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The patterns of Holocene temperature change can provide important insight for understanding the recent global warming and assessing future global climate change. However, the mismatch in Holocene mean annual temperature between proxy records and climate models remains controversial, which is likely caused by potential seasonal bias from the geological records. Here, 64 surface sediment samples are analyzed to examine the seasonal bias of brGDGTs reconstruction. Subsequently, we compile 23 brGDGT-based seasonal and annual temperature records from different regions in China and compare them with the TraCE-21 ka simulation results in the same geographical location. The linearly analysis shows a higher correlation between MBT′5me and MAF (mean temperature of months above freezing) than that of MAT (mean annual air temperatures), suggesting the reconstructed temperature based on brGDGTs from aquatic sources may be biased toward MAF. The regionally stacked results indicate that MAF in the Qinghai-Tibet Plateau and Northern China warmed from ~12 to 7 ka BP and then cooled thereafter, while an overall warming trend occurred in Southern China. These patterns of MAF change can be well reproduced by the model simulations. The summer and autumn temperature patterns during the Holocene in the Northern China are primarily driven by local insolation and modulated by ice sheets and greenhouse gas concentrations. The retreat of ice sheets in the early and middle Holocene, coupled with the increase in greenhouse gases, is considered the main driving factor for the long-term warming trend of the Holocene in southern China, whereas orbital-induced summer temperature change might be the major driving factor of MAF change in the Qinghai-Tibet Plateau. Our results suggest that the patterns of seasonal temperature change are basically matched between proxy records and climate models during the Holocene. [ABSTRACT FROM AUTHOR]

Multivariate bias correction (BC) models are well-known to correct more statistical attributes in climate model simulations. However, their inherent complexity and excessive parameters can introduce higher uncertainty into future climate simulations. In contrast, univariate BC models, with fewer parameters, are limited to correcting certain attributes. An issue that has not been investigated in-depth is the impact of an increased number of variables in the multivariate BC has on the bias-corrected climate models’ stability. This study compares the performance of a multivariate BC approach, Multivariate Recursive Nested Bias Correction (MRNBC), and a univariate BC approach, Continuous Wavelet-based Bias Correction (CWBC), as the number of variables to be corrected increases, known as the “curse of dimensionality” (CoD). The analysis uses high-resolution climate model outputs for both current and future simulations of sea surface temperature and precipitation in the Niño 3.4 region. Results show both BC models effectively correct current climate biases. As the number of variables increases, CWBC remains robust and produces sensible future simulations, while MRNBC’s complexity leads to deterioration in standard deviations and spatial cross-correlation. CWBC, based on univariate correction, is relatively unaffected by the CoD.

Contributions of the resolved waves and parameterized gravity waves to changes in the quasi‐biennial oscillation (QBO) in a future simulation (2015–2100) under the SSP370 scenario are investigated using the Community Earth System Model 2 (CESM2) with enhanced vertical resolution and are compared with those from four CESM2 historical simulations (1979–2014). The maximum QBO amplitude of the future simulation is 26.0 m s−1, which is slightly less than that of the historical simulations (27.4–29.3 m s−1). However, the QBO period in the future simulation is much shorter: 21.6 months in the early‐future (2015–2050) and 12 months in the late‐future (2065–2100) period, than in the historical simulations (23.5–30.9 months). The shortened QBO period in the future is primarily due to increases in both resolved wave forcing and parameterized gravity wave drag (GWD) in the stratosphere, with a more significant contribution by the GWD. As convective activity becomes stronger in the future simulation, the momentum flux of parameterized convective gravity waves at the cloud top increases, resulting in stronger GWD in the stratosphere. The increases in the magnitude of westward GWD dominate those of eastward GWD in the stratosphere. This is due to a significant increase in westward momentum flux in the troposphere, especially during the descending easterly QBO, and enhanced westerlies in the lowermost stratosphere, which introduces a westward anomaly. For the resolved waves, Kelvin wave forcing is a key contributor to increased eastward forcing in the future simulation, with relatively minor contributions by other equatorial planetary waves. Plain Language Summary: The quasi‐biennial oscillation (QBO) is a phenomenon in which easterly and westerly winds alternately descend in the equatorial stratosphere roughly every 28 months. The QBO affects various atmospheric phenomena not only at the equator but in mid‐ and high‐latitudes, such as the Madden‐Julian Oscillation, the subtropical jet, and the polar vortex and associated teleconnections. There is a debate over how the QBO cycle will be altered under future climate change. A future climate modeling experiment with a version of the Community Earth System Model 2 that represents the QBO is performed, and it is found that the QBO period decreases to 12 months in the future simulation. There are two main reasons for this change: First, strengthened convection in the equatorial region leads to enhanced convective gravity wave momentum flux, resulting in stronger gravity wave drag in the stratosphere. Second, an increase in eastward forcing by equatorial Kelvin waves strengthens the overall eastward planetary wave forcing. These increases in both gravity wave drag and Kelvin wave forcing contribute to a speeding up of the QBO cycle in the future climate. Key Points: Momentum budget analysis in a warming climate simulation is performed to diagnose the cause of changes in the quasi‐biennial oscillation (QBO)'s periodIncreasing westward parameterized gravity wave drag speeds up the easterly phase of the QBO in a warming climateIncreasing Kelvin wave forcing and eastward parameterized gravity wave drag speed up the westerly phase of the QBO [ABSTRACT FROM AUTHOR]

The change in heating and cooling needs of Greece in the near future due to the climate change is assessed in the present study. Global and regional climate models and two different representative concentration pathways (RCPs) are used to simulate the expected change in temperature. A widely used methodology of computation of heating degree days (HDDs) and cooling degree days (CDDs) is employed with a base temperature of 18 °C. In agreement with the expected temperature rise in the near future, an HDD decrease and CDD increase under both RCPs is also expected. The changes under RCP8.5 are stronger compared to those under RCP4.5. Differences related to topography are noted. The HDD decrease is stronger than CDD increase but the relative increase in CDDs is higher than the relative increase in HDDs. The highest absolute decreases in HDDs are expected for February and March while the highest absolute increases in CDDs are expected during the three summer months. [ABSTRACT FROM AUTHOR]

Climate data portals are essential tools for climate change adaptation. This study analyses differences between two Canadian portals providing bias-adjusted CMIP6 simulations: Climate Data Canada and Portraits Climatiques. The study evaluates three core variables (daily maximum temperature, daily minimum temperature and precipitation) as well as assesses five case studies, taken from the agriculture, transport and health sectors, that relied on climate indicators available through the portals. The underlying datasets vary in multiple ways (bias-adjustment methodology, climate of reference, ensemble composition, emissions scenarios) and, in general, the climatology of variables and indicators tends to be statistically different between portals towards the end of the century. Differences are significantly reduced when comparing projected changes with respect to present climate conditions, highlighting the important role played by the dataset used as a reference for the bias-adjustment procedure. When considered from the point of view of practical applications, the discrepancies between the portals are generally, although not always, sufficiently small that they do not impact the resulting decisions. Finally, indicators based on a fixed threshold were found to be strongly influenced by the reference used for the bias adjustment.

This article acts as an introduction to the JGR‐Atmospheres special section titled Monitoring the Earth Radiation Budget and its Implication to Climate Simulations: Recent Advances and Discussions. It outlines the key findings presented in the articles published in the special section. Additionally, it delves into some of the emerging trends in the ongoing research within this field of research. Plain Language Summary: This is the introduction to the special collection "Monitoring the Earth Radiation Budget and its Implication to Climate Simulations: Recent Advances and Discussions" Key Points: Motivations for this special section are presentedPapers in this special issue are summarizedSome discussions on the current state of the solar forcing within climate simulations [ABSTRACT FROM AUTHOR]

The tectonic closure of the Central American Seaway (CAS) during the mid‐Miocene to mid‐Pliocene (∼16–3 Ma BP) is thought of as a key interval for the onset of the present‐day tropical Pacific oxygen minimum zone (OMZ). In this study we investigate the impact of an open CAS on the ocean circulation and the OMZ in the tropical Pacific. We perform a series of sensitivity experiments with the Kiel Climate Model, where we vary the CAS sill depth from shallow to deep. We find that the eastern tropical Pacific OMZ was less developed during the period of an open CAS. This is driven mainly by an enhanced eastward subsurface current that facilitated an increased oxygen supply from the western tropical Pacific. In addition, a small decrease in net marine primary production and subsequent weaker export of particulate organic carbon induced less subsurface oxygen consumption in the Eastern Equatorial Pacific. Plain Language Summary: Oxygen plays a fundamental role for aerobic life and cycling of biogeochemical properties in the ocean. When low rates of oxygen supply combine with high rates of biological oxygen consumption, oxygen minimum zones (OMZs) are generally formed in the ocean. Today the world's largest OMZ is found in the eastern tropical Pacific where the constriction and final closure of the Central American Seaway (CAS) from 16 to 3 Ma BP created specific characteristics of ocean circulation and biogeochemistry. Using simulations with a climate and a marine biogeochemistry model we investigate whether the CAS closure led to the emergence of today's tropical Pacific OMZ. We find that the eastern tropical Pacific OMZ was less developed and oxygen levels were overall higher in the subsurface Eastern Equatorial Pacific (EEP) when the CAS was open. This was driven mainly by an enhanced eastward subsurface current from the northwestern tropical Pacific. In addition, a small decrease in net marine primary production induced less subsurface oxygen consumption from remineralization of particulate organic matter in the EEP. Key Points: An open Central American Seaway promotes higher oxygen concentrations in the subsurface Pacific waters, with strongest changes in the EEPAn increased eastward subsurface flow in the northeastern tropical Pacific transports young, oxygen‐rich waters in from the western PacificThe improved EEP ventilation is a result of the ocean current redirection in the North and South Pacific during open Central American Seaway [ABSTRACT FROM AUTHOR]

Tropical stratospheric variability is investigated in ensembles of historical simulations performed by nine models for the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Realizations from all the models feature a reasonable quasi‐biennial oscillation (QBO). Variability in the zonal mean zonal winds at the equator is found to be coherent among realizations when a model prescribes the CMIP6 ozone forcing. No such coherence is found when a model simulates ozone. The coherence results in an ensemble mean QBO signal with amplitude, depending on the model, 50%–80% of the mean QBO amplitude from a single realization from the same model. The ensemble mean signal is due to synchronization of QBO phases, attributed to the CMIP6 protocol including a QBO signal in the ozone forcing. Coherence in models using the CMIP6 ozone is, therefore, artificial and individual realizations from these models are not completely independent. Plain Language Summary: High above the equator winds in the stratosphere at altitudes from ∼16–40 km repeatedly switch direction from eastward to westward, and back again, roughly every 14 months. This so‐called quasi‐biennial oscillation (QBO) featured in only a subset of the simulations of the historical period that provided input for the latest international assessments of climate change. Variability in the stratospheric winds at the equator in these simulations is found to be remarkably coherent across ensembles of realizations from the individual models, but only for those models that did not simulate ozone variability. Instead, these models followed a common protocol that specified prescribing an ozone distribution that included a QBO in the tropical stratosphere. For each of the models this causes the simulated QBOs in the winds to synchronize across many realizations of the historical period. Consequently variability in the equatorial stratosphere in these realizations becomes coherent. However, this coherence is not real as it is merely an artifact of the simulations following the agreed ozone protocol. Likewise, due to the design of the protocol, individual realizations from these models can not be considered as been entirely independent in the tropical stratosphere. Key Points: Coupled Model Intercomparison Project phase 6 (CMIP6) historical simulations from several models feature a realistic quasi‐biennial oscillation (QBO) in the equatorial stratosphereQBO phases synchronize across ensembles of realizations from models not able to simulate evolving ozoneThe phase synchronization is artificial and attributed to the CMIP6 protocol prescribing a QBO signal in the ozone forcing data [ABSTRACT FROM AUTHOR]

The Holocene, the most recent interglacial, provides an important time window for evaluating current global warming and predicting future temperature changes. With the development of new temperature proxies and improvements in climate models, significant progress has been made in understanding Holocene temperature changes. However, a major debate persists about whether global temperatures during the Holocene followed a pattern of gradual warming from the end of the Last Glacial Maximum, which culminated in a temperature maximum in the early to middle Holocene, followed by gradual cooling in the late Holocene (the thermal maximum mode); or whether there was a continuous warming trend that continued to the present day (the continuous warming mode). Significant discrepancies exist between different proxy records as well as between proxy records and models, which have resulted in the "Holocene temperature conundrum" that has challenged paleoclimatologists for the past decade. Here, we summarize the progress made to date in the study of Holocene temperature change via proxy reconstructions, climate model simulations, and paleoclimate data assimilation. We emphasize that the current research has limitations in terms of the multiplicity and seasonality of proxy records, the spatial heterogeneity of temperature records, and the incorporation of feedback processes (e.g., vegetation, cloud-radiation feedback) in climate models. These limitations have hindered a comprehensive understanding of the processes and mechanisms of Holocene temperature changes. To solve the "Holocene temperature conundrum", it is necessary to strengthen theoretical research on climate proxies from the perspective of the underlying processes and mechanisms, elucidate the seasonal response of various temperature proxies, emphasize regional differences in temperature changes, and expand quantitative temperature reconstructions to areas with limited records. However, it is also necessary to improve the simulation performance of complex feedback processes in climate models, reduce simulation errors, and advance the research on data assimilation of Holocene continental temperature records, which may ultimately lead to the optimal integration of paleoclimate records and simulations. [ABSTRACT FROM AUTHOR]

The Pangea era is an exceptional phase in Earth's history. It is characterized by its hothouse climate state and the latest supercontinent. Thus, it is expected that atmospheric circulation in the Pangea era was largely different from that of the modern world. Here, we study the Hadley circulation in the Pangea era and compare it with that of the present, by performing climate simulations. Our results show that the annual mean Hadley cells are about 20% and 45% weaker than that in the pre-industrial (PI) climate, and their poleward edges are about 2° wider in latitude. The austral winter cell is weakened by 27% and expanded by 2.6°, while the changes of the boreal winter cell are not significant. One distinctive feature is that the ascending branches of the boreal and austral winter cells shift to 23°S and 18°N, respectively, which are much more poleward than their present locations. Our analyses demonstrate that the weakening and widening of the Hadley circulation is due to increasing tropical and subtropical static stability, and that the poleward shifts of the ascending branches of the winter cells are associated with the geographic configuration of the supercontinent Pangea. [ABSTRACT FROM AUTHOR]

Urban ecosystems represent the main providers of ecosystem services in cities and play a relevant role, among the many services, in the regulation of the urban microclimate and mitigation of the urban heat island effect. The amount, localization, and spatial configuration of vegetation (i.e., urban trees) are key elements for planners and designers aiming at maximizing the climate regulation potential and therefore extending the related benefits to a higher number of residents and city users. Different factors and constraints related to urban morphology and socio-economical characteristics of the urban environment influence the localization of new greening scenarios, therefore impacting the potential benefits that can be obtained by residents. This paper investigates these factors by identifying high-resolution greening scenarios that are able to maximize the cooling benefits for people and local residents. For the case study of metropolitan areas of Catania (Italy) with a hot Mediterranean climate, scenarios are derived by modelling physical and socio-economic factors as spatial constraints with the UMEP model and GIS spatial analysis. Results show that new greenery should be mostly located in public areas that are mostly used by residents. Built on the results obtained in the case study analyzed, the paper also proposes some general planning criteria for the localization of new urban greenery, which should be extended to other geographical urban contexts. [ABSTRACT FROM AUTHOR]

Stressors are especially widespread in urban agglomerations. Common themes of built environment interventions that support health and well-being are blue and green infrastructure, indoor and outdoor air quality, thermal comfort, access to natural lighting, and acoustics. Given the current megatrends of increasing summer temperatures and the high popularity of home offices, we aimed at modeling thermal comfort changes of people working at home in three Austrian cities (Vienna, Innsbruck, and Graz) during the next decades until 2090. We present findings based on (I) an inter-disciplinary literature search and (II) indoor and outdoor climate simulations for actual and future climate scenarios. Based on the results, we discuss the potential impacts for work and human health and well-being, and we suggest a framework for the home office in "post-COVID-19 Austria" that integrates social, ecological, and economic aspects. The results of our study indicate that, in future climate scenarios, overheating of the interior can no longer be prevented without active cooling measures and nature-based solutions. Recommendations on the adjustment of behavior under climate change, including greening, adequate ventilation, and cooling techniques, are thus urgently needed for employees who are working from home in order to maintain physical and mental health and wellbeing. [ABSTRACT FROM AUTHOR]

Bias adjustment of numerical climate model simulations involves several arguments wherein the notion of physical inconsistency is referred to, either for rejecting the legitimacy of bias adjustment in general or for justifying the necessity of sophisticated multivariate techniques. However, this notion is often mishandled, in part because the literature generally proceeds without defining it. In this context, the central objective of this study is to clarify and illustrate the distinction between physical inconsistency and multivariate bias, by investigating the effect of bias adjustment on two different kinds of intervariable relationships, namely a physical constraint expected to hold at every step of a time series and statistical properties that emerge with potential bias over a climatic timescale. To this end, 18 alternative bias adjustment techniques are applied on 10 climate simulations at 12 sites over North America. Adjusted variables are temperature, pressure, relative humidity and specific humidity, linked by a thermodynamic constraint. The analysis suggests on the one hand that a clear instance of potential physical inconsistency can be avoided with either a univariate or a multivariate technique, if and only if the bias adjustment strategy explicitly considers the physical constraint to be preserved. On the other hand, it also suggests that sophisticated multivariate techniques alone are not complete adjustment strategies in presence of a physical constraint, as they cannot replace its explicit consideration. By involving common bias adjustment procedures with likely effects on diverse basic statistical properties, this study may also help guide climate information users in the determination of adequate bias adjustment strategies for their research purposes. [ABSTRACT FROM AUTHOR]

This study addresses the applicability of general circulation models (GCMs) in studying the impact of climate change on hydrology. The statistical downscaling of precipitation based on circulation types (CTs) derived from the fuzzy, i.e., more than one CTs can occur in a given day, obliquely rotated principal component analysis is suggested as a robust methodology in using climate models to research the impact of climate change on hydrology. The methodology allows understanding of the mechanism of atmospheric circulation in the study region, and the physical relationship between atmospheric circulation and the regional hydrological cycle. The capability of climate simulations from the Max Planck Institute Earth System Model (MPI-ESM) GCM to reproduce the observed CTs in the target region is examined in light of the uncertainty of atmospheric GCMs when used for circulation typing. The results were discussed and it showed that, generally, the analyzed GCM can reproduce the underlying physics of atmospheric circulation in the study region, represented by the CTs, together with their dominant periods, probability of occurrence, and annual frequency of occurrence with modest biases. Generally, the Coupled Model Intercomparison Project 6 (CMIP6) simulation indicates some improvement for the CT-based analysis relative to the CMIP5 counterpart; however, this depends on the analyzed CT. HIGHLIGHTS Application of circulation typing to downscale rainfall.; Understanding the physical link between rainfall and large-scale atmospheric circulation.; Ability of climate simulations to reproduce observed circulation types.; Added value in using the CMIP6 simulation over the CMIP5.; Strengths and weaknesses of the GCM for circulation type analysis.;

Abstract Modern controlled environment facilities (CEFs) enable the simulation of dynamic microclimates in controlled ecological experiments through their technical ability to precisely control multiple environmental parameters. However, few CEF studies exploit the technical possibilities of their facilities, as climate change treatments are frequently applied by static manipulation of an inadequate number of climate change drivers, ignoring intra‐annual variability and covariation of multiple meteorological variables. We present a method for generating regionalized climate series in high temporal resolution that was developed to force the TUMmesa Model EcoSystem Analyzer with dynamic climate simulations. The climate series represent annual cycles for a reference period (1987–2016) and the climate change scenarios RCP2.6 and RCP8.5 (2071–2100) regionalized for a climate station situated in a forested region of the German Spessart mountains. Based on the EURO‐CORDEX and ReKliEs‐DE model ensembles, typical annual courses of daily resolved climatologies for the reference period and the RCP scenarios were calculated from multimodel means of temperature (ta), relative humidity (rh), global radiation (Rg), air pressure (P), and ground‐level ozone and complemented by CO2. To account for intra‐annual variation and the covariability of multiple climate variables, daily values were substituted by hourly resolved data resampled from the historical record. The resulting present climate Test Reference Year (TRY) well represented a possible annual cycle within the reference period, and expected shifts in future mean values (e.g., higher ta) were reproduced within the RCP TRYs. The TRYs were executed in eight climate chambers of the TUMmesa facility and—accounting for the technical boundaries of the facility—reproduced with high precision. Especially, as an alternative to CEF simulations that reproduce mere day/night cycles and static manipulations of climate change drivers, the method presented here proved well suited for simulating regionalized and highly dynamic annual cycles for ecological CEF studies.

The population of the Sahel region of West Africa has approximately doubled in the past 50 years, and could potentially double again by the middle of this century. This has led to the northward expansion of agricultural areas at the expense of natural savanna, leading to widespread land use -land cover change (LULCC). Because there is strong evidence of significant surface-atmosphere coupling in this region, one of the main goals of the West African Monsoon Modeling and Evaluation project phase II is to provide basic understanding of LULCC on the regional climate, and to evaluate the sensitivity of the seasonal variability of the West African Monsoon to LULCC. The prescribed LULCC is based on the changes from 1950 through 1990, representing a maximum feasible degradation scenario in the past half century. It is applied to 5 state of the art global climate models (GCMs) over a 6-year simulation period. Multiple GCMs are used because the magnitude of the impact of LULCC depends on model-dependent coupling strength between the surface and the overlying atmosphere, the magnitude of the surface biophysical changes, and how the key processes linking the surface with the atmosphere are parameterized within a particular model framework. Land cover maps and surface parameters may vary widely among models; therefore a special effort was made to impose consistent biogeophysical responses of surface parameters to LULCC using a simple experimental setup. The prescribed LULCC corresponds to degraded vegetation conditions, which mainly cause increases in the Bowen ratio and decreases in the surface net radiation, and result in a significant reduction in surface evaporation (upwards of 1 mm day−1 over a large part of the Sahel). This, in turn, mainly leads to less moisture convergence and precipitation over the LULCC zone. The overall impact is a rainfall reduction with every model, which ranges across models from 4 to 25 % averaged over the Sahel, and a southward shift of the rainfall peak in three of the five models which evokes a precipitation dipole pattern which is consistent with the observed pattern for dry climate anomalies over this region. The African Easterly Jet shifts equator-ward, although the strength of this change varies considerably among the models. In most of the models, the main factor causing diabatic cooling of the upper troposphere and enhanced subsidence over the region of LULCC is the reduction of convective heating rates linked to reduced latent heat flux and moisture flux convergence. In broad agreement with previous studies, the impact of degradation on the regional climate is found to vary among the different models, however, the signal is stronger and more consistent between the models here than in previous inter-comparison projects. This is likely related to our emphasis on prioritizing a consistent impact of LULCC on the surface biophysical properties.

Climate model outputs are commonly corrected using statistical univariate bias correction methods. Most of the time, those 1d-corrections do not modify the ranks of the time series to be corrected. This implies that biases in the spatial or inter-variable dependences of the simulated variables are not adjusted. Hence, over the last few years, some multivariate bias correction (MBC) methods have been developed to account for inter-variable structures, inter-site ones, or both. As proof-of-concept, we propose to adapt a computer vision technique used for Image-to-Image translation tasks (CycleGAN) for the adjustment of spatial dependence structures of climate model projections. The proposed algorithm, named MBC-CycleGAN, aims to transfer simulated maps (seen as images) with inappropriate spatial dependence structure from climate model outputs to more realistic images with spatial properties similar to the observed ones. For evaluation purposes, the method is applied to adjust maps of temperature and precipitation from climate simulations through two cross-validation approaches. The first one is designed to assess two different post-processing schemes (Perfect Prognosis and Model Output Statistics). The second one assesses the influence of nonstationary properties of climate simulations on the performance of MBC-CycleGAN to adjust spatial dependences. Results are compared against a popular univariate bias correction method, a "quantile-mapping" method, which ignores inter-site dependencies in the correction procedure, and two state-of-the-art multivariate bias correction algorithms aiming to adjust spatial correlation structure. In comparison with these alternatives, the MBC-CycleGAN algorithm reasonably corrects spatial correlations of climate simulations for both temperature and precipitation, encouraging further research on the improvement of this approach for multivariate bias correction of climate model projections. [ABSTRACT FROM AUTHOR]

Modern controlled environment facilities (CEFs) enable the simulation of dynamic microclimates in controlled ecological experiments through their technical ability to precisely control multiple environmental parameters. However, few CEF studies exploit the technical possibilities of their facilities, as climate change treatments are frequently applied by static manipulation of an inadequate number of climate change drivers, ignoring intra‐annual variability and covariation of multiple meteorological variables. We present a method for generating regionalized climate series in high temporal resolution that was developed to force the TUMmesa Model EcoSystem Analyzer with dynamic climate simulations. The climate series represent annual cycles for a reference period (1987–2016) and the climate change scenarios RCP2.6 and RCP8.5 (2071–2100) regionalized for a climate station situated in a forested region of the German Spessart mountains. Based on the EURO‐CORDEX and ReKliEs‐DE model ensembles, typical annual courses of daily resolved climatologies for the reference period and the RCP scenarios were calculated from multimodel means of temperature (ta), relative humidity (rh), global radiation (Rg), air pressure (P), and ground‐level ozone and complemented by CO2. To account for intra‐annual variation and the covariability of multiple climate variables, daily values were substituted by hourly resolved data resampled from the historical record. The resulting present climate Test Reference Year (TRY) well represented a possible annual cycle within the reference period, and expected shifts in future mean values (e.g., higher ta) were reproduced within the RCP TRYs. The TRYs were executed in eight climate chambers of the TUMmesa facility and—accounting for the technical boundaries of the facility—reproduced with high precision. Especially, as an alternative to CEF simulations that reproduce mere day/night cycles and static manipulations of climate change drivers, the method presented here proved well suited for simulating regionalized and highly dynamic annual cycles for ecological CEF studies. [ABSTRACT FROM AUTHOR]

Approximately 10 years ago, convection‐permitting regional climate models (CPRCMs) emerged as a promising computationally affordable tool to produce fine resolution (1–4 km) decadal‐long climate simulations with explicitly resolved deep convection. This explicit representation is expected to reduce climate projection uncertainty related to deep convection parameterizations found in most climate models. A recent surge in CPRCM decadal simulations over larger domains, sometimes covering continents, has led to important insights into CPRCM advantages and limitations. Furthermore, new observational gridded datasets with fine spatial and temporal (~1 km; ~1 h) resolutions have leveraged additional knowledge through evaluations of the added value of CPRCMs. With an improved coordination in the frame of ongoing international initiatives, the production of ensembles of CPRCM simulations is expected to provide more robust climate projections and a better identification of their associated uncertainties. This review paper presents an overview of the methodology to produce CPRCM simulations and the latest research on the related added value in current and future climates. Impact studies that are already taking advantage of these new CPRCM simulations are highlighted. This review paper ends by proposing next steps that could be accomplished to continue exploiting the full potential of CPRCMs. This article is categorized under:Climate Models and Modeling > Earth System Models [ABSTRACT FROM AUTHOR]

Humans have made such dramatic and permanent changes to Earth's landscapes that much of it is now substantially and irreversibly altered from its preanthropogenic state. Remote islands, until recently isolated from humans, offer insights into how these landscapes evolved in response to human-induced perturbations. However, little is known about when and how remote systems were colonized because archaeological data and historical records are scarce and incomplete. Here, we use a multiproxy approach to reconstruct the initial colonization and subsequent environmental impacts on the Azores Archipelago. Our reconstructions provide unambiguous evidence for widespread human disturbance of this archipelago starting between 700-60+50 and 850-60+60 Common Era (CE), ca. 700 y earlier than historical records suggest the onset of Portuguese settlement of the islands. Settlement proceeded in three phases, during which human pressure on the terrestrial and aquatic ecosystems grew steadily (i.e., through livestock introductions, logging, and fire), resulting in irreversible changes. Our climate models suggest that the initial colonization at the end of the early Middle Ages (500 to 900 CE) occurred in conjunction with anomalous northeasterly winds and warmer Northern Hemisphere temperatures. These climate conditions likely inhibited exploration from southern Europe and facilitated human settlers from the northeast Atlantic. These results are consistent with recent archaeological and genetic data suggesting that the Norse were most likely the earliest settlers on the islands. [ABSTRACT FROM AUTHOR]

We evaluate the benefits of the use of a regional coupled model over its stand-alone atmospheric component when forced by reanalysis data in the simulation of the South American climate. We find that the coupling allows for a better simulation of important features of the atmospheric circulation and surface temperature. The simulated 2 meters air temperature is improved over most of the continent, the sea level pressure over the South Pacific Anticyclone area is better represented in the coupled simulation and the location of the ITCZ is improved during the austral winter. The precipitation, especially over the Andes, benefits less from the coupling, although a more realistic humidity transport leads to a reduction of the precipitation biases over extensive regions. The austral summer precipitation bias is reduced in areas such as eastern Colombia, northern Bolivia, eastern Brazil and central Argentina. For austral winter, the coupled model has a better performance in a large part of the Amazon region, in areas such as east of Peru, west Brazil, north Bolivia and south Argentina. Moreover, the regionally coupled model not only improves the simulation of important features of the observed atmospheric fields but also demonstrates good skills in reproducing the Humboldt upwelling system. Therefore, our study highlights the advantages of regional coupled models for the simulation of the South American climate, as the ocean-atmosphere interaction is of utmost importance for the circulation mechanisms that determine the climate of the region. • ROM is a powerful tool simulating the South America climate. • The coupling improves the representation of many of its features. • The coupled simulation better reproduces the South Pacific anticyclone. • Regional coupling provides a good representation of the Humboldt upwelling system. [ABSTRACT FROM AUTHOR]

The electricity supply chain, especially electricity demand, is very sensitive to climate. Developing a clear and quantitative understanding of the impacts of climate change on monthly electricity demand is critical for long-term generation capacity planning to maintain a reliable electricity supply system. A methodological framework applicable to city-level study is proposed and applied in Tianjin to investigate the impacts of climate change on monthly electricity consumption. By combining the empirical results with an ensemble of climate predictions under three Representative Concentration Pathways (RCPs), the study simulates the changes in monthly electricity demand caused by climate change in Tianjin by the end-of-century. The simulation results showed that climate change is projected to have severe impacts on the frequency and intensity of monthly peak electricity demand. Specifically, electricity demand in July would be 56% higher than that in November in 2099 under the RCP8.5 scenario. Climate change may drive substantial changes to the electricity supply chain, and our study is indicative of a need for adaptive strategies. [ABSTRACT FROM AUTHOR]

Simulation of past climate is an important tool for the validation of climate models. The comparison with observed daily values allows us to assess the reliability of their projections on climatic extremes in a future climate. The frequency and amplitude of extreme events are fundamental aspects that climate simulations need to reproduce as they have high impacts on economy and society. The ability to simulate them will help policy makers in taking better measures to face climate change. This work aims at evaluating how six models within the High Resolution Model Intercomparison Project reproduce the trends on extreme indices as they have been observed over Europe in the 1970–2014 period. Observed values are provided by the new homogenized version of the E-OBS gridded dataset. The comparison is performed through the use of indices based on seasonal averages and on exceedances of percentile-based thresholds, focusing on six subregions. Winter-average minimum temperature is generally underestimated by models (down to − 4 °C difference over Italy and Norway) while simulated trends in seasonal averages and extreme values are found to be too cold on Eastern Europe and too warm on Iberia and Southern Europe (e.g. up to a difference of − 4% per decade on the number of Cold Nights over Spain). On the other hand the models tend to overestimate summer maximum temperatures averages in the Mediterranean Area (up to + 5 °C over the Balkans) and underestimate these at higher latitudes. Iberia, Southern and Eastern Europe are simulated with too low trends in average summer temperatures. The simulated trends are too strong on the North West part and too weak on the South East part of Europe (down to − 3%/decade on the number of Warm Days over Italy and Western Balkans). These results corroborate the findings of previous studies about the underestimation of the warming trends of summer temperatures in Southern Europe, where these are more intense and have more impacts. The high-resolution versions of the models are compared to their lower-resolution counterparts, similar to those used in the CMIP5, showing a slight improvement for the simulation of extreme winter minimum temperatures, while no significant progresses have been found for extreme summer maximum temperatures. [ABSTRACT FROM AUTHOR]

Natural modes of variability on many timescales influence aerosol particle distributions and cloud properties such that isolating statistically significant differences in cloud radiative forcing due to anthropogenic aerosol perturbations (indirect effects) typically requires integrating over long simulations. For state-of-the-art global climate models (GCM), especially those in which embedded cloud-resolving models replace conventional statistical parameterizations (i.e., multiscale modeling framework, MMF), the required long integrations can be prohibitively expensive. Here an alternative approach is explored, which implements Newtonian relaxation (nudging) to constrain simulations with both pre-industrial and present-day aerosol emissions toward identical meteorological conditions, thus reducing differences in natural variability and dampening feedback responses in order to isolate radiative forcing. Ten-year GCM simulations with nudging provide a more stable estimate of the global-annual mean net aerosol indirect radiative forcing than do conventional free-running simulations. The estimates have mean values and 95% confidence intervals of −1.19 ± 0.02 W/m2 and −1.37 ± 0.13 W/m2for nudged and free-running simulations, respectively. Nudging also substantially increases the fraction of the world's area in which a statistically significant aerosol indirect effect can be detected (66% and 28% of the Earth's surface for nudged and free-running simulations, respectively). One-year MMF simulations with and without nudging provide global-annual mean net aerosol indirect radiative forcing estimates of −0.81 W/m2 and −0.82 W/m2, respectively. These results compare well with previous estimates from three-year free-running MMF simulations (−0.83 W/m2), which showed the aerosol-cloud relationship to be in better agreement with observations and high-resolution models than in the results obtained with conventional cloud parameterizations.

In spring 2011, an unprecedented flood hit the complex eastern United States (U.S.)–Canada transboundary Lake Champlain–Richelieu River (LCRR) Basin, destructing properties and inducing negative impacts on agriculture and fish habitats. The damages, covered by the Governments of Canada and the U.S., were estimated to C$90M. This natural disaster motivated the study of mitigation measures to prevent such disasters from reoccurring. When evaluating flood risks, long‐term evolving climate change should be taken into account to adopt mitigation measures that will remain relevant in the future. To assess the impacts of climate change on flood risks of the LCRR basin, three bias‐corrected multi‐resolution ensembles of climate projections for two greenhouse gas concentration scenarios were used to force a state‐of‐the‐art, high‐resolution, distributed hydrological model. The analysis of the hydrological simulations indicates that the 20‐year return period flood (corresponding to a medium flood) should decrease between 8% and 35% for the end of the 21st Century (2070–2099) time horizon and for the high‐emission scenario representative concentration pathway (RCP) 8.5. The reduction in flood risks is explained by a decrease in snow accumulation and an increase in evapotranspiration expected with the future warming of the region. Nevertheless, due to the large climate inter‐annual variability, short‐term flood probabilities should remain similar to those experienced in the recent past. [ABSTRACT FROM AUTHOR]

Quantile mapping (QM) is a technique often used for statistical post‐processing (SPP) of climate model simulations, in order to adjust their biases relative to a selected reference product and/or to downscale their resolution. However, when QM is applied in univariate mode, there is a risk of generating other problems, like intervariable physical inconsistency (PI). Here, such a risk is investigated with daily temperature minimum (Tmin) and maximum (Tmax), for which the relationship Tmin> Tmax would be inconsistent with the definition of the variables. QM is applied to an ensemble of 78 daily CMIP5 simulations over Hudson Bay for the application period 1979–2100, with Climate Forecast System Reanalysis (CFSR) selected as the reference product during the calibration period 1979–2010. This study's specific objectives are as follows: to investigate the conditions under which PI situations are generated; to test whether PI may be prevented simply by tuning some of the QM technique's numerical choices; and to compare the suitability of alternative approaches that hinder PI by design. Primary results suggest that PI situations appear preferentially for small values of the initial (simulated) diurnal temperature range (DTR), but the differential between the respective biases of Tmin and Tmax also plays an important role; one cannot completely prevent the generation of PI simply by adjusting QM parameters and options, but forcing preservation of the simulated long‐term trends generates fewer PI situations; for avoiding PI between Tmin and Tmax, the present study supports a previous recommendation to directly post‐process Tmax and DTR before deducing Tmin. [ABSTRACT FROM AUTHOR]

Pacific quasi-decadal oscillation (PQDO) is one component of the multi-time-scale tropical Pacific decadal variability, with a variability center in the equatorial central Pacific (ECP). PQDO has emerged since the 1950s and has a significant impact on decadal climate variability over Asia and North America and Pacific storms. However, why it has intensified since the 1950s remains unknown. Here we test two competing hypotheses, (1) 11-year solar cycle forcing and (2) internal variability arising from El Niño–Southern Oscillation (ENSO) asymmetry, by analyzing simulation results, including one fixed-forcing control (CTRL) experiment and four sensitive experiments with millennial spectral solar irradiance (SSI), obtained from the Community Earth System Model–Last Millennium Ensemble modeling project. The four-member ensemble-averaged SSI experiments suggest that 11-year solar irradiance forcing cannot excite PQDO without stratospheric amplification of solar forcing. By analyzing 144 years of observations and the CTRL experiment, we find that the PQDO is nonstationary, and consecutive La Niña-induced decadal variability can boost PQDO in the ECP. El Niño could induce decadal ENSO signals in the NINO3.4 region but not in PQDO regions. The negative phase of PQDO tends to follow the occurrence of multi-year La Niña. We suggest that the emergence of PQDO since the 1950s is mainly due to the increase in multi-year La Niña events.

Extreme ocean warming events, known as marine heatwaves (MHWs), have been observed to perturb significantly marine ecosystems and fisheries around the world. Here, we propose a detection method for long-lasting and large-scale summer MHWs, using a local, climatological 99th percentile threshold, based on present-climate (1976–2005) daily SST. To assess their future evolution in the Mediterranean Sea we use, for the first time, a dedicated ensemble of fully-coupled Regional Climate System Models from the Med-CORDEX initiative and a multi-scenario approach. The models appear to simulate well MHW properties during historical period, despite biases in mean and extreme SST. In response to increasing greenhouse gas forcing, the events become stronger and more intense under RCP4.5 and RCP8.5 than RCP2.6. By 2100 and under RCP8.5, simulations project at least one long-lasting MHW every year, up to three months longer, about 4 times more intense and 42 times more severe than present-day events. They are expected to occur from June-October and to affect at peak the entire basin. Their evolution is found to occur mainly due to an increase in the mean SST, but increased daily SST variability also plays a noticeable role. Until the mid-21st century, MHW characteristics rise independently of the choice of the emission scenario, the influence of which becomes more evident by the end of the period. Further analysis reveals different climate change responses in certain configurations, more likely linked to their driving global climate model rather than to the individual model biases. [ABSTRACT FROM AUTHOR]

Performance portability on heterogeneous high-performance computing (HPC) systems is a major challenge faced today by code developers: parallel code needs to be executed correctly as well as with high performance on machines with different architectures, operating systems, and software libraries. The finite element method (FEM) is a popular and flexible method for discretizing partial differential equations arising in a wide variety of scientific, engineering, and industrial applications that require HPC. This article presents some preliminary results pertaining to our development of a performance portable implementation of the FEM-based Albany code. Performance portability is achieved using the Kokkos library. We present performance results for the Aeras global atmosphere dynamical core module in Albany. Numerical experiments show that our single code implementation gives reasonable performance across three multicore/many-core architectures: NVIDIA General Processing Units (GPU's), Intel Xeon Phis, and multicore CPUs. [ABSTRACT FROM AUTHOR]

The turbulent fluxes across the ocean/atmosphere interface represent one of the principal driving forces of the global atmospheric and oceanic circulation. Despite decades of effort and improvements, representation of these fluxes still presents a challenge due to the small-scale acting turbulent processes compared to the resolved scales of the models. Beyond this subgrid parameterization issue, a comprehensive understanding of the impact of air-sea interactions on the climate system is still lacking. In this paper we investigates the large-scale impacts of the transfer coefficient used to compute turbulent heat fluxes with the IPSL-CM4 climate model in which the surface bulk formula is modified. Analyzing both atmosphere and coupled ocean-atmosphere general circulation model (AGCM, OAGCM) simulations allows us to study the direct effect and the mechanisms of adjustment to this modification. We focus on the representation of latent heat flux in the tropics. We show that the heat transfer coefficients are highly similar for a given parameterization between AGCM and OAGCM simulations. Although the same areas are impacted in both kind of simulations, the differences in surface heat fluxes are substantial. A regional modification of heat transfer coefficient has more impact than uniform modification in AGCM simulations while in OAGCM simulations, the opposite is observed. By studying the global energetics and the atmospheric circulation response to the modification, we highlight the role of the ocean in dampening a large part of the disturbance. Modification of the heat exchange coefficient modifies the way the coupled system works due to the link between atmospheric circulation and SST, and the different feedbacks between ocean and atmosphere. The adjustment that takes place implies a balance of net incoming solar radiation that is the same in all simulations. As there is no change in model physics other than drag coefficient, we obtain similar latent heat flux between coupled simulations with different atmospheric circulations. Finally, we analyze the impact of model tuning and show that it can offset part of the feedbacks. [ABSTRACT FROM AUTHOR]

Abstract The impact of both climate change and climate variability on the supply of intermittent renewable energy sources (I-RES) in Europe are assessed based on global climate model simulations. The main driver of climate variability over Europe is the North Atlantic Oscillation (NAO) in winter and its equivalent in summer (sNAO) which determine to a large extent the atmospheric circulation in Europe. Four climate scenarios are constructed distinguished by a moderate and strong increase of the average global surface temperature, and a positive and negative phase of the atmospheric variability over the North Atlantic and Europe. This spans a framework which combines the effects of both climate change and climate variability. Using a 2050 distribution of PV panels and wind turbines, we found that although climate change is likely to have significant impact on future I-RES output in Europe, its effects, especially for wind power, are outweighed by the high and strongly variable impact of the NAO/sNAO phases. Variability in the large-scale atmospheric circulation is able to induce median I-RES yield differences of 20–30% for high wind potential regions. Due to the NAO variability also months were identified with persistent calm conditions over Europe linked to the inflow of frigid arctic air resulting in some regions in a decrease in wind power of up to 75%a accompanied with an increase in heating degree days of up to 30%. The results of the study imply that if requirements for the power system including back up capacity take into account the weather variability, the power system can also cope with the climate change impacts. Highlights • The impacts of climate change and climate variability on I-RES are assessed in a common framework. • Variability in the dominant mode of atmospheric variability over Europe and the North Atlantic dominates the climate change signal. • Variability in the large-scale atmospheric circulation is able to induce median I-RES yield differences of 20–30% for high wind potential regions. • Due to the NAO variability also months were identified with persistent calm conditions over Europe linked to the inflow of frigid arctic air resulting in some regions in a decrease in wind power of up to 75%a accompanied with an increase in heating degree days of up to 30%. [ABSTRACT FROM AUTHOR]

New pollen data from Omani mangroves (Kwar-al-Jaramah [22.49° N - 59.76° E] and Filim [20.61° N - 58.17° E]), in addition to previously published paleohydrological records from Southern Arabia improve our understanding of the timing and amplitude of the southward retreat of the Indian monsoon influence in Southern Arabia along a north-south transect. Comparison with simulations performed with the IPSL climate model, considering both snapshot experiments and transient simulations from 6000 cal yr BP to the present, confirm the latitudinally time-transgressive nature of the humid-arid transition at the end of the Holocene Humid Period. This occurred in two steps, respectively dated at around 5000 and 2700 cal yr BP. At around 5000 cal yr BP, the southward ITCZ shift was orbitally-driven and led to the abrupt aridification at Kwar-al-Jaramah and the progressive increase of dryness at Filim as the mean position of the ITCZ was centered ca 22.30°N. At 2700 cal yr BP, aridity was fully in place over all of southern Arabia due to increased climate variability. More intense rainy events during the last millennium, however, may have contributed to the discrete hydrological improvement without any impact on the regional vegetation which has remained desert to the present day. [ABSTRACT FROM AUTHOR]

Effects of climate change on agriculture are particularly significant in undeveloped and developing countries (such as Serbia), due to difficult economic situation and low investments in production improvement. A detailed study of current and future state of climate is the key stone for cost-effective and sustainable system of adaptation measures to climate change in the region such as Vojvodina, which is the most important agricultural part of Serbia. This article presents a detailed comparative analysis of the previous (1985-2005) and future (until 2040 and 2080) state of climate in Vojvodina region and its impact on the growing conditions of certain field crops. Data on expected climate conditions in 2040 and 2080 at six selected sites were obtained by applying statistical downscaling technique on outputs used from the three climate models (ECHAM5, HadCM3, NCAR-PCM). The expected changes in winter wheat yield were calculated using the crop model SIRIUS and by taking into account the assumed changes in CO2 concentration in the atmosphere. Adequate adaptation measures are proposed based on the obtained results.

ABSTRACT Developing high-quality long-term data sets at uniform space-time resolution is essential for improved climate studies. This article processes the outputs from two global and regional climate models, the Community Climate System Model ( CCSM3) and the Regional Climate Model driven by the Hadley Centre Coupled Model ( RegCM3). The results are bias-corrected time series of atmospheric variables corresponding to Intergovernmental Panel on Climate Change ( IPCC's) historical ( 20C3M) and future ( A2) climate scenarios over the Amazon Basin. We use a series of simple but effective interpolation approaches to produce hourly climate data sets at 1° by 1° grid cells. A quantile-based mapping approach is used to reduce the biases of temperature and precipitation in CCSM3 and RegCM3. Adjustments are also made on specific humidity and downwelling longwave radiation to avoid inconsistency between those variables and bias-corrected temperature values. We also interpolated an already bias-corrected Parallel Climate Model data set ( PCM1) from 3-hourly to the hourly resolution. The final climate data sets can be used as forcing of ecosystem and hydrologic models to study climate changes and impact assessments over the Amazon Basin. [ABSTRACT FROM AUTHOR]

Species diversity and how it is structured on a continental scale is influenced by stochastic, ecological, and evolutionary driving forces, but hypotheses on determining factors have been mainly examined for terrestrial and marine organisms. The extant diversity of African freshwater mollusks is in general well assessed to facilitate conservation strategies and because of the medical importance of several taxa as intermediate hosts for tropical parasites. This historical accumulation of knowledge has, however, not resulted in substantial macroecological studies on the spatial distribution of freshwater mollusks. Here, we use continental distribution data and a recently developed method of random and cohesive allocation of species distribution ranges to test the relative importance of various factors in shaping species richness of Bivalvia and Gastropoda. We show that the mid-domain effect, that is, a hump-shaped richness gradient in a geographically bounded system despite the absence of environmental gradients, plays a minor role in determining species richness of freshwater mollusks in sub-Saharan Africa. The western branch of the East African Rift System was included as dispersal barrier in richness models, but these simulation results did not fit observed diversity patterns significantly better than models where this effect was not included, which suggests that the rift has played a more complex role in generating diversity patterns. Present-day precipitation and temperature explain richness patterns better than Eemian climatic condition. Therefore, the availability of water and energy for primary productivity during the past does not influence current species richness patterns much, and observed diversity patterns appear to be in equilibrium with contemporary climate. The availability of surface waters was the best predictor of bivalve and gastropod richness. Our data indicate that habitat diversity causes the observed species-area relationship, and hence, that environmental heterogeneity is a principal driver of freshwater mollusk richness on a continental scale. [ABSTRACT FROM AUTHOR]

Summary Long-term changes of the Asian summer monsoon water vapor transport play a pivotal role in the variability of monsoon precipitation. Paleo-climate simulations have shown that there is an important monsoon vapor transport channel in western China. Previous studies mostly focused on the correlation between monsoon precipitation and intensity. Little research has been done on the verification of the water vapor channel. Compared with speleothem and lacustrine systems, the hydrological cycle of land surface sediments is more directly related to the monsoon water vapor. In this study, we used carbonate δ 18 O and organic matter δ 13 C of the surface eolian sediments from the piedmont of the northern Qilian Mountains to verify the monsoon water vapor on the Holocene millennial-scale. Two surface sedimentary sections were selected to study paleo-monsoon water vapor transport. Proxy data, including carbonate δ 18 O and organic matter δ 13 C of surface eolian sediments, as well as total organic matter and carbonate content were obtained from the two eolian sections. We also synthesized transient simulations of the CCSM3 and the Kiel climate models. The PMIP 3.0 project and TRACE isotopic simulations were also compared with the reconstructed monsoon water vapor transport. Our findings indicate that the strength of the Holocene Asian summer monsoon is consistent with the water vapor transport in western China that has significant impacts to long-term monsoon precipitation in northern China. This study verifies a significant millennial-scale correlation between the monsoon strength and monsoon water vapor transport intensity along the eastern Qinghai–Tibet Plateau. [ABSTRACT FROM AUTHOR]