Local and distant archives of observed weather data present unique opportunities for scientists to obtain long time series of the historical hydrology and climate for many regions of the world. Unfortunately, most of these observational records are still to-date available only on paper, and thus require digitization and transcribing to machine-readable formats to facilitate analysis of hydroclimatic trends. Here we discuss the data rescue efforts for hydroclimatic data recorded at 36 climate stations in the Democratic Republic of Congo from the early 1950’s to-date. We describe the procedures we follow to digitize over 10,000 paper records of daily precipitation and temperature within archives both in the Democratic Republic of Congo and Belgium, and subsequently the steps to transcribe this data set using different methods including machine learning. Furthermore, we undertake quality control and quality assessment of the transcribed data. The resultant time series, comprised of millions of observations from the archived data, will resolve the challenges of limited available hydroclimatic data within the Congo basin and expedite research on the hydroclimate in the basin.

Typically, climate simulations covering the historical period start in 1850, with the first fifty years used as a baseline to represent a ‘pre-industrial' climate. The period immediately prior to 1850 is however of particular interest, as it had far more volcanic activity than any time during the subsequent historical period, and this is known to have caused large cooling of global temperatures. Exploring the climate of this period could help to better understand early anthropogenic warming, natural climate variability and anticipate the response to large future eruptions.Here we will: (1) highlight the development of a new instrumental observation-based dataset (GloSAT) for temperature variations across the globe from 1781 to present; (2) discuss an ensemble of historical simulations with UKESM1 which were started in 1750, 100 years earlier than typical. These two sources of evidence will be used to identify the long-lasting impacts of the early 19th century volcanism and disentangle it from the response to other forcings and internal variations. Longer term effects of this period are also explored with significant differences found with historical simulations run using the same model initialised in 1850 lasting well into the 20th century. The implications of this discrepancy and the role of large volcanic eruptions on multi-decadal climate will be discussed.

Extreme weather events of unprecedented intensity in historical records can have major impacts on society and ecosystems. While adaptation plans often consider past trends in extreme weather events, few consider the possibility of exceptional extremes. This oversight leaves society underprepared and ill-equipped to handle ‘surprising’ events. There is a long history of science inquiry into the question of what low likelihood weather events are possible. Here, we present an overview of the methods used to identify exceptional weather events. We discuss tools for scientists, practitioners and policy-makers to ‘see the unseen’ and evaluate unexpected yet plausible disruptive events. We first discuss existing approaches for estimating rare extremes; then give an example for exceptional heat in The Netherlands; and finally outline how this knowledge can be leveraged to strengthen resilience and adaptation efforts.

It is well-established that explosive volcanic eruptions typically lead to cooler surface temperatures in summer, but the picture in Northern Hemisphere winter is much more uncertain. Recent large, low-latitude eruptions have been followed by warm anomalies across Eurasia in winter and cold anomalies near Greenland, hypothesized to be part of a dynamical response to the volcanic forcing that drives a positive North Atlantic Oscillation (NAO). But the evidence for a dynamical, winter warming response is inconclusive because internal variability is large, many climate models do not simulate a dynamical response like this, and there are few such eruptions to study.New datasets that allow additional eruptions from the early 19th century to be studied are therefore particularly valuable and we will present new analyses of the winters following four large eruptions in 1809, 1815, 1831 and 1835 (alongside four later eruptions in 1883, 1902, 1982 and 1991). This analysis is made possible by a new gridded instrumental dataset combining marine and land air temperatures from the 1780s onwards developed in the ongoing GloSAT project. It is supplemented by analysis of an ensemble of historically-forced simulations with UKESM1.1 initialised in 1750, also from the GloSAT project, and by two reanalyses (20CRv3 from 1806 and ModE-RA from 1421).For the instrumental and reanalysis datasets, warming in Europe was found in the first post-eruption winter following six out of the eight cases studied, and in the second post-eruption winter in five. Similar results were found for cold anomalies near Greenland and for a positive winter NAO index. The anomaly magnitudes for individual cases were mostly within the range of internal variability but the consistency of the response across eruptions and datasets was significant in comparison with non-volcanic winters. The UKESM1.1 simulations showed a significant response (with Eurasian winter warming, Greenland cooling and positive NAO) for only the largest eruption (Tambora), suggesting a response may require a minimum forcing strength to occur.

AbstractWe describe the transcription and quality control processes for rescuing around 570,000 sub‐daily and daily weather observations which were recorded in the UK Met Office Daily Weather Reports during the 1861–1875 period. These data are from the start of coordinated weather observations and were collected with the aim of making the first‐ever weather forecasts. The observations were rescued thanks to 3500 volunteers and include sub‐daily sea‐level pressure, dry and wet bulb temperatures, daily maximum and minimum temperatures, and daily rainfall amounts from 70 different locations across Western Europe, and one in Canada. We highlight how these observations will be used to fill gaps in existing pressure and temperature datasets and use two case studies to show how the pressure observations will likely better constrain the atmospheric circulation during two severe storms. We also compare a sub‐sample of the newly rescued observations with data that were previously digitized for a small number of locations for the same dates, finding good agreement in general, although some discrepancies remain.

There is high confidence that global warming intensifies all components of the global water cycle. This work investigates the possible effects of global warming on river flows worldwide in the coming decades. We conducted 18 global hydrological simulations to assess how river flows are projected to change in the near future (2015–2050) compared to the recent past (1950–2014). The simulations are forced by runoff from the High Resolution Model Intercomparison Project (HighResMIP) CMIP6 global climate models (GCMs), which assume a high-emission scenario for the projections. The assessment includes estimating the signal-to-noise (S/N) ratio and the time of emergence (ToE) of all the rivers in the world. Consistently with the water cycle intensification, the hydrological simulations project a clear positive global river discharge trend from ∼2000 that emerges beyond the levels of natural variability and becomes “unfamiliar” by 2017 and “unusual” by 2033. Simulations agree that the climate change signal is dominated by strong increases in the flows of rivers originating in central Africa and South Asia and those discharging into the Arctic Ocean, partially compensated for by the reduced flow projected for Patagonian rivers. The potential implications of such changes may include more frequent floods in central African and South Asian rivers, driven by the projected magnification of the annual cycles with unprecedented peaks, a freshening of the Arctic Ocean from extra freshwater release, and limited water availability in Patagonia given the projected drier conditions of its rivers. This underscores the critical need for a paradigm shift in prioritizing water-related concerns amidst the challenges of global warming.

The reality of human-induced climate change is unequivocal and exerts an ever-increasing global impact. Access to the latest scientific information on current climate change and projection of future trends is important for planning adaptation measures and for informing international efforts to reduce emissions of greenhouse gases (GHGs). Identification of hazards and risks may be used to assess vulnerability, determine limits to adaptation, and enhance resilience to climate change. This article highlights how recent research programs are continuing to elucidate current processes and advance projections across major climate systems and identifies remaining knowledge gaps. Key findings include projected future increases in monsoon rainfall, resulting from a changing balance between the rainfall-reducing effect of aerosols and rainfall-increasing GHGs; a strengthening of the storm track in the North Atlantic; an increase in the fraction of precipitation that falls as rain at both poles; an increase in the frequency and severity of El Niño Southern Oscillation (ENSO) events, along with changes in ENSO teleconnections to North America and Europe; and an increase in the frequency of hazardous hot-humid extremes. These changes have the potential to increase risks to both human and natural systems. Nevertheless, these risks may be reduced via urgent, science-led adaptation and resilience measures and by reductions in GHGs.

Exposure biases are a pervasive non-climatic change in land air temperature records which have been introduced as a result of changes in the way thermometers were sheltered from solar radiation and the elements over time. Exposure biases have not been widely accounted for in observational records, due to difficulties detecting/correcting the bias using traditional homogenisation techniques; therefore, exposure biases still contribute significant uncertainty to the early period in global temperature compilations. Here, an empirical approach to address the bias arising from the introduction of Stevenson-type screens from the late-19th century is presented. The approach consists of: (1) an empirical analysis of 54 parallel measurement series to identify the characteristics of the exposure bias in four exposure classes; (2) the development of bias-estimation models based on an analysis of which variables influence the bias; and (3) the application of the models to an extended version of CRUTEM5 (CRUTEM5_ext), based on exposure metadata, to quantify and reduce the bias. Step one identified differences between the temperatures recorded in Stevenson screens and early exposures, which vary seasonally, diurnally, and with location and exposure class. The largest biases (in mean temperatures) were found in freestanding exposures (up to -0.78 degrees C annually) and in summer, while the smallest biases were generally found in wall-mounted exposures (near-0 degrees C annually) and in winter. Significant relationships between the bias and temperature, downward top of atmosphere and/or received shortwave downward solar radiation were found in each exposure class and led to the development of three regression-based bias-estimation models. Application of these models to 1,960 mid-latitude stations in CRUTEM5_ext, resulted in small (<= 0.016 degrees C) positive adjustments to the Northern Hemisphere mid-latitude mean before 1880, and larger (<=-0.1 degrees C) negative adjustments to the Northern and Southern Hemisphere mid-latitude means between 1882-1934 and 1856-1900, respectively. Larger adjustments were estimated regionally: up to -0.57 degrees C annually and -0.79 degrees C seasonally in individual grid cells. The transition from non-standard thermometer exposures to Stevenson-type screens introduced exposure biases into land air temperature records. This study uses parallel measurements to (a) characterize the exposure bias in four main classes of exposure and (b) develop exposure-specific models to estimate the bias at individual weather stations. Application of the models to mid-latitude stations in CRUTEM5 suggests the biases present in the mid-latitude annual means are relatively small (<=+/- 0.1 degrees C) but can be larger in individual grid cells (up to -0.57 degrees C). image

Directly linking greenhouse gas emissions or global warming to experiences of local climatic changes is a potentially important communication tool. Using observations, we develop a physically plausible “causal chain” visualisation to demonstrate the connections between global carbon dioxide emissions and local climate events. We highlight how increased flood risk in one river basin in the UK could be discussed with people directly affected by recent floods.

Abstract The number and coverage of weather observations over the oceans were considerably reduced during World War II (WW2) due to disruptions to normal trade routes. The observations that do exist for this period are often unavailable to science as they are still only available as paper records or scanned images. We have rescued the detailed hourly weather observations contained in more than 28,000 logbook images of the US Navy Pacific Fleet stationed at Hawai'i during 1941–1945 to produce a dataset of more than 630,000 records. Each record contains the date and time, positional information and several meteorological measurements, totalling more than 3 million individual observations. The data rescue process consisted of a citizen science project asking volunteers to transcribe the observations from the available images, followed by additional quality control processes. This dataset not only contains hourly weather observations of air temperature, sea surface temperature, atmospheric pressure, wind speed and wind direction, mainly in the Pacific Ocean but also includes some observations from the Atlantic and Indian Oceans. The new observations are found to be of good quality by inter‐comparing independent measurements taken on ships travelling in convoy and by comparing with the 20th‐Century Reanalysis. This dataset provides invaluable instrumental weather observations at times and places during WW2, which fill gaps in existing reconstructions.

The rescue, digitization, quality control, preservation, and utilization of long and high quality meteorological and climate records, particularly related to historical marine data, are crucial for advancing our understanding of the Earth’s climate system. In combination with land and air measurements, historical marine records serve as foundational pillars in linking present and past weather and climate information, offering essential insights into natural climate variability, extreme events in marine areas, baseline data for assessing current changes, and inputs for enhancing predictive climate models and reanalyses. This paper provides an overview of rescue activities covering marine weather data over the past centuries and presents and highlights several ongoing projects across the world and how the data are used in an integrative and international framework. Current and future continuous efforts in data rescue, digitization, quality control, and the development of temporally high-resolution meteorological and climatological observations from oceans, will greatly help to further complete our understanding and knowledge of the Earth’s climate system, including extremes, as well as improve the quality of reanalysis.

Abstract Precipitation projections in transient climate change scenarios have been extensively studied over multiple climate model generations. Although these simulations have also been used to make projections at specific Global Warming Levels (GWLs), dedicated simulations are more appropriate to study changes in a stabilizing climate. Here, we analyze precipitation projections in six multi‐century experiments with fixed atmospheric concentrations of greenhouse gases, conducted with the UK Earth System Model and which span a range of GWLs between 1.5 and 5°C of warming. Regions are identified where the sign of precipitation trends in high‐emission transient projections is reversed in the stabilization experiments. For example, stabilization reverses a summertime precipitation decline across Europe. This precipitation recovery occurs concurrently with changes in the pattern of Atlantic sea surface temperature trends due to a slow recovery of the Atlantic Meridional Overturning Circulation in the stabilization experiments, along with changes in humidity and atmospheric circulation.

The intensity and frequency of extreme heat events is increasing due to climate change, resulting in a range of societal impacts. In this paper, we use temporal analogues to analyse how past UK heatwave events, such as during the summer of 1923, may change if they were to occur under different global warming scenarios. We find that the six most intense early heat events are caused by circulation patterns similar to that of 1923, which can cause intense heat over the UK and parts of NW Europe. Circulation analogues for the 1923 heatwave are also linked to intense heat events in the future, although not all analogues are anomalously hot. At 4 degrees C of global warming, mean summer temperatures in England over the duration of the 1923 heatwave are between 4.9 and 6.4 degrees warmer than pre-industrial levels across the three models used. At that global mean warming level, future heat events with similar circulation as 1923 over England are estimated to be on average 6.9 degrees C-10.7 degrees C hotter than those at pre-industrial levels. Exploring how the intensity of events similar to past events may change in the future could be an effective risk communication tool for adaptation decision making, particularly if past events are stored in society's memory, for example, due to high impacts.

The emergence of a climate change signal relative to background variability is a useful metric for understanding local changes and their consequences. Studies have identified emergent signals of climate change, particularly in temperature-based indices with weaker signals found for precipitation metrics. In this study, we adapt climate analogue methods to examine multivariate climate change emergence over the historical period. We use seasonal temperature and precipitation observations and apply a sigma dissimilarity method to demonstrate that large local climate changes may already be identified, particularly in low-latitude regions. The multivariate methodology brings forward the time of emergence by several decades in many areas relative to analysing temperature in isolation. We observed particularly large departures from an early-20th century climate in years when the global warming signal is compounded by an El Niño-influence. The latitudinal dependence in the emergent climate change signal means that lower-income nations have experienced earlier and stronger emergent climate change signals than the wealthiest regions. Analysis based on temperature and precipitation extreme indices finds weaker signals and less evidence of emergence but is hampered by lack of long-running observations in equatorial areas. The framework developed here may be extended to attribution and projections analyses.

The Coupled Model Intercomparison Project Phase 6 (CMIP6) model ensemble projects climate change emerging soonest and most strongly at low latitudes, regardless of the emissions pathway taken. In terms of signal-to-noise (S/N) ratios of average annual temperatures, these models project earlier and stronger emergence under the Shared Socio-economic Pathways than the previous generation did under corresponding Representative Concentration Pathways. Spatial patterns of emergence also change between generations of models; under a high emissions scenario, mid-century S/N is lower than previous studies indicated in Central Africa, South Asia, and parts of South America, West Africa, East Asia, and Western Europe, but higher in most other populated areas. We show that these global and regional changes are caused by a combination of higher effective climate sensitivity in the CMIP6 ensemble, as well as changes to emissions pathways, component-wise effective radiative forcing, and region-scale climate responses between model generations. We also present the first population-weighted calculation of climate change emergence for the CMIP6 ensemble, quantifying the number of people exposed to increasing degrees of abnormal temperatures now and into the future. Our results confirm the expected inequity of climate change-related impacts in the decades between now and the 2050 target for net-zero emissions held by many countries. These findings underscore the importance of concurrent investments in both mitigation and adaptation.

The 18.6-year lunar nodal cycle arises from variations in the angle of the Moon's orbital plane. Previous work has linked the nodal cycle to climate but has been limited by either the length of observations analysed or geographical regions considered in model simulations of the pre-industrial period. Here we examine the global effect of the lunar nodal cycle in multi-centennial climate model simulations of the pre-industrial period. We find cyclic signals in global and regional surface air temperature (with amplitudes of around 0.1 K) and in ocean heat uptake and ocean heat content. The timing of anomalies of global surface air temperature and heat uptake is consistent with the so-called slowdown in global warming in the first decade of the 21st century. The lunar nodal cycle causes variations in mean sea level pressure exceeding 0.5 hPa in the Nordic Seas region, thus affecting the North Atlantic Oscillation during boreal winter. Our results suggest that the contribution of the lunar nodal cycle to global temperature should be negative in the mid-2020s before becoming positive again in the early 2030s, reducing the uncertainty in time at which projected global temperature reaches 1.5 ∘C above pre-industrial levels.

Following efforts from leading centres for climate forecasting, sustained routine operational near-term climate predictions (NTCP) are now produced that bridge the gap between seasonal forecasts and climate change projections offering the prospect of seamless climate services. Though NTCP is a new area of climate science and active research is taking place to increase understanding of the processes and mechanisms required to produce skillful predictions, this significant technical achievement combines advances in initialisation with ensemble prediction of future climate up to a decade ahead. With a growing NTCP database, the predictability of the evolving externally-forced and internally-generated components of the climate system can now be quantified. Decision-makers in key sectors of the economy can now begin to assess the utility of these products for informing climate risk and for planning adaptation and resilience strategies up to a decade into the future. Here, case studies are presented from finance and economics, water management, agriculture and fisheries management demonstrating the emerging utility and potential of operational NTCP to inform strategic planning across a broad range of applications in key sectors of the global economy.

Abstract Recovering additional historical weather observations from known archival sources will improve the understanding of how the climate is changing and enable detailed examination of unusual events within the historical record. The UK National Meteorological Archive recently scanned more than 66,000 paper sheets containing 5.28 million hand‐written monthly rainfall observations taken across the UK and Ireland between 1677 and 1960. Only a small fraction of these observations were previously digitally available for climate scientists to analyse. More than 16,000 volunteer citizen scientists completed the transcription of these sheets of observations during early 2020 using the RainfallRescue.org website, built using the Zooniverse platform. A total of 3.34 million observations from more than 6000 locations have so far been quality controlled and made openly available. This has increased the total number of monthly rainfall observations that are available for this time period and region by a factor of six. The newly rescued observations will enable longer and much improved reconstructions of past variations in rainfall across the British and Irish Isles, including for periods of significant flooding and drought. Specifically, this data should allow the official gridded monthly rainfall reconstructions for the UK to be extended back to 1836, and even earlier for some regions.

Version 2.0.0 of the data from the RainfallRescue.org project, with many more stations added compared to v1. More than 4.9 million monthly rainfall amounts, taken across the UK and Ireland between 1677 and 1960, transcribed by 16,000 volunteers.