Global Temperature Research Articles

A two-dimensional semi-analytic thermal model for global temperature distribution predicting and hot spot monitoring in interior permanent magnet synchronous motor

A two-dimensional semi-analytical thermal model (SATM) is presented, aiming to quickly and accurately achieve global temperature distribution predicting and hot spot monitoring for interior permanent magnet synchronous motor (IPMSM). Thereby, it provides a reliable analysis tool for thermal behavior evaluation and prevents undesired consequences induced by excessive temperature rise, which is of great worth and significance in promoting the flourishing of IPMSM. SATM combines the analytical method, lumped parameter thermal network, and finite element analysis to obtain an analytical solution for thermal behavior through mathematical derivation by considering the complicated configuration, heat source distribution, heat dissipation condition, and material thermal dependence. Through SATM, it is possible to observe the global temperature distribution as well as the location and size of hot spots in each element. The temperature distribution gradient on the static is more pronounced than that on the dynamic; secondly, the area with the most severe heating is mainly found on the winding; furthermore, the hot spot on the winding is mainly located a little bit inside the center. Moreover, the thermal behavior of IPMSM at rated load is investigated by numerical analysis and experiments. A comprehensive comparison with SATM is done. The computational deviations between SATM and numerical analysis regarding the hot spot, minimum, and average temperatures on each element are all within 4.06 %. However, SATM consumes only 20.92 % of the time and 68.29 % of the storage of the numerical analysis. The measured data also fully prove the reliability and validity of the comparison. It is certain that SATM can well break through the limitation of the existing non-numerical technique to quickly and accurately achieve global temperature distribution predicting and hot spot monitoring of IPMSM. It provides researchers and engineers engaged in thermal behavior evaluation with good analysis means, design guidance, and optimization direction.

Wildfires and social media discourse: exploring mental health and emotional wellbeing through Twitter.

The rise in global temperatures due to climate change has escalated the frequency and intensity of wildfires worldwide. Beyond their direct impact on physical health, these wildfires can significantly impact mental health. Conventional mental health studies predominantly rely on surveys, often constrained by limited sample sizes, high costs, and time constraints. As a result, there is an increasing interest in accessing social media data to study the effects of wildfires on mental health. In this study, we focused on Twitter users affected by the California Tubbs Fire in 2017 to extract data signals related to emotional well-being and mental health. Our analysis aimed to investigate tweets posted during the Tubbs Fire disaster to gain deeper insights into their impact on individuals. Data were collected from October 8 to October 31, 2017, encompassing the peak activity period. Various analytical methods were employed to explore word usage, sentiment, temporal patterns of word occurrence, and emerging topics associated with the unfolding crisis. The findings show increased user engagement on wildfire-related Tweets, particularly during nighttime and early morning, especially at the onset of wildfire incidents. Subsequent exploration of emotional categories using Linguistic Inquiry and Word Count (LIWC) revealed a substantial presence of negative emotions at 43.0%, juxtaposed with simultaneous positivity in 23.1% of tweets. This dual emotional expression suggests a nuanced and complex landscape, unveiling concerns and community support within conversations. Stress concerns were notably expressed in 36.3% of the tweets. The main discussion topics were air quality, emotional exhaustion, and criticism of the president's response to the wildfire emergency. Social media data, particularly the data collected from Twitter during wildfires, provides an opportunity to evaluate the psychological impact on affected communities immediately. This data can be used by public health authorities to launch targeted media campaigns in areas and hours where users are more active. Such campaigns can raise awareness about mental health during disasters and connect individuals with relevant resources. The effectiveness of these campaigns can be enhanced by tailoring outreach efforts based on prevalent issues highlighted by users. This ensures that individuals receive prompt support and mitigates the psychological impacts of wildfire disasters.

Acceleration neglect in trend extrapolations.

Many decisions rely on intuitive predictions based on time series data showing a trend. For instance, the current upward trend in global temperatures might lead to specific predictions about the extent to which global temperatures will rise in the future, and these predictions might be used to inform judgments about the urgency with which climate change must be addressed. However, those predictions often need to be revised to incorporate the effects of unexpected events that might accelerate a trend (i.e., increase its rate of change), such as an unanticipated increase in CO₂ emissions, or decelerate a trend (i.e., decrease its rate of change), such as an unanticipated reduction in CO₂ emissions. In this work, we uncover a new cognitive bias by which people neglect how much a trend can accelerate (vs. decelerate) due to unexpected events. We explain this bias in terms of momentum theory and a naive understanding of physics. These findings have important implications for businesses and policymakers seeking to communicate information about topics such as climate change, stock market prices, or disease prevention. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Hydroclimatic anomalies detected by a sub-decadal diatom oxygen isotope record of the last 220 years from Lake Khamra, Siberia

Abstract. Northern latitudes have been significantly impacted by recent climate warming, which has increased the probability of experiencing extreme weather events. To comprehensively understand hydroclimate change and reconstruct hydroclimatic anomalies such as drought periods, appropriate proxy records reaching further back in time beyond meteorological measurements are needed. Here we present a 220-year (2015–1790 CE), continuous, stable oxygen isotope record of diatoms (δ18Odiatom) from Lake Khamra (59.99° N, 112.98° E) in eastern Siberia, an area highly sensitive to climate change and for which there is a demand for palaeohydrological data. This high-resolution proxy record was obtained from a 210Pb–137Cs-dated sediment short core and analysed to reconstruct hydroclimate variability at a sub-decadal scale. The interpretation of the δ18Odiatom record is supported by meteorological data, modern isotope hydrology and geochemical analyses of the same sediment, which is indicative of the conditions in the lake and catchment. A comparison with meteorological data going back to 1930 CE revealed that the δ18Odiatom record of Lake Khamra is primarily influenced by regional precipitation changes rather than the air temperature. We identified winter precipitation, which enters the lake as isotopically depleted snowmelt water, as the key process impacting the diatom isotope variability. We related the overall depletion of δ18Odiatom in recent decades to an observed increase in winter precipitation in the area, likely associated with the global air temperature rise, Arctic sea ice retreat and increased moisture transport inland. Available palaeoclimate proxy records, including a fire reconstruction for the same lake, support the idea that the new record is a valuable hydroclimate proxy that is indicative of precipitation deficits and excludes solar insolation and air temperature as primary driving forces, even before the first meteorological recordings. We propose two possible hydroclimatic anomalies that were detected in the Lake Khamra δ18Odiatom record: one at the beginning of the 19th century and a second prominent event in the 1950s. Both are interpreted as prolonged dry periods associated with enriched δ18Odiatom values likely caused by reduced winter precipitation, which coincide with phases of reconstructed severe wildfires in the region. Despite the apparent pristine lake area, we observed a three- to fourfold increase in mercury concentrations and accumulation rates within the sediment record since the early 20th century, which is partly attributed to human air pollution.

Investigating Vulnerability, Adaptation, and Resilience: A Comprehensive Review within the Context of Climate Change

This review seeks to enhance the understanding of the critical concepts of vulnerability, adaptation, and resilience within the context of global environmental challenges, with a particular focus on climate change. Climate change is characterized by rising global temperatures and an increase in extreme weather events, making the comprehension and addressing of these concepts crucial for effective adaptation strategies. Despite widespread recognition of the interconnectedness of vulnerability, adaptation, and resilience, there remains a gap in a comprehensive understanding of how these concepts interrelate. Through synthesizing existing literature, this review provides a detailed examination of their definitions and the interrelationships among vulnerability, adaptation, resilience, and climate-related disasters. Additionally, it explores the impact of climate change on future disaster risk reduction efforts by analyzing the nexus between climate change adaptation and disaster risk reduction. Key findings highlight the necessity of incorporating social, institutional, economic, and environmental factors into adaptation planning and call for innovative approaches to boost adaptive capacity and resilience. This review not only furthers the discourse in research, policy, and practice in this vital area but also offers strategic insights for developing more resilient and adaptive societies amidst the challenges posed by climate change.

In ovo feeding of α-ketoglutaric acid improves hepatic antioxidant-gene expression, plasma antioxidant activities and decreases body temperature without affecting broiler body weight under cyclic heat stress

The broiler industry is adversely affected by the rise in global temperature. This study investigated the effects of in ovo feeding of α-ketoglutaric acid (AKG) on growth performance, organ weight, plasma metabolite, plasma oxidative stress, rectal temperature (RT), and hepatic mRNA expression of antioxidant-related genes in Arbor Acres broilers subjected to cyclic heat stress (HS). Three hundred fifty fertile eggs during incubation were divided into 5 groups according to AKG concentrations and temperature conditions. After dissolving AKG in distilled water at 0, 0.5, 1.0, and 1.5, 0% AKG was in ovo administered to 2 of the 5 groups whereas the remaining 3 groups received 0.5, 1.0, and 1.5%, respectively. From d 29 to 34 of age, 4 groups of birds received heat stress (HS) at 31°C ± 1°C for 6 h per day while the other group was kept at room temperature (21°C ± 1°C; NT). So, the 5 treatment groups were: 1) 0AKG-NT, where chicks hatched from eggs receiving 0% AKG were reared under thermoneutral conditions. 2) 0AKG-HS, where chicks hatched from eggs receiving 0% AKG were reared under cyclic HS conditions. 3) 0.5AKG-HS, where chicks hatched from eggs receiving 0.5% AKG were reared under cyclic HS conditions. 4) 1.0AKG-HS, where chicks hatched from eggs receiving 1.0% AKG were reared under cyclic HS conditions. 5) 1.5AKG-HS, where chicks hatched from eggs receiving 1.5% AKG were reared under cyclic HS conditions. HS significantly reduced body weight change (ΔBW %) and average daily gain (ADG) without affecting average daily feed intake (ADFI). Feed conversion ratio (FCR) was significantly increased (P = 0.003) in all HS-treated groups. A significant linear decrease in the final RT (P = 0.005) and a change in RT (P = 0.003) were detected with increasing AKG concentration. Total antioxidant capacity (P = 0.029) and antioxidant balance (P = 0.001) in plasma increased linearly with increasing AKG concentration whereas malondialdehyde concentrations were linearly decreased (P = 0.001). Hepatic gene expression of CAT (P = 0.026) and GPX1 (P = 0.001) were dose-dependently upregulated while nicotinamide adenine dinucleotide phosphate oxidase (NOX)1, NOX4, and heat shock protein (HSP)70 were linearly downregulated (P < 0.05). Hence, in ovo injection of AKG was effective in mitigating HS-induced oxidative stress without attenuating the adverse effects on broiler growth.

Hygrothermal response of a wood-frame thick-wall assembly to rainwater wetting under future climate scenarios in Canada

Current exterior wall assembly designs for new low-rise residential buildings targeting low-energy demand in heating dominated countries include split-insulation wall and thick-wall assembly designs. Both have been shown to result in thermal efficiency gains compared to building-code minimum assemblies, however long-term hygrothermal performance can vary depending on boundary conditions and the presence of construction deficiencies. Future climate scenarios estimate many heating-dominated climates will experience a reduction in heating-degree day hours and an increase in annual rainfall. Using validated assembly performance data from a Passive House certified facility, a sensitivity analysis is performed to determine the impact of rainwater wetting, air exfiltration and insulation material properties on the hygrothermal response of a thick-wall assembly. Results show that rainwater leakage values of 0.50% and greater of the adhering rainfall on the exterior surface of the assembly results in the greatest risk for failure. The hygrothermal response of the assembly is then examined under a global temperature rise scenario of 3.5°C for five geographic locations across Canada. Results show that an increase in average annual total rainfall does not directly result in an increase in the failure rate of the assembly when a rainwater leak is present. Additional climatic factors, including outdoor air temperature, driving rain and solar radiation received will influence the hygrothermal response of the assembly and need to be considered when modelling the performance under future climate change scenarios.

Climate change impacts on mesophotic regions of the Great Barrier Reef

Climate change projections for coral reefs are founded exclusively on sea surface temperatures (SST). While SST projections are relevant for the shallowest reefs, neglecting ocean stratification overlooks the striking differences in temperature experienced by deeper reefs for all or part of the year. Density stratification creates a buoyancy barrier partitioning the upper and lower parts of the water column. Here, we mechanistically downscale climate models and quantify patterns of thermal stratification above mesophotic corals (depth 30 to 50 m) of the Great Barrier Reef (GBR). Stratification insulates many offshore regions of the GBR from heatwaves at the surface. However, this protection is lost once global average temperatures exceed ~3 °C above preindustrial, after which mesophotic temperatures surpass a recognized threshold of 30 °C for coral mortality. Bottom temperatures on the GBR (30 to 50 m) from 2050 to 2060 are estimated to increase by ~0.5 to 1 °C under lower climate emissions (SSP1-1.9) and ~1.2 to 1.7 °C under higher climate emissions (SSP5-8.5). In short, mesophotic coral reefs are also threatened by climate change and research might prioritize the sensitivity of such corals to stress.

Assessment of thermal and mechanical properties of fly ash based geopolymer blocks with a sustainability perspective using multi-criteria decision-making approach

Owing to the raising consciousness about the environment, geopolymers are slowly gaining the trust of researchers globally as the potential alternatives for the conventional building materials. Though, geopolymer emit far less CO2 than conventional building materials, the distance between the source and production site for a particular raw material can have significant impact on the environment. Thus, apart from meeting the mechanical and physical requirement of a building material, it must satisfy the sustainability requirement as well. Therefore, a combination of experimental and analytical method is adopted to select the optimal design mix to produce sustainable geopolymer block which fulfills the performance requirements as well. While compressive and flexural strength test were performed on the geopolymer block made using fly ash (FA) as the primary precursor and glass powder (GP) and steel slag (SS) as the partial replacement to ascertain its mechanical performance, physical performance was assessed by conducting tests like water absorption, bulk density, and thermal conductivity. The sustainability of geopolymer block is assessed by computing sustainability index based on embodied energy, global warming potential and global temperature potential. Multi-criteria decision making (MCDM) approach is then used to select the most optimal mix for geopolymer block production based on the mechanical, physical and sustainability index of each mix for geopolymer. A combination of FA-SS prepared with 14 M NaOH was found to be most sustainable based on the MDCM approach.

Reconciling East Asia's mid-Holocene temperature discrepancy through vegetation-climate feedback

The term “Holocene temperature conundrum” refers to the inconsistencies between proxy-based reconstructions and transient model simulations, and it challenges our understanding of global temperature evolution during the Holocene. Climate reconstructions indicate a cooling trend following the Holocene Thermal Maximum, while model simulations indicate a consistent warming trend due to ice-sheet retreat and rising greenhouse gas concentrations. Various factors, such as seasonal biases and overlooked feedback processes, have been proposed as potential causes for this discrepancy. In this study, we examined the impact of vegetation-climate feedback on the temperature anomaly patterns in East Asia during the mid-Holocene (∼6 ka). By utilizing the fully coupled Earth system model EC-Earth and performing simulations with and without coupled dynamic vegetation, our objective was to isolate the influence of vegetation changes on regional temperature patterns. Our findings reveal that vegetation-climate feedback contributed to warming across most of East Asia, resulting in spatially diverse temperature changes during the mid-Holocene and significantly improved model-data agreement. These results highlight the crucial role of vegetation-climate feedback in addressing the Holocene temperature conundrum and emphasize its importance for simulating accurate climate scenarios.

Assessment of Frost Depth and Frost Heave in Romania

The investigation of extreme weather and climate events has gained momentum in the last few decades, spurred in part by political involvement. However, not enough attention has been paid to the historical recorded data of climate monitoring. An accurate estimate of maximum soil frost depth is an important factor in determining construction costs and structures’ foundations, and designers also need reliable information about local meteorological parameters. In this study, the calculations of the parameters for the city of Arad are presented as an example. An updated Romanian frost depth map and a new Romanian freeze–thaw cycle (FTC) map are needed since recent climate studies have documented an increase in global and regional surface temperatures, with the greatest shift in warming occurring over the last three decades. This trend is particularly pronounced when comparing the 1990–2020 period with earlier periods, which could be indicative of broader climate change trends. It is important to note that these conclusions are based solely on the provided statistical parameters and do not take into account other potential factors influencing temperature trends in the region. The results from this investigation could be used to achieve a reduction in frost disasters and the formulation of policies and measures for the adaptation of geotechnical/structural design for Romanian territory. They may also support the development of maps that help to visualize and understand the evolving climate patterns in the region, including changes in frost depth and the frequency of freeze–thaw cycles, which are important for various sectors such as agriculture, construction, and infrastructural planning. Given the documented increase in global and regional surface temperatures, updating such maps will also provide valuable information for policymakers, researchers, and stakeholders on how to adapt to ongoing climate change and its impacts on the Romanian region.

Heat Transfer of Ca (NO3)2-KNO3 Molten Salt Mixtures for Austempering and Martempering Processes of Steels.

Molten salts are highly effective as a quenching medium for austempering and martempering processes, enabling precise control of cooling rates to achieve the desired microstructures and mechanical characteristics in steel components. One such promising molten salt is a multicomponent Ca (NO3)2-KNO3 molten salt. The current work explores the cooling severity of molten Ca (NO3)2-KNO3 mixtures, which are commonly used for such purposes. The said mixture, with varying concentrations and bath temperatures was used for quenching the Inconel probe with thermocouples. The temperature data extracted was used to determine the transient heat flux developed at the metal-quenchant interface. A set of critical points were assessed against the peak heat extraction rates. Additionally, the fluctuation of mean heat flux and surface temperature in relation to these crucial points were plotted, along with changes in composition and bath temperature of the quench media. The cooling intensity of these quench solutions, as measured by Inconel probes, correlated well with the average hardness values observed in steel probes. The level of homogeneity in heat transmission, as measured by the spatial variance of the normalized heat energy, decreased as the percentage of KNO3 in the quench medium increased.

Radiative forcing geoengineering under high CO2 levels leads to higher risk of Arctic wildfires and permafrost thaw than a targeted mitigation scenario

Radiative forcing geoengineering is discussed as an intermediate solution to partially offset greenhouse gas-driven warming by altering the Earth’s energy budget. Here we use an Earth System Model to analyse the response in Arctic temperatures to radiative geoengineering applied under the representative concentration pathway 8.5 to decrease the radiative forcing to that achieved under the representative concentration pathway 4.5. The three methods Stratospheric Aerosol Injection, Marine Cloud Brightening, and Cirrus Cloud Thinning, mitigate the global mean temperature rise, however, under our experimental designs, the projected Arctic temperatures are higher than if the same temperature was achieved under emission mitigation. The maximum temperature increase under Cirrus Cloud Thinning and Marine Cloud Brightening is linked to carbon dioxide plant physiological forcing, shifting the system into climatic conditions favouring the development of fires. Under Stratospheric Aerosol Injection, the Arctic land with temperatures permanently below freezing decreased by 7.8% compared to the representative concentration pathway 4.5. This study concludes that these specific radiative forcing geoengineering designs induce less efficient cooling of the Arctic than the global mean and worsen extreme conditions compared to the representative concentration pathway 4.5.

Predicting Summer Precipitation Anomalies in the Yunnan–Guizhou Plateau Using Spring Sea-Surface Temperature Anomalies

By constructing a correlation network between global sea surface temperature anomalies (SSTAs) and summer precipitation anomalies in the Yunnan–Guizhou Plateau, key SST regions influencing summer precipitation anomalies in the Yunnan–Guizhou Plateau were selected. It was found that spring SSTAs in the Bay of Bengal, southwestern Atlantic, and eastern Pacific are crucial for influencing summer precipitation anomalies in the Yunnan–Guizhou Plateau. Setting SSTAs from these three regions as predictor variables 3 months in advance, we constructed multiple linear regression (MLR), ridge regression (RR), and lasso regression (LR) models to predict summer precipitation anomalies over the Yunnan–Guizhou region. The training phase involved data spanning from 1961 to 2005, which aimed to predict precipitation anomalies in the Yunnan–Guizhou Plateau for the period extending from 2006 to 2022. Based on MLR, RR, and LR models, the correlations between predicted values and observed summer precipitation anomalies in Yunnan–Guizhou were 0.48, 0.46, and 0.46, respectively. These values were all higher than the correlation coefficients of the NCC_CSM model’s predicted and observed values. Additionally, its performance in predicting summer precipitation anomalies over the Yunnan–Guizhou region, based on key SST regions, was assessed using performance metrics such as anomaly correlation coefficient (ACC), anomaly sign consistency rate (PC), and trend anomaly comprehensive score (PS score). The average ACC of MLR, RR, and LR models was higher than that of the NCC_CSM model’s predictions. For MLR, RR, LR, and NCC_CSM models, the PCs exceeding 50% of the year were 14, 14, 11, and 10, respectively. Furthermore, the average PS score for predicting summer precipitation anomalies over the Yunnan–Guizhou region using MLR, RR, and LR was approximately 73 points; 8 higher than the average PS score of the NCC_CSM model. Therefore, predicting summer precipitation anomalies over the Yunnan–Guizhou region based on key SST regions is of great significance for improving the prediction skills of precipitation anomalies in this region.

Assessing scale-dependency of climate risks in coffee-based agroforestry systems

Agroforestry is a management strategy for mitigating the negative impacts of climate and adapting to sustainable farming systems. The successful implementation of agroforestry strategies requires that climate risks are appropriately assessed. The spatial scale, a critical determinant influencing climate impact assessments and, subsequently, agroforestry strategies, has been an overlooked dimension in the literature. In this study, climate risk impacts on robusta coffee production were investigated at different spatial scales in coffee-based agroforestry systems across India. Data from 314 coffee farms distributed across the districts of Chikmagalur and Coorg (Karnataka state) and Wayanad (Kerala state) were collected during the 2015/2016 to 2017/2018 coffee seasons and were used to quantify the key climate drivers of coffee yield. Projected climate data for two scenarios of change in global climate corresponding to (1) current baseline conditions (1985–2015) and (2) global mean temperatures 2 °C above preindustrial levels were then used to assess impacts on robusta coffee yield. Results indicated that at the district scale rainfall variability predominantly constrained coffee productivity, while at a broader regional scale, maximum temperature was the most important factor. Under a 2 °C global warming scenario relative to the baseline (1985–2015) climatic conditions, the changes in coffee yield exhibited spatial-scale dependent disparities. Whilst modest increases in yield (up to 5%) were projected from district-scale models, at the regional scale, reductions in coffee yield by 10–20% on average were found. These divergent impacts of climate risks underscore the imperative for coffee-based agroforestry systems to develop strategies that operate effectively at various scales to ensure better resilience to the changing climate.

Enhanced light olefin production from CO2 over potassium promoted Fe–Co bimetallic ZrO2 supported catalysts

Over 1300 tons of carbon dioxide (CO2) is emitted into the earth's atmosphere every second, threatening to breach the limiting global temperature increase of 1.5 °C set under the Paris Agreement. It is considered as sustainable feedstock that ensures season-wide availability for producing oxygenates and olefins. Likewise, CO2 hydrogenation to lower olefins was performed using bimetallic Fe-Co catalysts, processed in situ in a fixed-bed catalytic microreactor at 280–380 °C and a pressure of 0.5–3 MPa. A MOF framework (UIO-66) was used to fabricate ZrO2 NPs. In addition, a series of potassium-promoted Fe-Co bimetallic catalysts over the ZrO2 NPs were prepared, characterised and studied for the hydrogenation of carbon dioxide to light olefins. With increasing K content, the selectivity of C2-C4 increased under all operating conditions. The spent catalyst exhibits the bimodal size distribution of Fe3C, Fe2O3 and Fe° after a modified Fischer-Tropsch synthesis (M−FTS) reaction. The XANES data shows that the energy of the Fe K-edge and the Zr K-edge are shifted in a positive direction compared to the respective foil, indicating the presence of oxides in the fresh catalyst. Under the optimised reaction conditions, the H2-pretreated K promoted Fe-Co catalyst (K5Co3Fe10/ZrO2) showed remarkably low methanation with an olefin (C2-C4) selectivity of 38 %. In addition, the catalyst exhibits excellent stability and activity, providing nearly constant CO2 conversion and selectivity of (C2−C4=) lower olefins, CO and paraffin over the 100 h time-on-stream.

Representing natural climate variability in an event attribution context: Indo-Pakistani heatwave of 2022

Attribution of extreme climate events to global climate change as a result of anthropogenic greenhouse gas emissions has become increasingly important. Extreme climate events arise at the intersection of natural climate variability and a forced response of the Earth system to anthropogenic greenhouse gas emissions, which may alter the frequency and severity of such events. Accounting for the effects of both natural climate variability and the forced response to anthropogenic climate change is thus central for the attribution. Here, we investigate the reproducibility of probabilistic extreme event attribution results under more explicit representations of natural climate variability. We employ well-established methodologies deployed in statistical Earth System Model emulators to represent natural climate variability as informed from its spatio-temporal covariance structures. Two approaches towards representing natural climate variability are investigated: (1) where natural climate variability is treated as a single component; and (2) where natural climate variability is disentangled into its annual and seasonal components. We showcase our approaches by attributing the 2022 Indo-Pakistani heatwave to human-induced climate change. We find that explicit representation of annual and seasonal natural climate variability increases the overall uncertainty in attribution results considerably compared to established approaches such as the World Weather Attribution Initiative. The increase in likelihood of such an event occurring as a result of global warming differs slightly between the approaches, mainly due to different assessments of the pre-industrial return periods. Our approach that explicitly resolves annual and seasonal natural climate variability indicates a median increase in likelihood by a factor of 41 (95% range: 6-603). We find a robust signal of increased likelihood and intensification of the event with increasing global warming levels across all approaches. Compared to its present likelihood, under 1.5 °C (2 °C) of global near-surface air temperature increase relative to pre-industrial temperatures, the likelihood of the event would be between 2.2 to 2.5 times (8 to 9 times) higher. We note that regardless of the different statistical approaches to represent natural variability, the outcomes on the conducted event attribution are similar, with minor differences mainly in the uncertainty ranges. Possible reasons for differences are evaluated, including limitations of the proposed approach for this type of application, as well as the specific aspects in which it can provide complementary information to established approaches.

Harnessing climate services to support community resilience planning: lessons learned from a community-engaged approach to assessing NOAA’s National Water Model

IntroductionInland and coastal flooding and other water-based natural disasters are projected to increase in severity, frequency, and intensity as global temperatures rise, placing a growing number of US communities at risk. Governments at the local, state, and federal levels have been embracing resilience planning to better predict, mitigate, and adapt to such shocks and hazards. A growing number of climate services have been developed to aid communities engaged in these efforts to access, interpret, and make decisions with climate-related data and information. An important tool for potentially supporting this planning is the National Water Model (NWM), created by the National Oceanic and Atmospheric Administration’s (NOAA) National Water Center (NWC). The NWM is a river and streamflow model that can forecast conditions for the continental United States.MethodsHowever, community end-users were not being effectively engaged in ways that result in widespread tool use and adoption. From 2021 to 2023, seven geographically diverse US communities agreed to participate in a study to understand how the NWM might be applied in resilience planning. Interviews and collaborative sessions were conducted with NWC/NOAA staff and community resilience stakeholders in Burlington, VT; Cincinnati, OH; Portland, OR; Charlotte, NC; Boulder, CO; Minneapolis; MN; and Houston, TXResults and DiscussionResults provide an improved understanding of potential applications of the National Water Model and have identified actions to overcome the barriers to its use among municipal and regional resilience planners. This research yielded a set of recommendations, co-developed between the seven communities and NWC/ NOAA staff, for how these barriers could be overcome to facilitate wider use of the NWM and its data and visualization services in resilience planning. This study highlights the NWM’s applicability at shorter timescales in resilience planning and points to a more general need for climate services to accommodate near-, medium-, and longterm time frames. The study also found many community stakeholders who use water science and information in resilience planning have diverse disciplinarily backgrounds. Importantly, the majority were not trained hydrologists or water scientists, pointing to the critical need for climate service developers, including the NWC, to embrace co-development efforts that involve a wider range of end-users, including community resilience planners.

Regional reef fish assemblage maps provide baseline biogeography for tropicalization monitoring

The Anthropocene rise in global temperatures is facilitating the expansion of tropical species into historically non-native subtropical locales, including coral reef fish. This redistribution of species, known as tropicalization, has serious consequences for economic development, livelihoods, food security, human health, and culture. Measuring the tropicalization of subtropical reef fish assemblages is difficult due to expansive species ranges, temporal distribution shifts with the movement of isotherms, and many dynamic density-dependent factors affecting occurrence and density. Therefore, in locales where tropical and subtropical species co-occur, detecting tropicalization changes relies on regional analyses of the relative densities and occurrence of species. This study provides a baseline for monitoring reef fish tropicalization by utilizing extensive monitoring data from a pivotal location in southeast Florida along a known transition between tropical and subtropical ecotones to define regional reef fish assemblages and use benthic habitat maps to spatially represent their zoogeography. Assemblages varied significantly by ecoregion, habitat depth, habitat type, and topographic relief. Generally, the southern assemblages had higher occurrences and densities of tropical species, whereas the northern assemblages had a higher occurrence and density of subtropical species. A total of 108 species were exclusive to regions south of the Bahamas Fracture Zone (BFZ) (South Palm Beach, Deerfield, Broward-Miami) and 35 were exclusive to the north (North Palm Beach, Martin), supporting the BFZ as a pivotal location that affects the coastal biogeographic extent of tropical marine species in eastern North America. Future tropicalization of reef fish assemblages are expected to be evident in temporal deviance of percent occurrence and/or relative species densities between baseline assemblages, where the poleward expansion of tropical species is expected to show the homogenization of assemblage regions as adjacent regions become more similar or the regional boundaries expand poleward. Ecoregions, habitat depth, habitat type, and relief should be incorporated into the stratification and analyses of reef fish surveys to statistically determine assemblage differences across the seascape, including those from tropicalization.

Early 20th century Southern Hemisphere cooling

Abstract. Global surface air temperature increased by ca. 0.5 °C from the 1900s to the mid-1940s, also known as Early 20th Century Warming (ETCW). However, the ETCW started from a particularly cold phase, peaking in 1908–1911. The cold phase was global but more pronounced in the Southern Hemisphere than in the Northern Hemisphere and most pronounced in the Southern Ocean, raising the question of whether uncertainties in the data might play a role. Here we analyse this period based on reanalysis data and reconstructions, complemented with newly digitised ship data from 1903–1916, as well as land observations. The cooling is seen consistently in different data sets, though with some differences. Results suggest that the cooling was related to a La-Niña-like pattern in the Pacific, a cold tropical and subtropical South Atlantic, a cold extratropical South Pacific, and cool southern midlatitude land areas. The Southern Annular Mode was positive, with a strengthened Amundsen–Bellingshausen seas low, although the spread of the data products is considerable. All results point to a real climatic phenomenon as the cause of this anomaly and not a data artefact. Atmospheric model simulations are able to reproduce temperature and pressure patterns, consistent with a real and perhaps ocean-forced signal. Together with two volcanic eruptions just before and after the 1908–1911 period, the early 1900s provided a cold start into the ETCW.