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Analyses of the effects of extreme weather disasters on global crop production over the past five decades show that drought and extreme heat reduced national cereal production by 9–10%, whereas no discernible effect at the national level was seen for floods and extreme cold; droughts affect yields and the harvested area, whereas extreme heat mainly affects yields. Effects of extreme weather on crop yields This statistical analyses of the effects of extreme weather disasters on global crop yields — derived from country-level agricultural statistics — shows that drought and extreme heat reduced national cereal yields by about 10% over the past five decades. No discernible effect was seen for floods and extreme cold at the national level; droughts affect yields and the harvested area, whereas extreme heat mainly affects yields. In recent years, several extreme weather disasters have partially or completely damaged regional crop production 1 , 2 , 3 , 4 , 5 . While detailed regional accounts of the effects of extreme weather disasters exist, the global scale effects of droughts, floods and extreme temperature on crop production are yet to be quantified. Here we estimate for the first time, to our knowledge, national cereal production losses across the globe resulting from reported extreme weather disasters during 1964–2007. We show that droughts and extreme heat significantly reduced national cereal production by 9–10%, whereas our analysis could not identify an effect from floods and extreme cold in the national data. Analysing the underlying processes, we find that production losses due to droughts were associated with a reduction in both harvested area and yields, whereas extreme heat mainly decreased cereal yields. Furthermore, the results highlight ~7% greater production damage from more recent droughts and 8–11% more damage in developed countries than in developing ones. Our findings may help to guide agricultural priorities in international disaster risk reduction and adaptation efforts.

Changes in extreme cold events (ECEs) attract much attention due to their catastrophic effects on the economy and human life. Although evidence suggests that the frequency, intensity, and duration of ECEs have decreased significantly under global warming, a series of strong ECEs complicates their response to global warming. In this study, a 3D-connected algorithm was first used to detect spatiotemporally continuous ECEs in winter across the Northern Hemisphere (NH) and to evaluate the response of ECEs with varied intensities. Strong and weak ECEs are separated, and they show a distinct response to global warming. Weak ECEs significantly decrease in frequency, projection area and total area over the NH. However, the frequency, projection area and total area of strong ECEs show no significant trend, whereas they are increasing in Siberia and Canada. ECEs are influenced by global warming through both direct effects (increasing surface temperature) and indirect effects (changing atmospheric circulation). Based on the 1pctCO2 experiment from 22 CMIP6 models, the role of indirect effects in the contrast responses of strong and weak ECEs were investigated by removing the direct effect. The results indicate that the indirect effect is responsible for the contrast responses of strong and weak ECEs. The response of strong winter ECEs indicate that the risk of severe disasters remain, which motivates additional research to better prevent economic losses and develop adaptative strategies.

This study discovers a teleconnection of winter cold nights (TN10p) in the Northern Hemisphere lands, termed as the Circum–hemisphere teleconnection (CHT) of extreme cold events (CHTe). The CHTe exhibits five distinct centers of action situated in the Southeastern North America, Baffin Bay Coast, Northern Europe, Middle East–North Africa, and Eastern Siberia. Notably, it displays significant interannual (~ 3a) and decadal (~ 10a) variabilities. Besides, the differences between the CHTe and several known atmospheric and oceanic modes are also illustrated in terms of the occurrence year, physical nature, temporal variability, and spatial structure. Meanwhile, a new atmospheric teleconnection pattern in the troposphere, named as the CHT, corresponds to the atmospheric circulation associated with the CHTe. During the positive CHTe events, the positive CHT events occur, resulting in significant positive geopotential height anomalies (GHTa) over the Central North Atlantic, Western Europe and Songhua River as well as significant negative GHTa over Greenland and Caspian Sea, and vice versa. Compared with the horizontal advections, vertical convections and diabatic heating, the CHT may mainly influence the local TN10p anomalies by modulating atmospheric thickness anomalies over five regions of the CHTe.

From 17 November to 27 December 2022, extremely cold snowstorms frequently swept across North America and Eurasia. Diagnostic analysis reveals that these extreme cold events were closely related to the establishment of blocking circulations. Alaska Blocking (AB) and subsequent Ural Blocking (UB) episodes are linked to the phase transition of the North Atlantic Oscillation (NAO) and represent the main atmospheric regimes in the Northern Hemisphere. The downstream dispersion and propagation of Rossby wave packets from Alaska to East Asia provide a large-scale connection between AB and UB episodes. Based on the nonlinear multi-scale interaction (NMI) model, we found that the meridional potential vorticity gradient (PV y ) in November and December of 2022 was anomalously weak in the mid-high latitudes from North America to Eurasia and provided a favorable background for the prolonged maintenance of UB and AB events and the generation of associated severe extreme snowstorms. However, the difference in the UB in terms of its persistence, location, and strength between November and December is related to the positive (negative) NAO in November (December). During the La Niña winter of 2022, the UB and AB events are related to the downward propagation of stratospheric anomalies, in addition to contributions by La Niña and low Arctic sea ice concentrations as they pertain to reducing PV y in mid-latitudes.

This study investigates the relationship between all-cause mortality and extreme temperature events (ETEs) from 1975 to 2004. For 50 U.S. locations, these heat and cold events were defined based on location-specific thresholds of daily mean apparent temperature. Heat days were defined by a 3-day mean apparent temperature greater than the 95th percentile while extreme heat days were greater than the 97.5th percentile. Similarly, calculations for cold and extreme cold days relied upon the 5th and 2.5th percentiles. A distributed lag non-linear model assessed the relationship between mortality and ETEs for a cumulative 14-day period following exposure. Subsets for season and duration effect denote the differences between early- and late-season as well as short and long ETEs. While longer-lasting heat days resulted in elevated mortality, early season events also impacted mortality outcomes. Over the course of the summer season, heat-related risk decreased, though prolonged heat days still had a greater influence on mortality. Unlike heat, cold-related risk was greatest in more southerly locations. Risk was highest for early season cold events and decreased over the course of the winter season. Statistically, short episodes of cold showed the highest relative risk, suggesting unsettled weather conditions may have some relationship to cold-related mortality. For both heat and cold, results indicate higher risk to the more extreme thresholds. Risk values provide further insight into the role of adaptation, geographical variability, and acclimatization with respect to ETEs.

Against the backdrop of global warming, Northern East Asia experienced a record‐breaking extreme cold event during December 13 to 19 in 2023. The mechanisms behind this extreme cold event remain unclear. This study uses the circulation projection method to detect and quantify the contributions of various factors to this extreme cold event. The findings indicate that large‐scale atmospheric circulation anomalies are the predominant factors triggering this cold wave. The Polar‐Eurasian (POL)‐like teleconnection pattern is identified as a key driver for the cold anomalies, contributing approximately 85% of total cold anomalies in Northern East Asia in this event. Although the POL‐like teleconnection is largely internally generated, the preceding low sea ice levels in the Barents and Kara Seas can strengthen and maintain POL teleconnection. Additionally, preceding November increased snow cover in Northern East Asia can further amplify this cold event by enhancing local surface albedo and reducing incoming solar shortwave radiation. Plain Language Summary Between December 13 and 19, 2023, a powerful cold wave hit Northern East Asia, breaking temperature records. The exact causes of this extreme cold event are still being studied. This research looked at different climate factors to understand what drove this event. The study found that unusual patterns in large‐scale atmospheric circulation were the main reason behind the cold wave, accounting for about 88% of the drop in daily minimum temperatures. Specifically, a Polar‐Eurasian (POL) teleconnection pattern was the key driver, responsible for roughly 85% of the temperature anomalies in Northern East Asia. Low sea ice levels in the Barents and Kara Seas in November helped set up the conditions for this POL pattern, making the region colder. Additionally, increased snow cover in Northern East Asia during November amplified the cold by reflecting more sunlight and reducing warming from the sun. Key Points Large‐scale atmospheric circulation anomalies trigger this extreme cold event over Northern East Asia in December 2023 Extreme phase of POL‐like teleconnection is crucial in causing this cold event Preceding low sea‐ice cover in BKS and increased snow cover in Northern East Asia further amplify this cold event

Analyses of climate model simulations and observations reveal that extreme cold events are likely to persist across each land‐continent even under 21st‐century warming scenarios. The grid‐based intensity, duration and frequency of cold extreme events are calculated annually through three indices: the coldest annual consecutive three‐day average of daily maximum temperature, the annual maximum of consecutive frost days, and the total number of frost days. Nine global climate models forced with a moderate greenhouse‐gas emissions scenario compares the indices over 2091–2100 versus 1991–2000. The credibility of model‐simulated cold extremes is evaluated through both bias scores relative to reanalysis data in the past and multi‐model agreement in the future. The number of times the value of each annual index in 2091–2100 exceeds the decadal average of the corresponding index in 1991–2000 is counted. The results indicate that intensity and duration of grid‐based cold extremes, when viewed as a global total, will often be as severe as current typical conditions in many regions, but the corresponding frequency does not show this persistence. While the models agree on the projected persistence of cold extremes in terms of global counts, regionally, inter‐model variability and disparity in model performance tends to dominate. Our findings suggest that, despite a general warming trend, regional preparedness for extreme cold events cannot be compromised even towards the end of the century. Key Points Cold extremes will persist even under 21st century warming scenarios Credibility of projections is shown with model agreements and hindcast skills Adapting to regional cold extremes cannot be compromised despite global warming

It is well-known that climate warming increases air temperature and reduces cold extremes in the long-term. But internal variability strongly modulates the variability of temperature at mid- and- high latitudes, for example, causing the remarkable cooling and severe winter weather over Eurasia from the 1990s to the early 2010s. It remains unclear whether the occurrence of Eurasian cooling and cold extremes will be offset by climate warming or stimulated by internal variability in the future. Based on the Sixth phase of the Coupled Model Intercomparison Project multi-model projections for 2015–2100, this study shows that the projected probability of Eurasian cooling trend decreases with increasing greenhouse gas concentration in the long-term (i.e. 2070–2099) from 14.8% under SSP126 to 0.9% under SSP585. In the near-term (i.e. 2021–2050), however, Eurasian cooling occurrences are less influenced by different emission scenarios. Coinciding with deep Arctic warming throughout the troposphere, the projected significant Eurasian cooling exhibits similar pattern and intensity among different scenarios. The similar trend towards tropospheric anticyclone over the Arctic among different scenarios in the near-term promotes the deep Arctic warming-Eurasian cooling trend through transporting warm (cold) air into the Arctic (mid-latitudes). Moreover, winter extreme cold anomalies (i.e. −3.0–−2.0 °C) and extreme cold days (i.e. 4–6 d) over the Eurasian continent are not sensitive to emission scenarios in the near-term. In the long-term, the accelerating climate warming under high-emission scenarios significantly reduces the frequency and intensity of Eurasian cold extremes compared to low-emission scenarios. Therefore, the occurrence of Eurasian cooling trend and cold extremes in the near-term will be dominated by internal influences (e.g. Ural blocking) and will rely more on the internal variability after the mid-century if carbon neutrality goal is achieved.

In December 2022, North America experienced an unprecedented extreme cold event. However, the underlying physical mechanisms of this cold wave, and the extent to which it is driven by internal variability or external forcing, are not fully understood. Using ERA5 reanalysis data and the HadGEM3‐A‐N216 attribution simulations, we identified internal variability as the main cause, contributing −5.14 K to surface air temperature (SAT) anomalies in North America. External forcing slightly mitigated the cold by 0.42 K. An internally generated wave train from the North Pacific, influenced in combination by Pacific‐North American (PNA) and North Pacific Oscillation (NPO) teleconnection patterns, initiated this intense cyclonic event, contributing −2.18 K and −2.12 K to SAT anomalies, respectively. La Niña‐like sea surface temperature anomalies amplified this wave train and resultant cold wave. Additionally, excessive snow cover in the previous November also intensified the December cold anomalies by enhancing surface albedo and reducing solar radiation. Plain Language Summary In December 2022, North America was hit by an exceptionally severe cold event. Scientists have been trying to understand the reasons behind this cold wave. Using detailed weather data and climate models, researchers found that natural climate variability played a major role, causing temperatures to drop by about 5.14 degrees Celsius. On the other hand, external factors like human‐induced climate change had a minor effect, slightly reducing the severity of the cold by 0.42 degrees Celsius. The study identified an atmospheric wave train pattern, originating from the North Pacific and moving toward North America, which played a crucial role in triggering this extreme weather. Further investigations showed that this wave train was influenced by specific large‐scale weather patterns in the Pacific region, namely the Pacific‐North American (PNA) and North Pacific Oscillation (NPO) patterns, which contributed to the cold temperatures by approximately 2.18 and 2.12 degrees Celsius, respectively. Additionally, colder‐than‐normal sea surface temperatures in the tropical central Pacific, associated with La Niña, strengthened the wave train. Internal thermodynamical processes, such as increased snow cover, also slightly intensified the cold wave by reflecting more sunlight and reducing the amount of solar energy reaching the surface. Key Points Internal variability triggers 2022 December extreme cold wave in North America PNA and NPO are two key teleconnections responsible for this extreme cold wave Snow cover‐SAT feedback intensifies this extreme cold wave

Skillful prediction of wintertime cold extremes on seasonal time scales is beneficial for multiple sectors. This study demonstrates that North American cold extremes, measured by the frequency of cold days in winter, are predictable several months in advance in the Geophysical Fluid Dynamics Laboratory’s SPEAR (Seamless system for Prediction and EArth system Research) seasonal forecast system. Three predictable components of cold extremes over the North American continent are found to be skillfully predicted on seasonal scales. One is a trend-like component, which shows a continent-wide decrease in the frequency of cold extremes and is primarily attributable to external radiative forcing. This trend-like component is predictable at least 9 months ahead. The second predictable component displays a dipole structure over North America, with negative signs in the northwest and positive signs in the southeast. This dipole component is predictable with significant correlation skill for 2 months and is a response to the central Pacific ENSO (El Niño-Southern Oscillation) as revealed from SPEAR AMIP-style simulations. The third component with the largest loadings over Canada and the northern US shows significant correlations with snow anomalies over mid-to-high latitudes of the North American continent. Predictions using only the three predictable components yield higher/comparable skill relative to the SPEAR raw forecasts.