Search

Accelerometers are mainly used to measure the non-conservative forces at the center of mass of gravity satellites and are the core payloads of gravity satellites. All kinds of disturbances in the satellite platform and the environment will affect the quality of the accelerometer data. This paper focuses on the quality assessment of accelerometer data from the GRACE-FO satellites. Based on the ACC1A data, we focus on the analysis of accelerometer data anomalies caused by various types of disturbances in the satellite platform and environment, including thruster spikes, peaks, twangs, and magnetic torque disturbances. The data characteristics and data accuracy of the accelerometer in different operational states and satellite observation modes are analyzed using accelerometer observation data from different time periods. Finally, the data consistency of the accelerometer is analyzed using the accelerometer transplantation method. The results show that the amplitude spectral density of three-axis linear acceleration is better than the specified accuracy (above 10−1 Hz) in the accelerometer's nominal status. The results are helpful for understanding the characteristics and data accuracy of GRACE-FO accelerometer observations. [ABSTRACT FROM AUTHOR]

The atmospheric Green's function method is a technique for modeling the response of the atmosphere to changes in the spatial field of surface temperature. While early studies applied this method to changes in atmospheric circulation, it has also become an important tool to understand changes in radiative feedbacks due to evolving patterns of warming, a phenomenon called the "pattern effect." To better study this method, this paper presents a protocol for creating atmospheric Green's functions to serve as the basis for a model intercomparison project, GFMIP. The protocol has been developed using a series of sensitivity tests performed with the HadAM3 atmosphere‐only general circulation model, along with existing and new simulations from other models. Our preliminary results have uncovered nonlinearities in the response of the atmosphere to surface temperature changes, including an asymmetrical response to warming versus cooling patch perturbations, and a change in the dependence of the response on the magnitude and size of the patches. These nonlinearities suggest that the pattern effect may depend on the heterogeneity of warming as well as its location. These experiments have also revealed tradeoffs in experimental design between patch size, perturbation strength, and the length of control and patch simulations. The protocol chosen on the basis of these experiments balances scientific utility with the simulation time and setup required by the Green's function approach. Running these simulations will further our understanding of many aspects of atmospheric response, from the pattern effect and radiative feedbacks to changes in circulation, cloudiness, and precipitation. Plain Language Summary: Many properties of the atmosphere are affected by the temperature of the ocean surface. Knowing how strong these effects are would help us to better predict global warming. The response to a given surface warming depends on where the warming occurs. To account for this, researchers sometimes simulate the response to individual patches of warming and then assume the response to an arbitrary warming pattern can be summed together from these patch responses. This is sometimes called the atmospheric Green's function method, and it works well at recreating the atmospheric response to historical temperature changes. We are organizing a Green's Function Model Intercomparison Project (GFMIP), in which participants will apply the method consistently for many climate models. This paper presents the GFMIP protocol. In the course of developing this protocol, we found that the atmospheric response to warming is not proportional in all cases: the response to surface warming is not the opposite of the response to surface cooling; warming twice as much doesn't cause twice as much of a response; and making a patch of warming twice as large doesn't cause twice as large a response. GFMIP will help us figure out how to account for this nonlinearity. Key Points: The Green's Function Model Intercomparison Project (GFMIP) explores the atmospheric response to surface temperature patch perturbationsThis paper presents the GFMIP protocol, which was generated using insights from past studies and new sensitivity testsGreen's functions reconstruct the response to historical temperatures, but nonlinearities can affect responses to other warming patterns [ABSTRACT FROM AUTHOR]

Individuals' sensitivity to climate hazards is a central component of their vulnerability to climate change. In this paper, we introduce and outline the utility of a new intraindividual variability construct, affective sensitivity to air pollution (ASAP)–defined as the extent to which an individual's affective states fluctuate in accordance with daily changes in air quality. As such, ASAP pushes beyond examination of differences in individuals' exposures to air pollution to examination of differences in individuals' sensitivities to air pollution. Building on known associations between air pollution exposure and adverse mental health outcomes, we empirically illustrate how application of Bayesian multilevel models to intensive repeated measures data obtained in an experience sampling study (N = 150) over one year can be used to examine whether and how individuals' daily affective states fluctuate with the daily concentrations of outdoor air pollution in their county. Results indicate construct viability, as we found substantial interindividual differences in ASAP for both affect arousal and affect valence. This suggests that repeated measures of individuals' day-to-day affect provides a new way of measuring their sensitivity to climate change. In addition to contributing to discourse around climate vulnerability, the intraindividual variability construct and methodology proposed here can help better integrate affect and mental health in climate adaptation policies, plans, and programs. [ABSTRACT FROM AUTHOR]

Introduction: As an exceptional geographical entity, the vegetation of the Qinghai-Tibetan Plateau (QTP) exhibits high sensitivity to climate change. The Baima Snow Mountain National Nature Reserve (BNNR) is located in the southeastern sector of the QTP, serving as a transition area from sub-tropical evergreen broadleaf forest to high-mountain vegetation. However, there has been limited exploration into predicting the temporal and spatial variability of vegetation cover using anti-interference methods to address outliers in longterm historical data. Additionally, the correlation between these variables and environmental factors in natural forests with complex terrain has rarely been analyzed. Methods: This study has developed an advanced approach based on TS (Theil-Sen slope estimator) MK (Mann-Kendall test)-FVC (fractional vegetation cover) to accurately evaluate and predict the time and spatial shifts in FVC within the BNNR, utilizing the GEE (Google Earth Engine). The satellite data utilized in this paper consisted of Landsat images spanning from 1986 to2020. By integrating TS and MK methodologies to monitor and assess the FVC trend, the Hurst index was employed to forecast FVC. Furthermore, the association between FVC and topographic factors was evaluated, the partial correlation between FVC and climatic influences was analyzed at the pixel level (30×30m). Results and discussion: Here are the results of this research: (1) Overall, the FVC of the BNNR exhibits a growth trend, with the mean FVC value increasing from 59.40% in 1986 to 68.67% in 2020. (2) The results based on the TS-MK algorithm showed that the percentage of the area of the study area with an increasing and decreasing trend was 59.03% (significant increase of 28.04%) and 22.13% (significant decrease of 6.42%), respectively. The coupling of the Hurst exponent with the Theil-Sen slope estimator suggests that the majority of regions within the BNNR are projected to sustain an upward trend in FVC in the future. (3) Overlaying the outcomes of TS-MK with the terrain factors revealed that the FVC changes were notably influenced by elevation. The partial correlation analysis between climate factors and vegetation changes indicated that temperature exerts a significant influence on vegetation cover, demonstrating a high spatial correlation. [ABSTRACT FROM AUTHOR]

The rapid development of urbanization has caused obstructed urban natural ventilation and the contribution rate of urbanization is relatively high. Therefore, there is an urgent need for urban development planning that should respect natural ventilation and local climate to reduce negative impacts. By optimizing the urban construction layout to reduce obstruction and leave a passageway for wind to blow in, the natural ventilation environment could be improved. This paper presents a promising approach for natural ventilation planning at both the city and community scales. Based on the assessment of wind environment, heat island intensity, and ventilation potential, the results revealed that winds blowing from the western and northern mountainous area of Shijiazhuang play a natural ventilation inlet role which can provide clean air. The SSHI and SHI were mainly distributed within the Second Ring Road, which has a large proportion of the low ventilation potential level. Thus, six first-class ventilation corridors and thirteen secondary corridors were recommended, which were set to be adapted to the dominant wind direction. Subsequently, an urban climate analysis map (UCAnMap) was developed considering climate sensitivity, and planning recommendations were provided for different climate zones. The relationship between architectural spatial structure and ventilation efficiency was analyzed; the results revealed that increasing the height of the buildings will decrease the proportion of comfortable wind zones, and the overall ventilation efficiency will weaken, so the average building height of a typical block should be controlled within 45 m, which matches ventilation performance requirements. The ventilation efficiency of the block has a certain negative correlation with the building density, and as the building density decreased by more than 10%, the proportion of the comfortable wind zones could increase by 4–5%. [ABSTRACT FROM AUTHOR]

This paper presents a method to analyze and improve the set of equations constituting a rainfall‐runoff model structure based on a combination of a data assimilation algorithm and polynomial updates to the state equations. The method, which we have called "Data Assimilation Informed model Structure Improvement" (DAISI) is generic, modular, and demonstrated with an application to the GR2M model and 201 catchments in South‐East Australia. Our results show that the updated model generated with DAISI generally performed better for all metrics considered included Kling‐Gupta Efficiency, NSE on log transform flow and flow duration curve bias. In addition, the elasticity of modeled runoff to rainfall is higher in the updated model, which suggests that the structural changes could have a significant impact on climate change simulations. Finally, the DAISI diagnostic identified a reduced number of update configurations in the GR2M structure with distinct regional patterns in three sub‐regions of the modeling domain (Western Victoria, central region, and Northern New South Wales). These configurations correspond to specific polynomials of the state variables that could be used to improve equations in a revised model. Several potential improvements of DAISI are proposed including the use of additional observed variables such as actual evapotranspiration to better constrain internal model fluxes. Plain Language Summary: This paper presents a data‐driven method to improve rainfall‐runoff models used to generate future water resources scenario in climate change studies. The method, which we have called "Data Assimilation Informed model Structure Improvement" (DAISI) is generic, modular, and demonstrated with an application to monthly streamflow simulations over a large data set of catchments in South‐East Australia. Our results show that DAISI improves model performance for a wide range of metrics and increases the sensitivity of the model to climate inputs, which is critical in climate change scenarios. Finally, the improvements identified by DAISI take a simple mathematical form with distinct regional patterns in three sub‐regions of the study domain (Western Victoria, central region, and Northern New South Wales). Several improvements of DAISI are discussed including the inclusion of additional observed variables such as evapotranspiration to better constrain model simulations. Key Points: Data Assimilation Informed model Structure Improvement method diagnoses hydrological model structures by combining data assimilation with a polynomial update of state equationsThe method was applied to the GR2M rainfall‐runoff model with significantly improved streamflow simulations in 201 Australian catchmentsThe method identified updates to state equations with marked regional characteristics that could guide future improvement of GR2M [ABSTRACT FROM AUTHOR]

Calcium oxalate (CaOx) crystals, ubiquitous in numerous plant families, have emerged as fascinating and complex structures with far-reaching implications in plant physiology, ecology, and human health. This paper encapsulates a comprehensive exploration of CaOx crystals, beginning with their formation and physiological role within plants, to their larger ecological implications, and finally, their impact on human society. Recent research has elucidated key genes involved in CaOx crystal formation, as well as the crystals' diverse physiological roles, including their function in calcium regulation, defense against herbivory, and potential contributions to carbon sequestration. We also highlight the ecological significance of CaOx crystals in nutrient cycling and plant-soil interactions, and the potential hazards posed by these crystals in human nutrition, particularly in the context of oxalate-rich diets and kidney stone formation. Despite significant advances, many aspects, particularly their ecological impacts and potential role in climate change mitigation, remain under-explored, necessitating future research. [ABSTRACT FROM AUTHOR]

• Machine learning (ML) techniques were pioneered to analyze non-linear relationships. • Algorithm's predictive power validated ML models, preventing spurious relations. • Recursive feature elimination explored predictor importance. • Presence of non-linear relationships is suggested, advising further investigation. • Acknowledgment of skepticism stresses rigorous analysis for long-term correlations. The Earth's climate is a complex system that can be influenced by various internal and external factors. Previous research has explored the relationship between climate and external forcings such as solar activity and GCR. However, the relations are intricate and intertwined into almost chaotic meteorological measurements. This paper delves deeper into understanding their interactions. GCR flux, Sunspot number (SSN), total solar irradiance (TSI), UV irradiance (UVI), and the Oceanic Niño Index (ONI) are the predictor variables, while total cloud amount (TCA) and low cloud amount (LCA) are the response variables. The analysis begins with standard statistical techniques and continues with multiple regression models including random forest, which is a machine learning (ML) method that can be used for non-linear regression. Subsequently, Recursive Feature Elimination (RFE) is employed to scrutinize the correlation among the predictor parameters. In the ML model, the final 25% of the dataset is held out and tested for validation, so, the predictive power of the algorithm is measured. Both geographical and temporal patterns have been investigated. This study suggests that a non-linear relationship might exist between the parameters, and should be investigated further, particularly in specific regions of the world. [ABSTRACT FROM AUTHOR]

Many of the implications of climate change for Aotearoa (New Zealand) remain unclear. To identify so-far unseen or understudied threats and opportunities related to climate change we applied a horizon-scanning process. First, we collated 171 threats and opportunities across our diverse fields of research. We then scored each item for novelty and potential impact and finally reduced the list to ten threats and ten opportunities through a prioritisation process. Within the 20 items presented in this paper, we uncover a range of climate-related costs and benefits. Unexpected opportunities evolve from economic reorganisation and changes to perspectives. The threats we highlight include the overall failure to interconnect siloed policy responses, as well as those relating to extreme events and feedbacks, as well as pressures that undermine the coherence of society. A major theme of our work is that climate change effects in Aotearoa are likely to transgress the boundaries of research disciplines, industry sectors and policy systems, emphasising the importance of developing transdisciplinary methods and approaches. We use this insight to connect potential responses to climate change with Aotearoa's culture and geography. [ABSTRACT FROM AUTHOR]

This paper evaluates the relation between rockfall events and weather conditions for two regions in Norway – Romsdalen and Gudbrandsdalen and explores how rockfall frequency might change with future climate conditions. Our analysis focuses on understanding the relationship between rockfall occurrence and effective water inputs, including rainfall and snow melt, and temperature oscillations both in cold conditions (freeze-thaw cycles) and in warm conditions (hot-cold cycles). To accomplish this, regional weather data and rockfall information in the Norwegian Mass Movement Database have been employed. Our results indicate that temperature oscillations might be better suited than effective water input to depict the occurrence of rockfalls in the two study areas in Norway. Freeze-thaw cycles are most frequent during winter and spring, and hot-cold cycles are most frequent during summer. Climate change will affect rockfall seasonality and the frequency in which freeze-thaw cycles and hot-cold cycles are observed. Thus, altering the exposure of population and infrastructures to rockfalls. [ABSTRACT FROM AUTHOR]

Old plant communities are of utmost importance for nature conservation, carbon sequestration, as well as gene pool maintenance. Shrub populations occurring in extreme environments beyond abiotic tree-lines provide diverse ecosystem services and have potential as proxy archives because they often inhabit areas with scarce and short instrumental records. We provide dendrochronological insight into one such population made up of prostrate Juniperus communis shrubs in the northern Scandinavian tundra (Norway), growing on a competition-free boulder field. We dated and provided a growth chronology of the oldest living shrub population (190 ± 148 years) from Scandinavia with the oldest individual being 683 years old. This is a conservative estimate, as shrubs in extreme environments do not form even a single row of cells in some years. The cross-dating issues of poorly growing shrubs do not fully allow to rely on climate sensitivity of the juniper population studied, although the species' potential for dendroclimatological reconstructions is generally considered high, also because the common juniper is an abundant woody species distributed globally. Old populations present an important gene source in plant recruitment, particularly in the context of the present environmental change. [ABSTRACT FROM AUTHOR]

Designing effective spatial management strategies is challenging because marine ecosystems are highly dynamic and opaque, and extractive entities such as fishing fleets respond endogenously to ecosystem changes in ways that depend on ecological and policy context. We present a modelling framework, marlin, that can be used to efficiently simulate the bio‐economic dynamics of marine systems in support of both management and research. We demonstrate marlin's capabilities by focusing on two case studies on the conservation and food production impacts of marine protected areas (MPAs): a coastal coral reef and a pelagic tuna fishery. In the coastal coral reef example, we explore how heterogeneity in species distributions and fleet preferences can affect distributional outcomes of MPAs. In the pelagic case study, we show how our model can be used to assess the climate resilience of different MPA design strategies, as well as the climate sensitivity of different fishing fleets. This paper demonstrates how intermediate complexity simulation of coupled bio‐economic dynamics can help communities predict and potentially manage trade‐offs among conservation, fisheries yields and distributional outcomes of management policies affected by spatial bio‐economic dynamics. [ABSTRACT FROM AUTHOR]

Trees are a prominent feature of urban ecosystems. Urban tree productivity is a key component of urban ecosystem energetics and has been identified as a possible pathway for reducing global greenhouse gas concentrations. Recently, extensive research has been directed to evaluating the carbon dynamics of urban trees in cities throughout the world. Here, we synthesize this research, using results from previous studies from 154 cities to identify the distribution of urban tree productivity globally and the basis for generating urban tree productivity estimates. Reported urban tree productivity shows a strong relationship with estimated tree carbon content and exhibits increases with both temperature and precipitation, with land cover differences influencing the degree of climate sensitivity. Compared with a reference productivity estimate, urban trees showed greatly reduced estimated rates of productivity and the magnitude of reduced productivity was inversely correlated with precipitation but was independent of temperature. Reported rates of productivity across all studies suggest climate restrictions that are more important with less intensively managed land covers. Scaling these results globally suggests a limited opportunity for urban trees to contribute to atmospheric carbon dioxide reductions, especially in the absence of major carbon emission reductions. We found that the majority of results are derived from tree inventories from a single period with rates of productivity estimate through quasi-empirical or allometric models. The majority of studies have been conducted in temperate biomes and North America. These results show that existing urban tree assessments have substantial methodological restrictions and regional biases. Future research of urban tree productivity should look toward improved methods and can use this synthesis as a baseline for comparisons and improvement. [ABSTRACT FROM AUTHOR]

LAND degradation is one of the most important consequences of climate change that has socioeconomic repercussions world-wide, particularly in Egypt's Nile Delta region. It is therefore essential to inform of timely measurements of land degradation and identify its causes for the security of populations living on and near the Nile Delta. This paper calculates the Environmental Sensitivity Index using the MEDALUS-GEE (Mediterranean Desertification and Land Use in the Google Earth Engine) approach within two of Egypt's most climate-affected governorates, Alexandria and Beheira, on the district level. Results show that most of the districts in Alexandria is highly sensitive to climate change and is unsuitable for farming owing to their proximity to the Mediterranean Sea. The rise in sea level leads to the submergence of many lands. Besides, as a result of the geological composition of the region, seawater seeps into groundwater, all of which in turn was reflected in the rise in soil salinity. Also, the highest degree of land degradation and/or desertification was found in the hinterland of the Beheira Governorate, including high soil salinity and groundwater, which makes it difficult to undertake land reclamation and cultivation. Hence, the study suggests a crop suitability plan for the areas under study, particularly those highly subjected to land degradation and desertification. [ABSTRACT FROM AUTHOR]

The Pliocene Model Intercomparison Project (PlioMIP) was initiated in 2008. Over two phases PlioMIP has helped co-ordinate the experimental design and publication strategy of the community, which has included an increasing number of climate models and modelling groups from around the world. It has engaged with palaeoenvironmental scientists to foster new data synthesis supporting the construction of new model boundary conditions, as well as to facilitate new data-model comparisons. The work has advanced our understanding of Pliocene climates and environments, enhanced our knowledge regarding the ability of complex climate and Earth System models to accurately simulate climate change, and helped to refine our estimates of how sensitive the climate system is to forcing conditions. In this community protocol paper, we outline the scientific plan for PlioMIP Phase 3 (PlioMIP3). This plan provides the required guidance to participating modelling groups from around the world to successfully set up and perform PlioMIP3 climate model experiments. The project is open to new participants from the scientific community (both from the climate modelling and geosciences communities). In PlioMIP3, we retain the PlioMIP2 Core experiments (Eoi 400 , E 280 ) and extend the Core requirements to include either an experiment focussed on the Early Pliocene or an alternative Late Pliocene simulation (or both). These additions (a) allow a comparison of Early and Late Pliocene warm intervals and help build research connections and synergy with the MioMIP (Miocene Model Intercomparison Project - also known as DeepMIP-Miocene) and PlioMioVAR projects (Pliocene-Miocene Variability Working Group), and (b) create an alternative time slice simulation for 3.205 Ma (MIS KM5c) through removal of some of the largest palaeogeographic differences introduced between PlioMIP1 and 2 resulting in minimal land-sea mask variations from the modern. In addition, we present ten optional experiments designed to enhance our assessment of climate sensitivity and to explore the uncertainty in greenhouse gas-related forcing. For the first time, we introduce orbital sensitivity experiments into the science plan, as well as simulations incorporating dynamic vegetation-climate feedbacks and an experiment designed to examine the potential significance of East Antarctic Ice Sheet boundary condition uncertainty. These changes enhance palaeo-to-future scientific connections and enable an exploration of the significance of palaeogeographic uncertainties on climate simulations. • This paper presents the community agreed science plan for the 3rd phase of the Pliocene Model Intercomparison Project (PlioMIP3). • Experiments are prioritised/designed to enhance our knowledge of Pliocene and its use in understanding future climate change. • Guidance on model set-up, timescales, format of the model outputs and where these should be stored is outlined. • Information for modelling groups to access the required boundary conditions underpinning model experiments is provided. • Linkages between the climate modelling effort and ongoing co-ordinated geological proxy synthesis is described. [ABSTRACT FROM AUTHOR]

The supercooled liquid fraction (SLF) in mixed-phase clouds (MPCs) is an essential variable of cloud microphysical processes and climate sensitivity. However, the SLF is currently calculated in spaceborne remote sensing only as the cloud phase–frequency ratio of adjacent pixels, which results in a loss of the original resolution in observations of cloud liquid or ice content within MPCs. Here, we present a novel method for retrieving the SLF in MPCs based on the differences in radiative properties of supercooled liquid droplets and ice particles at visible (VIS) and shortwave infrared (SWI) channels of the geostationary Himawari-8. Liquid and ice water paths are inferred by assuming that clouds are composed of only liquid or ice, with the real cloud water path (CWP) expressed as a combination of these two water paths (SLF and 1-SLF as coefficients), and the SLF is determined by referring to the CWP from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The statistically relatively small cloud phase spatial inhomogeneity at a Himawari-8 pixel level indicates an optimal scene for cloud retrieval. The SLF results are comparable to global SLF distributions observed by active instruments, particularly for single-layered cloud systems. While accessing the method's feasibility, SLF averages are estimated between 74 % and 78 % in Southern Ocean (SO) stratocumulus across seasons, contrasting with a range of 29 % to 32 % in northeastern Asia. The former exhibits a minimum SLF around midday in summer and a maximum in winter, while the latter trend differs. This novel algorithm will be valuable for research to track the evolution of MPCs and constrain the related climate impact. [ABSTRACT FROM AUTHOR]

The ongoing biodiversity crisis is strongly threatening amphibians, mostly because of their peculiar physiology, their sensitivity to climate change and the spread of diseases. Effective monitoring involving assessments of pressure effects across time and estimation of population trends play a key role in mitigating amphibian decline. To improve implementation of standardized protocols and conservation efforts, we present here a dataset related to one of the amphibian genera whose onservation status is considered the most declining according to the IUCN. We report information on 66 populations of the endangered European cave salamanders, genus Speleomantes, that was collected through a standardized monitoring along a four-year period (2021–2024). Demographics data of the populations and fitness-related data of single individuals are reported. Furthermore, we include 3,836 high quality images of individuals that can allow to perform studies aiming to assess the phenotypic variability within the genus, and to perform long-term capture-mark-recaptured studies. [ABSTRACT FROM AUTHOR]

Accurately representing mixed‐phase clouds (MPCs) in global climate models (GCMs) is critical for capturing climate sensitivity and Arctic amplification. Secondary ice production (SIP), can significantly increase ice crystal number concentration (ICNC) in MPCs, affecting cloud properties and processes. Here, we introduce a machine‐learning (ML) approach, called Random Forest SIP (RaFSIP), to parameterize SIP in stratiform MPCs. RaFSIP is trained on 16 grid points with 10‐km horizontal spacing derived from a 2‐year simulation with the Weather Research and Forecasting (WRF) model, including explicit SIP microphysics. Designed for a temperature range of 0 to −25°C, RaFSIP simplifies the description of rime splintering, ice‐ice collisional break‐up, and droplet‐shattering using only a limited set of inputs. RaFSIP was evaluated offline before being integrated into WRF, demonstrating its stable online performance in a 1‐year simulation keeping the same model setup as during training. Even when coupled with the 50‐km grid spacing domain of WRF, RaFSIP reproduces ICNC predictions within a factor of 3 when compared to simulations with explicit SIP microphysics. The coupled WRF‐RaFSIP scheme replicates regions of enhanced SIP and accurately maps ICNCs and liquid water content, particularly at temperatures above −10°C. Uncertainties in RaFSIP minimally impact surface cloud radiative forcing in the Arctic, resulting in radiative biases under 3 Wm−2 compared to simulations with detailed microphysics. Although the performance of RaFSIP in convective clouds remains untested, its adaptable nature allows for data set augmentation to address this aspect. This framework opens possibilities for GCM simplification and process description through physics‐guided ML algorithms. Plain Language Summary: Being able to correctly simulate the amount of ice and liquid in clouds is essential for accurate predictions of the cloud radiative forcing in the climatologically sensitive polar regions. A number of collisional processes between ice and liquid particles in clouds, known as secondary ice production, can significantly enhance the ice crystal number concentrations contained in them. This enhancement is often accompanied by a decrease in the cloud liquid water content, resulting in less opaque clouds to incoming solar radiation, which, in turn, can cause a cloud‐induced warming at the surface. Currently most global climate models are missing the description of the most important secondary ice production processes, which can lead to a biased radiative impact of clouds at the surface. To address this, we propose using a machine learning algorithm trained on high‐resolution model outputs to include the effect of ice multiplication in large‐scale climate models. The machine learning framework effectively captures the physical processes underlying secondary ice production in stratiform clouds using only a few inputs readily available in model frameworks. This approach has the potential to improve model predictions bringing them closer to the observed cloud phase partitioning. Key Points: A random‐forest parameterization for secondary ice production is developed using outputs from a 10‐km horizontal grid spacing simulationCloud phase partitioning agrees within a factor of 3, with radiative biases below 3 Wm−2 compared to the detailed microphysics simulationThe scheme can be adjusted to coarser resolutions typical of climate models without losing computational efficiency and numerical stability [ABSTRACT FROM AUTHOR]

Basic ecological theory suggests that a tradeoff between competitiveness and stress tolerance dictates species range limits at regional extents. However, empirical support for this key theory remains deficient because the necessary spatial and temporal coverage and scalability of field observations has rarely been achieved. We harnessed an extensive dendroecological network (> 22 000 tree‐ring samples from 816 forest inventory plots) to disentangle competition‐limited from climate‐limited growth in both overstory and understory trees. Growth synchrony among trees thereby served as an integral metric of climate sensitivity, an approach that we justify in supplementary analyses of growth responses to temperature, precipitation, and the standardized precipitation‐evapotranspiration index. Sampling plots were arranged along elevational climate and vegetation gradients throughout the Carpathian Mountains, ranging from mixed‐species lowland forests to coniferous forests at high elevations. With mixed‐effect modelling, we also identified non‐climatic factors (stand characteristics, species diversity, and disturbance history) that modulate spatial patterns in the growth rate and synchrony of European beech Fagus sylvatica and Norway spruce Picea abies. Beech exhibited reduced growth and increased climate sensitivity towards higher elevations but performed better when species diversity was higher. The growth of spruce increased towards its lower range boundary, but understory cohorts grew poorly under interspecific competition. Overall, climate sensitivity was lower in more productive stands with benign climatic conditions and in recently disturbed sites with reduced stand density. These contrasting performances at mid‐elevations where the two species overlap (900–1300 m a.s.l.) reflect their evolutionary history, which enables them to be competitive (beech) or cold‐stress tolerant (spruce). This history will affect interactions between the two species under climate warming and shape macroecological patterns in the Carpathian ecoregion and likely other parts of Europe. Our findings point to a growing advantage of competitively stronger species in montane and subalpine vegetation zones. [ABSTRACT FROM AUTHOR]

In this paper, a CdTe photovoltaic double-skin ventilated window integrated with vacuum glazing (VPV-DSV) is proposed. The mathematical model of VPV-DSV was developed and validated through tests in Hefei, China. Annual energy performance and the economic analysis of the VPV-DSV was evaluated and compared with the other two PV-DSVs and an insulating glazed window (IG) under climate conditions of five selected cities, including Changchun, Hefei, Kunming, Shenzhen, and Shijiazhuang. Moreover, effects of window design factors, including the window-to-wall ratio, PV coverage, and pillar spacing of the VG, were explored. Results indicated that: (1) the VPV-DSV produced the best energy saving results and the least energy consumption. (2) NECs of the VPV-DSV in the five cities above was 955.05 kW•h, 464.31 kW•h, 110.66 kW•h, 53.71 kW•h, and 443.14 kW•h, respectively. (3) Due to high cost of the VG, the VPV-DSV only had the best economic performance in Shenzhen and the NPV was 3931.47 CNY. (4) The WWR and PV coverage had obvious impacts on the overall performance of the VPV-DSV, while the pillar spacing only had a more significant impact on the air conditioning energy consumption. [ABSTRACT FROM AUTHOR]

CO2 absorbs and emits radiation, which allows it to act both as radiative forcing and feedback. Recent work has shown CO2's feedback effect becomes dominant in hothouse climates, giving rise to a non‐monotonic climate sensitivity around 310 K. However, CO2's feedback effect in colder climates is less clear. We use a line‐by‐line model to explore the CO2‐dependence of the longwave clear‐sky feedback and identify a dividing temperature. Above 290 K, feedback increases with CO2 concentration; below 290 K, feedback decreases with CO2 concentration. We explain this dependence in terms of spectral competition under CO2 increases. In hot climates, CO2's moderate feedback replaces near‐zero feedback from the H2O bands; in cold climates, CO2's moderate feedback replaces the large feedback from the surface. Given that global mean temperature is currently close to 290 K, our results suggest that feedback CO2‐dependence is weak at present but can be important in past and future climates. Plain Language Summary: CO2 traps heat, causing warming. But CO2 also emits heat to space, acting as radiative feedback. Recent work has shown CO2's feedback effect crucially helps to stabilize very hot climates, but how does it affect present‐day Earth? We show that in hot climates, more CO2 increases Earth's feedback, while in cold climates, more CO2 decreases it. To understand why, we explain that the surface is an effective emitter, CO2 is a moderate emitter, while H2O is a poor emitter. At high temperatures, adding CO2 to the atmosphere thus replaces feedback that would have otherwise come from H2O, increasing the overall feedback; at low temperatures, adding CO2 replaces feedback that would have otherwise come from the surface, decreasing the overall feedback. Currently, Earth's global‐mean temperature falls between these two temperature regimes, where CO2's effect on feedback is nearly zero. Our results explain why CO2's impact on feedback is small now but can be significant in past or future climates. Key Points: An increase in CO2 concentration strengthens Earth's feedback in hot climates, ∂λ/∂CO2 > 0, but weakens it in colder climates, ∂λ/∂CO2 < 0Whether feedback CO2‐dependence, ∂λ/∂CO2, is positive or negative primarily depends on the extent of the H2O windowFeedback CO2‐dependence and forcing temperature‐dependence, ∂λ/∂CO2 = −∂F2x/∂Ts, can be important for past or future climates [ABSTRACT FROM AUTHOR]

The observed Southern Ocean sea surface temperature (SST) has experienced prominent inter-decadal variability nearly in phase with the Inter-decadal Pacific Oscillation (IPO), but less associated with the Atlantic Multidecadal Variability (AMV), challenging the prevailing view of Pacific-Atlantic synergistic effects. Yet, the mechanisms of distinct trans-hemispheric connections to the Southern Ocean remain indecisive. Here, by individually constraining the observed cold-polarity and warm-polarity IPO and AMV SSTs in a climate model, we show that the IPO is influential in initiating a basin-wide Southern Ocean response, with the AMV secondary. A tropical Pacific-wide cooling triggers a basin-scale Southern Ocean cold episode through a strong Rossby wave response to the north-to-south cross-equatorial weakened Hadley circulation. By contrast, due to the competing role of tropical Pacific cooling, an Atlantic warming partly cools the Southern Ocean via a weak Rossby wave response to the south-to-north cross-equatorial enhanced Hadley circulation. Conversely, tropical Pacific warming leads to a warm Southern Ocean episode. Our findings highlight that properly accounting for the tropical Pacific SST variability may provide a potential for skillful prediction of Southern Ocean climate change and more reliable estimates of climate sensitivity, currently overestimated by the misrepresented Southern Ocean warming. [ABSTRACT FROM AUTHOR]

Most climatic and glaciological processes exhibit internal variability, which is omitted from many ice sheet model simulations. Prior studies have found that climatic variability can change ice sheet sensitivity to the long-term mean and trend in climate forcing. In this study, we use an ensemble of simulations with a stochastic large-scale ice sheet model to demonstrate that variability in frontal ablation of marine-terminating glaciers changes the mean state of the Greenland Ice Sheet through noise-induced drift. Conversely, stochastic variability in surface mass balance does not appear to cause noise-induced drift in these ensembles. We describe three potential causes for noise-induced drift identified in prior statistical physics literature: noise-induced bifurcations, multiplicative noise, and nonlinearities in noisy processes. Idealized simulations and Reynolds decomposition theory show that for marine ice sheets in particular, noise-induced bifurcations and nonlinearities in variable ice sheet processes are likely the cause of the noise-induced drift. We argue that the omnipresence of variability in climate and ice sheet systems means that the state of real-world ice sheets includes this tendency to drift. Thus, the lack of representation of such noise-induced drift in spin-up and transient ice sheet simulations is a potentially ubiquitous source of bias in ice sheet models. [ABSTRACT FROM AUTHOR]

Purpose: The growing awareness of climate risks associated with food safety issues has drawn the attention of stakeholders urging the food industry to carry out a sustainable food safety management system (FSMS). This study aims to investigate whether the critical success factors (CSFs) of sustainable FSMS can contribute to achieving climate neutrality, and how the adoption of FSMS 4.0 supported by the Industry Revolution 4.0 (IR 4.0) technologies moderates the impact of the CSFs on achieving climate neutrality. Design/methodology/approach: Survey data from 255 food production firms in China and Vietnam were utilised for the empirical analysis. The research hypotheses were examined using structural equations modelling (SEM) with route analysis and bootstrapping techniques. Findings: The results show that top management support, human resource management, infrastructure and integration appear as the significant CSFs that directly impact food production firms in achieving climate neutrality. Moreover, the results demonstrate that the adoption of FSMS 4.0 integrated with the three components (ecosystems, quality standards and robustness) significantly moderates the impact of the CSFs on achieving climate neutrality with lower inputs in human resources, infrastructure investment, integration and external assistance, and higher inputs in strengthening food safety administration. Originality/value: This study provides empirical findings that fill the research gap in understanding the relationship between climate neutrality and the CSFs of sustainable FSMS while considering the moderating effects of the FSMS 4.0 components. The results provide theoretical and practical insights into how the food production sector can utilise IR 4.0 to attain sustainable FSMS for achieving climate neutrality. [ABSTRACT FROM AUTHOR]

We present the role of CO 2 forcing in controlling Late Pliocene sea surface temperature (SST) change using six models from Phase 2 of the Pliocene Model Intercomparison Project (PlioMIP2) and palaeoclimate proxy data from the PlioVAR working group. At a global scale, SST change in the Late Pliocene relative to the pre-industrial is predominantly driven by CO 2 forcing in the low and mid-latitudes and non-CO 2 forcing in the high latitudes. We find that CO 2 is the dominant driver of SST change at the vast majority of proxy data sites assessed (17 out of 19), but the relative dominance of this forcing varies between all proxy sites, with CO 2 forcing accounting for between 27 % and 82 % of the total change seen. The dearth of proxy data sites in the high latitudes means that only two sites assessed here are predominantly forced by non-CO 2 forcing (such as changes to ice sheets and orography), both of which are in the North Atlantic Ocean. We extend the analysis to show the seasonal patterns of SST change and its drivers at a global scale and at a site-specific level for three chosen proxy data sites. We also present a new estimate of Late Pliocene climate sensitivity using site-specific proxy data values. This is the first assessment of site-specific drivers of SST change in the Late Pliocene and highlights the strengths of using palaeoclimate proxy data alongside model outputs to further develop our understanding of the Late Pliocene. We use the best available proxy and model data, but the sample sizes remain limited, and the confidence in our results would be improved with greater data availability. [ABSTRACT FROM AUTHOR]

To reveal the characteristics and environmental indications for the combination of the grain size and magnetic susceptibility of coastal sediments, we provided a necessary basis for further study on their genetic mechanisms. Based on the data of grain size and magnetic susceptibility of the 36.10 m long core 07SR01 sediments in the Xiyang tidal channel of western South Yellow Sea, we analyzed their variations and correlations and further revealed their environmental indications and corresponding regional sedimentary evolution via the combination of the aforementioned analysis results, the reinterpretation results of the sedimentary sequence and the age of core 07SR01 and shallow seismic profiles, and the findings of climate and glacial–eustatic cycles during Late Quaternary. The three stages of the sedimentary evolution of the Xiyang tidal channel between marine isotope stage (MIS) 7 and MIS 5 were summarized as follows: First is the stage of marginal bank and riverbed developments in the tidal estuary under a relatively high sea level and strong hydrodynamic conditions during MIS 7 (core section: 36.10–26.65 m). The sediments deposited in this stage were mainly affected by the paleo-Changjiang River and characterized by a coarse grain size (mean: 4.02 Φ) and relatively high magnetic susceptibilities (mean: 27.06 × 10−8 m3·kg−1), with small fluctuations which were strongly and positively correlated with the sand component. Second is the stage dominated by fluviolacustrine and littoral environments with the weak hydrodynamics during MIS 6–5, in which the climate changed from cold and dry to warm and humid as the sea level rose after a drop (core section: 26.65–15.77 m). The sediments deposited in this stage were characterized by a fine grain size (mean: 5.27 Φ) and low magnetic susceptibilities with minor variations (mean: 10.83 × 10−8 m3·kg−1) which were weakly and positively correlated with the coarse silt component. Third is the stage of delta front in the tidal estuary with a relatively high sea level and strong hydrodynamics during MIS 5 (core section: 15.77–0 m). The sediments deposited in this stage were strongly influenced by the paleo-Yellow River and characterized by a relatively coarse grain size (mean: 4.86 Φ), and high magnetic susceptibilities (mean: 37.15 × 10−8 m3·kg−1) with large fluctuations which were weakly and positively correlated with the sand and coarse silt components. [ABSTRACT FROM AUTHOR]

Research simultaneously examining building energy consumption and outdoor thermal comfort within urban environments remains limited. Few studies have delved into the sensitivity of design parameters based on building energy consumption and outdoor thermal comfort. The purpose of this study is to investigate the correlations between urban morphological design parameters and performance indicators, focusing on building energy consumption and outdoor thermal comfort (UTCI), across different urban block layouts in hot-humid regions, like Guangzhou. By establishing six fundamental morphological models—three individual unit layouts and three group layouts—the research explores both control and descriptive parameters through extensive simulation studies. Scatter plot visualizations provide insights into the impacts of various design parameters on energy consumption and UTCI, facilitating a comprehensive analysis of trends and quantitative relationships. Additionally, the study conducts sensitivity analyses on design parameters under different layout conditions to highlight their influences on target performance indicators. The findings reveal common trends, such as the significant impacts of plan dimensions and the Floor Area Ratio (FAR) on energy efficiency and outdoor comfort, as well as differential patterns, such as the varying sensitivities of the Shape Factor (S/V) and the Sky View Factor (SVF), across individual and collective layouts. Ultimately, this study offers a nuanced understanding of urban block morphology's role in creating sustainable, comfortable, and energy-efficient urban environments, providing valuable guidelines for urban form design in hot-humid climates. [ABSTRACT FROM AUTHOR]

In the field of climate-change research a lot of effort is devoted to the 'narrowing down' of uncertainties in the estimation of the (fast-feedback) Equilibrium climate sensitivity (ECS), the mean global warming as a result of a doubling of the CO2 concentration in the atmosphere, in order to improve the predictability of the Earth climate system to determine required future greenhouse-gas mitigation targets. A recent update of this quantity was provided by Hansen et al. (2023), reporting a value of 4.8 °C ± 1.2 °C for doubled CO2. This outcome is based on a variety of paleo-climate information to overcome limitations of the present, mainly model-based, "best estimate" of about 3 °C (IPCC AR6, 2021). Applying the formal framework of feedback analysis, originating in electrical engineering and control systems, the present study sets out to explore possible consequences of this high-end ECS update for the long-term Earth system sensitivity (ESS), taking into account 'slow' feedbacks by ice sheets and trace gases in a warming world (according to the recent Hansen study for today's GHGs concentrations in the atmosphere likely leading to 10 °C equilibrium global warming). As a result, principal scaling relations between variations in the fast-feedback ECS and slow-feedback ESS are derived, primarily focusing on a better mechanistic understanding of interactions in (besides merely improving the predictability of) the Earth climate system. These scaling relations may be applied to determine the equilibrium global warming eventually to be expected for a specified CO2 amount in the atmosphere. As an illustration, implications for the current geopolitical approach, aiming at 1.5 or at most 2 degrees Celsius of global warming as required by the Paris agreement—while we already seem to be on a 10 degrees track because of warming in the pipeline—are analyzed. [ABSTRACT FROM AUTHOR]

Degrading rock wall permafrost was found responsible for the increase in rockfall and landslide activity in several cold mountain regions across the globe. In Greenland, rock wall permafrost has so far received little attention from the scientific community, despite mountains being a predominant feature on the ice-free coastline and landslide activity being significant. In this study, we aim to make a first step towards a better understanding of rock wall permafrost in Greenland by modelling rock wall temperatures in the mountain area around the town of Sisimiut, which is 68° N on the west coast of Greenland. We first acquire rock surface temperature (RST) data for the period September 2020–September 2022 to model rock surface temperatures from weather forcing. The model is then applied to weather data from 1870 to 2022, generating rock surface temperatures to force transient heat transfer simulations over the same period. By extrapolating this method at the landscape scale, we obtain permafrost distribution maps and ad hoc simulations for complex topographies. Our model results are compared to temperature data from two lowland boreholes (100 m depth) and geophysical data describing frozen and unfrozen conditions across a mid-elevation mountain ridge. Finally, we use regional carbon pathway scenarios 2.6 and 8.5 to evaluate future evolution of rock wall temperatures until the end of the 21st century. Our data and simulation describe discontinuous permafrost distribution in rock walls up to roughly 400 m a.s.l. Future scenarios suggest a decline of deep frozen bodies up to 800 m a.s.l., i.e. the highest summits in the area. In summary, this study depicts a picture of warm permafrost in this area, highlighting its sensitivity to ongoing climate change. [ABSTRACT FROM AUTHOR]

Lake Victoria, which is bordered by Uganda, Tanzania, Kenya, and has a catchment that extends to Rwanda and Burundi, is home to the largest human population surrounding any lake in the world and provides critical resources across eastern Africa. Lake Victoria is also the world's largest tropical lake by surface area, but it is relatively shallow and without a major inlet, making it very sensitive to changes in climate, and especially hydroclimate. Furthermore, its size creates abundant habitats for aquatic fauna, including the iconic hyper-diverse cichlids, and serves as a major geographic barrier to terrestrial fauna across equatorial Africa. Given Lake Victoria's importance to the eastern African region, its sensitivity to climate, and its influences on terrestrial and aquatic faunal evolution and dispersal, it is vital to understand the connection between the lake and regional climate and how the lake size, shape, and depth have changed through its depositional history. This information can only be ascertained by collecting a complete archive of Lake Victoria's sedimentary record. To evaluate the Lake Victoria basin as a potential drilling target, ∼ 50 scientists from 10 countries met in Dar es Salaam, Tanzania, in July 2022 for the International Continental Scientific Drilling Program (ICDP)-sponsored Lake Victoria Drilling Project (LVDP) workshop. Discussions of the main scientific objectives for a future drilling project included (1) recovering the Pleistocene and Holocene sedimentary records of Lake Victoria that document the dynamic nature of the lake, including multiple lacustrine and paleosol sequences; (2) establishing the chronology of recovered sediments, including using extensive tephra fingerprinting and other techniques from deposits in the region; (3) reconstructing past climate, environment, lacustrine conditions, and aquatic fauna, using an integrated multi-proxy approach, combined with climate and hydrologic modeling; and (4) connecting new records with existing sedimentary snapshots and fossils exposed in deposits around the lake, tying archaeological, paleontological, sedimentological, tectonic, and volcanic findings to new drilling results. The LVDP provides an innovative way to address critical geological, paleontological, climatological, and evolutionary biological questions about Quaternary to modern landscapes and ecosystems in eastern Africa. Importantly, this project affords an excellent opportunity to help develop conservation and management strategies for regional responses to current and future changes in climate, land use, fisheries, and resiliency of at-risk communities in equatorial Africa. [ABSTRACT FROM AUTHOR]

New satellite missions promise global reductions in the uncertainties in aerosol optical properties, but it is unclear how those reductions will propagate to uncertainties in the shortwave (SW) direct aerosol radiative effect (DARE) and direct aerosol radiative forcing (DARF), which are currently large, on the order of at least 20 %. In this work, we build a Monte Carlo framework to calculate the impact of uncertainties in aerosol optical depth (AOD), single scattering albedo (SSA), and the asymmetry parameter on the uncertainty in shortwave DARE and DARF. This framework uses the results of over 2.3 million radiative transfer simulations to calculate global clear-sky DARE and DARF based on a range of uncertainties in present-day and pre-industrial aerosol optical properties, representative of existing and future global observing systems. We find the 1 σ uncertainty varies between ± 0.23 and ± 1.91 W m -2 (5 % and 42 %) for the top-of-atmosphere (TOA) clear-sky DARE and between ± 0.08 and ± 0.47 W m -2 (9 % and 52 %) for the TOA DARF. At the TOA, AOD uncertainty is the main contributor to overall uncertainty except over bright surfaces where SSA uncertainty contributes most. We apply regionally varying uncertainties to represent current measurement uncertainties and find that aerosol optical property uncertainties represent 24 % of TOA DARE and DARF. Reducing regionally varying optical property uncertainties by a factor of 2 would reduce their contributions to TOA DARE and DARF uncertainty proportionally. Applying a simple scaling to all-sky conditions, aerosol optical property uncertainty contributes to about 25 % total uncertainty in TOA, all-sky SW DARE, and DARF. Compared to previous studies which considered uncertainties in non-aerosol variables, our results suggest that the aerosol optical property uncertainty accounts for one-third to half of the total direct SW uncertainty. Recent and future progress in constraining aerosol optical properties using ground-based or satellite retrievals could be translated into DARE and DARF uncertainty using our freely available framework. [ABSTRACT FROM AUTHOR]

Across many upland environments, soils are thin and plant roots extend into fractured and weathered bedrock where moisture and nutrients can be obtained. Root water extraction from unsaturated weathered bedrock is widespread and, in many environments, can explain gradients in vegetation community composition, transpiration, and plant sensitivity to climate. Despite increasing recognition of its importance, the "rock moisture" reservoir is rarely incorporated into vegetation and Earth system models. Here, we address this weakness in a widely used dynamic global vegetation model (DGVM; LPJ-GUESS). First, we use a water flux-tracking deficit approach to more accurately parameterize plant-accessible water storage capacity across the contiguous United States, which critically includes the water in bedrock below depths typically prescribed by soil databases. Secondly, we exploit field-based knowledge of contrasting plant-available water storage capacity in weathered bedrock across two bedrock types in the Northern California Coast Ranges as a detailed case study. For the case study in Northern California, climate and soil water storage capacity are similar at the two study areas, but the site with thick weathered bedrock and ample rock moisture supports a temperate mixed broadleaf–needleleaf evergreen forest, whereas the site with thin weathered bedrock and limited rock moisture supports an oak savanna. The distinct biomes, seasonality and magnitude of transpiration and primary productivity, and baseflow magnitudes only emerge from the DGVM when a new and simple subsurface storage structure and hydrology scheme is parameterized with storage capacities extending beyond the soil into the bedrock. Across the contiguous United States, the updated hydrology and subsurface storage improve annual evapotranspiration estimates as compared to satellite-derived products, particularly in seasonally dry regions. Specifically, the updated hydrology and subsurface storage allow for enhanced evapotranspiration through the dry season that better matches actual evapotranspiration patterns. While we made changes to both the subsurface water storage capacity and the hydrology, the most important impacts on model performance derive from changes to the subsurface water storage capacity. Our findings highlight the importance of rock moisture in explaining and predicting vegetation structure and function, particularly in seasonally dry climates. These findings motivate efforts to better incorporate the rock moisture reservoir into vegetation, climate, and landscape evolution models. [ABSTRACT FROM AUTHOR]

A realistic representation of top‐of‐the‐atmosphere (TOA) radiation response to surface warming is key for trusting climate model projections. We show that coupled models with freely evolving ocean‐atmosphere interactions systematically underestimate the observed global TOA radiation trend during 2001–2022 in 552 simulations. Locally, even if a simulation spontaneously reproduces observed surface temperature trends, TOA radiation trends are more likely under‐ than overestimated. This response bias stems from the models' inability to reproduce the observed large‐scale surface warming pattern and from errors in the atmospheric physics affecting short‐ and longwave radiation. Models with a better representation of the TOA radiation response to local surface warming have a relatively low equilibrium climate sensitivity. Our bias metric is a novel process‐based approach which links a model's current response to climate change to its behavior in the future. Plain Language Summary: A realistic representation of the radiation balance at the top of the Earth's atmosphere (TOA) by coupled climate models is essential for trust in future climate projections. Despite that relevance, it is still not clear whether the models correctly simulate the coupling between surface warming and TOA radiation because of the short observational record. We show that climate models systematically underestimate the observed increase in global TOA radiation during 2001–2022 in 552 simulations. Locally, even if a simulation reproduces observed changes in surface temperature, changes in TOA radiation are more likely under‐ than overestimated. This response bias stems from the models' inability to reproduce the observed large‐scale patterns of surface warming and from errors in the atmospheric physics which suppress the communication of the surface information to the TOA. Models that better represent the TOA radiation response to local surface warming have a relatively low equilibrium climate sensitivity, that is, a weak global‐mean surface warming in response to a doubling of the atmospheric CO2 concentration above pre‐industrial levels. Our new bias metric links a model's current response to climate change to its behavior in the future. Key Points: Climate models underestimate the observed global TOA radiation trend during 2001–2022Surface warming patterns and atmospheric physics matter for the observation‐model discrepancyModels with a small bias in the coupling between surface warming and TOA radiation trends have a relatively low climate sensitivity [ABSTRACT FROM AUTHOR]

The mid-Pliocene is the most recent geological period with similar atmospheric CO2 concentration to the present-day, and similar surface temperatures as projected at the end of this century for a moderate warming scenario. While not a perfect analogue, the mid-Pliocene can be used to study the functioning of the Earth system under similar forcings as a near future, especially regarding features in the climate system for which uncertainties exist in future projections. According to the mid-Pliocene modelling ensemble PlioMIP2, the variability of El Niño-Southern Oscillation (ENSO) was suppressed. In this study, we investigate how teleconnections of ENSO, specifically variability in the North Pacific atmosphere, responds to a suppressed ENSO, according to the PlioMIP2. The multi-model mean shows a similar sea-level pressure (SLP) variability in the Aleutian Low (AL) in the mid-Pliocene and pre-industrial, but a per-model view reveals that the change in AL variability is related to the change in ENSO variability. Even though ENSO is suppressed, the teleconnection between ENSO sea-surface temperature anomalies, tropical precipitation and North Pacific SLP anomalies is quite robust in the mid-Pliocene. We split AL variability in a part that is ENSO-related, and a residual variability which is related to internal stochastic variability, and find that the change in ENSO-related AL variability is strongly related to the change in ENSO variability itself, while the change in residual AL variability is unrelated to ENSO change. Since the internal atmospheric variability, which is the dominant forcing of the AL variability, is largely unchanged, we are able to understand that the AL variability is largely similar even though ENSO variability is suppressed. We find that the specific change in ENSO and AL variability depends on both the model equilibrium climate sensitivity ánd Earth system sensitivity. Finally, we present a perspective of (extra-)tropical Pacific variability in the PlioMIP2, combining our results with literature findings on changes in the tropical mean climate as well as the Pacific Decadal Oscillation (PDO). [ABSTRACT FROM AUTHOR]

The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR)--key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO2 forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections. [ABSTRACT FROM AUTHOR]

This work explores the impact of rotation on tropical convection and climate. As our starting point, we use the RCEMIP experiments as control simulations and run additional simulations with rotation. Compared to radiative convective equilibrium (RCE) experiments, rotating RCE (RRCE) experiments have a more stable and humid atmosphere with higher precipitation rates. The intensity of the overturning circulation decreases, water vapor is cycled through the troposphere at a slower rate, the subsidence fraction decreases, and the climate sensitivity increases. Several of these changes can be attributed to an increased flux of latent and sensible heat that results from an increase of near‐surface wind speed with rotation shortly after model initialization. The increased climate sensitivity results from changes of both the longwave cloud radiative effect and the longwave clear‐sky radiative fluxes. This work demonstrates the sensitivity of atmospheric humidity and surface fluxes of moisture and temperature to rotation. Plain Language Summary: Many useful studies of the tropical regions of Earth have neglected to include rotation; however, phenomena such as tropical cyclones and atmospheric waves are fundamentally tied to rotation. This work compares models of the tropics with and without rotation. Compared to experiments without rotation, rotating experiments have a more humid and stable atmosphere. Although water vapor is cycled through the atmosphere at a slower rate, the precipitation rate increases. The climate sensitivity also increases due to changes in both clouds and water vapor. Many of these changes are the result of increased wind speeds. We argue that idealized modeling of Earth's tropical regions should include not just stationary experiments but also experiments that include rotation. Key Points: Rotation leads to a decreased intensity of the overturning circulation but increased mean precipitation and precipitable waterStatic stability increases with rotation, net radiative cooling remains approximately constant, resulting in a smaller subsidence velocityRotating experiments have a larger effective climate sensitivity relative to RCE experiments mostly due to longwave radiative changes [ABSTRACT FROM AUTHOR]

Emission trading is an efficient measure to combat climate change, which is one of the biggest threats to the international community and human health. The shipping industry has previously been considered an energy-saving industry but the growth rate of its emissions far exceeds that of other industries. On 10 May 2023, the EU enacted Regulation (EU) 2023/957, which officially included the shipping industry in the EU-ETS. Therefore, this may lead to investor-state disputes regarding emission trading in the marine industry due to the conflicts between the obligation to combat climate change and the obligation to protect investments of the host states. This has resulted in the breaching of International Investment Agreements. In this context, this study aimed to propose practical recommendations for global marine market practitioners to avoid the potential risks of disputes by reflecting on the existing practice regarding climate changerelated investor-state dispute resolutions and identifying the trends and problems of the current dispute resolution mechanism. These included inconsistency in the review standard, inconsistency in the review scope, and broad interpretation by the tribunal. Finally, this study proposed that by setting public purpose and exception clauses in the preambles of the International Investment Agreements and incorporating the specific obligations of the foreign investors and the regulatory power of the hosting states in the drafting stage, the potential risks for disputes regarding the new EU directive in the global marine industry could be effectively reduced. [ABSTRACT FROM AUTHOR]

Clouds affect the sensitivity of the climate system by changing their distribution, height and optical properties under climate change. Additionally, clouds have a masking effect on CO2 forcing and can affect other feedback mechanisms such as the surface albedo feedback. To shed light on the overall effect of clouds, we compute how much the equilibrium climate sensitivity to a doubling of CO2 (ECS) changes when clouds are made transparent to radiation in an Earth system model (MPI-ESM1.2). Practically, to stabilise the model climate at near pre-industrial temperatures the solar constant was reduced by 8.8 percent. Our experiments suggest that clouds play a stabilising role in the model, with a clear-sky ECS of 4.34 K, which is higher than the corresponding full-sky ECS of 2.80 K. Detailed partial radiative perturbation diagnostics show that clouds strengthen the lapse rate and water vapour feedbacks and dampen the albedo feedback. [ABSTRACT FROM AUTHOR]

This study evaluates the performance of two planetary boundary parameterizations in simulating the mean climate of West Africa using the Regional Climate Model version 5 (RegCM5). These planetary boundary parameterizations are the Holtslag scheme and the University of Washington scheme. Two sets of three one-year simulations were carried out at 25 km horizontal resolution with three different initial conditions. The first set of simulations used the Holtslag scheme (hereafter referred to as Hol), while the second used the University of Washington (UW) scheme (hereafter referred to as UW). The results displayed in this study are an average of the three simulations. During the JJAS rainy season, with respect to GPCP, both models overestimated total rainfall in the orographic regions. The UW experiment represented total rainfall fairly well compared to its counterpart, Hol. Both models reproduced convective rainfall well, with a relatively weak dry bias over the Guinean coast subregion. Globally, UW performed better than Hol in simulating precipitation. The pattern of near-surface temperature in both models was well reproduced with a higher bias with Hol than with UW. Indeed, the UW scheme led to a cooling effect owing to the reduction in eddy heat diffusivity in the lower troposphere contributing to reduce the bias. As a consequence, the height of the planetary boundary layer (PBL) was best simulated using the UW scheme but was underestimated compared to ERA5, while using the Hol scheme failed to capture the height of the PBL. This is coherent with the distribution of total cloud cover, which was better simulated with the UW scheme compared to the Hol scheme. This study shows that use of both planetary boundary parameterizations leads to a good simulation of most of the climatological characteristics of the West African region. Nevertheless, use of the UW scheme contributes to a better performance than use of the Hol scheme, and the differentiation between the two schemes is significant along the Guinea Coast and in orographic regions. In these topographically complex regions, UW appears to be more appropriate than Hol. This study emphasizes the importance of planetary boundary parameterizations for accurately simulating climate variables and for improving climate forecasts and projections in West Africa. [ABSTRACT FROM AUTHOR]

Weighting models according to their performance has been used to produce multimodel climate change projections. But the added value of model weighting for future projection is not always examined. Here we apply an imperfect model framework to evaluate the added value of model weighting in projecting summer temperature changes over China. Members of large-ensemble simulations by three climate models of different climate sensitivities are used as pseudo-observations for the past and the future. Performance of the models participating in the phase 6 of the Coupled Model Intercomparison Project (CMIP6) are evaluated against the pseudo-observations based on simulated historical climatology and trends in global, regional, and local temperatures to determine the model weights for future projection. The weighted projections are then compared with the pseudo-observations in the future period. We find that regional trend as a metric of model performance yields generally better skill for future projection, while past climatology as performance metric does not lead to a significant improvement to projection. Trend at the grid-box scale is also not a good performance indicator as small-scale trend is highly uncertain. For the model weighting to be effective, the metric for evaluating the model's performance must be relatable to future changes, with the response signal separable from internal variability. Projected summer warming based on model weighting is similar to that of unweighted projection but the 5th–95th-percentile uncertainty range of the weighted projection is 38% smaller with the reduction mainly in the upper bound, with the largest reduction appearing in southeast China. [ABSTRACT FROM AUTHOR]

Peatlands store disproportionally large amounts of carbon per unit area, a function that is dependent on maintaining high and stable water tables. Climate change is likely to negatively impact carbon storage in peatlands, in part due to increases in vapour pressure deficit (VPD) driving higher evaporation (E) rates. However, the response of E to increasing VPD depends on the dominant vegetation type within peatlands. In this study, we used multiple years of eddy covariance (EC) measurements to compare E regimes at two peatlands with contrasting vegetation types – Kopuatai bog in Aotearoa / New Zealand, dominated by the vascular wire rush Empodisma robustum, and Mer Bleue bog in Canada, a "typical" shrub- and moss-dominated Northern Hemisphere peatland. We examined seasonal variability in E and equilibrium E (Eeq), energy balance partitioning, and the response of E , evaporative fraction (EF), and canopy conductance (gc) to VPD. Mean annual E was 45 % lower than mean annual Eeq at Kopuatai but only 16 % lower at Mer Bleue, demonstrating much greater limitations on E at Kopuatai. In addition, the mean midday (10:00–14:30 local standard time) dry-canopy Bowen ratio (β) at Kopuatai was 2.0 compared to 0.8 at Mer Bleue; therefore, the sensible heat flux (H) dominated over the latent heat flux (LE) at Kopuatai and vice versa at Mer Bleue. The responses of E , EF, and gc to increasing VPD at Kopuatai demonstrated stronger limitations on evaporative water loss for VPD > 0.7 kPa compared to Mer Bleue. The observed limitations at Kopuatai were attributed to strong stomatal control by E. robustum due to the rapid decrease in gc with increasing VPD; however, surface E could also be limited by its dense standing litter. At Mer Bleue, however, E was only weakly limited at VPD > 2 kPa, likely due to weak stomatal control over transpiration by the sparse shrub canopy and relatively large surface E from Sphagnum carpets. As such, the results of this study suggest that E. robustum drives a greater "hydrological resistance" to increasing VPD than the vegetation at Mer Bleue, leading to greater water retention at Kopuatai. This may enable greater resilience of the carbon sink function at Kopuatai to climatic warming and drying than at Mer Bleue. [ABSTRACT FROM AUTHOR]

The eventual planetary warming in response to elevated atmospheric carbon dioxide concentrations is not precisely known. This climate sensitivity S depends primarily on the net physical climate feedbacks, usually denoted as λ. Multiple lines of evidence can constrain this feedback parameter: proxy-based and model evidence from past equilibrium climates, process-based understanding of the physics underlying changes, and recent observations of temperature change, top-of-atmosphere energy imbalance, and ocean heat content. However, despite recent advances in combining these lines of evidence, the estimated range of S remains large. Here, using a Bayesian framework, we discuss three sources of uncertainty: uncertainty in the evidence, structural uncertainty in the model used to interpret that evidence, and differing prior beliefs, and show how these affect the conclusions we may draw from a single line of evidence. We then propose a method to combine multiple estimates of the evidence, multiple multiple explanatory models, and the subjective assessments of different experts in order to arrive at an assessment of λ (and hence, climate sensitivity S) that may be rapidly updated as new information arrives and truly reflects the existing community of experts. [ABSTRACT FROM AUTHOR]

In this article the development of a high-resolution Earth System Model (ESM) for the Baltic Sea region is described. In contrast to conventional coupling approaches, the presented model features an additional (technical) component, the flux calculator, which calculates fluxes between the model components on a common exchange grid. This approach naturally ensures conservation of exchanged quantities, a locally consistent treatment of the fluxes, and facilitates interchanging model components in a straightforward manner. The main purpose of this model is to downscale global reanalysis or climate model data to the Baltic Sea region as typically, global model grids are too coarse to resolve the region of interest sufficiently. The regional ESM consists of the Modular Ocean Model 5 (MOM5) for the ocean and the COSMO model in CLimate Mode (CCLM, version 5.0_clm3) for the atmosphere. The bi-directional ocean–atmosphere coupling allows for a realistic air–sea feedback that outperforms the traditional approach of using uncoupled standalone models, as typically pursued with the EURO-CORDEX protocol. In order to address marine environmental problems (e.g., eutrophication and oxygen depletion), the ocean model is internally coupled with the marine biogeochemistry model, ERGOM, set up for the Baltic Sea's hydrographic conditions. The regional ESM can be used for various scientific questions such as climate sensitivity experiments, reconstruction of ocean dynamics, study of past climates, and natural variability, as well as investigation of ocean–atmosphere interactions. Therefore, it can serve for a better understanding of natural processes via attribution experiments that relate observed changes to mechanistic causes. [ABSTRACT FROM AUTHOR]

After many years with little change in community views on equilibrium climate sensitivity (ECS), in 2021 the Intergovernmental Panel on Climate Change (IPCC) concluded that it was much better known than previously. This development underpinned increased confidence in long-term climate changes in that report. Here, we place this development in historical context, briefly assess progress since then, and discuss the challenges and opportunities for further improving our knowledge of this iconic concept. We argue that the probability distributions published in those assessments are still approximately valid; while various subsequent studies have claimed further narrowing, they have omitted important structural uncertainties associated with missing processes, imperfect relationships, or other factors that should be included. The distributions could nonetheless be narrowed in the future, particularly through better understanding of certain climate processes and paleoclimate proxies. Not all touted strategies are truly helpful, however. We also note that ECS does not address risks from the carbon cycle or possible tipping points, and as increasingly strong mitigation (i.e., "net-zero") scenarios are considered, ECS becomes less informative about future climate change compared to other factors such as aerosol radiative forcing and influences on regional change such as ocean dynamics. [ABSTRACT FROM AUTHOR]

A mixed statistical-physical approach is used to emulate the spatio-temporal variability of the Antarctic ice sheet surface mass balance and runoff of a regional climate model. We demonstrate the ability of this simple method to extend existing MAR simulations to other periods, scenarios or climate models, that were not originally processed through the regional climate model. This method is useful to quickly populate ensembles of surface mass balance and runoff which are needed to constrain ice sheet model ensembles. After correcting the distribution of equilibrium climate sensitivity of 16 climate models, we find a likely contribution of surface mass balance to sea level rise of 0.4 to 2.2 cm from 1900 to 2010, and -3.4 to -0.1 cm from 2100 to 2099 under the SSP1-2.6 scenario, versus -4.4 to -1.4 cm under SSP2-4.5 and -7.8 to -4.0 cm under SSP5-8.5. Based on a more limited and uncorrected ensemble, we find a considerable uncertainty in the contribution to sea level from 2000 to 2200: between -10 and -1 cm in SSP1-2.6 and between -33 and +6 cm in SSP5-8.5. Based on a runoff criteria in our reconstructions, we identify the emergence of surface conditions prone to hydrofracturing. A majority of ice shelves could remain safe from hydrofracturing under the SSP1-2.6 scenario, but all the Antarctic ice shelves could be prone to hydrofracturing before 2130 under the SSP5-8.5 scenario. [ABSTRACT FROM AUTHOR]

Copyright of Fire Ecology is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)