Explore the vast range of titles available.

Proxy reconstructions from marine sediment cores indicate peak temperatures in the first half of the last and current interglacial periods (the thermal maxima of the Holocene epoch, 10,000 to 6,000 years ago, and the last interglacial period, 128,000 to 123,000 years ago) that arguably exceed modern warmth 1 – 3 . By contrast, climate models simulate monotonic warming throughout both periods 4 – 7 . This substantial model–data discrepancy undermines confidence in both proxy reconstructions and climate models, and inhibits a mechanistic understanding of recent climate change. Here we show that previous global reconstructions of temperature in the Holocene 1 – 3 and the last interglacial period 8 reflect the evolution of seasonal, rather than annual, temperatures and we develop a method of transforming them to mean annual temperatures. We further demonstrate that global mean annual sea surface temperatures have been steadily increasing since the start of the Holocene (about 12,000 years ago), first in response to retreating ice sheets (12 to 6.5 thousand years ago), and then as a result of rising greenhouse gas concentrations (0.25 ± 0.21 degrees Celsius over the past 6,500 years or so). However, mean annual temperatures during the last interglacial period were stable and warmer than estimates of temperatures during the Holocene, and we attribute this to the near-constant greenhouse gas levels and the reduced extent of ice sheets. We therefore argue that the climate of the Holocene differed from that of the last interglacial period in two ways: first, larger remnant glacial ice sheets acted to cool the early Holocene, and second, rising greenhouse gas levels in the late Holocene warmed the planet. Furthermore, our reconstructions demonstrate that the modern global temperature has exceeded annual levels over the past 12,000 years and probably approaches the warmth of the last interglacial period (128,000 to 115,000 years ago). Reanalysis of Holocene sea surface temperature records affirms the role of retreating ice and rising greenhouse gases in driving a steady increase in global temperatures over the past 12,000 years.

High-resolution, downscaled climate model data are used in a wide variety of applications across environmental sciences. Here we introduce a new, high-resolution dataset, CHELSA-TraCE21k. It is obtained by downscaling TraCE-21k data, using the “Climatologies at high resolution for the earth's land surface areas” (CHELSA) V1.2 algorithm with the objective to create global monthly climatologies for temperature and precipitation at 30 arcsec spatial resolution in 100-year time steps for the last 21 000 years. Paleo-orography at high spatial resolution and for each time step is created by combining high-resolution information on glacial cover from current and Last Glacial Maximum (LGM) glacier databases and interpolations using data from a global model of glacial isostasy (ICE-6G_C) and a coupling to mean annual temperatures from TraCE21k (Transient Climate Evolution of the last 21 000 years) based on the Community Climate System Model version 3 (CCSM3). Based on the reconstructed paleo-orography, mean annual temperature and precipitation were downscaled using the CHELSA V1.2 algorithm. The data were validated by comparisons with the glacial extent of the Laurentide ice sheet based on expert delineations, proxy data from Greenland ice cores, historical climate data from meteorological stations, and a dynamic simulation of species distributions throughout the Holocene. Validations show that the CHELSA-TraCE21k V1.0 dataset reasonably represents the distribution of temperature and precipitation through time at an unprecedented 1 km spatial resolution, and simulations based on the data are capable of detecting known LGM refugia of species.

Late Pliocene and Early Pleistocene epochs 3.6 to 0.8 million years ago 1 had climates resembling those forecasted under future warming 2 . Palaeoclimatic records show strong polar amplification with mean annual temperatures of 11–19 °C above contemporary values 3 , 4 . The biological communities inhabiting the Arctic during this time remain poorly known because fossils are rare 5 . Here we report an ancient environmental DNA 6 (eDNA) record describing the rich plant and animal assemblages of the Kap København Formation in North Greenland, dated to around two million years ago. The record shows an open boreal forest ecosystem with mixed vegetation of poplar, birch and thuja trees, as well as a variety of Arctic and boreal shrubs and herbs, many of which had not previously been detected at the site from macrofossil and pollen records. The DNA record confirms the presence of hare and mitochondrial DNA from animals including mastodons, reindeer, rodents and geese, all ancestral to their present-day and late Pleistocene relatives. The presence of marine species including horseshoe crab and green algae support a warmer climate than today. The reconstructed ecosystem has no modern analogue. The survival of such ancient eDNA probably relates to its binding to mineral surfaces. Our findings open new areas of genetic research, demonstrating that it is possible to track the ecology and evolution of biological communities from two million years ago using ancient eDNA. Analysis of two-million-year-old ancient environmental DNA from the Kap København Formation in North Greenland shows there was an open boreal forest with diverse plant and animal species, of which several taxa have not previously been detected at the site, representing an ecosystem that has no present-day analogue.

Soil pH is a key factor that controls soil nutrient availability, soil microbial activities, and crop growth and development. However, studies on the soil pH variations of cultivated lands in different horizons at the regional scale remain limited. In this work, 348 soil samples were collected from three soil horizons (A, B, and C) at 120 sites over the hilly region of Chongqing, southwestern China. Six topographic indicators, four climate parameters, and parent material were considered. Classification and regression trees (CARTs) were applied to investigate the relationships between soil pH and the variables in the A, B, and C horizons. Model performances were evaluated by root mean square error (RMSE), relative root mean square error (RRMSE), and coefficient of determination (R2). Results showed that soil pH increased obviously from the A to C horizons. Soil pH was predicted well by the forcing factors with the CART models in all horizons. RMSE, RRMSE, and R2 varied between 0.37 and 0.435, between 5.93 and 7.23%, and between 0.71 and 0.80, respectively. The relative importance of the studied variables to soil pH differed with the horizons. Annual temperature range (ATR), terrain wetness index (TWI), and Melton ruggedness number were critical factors that controlled soil pH variability in the A horizon. Parent material, precipitation of warmest quarter (PWQ), ATR, and TWI were important variables in the B horizon. Parent material, PWQ, ATR, and precipitation were key factors in the C horizon. The results are expected to provide valuable information for designing appropriate measurements for agricultural practices and preventing soil acidification.

The century-long search for the precise mechanisms responsible for urban heat islands continues, while urban warming worsens in many megacities. Most studies have focused on mean temperature, daily and annual temperature ranges and urban heat island intensity. We hypothesize that an analysis of the changes in the characteristics of the complete daily and annual temperature cycles, including not only the mean temperature and temperature ranges (amplitudes) but also the maximum and minimum temperatures and the phases, can provide more information on urban warming phenomena. Through a detailed analysis of long-term observations in Hong Kong, we found that the difference in the daily cycle between urban and rural stations is very distinct, whereas the annual cycles are much more similar, suggesting that the urban environment has a greater effect on the daily cycle than on the annual cycle. The daily phase has shifted a total of 1.77 h later over the last 130 years (1.36 h per century) in the urban area of Hong Kong according to the Hong Kong Observatory (HKO) data. The annual phase change at HKO reflects the globally observed phenomenon that the annual phase advances or seasons onset earlier.

Reconciling the geology of Mars with models of atmospheric evolution remains a major challenge. Martian geology is characterized by past evidence for episodic surface liquid water, and geochemistry indicating a slow and intermittent transition from wetter to drier and more oxidizing surface conditions. Here we present a model that incorporates randomized injection of reducing greenhouse gases and oxidation due to hydrogen escape to investigate the conditions responsible for these diverse observations. We find that Mars could have transitioned repeatedly from reducing (hydrogen-rich) to oxidizing (oxygen-rich) atmospheric conditions in its early history. Our model predicts a generally cold early Mars, with mean annual temperatures below 240 K. If peak reducing-gas release rates and background carbon dioxide levels are high enough, it nonetheless exhibits episodic warm intervals sufficient to degrade crater walls, form valley networks and create other fluvial/lacustrine features. Our model also predicts transient build-up of atmospheric oxygen, which can help explain the occurrence of oxidized mineral species such as manganese oxides at Gale Crater. We suggest that the apparent Noachian–Hesperian transition from phyllosilicate deposition to sulfate deposition around 3.5 billion years ago can be explained as a combined outcome of increasing planetary oxidation, decreasing groundwater availability and a waning bolide impactor flux, which dramatically slowed the remobilization and thermochemical destruction of surface sulfates. Ultimately, rapid and repeated variations in Mars’s early climate and surface chemistry would have presented both challenges and opportunities for any emergent microbial life. Mars’s early climate and surface chemistry varied between a generally cold, oxidizing environment and warmer, more reducing conditions, according to a model of atmospheric evolution driven by stochastic, random injection of greenhouse gases.

Xinjiang is one of the most sensitive regions in China in terms of its response to climate change. Against the background of global warming, analyses and predictions using different scenarios for Xinjiang should be conducted. The spatial and temporal distribution characteristics and trends of future temperature and precipitation trends should be considered to provide a scientific basis for the government to respond to future climate change. In this paper, using the CN05.1 dataset and seven models from the sixth phase of the Coupled Model Intercomparison Project, the delta downscaling method is used to predict the temperature and precipitation changes in Xinjiang Province from 2021 to 2050 under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios. The results show that (1) most models of CMIP6 have a good effect on temperature simulation in Xinjiang, and the mean values as well as the trends of the temperatures expressed by the multi-model ensemble averaging are in good agreement with the observed data and have a high degree of confidence. The observed precipitation increase rate is significantly higher than that predicted by the model, and the simulation results of each model overestimate the precipitation. (2) The mean annual temperatures in the Xinjiang region increase at rates of 0.32°C/10 a, 0.46°C/10 a, 0.47°C/10 a and 0.67°C/10 a, respectively, under the four scenarios. The rates of temperature increase in the four seasons exhibit the following pattern: autumn > summer > spring > winter. (3) From 2021 to 2050, the average annual precipitation in Xinjiang will change at rates of 3.95 mm/10 a, 1.90 mm/10 a, 2.50 mm/10 a, and 8.67 mm/10 a, respectively, under the four scenarios. The precipitation amounts predicted under the different scenarios increase at the slowest rates in winter and at faster rates in spring. Spatially, the precipitation in the whole Xinjiang region under the four scenarios shows an increasing trend. Overall, except for the SSP1-2.6 scenario, the rates of increase in precipitation increase gradually in all seasons during the future period as the emission scenarios increase. Overall, the climate of the Xinjiang region will be characterized by warming and humidification from 2021 to 2050.

Utility-scale solar power plants are a rapidly growing component of the renewable energy sector. While most agree that solar power can decrease greenhouse gas emissions, the effects of photovoltaic (PV) systems on surface energy exchanges and near-surface meteorology are not well understood. This study presents data from two eddy covariance observational towers, placed within and adjacent to a utility-scale PV array in southern Arizona. The observational period (October 2017–July 2018) includes the full range of annual temperature variation. Average daily maximum 1.5-m air temperature at the PV array was 1.3°C warmer than the reference (i.e., non-PV) site, whereas no significant difference in 1.5-m nocturnal air temperature was observed. PV modules captured the majority of solar radiation and were the primary energetically active surface during the day. Despite the removal of energy by electricity production, the modules increased daytime net radiation Q* available for partitioning by reducing surface albedo. The PV modules shift surface energy balance partitioning away from upward longwave radiation and heat storage and toward sensible heat flux QH because of their low emissivity, low heat capacity, and increased surface area and roughness, which facilitates more efficient QH from the surface. The PV modules significantly reduce ground heat flux QG storage and nocturnal release, as the soil beneath the modules is well shaded. Our work demonstrates the importance of targeted observational campaigns to inform process-based understanding associated with PV systems. It further establishes a basis for observationally based PV energy balance models that may be used to examine climatic effects due to large-scale deployment.

The greenhouse-to-icehouse climate transition from the Eocene into the Oligocene is well documented by sea surface temperature records from the southwest Pacific and Antarctic margin, which show evidence of pronounced long-term cooling. However, identification of a driving mechanism depends on a better understanding of whether this cooling was also present in terrestrial settings. Here, we present a semi-continuous terrestrial temperature record spanning from the middle Eocene to the early Oligocene (~41–33 million years ago), using bacterial molecular fossils (biomarkers) preserved in a sequence of southeast Australian lignites. Our results show that mean annual temperatures in southeast Australia gradually declined from ~27 °C (±4.7 °C) during the middle Eocene to ~22–24 °C (±4.7 °C) during the late Eocene, followed by a ~2.4 °C-step cooling across the Eocene/Oligocene boundary. This trend is comparable to other temperature records in the Southern Hemisphere, suggesting a common driving mechanism, likely p CO 2 . We corroborate these results with a suite of climate model simulations demonstrating that only simulations including a decline in p CO 2 lead to a cooling in southeast Australia consistent with our proxy record. Our data form an important benchmark for testing climate model performance, sea–land interaction and climatic forcings at the onset of a major Antarctic glaciation. Terrestrial Southern Hemisphere cooling through the Eocene–Oligocene transition points to decreasing atmospheric CO 2 dominantly driving global change, according to biomarker records from southeast Australian coals and palaeoclimate modelling.

The impacts of climate change are expected to vary considerably across regional and local scales, underscoring the urgent need for localized assessments. This study investigates the spatio-temporal characteristics of meteorological drought across three distinct periods- baseline (1985–2018), near future (2020–2050), and mid-future (2051–2081) under two climate scenarios: SSP2–4.5 and SSP5–8.5, within the North Gojjam sub-basin of the Abay Basin, Ethiopia. It further examines long-term trends in precipitation and both minimum and maximum temperatures across the sub-basin. Future climate projections were derived using six global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under the Shared Socioeconomic Pathways (SSPs). Data from seven stations were extracted, bias-corrected, and aggregated using R software and relevant analytical packages. Key statistical metrics confirm a strong alignment between corrected GCM outputs and observed historical data. Meteorological drought was assessed using the Standardized Precipitation Evapotranspiration Index (SPEI) over a three-month scale, with run theory applied for drought characterization. Precipitation and SPEI trends were analyzed using the Mann-Kendall test and Sen’s slope estimator, with statistical significance set at p < 0.05. Projections suggest an increase in both minimum and maximum mean annual temperatures during the near and mid-future periods, with minimum temperatures rising more sharply. Under SSP5–8.5, precipitation is expected to decrease, except during the mid-future period. The SPEI indicates an intensification and increased frequency of severe drought events. The northeastern and southeastern parts of the North Gojjam sub-basin are particularly vulnerable, posing significant risks for agriculture and water resource management. This study provides critical localized insights into future climate scenarios, highlighting the importance of temporal drought forecasting and the need for targeted adaptation and mitigation strategies in the region.