Heat, humidity and health impacts: how causal diagrams can help tell the complex story.

The global health burden associated with exposure to heat is a grave concern and is projected to further increase under climate change. While physiological studies have demonstrated the role of humidity alongside temperature in exacerbating heat stress for humans, epidemiological findings remain conflicted. Understanding the intricate relationships between heat, humidity, and health outcomes is crucial to inform adaptation and drive increased global climate change mitigation efforts. This article introduces 'directed acyclic graphs' (DAGs) as causal models to elucidate the analytical complexity in observational epidemiological studies that focus on humid-heat-related health impacts. DAGs are employed to delineate implicit assumptions often overlooked in such studies, depicting humidity as a confounder, mediator, or an effect modifier. We also discuss complexities arising from using composite indices, such as wet-bulb temperature. DAGs representing the health impacts associated with wet-bulb temperature help to understand the limitations in separating the individual effect of humidity from the perceived effect of wet-bulb temperature on health. General examples for regression models corresponding to each of the causal assumptions are also discussed. Our goal is not to prioritize one causal model but to discuss the causal models suitable for representing humid-heat health impacts and highlight the implications of selecting one model over another. We anticipate that the article will pave the way for future quantitative studies on the topic and motivate researchers to explicitly characterize the assumptions underlying their models with DAGs, facilitating accurate interpretations of the findings. This methodology is applicable to similarly complex compound events.

ModE-RA: a global monthly paleo-reanalysis of the modern era 1421 to 2008.

The Modern Era Reanalysis (ModE-RA) is a global monthly paleo-reanalysis covering the period between 1421 and 2008. To reconstruct past climate fields an offline data assimilation approach is used, blending together information from an ensemble of transient atmospheric model simulations and observations. In the early period, ModE-RA utilizes natural proxies and documentary data, while from the 17th century onward instrumental measurements are also assimilated. The impact of each observation on the reconstruction is stored in the observation feedback archive, which provides additional information on the input data such as preprocessing steps and the regression-based forward models. The monthly resolved reconstructions include estimates of the most important climate fields. Furthermore, we provide a reconstruction, ModE-RAclim, which together with ModE-RA and the model simulations allows to disentangle the role of observations and model forcings. ModE-RA is best suited to study intra-annual to multi-decadal climate variability and to analyze the causes and mechanisms of past extreme climate events.

DOCU-CLIM: A global documentary climate dataset for climate reconstructions.

Documentary climate data describe evidence of past climate arising from predominantly written historical documents such as diaries, chronicles, newspapers, or logbooks. Over the past decades, historians and climatologists have generated numerous document-based time series of local and regional climates. However, a global dataset of documentary climate time series has never been compiled, and documentary data are rarely used in large-scale climate reconstructions. Here, we present the first global multi-variable collection of documentary climate records. The dataset DOCU-CLIM comprises 621 time series (both published and hitherto unpublished) providing information on historical variations in temperature, precipitation, and wind regime. The series are evaluated by formulating proxy forward models (i.e., predicting the documentary observations from climate fields) in an overlapping period. Results show strong correlations, particularly for the temperature-sensitive series. Correlations are somewhat lower for precipitation-sensitive series. Overall, we ascribe considerable potential to documentary records as climate data, especially in regions and seasons not well represented by early instrumental data and palaeoclimate proxies.

Impact of the Tambora volcanic eruption of 1815 on islands and relevance to future sunlight-blocking catastrophes.

Island nations may have potential long-term survival value for humanity in global catastrophes such as sun-blocking catastrophes from nuclear winter and large magnitude volcanic eruptions. One way to explore this issue further is to understand the impact on islands after the largest historically observed volcanic eruption: that of Mt Tambora in 1815. For each of the 31 large, populated islands selected, we conducted literature searches for relevant historical and palaeoclimate studies. We also analysed results from a reconstruction (EKF400v2), which uses atmospheric-only general circulation model simulations with assimilated observational and proxy data. From the literature review, there was widespread evidence for weather/climate anomalies in 1815-1817 for these islands (29/29 for those with data). But missing data was an issue for other dimensions such as impaired food production (seen in 8 islands out of only 12 with data). Based on the EKF400v2 reconstruction for temperature anomalies (compared to the relatively "non-volcanic" reference period of 1779 to 1808), the islands had lower temperature anomalies in the 1815-1818 period than latitudinally equivalent continental sites (at 100 km and 1000 km inland). This was statistically significant for the great majority of the comparisons for group analyses by hemisphere, oceans, and temperate/tropical zone. When considering just the islands, all but four showed statistically anomalous temperature reductions in the 1816-1817 period (for most p < 0.00001). In the peak impact year of 1816, the lowest anomalies were seen for islands in the Southern Hemisphere (p < 0.0001), the Indian Ocean (p < 0.0001), and in the tropics and subtropics of the Southern Hemisphere (p = 0.0057). In conclusion, the findings of both the literature review and reconstruction simulations suggest climatic impacts of the Tambora eruption for nearly all these 31 large islands, albeit less than for continental sites. Islands with the smallest temperature anomalies were in the Southern Hemisphere, in particular the Indian Ocean and the tropics and subtropics of the Southern Hemisphere.

The global historical climate database HCLIM.

There is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and construction of a global multivariable (air temperature, pressure, precipitation sum, number of precipitation days) monthly instrumental climate database that encompasses a substantial body of the known early instrumental time series. The dataset contains series compiled from existing databases that start before 1890 (though continuing to the present) as well as a large amount of newly rescued data. All series underwent a quality control procedure and subdaily series were processed to monthly mean values. An inventory was compiled, and the collection was deduplicated based on coordinates and mutual correlations. The data are provided in a common format accompanied by the inventory. The collection totals 12452 meteorological records in 118 countries. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate dataset for the preindustrial period so far.

An updated global atmospheric paleo-reanalysis covering the last 400 years.

Data assimilation techniques are becoming increasingly popular for climate reconstruction. They benefit from estimating past climate states from both observation information and from model simulations. The first monthly global paleo-reanalysis (EKF400) was generated over the 1600 and 2005 time period, and it provides estimates of several atmospheric fields. Here we present a new, considerably improved version of EKF400 (EKF400v2). EKF400v2 uses atmospheric-only general circulation model simulations with a greatly extended observational network of early instrumental temperature and pressure data, documentary evidences and tree-ring width and density proxy records. Furthermore, new observation types such as monthly precipitation amounts, number of wet days and coral proxy records were also included in the assimilation. In the version 2 system, the assimilation process has undergone methodological improvements such as the background-error covariance matrix is estimated with a blending technique of a time-dependent and a climatological covariance matrices. In general, the applied modifications resulted in enhanced reconstruction skill compared to version 1, especially in precipitation, sea-level pressure and other variables beside the mostly assimilated temperature data, which already had high quality in the previous version. Additionally, two case studies are presented to demonstrate the applicability of EKF400v2 to analyse past climate variations and extreme events, as well as to investigate large-scale climate dynamics.

A decade of cold Eurasian winters reconstructed for the early 19th century.

Annual-to-decadal variability in northern midlatitude temperature is dominated by the cold season. However, climate field reconstructions are often based on tree rings that represent the growing season. Here we present cold-season (October-to-May average) temperature field reconstructions for the northern midlatitudes, 1701-1905, based on extensive phenological data (freezing and thawing dates of rivers, plant observations). Northern midlatitude land temperatures exceeded the variability range of the 18th and 19th centuries by the 1940s, to which recent warming has added another 1.5 °C. A sequences of cold winters 1808/9-1815/6 can be explained by two volcanic eruptions and unusual atmospheric flow. Weak southwesterlies over Western Europe in early winter caused low Eurasian temperatures, which persisted into spring even though the flow pattern did not. Twentieth century data and model simulations confirm this persistence and point to increased snow cover as a cause, consistent with sparse information on Eurasian snow in the early 19th century.

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.

Homogeneity assessment of phenological records from the Swiss Phenology Network.

Phenological data have become increasingly important as indicators of long-term climate change. Consequently, long-term homogeneity of the records is an important aspect. In this paper, we apply a breakpoint detection algorithm to the phenological series from the Swiss Phenology Network (SPN). A combination of three statistical tests is applied and different constraints are tested with respect to the choice of reference series. Breakpoint detection is only possible for a fraction of the series due to the shortness of some series and the lack of suitable reference series. Spring phases are more likely to be suitable than fall phases because of their higher spatial correlation. Out of nearly 3000 phenological series with at least 20 data points, only about 5% were found to be significantly inhomogeneous, although a visual validation indicates that many mid-sized breakpoints remained undetected. The detected breakpoints were compared with metadata and more than half of them could be attributed to a change of observer.

Consistent multi-decadal variability in global temperature reconstructions and simulations over the Common Era.

Multi-decadal surface temperature changes may be forced by natural as well as anthropogenic factors, or arise unforced from the climate system. Distinguishing these factors is essential for estimating sensitivity to multiple climatic forcings and the amplitude of the unforced variability. Here we present 2,000-year-long global mean temperature reconstructions using seven different statistical methods that draw from a global collection of temperature-sensitive paleoclimate records. Our reconstructions display synchronous multi-decadal temperature fluctuations, which are coherent with one another and with fully forced CMIP5 millennial model simulations across the Common Era. The most significant attribution of pre-industrial (1300-1800 CE) variability at multi-decadal timescales is to volcanic aerosol forcing. Reconstructions and simulations qualitatively agree on the amplitude of the unforced global mean multi-decadal temperature variability, thereby increasing confidence in future projections of climate change on these timescales. The largest warming trends at timescales of 20 years and longer occur during the second half of the 20th century, highlighting the unusual character of the warming in recent decades.

On the extraordinary winter flood episode over the North Atlantic Basin in 1936.

In this study, we analyze the linkage between atmosphere and ocean modes and winter flood variability over the 20th century based on long-term flow-discharge series, historical archives, and tree-ring records of past floods in the North Atlantic Basin (NAB). The most extreme winter floods occurred in 1936 and had strong impacts on either side of the Atlantic. We hypothesize that the joint effects of sea surface temperatures (SSTs) over the Atlantic and Pacific Oceans and the Arctic Oscillation (AO), which is closely related to the North Atlantic Oscillation, play a significant role when describing flood variability in North America and Europe since 1900. Statistical modeling supports the assumption that the response of flood anomalies over the NAB to AO phases is subsidiary of SST phases. Besides, we shed light on the extraordinarily winter flood of 1936 that was characterized by very high SSTs over both the Atlantic and Pacific (>98th percentile) and very low, negative values of AO (<1st percentile). This outstanding winter flood episode was most likely characterized by stratospheric polar vortex anomalies, which can usually be linked to an increased probability of storms in western and southwestern Europe and increased snowfall events in eastern North America. By assessing the flood anomalies over the NAB as a coupled AO and SST function, one could further the understanding of such large-scale events and presumably improve anticipation of future extreme flood occurrences.

Historical weather data for climate risk assessment.

Weather- and climate-related hazards are responsible for monetary losses, material damages, and societal consequences. Quantifying related risks is, therefore, an important societal task, particularly in view of future climate change. For this task, climate risk assessment increasingly uses model chains, which mainly build on data from the last few decades. The past record of events could play a role in this context. New numerical techniques can make use of historical weather data to simulate impacts quantitatively. However, using historical data for model applications differs from using recent products. Here, we provide an overview of climate risk assessment methodologies and of the properties of historical instrumental and documentary data. Using three examples, we then outline how historical environmental data can be used today in climate risk assessment by (1) developing and validating numerical model chains, (2) providing a large statistical sample which can be directly exploited to estimate hazards and to model present risks, and (3) establishing "worst-case" events which are relevant references in the present or future. The examples show that, in order to be successful, different sources (reanalyses, digitized instrumental data, and documentary data) and methods (dynamical downscaling and analog methods) need to be combined on a case-by-case basis.

The early 20th century warming: Anomalies, causes, and consequences.

The most pronounced warming in the historical global climate record prior to the recent warming occurred over the first half of the 20th century and is known as the Early Twentieth Century Warming (ETCW). Understanding this period and the subsequent slowdown of warming is key to disentangling the relationship between decadal variability and the response to human influences in the present and future climate. This review discusses the observed changes during the ETCW and hypotheses for the underlying causes and mechanisms. Attribution studies estimate that about a half (40-54%; p > .8) of the global warming from 1901 to 1950 was forced by a combination of increasing greenhouse gases and natural forcing, offset to some extent by aerosols. Natural variability also made a large contribution, particularly to regional anomalies like the Arctic warming in the 1920s and 1930s. The ETCW period also encompassed exceptional events, several of which are touched upon: Indian monsoon failures during the turn of the century, the "Dust Bowl" droughts and extreme heat waves in North America in the 1930s, the World War II period drought in Australia between 1937 and 1945; and the European droughts and heat waves of the late 1940s and early 1950s. Understanding the mechanisms involved in these events, and their links to large scale forcing is an important test for our understanding of modern climate change and for predicting impacts of future change. This article is categorized under:Paleoclimates and Current Trends > Modern Climate Change.

The effect of the Tambora eruption on Swiss flood generation in 1816/1817.

The Tambora volcano erupted in April 1815 caused many direct and indirect impacts on the climate system, as well as ecosystems and societies around the world. In Switzerland, the eruption contributed to the 1816 "Year Without a Summer", which is considered to be a key factor in generating the highest flooding ever documented of the Lake Constance (7th July 1817) and the flood of the Rhine in Basel. Snow was reported to remain during the summer of 1816, which laid the basis for a massive snow accumulation in the spring of 1817. The meltwater together with a triggering event led to the reported flooding. We aim to create a hydro-meteorological reconstruction of the 1816/1817 period in Switzerland to verify and quantify the historical sources and place them into present-day context. We used an analogue method that was based on historical measurements to generate temperature and precipitation fields for 1816/1817. These data drove a hydrological model that covers the Rhine Basin to Basel. We reproduced the reported features of the hydroclimate, especially in regards to the temperature and snow storage. We showed that the snow storage in spring 1816 and 1817 was substantial and attained the magnitude of a recent extreme, snow-rich winter (1999). However, simulations suggest that the snowfall alone in the spring of 1817, rather than the enduring snow from 1815/1816, led to the meltwater produced from the snow pack that contributed to the flooding in Lake Constance and Basel. These events were strongly underestimated, as the triggering rainfall event was reconstructed too weak. Artificial scenarios reveal that a precipitation amount with a magnitude higher than the largest recent flood (2005) was necessary to generate the documented flood levels. We conclude that these Tambora-following flood events were a product of an adverse combination of extreme weather within an extreme climate.

A monthly global paleo-reanalysis of the atmosphere from 1600 to 2005 for studying past climatic variations.

Climatic variations at decadal scales such as phases of accelerated warming or weak monsoons have profound effects on society and economy. Studying these variations requires insights from the past. However, most current reconstructions provide either time series or fields of regional surface climate, which limit our understanding of the underlying dynamics. Here, we present the first monthly paleo-reanalysis covering the period 1600 to 2005. Over land, instrumental temperature and surface pressure observations, temperature indices derived from historical documents and climate sensitive tree-ring measurements were assimilated into an atmospheric general circulation model ensemble using a Kalman filtering technique. This data set combines the advantage of traditional reconstruction methods of being as close as possible to observations with the advantage of climate models of being physically consistent and having 3-dimensional information about the state of the atmosphere for various variables and at all points in time. In contrast to most statistical reconstructions, centennial variability stems from the climate model and its forcings, no stationarity assumptions are made and error estimates are provided.

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. WIREs Clim Change 2016, 7:569-589. doi: 10.1002/wcc.407 This article is categorized under: 1Paleoclimates and Current Trends > Paleoclimate.