Seasonal Temperature Cycle Research Articles

The Streamflow Response to Multi‐Day Warm Anomaly Events: Sensitivity to Future Warming and Spatiotemporal Variability by Event Magnitude

AbstractPersistent warm temperature anomalies can drive streamflow in regions where snow and glacier melt are important constituents of streamflow. However, the spatiotemporal variability of the streamflow response depends on both the magnitude of the forcing temperature anomalies and the nature of the underlying hydrological system. Here we ask: when, where, and for what magnitude of temperature anomalies will the streamflow response change most rapidly under warming? We use observed streamflow and temperature for 868 basins across Canada to quantify the streamflow response during warm temperature anomalies and how such responses vary in space, time, and by anomaly magnitude. We first identify two temporal modes of the streamflow response, one in autumn and one in spring, the relative strength of which varies by climate. We then use sinusoidal approximations of seasonal temperature cycles to characterize the sensitivity of such modes to changes in annual temperature. At individual basins, we find that relative to moderate warm events, the streamflow response to more extreme warm events is more sensitive to changes in mean annual temperatures, and this sensitivity is greatest in the coastal, southern, and central regions of Canada. Our results have implications for how the hydrological impacts of extreme events, such as heatwaves, will change in space and time under future climate change.

Unconventional cold vortex as precursor to historic early summer heatwaves in North China 2023

In mid-June to July 2023, North China witnessed extreme heatwaves, marked by intense near-surface warming with an advanced seasonal cycle of local air temperature. An unconventional upper-tropospheric cold vortex in early June, deviating from conventional “heat dome” patterns, preceded the heatwave extremes. The zonal SSTA gradient in Indo-Pacific warm pool initially suppressed Indian summer monsoon convection, which stimulated the cold vortex around North China via a tropical-extratropical teleconnection. This anomaly intensified the air-land thermal contrast, leading to increased sensible heating and reduced soil moisture in situ. The drier soil conditions maintained and further augmented sensible heating, escalating surface air temperature, and culminating in extraordinary heatwaves. The air column was then destabilized to mitigate the upper-level cold vortex. Historical records corroborate the extremity of the air-sea interactions in 2023. The ECMWF real-time subseasonal-to-seasonal (S2S) forecasts successfully capture the air-land feedback in both cold vortex and heatwave stages, albeit with an underestimation of heatwave intensity due to biases in soil moisture anomalies. Consequently, the initial cold vortex condition and air-land-sea interactions yield S2S predictability to the historic 2023 heatwaves in North China.

Evaluation of effects of heat released from SOC decomposition on soil carbon stock and temperature

AbstractHeat released from soil organic carbon (SOC) decomposition (referred to as microbial heat hereafter) could alter the soil's thermal and hydrological conditions, subsequently modulate SOC decomposition and its feedback with climate. While understanding this feedback is crucial for shaping policy to achieve specific climate goal, it has not been comprehensively assessed. This study employs the ORCHIDEE‐MICT model to investigate the effects of microbial heat, referred to as heating effect, focusing on their impacts on SOC accumulation, soil temperature and net primary productivity (NPP), as well as implication on land‐climate feedback under two CO2 emissions scenarios (RCP2.6 and RCP8.5). The findings reveal that the microbial heat decreases soil carbon stock, predominantly in upper layers, and elevates soil temperatures, especially in deeper layers. This results in a marginal reduction in global SOC stocks due to accelerated SOC decomposition. Altered seasonal cycles of SOC decomposition and soil temperature are simulated, with the most significant temperature increase per unit of microbial heat (0.31 K J−1) occurring at around 273.15 K (median value of all grid cells where air temperature is around 273.15 K). The heating effect leads to the earlier loss of permafrost area under RCP8.5 and hinders its restoration under RCP2.6 after peak warming. Although elevated soil temperature under climate warming aligns with expectation, the anticipated accelerated SOC decomposition and large amplifying feedback on climate warming were not observed, mainly because of reduced modeled initial SOC stock and limited NPP with heating effect. These underscores the multifaceted impacts of microbial heat. Comprehensive understanding of these effects would be vital for devising effective climate change mitigation strategies in a warming world.

Amplified seasonality in western Europe in a warmer world.

Documenting the seasonal temperature cycle constitutes an essential step toward mitigating risks associated with extreme weather events in a future warmer world. The mid-Piacenzian Warm Period (mPWP), 3.3 to 3.0 million years ago, featured global temperatures approximately 3°C above preindustrial levels. It represents an ideal period for directed paleoclimate reconstructions equivalent to model projections for 2100 under moderate Shared Socioeconomic Pathway SSP2-4.5. Here, seasonal clumped isotope analyses of fossil mollusk shells from the North Sea are presented to test Pliocene Model Intercomparison Project 2 outcomes. Joint data and model evidence reveals enhanced summer warming (+4.3° ± 1.0°C) compared to winter (+2.5° ± 1.5°C) during the mPWP, equivalent to SSP2-4.5 outcomes for future climate. We show that Arctic amplification of global warming weakens mid-latitude summer circulation while intensifying seasonal contrast in temperature and precipitation, leading to an increased risk of summer heat waves and other extreme weather events in Europe's future.

Human-induced intensified seasonal cycle of sea surface temperature

Changes in the seasonal cycle of sea surface temperature (SST) have far-reaching ecological and societal implications. Previous studies have found an intensified SST seasonal cycle under global warming, but whether such changes have emerged in historical records remains largely unknown. Here, we reveal that the SST seasonal cycle globally has intensified by 3.9 ± 1.6% in recent four decades (1983–2022), with hotspot regions such as the northern subpolar gyres experiencing an intensification of up to 10%. Increased greenhouse gases are the primary driver of this intensification, and decreased anthropogenic aerosols also contribute. These changes in anthropogenic emissions lead to shallower mixed layer depths, reducing the thermal inertia of upper ocean and enhancing the seasonality of SST. In addition, the direct impacts of increased ocean heat uptake and suppressed seasonal amplitude of surface heat flux also contribute in the North Pacific and North Atlantic. The temperature seasonal cycle is intensified not only at the ocean surface, but throughout the mixed layer. The ramifications of this intensified SST seasonal cycle extend to the seasonal variation in upper-ocean oxygenation, a critical factor for most ocean ecosystems.

Geographical, Seasonal and Diurnal Variations of Acoustic Attenuation, and Sound Speed in the Near‐Surface Martian Atmosphere

AbstractThis work introduces a comprehensive model of sound attenuation and speed on Mars, in light of the recent operation of several microphones on the surface of Mars. The proposed acoustic model calculates the sound speed and attenuation throughout the near‐surface Martian atmosphere based on first‐principles. We evaluate the effects of the seasonal and diurnal cycle of air temperature, pressure and CO2, as well as the concentration of airborne dust on the sound attenuation. The attenuation and speed of sound are most sensitive to the air temperature and, therefore, they vary with the diurnal temperature cycle and to a lesser degree with the seasonal changes in temperature. The speed of sound also varies with the seasonal variations of the concentration of CO2. The main outcome of this work is an acoustic model capable of computing the sound speed and attenuation for any location at the Martian surface at any time of year and any time of day.

The Northeast Water Polynya, Greenland: Climatology, Atmospheric Forcing and Ocean Response

AbstractThe Northeast Water Polynya is a significant annually recurring summertime Arctic polynya, located off the coast of Northeast Greenland. It is important for marine wildlife and affects local atmospheric and oceanic processes. In this study, over 40 years of observational and reanalysis products (ERA5 and ORAS5) are analyzed to characterize the polynya's climatology and ascertain forcing mechanisms. The Northeast Water Polynya has high spatiotemporal variability; its location, size and structure vary interannually, and the period for which it is open is changing. We show this variability is largely driven by atmospheric forcing. The polynya extent is determined by the direction of the near‐surface flow regime, and the relative locations of high and low sea‐level pressure centers over the region. The surface conditions also impact the oceanic water column, which has a strong seasonal cycle in potential temperature and salinity, the amplitude of which decreases with depth. The ocean reanalyses also show a significant warming trend at all depths and a freshening near the surface consistent with greater ice melt, but salinification at lower depths (∼200 m). As the Arctic region changes due to anthropogenic forcing, the sea‐ice edge is migrating northwards and the Northeast Water Polynya is generally opening earlier and closing later in the year. This could have significant implications for both the atmosphere and ocean in this complex and rapidly changing environment.

Spatio-temporal variability of small-scale leads based on helicopter maps of winter sea ice surface temperatures

Observations of sea ice surface temperature provide crucial information for studying Arctic climate, particularly during winter. We examined 1 m resolution surface temperature maps from 35 helicopter flights between October 2, 2019, and April 23, 2020, recorded during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC). The seasonal cycle of the average surface temperature spanned from 265.6 K on October 2, 2019, to 231.8 K on January 28, 2020. The surface temperature was affected by atmospheric changes and varied across scales. Leads in sea ice (cracks of open water) were of particular interest because they allow greater heat exchange between ocean and atmosphere than thick, snow-covered ice. Leads were classified by a temperature threshold. The lead area fraction varied between 0% and 4% with higher variability on the local (5–10 km) than regional scale (20–40 km). On the regional scale, it remained stable at 0–1% until mid-January, increasing afterward to 4%. Variability in the lead area is caused by sea ice dynamics (opening and closing of leads), as well as thermodynamics with ice growth (lead closing). We identified lead orientation distributions, which varied between different flights but mostly showed one prominent orientation peak. The lead width distribution followed a power law with a negative exponent of 2.63, which is in the range of exponents identified in other studies, demonstrating the comparability to other data sets and extending the existing power law relationship to smaller scales down to 3 m. The appearance of many more narrow leads than wide leads is important, as narrow leads are not resolved by current thermal infrared satellite observations. Such small-scale lead statistics are essential for Arctic climate investigations because the ocean–atmosphere heat exchange does not scale linearly with lead width and is larger for narrower leads.

The emerging human influence on the seasonal cycle of sea surface temperature

The emerging human influence on the seasonal cycle of sea surface temperature

Understanding seasonal cycle of daily extreme temperatures based on generalized additive model for location, scale and shape with smoothing spline

AbstractThe seasonal cycle (SC) of surface air temperature is a substantial element in climatology. Some basic and important topics in climate change studies are based on accurate and reliable estimation of SCs, such as percentile‐based indices of extremes and probability density function (PDF) changes of daily temperatures. For both of them, most studies characterized SCs using averages of multi‐days windows, which is not smooth and accurate enough representing the extreme thresholds and climatological normal of SCs. It is necessary to construct smooth and reasonable SCs for more accurate estimation of temperature changes on extreme thresholds and PDFs. In this study, we propose a flexible method based on generalized additive models for location scale and shape and penalized b‐spline smoothing technique with respective distributions to construct smooth SCs and SC for extreme temperatures (SCETs). The accuracy of the constructed smooth SCETs is good with the estimation biases of percentiles tending to be zero. The constructed smooth SCET also exhibits good stability over time, such that the magnitude changes of temperatures on each calendar day are close to climatic changes of mean temperature when the concerned period shifts. Based on the constructed smooth SCs, climatic changes by seasons and PDFs between two periods, 1961–1990 and 1991–2020, are examined over China. The increase of thresholds for hot extremes in spring during the recent period is prominent, while the increase of thresholds for daytime cold extremes in summer over a part of central to southern China is also notable. The smooth SCs and SCETs based on our flexible statistical modelling framework can characterize daily extreme temperatures reasonably and accurately, and should be expected to have more applications for a better understanding of climate changes related to distributions and seasonal cycles.

Oceanographic Variability in Cumberland Bay, South Georgia, and Its Implications for Glacier Retreat

AbstractSouth Georgia is a heavily glaciated sub‐Antarctic island in the Southern Ocean. Cumberland Bay is the largest fjord on the island, split into two arms, each with a large marine‐terminating glacier at the head. Although these glaciers have shown markedly different retreat rates over the past century, the underlying drivers of such differential retreat are not yet understood. This study uses observations and a new high‐resolution oceanographic model to characterize oceanographic variability in Cumberland Bay and to explore its influence on glacier retreat. While observations indicate a strong seasonal cycle in temperature and salinity, they reveal no clear hydrographic differences that could explain the differential glacier retreat. Model simulations suggest the subglacial outflow plume dynamics and fjord circulation are sensitive to the bathymetry adjacent to the glacier, though this does not provide persuasive reasoning for the asymmetric glacier retreat. The addition of a postulated shallow inner sill in one fjord arm, however, significantly changes the water properties in the resultant inner basin by blocking the intrusion of colder, higher salinity waters at depth. This increase in temperature could significantly increase submarine melting, which is proposed as a possible contribution to the different rates of glacier retreat observed in the two fjord arms. This study represents the first detailed description of the oceanographic variability of a sub‐Antarctic island fjord, highlighting the sensitivity of fjord oceanography to bathymetry. Notably, in fjords systems where temperature decreases with depth, the presence of a shallow sill has the potential to accelerate glacier retreat.

Inferring Northern Hemisphere Continental Warming Patterns from the Amplitude and Phase of the Seasonal Cycle in Surface Temperature

Abstract The seasonal cycle in temperature is a large and well-observed response to radiative forcing, suggesting its potential as a natural analog to human-caused climate change. Although there have been advances constraining some climate feedback parameters using seasonal observations, the seasonal cycle has not been used to inform about the local temperature sensitivity to greenhouse gas forcing. In this study, we uncover a nonlinear relationship between the amplitude and phase of the seasonal cycle and forced temperature trends in seven CMIP5-era large ensembles across the Northern Hemisphere extratropical continents. We develop a mixture energy balance model that reproduces this relationship and reveals the unexpected finding that the phasing of the seasonal cycle—in addition to the amplitude—contains information about local temperature sensitivity to seasonal forcing over land. Using this energy balance model framework, we compare the pattern and magnitude of the seasonally inferred sensitivity of the surface temperature response to anthropogenic radiative forcing. The seasonally constrained model largely reproduces the pattern of human-caused temperature trends seen in climate models (r = 0.81, p value < 0.01), including polar amplification, but the magnitude of the response is smaller by about a factor of 3. Our results show the relevance of both phasing and amplitude for constraining patterns of local feedbacks and suggest the utility of additional research to better understand the differences in sensitivity between seasonal and greenhouse gas forcing. Significance Statement Warming in response to increased greenhouse gases is not spatially uniform across land. We wanted to understand whether the familiar seasonal cycle in temperature could provide information about climate change. We found that climate models show a strong link between the seasonal cycle and future warming: places with a larger and more delayed temperature response to the seasonal cycle in solar forcing tend to warm more across the Northern Hemisphere midlatitudes. A very simple model for the climate system, whose parameters are based on the seasonal cycle, captures the pattern but not the magnitude of warming. Our findings suggest that there are some similarities between the processes that control temperature change on seasonal and climate change time scales, but that we must understand the difference between seasonal and longer-term sensitivity to warming before the seasonal cycle can be used to reduce uncertainty about climate change.

Effects of elevated temperature and different crystal structures of TiO2 nanoparticles on the gut microbiota of mussel Mytilus coruscus

Coastal habitats are exposed to increasing pressure of nanopollutants commonly combined with warming due to the seasonal temperature cycles and global climate change. To investigate the toxicological effects of TiO2 nanoparticles (TiO2 NPs) and elevated temperature on the intestinal health of the mussels (Mytilus coruscus), the mussels were exposed to 0.1 mg/L TiO2 NPs with different crystal structures for 14 days at 20 °C and 28 °C, respectively. Compared to 20 °C, the agglomeration of TiO2 NPs was more serious at 28 °C. Exposure to TiO2 NPs led to elevated mortality of M. coruscus and modified the intestinal microbial community as shown by 16S rRNA sequence analysis. Exposure to TiO2 NPs changed the relative abundance of Bacteroidetes, Proteobacteria and Firmicutes. The relative abundances of putative mutualistic symbionts Tenericutes and Fusobacteria increased in the gut of M. coruscus exposed to anatase, which have contributed to the lower mortality in this group. LEfSe showed the combined stress of warming and TiO2 NPs increased the risk of M. coruscus being infected with potential pathogenic bacteria. This study emphasizes the toxicity differences between crystal structures of TiO2 NPs, and will provides an important reference for analyzing the physiological and ecological effects of nanomaterial pollution on bivalves under the background of global climate change.

Ensembles of climate simulations to anticipate worst case heatwaves during the Paris 2024 Olympics

The Summer Olympic Games in 2024 will take place during the apex of the temperature seasonal cycle in the Paris Area. The mid-latitudes of the Northern hemisphere have witnessed a few intense heatwaves since the 2003 event. Those heatwaves have had environmental and health impacts, which often came as surprises. In this paper, we search for the most extreme heatwaves in Ile-de-France that are physically plausible, under climate change scenarios, for the decades around 2024. We circumvent the sampling limitation by applying a rare event algorithm on CMIP6 data to evaluate the range of such extremes. We find that the 2003 record can be exceeded by more than 4 °C in Ile-de-France before 2050, with a combination of prevailing anticyclonic conditions and cut-off lows. This study intends to raise awareness of those unprecedented events, against which our societies are ill-prepared, in spite of adaptation measures designed from previous events. Those results could be extended to other areas of the world.

Seasonal Evolution of Stable Thermal Stratification in Central Area of Lake Ladoga

The complete climatic courses of the parameters of stable thermal stratification for the central part of Lake Ladoga, the largest European lake, are presented on the basis of empirical relationships, taking into account the physical processes governing water temperature variations. For the first time, the seasonal cycle of the surface water temperature, the temperature and the depth of the thermocline, and the hypolimnion temperature are calculated using the vertical profiles of the temperature obtained from the central area of Lake Ladoga. Temperature data are used for the period of in situ observations from 1897 to the present. The proposed functional forms of the temporal temperature cycle and the course of thermocline’s boundaries deepening are useful for examination and simulation of the heat vertical transport from air to water. Approximation curves for the parameters of heating and cooling periods were developed with high significant determination coefficients. Time dependencies of the climatic rates of change in water temperature and the depth of the thermocline boundaries were determined from the onset of stable stratification to its dissipation. The highest rate of water temperature change in the heating stage takes place in late June–early July, which at the water surface, is 0.32 °C/day, while in the thermocline layer, it is 0.18 °C/day. The peak velocity during the cooling stage at the surface occurs in late August–early September and is 0.14 °C/day, whereas in the thermocline, it is 0.08 °C/day and takes place between September and early October. During the period of heating, the deepening parameters of the thermocline layer do not fluctuate very much, only within the range of 0.1–0.3 m/day. During the cooling period, under the influence of free convection, rates increase drastically. The maximum rates of deepening during the period of full autumn mixing reach 1.8 m/day. When the autumn overturn occurs, the epilimnion thickness equals the bottom depth, and the bottom temperature reaches its maximum during the annual cycle. Climatic norms of the stratification parameters against which it is necessary to assess climate change are calculated.

Large-Scale Stability and the Greater Horn of Africa Long and Short Rains

Abstract The societies of the coastal regions of the Greater Horn of Africa (GHA) experience two distinct rainy seasons: the generally wetter “long” rains in the boreal spring and the generally drier “short” rains in the boreal fall. The GHA rainfall climatology is unique for its latitude in both its aridity and for the dynamical differences between its two rainy seasons. This study explains the drivers of the rainy seasons through the climatology of moist static stability, estimated as the difference between surface moist static energy hs and midtropospheric saturation moist static energy . In areas and at times when this difference, , is higher, rainfall is more frequent and more intense. However, even during the rainy seasons, on average and the atmosphere remains largely stable, in line with the GHA’s aridity. The seasonal cycle of , to which the unique seasonal cycles of surface humidity, surface temperature, and midtropospheric temperature all contribute, helps explain the double-peaked nature of the regional hydroclimate. Despite tropospheric temperature being relatively uniform in the tropics, even small changes in can have substantial impacts on instability; for example, during the short rains, the annual minimum in GHA lowers the threshold for convection and allows for instability despite surface humidity anomalies being relatively weak. This framework can help identify the drivers of interannual variability in GHA mean rainfall or diagnose the origin of biases in climate model simulations of the regional climate.

Shifting summer holidays in Spain as an adaptation measure to climate change

This paper assesses whether moving summer holidays to the warmest period of the year in Spain could be a useful climate change adaptation strategy. While the most popular period for Spanish summer holidays has traditionally been August, we illustrate that the second half of July is the hottest period of the year and when the negative effects of high temperatures are most pronounced. If the holiday period in the second fortnight of August was moved to the second fortnight of July, some of the associated impacts would be mitigated due to the reduced anthropogenic activity during non-working days. In particular, we find a significant reduction in the annual peak of labour productivity loss (~25 %) and, to a lesser extent, of electricity demand and near-surface ozone concentrations (~3–4 %). Finally, we also show that global warming could lead to enhanced differences between both fortnights (even with no change in the seasonal cycle of temperature) because of the non-linear relationships between temperature and its impacts. Therefore, the positive effect of shifting holidays would be even larger in the coming future.

Thermal insulation versus capacitance: A simulation experiment comparing effects of shade and hyporheic exchange on daily and seasonal stream temperature cycles

AbstractIn streams where water temperatures stress native biota, management of riparian shade or hyporheic exchange are both considered viable management strategies for reducing the peaks of daily and seasonal stream channel temperature cycles. Although shade and hyporheic exchange may have similar effects on stream temperatures, their mechanisms differ. Improved understanding of the heat‐exchange mechanisms influenced by shade and hyporheic exchange will aid in the appropriate application of either stream temperature management strategy. To illustrate a conceptual model highlighting shade as ‘thermal insulation’ and hyporheic exchange imparting ‘thermal capacitance’ to a stream reach, we conducted an in‐silico simulation modelling experiment increasing shade or hyporheic exchange parameters on an idealized, hypothetical stream. We assessed the potential effects of increasing shade or hyporheic exchange on a stream reach using an established process‐based heat‐energy budget model of stream‐atmosphere heat exchange and incorporated an advection‐driven hyporheic heat exchange routine. The model tracked heat transport through the hyporheic zone and exchange with the stream channel, while including the effects of hyporheic water age distribution on upwelling hyporheic temperatures. Results showed that shade and hyporheic exchange similarly damped diurnal temperature cycles and differentially altered seasonal cycles of our theoretical stream. In winter, hyporheic exchange warmed simulated channel temperatures whereas shade had little effect. In summer, both shade and hyporheic exchange cooled channel temperatures, though the effects of shade were more pronounced. Our simple‐to‐grasp analogies of ‘thermal insulation’ for shade effects and ‘thermal capacitance’ for hyporheic exchange effects on stream temperature encourage more accurate conceptualization of complex, dynamic heat exchange processes among the atmosphere, stream channel, and alluvial aquifer.

A survey of coastal conditions around the continental US using a high-resolution ocean reanalysis

Obtaining a long-term perspective on the evolution of the ocean is hindered by a lack of sub-surface observations. Ocean reanalyses, which merge fields from an ocean model with observations using complex data assimilation techniques, provide a dynamically consistent estimate of the ocean in time and space. Recently developed ocean reanalyses, several with resolutions finer than 10 km, provide a three-dimensional view of the ocean, including on the continental shelf. Here, we use monthly fields from the 1/12° Global Ocean Reanalysis and Simulations (GLORYS) over the years 1993–2019 to provide a broad survey of temperature, salinity, and mixed layer depth over the shelf (depth < 400 m) around the continental United States. The analyses reveal noteworthy aspects of US coastal oceanography, including: i) how bathymetry shapes the seasonal cycle of bottom water temperature (BWT) and the role of the mixed layer in linking the BWT and sea surface temperature (SST) anomalies; ii) the persistence, trends and distributions of SST and BWT anomalies, which strongly influence extremes such as marine heatwaves; iii) the influence of the outflow from the Mississippi and Columbia rivers on the adjacent ocean; and iv) how the mean and anomalous vertical structure of temperature and salinity vary between the northeast, southeast, Gulf of Mexico and California Current Large Marine Ecosystems. In addition to documenting coastal ocean conditions, the broader goal of the survey is to encourage more detailed studies using high resolution ocean reanalyses such as GLORYS.

Various ways of using empirical orthogonal functions for climate model evaluation

Abstract. We present a framework for evaluating multi-model ensembles based on common empirical orthogonal functions (common EOFs) that emphasize salient features connected to spatio-temporal covariance structures embedded in large climate data volumes. This framework enables the extraction of the most pronounced spatial patterns of coherent variability within the joint dataset and provides a set of weights for each model in terms of the principal components which refer to exactly the same set of spatial patterns of covariance. In other words, common EOFs provide a means for extracting information from large volumes of data. Moreover, they can provide an objective basis for evaluation that can be used to accentuate ensembles more than traditional methods for evaluation, which tend to focus on individual models. Our demonstration of the capability of common EOFs reveals a statistically significant improvement of the sixth generation of the World Climate Research Programme (WCRP) Climate Model Intercomparison Project (CMIP6) simulations in comparison to the previous generation (CMIP5) in terms of their ability to reproduce the mean seasonal cycle in air surface temperature, precipitation, and mean sea level pressure over the Nordic countries. The leading common EOF principal component for annually or seasonally aggregated temperature, precipitation, and pressure statistics suggests that their simulated interannual variability is generally consistent with that seen in the ERA5 reanalysis. We also demonstrate how common EOFs can be used to analyse whether CMIP ensembles reproduce the observed historical trends over the historical period 1959–2021, and the results suggest that the trend statistics provided by both CMIP5 RCP4.5 and CMIP6 SSP245 are consistent with observed trends. An interesting finding is also that the leading common EOF principal component for annually or seasonally aggregated statistics seems to be approximately normally distributed, which is useful information about the multi-model ensemble data.