Global Temperature Research Articles

Measuring the extent of trees outside of forests: a nature-based solution for net zero emissions in South Asia

Abstract To reduce emissions of carbon and other greenhouse gases on a pathway that does not overshoot and keeps global average temperature increase to below the 1.5 oC target stipulated by the Paris Agreement, it shall be necessary to rely on nature-based solutions with atmospheric removals. Without activities that create removals from carbon sequestration it will not be possible to balance residual emissions. Policies that focus solely on reducing deforestation will only lower future emissions. On the other hand, activities that include regeneration or regrowth of tree biomass can be used to create net-zero emissions through carbon sequestration and atmospheric removals now. New methods demonstrated here using high resolution remote sensing and deep machine learning enable analyses of carbon stocks of individual trees outside of forests (TOF). Allometric scaling models based on tree crowns at very high spatial resolution (<0.5 m) can map carbon stocks across large landscapes with millions of trees outside of forests. In addition to carbon removals, these landscapes are also important to livelihoods for millions of rural farmers and most TOF activities have the capacity to bring more countries into climate mitigation while also providing adaptation benefits. Here were present a multi-resolution, multi-sensor method that provides a way to measure carbon at the individual tree level in TOF landscapes in India. The results of this analysis show the effectiveness of mapping trees outside of forest across a range of satellite data resolution from 0.5 m to 10 m and for measuring carbon across large landscapes at the individual tree scale.

Efficient Estimation of Climate State and Its Uncertainty Using Kalman Filtering with Application to Policy Thresholds and Volcanism

Abstract We present the Energy Balance Model – Kalman Filter (EBM-KF), a hybrid model projecting and assimilating the global mean surface temperature (GMST) and ocean heat content anomaly (OHCA). It combines an annual energy balance model (difference equations) with 17 parameters drawn from the literature and a statistical Extended Kalman Filter assimilating GMST and OHCA, either observed timeseries or simulated by earth system models. Our motivation is to create an efficient and natural estimator of the climate state and its uncertainty, which we believe to be Gaussian at a global scale. We illustrate four applications: 1) EBM-KF generates a similar estimate to the 30-year time-averaged climate state 15 years sooner, or a model-simulated hindcasts’ annual ensemble average, depending on whether volcanic forcing is filtered or not. 2) EBM-KF conveniently assesses annually likelihoods of crossing a policy threshold. For example, based on temperature records up to the end of 2023, p=0.0017 that the climate state was 1.5°C over preindustrial, but there is a 16% likelihood that the GMST in 2023 itself could have been over that threshold. 3) A variant of the EBM-KF also approximates the spread of an entire climate model large ensemble using only one or a few ensemble members. 4) All variants of the EBM-KF are sufficiently fast to allow thorough sampling from non-Gaussian probabilistic futures, e.g., the impact of rare but significant volcanic eruptions. This sampling with the EBM-KF better determines how future volcanism may affect when policy thresholds will be crossed and what an ensemble with thousands of members exploring future intermittent volcanism reveals.

Changing windstorm characteristics over the US Northeast in a single model large ensemble

Abstract Extreme windstorms pose a significant hazard to infrastructure and public safety, particularly in the highly populated US Northeast (NE). However, the influence climate change and changing land use will have on these events remains unclear. A large ensemble generated using the Max-Planck Institute (MPI) Earth system model is used to generate projections of NE windstorms under different shared socioeconomic pathways (SSPs) and to attribute changes to projected land use land cover (LULC) change, externally forced changes and internal climate variability. To reduce the influence of coarse grid cell resolution and uncertainties in surface roughness lengths, windstorms are identified using simultaneous widespread exceedance of local 99th percentile 10 m wind speeds (U99). Projected declines in forest cover in the NE and the resulting reductions in surface roughness length under SSP3-7.0 lead to projections of large increases in U99 and derived windstorm intensity and scale. However, these projected changes in regional LULC under SSP3-7.0 are unprecedented in a historical context and may not be realistic. After corrections are applied to remove the influence of LULC on wind speeds, regionally averaged U99 exhibit declines for most of the single model initial-condition large ensemble (SMILE) members which are broadly proportional to the radiative forcing and global air temperature increase in the SSPs, with a median value of −0.15 ms−1 °C−1. While weak cyclones are projected to decline in frequency in the NE, intense cyclones and the resulting windstorms and indices of socioeconomic loss do not. Where present, significant trends in these loss indices are positive, and some MPI SMILE members generate future windstorms that are unprecedented in the historical period.

Substantial reduction in population exposure to sea level changes along the Chinese mainland coast through emission mitigation

Abstract Rising sea level increases the exposure to flooding and related damage in coastal areas with high population density and substantial economic activity. As global temperatures continue to rise due to climate change, sea levels have been consistently increasing and are projected to continue this upward trend. This study assesses the future exposure at provincial and city levels populations coastal mainland China coast to local sea level changes under five greenhouse gas (GHG) emission scenarios from IPCC-AR6, as well as two low-confidence scenarios accounting for the potential impact of uncertain ice sheet processes with low- and high-GHG emissions. We incorporate spatial heterogeneity into regional sea level projections and population projections from 2020 to 2100, extreme sea levels (ESLs) of 10-, 50-, and 100 year return periods (RP), and local coastal protection standards. Our findings indicate that the inundated areas expand continuously within the century with heightened exposure under higher emission scenarios. Although the coastal population is projected to decline, the fraction of the coastal population exposed to flooding increases across all scenarios, with accelerated growth under higher GHG emissions and higher ESLs. Zhejiang and Jiangsu emerge as the provinces most exposed to sea-level rise, whereas Taizhou, Nantong, Wuxi, Panjin, and Huzhou are identified as the top five cities with the highest population exposure to local sea level rise (SLR). Transitioning towards a sustainable scenario (i.e. SSP1-2.6) rather than a fossil fuel-intensive one (i.e. SSP5-8.5) can reduce the local SLR and substantially mitigate these exposures. Compared to the median projections under SSP5-8.5, aligning GHG emissions with SSP1-2.6 could reduce population exposure substantially in all coastal provinces, especially in Jiangsu, where population exposure to 100 year RP coastal floods would be reduced by ∼1.6 M in 2050 and by ∼5.4 M in 2100.

Rising global temperatures and its impact on sleep behavior of male redheaded bunting (Emberiza bruniceps).

Anthropogenic global warming is one of the most pervasive threats to nature and biodiversity. The magnitude with which earths' temperature is rising is affecting every lifeform uniquely; however, the studies highlighting the impacts of global warming on avian sleep are scarce. To this end, the present study was aimed at analyzing the impact of global warming on sleep behavior of a nocturnal migrant, Emberiza bruniceps. For this purpose, the birds were divided into two groups (N = 15 each), subjected to high (35 ± 1°C) and low (19 ± 1°C) temperature schedule with concurrent exposure to 8L:16D (short day; SD) photoperiod followed by 13L:11D (long day; LD). The experiment continued till 7 cycles of zugunruhe (LD) in birds. The results reveal significant impact of temperature treatment on initiation and quality of zugunruhe. Temporal distribution of activity and rest varied according to the temperature provided. Focusing on rest and specifically on sleep of birds, high ambient temperatures resulted in greater sleep fragmentation (evident by increased awakenings during night), whereas low temperature created a sleep conducive environment (evident by abundance of back sleep). Besides postural differences, high temperature resulted in reduced sleep duration, sleep onset latency and circulating plasma melatonin levels in comparison with low temperature suggesting the negative impact of high temperature on different sleep attributes. Not only sleep, seasonal physiology of birds such as hyperphagia, gain in body mass, and fat stores showed significant reduction in high temperature condition. Besides behavioral and physiological alterations, high ambient temperature led to elevated expression of temperature sensitive (trpv4, trpm8, hspa8, and hsp70) genes. Enhanced expression of chrm3 (responsible for wakefulness) also affirms sleep fragmentation in response to high temperature. Thus, the study highlights the negative impact of high temperature on birds' sleep behavior and seasonal physiology.

Structural Reuse of Decommissioned Ski Lift Steel Trusses for Load-Bearing Applications

The ongoing effects of climate change have led to a rise in global temperature, significantly reducing snow cover and resulting in the abandonment of numerous ski areas across Switzerland. As a result, many ski lifts have been decommissioned and left to deteriorate due to lenient local regulations. To address this issue, this paper presents a case study approach to repurposing steel trusses from abandoned ski lifts for a new structural application within the building industry. The design, sourcing, and construction of a new load-supporting column are described, focusing on reusing the ski lift steel trusses as a whole, without dismantling them into their components. After collection, these elements are adapted to comply with current building standards. By pouring out the hollow structure with the recently developed building material Cleancrete ©, a new load-bearing structure is developed. A comprehensive life cycle assessment (LCA) demonstrates the environmental performance of the steel–Cleancrete hybrid construction, which achieves a global warming potential (GWP) of 536.58 kg CO2-eq. In comparison, alternative designs using wood and concrete exhibited GWP values of 679.45 kg CO2-eq, +26.6%, and 1593.72 kg CO2-eq, +197.02%, respectively. These findings suggest that repurposing abandoned ski lift structures can significantly contribute to sustainable building practices, waste reduction, and the promotion of circular economy principles. The process outlined in this paper holds potential for future applications, particularly in the reuse of other steel components, ensuring continued circularity even as the supply of ski lift structures may dwindle.

Poultry Preslaughter Operations in Hot Environments: The Present Knowledge and the Next Steps Forward.

Poultry production faces significant challenges, including high feed prices, diseases, and thermal stress, which impact broiler welfare and productivity. Despite advances in cooling technologies and ventilation, preslaughter operations still lead to considerable losses. This review highlights the need for the improved management of thermal environments and animal logistics. Preslaughter operations typically involve fasting broilers for 8-12 h to reduce gastrointestinal contents and contamination. Following fasting, broilers are caught, crated, and transported. Stress levels vary based on distance and conditions, with manual catching often causing stress and injuries. Catching should occur during cooler periods to minimise these issues, and transport conditions must be carefully managed. Lairage, the waiting period after transport, should be kept short (1-2 h) in climate-controlled environments to avoid stress and deterioration. Proper handling and efficient unloading are essential to prevent injuries and reduce economic losses. Stunning methods, such as electronarcosis and a controlled atmosphere, aim to minimise suffering before slaughter, though practices vary culturally and religiously. Logistics and real-time monitoring technology are crucial for enhancing animal welfare during transportation. Effective planning and the optimisation of transport processes is vital for reducing stress and losses, especially with regard to rising global temperatures and production demands.

How Extreme Were Daily Global Temperatures in 2023 and Early 2024?

AbstractGlobal temperatures were exceptionally high in 2023/24. Every month from June 2023 to June 2024 set a new record, and September shattered the previous record by °C. The 2023 annual average approached °C above pre‐industrial levels. This results from both long‐term warming and internal variability, with the occurrence of an El Niño episode. However the amplitude of the 2023/24 anomalies was remarkable and surprised the scientific community. Here we analyze the rarity of 2023/24 global temperatures from a climate perspective. We show that a ‘normal’ year 2023 would have roughly equaled the previous annual record, and that the most extreme events of 2023/24 rank among the most extreme since 1940. Our analysis suggests that the 2023/24 event can be reconciled with the long‐term trend and an intense, but not implausible, peak of internal variability.

Lithium isotopes track changes in continental weathering regimes across the end-Permian mass extinction in Southwest China

It has been assumed there was a massive amount of volcanic CO2 injection into the Permian-Triassic atmosphere and ocean systems, leading to rapid climatic warming and expansion of marine anoxia. However, it remains intriguing how Earth recovered from such a CO2-driven hyperthermal condition. One potential mechanism involves the negative feedback between continental silicate weathering and atmospheric CO2, which could have helped maintain habitability across the end-Permian mass extinction (EPME) interval. This process can be examined using lithium isotopes (δ7Li), which reflect the balance of physical erosion and chemical weathering, and chemical weathering indices such as the Chemical Index of Alteration (CIA), which indicates the chemical alteration of parent materials during weathering. In this study, we analyze siliciclastic sedimentary rocks from the Lopingian to Lower Triassic depositional sequences in the HK-1 drill core at the Lengqinggou section, a terrestrial coastal depositional environment in Southwest China, to reconstruct changes in continental chemical weathering intensity across the EPME. We observed a significant ∼4 ‰ positive shift in δ7Li, accompanied by a marked decrease in Li content from 26 ppm to 6 ppm. Our corrected CIA data (CIAcorr) also exhibits a considerable decrease from 94 to 59 across the EPME. The new δ7Li and CIAcorr data from the terrestrial section indicate a decrease in overall chemical weathering intensity in Southwest China, alongside an increase in physical erosion rates, suggesting a shift from a transport-limited to a kinetically limited weathering regime across the EPME. These changes in the continental weathering regime appear to be linked to active volcanic activity near the South China Block, which led to massive deforestation and the collapse of soil systems. Dramatic reductions in chemical weathering intensity may result in inefficient atmospheric CO2 consumption through silicate weathering if other climatic and tectonic conditions remain constant, potentially contribute to maintaining high global surface temperatures and prolonged marine anoxia into the Early Triassic.

Quantifying the economy-wide employment effects of coal-fired power plants: Two different cases China and the United States

Ensuring a swift transition from coal to clean energy is essential for capping global temperature increases at 1.5 °C, but it poses significant economic and social challenges in coal-dependent regions. This paper examines the economy-wide employment impacts resulting from the activities of coal-fired power plants in China and the United States, the world's largest coal consumers. By analyzing observational data on the different stages of coal power, including both expansion and reduction in the two countries, we aim to derive insights that can inform a more effective and just transition during the phase-out of coal power. We leveraged unique periods post-2010 when China was predominantly opening coal plants while the US was closing them, identifying the economy-wide employment impacts at the county level. By using both two-way fixed effects and spatial econometric models for over 10 years of panel data, covering 2875 in China and 3233 counties in the US, we addressed spillover effects and ensured robust and comprehensive results. Our findings revealed that in China, coal plant deployment increased employment both locally and in the neighboring counties. In the U.S., our findings indicate that before 2015, closing coal plants generally had a negative impact on jobs. However, after 2015, when the U.S. introduced new federal and state-level transition policies, the impact on employment became positive. While it is hard to prove these policies directly facilitate the just transition, our findings demonstrate that they do not hinder the employment aspect of a just transition focused on coal power generation at a regional scale.

Integrating environmental remediation with biodiesel production from toxic non-edible oil seeds (Croton bonplandianus) using a sustainable phyto-nano catalyst

In the current situation of the environmental uprising toxicology, rising global temperature, and energy-depleting urges to explore and discover more renewable and greener ecological-benefiting energy resources. Biobased renewable fuels generated by using waste products can help in waste management, climate change mitigation, and a low-carbon future. The main objective of this research is to produce environment-friendly and cost-effective biofuel. The potentiality of the novel, toxic, waste, and inedible feedstock Croton bonplandianus was evaluated for biodiesel synthesis through transesterification utilizing a Phyto-nano catalyst of potassium oxide prepared by Croton bonplandianus floral stalk's aqueous extract focusing on waste management. Phyto-nano catalyst characterization was done through innovative tools such as Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS), Zeta Potential (ZP), X-Ray Diffraction (XRD), Fourier Transformed Infrared spectroscopy (FTIR), and Diffuse Reflectance Spectroscopy (DRS). The characterization results revealed that the potassium oxide phyto-nanocatalyst possesses an average nanoparticle size of 44.5 nm. This size is optimal for enhanced catalytic activity, indicating significant potential for efficient catalysis. The highest yield (94 %) of biodiesel was secured at optimized reaction conditions of catalyst quantity (0.50 wt%), reaction time (180 min), methanol: oil ratio (9:1), and reaction thermal point (70 °C). Transformation of triglycerides to methyl esters was confirmed by GC/MS, NMR, and FTIR techniques. A total of 21 methyl esters were observed in Croton bonplandianus biodiesel confirmed via GC/MS results. Evaluation of fuel properties was done and matched with international fuel standards. The conclusive remarks for the conducted research are that Croton bonplandianus has a high potential for biodiesel production by applying Phyto-nanocatalysts of potassium oxide while dealing with hazardous environmental conditions and waste management. Phyto nanocatalyst of potassium oxide can be reused and gives the same yield after several cycles of reusability, this reusability of heterogenous Phyto nanocatalyst can reduce to total cost of biodiesel production and can contribute towards circular economy.

Forecasting crude oil prices with global ocean temperatures

This paper explores the role of ocean temperature (OT) in forecasting crude oil prices. Global OT shows statistically and economically significant predictive power, with corresponding in-sample and out-of-sample R2s of 1.81 % and 1.74 %, respectively. Both southern and northern hemisphere OTs can predict future oil prices, and the former is more predictive. Compared to the Atlantic, OTs in the Indian and Pacific Oceans display considerable predictive gains. In addition, we find that OTs have stronger forecasting power for crude oil prices in the recent period, with the in-sample R2 of global OT for the recent decade's sample reaching as high as 2.74 %. Correspondingly, we find that OTs' predictive power in the full sample can be explained through two channels: market risk and investor attention. In the recent period, in addition to these two channels, OTs have also influenced crude oil prices through the oil fundamental channel.

Drying trend in land and sea in East Asia during the warm season over the past four decades

Abstract The East Asian region is typically characterized by warm and humid conditions from late spring to summer. However, in recent decades, this region has experienced an increase in severe drying conditions, deviating from historical climatological patterns. This study investigated the precipitation-evaporation (P-E) trends across land and sea regions in East Asia (EA) during the extended summer season (April to September) from 1980 to 2022, and the key physical processes driving these trends through moisture budget decomposition and numerical experiments. The results reveal pronounced drying trends in southeastern China and the Yellow Sea and parts of the Korea Strait and Korean Peninsula over the past 43 years. The underlying physical processes driving these drying conditions differ between land and sea in EA. In southeastern China, the drying is driven by dynamic processes, particularly moisture divergence related to wind changes. This is linked to anomalous strengthening of descending motion due to the Indo-Pacific warm pool warming induced by both anthropogenic global warming and natural Pacific Decadal Oscillation-like sea surface temperature (SST) patterns. Conversely, drying in the Yellow Sea and adjacent areas is influenced by thermodynamic moisture advection. The altered humidity distribution due to global warming-induced SST patterns, which are higher over the Northwest Pacific marginal sea and lower in inland China, drives dry air transport from inland China to the Yellow Sea via background southwesterly wind. These findings enhance our understanding of the drying trend and their distinct processes in EA’s land and sea areas during the extended summer.

Cyanobacterial Blooms in City Parks: A Case Study Using Zebrafish Embryos for Toxicity Characterization

Cyanobacteria are photosynthetic prokaryotes that play an important role in the ecology of aquatic ecosystems. However, they can also produce toxins with negative effects on aquatic organisms, wildlife, livestock, domestic animals, and humans. With the increasing global temperatures, urban parks, renowned for their multifaceted contributions to society, have been largely affected by blooms of toxic cyanobacteria. In this work, the toxicity of two different stages of development of a cyanobacterial bloom from a city park was assessed, evaluating mortality, hatching, development, locomotion (total distance, slow and rapid movements, and path angles) and biochemical parameters (oxidative stress, neurological damage, and tissue damage indicators) in zebrafish embryos/larvae (Danio rerio). Results showed significant effects for the samples with more time of evolution at the developmental level (early hatching for low concentrations (144.90 mg/L), delayed hatching for high concentrations (significant values above 325.90 mg/L), and delayed development at all concentrations), behavioral level (hypoactivity), and biochemical level (cholinesterase (ChE)) activity reduction and interference with the oxidative stress system for both stages of evolution). This work highlights the toxic potential of cyanobacterial blooms in urban environments. In a climate change context where a higher frequency of cyanobacterial proliferation is expected, this topic should be properly addressed by competent entities to avoid deleterious effects on the biodiversity of urban parks and poisoning events of wildlife, pets and people.

Increasing Optimum Temperature of Vegetation Activity Over the Past Four Decades

AbstractOver the past four decades, global temperatures have increased more rapidly than before, potentially reducing vegetation activity if temperatures exceed the optimum temperature (Topt). However, plants have the capacity to acclimate to rising temperatures by adjusting Topt, thereby maintaining or even enhancing photosynthesis and carbon uptake. Despite this, it remains unclear how Topt of vegetation activity changes over time and to what extent global vegetation can acclimate to current temperature changes. In this study, we evaluated the temporal trends of Topt of vegetation activity and the thermal acclimation magnitudes globally using three remote‐sensed vegetation indices and eddy‐covariance observations of gross primary productivity from 1982 to 2020. We found that the global Topt of vegetation activity has increased at an average rate of 0.63°C per decade over the past four decades. The increase in Topt closely tracked the rise in annual maximum daily mean temperature (Tmax), indicating that thermal acclimation has occurred widely across the globe. Globally, we found an average thermal acclimation magnitude of 0.38°C per 1°C increase in Tmax. Notably, polar and continental regions exhibited the highest thermal acclimation magnitudes, while arid areas showed the lowest. Additionally, the thermal acclimation magnitude was positively affected by interannual temperature variability and negatively affected by soil moisture and vapor pressure deficits. Our findings indicate that terrestrial ecosystems have acclimated to current climate warming trends with varying degrees, suggesting a greater potential for land carbon uptake. Moreover, these results highlight the necessity for earth system models to integrate the thermal acclimation of Topt to better forecast the global carbon cycle.

Variability of seasonal temperature from 1990 to 2020 within Oum Er Rbia hydraulic basin (Morocco): Study of trends and anomalies

Abstract The fifth report of the Intergovernmental Panel on Climate Change (IPCC) indicates that global temperatures have increased during the 20th century. In Morocco, numerous studies have unveiled that the nation has been contending with the effects of global warming for several decades, attributed to its geographical location. The studies have mainly focused on the evolution of rainfall and the recurrence of droughts. Nevertheless, temperature variations remain less addressed, especially at large spatial scales. This paper aims to study the seasonal temperature variability in the large hydraulic basin of Oum Er Rbia, focusing on its anomalies and trends as well as identifying their impacts on the basin’s territory. Indeed, the large basin of Oum Er Rbia occupies more than 48,.000 km2 and is characterized by an arid to semi-arid climate. Its water resources are important and play an essential role in the country’s socio-economic development. This basin is well-known for its agricultural activity. Although its water and economic potential are significant, the great basin is considered vulnerable to climatic variations, which strongly condition its development. Considering the significance of temperature trends within the framework of global warming, this current study delves into the topic of seasonal temperature variability within the expansive hydraulic basin of Oum Er Rbia. Based on statistical analysis using the temperature anomaly index and the Mann-Kendall trend test, this study reveals that strong interannual variability marked the evolution of seasonal temperatures during the period of 1990-2020, with a remarkable upward trend during the autumn and spring. When the temperature increase, the temperature increases in turn: thus, the negative impacts affect both water resources and the agriculture sector, which suffers from the combined effect of increased evapotranspiration and reduction of irrigation water.

A Dirt(y) World in a Changing Climate: Importance of Heat Stress in the Risk Assessment of Pesticides for Soil Arthropods.

The rise in global temperatures and increasing severity of heat waves pose significant threats to soil organisms, disrupting ecological balances in soil communities. Additionally, the implications of environmental pollution are exacerbated in a warmer world, as changes in temperature affect the uptake, transformation and elimination of toxicants, thereby increasing the vulnerability of organisms. Nevertheless, our understanding of such processes remains largely unexplored. The present study examines the impact of high temperatures on the uptake and effects of the fungicide fluazinam on the springtail Folsomia candida (Collembola, Isotomidae). Conducted under non-optimum but realistic high temperatures, the experiments revealed that increased temperature hampered detoxification processes in F. candida, enhancing the toxic effects of fluazinam. High temperatures and the fungicide exerted synergistic interactions, reducing F. candida's reproduction and increasing adult mortality beyond what would be predicted by simple addition of the heat and chemical effects. These findings highlight the need to reevaluate the current ecological risk assessment and the regulatory framework in response to climate changes. This research enhances our understanding of how global warming affects the toxicokinetics and toxicodynamics (TK-TD) of chemicals in terrestrial invertebrates. In conclusion, our results suggest that adjustments to regulatory threshold values are necessary to address the impact of a changing climate.

How unusual was Australia's 2017–2019 Tinderbox Drought?

Australia’s Murray-Darling Basin experienced three consecutive years of meteorological drought across 2017–2019, collectively named the ‘Tinderbox Drought’. Rainfall deficits during the three-year drought were most pronounced in the Australian cool season (April to September). Deficits in both the cool season and annual total rainfall were unprecedented in the instrumental record. However, the instrumental record provides just one of a range of equally plausible climate trajectories that could have occurred during this period. To determine if the Tinderbox Drought was outside this range, we used observational data from prior to the onset of the drought to construct Linear Inverse Models (LIMs) that emulate the stationary statistics of Australian rainfall and its connection to global sea surface temperature (SST) anomalies. Overall, we find that rainfall deficits were most unusual in the northern Murray-Darling Basin, and during the final year of the drought. The global SST anomalies observed during the first two years of the Tinderbox Drought, particularly the cool anomalies in the central tropical Pacific and western Indian Ocean, are not typically associated with low rainfall across the Murray-Darling Basin. In terms of single-year rainfall anomalies, the only aspect of the Tinderbox Drought that was beyond the range of the LIMs was annual-total rainfall over the northern Murray-Darling Basin during 2019. This coincided with an extreme positive Indian Ocean Dipole event that was also beyond the range of the LIMs. When considered in terms of basin-wide rainfall over the full three years, rainfall deficits during the Tinderbox Drought were beyond the LIM range in terms of both cool-season and annual-total rainfall. This suggests an anthropogenic contribution to the severity of the drought—likely exacerbated by the 2019 extreme positive Indian Ocean Dipole event.

Late Holocene extraordinary palaeoflood events and their climatological context in the Shahe River, Huaihe River Basin, China

Palaeoflood events represent immediate hydrological responses to extreme climate change. A loess-paleosol sedimentary profile containing three overbank flood deposits (OFD1, OFD2, and OFD3) layers that recorded palaeoflood events was discovered on the platform scarp of the Shahe River, a tributary of the Huaihe River through a field investigation. Sediment samples were collected, and their physicochemical properties, as well as optically stimulated luminescence (OSL) dating, were analyzed. The results indicated that OFD1, OFD2, and OFD3 were indeed overbank flood deposits influenced by hydrodynamic forces. However, OFD3 and OFD1 consisted primarily of sand (>60 %) in terms of particle size composition, whereas paleosol (S0), transitional loess (Lt), and Malan loess (L1) mainly comprised silt (>70 %). Moreover, the magnetic susceptibility values of OFD3 and OFD1 exceeded those of S0, Lt, and L1. The contents of Na2O, K2O, and SiO2 were higher, while their contents of Al2O3 and Fe2O3 were lower in OFD3 and OFD1. These suggested that OFD3 and OFD1 may originate from weathered bedrock materials transported from the upper reaches of the Shahe River under significant hydrodynamic forces. The particle size composition, magnetic susceptibility value, and geochemical element composition of OFD2 were similar to those of S0, Lt, and L1 but diverged significantly from those of OFD1 and OFD3, indicating that OFD2 originated from loess and soil sediments widely distributed on both sides of the valley. Through OSL dating and stratigraphic chronological framework of the sedimentary profile, these three extraordinary palaeoflood events in the Huaihe River Basin occurred during the late Holocene, ∼1470 a. The analysis of high-resolution climate proxy indicators, atmospheric circulation factors, and global mean temperature demonstrated a direct correlation between these extreme flood events and abrupt climate changes during ∼ 1470 a. This period corresponded to severe climate deterioration during the Northern and Southern Dynasties (589–420 CE) in China. These findings are crucial for enhancing our understanding of regional hydrological climate responses to global changes.

Ensemble Based Estimation of Wet Refractivity Indices Using a Functional Model Approach

AbstractThe estimation of the wet refractivity indices is crucial for applications like weather predictions or improving the accuracy of real‐time positioning techniques. Traditionally, solving the inverse tomography problem to estimate these atmospheric parameters has been challenging due to its ill‐posed nature and high computational demands, necessitating additional constraints. To overcome these challenges, the data assimilation method is proposed here to integrate Global Navigation Satellite System (GNSS) observations into a background model. In this study, the Ensemble Kalman Filter (EnKF) was served as the assimilation core to reduce the computational load and to enable the epoch‐wise estimation of wet refractivity indices. The Global Pressure and Temperature 3 (GPT3w) model was utilized as the background, and wet refractivity indices at each epoch were transformed into B‐spline coefficients, representing state vector parameters. Subsequently, GNSS derived zenith wet delay (ZWD) values were integrated into the model using the EnKF method. The study's region encompassed the western parts of Europe and incorporated approximately 893 GNSS stations. Evaluation spanned from 1 January 2017 to 31 December 2017. The estimated wet refractivity indices from the proposed method were compared with observations from 16 existing radiosonde stations, radio occultation data, and ZWD values from the 47 selected GNSS test stations. Additionally, calculated ZWD values, resulting from the integration of wet refractivity indices, were compared to the ZWD values from 47 test stations in the study region. The numerical results demonstrated that the proposed method achieved a root mean square error value of approximately 2.6 ppm, which was nearly 49% and 18% lower than that of the considered empirical and numerical atmospheric models, respectively.