Global Surface Research Articles

Increased Surface Temperatures of Habitable White Dwarf Worlds Relative to Main-sequence Exoplanets

Abstract Discoveries of giant planet candidates orbiting white dwarf (WD) stars and the demonstrated capabilities of the James Webb Space Telescope bring the possibility of detecting rocky planets in the habitable zones (HZs) of WDs into pertinent focus. We present simulations of an aqua planet with an Earth-like atmospheric composition and incident stellar insolation orbiting in the HZ of two different types of stars—a 5000 K WD and main-sequence K-dwarf star Kepler-62 (K62) with a similar effective temperature—and identify the mechanisms responsible for the two differing planetary climates. The synchronously rotating WD planet's global mean surface temperature is 25 K higher than that of the synchronously rotating planet orbiting K62, due to its much faster (10 hr) rotation and orbital period. This ultrafast rotation generates strong zonal winds and meridional flux of zonal momentum, stretching out and homogenizing the scale of atmospheric circulation, and preventing an equivalent buildup of thick, liquid water clouds on the dayside of the planet compared to the synchronous planet orbiting K62, while also transporting heat equatorward from higher latitudes. White dwarfs may therefore present amenable environments for life on planets formed within or migrated to their HZs, generating warmer surface environments than those of planets with main-sequence hosts to compensate for an ever shrinking incident stellar flux.

Sustainability of regional Antarctic ice sheets under late Eocene seasonal atmospheric conditions

Abstract. The Eocene–Oligocene transition (EOT) is marked by a sudden δ18O excursion occurring in two distinct phases approximately 500 kyr apart. These phases signal a shift from the warm middle to late Eocene greenhouse climate to cooler conditions, with global surface air temperatures decreasing by 3–5 °C and the emergence of the first continent-wide Antarctic ice sheet (AIS). While ice sheet modelling suggests that ice sheet growth can be triggered by declining pCO2, it remains unclear how this transition was initiated, particularly the first growth phase that appears to be related to oceanic and atmospheric cooling rather than ice sheet growth. Recent climate model simulations of the late Eocene show improved accuracy but depict climatic conditions that are not conducive to the survival of incipient ice sheets throughout the summer season. This study therefore examines whether it is plausible to develop ice sheets of sufficient scale to trigger the feedback mechanisms required to disrupt the atmospheric regime above the Antarctic continent during warm and moist late Eocene summers and establish more favourable conditions for ice expansion. We aim to assess the sustainability of an incipient AIS under varying radiative, orbital and cryospheric forcing. To do so, we evaluate Community Earth System Model 1.0.5 simulations, using a 38 Ma geographical and topographical reconstruction, considering different radiative and orbital forcings. The climatic conditions prevailing during (and leading up to) the EOT can be characterised as extremely seasonal and monsoon-like, featuring a short yet intense summer period and contrasting cold winters. A narrow convergence zone with moist convection around the region with high sub-cloud equivalent potential temperature exhibits a ring-like structure, advecting moist surface air from the Southern Ocean in both summer and winter. This advection leads to high values of moist static energy and subsequent precipitation in coastal regions. Paradoxically, this atmospheric regime – particularly its coastal precipitation in winter – appears to be necessary for the sustenance of the moderately sized regional ice sheets we imposed on the continent, contrary to our assumption that these ice sheets would disrupt the atmospheric regime. This underscores a hysteresis effect for regional ice sheets on the Antarctic continent, suggesting the potential for a significant volume of ice on the continent without imminent full glaciation prior to the EOT.

Mapping of water spread dynamics of a tropical Ramsar wetland of India for conservation and management.

Wetlands are dynamic ecosystems vital for sustaining ecological health and development at regional and global scales. Geospatial tools have emerged as essential for managing wetland ecosystems. This study assessed the spatiotemporal dynamics of water spread in the Point Calimere Wetland, a coastal Ramsar site located along the Bay of Bengal, India, from 1984 to 2023. The analysis based on Global Surface Water Explorer (GSWE) and Normalized Difference Water Index (NDWI) derived from Landsat 5, 7, and 8 data revealed that 21% of the total wetland area showed an increasing trend. In comparison, 5.7% of the area showed a decreasing trend of surface water coverage, largely driven by erosion and climatic variability. The mean water spread increased from 119.47 km2 (2000-2003) to 160.88 km2 (2020-2023), with notable seasonal fluctuations. Among all seasons, the monsoon with the highest surge (41.1%) in water dynamics reported the largest water spread in 2020-2023 (221.87 km2). A moderate positive and negative relationship was noted between rainfall and water spread (r = 0.35) and temperature and water spread (r = - 0.43). A marked increase in habitat patches and edge density between 2000-2003 and 2020-2023 indicates the wetland's vulnerability to changing climatic conditions and the critical role of seawater intrusion, shoreline changes, and tidal forces in shaping its hydrological dynamics. The data presented on the historical water dynamics in this study is invaluable for the conservation planning and management of wetlands to support the associated coastal biodiversity and livelihood of the dependent communities.

Crashworthiness analysis of a novel corrugated multi-cellular tube structure

This study innovatively combines Fourier curves with circular tube design and proposes a novel corrugated multi-cellular tube structure (NCMTS), aiming to improve crashworthiness. The accuracy of the finite element model was validated through axial quasi-static compression tests. The influence mechanism of different structural parameter combinations on the energy absorption capacity of NCMTS was further investigated. The results reveal that the EA of NCMTS increases monotonically with rising of parameter ru , with a notable acceleration in growth rate as parameter Rc is elevated. Notably, the combination of larger values of ru and Rc , and tout and tc can significantly improve the crashworthiness performance. Moreover, appropriately increasing C 1 and C can increase the EA of NCMTS by approximately 50%. Through multi-objective optimization analysis utilizing the global response surface method, the optimal structural parameters for NCMTS were identified: at Rc = 0.68, C = −0.57, C 1 = 0.16, tout = 2.0 mm, tc = 0.68, the EA, SEA and IPCF reached 7.02 kJ, 15.33 kJ/kg and 400 kN respectively. This study offers valuable guidance for the design and optimization of high-performance collision energy-absorbing structures.

Mapping the fine spatial distribution of global offshore surface seawater mariculture using remote sensing big data

ABSTRACT Against the backdrop of near-saturation in global marine capture fisheries, current mariculture production now exceeds one-third of capture production and continues to hold significant growth potential. However, the lack of spatially detailed global offshore surface seawater mariculture (OSSM) data hampers scientific understanding and management from a spatial perspective. In this study, utilizing multi-source remote sensing time-series imagery, we achieve the world’s first spatially detailed mapping of both raft and cage mariculture types. The results show that (1) in 2020, the total global OSSM area was 20,079.97 km², comprising 85.04% raft mariculture and 14.96% cage mariculture. 95.33% of the OSSM was concentrated in Asia. (2) The interpreted national OSSM areas align well with the FAO production statistics trends. Obtaining these areas using remote sensing offers greater timeliness compared to production statistics, which is advantageous for dynamic monitoring and production estimation. (3) Through analysis of global pond aquaculture data, it was found that most coastal areas worldwide had a single-type of aquaculture. However, in parts of Asia, regions with both OSSM and pond aquaculture coexisted. The data acquired in this study, characterized by detailed spatial information, provide significant insights for constructing spatial models of mariculture, researching resource-environment effects, and informing management practices.

Impacts of Antarctic Sea Ice Change on Global Warming Pattern Inferred From CMIP6 Intermodel Spread

AbstractGlobal climate models generally project a robust decline in Antarctic sea ice (ASI) under increased atmospheric carbon dioxide (CO2) while an ASI expansion has been observed over the recent four decades. Motivated by the apparent model‐observation discrepancy, this study investigates the influences of ASI change on global warming pattern by exploiting the spread across models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6). The results indicate a close intermodel relationship between ASI change and global sea surface warming pattern. Models with less ASI loss tend to produce a weaker warming globally, especially in the Southern Ocean, subtropical southeastern Pacific Ocean, and tropical Pacific Ocean. This extratropical teleconnection to the tropics agrees with the theory of cross‐equator energy transport. By correcting the modeled ASI change with observations, we can bring the SST warming pattern closer to observations, especially in the Southern Hemisphere and tropics.

Uncertainties on projecting future cloud feedback and possible ways to address them

The issue of climate change is hotly debated in today's world. More attention is paid to climate-related issues, including global warming. It is accepted that clouds are responsible for the rise of global surface temperature. People have spent decades trying to develop climate models that are capable of more accurate cloud projections without getting the ultimate solution since clouds are complicated compounds. This review article focuses on clouds' role in global warming, the mechanisms of cloud warming the Earth's surface, uncertainties of cloud parameterizations, and some researches aiming at mitigating the uncertainties . This paper concluded that although advancements are made in adding new constraints and taking new observable variables, uncertainty remains. The majority of new methods and constraints reviewed in this paper are still limited to different extents. Therefore, more complete climate models that can be applied to more conditions and regions could be the direction for future studies in the field.

INTRODUCTION: CLIMATE SUSTAINABILITY – EVIDENCE AND POLICY

Last year saw yet another year of weather extremes. The Copernicus Climate Change Service run by the European Centre for Medium-Range Weather Forecasts on behalf of the European Commission (Copernicus, 2024) measured 2023 as being globally the warmest year since records began in 1850. This was by a large margin (0.17 per cent) over the previous record in 2016, with global surface air temperature at nearly 1.5°C above pre-industrial levels. While last year’s observations embodied an El Niño effect, which every few years sees temperatures affected by warmer waters coming to the surface of the tropical eastern Pacific Ocean, changes and anomalies consistently observed over the last few years across the globe are becoming more pronounced. What is commonly labelled “climate change” is turning into a global climate emergency. No economy or society are immune to its effects. Today, we see the global average temperature at over 1.1°C above pre-industrial levels, a rise that has been extraordinarily rapid on a planetary timescale, and one that has been primarily caused through our (humans) burning fossil fuels. Nearly a decade has passed since the United Nations’ Climate Change Conference in 2015, COP21, where 196 nations adopted The Paris Agreement – a legally binding international treaty on climate change. Its goal was to hold “the increase in the global average temperature to well below 2°C above pre-industrial levels” and to pursue efforts “to limit the increase to 1.5°C”.

Assessment of the global ocean heat content and North Atlantic heat transport over 1993–2020

Understanding changes in global ocean heat content (OHC) is essential for investigating Earth’s energy imbalance and climate change. OHC trends are assessed using four state-of-the-art ocean reanalyses and one objective analysis. The spatial OHC trend patterns captured by reanalyses are consistent with each other, but sensitive to the selected time period. A higher proportion of heat uptake in the 100–2000 m sub-surface layer over 2001–2010 than 1994–2000 contributed to the temporary slowdown in global surface warming. The North Atlantic meridional overturning circulation (MOC) and heat transport show better agreement with RAPID observations compared with previous studies. Zonal mean OHC trends in the North Atlantic over 40–60 °N differ for the MOC increasing (2000–2004) and decreasing periods (2005–2010) and OHC increases are more concentrated between 30 and 40 °N in the later MOC increasing period (2011–2022). These results do not support previous studies suggesting that MOC changes are reducing Earth’s mean surface warming.

Modeling global surface dust deposition using physics-informed neural networks

Paleoclimatic measurements serve to understand Earth System processes and evaluate climate model performances. However, their spatial coverage is generally sparse and unevenly distributed across the globe. Statistical interpolation methods are the prevalent techniques to grid such data, but these purely data-driven approaches sometimes produce results that are incoherent with our knowledge of the physical world. Physics-Informed Neural Networks follow an innovative approach to data analysis and physical modeling through machine learning, as they incorporate physical principles into the data-driven learning process. Here, we develop a machine-learning algorithm to reconstruct global maps of atmospheric dust surface deposition fluxes from paleoclimatic archives for the Holocene and Last Glacial Maximum periods. We design an advection-diffusion equation that prevents dust particles from flowing upwind. Our physics-informed neural network improves on kriging interpolation by allowing variable asymmetry around data points. The reconstructions display realistic dust plumes from continental sources towards ocean basins following prevailing winds.

Growing aridity poses threats to global land surface

Global warming has impacted water cycle, but not exist a global study of the changes at global scale of the impacts on water available for plants. Here, cloud-optimized monthly aggregated climate reanalysis from the European Centre for Medium-Range Weather Forecasts dataset indicates that from 1960 to 2023, 27.9% of the global land surface became significantly more arid, while 20.5% became significantly less arid. This indicates a shift towards drier climates, with humid, semi-humid, and semi-arid areas decreasing by 8.51, 1.45, and 0.53 million-km², respectively, and arid and hyper-arid areas increasing by 6.34 and 4.18 million-km², respectively. This total increase of 9.99 million km² in arid areas represents 5.9% of the global land surface, excluding Greenland and Antarctica. Accelerated aridification has occurred in already dry regions, such as South-west North-America, North-Brazil, the European-Basin, North-Africa, the Middle-East, the Sahel, and central-Asia, with central-Africa as a new hotspot. The main driver is the disproportionate increase in potential evapotranspiration relative to rainfall, attributed to rising atmospheric temperatures, which also reduces the land’s carbon sink capacity, potentially exacerbating climate warming.

Global Gridded Crop Production Dataset at 10 km Resolution from 2010 to 2020

The global gridded crop production dataset at 10 km resolution from 2010 to 2020 (GGCP10) for maize, wheat, rice, and soybean was developed to address limitations of existing datasets characterized by coarse resolution and discontinuous time spans. GGCP10 was generated using a series of adaptively trained data-driven crop production spatial estimation models integrating multiple data sources, including statistical data, gridded production data, agroclimatic indicator data, agronomic indicator data, global land surface satellite products, and ground data. These models were trained based on agroecological zones to accurately estimate crop production in different agricultural regions. The estimates were then calibrated with regional statistics for consistency. Cross-validation results demonstrated the models’ performance. GGCP10’s accuracy and reliability were evaluated using gridded, survey, and statistical data. This dataset reveals spatiotemporal distribution patterns of global crop production and contributes to understanding mechanisms driving changes in crop production. GGCP10 provides crucial data support for research on global food security and sustainable agricultural development.

Evidence and Explanation for the 2023 Global Warming Anomaly

In 2023, the rapid increase in global temperature of around 0.25 °C caught the scientific community by surprise. Its cause has been investigated largely by exploring variations on a long-term trend, with little success. Building on previous work, this paper proposes an alternative explanation—on decadal timescales, observed temperature shows a complex, nonlinear response to forcing, stepping through a series of steady-state regimes. The 2023 event is nominated as the latest in the sequence. Step changes in historical and modeled global mean surface temperatures (GMSTs) were detected using the bivariate test. Each time series was then separated into gradual (trends) and rapid components (shifts) and tested using probative criteria. For sea surface, global and land surface temperatures from the NOAA Global Surface Temperature Dataset V6.0 1880–2022, the rapid component of total warming was 94% of 0.72 °C, 78% of 1.16 °C and 74% of 1.93 °C, respectively. These changes are too large to support the gradual warming hypothesis. The recent warming was initiated in March 2023 by sea surface temperatures (SSTs) in the southern hemisphere, followed by an El Niño signal further north. Global temperatures followed, then land. A preceding regime shift in 2014 and subsequent steady-state 2015–2022 was also initiated and sustained by SSTs. Analysis of the top 100 m annual average ocean temperature from 1955 shows that it forms distinct regimes, providing a substantial ‘heat bank’ that sustains the changes overhead. Regime shifts are also produced by climate models. Archived data show these shifts emerged with coupling of the ocean and atmosphere. Comparing shifts and trends with equilibrium climate sensitivity (ECS) in an ensemble of 94 CMIP5 RCP4.5 models 2006–2095 showed that shifts had 2.9 times the influence on ECS than trends. Factors affecting this relationship include ocean structure, initialization times, physical parameters and model skill. Single model runs with skill ≥75 showed that shifts were 6.0 times more influential than trends. These findings show that the dominant warming mechanism is the sudden release of heat from the ocean rather than gradual warming in the atmosphere. The model ensemble predicted all regime changes since the 1970s within ±1 year, including 2023. The next shift is projected for 2036, but current emissions are tracking higher than projected by RCP4.5. Understanding what these changes mean for the estimation of current and future climate risks is an urgent task.

Interannual Variation of Global Surface Potential Vorticity Forcing in Boreal January and Its Link with Long-Persisting Droughts in Southwest China

Abstract An increasing number of studies have recognized the essential influence of surface potential vorticity (PV) forcing on atmospheric circulation. In this study, we investigated the temporal characteristics of global surface PV forcing in January and its associated climate anomalies. The global surface PV forcing exhibited a pronounced decreasing trend, implying reduced forcing on atmospheric PV. Its interannual component was accompanied by cold winters on the Eurasian and North American continents and long-persisting droughts in southwest China (SWC), consistent with the coexistence of these extreme events. Based on the global surface PV forcing index, the mechanism underlying long-persisting droughts, which lasted from October to January, was investigated. The formation mechanisms of persistent drought varied monthly. Specifically, the occurrence of drought in October was closely related to Rossby wave activity over Eurasia, which enhanced the anomalous anticyclone over the Tibetan Plateau and subsequently induced air descent over SWC. In contrast, drought in November and December could be ascribed to La Niña events in the central Pacific, which facilitated subsidence over SWC through local meridional circulation anomalies. Distinct from other months, the combined effects of La Niña events and circulation anomalies over northern Eurasia caused the drought in January. The former reduced precipitation over southern SWC, whereas the latter influenced precipitation over central SWC. The present study provides novel insights into simultaneous extreme events in the Northern Hemisphere. Significance Statement Long-persisting droughts in southwest China (SWC) usually coexist with cold winters in the Eurasian and North American continents. Here, we suggested that the coexistence of these extremes was closely linked to interannual variability in global surface potential vorticity forcing. Based on this relationship, the mechanism underlying long-persisting droughts in SWC, lasting from October to January, was investigated. The formation of these droughts could be ascribed to Rossby wave activity over Eurasia in October and to La Niña events in the central Pacific in November and December. The drought in January was ascribed to the combined effects of La Niña and circulation anomalies over northern Eurasia. This study provides a broader view for understanding extremes that occurred simultaneously in the Northern Hemisphere.

Land Degradation Neutrality: Concepts and Implementation Mechanism

All forms of life on Earth depend on ‘land’ through varied means, such as finding habitats, getting the right environment for human beings to survive, using land as substrate for agriculture etc. In the recent times, land-based ecosystem goods and services have gone to unprecedented levels of land exploitation causing a sharp increase in the process of land degradation. About one-third of the global land surface has been affected by desertification and land degradation (DLD). More than 100 countries, comprising of about 2.6 billion people are under the effect of DLD-directly or in directly. In Asia alone, 38 out of 48 countries are affected while in India, about 32% of its geographical area is undergoing the process of DLD. The present paper discusses the fundamental concepts of land degradation, its causes and drivers and methods to mitigate it. National, regional and global efforts on mapping, monitoring and assessment of land degradation have been reviewed. United Nation’s Land Degradation Neutrality (LDN) program, its conceptual framework and its implementation mechanisms in India has been discussed in detail.

More flow upstream and less flow downstream: The changing form and function of global rivers.

We mapped daily streamflow from 1984 to 2018 in approximately 2.9 million rivers to assess recent changes to global river systems. We found that river outlets were dominated by significant decreases in flow, whereas headwaters were 1.7 times more likely to have significantly increased flow than decreased. These changes result in a significant upstream shift in streamflow experienced by about 29% of the global land surface. We found the most changes in the smallest steams in our study: increases in erosion potential (approximately 5% increase in stream power), flood frequency (approximately 42% increase in 100-year floods), and likely nutrient dynamics (altered seasonal flow regimes). We revealed these changes using "detail at scale" by mapping millions of individual rivers. Widely adopting this approach could reveal other changes to the hydrosphere.

Future forecast of global mean surface temperature using machine learning and conventional time series methods

Future forecast of global mean surface temperature using machine learning and conventional time series methods

Extrapolation-Based Regionalized Re-evaluation of the Global Estuarine Surface Area

At the interface between the continental and oceanic domains, estuaries are essential components of the land–ocean aquatic continuum. These coastal ecosystems play a significant role in biogeochemical cycles, as they transform and export large amounts of terrigenous carbon and nutrients from rivers to marine waters. Because of this intense biogeochemical processing, they are significant ecosystems in terms of greenhouse gas exchange with the atmosphere. However, in spite of recent advances in remote sensing and the need for accurate estimates to calculate regional and global estuarine budgets, the global quantification of the estuarine spatial extent available for gas exchange has not been updated in over a decade and remains poorly constrained. This is due to the lack of a global extensive database, the diversity of estuaries, and the controversial definition of their boundaries. To address these challenges, a hybrid approach was developed that combines the surface areas of over 700 estuaries worldwide (extracted from the literature or calculated using geographical information systems) with a novel extrapolation method to provide type-specific regional estimates for 45 regions. The three estuarine types considered are ‘tidal systems and deltas’, ‘lagoons’, and ‘fjords’. The upscaling formula applied is determined and calibrated using data from several regions where an extensive survey of total estuarine surface areas was available. The new global estimate of 733,801 ± 39,892 km2 (mean ± 2 σ) is 31% lower than the previous global assessment. It also provides quantitative uncertainty estimates for regional and global estuarine surface areas as well as a breakdown between tidal systems and deltas (294,956 ± 30,780 km2), lagoons (179,946 ± 12,056 km2), and fjords (259,899 ± 22,328 km2). This decrease of the global estuarine surface area is related to the novel method used in this study and does not reflect a temporal trend.

Global monthly sea surface temperature forecasting using the SARIMA, LSTM, and GRU models

Global monthly sea surface temperature forecasting using the SARIMA, LSTM, and GRU models

Effect of biodynamic preparations 500 and 501 on vine and berry physiology, pedology and the soil microbiome

The increasing interest in organic and biodynamic wine production is driven by a desire for sustainability and reduced reliance on synthetic inputs. As of 2021, organic viticulture accounted for 6.4 % of the global vineyard surface, with biodynamic practices gaining traction, particularly among high-end wineries seeking to differentiate their products through unique, environmentally conscious cultivation methods. Biodynamic viticulture, while rooted in organic principles, incorporates specific biodynamic preparations (notably preparations 500 and 501), with proponents asserting benefits such as enhanced soil vitality, vine resilience, and superior wine quality. However, the scientific community remains divided on whether biodynamic methods offer substantial advantages over organic practices alone. Previous studies (Döring et al., 2019; Rienth et al., 2023) have shown minimal differences between the two in terms of vine performance and berry quality. This study aims to evaluate the long-term effects of biodynamic preparations 500 and 501 on vine physiology, berry quality, and soil properties in a Swiss vineyard.