Climate Warming Scenarios Research Articles

Future projections of thermal regimes and mixing characteristics in a monomictic reservoir under climate change

Stratified structures are basic physical characteristics of lakes and reservoirs, which play important roles in vertical convection and mixing processes. Global warming is expected to alter the thermal regimes and stratified characteristics of lakes and reservoirs, leading to potential environmental risks and ecological problems. In this study, we used a two-dimensional hydrodynamic model to explore the response characteristics of the thermal regime to climate change in the Xiluodu Reservoir. The study is conducted based on four representative concentration pathways (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5). The results show that the projected surface water temperature of the reservoir will significantly increase (0.13 °C/10a-0.34 °C/10a) from 2022 to 2099, and the warming rate of the water in the epilimnion and thermocline will be greater than that in the hypolimnion, leading to enhanced vertical stratification in the reservoir. The stratification stability index (SI) will increase by 14.4 % under RCP 8.5 compared to that under RCP 2.6. The main responses of the reservoir to climate change are earlier start date and later end date of stratification, which may increase the duration of hypoxia in the hypolimnion and promote the succession of planktonic algal communities. The withdrawal water temperature in the reservoir will significantly increase under the climate warming scenarios (0.03 °C/10a-0.22 °C/10a). Furthermore, our research results indicate that selective withdrawal is still needed to mitigate the adverse effects of cold water from the reservoir during the fish spawning period under the strongest warming scenario, and can also be an effective adaptive management strategy to regulate thermal stability in the reservoir. This study provides a scientific and theoretical reference for the sustainable management of similar deep monomictic reservoirs under climate change.

Evaluating the efficacy of fisheries management strategies in China for achieving multiple objectives under climate change

It is increasingly recognized that effective fisheries management needs to take into account not only the target species, but also the broader scope of biological, environmental, socio-economic and institutional factors pertaining to human utilization of fishery resources. This recognition has stimulated a global call for the Ecosystem-Based Fisheries Management (EBFM), with an increasing appreciation of its merits in the face of climate change. In this study, we applied the concept of EBFM to China's fisheries and tested the performance of various fisheries management strategies, including status quo management and alternative strategies with different objective priorities, under contrasting climate warming scenarios. We used the Ecopath with Ecosim (EwE) as an operating model, with an explicit consideration of trophic interactions, and specifically quantified the trade-offs across multiple metrics (i.e., sustainable fishery production, economic profitability, seafood security, and ecosystem health). No single strategy was superior across all the four dimensions. Importantly, the existing approach to fisheries management underperformed in most metrics, with the current fishing intensity exceeding the level that would maximize multispecies yields (fMSY) and total profits (fMEY). In contrast, an alternative harvest control rule (HCR) strategy, designed to respond to variations in biomass, provided inherent resilience of the ecosystem under climate warming, resulting in increased commercial fish biomass, improved profit and seafood supply, as well as enhanced ecosystem structure and function across various time-climate scenarios. From a tactic perspective, the multiple species management strategies of “fMSY” and “fMEY” can be better suited for the highly mixed fishery context in China. These alternatives also consistently demonstrated superior performance compared to the existing fisheries management strategy. Our work reveals potential trade-offs among diverse ecosystem services and provides a framework using EwE model for quantifying possible performance of management strategies under climate change, leading to more informed and transparent decision-making.

AMOC decline and recovery in a warmer climate

This study presents novel insight into the mechanisms of Atlantic Meridional Overturning Circulation (AMOC) reduction and its recovery under a warmer climate scenario. An one-thousand-year-long numerical simulation of a global coupled ocean–ice–atmosphere climate model, subjected to a stationary atmospheric radiative forcing, depict a coherent picture of the Arctic sea ice melting as a trigger for the initial AMOC reduction, along with decreases in the northward fluxes of salt and heat. Further atmospheric-driven ocean processes contribute to an erosion of the stable stratification of the fresher, yet colder waters in the surface layers of the North Atlantic, contributing to the recovery of a permanently altered AMOC.

Water Mass Transport Changes through the Venice Lagoon Inlets from Projected Sea-Level Changes under a Climate Warming Scenario

In this study, an ensemble of numerical simulations with a state-of-the-art hydrodynamic model for coastal applications is used to characterize, for the first time, the expected mid-21st-century changes in circulation and associated sea-level height inside the Venice lagoon induced by projected Mediterranean sea level rise and atmospheric circulation changes over the Adriatic Sea under the RCP8.5 emission scenario. Our results show that water transports through the three inlets connecting the Venice lagoon to the open sea are expected to change significantly, with consequent significant persistent alterations of the circulation and sea-level height inside the lagoon. The projected water mass redistributions motivate further studies on the implications of climate change for the lagoon environment.

An empirical analysis of US land‐use change under multiple climate change scenarios

AbstractThis study empirically estimates the effects of climate on land‐use change across the conterminous United States and uses the empirical model to simulate the effects of a range of future climate change scenarios on the allocation of land to forestry, agriculture, and development. Ricardian estimation linking climate with the net returns to land production is integrated with a discrete‐choice estimation of plot‐level land‐use change. Comparing projected land‐use changes across scenarios, we find that drier and warmer climate scenarios favor forest land, wetter and cooler climate scenarios favor developed land, and wetter and warmer climate scenarios favor crop lands.

Statistically parameterizing and evaluating a positive degree-day model to estimate surface melt in Antarctica from 1979 to 2022

Abstract. Surface melting is one of the primary drivers of ice shelf collapse in Antarctica and is expected to increase in the future as the global climate continues to warm because there is a statistically significant positive relationship between air temperature and melting. Enhanced surface melt will impact the mass balance of the Antarctic Ice Sheet (AIS) and, through dynamic feedbacks, induce changes in global mean sea level (GMSL). However, the current understanding of surface melt in Antarctica remains limited in terms of the uncertainties in quantifying surface melt and understanding the driving processes of surface melt in past, present and future contexts. Here, we construct a novel grid-cell-level spatially distributed positive degree-day (PDD) model, forced with 2 m air temperature reanalysis data and spatially parameterized by minimizing the error with respect to satellite estimates and surface energy balance (SEB) model outputs on each computing cell over the period 1979 to 2022. We evaluate the PDD model by performing a goodness-of-fit test and cross-validation. We assess the accuracy of our parameterization method, based on the performance of the PDD model when considering all computing cells as a whole, independently of the time window chosen for parameterization. We conduct a sensitivity experiment by adding ±10 % to the training data (satellite estimates and SEB model outputs) used for PDD parameterization and a sensitivity experiment by adding constant temperature perturbations (+1, +2, +3, +4 and +5 ∘C) to the 2 m air temperature field to force the PDD model. We find that the PDD melt extent and amounts change analogously to the variations in the training data with steady statistically significant correlations and that the PDD melt amounts increase nonlinearly with the temperature perturbations, demonstrating the consistency of our parameterization and the applicability of the PDD model to warmer climate scenarios. Within the limitations discussed, we suggest that an appropriately parameterized PDD model can be a valuable tool for exploring Antarctic surface melt beyond the satellite era.

Chemodiversity of Cyanobacterial Toxins Driven by Future Scenarios of Climate Warming and Eutrophication.

Climate change and eutrophication are two environmental threats that can alter the structure of freshwater ecosystems and their service functions, but we know little about how ecosystem structure and function will evolve in future scenarios of climate warming. Therefore, we created different experimental climate scenarios, including present-day conditions, a 3.0 °C increase in mean temperature, and a "heatwaves" scenario (i.e., an increase in temperature variability) to assess the effects of climate change on phytoplankton communities under simultaneous stress from eutrophication and herbicides. We show that the effects of climate warming, particularly heatwaves, are associated with elevated cyanobacterial abundances and toxin production, driven by a change from mainly nontoxic to toxic Microcystis spp. The reason for higher cyanobacterial toxin concentrations is likely an increase in abundances because under the dual pressures of climate warming and eutrophication individual Microcystis toxin-producing ability decreased. Eutrophication and higher temperatures significantly increased the biomass of Microcystis, leading to an increase in the cyanobacterial toxin concentrations. In contrast, warming alone did not produce higher cyanobacterial abundances or cyanobacterial toxin concentrations likely due to the depletion of the available nutrient pool. Similarly, the herbicide glyphosate alone did not affect abundances of any phytoplankton taxa. In the case of nutrient enrichment, cyanobacterial toxin concentrations were much higher than under warming alone due to a strong boost in biomass of potential cyanobacterial toxin producers. From a broader perspective our study shows that in a future warmer climate, nutrient loading has to be reduced if toxic cyanobacterial dominance is to be controlled.

Potential Distribution of Bryophyte, Entodon challengeri (Entodontaceae), under Climate Warming in China

Entodon challengeri (Paris) Cardot has important environmental monitoring and medical value. It is critical we inspect the influence of climate warming on its spatiotemporal distribution pattern. Based on actual geographical distribution records and environmental datasets, a MaxEnt model coupled with ArcGIS was executed to display the potential suitable habitats of E. challengeri in China under future climate warming scenarios. We showed the following. (i) The simulation accuracy of the MaxEnt model was excellent, with an AUC value of 0.918. (ii) Annual precipitation and precipitation during the wettest month were the critical factors that restricted the distribution range of E. challengeri. (iii) Current suitable habitats were concentrated in the northern temperate zone in eastern China. (iv) Under climate warming scenarios, on the spatial scale, the distributional pattern presented a shrinkage in the south and expansion in the north, which was more obvious in the RCP8.5 than in the RCP2.6 scenario. On the time scale, shrinkage of the potential distributional range was greater in the 2070s than in the 2050s. (v) The distributional centroids shifted to the northeast. In general, future climate warming will have a great negative effect on the suitability of habitats of E. challengeri.

Spatiotemporal Variability of Alpine Meadow Aboveground Biomass and Sustainable Grazing in Light of Climate Warming

Understanding spatiotemporal variability of aboveground biomass (AGB) in alpine grassland ecosystems is required to better formulate sustainable grazing strategies, especially in climate-sensitive areas such as the Qinghai-Tibet Plateau. Drawing from recent modeling results, we analyzed spatial variability in grassland AGB over seasonal and annual timescales. Theoretical livestock carrying capacity (LCC) was predicted in relation to projected warming and simulated pika disturbance. We found that elevation and slope were key determinants of the distribution of AGB and its change. Although grasses and shrubs occupied an equivalent area, the latter generated approximately double the amount of total biomass, but the former generated slightly more available biomass. Although pika habitat extended over 45.3% of the study area, the impacts of pika only reduced the total available AGB (AGBV) by < 0.07%. The actual LCC (2.16 SU · ha−1 [sheep unit per hectare]) of the study area was lower than the theoretical LCC (2.77−2.96 SU · ha−1). Under climate warming scenarios of 1.0°C, 1.5°C, and 2.0°C, the actual LCC can be increased by 0.82-1.25, 0.99-1.53, and 0.77−1.23 SU · ha−1, respectively. Although systematic climate warming increased AGB, impacts were especially marked at lower elevations and on north-facing slopes because of higher soil water availability. Results highlight that rather than implementing LCC in a static manner in light of climate warming, deeper understanding of biomass availability and the combined effects of climate change and topographic heterogeneity is required to support better management of grasslands.

Impacts of climate change on streamflow in the McKenzie Creek watershed in the Great Lakes region

Introduction: This study explored streamflow dynamics of the McKenzie Creek watershed in Southern Ontario, Canada under a changing climate. The Creek is located in the southern portion of the Grand River watershed in the Great Lakes region and is an important water and ecosystem service provider for the Six Nations of the Grand River reserve, the largest (by population) Indigenous community in Canada and the fourth largest in North America.Methods: The Coupled Groundwater and Surface-Water Flow Model (GSFLOW) was used to simulate streamflow from 1951 to 2020 using observed gridded meteorological data from Natural Resources Canada (NRCANmet) and in situ data from Environment and Climate Change Canada (ECCC). Downscaled data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) for two Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCP) climate warming scenarios, RCP 4.5 and RCP 8.5 were used to run GSFLOW for the historic (1951–2020) and projected (2021–2099) period.Results: Results suggested that streamflow in the McKenzie Creek will be significantly impacted by climate change in winter months when streamflow is projected to increase due to higher temperatures causing early melting of snowpack and increasing winter precipitation. Consequently, spring streamflow is expected to decrease and little or no change in streamflow in the summer and autumn. These changes in streamflow dynamics may lead to more flooding incidents in the winter, while at the same time, the region may face reduced water availability or dry conditions in late spring and summer due to warm temperatures.Discussion: This study provides important information about streamflow and hydrologic dynamics of this watershed that will help managers and planners to better manage water resources and be prepared to deal with climate change and its impacts on water availability and security not only for the Six Nations area but also for Southern Ontario which houses one-third of Canada’s population.

Simulating dynamic fire regime and vegetation change in a warming Siberia

BackgroundClimate change is expected to increase fire activity across the circumboreal zone, including central Siberia. However, few studies have quantitatively assessed potential changes in fire regime characteristics, or considered possible spatial variation in the magnitude of change. Moreover, while simulations indicate that changes in climate are likely to drive major shifts in Siberian vegetation, knowledge of future forest dynamics under the joint influence of changes in climate and fire regimes remains largely theoretical. We used the forest landscape model, LANDIS-II, with PnET-Succession and the BFOLDS fire extension to simulate changes in vegetation and fire regime characteristics under four alternative climate scenarios in three 10,000-km2 study landscapes distributed across a large latitudinal gradient in lowland central Siberia. We evaluated vegetation change using the fire life history strategies adopted by forest tree species: fire resisters, fire avoiders, and fire endurers.ResultsAnnual burned area, the number of fires per year, fire size, and fire intensity all increased under climate change. The relative increase in fire activity was greatest in the northernmost study landscape, leading to a reduction in the difference in fire rotation period between study landscapes. Although the number of fires per year increased progressively with the magnitude of climate change, mean fire size peaked under mild or moderate climate warming in each of our study landscapes, suggesting that fuel limitations and past fire perimeters will feed back to reduce individual fire extent under extreme warming, relative to less extreme warming scenarios. In the Southern and Mid-taiga landscapes, we observed a major shift from fire resister-dominated forests to forests dominated by broadleaved deciduous fire endurers (Betula and Populus genera) under moderate and extreme climate warming scenarios, likely associated with the substantial increase in fire activity. These changes were accompanied by a major decrease in average cohort age and total vegetation biomass across the simulation landscapes.ConclusionsOur results imply that climate change will greatly increase fire activity and reduce spatial heterogeneity in fire regime characteristics across central Siberia. Potential ecological consequences include a widespread shift toward forests dominated by broadleaved deciduous species that employ a fire endurer strategy to persist in an increasingly fire-prone environment.

A multi-model ensemble-based CMIP6 assessment of future solar radiation and PV potential under various climate warming scenarios

The ability of the hybrid evolutionary auto-regression integrated moving average (ARIMA) with a transformed probabilistically optimized Gumbel (GP) model (ARIMA-GP) and empirical technique (EM-GP) to predict global solar radiation (H) was investigated in Nigeria. The outcome showed that the hybrid ARIMA-GP2 (0, 0, 0) significantly outperformed the empirical and other ARIMA configuration models. Additionally, the potential for PV generation was estimated using six different PV power technology models that were fitted to Nigeria's comparable climatic conditions. It was found that, compared to other technologies, poly-crystalline silicon (p-Si) technology yielded the highest increase in solar PV output compared to other modules in both moderate forcing-case scenarios (SSP245) and strong forcing-case scenarios (SSP585) between 2015–2050 and 2051–2099. However, in the mitigation-case scenario (SSP126), amorphous silicon (a-Si) technology produces less than a 1% increase in solar PV production, while other technologies produce less than a 1% decrease in solar PV output. The CMIP6 climate model was also used to assess the effects of climate change on global solar radiation (insolation). With the exception of the far-future sequencing period (2051–2099), as the impact of climate change intensifies, there may be a corresponding increase in insolation in the moderate forcing- and strong forcing-case scenarios in all seasons between 2015–2050 and 2051–2099, as well as in the annual resolution. However, under the mitigation-case scenario (SSP126), with the exception of the DJF season during the 2015–2050 and 2051–2099 sequencing periods, impacts of climate change resulted in a maximum decline in insolation of 2.988% in Nigeria. This suggests that solar energy should be Nigeria's primary source of renewable energy and low-carbon economic planning, but Nigeria may not achieve the net-zero energy transition by 2050 if prompt climate mitigation and adaptation measures are not implemented.

SWAMP: A new experiment for simulating permafrost warming and active layer deepening on the Tibetan Plateau

Abstract Our knowledge on the responses of permafrost ecosystems to climate warming is critical for assessing the direction and magnitude of permafrost carbon‐climate feedback. However, most of the previous experiments have only been able to warm the air and surface soil, with limited effects on the permafrost temperature. Consequently, it remains challenging to realistically simulate permafrost thawing in terms of increased active layer (a layer freezing and thawing seasonally above permafrost) thickness under climate warming scenarios. Here, we presented the experimental design and warming performance of a novel experiment, Simulate Warming at Mountain Permafrost (SWAMP), the first one to successfully simulate permafrost warming and the subsequent active layer deepening in a swamp meadow situated on the Tibetan Plateau. Infrared heating was employed as above‐ground warming to elevate the temperature of the air and surface soil, and heating rods were inserted vertically in the soil to provide below‐ground warming for transmitting heat to the deep active layer and even to permafrost deposits. In 3 m diameter warmed circular plots, the air and the entire soil profile (from surface soil to 120 cm) was effectively heated, with an increase of approximately 2°C in the upper 60 cm, which progressively weakened with soil depth. Warming increased soil moisture across the growing season by inducing an earlier thawing of the soil. Values varied from 1.8 ± 1.8 to 12.3 ± 2.3% according to the soil depth. Moreover, during the growing season, the warmed plots had greater thaw depths and a deeper active layer thickness of 12.6 ± 0.8 cm. In addition, soil thawing duration was prolonged by the warming, ranging from 22.8 ± 3.3 to 49.3 ± 4.5 days depending on the soil depth. The establishment of SWAMP provides a more realistic simulation of warming‐induced permafrost thaw, which can then be used to explore the effect of climate warming on permafrost ecosystems and the potential permafrost carbon‐climate feedback. Notably, our experiment is more advantageous for investigating how deep soil processes respond to climate warming and active layer deepening, compare with experiments which use passive warming techniques such as open top chambers (OTCs).

Simulating the thermal regime of a railway embankment structure on the Tibetan Plateau under climate change

With global warming and its amplified effect on the Tibetan Plateau, the permafrost on the Tibetan Plateau has been significantly degraded, manifested by decreased permafrost thickness, increased active layer thickness, thermokarst, and surface subsidence, causing severe damage to infrastructure. To better understand and assess the future stability of the Qinghai-Tibet Railway, we used a laterally coupled version of the one-dimensional CryoGrid3 land surface model to simulate the thermal regimes of the railway subgrade under current climate conditions. By modeling ground subsidence (i.e., by simulating the melting of excess ice) we provide estimates of future subgrade stability under low (Representative Concentration Pathway 2.6 [RCP2.6]) and high (RCP8.5) climate warming scenarios. Our modeled results reveal satisfactory performance with respect to the comparison of measured and modeled ground thermal regimes. Under current climate conditions, we infer that mostly thaw-stable conditions as maximum thaw depths do not reach the embankment base. The sunny side of the embankment (southeast-facing) reveals being more vulnerable to suffering from thaw settlement or thermal erosion than the shady side (northwest-facing). The extent of future railway failure due to thawing permafrost will depend on the magnitude of the warming. For conditions typical of Beiluhe (situated on continuous permafrost in the central Tibetan Plateau), the railway embankment might largely maintain safe operation until the end of the century under a scenario of climate stabilization. In contrast, under strong warming the railway subgrade is likely to destabilize from the 2030s onwards and embankment subsidence is initiated at mid-century through the melting of excess ice.

Projected changes of precipitation extremes in North America using CMIP6 multi-climate model ensembles

In this study, we estimated a comprehensive set of extreme precipitation indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) over North America (NA) using 18 selected higher-resolution GCMs of the sixth Coupled Model Intercomparison Project (CMIP6). The GCMs are evaluated in their historical simulations (1981–2010) against those estimated from in-situ (Daymet) and reanalysis (NARR) dataasets, followed by the projected changes in precipitation extremes of NA in response to climate warming (SSP1-2.6, SSP2-4.5 and SSP5-8.5) scenarios of CMIP6 in terms of temporal variations, spatial distributions, seasonal patterns and model agreement over the 21st century relative to 1981–2010. Results show that the CMIP6 ensemble median (CMIP6-EnM) can generally capture the observed extreme precipitation patterns of NA, and it out-performs all 18 individual GCMs with negative RMSE′XY, higher R statistics (R > 0.8) and the signal-to-noise ratio (SNR) > 1 in most sub-regions of NA. In general, extreme precipitation events are projected to occur more frequently and severely in the future, particularly in latitudes above 55°N of NA and in coastal areas. In contrast, dry conditions in southern NA (e.g., NCA and SCA) are projected to intensify over the 21st century. Seasonal changes are projected to be more significant in winter than in summer for northern NA (e.g., GIC, NWN and NEN), while in Central America (e.g., WNA, CAN, ENA), precipitation extremes will likely be less severe in both summer and winter. However, unlike strong model agreements in high (100%) and mid-latitudes (80%), there is often a wide disparity among the signs of projected changes between GCMs in southern NA. Unless greenhouse gas emissions are drastically reduced immediately, NA will likely be vulnerable to the impact of worsening extreme precipitation events especially in northern and coastal regions.

Assessment of the Damage Incurred by biodiversity and ecological degradation via HEC-HMS simulations and of Stream Flow Assessment and Analysis (SAAS).A case study.

Findings on the quality of River Ikpoba samplings is an essential matter because water resources management coupled with hydro-chemical interfaces is of the essence, especially for monitoring and discovering of surface-water contaminants origins. Thus, River Ikpoba samplings were scrutinized using Stream Flow Simulation Model (SFSM) and Multivariate Statistical techniques. Runoff occasion due to land use change shows increase in curve number at peak runoff of 11.60m3/s, while the maximum rainfall is greater in the circumstances up to 141.0 mm. All though the year, not only that envisaged medians always greater than the mean monthly scrutinized, but the anticipated minimum temperature is also bigger, i.e. even more unadventurous prognosis of temperature result in warmer climate scenario in the study region. As the computed runoff occasion p-value (0.998) is greater than the significance level alpha=0.05, one cannot reject the null hypothesis H0. Hence, it was concluded that the simulated flow data are closely related to the observed flow data. Likewise, an increase in curve number (from 74.58 to 79.99) resulted in a corresponding increase in outflow (from 8.00cms to 10.350cms) was observed. Indicating, with increasing curve number, the peak discharge and direct runoff volume also increases proportionately.

On the Role of Sea Surface Temperature in the Clustering of Global Tropical Cyclone Formation

Abstract This study examines the potential impacts of large-scale atmospheric circulations that are forced by sea surface temperatures (SST) on global tropical cyclone (TC) formation. Using the Geophysical Fluid Dynamics Laboratory (GFDL) global atmosphere and land surface model, version 4 (AM4), under different SST distributions, it is found that the east–west clustering of global TC formation is mainly governed by large-scale circulations in response to given SSTs, instead of direct ocean surface fluxes associated with zonal SST anomalies. Our zonally homogeneous SST simulations in the presence of realistic surface coverage show that TC clusters still emerge as a result of the breakdown of zonal circulations related to land–sea distribution, which produce specific “hotspots” for global TC formation. Sensitivity experiments with different climate warming scenarios and model physics confirm the persistence of these TC clusters in the absence of all zonal SST variations. These robust results offer new insights into the effects of large-scale circulation and terrain forcing on TC clusters beyond the traditional view of direct SST impacts, which are based on the direct alignment of the warmest SST regions and TC clusters. In addition, our experiments also capture internal variability of the global TC frequency, with an average fluctuation of 6–8 TCs at several dominant frequencies of ∼3, 6, and 9 years, even in the absence of all SST interannual variability and ocean coupling. This finding reveals an intrinsic “noise” level of the global TC frequency that one has to take into account when examining the past and future trends in TC activity and their related significance or detectability. Significance Statement In this study, the clustering of global tropical cyclone (TC) formation is investigated, using global simulations under different idealized sea surface temperature (SST) distributions. Our results show that it is the response of the large-scale tropical circulations to SST anomalies that is mostly responsible for the clustering of global TC formation rather than surface flux differences. It is also found that the tropical atmosphere contains inherent fluctuations in the global TC frequency of 6–8 TCs every 3–9 years, even in the absence of all SST interannual and zonal variability. These results offer new insight into the role of tropical dynamics in governing TC climatology and suggest possible mechanisms underlying the clustering of global TC formation under different climate conditions.

Genomic insights into local adaptation in the Asiatic toad Bufo gargarizans, and its genomic offset to climate warming.

Genomic signatures of local adaptation have been identified in many species but remain sparsely studied in amphibians. Here, we explored genome-wide divergence within the Asiatic toad, Bufo gargarizans, to study local adaptation and genomic offset (i.e., the mismatch between current and future genotype-environment relationships) under climate warming scenarios. We obtained high-quality SNP data for 94 Asiatic toads from 21 populations in China to study spatial patterns of genomic variation, local adaptation, and genomic offset to warming in this wide-ranging species. Population structure and genetic diversity analysis based on high-quality SNPs revealed three clusters of B. gargarizans in the western, central-eastern, and northeastern portions of the species' range in China. Populations generally dispersed along two migration routes, one from the west to the central-east and one from the central-east to the northeast. Both genetic diversity and pairwise F ST were climatically correlated, and pairwise F ST was also correlated with geographic distance. Spatial genomic patterns in B. gargarizans were determined by the local environment and geographic distance. Global warming will increase the extirpation risk of B. gargarizans.

Impacts of historical droughts on maize and soybean production in the southeastern United States

The trend of yield losses to drought in United States (U.S.) agriculture has increased over the years, in spite of financial investments and technological development to alleviate drought impacts. As climate change threatens to worsen future drought conditions, it is crucial to evaluate drought impacts on crop production for efficient yet robust decision-making at the regional level. This study evaluated the robustness of modified Standardized Precipitation Indices (SPIs) using effective precipitation (EP) and the Standardized Precipitation-Evapotranspiration Index (SPEI) in assessing drought impacts on county-level maize and soybean yields in the southeastern U.S during 1979–2019. The results showed that the modified SPI using the CROPWAT EP formula can be as effective as SPEI in assessing drought impacts on crop production. Assessment of drought impacts on crop yield year-to-year variability was then assessed by fitting linear regression through the yield-drought time series. Probability of yield loss due to drought in the region was estimated by using a copula-based probabilistic model. Results show that drought events occurring during the critical development growth stage had significantly negative impacts on year-to-year yield variability in over 50% of the counties in the study region, though the impact magnitude varied across the region due to different characteristics, historical climatic condition and irrigation infrastructure. On average, an extremely dry event occurring during the critical development growth stage resulted in a region-wide average yield reduction between − 42.7% and − 31.9% for maize and between − 25.4% and − 23.4% for soybean. Moderately wet conditions may increase crop yield, but excessively wet conditions may diminish the benefits for both crops. The average probability of yield loss of the study region under the extremely dry condition is more than 80%. Irrigation may help to reduce the impacts of drought on crop production: maize-producing irrigated counties on average were found to be 50% less sensitive to drought than non-irrigated counties, though this effect is smaller for soybean. As crop production in the region is highly vulnerable to drought, adaptation interventions under are required to adapt to warming climate scenarios.

An Arctic delta reduced-complexity model and its reproduction of key geomorphological structures

Abstract. Arctic river deltas define the interface between the terrestrial Arctic and the Arctic Ocean. They are the site of sediment, nutrient, and soil organic carbon discharge to the Arctic Ocean. Arctic deltas are unique globally because they are underlain by permafrost and acted on by river and sea ice, and many are surrounded by a broad shallow ramp. Such ramps may buffer the delta from waves, but as the climate warms and permafrost thaws, the evolution of Arctic deltas will likely take a different course, with implications for both the local scale and the wider Arctic Ocean. One important way to understand and predict the evolution of Arctic deltas is through numerical models. Here we present ArcDelRCM.jl, an improved reduced-complexity model (RCM) of arctic delta evolution based on the DeltaRCM-Arctic model (Lauzon et al., 2019), which we have reconstructed in Julia language using published information. Unlike previous models, ArcDelRCM.jl is able to replicate the ramp around the delta. We have found that the delayed breakup of the so-called “bottom-fast ice” (i.e. ice that is in direct contact with the bed of the channel or the sea, also known as “bed-fast ice”) on and around the deltas is ultimately responsible for the appearance of the ramp feature in our models. However, changes made to the modelling of permafrost erosion and the protective effects of bottom-fast ice are also important contributors. Graph analyses of the delta network performed on ensemble runs show that deltas produced by ArcDelRCM.jl have more interconnected channels and contain less abandoned subnetworks. This may suggest a more even feeding of sediments to all sections of the delta shoreline, supporting ramp growth. Moreover, we showed that the morphodynamic processes during the summer months remain active enough to contribute significant sediment input to the growth and evolution of Arctic deltas and thus should not be neglected in simulations gauging the multi-year evolution of delta features. Finally, we tested a strong climate-warming scenario on the simulated deltas of ArcDelRCM.jl, with temperature, discharge, and ice conditions consistent with RCP7–8.5. We found that the ramp features degrade on the timescale of centuries and effectively disappear in under 1 millennium. Ocean processes, which are not included in these models, may further shorten the timescale. With the degradation of the ramps, any dissipative effects on wave energy they offered would also decrease. This could expose the sub-aerial parts of the deltas to increased coastal erosion, thus impacting permafrost degradation, nutrients, and carbon releases.