Warm Winter Research Articles

Assimilating ESA CCI land surface temperature into the ORCHIDEE land surface model: insights from a multi-site study across Europe

Abstract. Land surface temperature (LST) plays an essential role in water and energy exchanges between the Earth's surface and atmosphere. Recent advancements in high-quality satellite-derived LST data and land data assimilation systems present a unique opportunity to bridge the gap between global observational data and land surface models (LSMs) to better constrain the water and energy budgets in a changing climate. In this vein, this study focuses on the assimilation of the ESA CCI-LST product into the ORCHIDEE LSM (the continental part of the Institut Pierre-Simon Laplace Earth system model) with the aim of optimizing key parameters to improve the simulation of LST and surface energy fluxes. We use the land data assimilation system for the ORCHIDEE model (ORCHIDAS) to conduct a series of synthetic twin data assimilation experiments accounting for actual data availability and uncertainty from ESA CCI-LST to find an optimal strategy for assimilating LST. Here, we test different strategies of assimilation, notably investigating (i) two optimization methods (a random search technique and a gradient-based technique) and (ii) different ways to assimilate LST using the only raw data and/or different characteristics of the LST diurnal cycle (e.g. mean daily, daily amplitude, maximum and minimum temperatures, and morning and afternoon gradients). Upon identifying the optimal approach, we use ORCHIDAS to assimilate ESA CCI-LST data across 34 European sites provided by the Warm Winter database. Our results demonstrate the effectiveness of assimilating 3 h CCI-LST data in ORCHIDEE over a single year in 2018, thereby improving the accuracy of simulated LST and fluxes. This improvement, assessed against CCI-LST and in situ observations, reaches up to a 60 % reduction in the root-mean-square deviation, with a median decrease of 20 % over the entire validation period (2009–2020). Furthermore, we evaluate the effectiveness of optimized parameters for application at larger scales using the median of optimized parameters per vegetation type across sites. Notably, the performance for both LST and fluxes exhibits consistent stability over the years, comparable to using site-specific parameters, and indicates a significant improvement in the modelled fluxes. Future work will be focused on refining the utilization of the observation uncertainties provided by the ESA CCI-LST product (e.g. decomposed uncertainties and spatio-temporal variability) in the assimilation process.

Winter warming of McMurdo Dry Valleys soils

Winter warming of McMurdo Dry Valleys soils

Interactive effects of nitrogen deposition and climate change on a globally rare forest geophyte

Abstract Nitrogen (N) deposition and climate change are both known to threaten global biodiversity. However, we still have a limited understanding of how interactions between these global change drivers affect individuals and populations of specialist species, such as geophytes, within their natural habitat. We explored possible interactive effects of N, drought, and warming on population vitality (mean leaf length, leaf density, flowering probability) and morpho‐physiological traits (e.g., leaf and bulb size, N allocation to leaves and bulbs) of the globally rare forest geophyte Gagea spathacea (Liliaceae) in deciduous forests of northern Germany by applying experimental N addition across a climate gradient over a 5‐year period. Mean leaf growth and leaf density were not affected by N addition but were enhanced by warmer and drier conditions in the months before leaf emergence. N addition increased N allocation of individual plants towards their subterranean bulbs. Importantly, effects of N addition on morpho‐physiological traits depended on warming and drought, with N‐fertilized plants showing increased leaf length and decreased specific leaf and bulb N concentration after drier autumns and warmer winters. This indicates that N deposition may partially compensate for increased N demands during warming‐induced growth, although this growth‐promoting interaction effect is not (yet) reflected in population vitality. Our results highlight the importance of considering multiple global environmental change drivers and a whole plant perspective (above‐ and belowground traits) to predict long‐term growth responses of (endangered) forest spring geophytes and to develop adapted long‐term protection strategies.

Influence of an abnormally cold stratospheric polar vortex on the sub-regional PM2.5 anomaly in East Asia in March of 2021

This study investigates the critical role of meteorological variability, particularly polar vortex dynamics, in shaping PM2.5 anomaly patterns across sub-regions in East Asia. Following sudden stratospheric warming (SSW) in winter, East Asia experienced significant tropospheric transitions, including cooling-to-warming shifts. The strengthening of the Mongolian high, combined with tropospheric warming, altered lower tropospheric dynamics. Contrasting warming in Mongolia and cooling to the north intensified baroclinic instability, creating anomalous Mongolian cyclones for increased dust storm activity and higher PM2.5 levels. Elevated PM2.5 concentrations in eastern China, driven by substantial anthropogenic emissions, were dispersed by the divergent flow under the Mongolian high. Cyclones with increased baroclinic instability over southern and northeastern China contributed to precipitation, which led to negative anomaly variations of PM2.5 aerosols. Downwind regions like Korea saw elevated PM2.5 anomalies due to stable lower tropospheric conditions driven by the movement of the warmed Mongolian high.

Atmospheric rivers cause warm winters and extreme heat events.

Atmospheric rivers (ARs) are narrow regions of intense water vapour transport in the Earth's atmosphere. These transient phenomena carry water from the subtropics to the mid-latitudes and polar regions1,2, making up the majority of polewards moisture transport3-5 and exerting control on the precipitation and water resources in many regions6,7. In addition to transporting moisture, ARs also transport heat, but the impact of this transport on global near-surface air temperatures has not yet been characterized. Here we show that seasons with more frequent ARs also have warmer than average temperatures in many mid-latitude regions, and that AR events are associated with temperature anomalies of 5-10 °C above the climatological mean. This is due to anomalous horizontal transport and convergence of sensible heat and moisture in the lower atmosphere, which increases both downward sensible heat flux and downwelling long-wave radiation at the surface. On an hourly timescale, over 70% of extreme warm-temperature anomalies occur within ARs in large portions of the mid-latitudes, and ARs are associated with moist and compound heatwaves in many regions worldwide, suggesting that consideration of ARs may improve predictive capability for certain extreme heat events. Our results demonstrate that ARs significantly impact air temperatures on a wide array of timescales, and that they may play a wider role in global energy transport than previously recognized.

Causes of a Lack of QBO/Solar‐MJO Connection in Certain CMIP6 Models

AbstractA connection between the quasi‐biennial oscillation (QBO), solar variability, and the short‐term convective climate oscillation, the Madden‐Julian oscillation (MJO), in boreal winter has been found in observational data, yet it is generally lacking in current global climate models (GCMs). A proposed mechanism is changes in tropical lower stratospheric upwelling rates and static stability caused by QBO and solar UV effects on extratropical wave forcing of the stratospheric residual meridional circulation (the Brewer‐Dobson circulation). The extent to which this mechanism, which operates only in boreal winter and enhances similar effects of the QBO‐induced meridional circulation, is simulated in a series of GCMs participating in the Coupled Model Intercomparison Project 6 (CMIP6) is investigated. The models are found to be often lacking complete representation of several elements of the mechanism, with particular issues being QBOs that are westerly biased and weak in the lower stratosphere, insufficient solar or QBO modulation of extratropical wave activity (the Holton‐Tan effect), too weak reductions in equatorial tropopause static stability in response to extratropical wave forcing, and MJOs that in some cases do not respond to these reductions. Through bypassing many of these deficiencies via data selection, it is demonstrated that effects on the MJO that resemble those found in observations (strengthening of the MJO following early winter sudden stratospheric warmings and during easterly QBO winters) can be simulated by a subset of the models. This supports operation of the proposed mechanism, and points to needed model improvements, although caveats exist and further work is needed.

MPI‐ESM Grand Ensemble‐Simulated Influence of the Mount Pinatubo Volcanic Eruption on Winter Climate Over the Mid‐to High‐Latitude Northern Hemisphere Continents

ABSTRACTIn this study, the effects of the Mount Pinatubo eruption on surface air temperature (SAT) over mid‐ to high‐latitude Northern Hemisphere (NH) continents in December–January–February (DJF) 1991/92 were investigated using MPI‐ESM Grand Ensemble simulations, observations and reanalysis data. The results indicated that the 1991 Mount Pinatubo eruption was not the primary cause of the SAT warming anomaly over the mid‐ to high‐latitude NH continents in DJF 1991/92. In the observations, a positive Arctic Oscillation (AO) or North Atlantic Oscillation (NAO)‐like pattern dominated the warming of Eurasia, while a Pacific North American (PNA)‐like pattern dominated the warming of North America. However, the model ensemble mean (MEM) simulated SAT and sea level pressure anomalies were much weaker over high‐latitude continents. Furthermore, by categorising the 100 MPI‐ESM Grand Ensemble simulations into four categories, we found that the probability of warm and cold temperature anomalies occurring over Eurasia and North America was nearly equal. Only about 22% of the MPI‐ESM Grand Ensemble members simulated winter warming over the mid‐ to high‐latitude NH continents that matched observations. Our study suggested that this winter warming was mostly caused by the internal variability of the climate system, which was consistent with previous studies. A more detailed analysis indicated that, following the Mount Pinatubo eruption, the intrinsic phase shifts in the AO and PNA remained key factors driving the SAT variations in Eurasia and North America, respectively.

Climate-sensitive models of tree mortality based on lifetime analysis and irregular permanent-plot remeasurements

Climate change has driven forest growth modellers to develop different climate sensitivity implementations (CSI) for their models. Among others, a model can rely on annual climate variables or average climate variables, such as 30-year normals. The novelty of this study was to develop a framework based on lifetime analysis to enable annual or average CSI in empirical models of tree mortality. Using this framework, we compared models of individual tree mortality based on an annual CSI with similar models relying on two average CSIs, one using interval-averaged climate variables, and the other, 30-year normals. We fitted these models to permanent-plot data of eight species in Ontario and tested the effects of summer and winter temperature as well as spring and summer precipitation in the models. Our results showed that the annual CSI was not superior to the average CSIs, but could be a valid alternative for some species. Warmer winter temperature was detrimental to the survival of Abies balsamea, Betula papyrifera, Picea glauca, and Pinus strobus, whereas greater spring and summer precipitation resulted in greater mortality occurrence for Picea mariana, Pinus banksiana, and Populus tremuloides. In most cases, the effects of climate variables were contrary to our initial hypotheses. We conclude that the effects of climate on tree mortality occurrence interact with other factors such as species distribution and ecophysiology.

Comparing the Atmospheric Responses to Reduced Arctic Sea Ice, a Warmer Ocean, and Increased CO2 and Their Contributions to Projected Change at 2°C Global Warming

Abstract We consider the combined and individual influences of Arctic sea ice loss, sea surface temperature (SST) warming, and the direct radiative effect of increased CO2 on the Northern Hemispheric climate. The surface climate (e.g., temperature and precipitation) and atmospheric circulation responses (e.g., sea level pressure and wind) to these drivers are quantified using simulations from the Polar Amplification Model Intercomparison Project (for sea ice loss and SST warming) and the Cloud Feedback Model Intercomparison Project (for increased CO2). We verify the linear additivity of the PAMIP-derived winter responses to sea ice loss and SST change. The responses to SST change are of greater magnitude than that due to sea ice loss or due to CO2 direct radiative forcing in most seasons and regions, excluding the Arctic. Notably, however, sea ice loss is at least as important as SST change for the winter atmospheric circulation response over the North Atlantic and Siberia. The dynamical responses to sea ice loss and SST change oppose each other in many regions in winter, while the responses to SST and CO2 direct radiative forcing are often opposing in summer. Such opposing responses are less evident for the thermodynamical response. The sum of all three responses reproduces well the spatial patterns of change at 2°C global warming in winter and autumn in phase 6 of the Coupled Model Intercomparison Project projections but overestimates their magnitude.

Cytoplasm of the Wild Species Aegilops mutica Reduces VRN1 Gene Expression in Early Growth of Cultivated Wheat: Prospects for Using Alloplasmic Lines to Breed Varieties Adapted to Global Warming.

In a warm winter due to climate warming, it is necessary to suppress early flowering of autumn-sown wheat plants. Here, we propose the use of cytoplasmic genome effects for this purpose. Alloplasmic lines, or cytoplasmic substitution lines, of bread wheat (Triticum aestivum) have cytoplasm from a related wild Aegilops species through recurrent backcrossing and exhibit altered characteristics compared with the euplasmic lines from which they are derived. Thus, alloplasmic lines with Aegilops mutica cytoplasm show delayed flowering compared with lines carrying normal cytoplasm. In the wheat flowering pathway, VERNALIZATION 1 (VRN1) encodes an APETALA1/FRUITFULL-like MADS box transcription factor that plays a central role in the activation of florigen genes, which induce floral meristems in the shoot apex. Here, we compared expression of VRN1 alleles in alloplasmic and euplasmic lines after vernalization. We found that alloplasmic wheat showed a lower level of VRN1 expression after vernalization compared with euplasmic wheat. Thus, nuclear-cytoplasm interactions affect the expression levels of the nuclear VRN1 gene; these interactions might occur through the pathway termed retrograde signaling. In warm winters, autumn-sown wheat cultivars with spring habit can pass through the reproductive growth phase in very early spring, resulting in a decreased tiller/ear number and reduced yield performance. Here, we present data showing that an alloplasmic line of 'Fukusayaka' can avoid the decrease in tiller/ear numbers during warm winters, suggesting that this alloplasmic line may be useful for development of varieties adapted to global warming.

Intercomparison of machine learning methods for statistical downscaling of daily temperature under CMIP6 scenarios: a case study from Iran

ABSTRACT General circulation models (GCM) represent a contemporary and advanced tool designed to simulate the response of climate system to alterations in greenhouse gas levels. Increasing spatial resolutions of the outputs of GCMs on a regional scale requires downscaling process. In this study, four machine learning (ML) models, namely, decision tree regression (DTR), support vector regression, artificial neural network, and K-nearest neighbors (KNN) were employed to downscale the outputs of four Coupled Model Intercomparison Project 6 climate models. The daily observations of temperature data at Nazmakan station in Kohgiluyeh and Boyer-Ahmad Province, Iran, were trained and tested for the periods 1995–2009 and 2009–2015, respectively. According to results of four metrics, DTR and KNN obtained the most valid evaluation in the training and test data, respectively. In addition, downscaling methods were used to predict future daily temperature for 2015–2045 under two Shared Socioeconomic Pathway (SSP2-4.5 and SSP5-8.5) scenarios. Mann–Kendall test results revealed an increasing trend of temperature in most of the coming years. The projected trend expects cooler summers and warmer winters in future. Furthermore, the predicted data under two climate scenarios were assessed in comparison with observed data for 2015–2022. Finally, this study demonstrates the strengths and weaknesses of nonlinear ML techniques in statistical downscaling.

Research on systematic analysis and optimization method for ice storage cooling system based on model predictive control: A case study

Ice storage systems are commonly applied for space cooling in large-scale commercial buildings to realize cost-saving effects. However, the practical operation performance is far poorer than expected. This paper conducted field tests to study the operation performance of ice storage system in a commercial building located in hot summer and warm winter area in China. Where the mismatch between ice storage capacity of chiller plant and cooling demand of buildings was found the typical issue leading to insufficient ice storage in cooling season and over ice-storage in transition season. Thus the annual average COP of Ice-storage chillers and the annual EER of whole chiller plant only reached 3.19 and 2.53 respectively, and the cooling price reached 0.194 Yuan RMB/kWh. To address this, a control strategy based on a cooling load prediction model was implemented. The model inputs the easily obtainable parameters such as ambient meteorological conditions, working/rest days, and previous cooling load data to predict the cooling demand next day, and then to guide the daily ice storage capacity during valley electricity price period, as well as the cooperation of ice melting system and direct cooling system for space cooling. Therefore, significant energy and cost-saving effects were achieved, where the cost-saving rate reached 41.9%, and the cooling price decreased to 0.111 Yuan/kWh.

Seasonal forecasts have sufficient skill to inform some agricultural decisions

Abstract Seasonal forecasts, which look several months into the future, are currently underutilized in active decision-making, particularly for agricultural and natural resource management. This underutilization can be attributed to the absence of forecasts for decision-relevant variables at the required spatiotemporal resolution and at the time when the decisions are made and a perception of poor skill by decision-makers. Addressing these constraints, we quantified the skill of seasonal forecasts in informing two agricultural decisions with differing decision timeframes and influencer variables: (a) whether to apply fertilizer in fall or wait until spring based on expected winter temperatures, and (b) drought response, such as whether to lease water based on expectations of drought. We also looked into how early the forecast can be provided without significant degradation in skill. Currently, drought response decisions are typically formulated in April, utilizing drought forecasts issued in the same month, while fall fertilization decisions are generally made between August and September. There is growing interest among stakeholders in the availability of earlier forecasts to inform these critical choices. We utilized the North American Multi-Model Ensemble (NMME) hindcasts for the time period 1982 - 2020 over the Pacific Northwest US to obtain meteorological variables. Runoff was estimated via simulations of the coupled crop-hydrology VIC-CropSyst model. The skill assessment with the Heidke Skill Score (HSS) yielded promising outcomes in both decisions for the entire Pacific Northwest region. Notably, NMME’s positive skill (median HSS of 30%) in predicting warmer winters identifies years when fertilizer application should be avoided to prevent fertilizer loss through mineralization (and associated costs). Similarly, there is skill in forecasting drought conditions in most irrigated watersheds for up to two months in advance of April, the current decision time. In conclusion, our findings affirm that contrary to the perception of low skill and resulting underutilization, current seasonal forecasts hold the potential to inform at least some key agricultural decisions.

Stratigraphy and paleontology (plant and arthropod fossils) from the Late Neogene Niguanak site, Arctic Slope, Northern Alaska

ABSTRACT Motivated by the need for more paleodata for Pliocene paleoclimate data-model comparison, we revisited unpublished investigations of a fossiliferous site on the Niguanak River in Arctic North America. Analyses of the samples indicates forested conditions during an early phase of sedimentation in which environments were perhaps similar to those near tree line in the modern Anchorage area or farther south along the Pacific coast, whereas during a later phase of sedimentation, environments were characterized by shrub tundra vegetation and were possibly similar to the present-day conditions in the interior of southern Seward Peninsula. We describe the site stratigraphy and discuss the macrofossils and pollen recovered from the sediments, their paleoecological implications, and their significance for paleoclimate and sea ice. Mean annual temperatures were found to be 12.7°C warmer than current, with a pattern of much warmer winters, and less difference in summer warming as observed at other Pliocene Arctic sites. Finally, we discuss possible age assignments for the sediments, based on regional stratigraphy and geomorphology, and the probable sequence of evolution of arctic borderland climate and ecosystems.

Cold Intermediate Water Formation in the Black Sea Triggered by March 2022 Cold Intrusions

In mid-March 2022, a Siberian High brought intense cold air masses, leading to severe weather conditions across southern Europe, including the Black Sea region. This study investigates the spatial and temporal evolution of cold intermediate water (CIW) masses in the Black Sea, with a particular focus on the successive anomalously cold episodes that occurred in March 2022. The research underscores the significance of the northwestern continental slope and cyclonic gyres, especially as the only cold-water mass observations during the warm winters of 2020 and 2021 were concentrated in these areas. Following two warm winters, the cold episodes of March 2022 revealed notable convection and simultaneous cooling, particularly in the cyclonic interior and the Rim Current periphery, excluding the northeastern periphery. Subsequently, cold waters spreading isopycnally throughout the summer months were transported laterally and reached these regions. Argo float measurements provided clear evidence of widespread replenishment of the CIW, indicating that it is not confined to specific areas. The study also highlights regional variability in the characteristics of CIW formation, which is influenced by local dynamics and preconditioning temperatures. The temperatures of CIW increased from west to east, in line with the sea surface temperature gradient. Notably, thicker and colder CIW was found in the western cyclonic gyre compared to the eastern cyclonic area. Furthermore, the study confirms that the warming trend in CIW, identified in previous research, not only continues but has intensified during the recent period analyzed. These findings, observed under the extreme conditions analyzed in this research, offer valuable insights into the widespread occurrence of CIW formation in the Black Sea. Additionally, the study confirms that the warming trend in CIW, identified in previous studies, continued in the region throughout the warm winter period and after the cold spell in 2022. These insights contribute to a deeper understanding of CIW dynamics and their response to extreme weather events in the Black Sea.

Impact of climate change on the kelp Laminaria digitata – simulated Arctic winter warming

The Arctic is seasonally exposed to long periods of low temperatures and complete darkness. Consequently, perennial primary producers have to apply strategies to maximize energy efficiency. Global warming is occurring in the Arctic faster than the rest of the globe. The highest amplitude of temperature rise occurs during Polar Night. To determine the stress resistance of the ecosystem-engineering kelp Laminaria digitata against Arctic winter warming, non-meristematic discs of adult sporophytes from Porsangerfjorden (Finnmark, Norway) were kept in total darkness at 0°C and 5°C over a period of three months. Physiological variables, namely maximum quantum yield of photosynthesis (Fv/Fm) and dry weight, as well as underlying biochemical variables including pigments, storage carbohydrates, total carbon and total nitrogen were monitored throughout the experiment. Although all samples remained in generally good condition with Fv/Fm values above 0.6, L. digitata performed better at 0°C than at 5°C. Depletion of metabolic products resulted in a constant decrease of dry weight over time. A strong decrease in mannitol and laminarin was observed, with greater reductions at 5°C than at 0°C. However, the total carbon content did not change, indicating that the sporophytes were not suffering from “starvation stress” during the long period of darkness. A decline was also observed in the accessory pigments and the pool of xanthophyll cycle pigments, particularly at 5°C. Our results indicate that L. digitata has a more active metabolism, but a lower physiological and biochemical performance at higher temperatures in the Arctic winter. Obviously, L. digitata is well adapted to Arctic Polar Night conditions, regardless of having its distributional center at lower latitudes. Despite a reduced vitality at higher temperatures, a serious decline in Arctic populations of L. digitata due to winter warming is not expected for the near future.

Antarctic extreme seasons under 20th and 21st century climate change

In this study, available large ensemble datasets in the Coupled Model Intercomparison Phase 6 (CMIP6) archive were used to provide the first multi-variate overview of the evolution of extreme seasons over Antarctica and the Southern Ocean during the 20th and 21st centuries following medium-to-high radiative forcing scenarios. The results show significant differences between simulated changes in background mean climate and changes in low (10th percentile) and high (90th percentile) extreme seasons. Regional winter warming is most pronounced for cold extremes. In summer, there are more pronounced increases in high extremes in precipitation and westerly wind during the ozone hole formation period (late 20th century), affecting coastal regions and, in particular, the Antarctic Peninsula. At midlatitudes, there is a reduction in the range of summer season wind extremes. Suggested mechanisms for these differences are provided relating to sea ice retreat and westerly jet position.

No Evidence of Winter Warming in Eurasia Following Large, Low-Latitude Volcanic Eruptions during the Last Millennium

Abstract We critically reexamine the question of whether volcanic eruptions cause surface warming over Eurasia in winter, in the light of recent modeling studies that have suggested internal variability may overwhelm any forced volcanic response, even for the very largest eruptions during the Common Era. Focusing on the last millennium, we combine model output, instrumental observations, tree-ring records, and ice cores to build a new temperature reconstruction that specifically targets the boreal winter season. We focus on 20 eruptions over the last millennium with volcanic stratospheric sulfur injections (VSSIs) larger than the 1991 Pinatubo eruption. We find that only 7 of these 20 large events are followed by warm surface temperature anomalies over Eurasia in the first posteruption winter. Examining the 13 events that show cold posteruption anomalies, we find no correlation between the amplitude of winter cooling and VSSI mass. We also find no evidence that the North Atlantic Oscillation is correlated with VSSI in winter, a key element of the proposed mechanism through which large, low-latitude eruptions might cause winter warming over Eurasia. Furthermore, by inspecting individual eruptions rather than combining events into a superposed epoch analysis, we are able to reconcile our findings with those of previous studies. Analysis of two additional paleoclimatic datasets corroborates the lack of posteruption Eurasian winter warming. Our findings, covering the entire last millennium, confirm the findings of most recent modeling studies and offer important new evidence that large, low-latitude eruptions are not, in general, followed by significant surface wintertime warming over Eurasia.

Combining a Multi-Lake Model Ensemble and a Multi-Domain CORDEX Climate Data Ensemble for Assessing Climate Change Impacts on Lake Sevan.

Global warming is shifting the thermal dynamics of lakes, with resulting climatic variability heavily affecting their mixing dynamics. We present a dual ensemble workflow coupling climate models with lake models. We used a large set of simulations across multiple domains, multi-scenario, and multi GCM- RCM combinations from CORDEX data. We forced a set of multiple hydrodynamic lake models by these multiple climate simulations to explore climate change impacts on lakes. We also quantified the contributions from the different models to the overall uncertainty. We employed this workflow to investigate the effects of climate change on Lake Sevan (Armenia). We predicted for the end of the 21st century, under RCP 8.5, a sharp increase in surface temperature and substantial bottom warming , longer stratification periods (+55days) and disappearance of ice cover leading to a shift in mixing regime. Increased insufficient cooling during warmer winters points to the vulnerability of Lake Sevan to climate change. Our workflow leverages the strengths of multiple models at several levels of the model chain to provide a more robust projection and at the same time a better uncertainty estimate that accounts for the contributions of the different model levels to overall uncertainty. Although for specific variables, for example, summer bottom temperature, single lake models may perform better, the full ensemble provides a robust estimate of thermal dynamics that has a high transferability so that our workflow can be a blueprint for climate impact studies in other systems.

Mangrove freeze resistance and resilience across a tropical‐temperate transitional zone

Abstract Freeze events govern the distribution and structure of mangrove ecosystems, especially in tropical‐temperate transitional zones. Understanding mangrove responses to freezing is crucial for predicting their poleward expansion under climate change. However, there is a need for field‐based measurements of mangrove freeze resistance and resilience. After an extreme winter storm in December 2022, we measured mangrove post‐freeze damage and recovery (January and November 2023), building on a pre‐freeze baseline assessment conducted in July 2022 across 12 sites along the temperature gradient of Florida's Gulf of Mexico coast (USA). Low‐temperature thresholds for leaf damage to Avicennia germinans, Rhizophora mangle and Laguncularia racemosa were quantified near −6, −4 and − 4°C, respectively. Thresholds for mortality were found to be near −6 to −7°C for A. germinans and −4 to −5°C for R. mangle. A threshold for loss of reproductivity in A. germinans was identified near −6 to −7°C. Resprouting was observed in all three species but limited to just one individual for R. mangle. Surviving A. germinans resprouted vigorously and had the greatest number of resprout branches, which was proportional to leaf damage. Tall A. germinans had a higher resprout percentage than short trees. Strata‐specific differences in freeze damage were most pronounced for R. mangle, with higher damage in tall versus short trees, while no difference was found between A. germinans strata. These results suggest that R. mangle population recovery may depend on the growth of short trees, while A. germinans can recover from all strata. Minimum air temperature was strongly correlated with mangrove height and above‐ground biomass. Projections of future minimum temperature and species‐specific freeze degree days predict warming winters, suggesting further mangrove development and range expansion under climate change. Synthesis: Collectively, our study advances understanding of mangrove responses to freezing and identifies low‐temperature thresholds for each species, aiding predictions of mangrove range expansion.