on both mean and extreme temperatures within the region. An optimal fingerprinting method was applied in a vertical space rather than in traditional horizontal space. We found that the long-term trends in mean and extreme temperature amplified with increasing elevation, with larger magnitude of trends at higher elevations. The response to external forcing, primarily driven by human activities, was robustly detected in altitudinal amplification of temperature increase, providing clear evidence of human causes of EDW. As warming increases, the EDW in the region will continue, with more pronounced EDW corresponding to larger magnitude of warming under a high emission scenario. These findings mark the first evidence of human influence on temperature across different vertical altitudes of climate system.

Sea Ice Loss, Water Vapor Increases, and Their Interactions with Atmospheric Energy Transport in Driving Seasonal Polar Amplification

Abstract The ice–albedo feedback associated with sea ice loss contributes to polar amplification, while the water vapor feedback contributes to tropical amplification of surface warming. However, these feedbacks are not independent of atmospheric energy transport, raising the possibility of complex interactions that may obscure the drivers of polar amplification, in particular its manifestation across the seasonal cycle. Here, we apply a radiative transfer hierarchy to an idealized aquaplanet global climate model coupled to a thermodynamic sea ice model. The climate responses and radiative feedbacks are decomposed into the contributions from sea ice loss, including both retreat and thinning, and the radiative effect of water vapor changes. We find that summer sea ice retreat causes winter polar amplification through ocean heat uptake and release, and the resulting decrease in dry energy transport weakens the magnitude of warming. Moreover, sea ice thinning is found to suppress summer warming and enhance winter warming, additionally contributing to winter amplification. The water vapor radiative effect produces seasonally symmetric polar warming via offsetting effects: enhanced moisture in the summer hemisphere induces the summer water vapor feedback and simultaneously strengthens the winter latent energy transport in the winter hemisphere by increasing the meridional moisture gradient. These results reveal the importance of changes in atmospheric energy transport induced by sea ice retreat and increased water vapor to seasonal polar amplification, elucidating the interactions among these physical processes.

Statistical Analysis for the Detection of Change Points and the Evaluation of Monthly Mean Temperature Trends of the Moulouya Basin (Morocco)

This study examines the spatiotemporal variability of mean monthly temperature in the Moulouya watershed of northeastern Morocco, highlighting associated trends. To this end, statistical methods widely recommended by climate researchers were adopted. We used monthly mean temperature data for the period 1980–2020 from 9 measuring stations belonging to the Moulouya Watershed Agency (ABHM). These stations were rigorously selected, taking into account their reliability, the length of their records, and their geographical position in the basin. In addition, a quality test and homogenization of the temperature series were carried out using the Climatol tool. The results obtained show a significant upward trend in mean monthly temperature, mainly pronounced during the summer months, in the Moulouya watershed. In fact, Z values generally exceeded the 0.05 significance level at all stations during April, May, June, July, August, and October. According to the results of Sen’s slope test, mean monthly temperatures show an annual increase ranging from 0 to 0.13°C. The maximum magnitude of warming is recorded in July, specifically at Oujda Station. On an overall watershed scale, May, August, and July show a rapid warming trend, with average rates of 0.093, 0.086, and 0.08°C per year, respectively. By contrast, the series for the other months show no significant trend. Significant trend change points were also identified at watershed and station scales, mainly around 2000, primarily for accelerated warming of the summer months.

Dynamical Downscaling of Daily Extreme Temperatures over China Using PRECIS Model

As global warming intensifies and the frequency of extreme weather events rises, posing a major threat to the world’s economy and sustainable development, accurate forecasting of future extreme events is of great significance to mankind’s response to extreme weather events and to the sustainable development of society. Global Climate Models (GCMs) have limitations in their applicability at regional scales due to their coarse resolution. Utilizing dynamical downscaling methods based on regional climate models (RCMs) is an essential approach to obtaining high-resolution climate simulation information in future. This study represents an attempt to extend the use of the Providing REgional Climates for Impacts Studies (PRECIS) regional climate model by employing the BCC-CSM2-MR model from the Beijing Climate Center to drive it, conducting downscaling experiments over China at a spatial resolution of 0.22° (25 km). The simulation and prediction of daily maximum and minimum temperatures across the China region are conducted, marking a significant effort to expand the usage of PRECIS with data from alternative GCMs. The results indicate that PRECIS performs well in simulating the daily maximum and minimum temperatures over the China region, accurately capturing their spatial distribution and demonstrating notable simulation capabilities for both cold and warm regions. In the annual cycle, the simulation performance of PRECIS is superior to its driving GCM, particularly during cold months (i.e., December and from January to May). Regarding future changes, the daily extreme temperatures in most regions are projected to increase gradually over time. In the early 21st century, the warming magnitude is approximately 1.5 °C, reaching around 3 °C by the end of the century, with even higher warming magnitudes exceeding 4.5 °C under the SSP585 scenario. Northern regions will experience greater warming magnitudes than southern regions, suggesting faster increases in extreme temperatures in higher latitudes. This paper provides forecasts of extreme temperatures in China, which will be useful for studying extreme events and for the government to make decisions in response to extreme events.

Relative Impacts of Sea Ice Loss and Atmospheric Internal Variability on the Winter Arctic to East Asian Surface Air Temperature Based on Large-Ensemble Simulations with NorESM2

To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia” (WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day (or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day (or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four (ten) times larger than the ice-induced East Asian cooling in the present-day (future) experiment; the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60% (80%) to the Arctic winter warming in the present-day (future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-loss-induced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.

Diurnal warming rectification in the tropical Pacific linked to sea surface temperature front

Sharp and rapid changes in the sea surface temperature (SST) associated with fronts and the diurnal cycle can drive changes in the atmospheric boundary-layer stability and circulation. Here we show how a one-dimensional surface ocean model forced with either high-resolution or daily averaged surface fluxes can be used to distinguish diurnal versus frontal SST anomalies observed from an uncrewed surface vehicle. The model, forced with daily satellite fluxes, shows that the diurnal warming is largest within the equatorial Pacific cold tongue of SST. The strong persistent SST front north of the cold tongue is evident in both the oceanic and atmospheric boundary-layer stability scales and, as a consequence, in the magnitude of the diurnal ocean warming. Using SST, barometric pressure and surface wind measurements from moorings at 0°, 95° W and 2° N, 95° W, we show that the front in the SST diurnal warming results in a weakened SST front in the afternoon and a corresponding reduced meridional gradient in the barometric pressure that appears to contribute to a diurnal pulsing of the surface meridional winds. To the extent that these modulate the surface branch of the Hadley cell, these diurnal variations may have remote impacts.

Changes in glacier surface temperature across the Third Pole from 2000 to 2021

Glacier surface temperature is not only an important indicator of climate change, but is also directly related to glacier physical processes and mass balance. Glaciers over the Third Pole have shown heterogeneous but accelerated mass loss over the past two decades. However, few studies have focused on changes of glacier surface temperature in this region. In this study, we investigate this change from 2000 to 2021 using an altitudinal area-weighting method based on Landsat surface temperature products. The results show that this method can robustly derive inter-annual variability and long-term trends of subregional glacier surface temperature. Over the entire Third Pole, glacier surfaces exhibited warming at the rate of +0.17 ± 0.35 °C dec−1 (p = 0.32). The warming had a distinct seasonal pattern: warming in autumn (+0.50 ± 0.53 °C dec−1, p = 0.06) but cooling in spring (−0.22 ± 0.36 °C dec−1, p = 0.23). Correspondingly, the ablation season 0 °C isotherm altitude has risen >100 m and the glacier area with GST ≥0 °C has expanded by 10%. Moreover, the GST changes displayed large spatial heterogeneity. In the westerlies-dominated regions (e.g., Karakoram and Kun Lun), glacier surfaces showed slight warming or even cooling on average (from −0.10 to +0.06 °C dec−1), while in the monsoon-dominated regions (e.g., East Himalaya, Southeast Tibetan Plateau and Hengduan Mountains), strong warming was observed (> +0.50 °C dec−1, p < 0.05). Glacier surfaces generally showed a faster warming at north slopes than south slopes, especially in the ablation season. These results emphasize that different magnitudes of glacier surface warming are important indicators for the contrasting glacier changes over the Third Pole. The method presented here opens the way to investigate long-term surface temperature change of global mountain glaciers, which can help us further understand the mechanisms of glacier response to global climate change.

Effects of global warming on drought onset in China

This study investigated the effects of warming on the drought onset in China using meteorological data and soil moisture data from 1980 to 2020. The variation characteristics of drought onset time and onset speed were analyzed systematically. The differences in drought onset time and onset speed during the period 1995–2020 and the period 1980–1994 were compared, and possible impact factors were analyzed. Results indicated that the spatial distribution of drought onset time decreased with an increase in regional wetness in China. In arid regions, onset time at 73 % of sites was over 35 days, and about 13 % was among 60–90 days. In semi-arid and sub-humid regions, the onset time was 25–40 days, and in humid regions, it was 20–30 days. After 1994, namely the significant temperature rise period, the onset time has remarkably shortened in parts of the southern Northeast, North China, the eastern Northwest, the western Southwest, the middle of Tibet, the lower reaches of the Yangtze River, and the coastal region of South China. The shortening was most obvious in sub-humid regions. The greater the warming magnitude, the wetter the region, the faster the drought onset speed. Drought onset speed (γ) was higher in the southern humid region than that in the northern region, and γ for southern Northeast China, northern North China, and eastern Northwest China was higher than that for the rest of North China. After 1994, drought onset speed was accelerated in most regions, especially in the semi-arid and sub-humid regions with precipitation in the range of 300–600 mm. Under the combined effect of increased evapotranspiration and reduced precipitation, the region has been the hot spot with increased drought speed after obvious warming in China.

A Simple Relationship Between the Magnitude and Spatial Extent of Global Surface Temperature Anomalies

AbstractPreparing for climate change requires an understanding of the degree to which global warming has regional implications. Here we document a strong relationship between the magnitude and extent of warming and explain its origin using a simple model based on binomial statistics. Applied to HadCRUT5 instrumental observations, the model shows that 96% of interannual variability in the proportion of regions experiencing anomalous warmth over the last century can be explained on the basis of the magnitude of global mean surface temperature (GMST) anomalies. The model performs similarly well when applied to a variety of unforced and forced model simulations and represents a general thermodynamic link between global and local warming on annual timescales. Our model predicts that, independent of the baseline that is chosen, 95% of the globe is expected to experience above‐average annual temperatures at 0.7°C of GMST warming, and 99% at 1.0°C of warming.

Characteristics of flash droughts and their association with compound meteorological extremes in China: Observations and model simulations

Flash droughts have gained considerable public attention due to the imminent threats they pose to food security, ecological safety, and human health. Currently, there has been little research exploring the projected changes in flash droughts and their association with compound meteorological extremes (CMEs). In this study, we applied the pentad-mean water deficit index to investigate the characteristics of flash droughts and their association with CMEs based on observational data and downscaled model simulations. Our analysis reveals an increasing trend in flash drought frequency in China based on historical observations and model simulations. Specifically, the proportion of flash drought frequency with a one-pentad onset time showed a consistent upward trend, with the southern parts of China experiencing a high average proportion during the historical period. Furthermore, the onset dates of the first (last) flash droughts during year are projected to shift earlier (later) in a warmer world. Flash droughts become significantly more frequent in the future, with a growth rate approximately 1.3 times higher in the high emission scenario than in the medium emission scenario. The frequency of flash droughts with a one-pentad onset time also exhibits a significant upward trend, indicating that flash droughts will occur more rapidly in the future. CMEs in southern regions of China were found to be more likely to trigger flash droughts in the historical period. The probability of CMEs triggering flash droughts is expected to increase with the magnitude of warming, particularly in the far-future under the high emissions scenario.

Inferring Northern Hemisphere Continental Warming Patterns from the Amplitude and Phase of the Seasonal Cycle in Surface Temperature

Abstract The seasonal cycle in temperature is a large and well-observed response to radiative forcing, suggesting its potential as a natural analog to human-caused climate change. Although there have been advances constraining some climate feedback parameters using seasonal observations, the seasonal cycle has not been used to inform about the local temperature sensitivity to greenhouse gas forcing. In this study, we uncover a nonlinear relationship between the amplitude and phase of the seasonal cycle and forced temperature trends in seven CMIP5-era large ensembles across the Northern Hemisphere extratropical continents. We develop a mixture energy balance model that reproduces this relationship and reveals the unexpected finding that the phasing of the seasonal cycle—in addition to the amplitude—contains information about local temperature sensitivity to seasonal forcing over land. Using this energy balance model framework, we compare the pattern and magnitude of the seasonally inferred sensitivity of the surface temperature response to anthropogenic radiative forcing. The seasonally constrained model largely reproduces the pattern of human-caused temperature trends seen in climate models (r = 0.81, p value &lt; 0.01), including polar amplification, but the magnitude of the response is smaller by about a factor of 3. Our results show the relevance of both phasing and amplitude for constraining patterns of local feedbacks and suggest the utility of additional research to better understand the differences in sensitivity between seasonal and greenhouse gas forcing. Significance Statement Warming in response to increased greenhouse gases is not spatially uniform across land. We wanted to understand whether the familiar seasonal cycle in temperature could provide information about climate change. We found that climate models show a strong link between the seasonal cycle and future warming: places with a larger and more delayed temperature response to the seasonal cycle in solar forcing tend to warm more across the Northern Hemisphere midlatitudes. A very simple model for the climate system, whose parameters are based on the seasonal cycle, captures the pattern but not the magnitude of warming. Our findings suggest that there are some similarities between the processes that control temperature change on seasonal and climate change time scales, but that we must understand the difference between seasonal and longer-term sensitivity to warming before the seasonal cycle can be used to reduce uncertainty about climate change.

Responses of CO2 and CH4 in the alpine wetlands of the Tibetan Plateau to warming and nitrogen and phosphorus additions.

Wetland ecosystems store large amounts of carbon, and CO2 and CH4 fluxes from this ecosystem receive the double impact of climate change and human activities. Nonetheless, research on how multi-gradient warming and nitrogen and phosphorus additions affect these wetland greenhouse gas emissions is still limited, particularly in alpine wetland ecosystems. Therefore, we conducted a field experiment on the Tibetan Plateau wetlands, investigating the effects of warming and nitrogen and phosphorus additions on the CO2 and CH4 fluxes in alpine wetlands. Results indicated that warming enhanced the CO2 absorption and CH4 emission in the alpine meadow ecosystem, possibly related to changes in plant growth and microbial activity induced by warming, while we noticed that the promotion of CO2 uptake weakened with the increase in the magnitude of warming, suggesting that there may be a temperature threshold beyond which the ecosystem's capacity for carbon sequestration may be reduced. Nitrogen addition increased CH4 emission, with the effect on CO2 absorption shifting from inhibition to enhancement as the amount of applied nitrogen or phosphorus increased. The interaction between warming and nitrogen and phosphorus additions further influenced CH4 emission, exhibiting a synergistic enhancement effect. This study deepens our understanding of the greenhouse gas responses of alpine wetland ecosystems to warming and nitrogen and phosphorus additions, which is significant for predicting and managing ecosystem carbon balance under global change.

Assessing the impact of climate warming on tree species composition and distribution in the forest region of Northeast China.

Global climate change has markedly influenced the structure and distribution of mid-high-latitude forests. In the forest region of Northeast China, the magnitude of climate warming surpasses the global average, which presents immense challenges to the survival and habitat sustainability of dominant tree species. We predicted the potential changes in aboveground biomass, dominant tree species composition, and distribution in the forest region of Northeast China over the next century under different climatic conditions encompassing the current scenario and future scenarios (RCP2.6, RCP4.5, and RCP8.5). Forest ecosystem process model LINKAGES 3.0 was used to simulate dynamic changes in species-level aboveground biomass under four climate scenarios at the homogeneous land-type unit level. The potential spatial distribution of tree species was investigated based on three indicators: extinction, colonization, and persistence. The results showed that LINKAGES 3.0 model effectively simulated the aboveground biomass of 17 dominant tree species in the forest region of Northeast China, achieving a high accuracy with R² = 0.88. Under the current, RCP2.6, and RCP4.5 climate scenarios, the dominant tree species presented gradual increases in aboveground biomass, whereas under RCP8.5, an initial increase and subsequent decline were observed. With increasing warming magnitude, cold-temperate coniferous tree species will gradually be replaced by other temperate broad-leaved tree species. Furthermore, a large temperature increase under RCP8.5 will likely produce a significant contraction in the potential distribution range of tree species like Larch, Scotch pine, Ribbed birch, Spruce and Fir, while most temperate broad-leaved tree species and Korean pine are expected to demonstrate a northward migration. These findings provide guidance for enhancing the adaptability and resilience of forest ecosystems in middle and high latitudes and addressing the threats posed by climate warming.