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CRU TS (Climatic Research Unit gridded Time Series) is a widely used climate dataset on a 0.5° latitude by 0.5° longitude grid over all land domains of the world except Antarctica. It is derived by the interpolation of monthly climate anomalies from extensive networks of weather station observations. Here we describe the construction of a major new version, CRU TS v4. It is updated to span 1901–2018 by the inclusion of additional station observations, and it will be updated annually. The interpolation process has been changed to use angular-distance weighting (ADW), and the production of secondary variables has been revised to better suit this approach. This implementation of ADW provides improved traceability between each gridded value and the input observations, and allows more informative diagnostics that dataset users can utilise to assess how dataset quality might vary geographically. Measurement(s) temperature • volume of hydrological precipitation • vapour pressure • wet days • cloud cover Technology Type(s) digital curation Factor Type(s) date of observation • location of observation Sample Characteristic - Environment climate system Sample Characteristic - Location Asia • Africa • Europe • Australia • North America • South America Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.11980500

The North Atlantic experiences climate variability on multidecadal scales, which is sometimes referred to as Atlantic multidecadal variability. However, the relative contributions of external forcing such as changes in solar irradiance or volcanic activity and internal dynamics to these variations are unclear. Here we provide evidence for persistent summer Atlantic multidecadal variability from AD 800 to 2010 using a network of annually resolved terrestrial proxy records from the circum-North Atlantic region. We find that large volcanic eruptions and solar irradiance minima induce cool phases of Atlantic multidecadal variability and collectively explain about 30% of the variance in the reconstruction on timescales greater than 30 years. We are then able to isolate the internally generated component of Atlantic multidecadal variability, which we define as the Atlantic multidecadal oscillation. We find that the Atlantic multidecadal oscillation is the largest contributor to Atlantic multidecadal variability over the past 1,200 years. We also identify coherence between the Atlantic multidecadal oscillation and Northern Hemisphere temperature variations, leading us to conclude that the apparent link between Atlantic multidecadal variability and regional to hemispheric climate does not arise solely from a common response to external drivers, and may instead reflect dynamic processes. The North Atlantic region experiences climate variability on multidecadal timescales. An analysis of a tree-ring network shows this variability can be attributed to both internal and external forcing over the past 1,200 years.

Vibrio vulnificus is an opportunistic bacterial pathogen, occurring in warm low-salinity waters. V. vulnificus wound infections due to seawater exposure are infrequent but mortality rates are high (~ 18%). Seawater bacterial concentrations are increasing but changing disease pattern assessments or climate change projections are rare. Here, using a 30-year database of V. vulnificus cases for the Eastern USA, changing disease distribution was assessed. An ecological niche model was developed, trained and validated to identify links to oceanographic and climate data. This model was used to predict future disease distribution using data simulated by seven Global Climate Models (GCMs) which belong to the newest Coupled Model Intercomparison Project (CMIP6). Risk was estimated by calculating the total population within 200 km of the disease distribution. Predictions were generated for different “pathways” of global socioeconomic development which incorporate projections of greenhouse gas emissions and demographic change. In Eastern USA between 1988 and 2018, V. vulnificus wound infections increased eightfold (10–80 cases p.a.) and the northern case limit shifted northwards 48 km p.a. By 2041–2060, V. vulnificus infections may expand their current range to encompass major population centres around New York (40.7°N). Combined with a growing and increasingly elderly population, annual case numbers may double. By 2081–2100 V. vulnificus infections may be present in every Eastern USA State under medium-to-high future emissions and warming. The projected expansion of V. vulnificus wound infections stresses the need for increased individual and public health awareness in these areas.

Mediterranean-type climates are defined by temperate, wet winters, and hot or warm dry summers and exist at the western edges of five continents in locations determined by the geography of winter storm tracks and summer subtropical anticyclones. The climatology, variability, and long-term changes in winter precipitation in Mediterranean-type climates, and the mechanisms for model-projected near-term future change, are analyzed. Despite commonalities in terms of location in the context of planetary-scale dynamics, the causes of variability are distinct across the regions. Internal atmospheric variability is the dominant source of winter precipitation variability in all Mediterranean-type climate regions, but only in the Mediterranean is this clearly related to annular mode variability. Ocean forcing of variability is a notable influence only for California and Chile. As a consequence, potential predictability of winter precipitation variability in the regions is low. In all regions, the trend in winter precipitation since 1901 is similar to that which arises as a response to changes in external forcing in the models participating in phase 5 of the Coupled Model Intercomparison Project. All Mediterranean-type climate regions, except in North America, have dried and the models project further drying over coming decades. In the Northern Hemisphere, dynamical processes are responsible: development of a winter ridge over the Mediterranean that suppresses precipitation and of a trough west of the North American west coast that shifts the Pacific storm track equatorward. In the Southern Hemisphere, mixed dynamic–thermodynamic changes are important that place a minimum in vertically integrated water vapor change at the coast and enhance zonal dry advection into Mediterranean-type climate regions inland.

Asian summer monsoon (ASM) variability and its long-term ecological and societal impacts extending back to Neolithic times are poorly understood due to a lack of high-resolution climate proxy data. Here, we present a precisely dated and well-calibrated treering stable isotope chronology from the Tibetan Plateau with 1- to 5-y resolution that reflects high- to low-frequency ASM variability from 4680 BCE to 2011 CE. Superimposed on a persistent drying trend since the mid-Holocene, a rapid decrease in moisture availability between ∼2000 and ∼1500 BCE caused a dry hydroclimatic regime from ∼1675 to ∼1185 BCE, with mean precipitation estimated at 42 ± 4% and 5 ± 2% lower than during themid-Holocene and the instrumental period, respectively. This second-millennium–BCE megadrought marks the mid-to late Holocene transition, during which regional forests declined and enhanced aeolian activity affected northern Chinese ecosystems. We argue that this abrupt aridification starting ∼2000 BCE contributed to the shift of Neolithic cultures in northern China and likely triggered human migration and societal transformation.

The United Nations Framework Convention on Climate Change (UNFCCC) process agreed in Paris to limit global surface temperature rise to “well below 2°C above pre-industrial levels.” But what period is preindustrial? Somewhat remarkably, this is not defined within the UNFCCC’s many agreements and protocols. Nor is it defined in the IPCC’s Fifth Assessment Report (AR5) in the evaluation of when particular temperature levels might be reached because no robust definition of the period exists. Here we discuss the important factors to consider when defining a preindustrial period, based on estimates of historical radiative forcings and the availability of climate observations. There is no perfect period, but we suggest that 1720–1800 is the most suitable choice when discussing global temperature limits. We then estimate the change in global average temperature since preindustrial using a range of approaches based on observations, radiative forcings, global climate model simulations, and proxy evidence. Our assessment is that this preindustrial period was likely 0.55°–0.80°C cooler than 1986–2005 and that 2015 was likely the first year in which global average temperature was more than 1°C above preindustrial levels. We provide some recommendations for how this assessment might be improved in the future and suggest that reframing temperature limits with a modern baseline would be inherently less uncertain and more policy relevant.

An annually resolved and absolutely dated ring-width chronology spanning 4,500 y has been constructed using subfossil, archaeological, and living-tree juniper samples from the northeastern Tibetan Plateau. The chronology represents changing mean annual precipitation and is most reliable after 1500 B.C. Reconstructed precipitation for this period displays a trend toward more moist conditions: the last 10-, 25-, and 50-y periods all appear to be the wettest in at least three and a half millennia. Notable historical dry periods occurred in the 4th century BCE and in the second half of the 15th century CE. The driest individual year reconstructed (since 1500 B.C.) is 1048 B.C., whereas the wettest is 2010. Precipitation variability in this region appears not to be associated with inferred changes in Asian monsoon intensity during recent millennia. The chronology displays a statistical association with the multidecadal and longer-term variability of reconstructed mean Northern Hemisphere temperatures over the last two millennia. This suggests that any further large-scale warming might be associated with even greater moisture supply in this region.

The UKCP18 Convection-permitting model (CPM) provides the latest high-resolution climate projections for the UK. Compared with regional climate model projections, the CPM projections are more capable of simulating small-scale atmospheric convection particularly during extreme weather events such as intense rainfall and localised storms. However, systematic biases still exist in these projections. To improve the reliability of these projections, bias correction is crucial. In this study, we apply and evaluate a quantile mapping (QM) bias correction method for UKCP18-CPM hourly precipitation (with diurnal correction) and daily temperature over England. We quantify how closely the bias corrected simulations align with observations relative to the raw simulations. The raw UKCP18-CPM simulations exhibit wet precipitation biases, particularly in northern England, with annual mean biases ranging from 4.6 % to 18.3 %, and cool temperature biases, with annual mean biases from -0.87 to 0.02 °C. Bias correction substantially improved agreement with observational datasets, increasing R.sup.2 values for the 95th percentile of hourly precipitation from 0.80-0.88 to 0.98 and achieving near-perfect alignment (R.sup.2 = 1) for temperature extremes. Future projections for the 2070s indicate notable increases in annual maximum precipitation by 25.1 %-39.1 % and mean daily temperature by 3.1 to 4.5 °C, highlighting the potential for more intense climate-related events. Overall, the applied bias-correction method brings UKCP18-CPM simulations into closer agreement with observations for both mean behaviour and extremes, providing a more reliable basis for high-resolution impact modelling and assessments that require hourly precipitation forcing.

The Arctic is warming faster than any other region on Earth. Putting this rapid warming into perspective is challenging because instrumental records are often short or incomplete in polar regions and precisely-dated temperature proxies with high temporal resolution are largely lacking. Here, we provide this long-term perspective by reconstructing past summer temperature variability at Yamal Peninsula – a hotspot of recent warming – over the past 7638 years using annually resolved tree-ring records. We demonstrate that the recent anthropogenic warming interrupted a multi-millennial cooling trend. We find the industrial-era warming to be unprecedented in rate and to have elevated the summer temperature to levels above those reconstructed for the past seven millennia (in both 30-year mean and the frequency of extreme summers). This is undoubtedly of concern for the natural and human systems that are being impacted by climatic changes that lie outside the envelope of natural climatic variations for this region. A 7,638 yr summer temperature reconstruction based on subfossil trees buried in the Siberian Arctic shows that recent warming is unprecedented and interrupted a multi-millennial cooling trend.

Aridity—the ratio of atmospheric water supply (precipitation; P) to demand (potential evapotranspiration; PET)—is projected to decrease (that is, areas will become drier) as a consequence of anthropogenic climate change, exacerbating land degradation and desertification1–6. However, the timing of significant aridification relative to natural variability—defined here as the time of emergence for aridification (ToEA)—is unknown, despite its importance in designing and implementing mitigation policies7–10. Here we estimate ToEA from projections of 27 global climate models (GCMs) under representative concentration pathways (RCPs) RCP4.5 and RCP8.5, and in doing so, identify where emergence occurs before global mean warming reaches 1.5 °C and 2 °C above the pre-industrial level. On the basis of the ensemble median ToEA for each grid cell, aridification emerges over 32% (RCP4.5) and 24% (RCP8.5) of the total land surface before the ensemble median of global mean temperature change reaches 2 °C in each scenario. Moreover, ToEA is avoided in about two-thirds of the above regions if the maximum global warming level is limited to 1.5 °C. Early action for accomplishing the 1.5 °C temperature goal can therefore markedly reduce the likelihood that large regions will face substantial aridification and related impacts.