ALBERT

Description: Background Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures. Methods In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature–mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature–mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division. Findings Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967–5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58–11·07) of all deaths (8·52% [6·19–10·47] were cold-related and 0·91% [0·56–1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60–87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000–03 to 2016–19, the global cold-related excess death ratio changed by −0·51 percentage points (95% eCI −0·61 to −0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13–0·31), leading to a net reduction in the overall ratio. The largest decline in overall excess death ratio occurred in South-eastern Asia, whereas excess death ratio fluctuated in Southern Asia and Europe. Interpretation Non-optimal temperatures are associated with a substantial mortality burden, which varies spatiotemporally. Our findings will benefit international, national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately and under climate change scenarios.

Description: Early to Middle Miocene sea-level oscillations of approximately 40–60 m estimated from far-field records1–3 are interpreted to reflect the loss of virtually all East Antarctic ice during peak warmth2. This contrasts with ice-sheet model experiments suggesting most terrestrial ice in East Antarctica was retained even during the warmest intervals of the Middle Miocene4,5. Data and model outputs can be reconciled if a large West Antarctic Ice Sheet (WAIS) existed and expanded across most of the outer continental shelf during the Early Miocene, accounting for maximum ice-sheet volumes. Here we provide the earliest geological evidence proving large WAIS expansions occurred during the Early Miocene (~17.72–17.40 Ma). Geochemical and petrographic data show glacimarine sediments recovered at International Ocean Discovery Program (IODP) Site U1521 in the central Ross Sea derive from West Antarctica, requiring the presence of a WAIS covering most of the Ross Sea continental shelf. Seismic, lithological and palynological data reveal the intermittent proximity of grounded ice to Site U1521. The erosion rate calculated from this sediment package greatly exceeds the long-term mean, implying rapid erosion of West Antarctica. This interval therefore captures a key step in the genesis of a marine-based WAIS and a tipping point in Antarctic ice-sheet evolution.

Description: Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data on European forests to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO2, nitrogen deposition, tree and forest stand level, and remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a “SQLite” relational database or “ASCII” flat file version (at https://doi.org/10.5880/PIK.2020.006/; Reyer et al., 2020). The data policies of the individual contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R package (https://CRAN.R-project.org/package=ProfoundData; Silveyra Gonzalez et al., 2020), which provides basic functions to explore, plot and extract the data for model set-up, calibration and evaluation.

Description: 29 April 2020: Release of Version 0.3 This is an updated version of Reyer et al., (2019, V. 0.1.12, http://doi.org/10.5880/PIK.2019.008). All changes and updates are documented in the changelog available via the data download section. Current process-based vegetation models are complex scientific tools that require proper evaluation of the different processes included in the models to prove that the models can be used to integrate our understanding of forest ecosystems and project climate change impacts on forests. The PROFOUND database (PROFOUND DB) described here aims to bring together data from a wide range of data sources to evaluate vegetation models and simulate climate impacts at the forest stand scale. It has been designed to fulfill two objectives: - Allow for a thorough evaluation of complex, process-based vegetation models using multiple data streams covering a range of processes at different temporal scales - Allow for climate impact assessments by providing the latest climate scenario data. Therefore, the PROFOUND DB provides general a site description as well as soil, climate, CO2, Nitrogen deposition, tree-level, forest stand-level and remote sensing data for 9 forest stands spread throughout Europe. Moreover, for a subset of 5 sites, also time series of carbon fluxes, energy balances and soil water are available. The climate and nitrogen deposition data contains several datasets for the historic period and a wide range of future climate change scenarios following the Representative Emission Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). In addition, we also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND Database is available freely but we incite users to respect the data policies of the individual datasets as provided in the metadata of each data file. The database can also be accessed via the PROFOUND R-package, which provides basic functions to explore, plot and extract the data. The data (PROFOUND DB) are provided in two different versions (ProfoundData.sqlite download as ProfoundData.zip, ProfoundData_ASCII.zip) accompanied by a change-log to the previous published version (changelog_Profound-DB_v03.pdf), auxiliary data of reconstructed single tree data at the site Sorø (Soroe_DBH_H_AGE_20200428.zip) and documented by the three explanatory documents: (1) PROFOUNDdatabase.pdf: describes the structure, organisation and content of the PROFOUND DB. (2) PROFOUNDsites.pdf: displays the main data of the PROFOUND DB for each of the 9 forest sites in tables and plots. (3) ProfoundData.pdf: explains how to use the PROFOUND R-Package "ProfoundData" to access the PROFOUND DB and provides example scripts on how to apply it.

Description: Air temperature has been the most commonly used exposure metric in assessing relationships between thermal stress and mortality. Lack of the high-quality meteorological station data necessary to adequately characterize the thermal environment has been one of the main limitations for the use of more complex thermal indices. Global climate reanalyses may provide an ideal platform to overcome this limitation and define complex heat and cold stress conditions anywhere in the world. In this study, we explored the potential of the Universal Thermal Climate Index (UTCI) based on ERA5 – the latest global climate reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) – as a health-related tool. Employing a novel ERA5-based thermal comfort dataset ERA5-HEAT, we investigated the relationships between the UTCI and daily mortality data in 21 cities across 9 European countries. We used distributed lag nonlinear models to assess exposure-response relationships between mortality and thermal conditions in individual cities. We then employed meta-regression models to pool the results for each city into four groups according to climate zone. To evaluate the performance of ERA5-based UTCI, we compared its effects on mortality with those for the station-based UTCI data. In order to assess the additional effect of the UTCI, the performance of ERA5-and station-based air temperature (T) was evaluated. Whilst generally similar heat- and cold-effects were observed for the ERA5-and station-based data in most locations, the important role of wind in the UTCI appeared in the results. The largest difference between any two datasets was found in the Southern European group of cities, where the relative risk of mortality at the 1st percentile of daily mean temperature distribution (1.29 and 1.30 according to the ERA5 vs station data, respectively) considerably exceeded the one for the daily mean UTCI (1.19 vs 1.22). These differences were mainly due to the effect of wind in the cold tail of the UTCI distribution. The comparison of exposure-response relationships between ERA5-and station-based data shows that ERA5-based UTCI may be a useful tool for definition of life-threatening thermal conditions in locations where high-quality station data are not available.

Description: As the largest river basin on Earth, the Amazon is of major importance to the world's climate and water resources. Over the past decades, advances in satellite-based remote sensing (RS) have brought our understanding of its terrestrial water cycle and the associated hydrological processes to a new era. Here, we review major studies and the various techniques using satellite RS in the Amazon. We show how RS played a major role in supporting new research and key findings regarding the Amazon water cycle, and how the region became a laboratory for groundbreaking investigations of new satellite retrievals and analyses. At the basin-scale, the understanding of several hydrological processes was only possible with the advent of RS observations, such as the characterization of "rainfall hotspots" in the Andes-Amazon transition, evapotranspiration rates, and variations of surface waters and groundwater storage. These results strongly contribute to the recent advances of hydrological models and to our new understanding of the Amazon water budget and aquatic environments. In the context of upcoming hydrology-oriented satellite missions, which will offer the opportunity for new synergies and new observations with finer space-time resolution, this review aims to guide future research agenda toward integrated monitoring and understanding of the Amazon water from space. Integrated multidisciplinary studies, fostered by international collaborations, set up future directions to tackle the great challenges the Amazon is currently facing, from climate change to increased anthropogenic pressure.

Description: A rapid coal phase-out is needed to meet the goals of the Paris Agreement, but is hindered by serious challenges ranging from vested interests to the risks of social disruption. To understand how to organize a global coal phase-out, it is crucial to go beyond cost-effective climate mitigation scenarios and learn from the experience of previous coal transitions. Despite the relevance of the topic, evidence remains fragmented throughout different research fields, and not easily accessible. To address this gap, this paper provides a systematic map and comprehensive review of the literature on historical coal transitions. We use computer-assisted systematic mapping and review methods to chart and evaluate the available evidence on historical declines in coal production and consumption. We extracted a dataset of 278 case studies from 194 publications, covering coal transitions in 44 countries and ranging from the end of the 19th century until 2021. We find a relatively recent and rapidly expanding body of literature reflecting the growing importance of an early coal phase-out in scientific and political debates. Previous evidence has primarily focused on the United Kingdom, the United States, and Germany, while other countries that experienced large coal declines, like those in Eastern Europe, are strongly underrepresented. An increasing number of studies, mostly published in the last 5 years, has been focusing on China. Most of the countries successfully reducing coal dependency have undergone both demand-side and supply-side transitions. This supports the use of policy approaches targeting both demand and supply to achieve a complete coal phase-out. From a political economy perspective, our dataset highlights that most transitions are driven by rising production costs for coal, falling prices for alternative energies, or local environmental concerns, especially regarding air pollution. The main challenges for coal-dependent regions are structural change transformations, in particular for industry and labor. Rising unemployment is the most largely documented outcome in the sample. Policymakers at multiple levels are instrumental in facilitating coal transitions. They rely mainly on regulatory instruments to foster the transitions and compensation schemes or investment plans to deal with their transformative processes. Even though many models suggest that coal phase-outs are among the low-hanging fruits on the way to climate neutrality and meeting the international climate goals, our case studies analysis highlights the intricate political economy at work that needs to be addressed through well-designed and just policies.

Description: The city of Venice and the surrounding lagoonal ecosystem are highly vulnerable to variations in relative sea level. In the past ∼150 years, this was characterized by an average rate of relative sea-level rise of about 2.5 mm/year resulting from the combined contributions of vertical land movement and sea-level rise. This literature review reassesses and synthesizes the progress achieved in quantification, understanding and prediction of the individual contributions to local relative sea level, with a focus on the most recent studies. Subsidence contributed to about half of the historical relative sea-level rise in Venice. The current best estimate of the average rate of sea-level rise during the observational period from 1872 to 2019 based on tide-gauge data after removal of subsidence effects is 1.23 ± 0.13 mm/year. A higher – but more uncertain – rate of sea-level rise is observed for more recent years. Between 1993 and 2019, an average change of about +2.76 ± 1.75 mm/year is estimated from tide-gauge data after removal of subsidence. Unfortunately, satellite altimetry does not provide reliable sea-level data within the Venice Lagoon. Local sea-level changes in Venice closely depend on sea-level variations in the Adriatic Sea, which in turn are linked to sea-level variations in the Mediterranean Sea. Water mass exchange through the Strait of Gibraltar and its drivers currently constitute a source of substantial uncertainty for estimating future deviations of the Mediterranean mean sea-level trend from the global-mean value. Regional atmospheric and oceanic processes will likely contribute significant interannual and interdecadal future variability in Venetian sea level with a magnitude comparable to that observed in the past. On the basis of regional projections of sea-level rise and an understanding of the local and regional processes affecting relative sea-level trends in Venice, the likely range of atmospherically corrected relative sea-level rise in Venice by 2100 ranges between 32 and 62 cm for the RCP2.6 scenario and between 58 and 110 cm for the RCP8.5 scenario, respectively. A plausible but unlikely high-end scenario linked to strong ice-sheet melting yields about 180 cm of relative sea-level rise in Venice by 2100. Projections of human-induced vertical land motions are currently not available, but historical evidence demonstrates that they have the potential to produce a significant contribution to the relative sea-level rise in Venice, exacerbating the hazard posed by climatically induced sea-level changes.

Description: Climate reconstructions for the whole of the Common Era are compromised by the paucity of annually-resolved and absolutely-dated proxy records prior to medieval times. Where reconstructions are based on combinations of different climate archive types of varying spatiotemporal resolution, dating uncertainty, record length and predictive skill, it is challenging to estimate past amplitude ranges, disentangle the relative roles of natural and anthropogenic forcing, and probe deeper interrelationships between climate variability and human history. Here, we compile and analyse updated versions of all the existing summer temperature sensitive treering width chronologies from the Northern Hemisphere that span the entire Common Era. We apply a novel ensemble approach to reconstruct extra-tropical summer temperatures from 1–2010 CE, and calculate uncertainties at continental to hemispheric scales. Peak warming in the 280s, 990s and 1020s, when volcanic forcing was low, was comparable to modern conditions until 2010 CE. The lowest June–August temperature anomaly in 536 not only marks the beginning of the coldest decade, but also defines the onset of the Late Antique Little Ice Age (LALIA). While prolonged warmth during Roman and medieval times roughly coincides with the tendency towards societal prosperity across much of the North Atlantic/European sector and East Asia, major episodes of volcanically-forced summer cooling often presaged widespread famines, plague outbreaks and political upheavals. Our study reveals a larger amplitude of spatially synchronized summer temperature variation during the first millennium of the Common Era than previously recognised. Uncertainties associated with the available tree-ring width measurements emphasize the need to develop more and longer chronologies of wood density and cell anatomy from temperature sensitive sites on both hemispheres where living and relict materials are abundant.

Description: Modelling N transformations within cropping systems is crucial for N management optimization in order to increase N use efficiency and reduce N losses. Such modelling remains challenging because of the complexity of N cycling in soil–plant systems. In the current study, the uncertainties of six widely used process-based models (PBMs), including APSIM, CROPSYST, DAISY, FASSET, HERMES and STICS, were tested in simulating different N managements (catch crops (CC) and different N fertilizer rates) in 12-year rotations in Western Europe. Winter wheat, sugar beet and pea were the main crops, and radish was the main CC in the tested systems. Our results showed that PBMs simulated yield, aboveground biomass, N export and N uptake well with low RMSE values, except for sugar beet, which was generally less well parameterized. Moreover, PBMs provided more accurate crop simulations (i.e. N export and N uptake) compared to simulations of soil (N mineralization and soil mineral N (SMN)) and environmental variables (N leaching). The use of multi-model ensemble mean or median of four PBMs significantly reduced the mean absolute percentage error (MAPE) between simulations and observations to less than 15% for yield, aboveground biomass, N export and N uptake. Multi-model ensemble also significantly reduced the MAPE for net N mineralization and annual N leaching to around 15%, while it was larger than 20% for SMN. Generally, PBMs well simulated the CC effects on N fluxes, i.e. increasing N mineralization and reducing N leaching in both short-term and long-term, and all PBMs correctly predicted the effects of the reduced N rate on all measured variables in the study. The uncertainties of multi-model ensemble for N mineralization, SMN and N leaching were larger, mainly because these variables are influenced by plant-soil interactions and subject to cumulative long-term effects in crop rotations, which makes them more difficult to simulate. Large differences existed between individual PBMs due to the differences in formalisms for describing N processes in soil–plant systems, the skills of modelers and the model calibration level. In addition, the model performance also depended on the simulated variables, for instance, HERMES and FASSET performed better for yield and crop biomass, APSIM, DAISY and STICS performed better for N export and N uptake, STICS provided best simulation for SMN and N leaching among the six individual PBMs in the study, but all PBMs met difficulties to well predict either average or variance of soil N mineralization. Our results showed that better calibration for soil N variables is needed to improve model predictions of N cycling in order to optimize N management in crop rotations.