Towards improved understanding of cascading and interconnected risks from concurrent weather extremes: Analysis of historical heat and drought extreme events

Weather extremes can affect many different assets, sectors and systems of the human environment, including human security, health and well-being. Weather extremes that compound, such as heat and drought, and their interconnected risks are complex, difficult to understand and thus a challenge for risk analysis and management, because (in intertwined systems) impacts can propagate through multiple sectors. In a warming climate, extreme concurrent heat and drought events are expected to increase in frequency, intensity and duration, posing growing risks to societies. To gain a better understanding of compound extremes and associated risks, we analyze eight historical heat and drought extreme events in Europe, Africa and Australia. We investigated and visualized the direct and indirect impact paths through different sectors and systems together with the impacts of response and adaptation measures. We found the most important cascading processes and interlinkages centered around the health, energy and agriculture and food production sectors. The key cascades result in impacts on the economy, the state and public services and ultimately also on society and culture. Our analysis shows that cascading impacts can propagate through numerous sectors with far reaching consequences, potentially being able to destabilize entire socio-economic systems. We emphasize that the future challenge in research on and adaptation to concurrent extreme events lies in the integration of assets, sectors and systems with strong interlinkages to other sectors and with a large potential for cascading impacts, but for which we cannot resort to historical experiences. Integrating approaches to deal with concurrent extreme events should furthermore consider the effects of possible response and adaptation mechanisms to increase system resilience

Future trends in compound concurrent heat extremes in Swiss cities - An assessment considering deep uncertainty and climate adaptation options

The interaction of multiple hazards across various spatial and temporal scales typically causes compound climate and extreme weather events. Compound concurrent hot day and night (CCHDNs) extremes that combine daytime and nighttime heat are of greater concern for health than individual hot days (HDs) or hot nights (HNs), even though their frequency is lower. We utilize a bottom-up exploratory approach to investigate how adaptation options and various unfolding future scenarios alleviate the impacts of the heatwaves and affect the frequency and intensity of CCHDNs. We use climate observations (1981–2020) and Switzerland's future climate model scenarios (CH2018) to analyze historical and future trends of the individual hot day followed by a hot night (HDNs, first metric), and the length and frequency of CCHDNs (second and third metrics) in the near-future (2020–2050) and far-future (2070–2100). Results show more frequent and lengthier HDNs in cities under all emission scenarios, notably significant under high emissions scenarios. The highest increase of HDNs occur in i) Lugano with 65.8 days (decade−1) in the historical period and 110 (371) days (decade−1) in near-future (far-future), ii) Geneva with historical 48 days (decade−1) to 108 (362) (decade−1), iii) Basel with 48–74 (217) days in the future, followed by iv) Bern with 15–44 (213) days and v) Zürich with 14–50 (217) days (decade−1) in the near-future and far-future, respectively. We consistently project that the CCHDNs in April–October become more likely and intense in all cities under all emission scenarios, with higher increases under the RCP8.5 scenario and after the 2050s. The frequency of compound extreme heatwaves (exceeding both historical thresholds of night and day temperatures) may increase by 3.5–7.8-fold and become 3.3–5.3-fold lengthier in all cities of Switzerland in the far-future. We find that the adaptation options targeting higher tolerance to increased minimum temperatures contribute more to reducing compound extreme events' frequency and intensity than adaptation options that address the maximum daily temperature

An ensemble reconstruction of global monthly sea surface temperature and sea ice concentration 1000–1849

This paper describes a global monthly gridded Sea Surface Temperature (SST) and Sea Ice Concentration (SIC) dataset for the period 1000 – 1849, which can be used as boundary conditions for atmospheric model simulations. The reconstruction is based on existing coarse-resolution annual temperature ensemble reconstructions, which are then augmented with intra-annual and sub-grid scale variability. The intra-annual component of HadISST.2.0 and oceanic indices estimated from the reconstructed annual mean are used to develop grid-based linear regressions in a monthly stratified approach. Similarly, we reconstruct SIC using analog resampling of HadISST.2.0 SIC (1941 – 2000), for both hemispheres. Analogs are pooled in four seasons, comprising of 3-months each. The best analogs are selected based on the correlation between each member of the reconstructed SST and its target. For the period 1780 to 1849, we assimilate historical observations of SST and night-time marine air temperature from the ICOADS dataset into our reconstruction using an offline Ensemble Kalman Filter approach. The resulting dataset is physically consistent with information from models, proxies, and observations

Tambora 1815 as a test case for high impact volcanic eruptions: Earth system effects

The eruption of Tambora (Indonesia) in April 1815 had substantial effects on global climate and led to the ‘Year Without a Summer’ of 1816 in Europe and North America. Although a tragic event—tens of thousands of people lost their lives—the eruption also was an ‘experiment of nature’ from which science has learned until today. The aim of this study is to summarize our current understanding of the Tambora eruption and its effects on climate as expressed in early instrumental observations, climate proxies and geological evidence, climate reconstructions, and model simulations. Progress has been made with respect to our understanding of the eruption process and estimated amount of SO2 injected into the atmosphere, although large uncertainties still exist with respect to altitude and hemispheric distribution of Tambora aerosols. With respect to climate effects, the global and Northern Hemispheric cooling are well constrained by proxies whereas there is no strong signal in Southern Hemisphere proxies. Newly recovered early instrumental information for Western Europe and parts of North America, regions with particularly strong climate effects, allow Tambora's effect on the weather systems to be addressed. Climate models respond to prescribed Tambora-like forcing with a strengthening of the wintertime stratospheric polar vortex, global cooling and a slowdown of the water cycle, weakening of the summer monsoon circulations, a strengthening of the Atlantic Meridional Overturning Circulation, and a decrease of atmospheric CO2. Combining observations, climate proxies, and model simulations for the case of Tambora, a better understanding of climate processes has emerged

Multi-proxy summer and winter precipitation reconstruction for southern Africa over the last 200 years

This study presents the first consolidation of palaeoclimate proxy records from multiple archives to develop statistical rainfall reconstructions for southern Africa covering the last two centuries. State-of-the-art ensemble reconstructions reveal multi-decadal rainfall variability in the summer and winter rainfall zones. A decrease in precipitation amount over time is identified in the summer rainfall zone. No significant change in precipitation amount occurred in the winter rainfall zone, but rainfall variability has increased over time. Generally synchronous rainfall fluctuations between the two zones are identified on decadal scales, with common wet (dry) periods reconstructed around 1890 (1930). A strong relationship between seasonal rainfall and sea surface temperatures (SSTs) in the surrounding oceans is confirmed. Coherence among decadal-scale fluctuations of southern African rainfall, regional SST, SSTs in the Pacific Ocean and rainfall in south-eastern Australia suggest SST-rainfall teleconnections across the southern hemisphere. Temporal breakdowns of the SST-rainfall relationship in the southern African regions and the connection between the two rainfall zones are observed, for example during the 1950s. Our results confirm the complex interplay between large-scale teleconnections, regional SSTs and local effects in modulating multi-decadal southern African rainfall variability over long timescales

The freezing level in the tropical Andes, Peru: An indicator for present and future glacier extents: the freezing level in the tropical Andes

Along with air temperatures, the freezing level height (FLH) has risen over the last decades. The mass balance of tropical glaciers in Peru is highly sensitive to a rise in the FLH, mainly due to a decrease in accumulation and increase of energy for ablation caused by reduced albedo. Knowledge of future changes in the FLH is thus crucial to estimating changes in glacier extents. Since in situ data are scarce at altitudes where glaciers exist (above ~4800 m above sea level (asl)), reliable FLH estimates must be derived from multiple data types. Here we assessed the FLHs and their spatiotemporal variability, as well as the related snow/rain transition in the two largest glacier-covered regions in Peru by combining data from two climate reanalysis products, Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar Bright Band data, Micro Rain Radar data, and meteorological ground station measurements. The mean annual FLH lies at 4900 and 5010 m asl, for the Cordillera Blanca and Vilcanota, respectively. During the wet season, the FLH in the Cordillera Vilcanota lies ~150 m higher compared to the Cordillera Blanca, which is in line with the higher glacier terminus elevations. Coupled Model Intercomparison Project version 5 (CMIP5) climate model projections reveal that by the end of the 21st century, the FLH will rise by 230 m (±190 m) for Representative Concentration Pathway (RCP) 2.6 and 850 m (±390 m) for RCP8.5. Even under the most optimistic scenario, glaciers may continue shrinking considerably, assuming a close relation between FLH and glacier extents. Under the most pessimistic scenario, glaciers may only remain at the highest summits above approximately 5800 m asl

Relevance of future snowfall level height in the Peruvian Andes for glacier loss in the 21st century under different emission scenarios

In many regions of Peru, the competition for limited hydrological resources already represents a large risk for conflicts. In this context, and within the circumstances of climate change, there is a great interest in estimating the future loss of Peruvian glaciers. Solid precipitation on glaciers, which affects the shortwave radiation budget via its effects on albedo, in general reduces ablation. For that reason, the height of the upper level of the transition zone between liquid and solid precipitation (snowfall level height) is considered to play a critical role. This snowfall level height is linked to air temperature. The observed and projected warming of the atmosphere is therefore affecting the glaciers amongst others by changing the snowfall level height. Despite the potential significance of these changes for Peruvian glaciers, the relations between snowfall level heights, glacier extents and climate scenarios have been poorly investigated so far. In our study, we first analyse the snowfall level heights over the Peruvian Cordilleras

Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation

Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumvents assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system

Assessing the robustness of Antarctic temperature reconstructions over the past 2 millennia using pseudoproxy and data assimilation experiments

The Antarctic temperature changes over the past millennia remain more uncertain than in many other continental regions. This has several origins: (1) the number of high-resolution ice cores is small, in particular on the East Antarctic plateau and in some coastal areas in East Antarctica; (2) the short and spatially sparse instrumental records limit the calibration period for reconstructions and the assessment of the methodologies; (3) the link between isotope records from ice cores and local climate is usually complex and dependent on the spatial scales and timescales investigated. Here, we use climate model results, pseudoproxy experiments and data assimilation experiments to assess the potential for reconstructing the Antarctic temperature over the last 2 millennia based on a new database of stable oxygen isotopes in ice cores compiled in the framework of Antarctica2k (Stenni et al.,). The well-known covariance between δ 18 O and temperature is reproduced in the two isotope-enabled models used (ECHAM5/MPI-OM and ECHAM5-wiso), but is generally weak over the different Antarctic regions, limiting the skill of the reconstructions. Furthermore, the strength of the link displays large variations over the past millennium, further affecting the potential skill of temperature reconstructions based on statistical methods which rely on the assumption that the last decades are a good estimate for longer temperature reconstructions. Using a data assimilation technique allows, in theory, for changes in the δ 18 O-temperature link through time and space to be taken into account. Pseudoproxy experiments confirm the benefits of using data assimilation methods instead of statistical methods that provide reconstructions with unrealistic variances in some Antarctic subregions. They also confirm that the relatively weak link between both variables leads to a limited potential for reconstructing temperature based on δ 18 O. However, the reconstruction skill is higher and more uniform among reconstruction methods when the reconstruction target is the Antarctic as a whole rather than smaller Antarctic subregions. This consistency between the methods at the large scale is also observed when reconstructing temperature based on the real δ 18 O regional composites of Stenni et al. (2017). In this case, temperature reconstructions based on data assimilation confirm the long-term cooling over Antarctica during the last millennium, and the later onset of anthropogenic warming compared with the simulations without data assimilation, which is especially visible in West Antarctica. Data assimilation also allows for models and direct observations to be reconciled by reproducing the east-west contrast in the recent temperature trends. This recent warming pattern is likely mostly driven by internal variability given the large spread of individual Paleoclimate Modelling Intercomparison Project (PMIP)/Coupled Model Intercomparison Project (CMIP) model realizations in simulating it. As in the pseudoproxy framework, the reconstruction methods perform differently at the subregional scale, especially in terms of the variance of the time series produced. While the potential benefits of using a data assimilation method instead of a statistical method have been highlighted in a pseudoproxy framework, the instrumental series are too short to confirm this in a realistic setup

A global multiproxy database for temperature reconstructions of the Common Era

Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature- sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850–2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python