Future Climate Warming Research Articles

Seasonal prediction of midsummer compound heat-humidity events over Southeast China

In recent years, there has been an increasing occurrence of compound heat-humidity (HH) events worldwide, leading to excessive morbidity and mortality. Southeast China has been particularly affected by HH events over the past decade. However, the seasonal prediction of HH events in Southeast China remains a considerable challenge. Based on the year-to-year increment (DY) approach and the empirical orthogonal function analysis, a robust prediction model is developed in this study for the midsummer HH events in Southeast China during 1981–2022. Three prediction models are individually constructed for the first three principal components (PCs) of the DY for HH events (hereafter referred to as HH_DY). The correlation coefficients (CCs) between the predicted and observed PCs exceed 0.75 in the cross-validation test for 1981–2022 and 0.80 in independent hindcasts for 2013–2022. The predicted graphical maps of HH_DY are reconstructed by the projecting the fitted three PCs onto the observed first three empirical orthogonal function modes, and the geographical patterns of HH events are obtained by adding the simulated HH_DY to the observed HH events for the preceding year. In the cross-validation test, the spatial features of the predicted HH events are highly accordant with those of the observations in nine extreme compound HH years, with area CC values ranging from 0.89 to 0.95. In the independent hindcasts for the past decade, the area CC values exceed 0.76 in all years and are >0.80 in eight years. Moreover, the predicted high-incidence areas of HH events are highly consistent with the observations in both the cross-validation test and independent hindcasts. The reliable prediction for geographical distributions of HH events in Southeast China is of great significance for human adaptation to future climate warming.

Experimental Warming Reduces the Grain Yield and Nitrogen Utilization Efficiency of Double-Cropping indica Rice in South China

The effect of climate warming on rice production in China is profound, yet there has been limited research on how it affects the grain yield, nitrogen (N) uptake, and N utilization efficiency (NUtE) of the double-cropping indica rice in South China. To address this gap, we conducted a free air temperature increase (FATI) experiment in Guangdong province during 2020 and 2021. Our findings revealed that warming led to a significant reduction in grain yield, with early rice (ER) and late rice (LR) experiencing average decreases of 5.2% and 6.3%, respectively, compared to control treatments. This decline was primarily attributed to the reduced grain weight of ER and the fewer spikelet numbers per panicle of LR under warming conditions. Although the dry matter translocation, harvest index, and N translocation efficiency of ER remained unchanged under warming conditions, these of LR decreased by an average of 58.1%, 8.8%, and 22.3%, respectively. Additionally, while warming did not affect the N uptake in ER at maturity, it significantly increased the N uptake in LR by an average of 11.0%. Therefore, under warming conditions, the NUtE of both ER and LR was markedly decreased by 6.9% and 15.5% over the two years. These results indicate that climate warming may have significant negative impacts on the grain yield and the NUtE of indica rice within double-rice cropping systems in South China. Understanding these dynamics is vital for maintaining the stability of rice yields in anticipation of future climate warming.

The impact of spongy moth (Lymantria dispar dispar) defoliation on carbon balance of a temperate deciduous forest in North America

Temperate deciduous forests are an important contributor to the global carbon (C) sink. However, changes in environmental conditions and natural disturbances such as insect infestations can impact carbon sequestration capabilities of these forests. While, insect infestations are expected to increase in warmer future climates, there is a lack of knowledge on the quantitative impact of these natural disturbances on the carbon balance of temperate deciduous forests. In 2021, a record-breaking defoliation, caused by the spongy moth (Lymantria dispar dispar (LDD), formerly knows as the gypsy moth) occurred in eastern North America. In this study, we assess the impact of this spongy moth defoliation on carbon uptake in a mature oak-dominated temperate forest in the Great Lakes region in Canada, using eddy covariance flux data from 2012 to 2022. Study results showed that the forest was a large C sink with mean annual net ecosystem productivity (NEP) of 207 ± 77 g C m–2 yr−1 from 2012 to 2022, excluding 2021, which experienced the infestation. Over this period mean annual gross ecosystem productivity (GEP) was 1,398 ± 137 g C m–2 yr−1, while ecosystem respiration (RE) was 1,209 ± 139 g C m–2 yr−1. However, in 2021 due to defoliation in the early growing season, annual GEP of the forest declined to 959 g C m–2 yr−1, while annual RE increased to 1,345 g C m–2 yr−1 causing the forest to become a large source of C with annual NEP of -351 g C m–2 yr−1. The forest showed a rapid recovery from this major disturbance event, with annual GEP, RE, and NEP values of 1,671, 1,287, and 298 g C m–2 yr−1, respectively in 2022 indicating that the forest was once again a large C sink. This study demonstrates that major transient natural disturbances under changing climate can have a significant impact on forest C dynamics. The extent to which North American temperate forests will remain a major C sink will depend on the severity and intensity of these disturbance events and the rate of recovery of forests following disturbances. Lay abstractTemperate deciduous forests play an important role in carbon sequestration from the atmosphere. However, the impact of climate change, extreme weather, and disturbance events can alter the extent to which these forests sequester carbon, in some cases shifting their role from being a carbon sink to becoming a carbon source to the atmosphere. In 2021, a spongy moth infestation severely defoliated a mature oak-dominated temperate forest north of Lake Erie, Ontario, Canada, turning the forest from a 10-year mean carbon sink of about 2 tons of carbon per hectare to a carbon source of about 3.5 tons of carbon per hectare. Our analysis indicates that meteorological conditions during the early growing season might have influenced the severity of this infestation. Specifically, the prevalence of dry and warm weather conditions enabled the moth to survive and thrive longer. This study shows the significant influence of natural disturbances on forest carbon dynamics as temperatures continue to rise due to climate change. The future role forests play in carbon sequestration will be determined by the severity of disturbance events and the effectiveness of forests to recover in the aftermath of these events.

Holocene hydroclimate variability of the Baltic region inferred from stable isotopes, d-excess and multi-proxy data at lake Nuudsaku, Estonia (NE Europe)

Long-term hydroclimate records provide an opportunity to understand potential drivers of the past, and give context to modern and future climate warming. A wide variety of proxy data now allow for reconstruction of climate variables that were not previously possible. Here we present a multi-proxy dataset including n-alkane δ2H (δ2Hn-alk) values from an open-basin lake in Estonia to reconstruct past hydroclimate conditions for the eastern Baltic region. We complement our sedimentary δ2Hn-alk data with existing carbonate-based oxygen stable isotope (δ18O) data to derive deuterium (d-) excess. We present multiple isotopic records and reconstructed relative humidity (ΔRH) values over the Holocene, and link these with modern precipitation δ2H and δ18O values to guide the interpretation of the paleo-proxies. Fossil pollen and chironomid-based temperature reconstructions, as well as biogeochemical data provide additional information for inferring past environmental changes. Our results indicate that the middle Holocene in Estonia had on average 6 ± 3% higher RH values than the late Holocene. The δ18O and δ2H values were also higher during the middle Holocene, which we interpret as increased warm season precipitation. Our reconstructed d-excess values were relatively higher during the middle Holocene, indicating a more northerly or cold source water origin, in comparison to the late Holocene. In addition to the paleoclimatic significance, our results show how multiple quantitative proxies can be combined to characterize hydroclimate sensitivity to changes in relative humidity, temperature and moisture source.

Amplification of the discrepancy between simplified and physics-based wet-bulb globe temperatures in a warmer climate

The Simplified Wet Bulb Globe Temperature (sWBGT) is widely used in heat stress assessments for climate-change studies, but its limitations have not been thoroughly explored. Building on recent critiques of sWBGT's use for current climate on global scale, this study examines sWBGT's biases using dynamically-downscaled sub-daily climate projections under multiple future emission scenarios. The analysis is aimed at understanding caveats in the application of sWBGT and the uncertainties in existing climate change analysis dependent on sWBGT. Results indicate sWBGT's biases are heavily influenced by local near-surface air temperature, with overestimation of heat stress in East Asia regions, particularly hot and humid areas, due to static assumptions of radiation and wind speed. This overestimation is amplified in warmer climates, leading to exaggerated projected heat stress increases in future. In contrast, underestimations are found for heat stress levels attributed to low wind speeds and strong radiations, such as over the Tibetan Plateau and certain extreme events. Additionally, sWBGT underestimates variability in extreme heatwave events compared to WBGT in both current and future climates, irrespective of overestimation in absolute heatwave intensities. This study emphasizes the limitations of sWBGT, especially in future warmer climates. Importance of sub-daily data for capturing daily maximum heat stress level and reflecting diurnal variations in different components is also discussed. In conclusion, we recommend using Liljegren's model (i.e., physics-based calculation) with high-resolution sub-daily climate data for more accurate outdoor heat stress assessments in climate change studies.

Influence of forest age, tree size, and climate factors on biomass and carbon storage allocation in Chinese fir forests

Biomass and carbon allocation among plant organs are influenced by the individual tree's development and climate conditions. Chinese fir forests play an important role in the carbon cycle and climate change mitigation in China. Understanding how forest age, tree size, and climate factors affect biomass and carbon allocation in Chinese fir forests is crucial to fully utilize the carbon sequestration potential. We analyzed the response of Chinese fir biomass allocation fractions (BAFs) and carbon stock allocation fractions (CAFs) to forest age, tree size, and climate factors, utilizing field survey data on biomass of 93 trees in Fujian, Sichuan, Guangxi, and Jiangxi provinces and carbon storage of 40 trees in Fujian, Sichuan, and Guangxi provinces in China. Our results showed that BAFs depend on individual development. In young and middle-aged forests, BAFs were unaffected by diameter at breast height (DBH), whereas branch and root biomass fractions displayed a significant positive correlation with DBH, and stem biomass fraction displayed a negative correlation with DBH in mature forests. Carbon concentration exhibited substantial variation among distinct components and regions. Overall, the carbon concentration of each organ ranked as Guangxi > Sichuan > Fujian. BAFs of dominant trees are almost independent of climatic factors, while suppressed trees will alter their strategies for biomass allocation in response to climate change. Stem biomass fraction exhibited a significant positive correlation with maximum growing season temperature, mean summer temperature, and maximum summer temperature, whereas leaf biomass fraction showed the opposite trend. Under future climate warming, Chinese fir will allocate more biomass to the stem, at the expense of leaf biomass. These findings support the idea that biomass allocation patterns serve as adaptive patterns to address fluctuations in internal and external conditions. The interaction between climate factors and tree size shows promise for predicting trends in forest biomass and carbon accumulation in the context of future climate change.

Research progress on cambium activity and radial growth dynamics monitoring of coniferous species

The radial growth of trees plays a crucial role in determining forest carbon sequestration capacity. Understanding the growth dynamics of trees and their response to environmental factors is essential for predicting forest's carbon sink potential under future climate change. Coniferous forest trees are particularly sensitive to climate change, with growth dynamics responding rapidly to environmental shifts. We collected and analyzed data from 99 papers published between 1975 and 2023, and examined the effects of exogenous factors (such as temperature, water, and photoperiod) and endogenous factors (including tree age and species) on cambial activity and radial growth in conifers. We further explored the mechanisms underlying these effects. The results showed that climate warming had the potential to advance the onset while delayed the end of xylem differentiation stages in conifers in temperate and boreal regions. Water availability played a crucial role in regulating the timing of cambial phenology and wood formation by influencing water potential and cell turgor. Additionally, the photoperiod not only participated in regulating the start and end times of growth, but also influenced the timing of maximum growth rate occurrence. Future climate warming was expected to extend the growing season, leading to increase in growth of conifers in boreal regions and expanding forests to higher altitudes or latitudes. However, changes in precipitation patterns and increased evapotranspiration resulting from temperature increases might advance the end of growing season and reduce growth rate in arid areas. To gain a more comprehensive understanding of the relationship between radial growth and climatic factors, it is necessary to develop process-based models to elucidate the physiological mechanisms underlying wood formation and the response of trees to climatic factors.

Using wood rings to determine age and climate constraints of grapevine (Vitis vinifera) radial growth

Summary Grapevine (Vitis vinifera) is the most widely cultivated and economically relevant crop in the world, but its productivity is menaced by aridification in some wine-growing regions such as the Mediterranean Basin. The impacts of climate on vines depend on regional conditions, cultivar, and vine age, among other factors. Hence, a better understanding of vine radial-growth responses to climate in different regions is sorely needed. First, we related climate data and drought severity with a long-term series of vine leaf unfolding from NE Spain to test if climate warming is advancing the onset of the growing season. Second, we used growth rings to estimate age and quantify climate-growth relationships of vines using dendrochronology. Three sites from different designations of origin and vine varieties were studied: Logroño in northern Spain (La Rioja, Tempranillo), San Martín del Río in northeast Spain (Calatayud, Garnacha) and Anzi in southern Italy (Aglianico, Aleatico). Vine leaf unfolding occurred earlier as winter-spring conditions were warmer and drier. Vine ages ranged between 16 (Logroño, Anzi) and 56 years (S. Martín del Río), and growth rates declined in the two youngest grapevines. Ring widths varied between 1.19 (S. Martín del Río) and 1.80 mm (Logroño), with Anzi showing intermediate values (1.37 mm). February precipitation enhanced vine growth in San Martín del Río () and Anzi (), whereas the correlation with soil moisture peaked in March in San Martín del Río (). Vine growth rates positively responded to September minimum temperatures in San Martín del Río () and Logroño (). Garnacha cultivar in San Martín del Río showed the highest responsiveness to water availability. Therefore, similar old grapevines from continental, seasonally dry areas could be the most negatively affected by future warmer and drier climate conditions.

Climate warming effects in stratified reservoirs: Thorough assessment for opportunities and limits of machine learning techniques versus process-based models in thermal structure projections

It is nowadays a hot topic to apply machine learning (ML) algorithms to illustrate water temperature dynamics in lentic waters. Due to the limited amount of in-situ temperature measurements from traditional sampling programmes, most of the related studies, however, restricted their analysis within the surface and rarely checked the results for whole depth profiles. Moreover, capability of such methods in projecting thermal dynamics under future climate conditions is even less illustrated. To fill the gap, we collected an unparalleled huge database including 9 million water temperature measurements, from 2013 to 2022, in Rappbode Reservoir, Germany as well as the corresponding climatic and hydrological observations, to train three commonly used ML models (Random Forest, XGBoost, and Long Short-Term Memory) and comprehensively evaluate their performance in reproducing thremal structure within the whole water column. We also systemically compared such simulation results with a well-established process-driven model (CE-QUAL-W2). Going beyond a pure reproduction of observatiosn, we further evaluated the ability of CE-QUAL-W2 and ML models in projecting thermal dynamics under RCP8.5 climate scenario up to 2100. Our results suggested three ML methods yielded high accuracy in capturing water temperature dynamics from the surface (epilimnion) to bottom (hypolimnion), and also satisfactorily reproduced temporal development of the stratification pattern, with the results corresponding well with those from CE-QUAL-W2. By contrast, the projections by ML models were rather insensitive to future climate warming under RCP8.5 comparing with those by CE-QUAL-W2, pointing to an important risk whenever ML-based models are extrapolated beyond their training data range. Supported by millions of in situ measurements, our research clearly illustrated the opportunities (limits) of ML models in projecting thermal dynamics in deep waters, and the conclusion also provides key guidance for scientists to select the appropriate tools in projecting water temperature, and other environmental factors, under changing climate.

Model-aided climate adaptation for future maize in the US

Abstract Over the next three decades rising population and changing dietary preferences are expected to increase food demand by 25%–75%. At the same time climate is also changing—with potentially drastic impacts on food production. Breeding new crop characteristics and adjusting management practices are critical avenues to mitigate yield loss and sustain yield stability under a changing climate. In this study, we use a mechanistic crop model (MAIZSIM) to identify high-performing trait and management combinations that maximize yield and yield stability for different agroclimate regions in the US under present and future climate conditions. We show that morphological traits such as total leaf area and phenological traits such as grain-filling start time and duration are key properties that impact yield and yield stability; different combinations of these properties can lead to multiple high-performing strategies under present-day climate conditions. We also demonstrate that high performance under present day climate does not guarantee high performance under future climate. Weakened trade-offs between canopy leaf area and reproductive start time under a warmer future climate led to shifts in high-performing strategies, allowing strategies with higher total leaf area and later grain-filling start time to better buffer yield loss and out-compete strategies with a smaller canopy leaf area and earlier reproduction. These results demonstrate that focused effort is needed to breed plant varieties to buffer yield loss under future climate conditions as these varieties may not currently exist, and showcase how information from process-based models can complement breeding efforts and targeted management to increase agriculture resilience.

Differential effects of warming on the complexity and stability of the microbial network in Phragmites australis and Spartina alterniflora wetlands in Yancheng, Jiangsu Province, China.

The impact of climate warming on soil microbial communities can significantly influence the global carbon cycle. Coastal wetlands, in particular, are susceptible to changes in soil microbial community structure due to climate warming and the presence of invasive plant species. However, there is limited knowledge about how native and invasive plant wetland soil microbes differ in their response to warming. In this study, we investigated the temporal dynamics of soil microbes (prokaryotes and fungi) under experimental warming in two coastal wetlands dominated by native Phragmites australis (P. australis) and invasive Spartina alterniflora (S. alterniflora). Our research indicated that short-term warming had minimal effects on microbial abundance, diversity, and composition. However, it did accelerate the succession of soil microbial communities, with potentially greater impacts on fungi than prokaryotes. Furthermore, in the S. alterniflora wetland, experimental warming notably increased the complexity and connectivity of the microbial networks. While in the P. australis wetland, it decreased these factors. Analysis of robustness showed that experimental warming stabilized the co-occurrence network of the microbial community in the P. australis wetland, but destabilized it in the S. alterniflora wetland. Additionally, the functional prediction analysis using the Faprotax and FunGuild databases revealed that the S. alterniflora wetland had a higher proportion of saprotrophic fungi and prokaryotic OTUs involved in carbon degradation (p < 0.05). With warming treatments, there was an increasing trend in the proportion of prokaryotic OTUs involved in carbon degradation, particularly in the S. alterniflora wetland. Therefore, it is crucial to protect native P. australis wetlands from S. alterniflora invasion to mitigate carbon emissions and preserve the health of coastal wetland ecosystems under future climate warming in China.

Five million years of Antarctic Circumpolar Current strength variability

The Antarctic Circumpolar Current (ACC) represents the world’s largest ocean-current system and affects global ocean circulation, climate and Antarctic ice-sheet stability1–3. Today, ACC dynamics are controlled by atmospheric forcing, oceanic density gradients and eddy activity4. Whereas palaeoceanographic reconstructions exhibit regional heterogeneity in ACC position and strength over Pleistocene glacial–interglacial cycles5–8, the long-term evolution of the ACC is poorly known. Here we document changes in ACC strength from sediment cores in the Pacific Southern Ocean. We find no linear long-term trend in ACC flow since 5.3 million years ago (Ma), in contrast to global cooling9 and increasing global ice volume10. Instead, we observe a reversal on a million-year timescale, from increasing ACC strength during Pliocene global cooling to a subsequent decrease with further Early Pleistocene cooling. This shift in the ACC regime coincided with a Southern Ocean reconfiguration that altered the sensitivity of the ACC to atmospheric and oceanic forcings11–13. We find ACC strength changes to be closely linked to 400,000-year eccentricity cycles, probably originating from modulation of precessional changes in the South Pacific jet stream linked to tropical Pacific temperature variability14. A persistent link between weaker ACC flow, equatorward-shifted opal deposition and reduced atmospheric CO2 during glacial periods first emerged during the Mid-Pleistocene Transition (MPT). The strongest ACC flow occurred during warmer-than-present intervals of the Plio-Pleistocene, providing evidence of potentially increasing ACC flow with future climate warming.

Empirical stream thermal sensitivity cluster on the landscape according to geology and climate

Abstract. Climate change is modifying river temperature regimes across the world. To apply management interventions in an effective and efficient fashion, it is critical to both understand the underlying processes causing stream warming and identify the streams most and least sensitive to environmental change. Empirical stream thermal sensitivity, defined as the change in water temperature with a single degree change in air temperature, is a useful tool to characterize historical stream temperature conditions and to predict how streams might respond to future climate warming. We measured air and stream temperature across the Snoqualmie and Wenatchee basins, Washington, during the hydrologic years 2015–2021. We used ordinary least squares regression to calculate seasonal summary metrics of thermal sensitivity and time-varying coefficient models to derive continuous estimates of thermal sensitivity for each site. We then applied classification approaches to determine unique thermal sensitivity regimes and, further, to establish a link between environmental covariates and thermal sensitivity regimes. We found a diversity of thermal sensitivity responses across our basins that differed in both timing and magnitude of sensitivity. We also found that covariates describing underlying geology and snowmelt were the most important in differentiating clusters. Our findings and our approach can be used to inform strategies for river basin restoration and conservation in the context of climate change, such as identifying climate-insensitive areas of the basin that should be preserved and protected.

Intraguild interactions and abiotic conditions mediate occupancy of mammalian carnivores: co‐occurrence of coyotes–fishers–martens

The widespread eradication of large carnivores and subsequent expansion of top mesopredators has the potential to impact species and community interactions with ecosystem‐wide implications. An example of these trophic dynamics is the widespread establishment of coyotes following extirpation of wolves and mountain lions in eastern North America. Here, we examined occupancy of three carnivores in northern New York considering both environmental/habitat factors and interspecific interactions. We estimated the co‐occurrence of coyotes, fishers, and martens from a landscape‐scale winter camera trap survey repeated annually for three years. Martens occurred independently of both coyotes and fishers, while fishers and coyotes displayed positive intraguild interactions that were constant across the landscape. Both marten and fisher first‐order occupancy were driven by a combination of biotic and abiotic factors, with both species displaying positive associations with forest cover but antithetical responses to average snow depth. The integral and antithetical role of snow depth in driving the occurrence of martens (positive) and fishers (negative) in the landscape indicates that future climatic warming could reduce the availability of current spatial refuges for martens created by severe winter conditions. Climate‐driven alterations to established competitive interactions and co‐existence patterns between marten and fisher have critical implications for the species survival and conservation. We provide correlational evidence consistent with the potential for positive top–down effects of dominant mesocarnivores on subordinate species, with fisher occupancy increasing conditional on the presence of coyotes across the landscape. These findings align with the hypothesis that under certain conditions, coyotes may facilitate certain subordinate carnivores. The evidence produced here is consistent with hypotheses on the dynamic nature of trophic niches. We demonstrate the need to consider the interplay between climate, habitat, and interspecific interactions to understand wildlife occupancy patterns and inform wildlife management in a rapidly changing world.

Mid-Pliocene not analogous to high-CO2 climate when considering Northern Hemisphere winter variability

Abstract. In this study, we address the question of whether the mid-Pliocene climate can act as an analogue for a future warm climate with elevated CO2 concentrations, specifically regarding Northern Hemisphere winter variability. We use a set of sensitivity simulations with the global coupled climate model CESM1.0.5 (CCSM4-Utr), which is part of the PlioMIP2 model ensemble, to separate the response to a CO2 doubling and to mid-Pliocene boundary conditions other than CO2. In the CO2 doubling simulation, the Aleutian low deepens, and the Pacific–North American pattern (PNA) strengthens. In response to the mid-Pliocene boundary conditions, sea-level pressure variance decreases over the North Pacific, the PNA becomes weaker and the North Pacific Oscillation (NPO) becomes the dominant mode of variability. The mid-Pliocene simulation shows a weak North Pacific jet stream that is less variable in intensity but has a high level of variation in jet latitude, consistent with a dominant NPO and indicating that North Pacific atmospheric dynamics become more North Atlantic-like. We demonstrate that the weakening of the Aleutian low, and subsequent relative dominance of the NPO over the PNA, is related to shifts in tropical Pacific convection. Variability in the North Atlantic shows little variation between all simulations. The opposite response in North Pacific winter variability to elevated CO2 or mid-Pliocene boundary conditions demonstrates that the mid-Pliocene climate cannot serve as a future analogue in this regard.

Improving our understanding of future tropical cyclone intensities in the Caribbean using a high-resolution regional climate model

The Caribbean region is prone to the strong winds and low air pressures of tropical cyclones and their corresponding storm surge that driving coastal flooding. To protect coastal communities from the impacts of tropical cyclones, it is important to understand how this impact of tropical cyclones might change towards the future. This study applies the storyline approach to show what tropical cyclones Maria (2017) and Dorian (2019) could look like in a 2 °C and 3.4 °C warmer future climate. These two possible future climates are simulated with a high-resolution regional climate model using the pseudo global warming approach. Using the climate response from these simulations we apply a Delta-quantile mapping technique to derive future changes in wind speed and mean sea level pressure. We apply this Delta technique to tropical cyclones Maria and Dorian’s observed wind and pressure fields to force a hydrodynamic model for simulating storm surge levels under historical and future climate conditions. Results show that the maximum storm surge heights of Maria and Dorian could increase by up to 0.31 m and 0.56 m, respectively. These results clearly show that future changes in storm surge heights are not negligible compared to end-of-the-century sea level rise projections, something that is sometimes overlooked in large-scale assessments of future coastal flood risk.

Microbial mediation of soil carbon loss at the potential climax of alpine grassland under warming

Soil in high latitude and altitude cold regions contains over half of soil organic carbon (SOC) globally, so the decomposition of these SOCs under climate warming could release huge amounts of carbon dioxide to the atmosphere, amplifying climate warming. However, it is still unclear how the SOC storages will change when the ecosystem reaches the final and stable stage (i.e., the climax) under long-term warming. This is mainly because the turnover times of SOC in cold regions exceeds hundreds or even thousands of years, much longer than the periods of simulated warming experiments. Herein we used natural geothermal warming gradients in a Tibetan alpine grassland to determine SOC changes and underlying plant and microbial mechanisms at the potential climax. SOC concentrations were significantly decreased by 21.4%–30.6% under high-level soil warming (+4∼+6 °C), but remained unchanged under low-level soil warming (+2 °C). The losses of SOC were primarily from mineral-associated organic carbon, rather than unprotected particulate organic carbon. The shifts of microbial communities and associated decline of microbial carbon use efficiency, rather than plant-driven carbon fluxes, substantially contributed to the SOC changes. This observed SOC losses at the climax of alpine grassland by high-level warming provide strong empirical support for the positive soil carbon-climate feedback in cold regions, which could not be concluded from short-term experiments or only based on ecosystem carbon fluxes alone. The divergent responses of SOC to different degrees of warming suggest that models must account for these heterogeneous carbon dynamics for projecting future climate warming scenarios.

Velocity variations and hydrological drainage at Baltoro Glacier, Pakistan

Abstract. Glacial meltwater directly influences glacier dynamics. However, in the case of debris-covered glaciers, the drivers of glacier velocity and the influence of supraglacial lakes have not yet been sufficiently analysed and understood. We present a spatio-temporal analysis of key glacier characteristics for Baltoro Glacier in the Karakoram from October 2016 to September 2022 based on Earth observation data and climate parameters extracted from the High Asia Refined analysis (HAR) data set. For the glacier variables, we used surface velocity, supraglacial lake extent, melt of snow and ice, and proglacial run-off index. For climate variables, we focused on air temperature and precipitation. The surface velocity of Baltoro Glacier was characterized by a spring speed-up, summer peak, and fall speed-up with a relative increase in summer of 0.2–0.3 m d−1 (75 %–100 %) in relation to winter velocities, triggered by the onset of or an increase in basal sliding. Snow and ice melt have the largest impact on the spring speed-up, summer velocity peak, and the transition from inefficient to efficient subglacial drainage. The melt covered up to 64 % (353 km2) of the entirety (debris-covered and debris-free) of Baltoro Glacier and reached up to 4700 m a.s.l. during the first melt peak and up to 5600 m a.s.l. during summer. The temporal delay between the initial peak of seasonal melt and the first relative velocity maximum decreases downglacier. Drainage from supraglacial lakes (3.6–5.9 km2) contributed to the fall speed-up, which showed a 0.1–0.2 m d−1 (20 %–30 %) lower magnitude compared to the summer velocity peak. Most of the run-off can be attributed to the melt of snow and ice. However, from mid-June onward, the lakes play an increasing role, even though their contribution is estimated to be only about half of that of the melt. The observed increase in summer air temperatures leads to a greater extent of melt, as well as to a rise in the number and total area of supraglacial lakes. This tendency is expected to intensify in a future warming climate.

Increasing Flood Hazard Posed by Tropical Cyclone Rapid Intensification in a Changing Climate

AbstractTropical cyclones (TCs) that undergo rapid intensification (RI) before landfall are notoriously difficult to predict and have caused tremendous damage to coastal regions in the United States. Using downscaled synthetic TCs and physics‐based models for storm tide and rain, we investigate the hazards posed by TCs that rapidly intensify before landfall under both historical and future mid‐emissions climate scenarios. In the downscaled synthetic data, the percentage of TCs experiencing RI is estimated to rise across a significant portion of the North Atlantic basin. Notably, future climate warming causes large increases in the probability of RI within 24 hr of landfall. Also, our analysis shows that RI events induce notably higher rainfall hazard levels than non‐RI events with equivalent TC intensities. As a result, RI events dominate increases in 100‐year rainfall and storm tide levels under climate change for most of the US coastline.

Pyraingen: A python package for constrained continuous rainfall generation

Continuous rainfall is often required for flood estimation and water resources assessment. However, stochastically generated continuous rainfall records are typically inconsistent with intensity-frequency-durations (IFDs) used in design, and do not simulate the rainfall behaviour we can expect in a future warmer climate. Here, we present the python package pyraingen to generate ensembles of continuous subdaily rainfalls at a single location that preserve IFD relationships. Rainfall generation can also be conditioned on a climate covariate, in this case temperature, to produce rainfall timeseries reflective of a future climate. We present an implementation at five climatologically unique sites across Australia and demonstrate its ability to produce rainfall timeseries that reflect both present day and future changes in rainfall persistence, temporal patterns, means, and extremes. This package will enable studies using continuous simulation to assess the impacts of climate change using the current guidance on changes to both IFDs and mean annual rainfalls.