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Common Era temperature variability has been a prominent component in Intergovernmental Panel on Climate Change reports over the last several decades and was twice featured in their Summary for Policymakers. A single reconstruction of mean Northern Hemisphere temperature variability was first highlighted in the 2001 Summary for Policymakers, despite other estimates that existed at the time. Subsequent reports assessed many large-scale temperature reconstructions, but the entirety of Common Era temperature history in the most recent Sixth Assessment Report of the Intergovernmental Panel on Climate Change was restricted to a single estimate of mean annual global temperatures. We argue that this focus on a single reconstruction is an insufficient summary of our understanding of temperature variability over the Common Era. We provide a complementary perspective by offering an alternative assessment of the state of our understanding in high-resolution paleoclimatology for the Common Era and call for future reports to present a more accurate and comprehensive assessment of our knowledge about this important period of human and climate history. 

During summer 2010, exceptional heat and drought in western Russia (WRU) occurred simultaneously with heavy rainfall and flooding in northern Pakistan (NPK). Here, we use the Great Eurasian Drought Atlas (GEDA), a new 1,021 year tree-ring reconstruction of summer soil moisture, to investigate the variability and dynamics of this exceptional spatially concurrent climate extreme over the last millennium. Summer 2010 in the GEDA was the second driest year over WRU and the largest wet–dry contrast between NPK and WRU; it was also the second warmest year over WRU in an independent 1,015 year temperature reconstruction. Soil moisture variability is only weakly correlated between the two regions and 2010 event analogues are rare, occurring in 31 (3.0%) or 52 (5.1%) years in the GEDA, depending on the definition used. Post-1900 is significantly drier in WRU and wetter in NPK compared to previous centuries, increasing the likelihood of concurrent wet NPK–dry WRU extremes, with over 20% of the events in the record occurring in this interval. The dynamics of wet NPK–dry WRU events like 2010 are well captured by two principal components in the GEDA, modes correlated with ridging over northern Europe and western Russia and a pan-hemispheric extratropical wave train pattern similar to that observed in 2010. Our results highlight how high resolution paleoclimate reconstructions can be used to capture some of the most extreme events in the climate system, investigate their physical drivers, and allow us to assess their behavior across longer timescales than available from shorter instrumental records. 

Abstract The Southern Annular Mode (SAM) is the leading mode of atmospheric variability in the extratropical Southern Hemisphere and has wide ranging effects on ecosystems and societies. Despite the SAM’s importance, paleoclimate reconstructions disagree on its variability and trends over the Common Era, which may be linked to variability in SAM teleconnections and the influence of specific proxies. Here, we use data assimilation with a multi-model prior to reconstruct the SAM over the last 2000 years using temperature and drought-sensitive climate proxies. Our method does not assume a stationary relationship between the SAM and the proxy records and allows us to identify critical paleoclimate records and quantify reconstruction uncertainty through time. We find no evidence for a forced response in SAM variability prior to the 20th century. We do find the modern positive trend falls outside the 2 σ range of the prior 2000 years at multidecadal time scales, supporting the inference that the SAM’s positive trend over the last several decades is a response to anthropogenic climate change. 

Across western North America (WNA), 20th-21st century anthropogenic warming has increased the prevalence and severity of concurrent drought and heat events, also termed hot droughts. However, the lack of independent spatial reconstructions of both soil moisture and temperature limits the potential to identify these events in the past and to place them in a long-term context. We develop the Western North American Temperature Atlas (WNATA), a data-independent 0.5° gridded reconstruction of summer maximum temperatures back to the 16th century. Our evaluation of the WNATA with existing hydroclimate reconstructions reveals an increasing association between maximum temperature and drought severity in recent decades, relative to the past five centuries. The synthesis of these paleo-reconstructions indicates that the amplification of the modern WNA megadrought by increased temperatures and the frequency and spatial extent of compound hot and dry conditions in the 21st century are likely unprecedented since at least the 16th century.

 

Paleoclimate reconstructions are now integral to climate assessments, yet the consequences of using different methodologies and proxy data require rigorous benchmarking. Pseudoproxy experiments (PPEs) provide a tractable and transparent test bed for evaluating climate reconstruction methods and their sensitivity to aspects of real-world proxy networks. Here we develop a dataset that leverages proxy system models (PSMs) for this purpose, which emulates the essential physical, chemical, biological, and geological processes that translate climate signals into proxy records, making these synthetic proxies more relevant to the real world. We apply a suite of PSMs to emulate the widely-used PAGES 2k dataset, including realistic spatiotemporal sampling and error structure. A hierarchical approach allows us to produce many variants of this base dataset, isolating the impact of sampling bias in time and space, representation error, sampling error, and other assumptions. Combining these various experiments produces a rich dataset (“pseudoPAGES2k”) for many applications. As an illustration, we show how to conduct a PPE with this dataset based on emerging climate field reconstruction techniques.

 

Observational and modeling studies indicate significant changes in the global hydroclimate in the twentieth and early twenty-first centuries due to anthropogenic climate change. In this review, we analyze the recent literature on the observed changes in hydroclimate attributable to anthropogenic forcing, the physical and biological mechanisms underlying those changes, and the advantages and limitations of current detection and attribution methods. Changes in the magnitude and spatial patterns of precipitation minus evaporation (P–E) are consistent with increased water vapor content driven by higher temperatures. While thermodynamics explains most of the observed changes, the contribution of dynamics is not yet well constrained, especially at regional and local scales, due to limitations in observations and climate models. Anthropogenic climate change has also increased the severity and likelihood of contemporaneous droughts in southwestern North America, southwestern South America, the Mediterranean, and the Caribbean. An increased frequency of extreme precipitation events and shifts in phenology has also been attributed to anthropogenic climate change. While considerable uncertainties persist on the role of plant physiology in modulating hydroclimate and vice versa, emerging evidence indicates that increased canopy water demand and longer growing seasons negate the water-saving effects from increased water-use efficiency.

 

Abstract. Paleoclimate data assimilation (DA) is a tool for reconstructing past climates that directly integrates proxy records with climate model output. Despite the potential for DA to expand the scope of quantitative paleoclimatology, these methods remain difficult to implement in practice due to the multi-faceted requirements and data handling necessary for DA reconstructions, the diversity of DA methods, and the need for computationally efficient algorithms. Here, we present DASH, a MATLAB toolbox designed to facilitate paleoclimate DA analyses. DASH provides command line and scripting tools that implement common tasks in DA workflows. The toolbox is highly modular and is not built around any specific analysis, and thus DASH supports paleoclimate DA for a wide variety of time periods, spatial regions, proxy networks, and algorithms. DASH includes tools for integrating and cataloguing data stored in disparate formats, building state vector ensembles, and running proxy (system) forward models. The toolbox also provides optimized algorithms for implementing ensemble Kalman filters, particle filters, and optimal sensor analyses with variable and modular parameters. This paper reviews the key components of the DASH toolbox and presents examples illustrating DASH's use for paleoclimate DA applications.

 

Extreme summer temperatures are increasingly common across the Northern Hemisphere and inflict severe socioeconomic and biological consequences. In summer 2021, the Pacific Northwest region of North America (PNW) experienced a 2-week-long extreme heatwave, which contributed to record-breaking summer temperatures. Here, we use tree-ring records to show that summer temperatures in 2021, as well as the rate of summertime warming during the last several decades, are unprecedented within the context of the last millennium for the PNW. In the absence of committed efforts to curtail anthropogenic emissions below intermediate levels (SSP2–4.5), climate model projections indicate a rapidly increasing risk of the PNW regularly experiencing 2021-like extreme summer temperatures, with a 50% chance of yearly occurrence by 2050. The 2021 summer temperatures experienced across the PNW provide a benchmark and impetus for communities in historically temperate climates to account for extreme heat-related impacts in climate change adaptation strategies.