Search

In order to identify the most relevant environmental parameters that regulate flowering time of bulbous perennials, first flowering dates of 329 taxa over 33 yr are correlated with monthly and daily mean values of 16 environmental parameters (such as insolation, precipitation, temperature, soil water content, etc.) spanning at least 1 yr back from flowering. A machine learning algorithm is deployed to identify the best explanatory parameters because the problem is strongly prone to overfitting for traditional methods: if the number of parameters is the same or greater than the number of observations, then a linear model can perfectly fit the dependent variable (observations). Surprisingly, the best proxy of flowering date fluctuations is the daily snow depth anomaly, which cannot be a signal itself, however it should be related to some integrated temperature signal. Moreover, daily snow depth anomaly as proxy performs much better than mean soil temperature preceding the flowering, the best monthly explanatory parameter. Our findings support the existence of complicated temperature sensing mechanisms operating on different timescales, which is a prerequisite to precisely observe the length and severity of the winter season and translate for example, 'lack of snow' information to meaningful internal signals related to phenophases., (©2020 The Authors. New Phytologist ©2020 New Phytologist Foundation.)

Future flood risk assessment has primarily focused on heavy rainfall as the main driver, with the assumption that projected increases in extreme rain events will lead to subsequent flooding. However, the presence of and changes in vegetation have long been known to influence the relationship between rainfall and runoff. Here, we extract historical (1850–1880) and projected (2070–2100) daily extreme rainfall events, the corresponding runoff, and antecedent conditions simulated in a prominent large Earth system model ensemble to examine the shifting extreme rainfall and runoff relationship. Even with widespread projected increases in the magnitude (78% of the land surface) and number (72%) of extreme rainfall events, we find projected declines in event‐based runoff ratio (runoff/rainfall) for a majority (57%) of the Earth surface. Runoff ratio declines are linked with decreases in antecedent soil water driven by greater transpiration and canopy evaporation (both linked to vegetation greening) compared to areas with runoff ratio increases. Using a machine learning regression tree approach, we find that changes in canopy evaporation is the most important variable related to changes in antecedent soil water content in areas of decreased runoff ratios (with minimal changes in antecedent rainfall) while antecedent ground evaporation is the most important variable in areas of increased runoff ratios. Our results suggest that simulated interactions between vegetation greening, increasing evaporative demand, and antecedent soil drying are projected to diminish runoff associated with extreme rainfall events, with important implications for society. Plain Language Summary: Climate change is leading to increases in the magnitude and number of extreme rainfall events. These increases in extreme rainfall events are often assumed to lead to an increase in extreme flooding events. However, using a climate model ensemble, our results indicate that changes in vegetation and atmospheric water demand may alter the relationship between extreme rainfall and extreme runoff. Notably, for a majority of the Earth surface, we find that projected changes in atmospheric aridity and vegetation lead to drier soil conditions prior to the extreme rainfall event that reduces the amount of hydrologic runoff generated. These findings have important implications for water resources management. Key Points: The number and magnitude of extreme rainfall events are projected to increase throughout the global land surfaceProjected declines in event‐based runoff ratio are found for a majority of the global land surfaceProjected runoff ratio declines are linked to decreased antecedent soil water from changes in individual evapotranspiration components [ABSTRACT FROM AUTHOR]

Drought is a severe disaster, increasingly exacerbated by climate change, and poses significant challenges worldwide, particularly in arid and semi-arid regions like Morocco. This study aims to assess and monitor drought using a multi-index approach to provide a comprehensive understanding of its spatio-temporal dynamics at both meteorological and agricultural levels. The research focuses on the Upper Oum Er Rabia watershed, which spans 35,000 km2 and contributes approximately a quarter of Morocco's renewable water resources. We propose a methodology that combines ERA5 temperature data from remote sensing with ground-based precipitation data to analyze drought characteristics. Three meteorological indices were utilized: the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), and the Reconnaissance Drought Index (RDI). Additionally, three remote-sensing indices were employed to capture agricultural drought: the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), and the Crop Water Stress Index (CWSI), with a total of 528 NDVI and EVI images and 1016 CWSI images generated through Google Earth Engine (GEE), using machine-learning techniques. Trend analyses were conducted to monitor drought patterns spatio-temporally. Our results reveal that the three-month interval is critical for effective drought monitoring and evaluation. Among the indices, SPEI emerged as the most effective for capturing drought in combination with remote-sensing data, while CWSI exhibited the highest correlation with SPEI over the three-month period, outperforming NDVI and EVI. The trend analysis indicates a significant precipitation deficit, alongside increasing trends in temperature and evapotranspiration over both the short and long term. Furthermore, all drought indices (SPI, SPEI, and RDI) demonstrate an intensification of drought conditions. Adaptation strategies are essential for managing water resources in the Upper Oum Er Rabia watershed under these evolving climate conditions. Continuous monitoring of climate variables and drought indices will be crucial for tracking changes and informing future water management strategies. [ABSTRACT FROM AUTHOR]

Despite the strong interest concerning the responsive façades, today there are still few built examples and few tools to assess their benefits due to the complex description of the phenomenon. Energy simulations should consider the interactions between a time-varying environment and an environment-dependent envelope, increasing the intricacy of the problem; moreover, these strong environment–envelope interlinkages increase the importance of the location and climate scenarios considered. The aim of this study is to provide a tool to easily model these phenomena in different geographical and climate contexts. For this purpose, an innovative interactive computational platform (ICP) was developed based on EnergyPlus as a simulation engine, Python as a simulation manager, and Grasshopper as a user interface. Thanks to a single user-friendly environment, the users can simply select the climate scenario, the location, the responsive technology, and its main properties to set and run the dynamic energy simulation. After an overview of the current state of the art, this study provides a description of the structure and workflow adopted for developing this platform and details regarding its functioning and input management. Finally, the platform was tested to run an evolutionary optimization of an electrochromic window control strategy in different climate scenarios. [ABSTRACT FROM AUTHOR]

Regional hydrological sensitivity (i.e., precipitation change per degree local surface warming) contributes substantially to the uncertainty in future precipitation projections over tropical oceans. Here, we investigate the sensitivity of relative precipitation (P*, precipitation divided by the basin average precipitation) to local sea surface temperature (SST) change by dissecting it into three components, namely the sensitivity of P* to relative SST (SSTrel, SST minus the tropical mean SST) changes, the sensitivity of P* to surface convergence changes, and the sensitivity of surface convergence to SST gradient changes. We show that the relationships between P* and SSTrel, and between P*, surface convergence, and SST gradients are largely constant during climate change. This allows us to constrain regional hydrological sensitivity based on present‐day SST‐precipitation relationships. The sensitivity of surface convergence to SST gradient changes is a main source of uncertainty in regional hydrological sensitivity and is likely underestimated in GCMs. Plain Language Summary: Understanding how precipitation will change over tropical oceans is important because these changes influence the atmospheric circulation, which in turn affects the global climate and weather patterns. Climate models disagree on their projections of precipitation changes over tropical oceans in part due to a lack of understanding on how precipitation should respond to a given amount of local surface warming. We find that the sensitivity of precipitation to future changes in local sea surface temperature (which is commonly referred to as regional hydrological sensitivity) largely depends on the present‐day relationship between precipitation and local sea surface temperature, as well as that between precipitation and the spatial gradient in sea surface temperature, and both relationships are observable and thus can serve as constraints. We find that inter‐model differences in regional hydrological sensitivity result primarily from differences in the response of surface winds to sea surface temperature gradient changes. Key Points: Regional hydrological sensitivity is an important source of uncertainty in rainfall projections over tropical oceansRegional hydrological sensitivity can be constrained by components of rainfall‐temperature relationship that stay constant during warmingUncertainty in regional hydrological sensitivity originates largely from surface convergence sensitivity to temperature gradient changes [ABSTRACT FROM AUTHOR]

This study analyzed the change in and mechanisms of summer extreme precipitation in Southwest China (SWC) during 1979–2021. The trend in summer extreme precipitation showed an evident interdecadal mutation in the late 1990s; it decreased during 1979–1996 (P1) and increased during 1997–2021 (P2). It is observed that the moisture flux in SWC is more abundant in P2 than in P1. The South Asian high (SAH) and western Pacific subtropical high (WPSH) contributed to the change in extreme precipitation in SWC. Both the SAH and WPSH weakened in 1979–1996 and enhanced in 1997–2021. The enhanced SAH and WPSH are conducive to forming updrafts in SWC and transporting moisture from the Bay of Bengal (BOB) and South China Sea (SCS) into SWC. Further research found that the causes for the interdecadal variation of the SAH and WPSH are the anomalies of sensible heat flux (SSH) over the Tibetan Plateau (TP) and sea surface temperature (SST) in the tropical western Pacific–Indian Oceans. The SSH is the main energy source of troposphere air and an essential component of the surface heat balance because it can maintain the intensity and influence range of the SAH. The increasing SST stimulated strong upward motion and thus maintained the strength of the WPSH, which also made the WPSH extend westward into mainland China. This study also summarized local human adaptation to climate change. The use of advanced science and technology to improve monitoring and forecasting ability is an important measure for human society to adapt to climate change. At the same time, increasing the participation of individuals and social organizations is also an indispensable way to increase human resilience to climate change. [ABSTRACT FROM AUTHOR]

Tropical Cyclones (TCs) inflict substantial coastal damages, making it pertinent to understand changing storm characteristics in the important nearshore region. Past work examined several aspects of TCs relevant for impacts in coastal regions. However, few studies explored nearshore storm intensification and its response to climate change at the global scale. Here, we address this using a suite of observations and numerical model simulations. Over the historical period 1979–2020, observations reveal a global mean TC intensification rate increase of about 3 kt per 24‐hr in regions close to the coast. Analysis of the observed large‐scale environment shows that stronger decreases in vertical wind shear and larger increases in relative humidity relative to the open oceans are responsible. Further, high‐resolution climate model simulations suggest that nearshore TC intensification will continue to rise under global warming. Idealized numerical experiments with an intermediate complexity model reveal that decreasing shear near coastlines, driven by amplified warming in the upper troposphere and changes in heating patterns, is the major pathway for these projected increases in nearshore TC intensification. Plain Language Summary: Tropical cyclones (TCs) that intensify close to the coast pose a major socio‐economic threat and are a substantial challenge from an operational standpoint. Therefore understanding historical trends in nearshore storm intensification and how they may change in future is of considerable significance. Despite this, few studies examined this key aspect of TCs at the global scale. Here we show, using an analysis of observations and atmospheric reanalyses, that the mean TC intensification rate has increased significantly over the period 1979–2020 primarily aided by increases in relative humidity and decreases in vertical wind shear. Further, high‐resolution climate models, which explicitly resolve TCs, suggest that nearshore TC intensification will continue to increase in future. These increases in coastal TC intensification rates can mainly be attributed to stronger projected decreases in vertical wind shear. To better understand wind shear projections, a suite of idealized numerical experiments with an intermediate complexity model were conducted. The experiments indicate that enhanced warming in the upper‐troposphere and changing heating patterns are likely responsible. Key Points: Tropical cyclone (TC) intensification rates have increased in near coastal regions over the 42‐year period 1979‐2020Increases in relative humidity along with decreases in vertical wind shear are responsibleClimate models project a continued increase in nearshore TC intensification rates with decreasing wind shear playing a crucial role [ABSTRACT FROM AUTHOR]

This article provides high-resolution information on the projected changes in annual extreme rainfall and high- and low-streamflow events over Southeast Asia under extreme climate change. The analysis was performed using the bias-corrected result of the High-Resolution Model Intercomparison Project (HighResMIP) multi-model experiment for the period 1971–2050. Eleven rainfall indices were calculated, along with streamflow simulation using the PCR-GLOBWB hydrological model. The historical period 1981–2010 and the near-future period 2021–2050 were considered for this analysis. Results indicate that, over former mainland Southeast Asia, Myanmar will face more challenges in the near future. The east coast of Myanmar will experience more extreme high-rainfall conditions, while northern Myanmar will have longer dry spells. Over the Indonesian maritime continent, Sumatra and Java will suffer from an increase in dry-spell length of up to 40 %, while the increase in extreme high rainfall will occur over Borneo and mountainous areas in Papua. Based on the streamflow analysis, the impact of climate change is more prominent in a low-flow event than in a high-flow event. The majority of rivers in the central Mekong catchment, Sumatra, Peninsular Malaysia, Borneo, and Java will experience more extreme low-flow events. More extreme dry conditions in the near future are also seen from the increasing probability of future low-flow occurrences, which reaches 101 % and 90 %, on average, over Sumatra and Java, respectively. In addition, based on our results over Java and Sumatra, we found that the changes in extreme high- and low-streamflow events are more pronounced in rivers with steep hydrographs (rivers where flash floods are easily triggered), while rivers with flat hydrographs have a higher risk in terms of the probability of low-flow change. [ABSTRACT FROM AUTHOR]

Atlantic hurricane season length is important for emergency management preparation, motivating the need to understand its variability and change. We investigated the influence of ocean variability on Atlantic hurricane season length in observations and a future climate simulated by the Energy Exascale Earth System Model (E3SM). We found that multiple factors influence hurricane season length, through their influence on season start and end. Warm western subtropical Atlantic sea‐surface temperature anomalies (SSTAs) during boreal spring (before the official hurricane season start) drive early starts to the hurricane season, and vice versa for cool SSTAs. Meanwhile, La Niña in autumn (before the official hurricane season end) drives late ends to the hurricane season, and vice versa for El Niño. E3SM projects a 27‐day increase in future Atlantic hurricane season length given La Niña and warm northern tropical Atlantic SSTAs. This research documents sources of predictability for Atlantic hurricane season length. Plain Language Summary: Atlantic hurricane season length is important for emergency management preparation, motivating the need to understand its variability and change. We investigated the influence of ocean variability on Atlantic hurricane season length in historical observations and a future climate simulated by a global climate model. We found that multiple factors influence Atlantic hurricane season length, through their influence on season start and end. Warm sea‐surface temperature anomalies (SSTAs) in the western subtropical Atlantic during boreal spring (before the official hurricane season start) drive early starts to the hurricane season, and vice versa for cool SSTAs. Meanwhile, La Niña events in autumn (before the official hurricane season ends) drive late ends to the hurricane season, and vice versa for El Niño. The global model projects a 27–41‐day increase in future Atlantic hurricane season length. This research documents sources of predictability for Atlantic hurricane season length. Key Points: Multiple oceanic factors influence Atlantic hurricane season length, by influencing the first and last Tropical Storm of the seasonA warm western subtropical Atlantic ocean in boreal spring drives early hurricane season starts; La Niña in autumn drives late season endsFuture Atlantic hurricane season length increases by 27 days in Energy Exascale Earth System Model simulations given La Niña and a positive Atlantic Meridional Mode [ABSTRACT FROM AUTHOR]

Theory suggests that the response time of alluvial channel long-profiles to perturbations in climate is related to the magnitude of the forcing and the length of the system. Shorter systems may record a higher frequency of forcing compared to longer systems. Empirical field evidence that system length plays a role in the climate periodicity preserved within the sedimentary record is, however, sparse. The Toro Basin in the Eastern Cordillera of NW Argentina provides an opportunity to test these theoretical relationships as this single source-to-sink system contains a range of sediment deposits, located at varying distances from the source. A suite of eight alluvial fan deposits is preserved along the western flanks of the Sierra de Pascha. Farther downstream, a flight of cut-and-fill terraces have been linked to eccentricity-driven (100-kyr) climate cycles since ca. 500 ka. We applied cosmogenic radionuclide (10Be) exposure dating to the fan surfaces to explore (1) how channel responses to external perturbations may or may not propagate downstream, and (2) the differences in landscape response to forcing frequency as a function of channel length. We identified two generations of fan surfaces: the first (G1) records surface activity and abandonment between ca. 800 and 500 ka and the second (G2) within the last 100 kyr. G1 fans record a prolonged phase of net incision, which has been recognised throughout the Central Andes, and was likely triggered by enhanced 100-kyr global glacial cycles following the Mid-Pleistocene Transition. Relative fan surface stability followed, while 100-kyr cut-and-fill cycles occurred downstream, suggesting a disconnect in behaviour between the two channel reaches. G2 fans record higher frequency climate forcing, possibly the result of precessional forcing of climate (ca. 21/40-kyr timescales). The lack of a high-frequency signal farther downstream provides field support for theoretical predictions of a filtering of high-frequency climate forcing with increasing channel length. We show that multiple climate periodicities can be preserved within the sedimentary record of a single basin. Differences in the timing of alluvial fan and fluvial terrace development in the Toro Basin appears to be associated with how channel length affects fluvial response times to climate forcing as well as local controls on net incision, such as tectonic deformation. [ABSTRACT FROM AUTHOR]

Recent years were characterized by spatially co‐occurring hot and wet extremes around the globe, raising questions about the contribution of human‐induced global warming to the changing likelihoods of such extreme years. To characterize spatially co‐occurring extremes we investigate recent trends in global and regional land area that is concurrently affected by hot or wet annual maxima taking observational uncertainty into account. Observed trends in the land area affected by extreme events are assessed in the context of Earth System Model (ESM) simulations for present‐day and early‐industrial climate conditions in a detection and attribution setting. We compare different reanalysis and station‐based observational products to account for observational data uncertainty. At the global scale, trends of spatially co‐occurring hot or wet annual maxima in all observational products can be explained by ESM simulations driven by historical radiative forcing that accounts for human‐induced changes in the composition of the atmosphere but cannot be explained by ESM simulations that account for an early‐industrial radiative forcing. At the regional scale, trends in spatially co‐occurring hot annual maxima are in general coherent among observational products and can in most cases be attributed to human influence on the climate system. Trends in spatially co‐occurring wet annual maxima show differences in some regions, highlighting the importance of a multi‐dataset approach to overcome observational product dependencies. Despite observational uncertainty, we find robust detection and attribution results for many regions. These results can complement previous assessments on regional exposure to hot and wet events from the new IPCC AR6 report. Plain Language Summary: Recent years were characterized by spatially co‐occurring hot and wet extremes around the globe, leading to questions about the contribution of human‐induced climate change to the occurrence of such extreme years. In this study, we investigate trends in the global and regional land area that is concurrently affected by hot or wet annual maxima. Due to observational uncertainties, we investigate different observation‐based data products for temperature and rainfall. By comparing observational trends in the land area affected by extreme events to respective trends from Earth System Model ensemble simulations accounting for climate conditions of the past decades and early‐industrial climate conditions, we can evaluate their attribution to human‐induced climate change. On the global scale, observed trends of spatially co‐occurring hot or wet annual maxima cannot be simulated by climate models when considering early‐industrial climate conditions, but are captured by climate models considering recent climate conditions. This holds also true for the detection and attribution of regional trends in concurrent land area affected by hot annual maxima. Observational products agree in many regions on the detection and attribution of regional trends in concurrent land area affected by wet annual maxima, but also disagree in some regions. Key Points: Global and regional trends of spatially concurrent hot or wet annual maxima can be attributed to human‐induced climate changeIn some regions observational products show inconsistencies in the sign of detectable trends in concurrent wet annual maximaLarge regional differences in spatial exposure and steady increase in concurrent land area affected by hot or wet annual maxima is detected [ABSTRACT FROM AUTHOR]

The Rocky Mountain Population (RMP) of greater sandhill cranes uses a key stopover area, the San Luis Valley (SLV) in Colorado. Parameters of migration phenology can differ between autumn and spring and are affected by weather and environmental factors. We hypothesized that sandhill cranes in the SLV would have a longer stopover duration in autumn than in spring, and that wind assistance, crosswinds, temperature change, barometric air pressure, and surface water area would influence persistence probability. We used data from sandhill cranes fitted with transmitters that spanned autumn and spring, 2015-2022. We used an open robust design mark-recapture model to estimate stopover duration, arrival probability, and persistence probability. We examined the effects of weather and surface water on the persistence probability for 106 sandhill cranes in the SLV. Stopover duration was longer in autumn than in spring and had higher variability across years. Arrival probability to the SLV peaked on 13 October in autumn and 21 February in spring. Persistence probability declined around mid-December in autumn and mid-March in spring. We found that several weather covariates influenced persistence in both seasons. In autumn, sandhill cranes departed the SLV with higher tailwinds, lower crosswinds, and higher surface water availability. In spring, sandhill cranes departed the SLV with lower crosswinds and higher barometric air pressure at the surface and higher wind speeds at altitudes of about 3,000 m. The effect of wind speed was stronger later in the spring. Given the lower variability of arrival and persistence probability and shorter stopover duration in spring compared to autumn, we suspect that RMP sandhill cranes are using a time-minimization strategy during spring. However, given the use of supportive winds and weather conditions ideal for soaring, RMP sandhill cranes appear to be using strategies that save energy in both seasons. Our study identifies the optimal timing of water management and surveys for RMP sandhill cranes and confirms that weather influences their persistence. Understanding differences in migration patterns between seasons and the factors that influence persistence at stopover sites will also be important for anticipating phenological impacts from climate change and land use alterations. [ABSTRACT FROM AUTHOR]

In recent decades, rise of sea surface temperature (SST) in the Kuroshio region of the East China Sea (ECS), which is associated with global warming, has attracted considerable attention. Despite its relevance to air‐sea interaction phenomena, the atmospheric consequences of this SST increase remain largely unexplored. Using the ERA5 reanalysis data set in conjunction with a moisture budget analysis, we found that during 1979–2022, warming in the ECS‐Kuroshio has contributed to the intensification of the East Asian Meiyu‐Baiu rainband in June. This intensification is attributed to augmented wind convergence in the low‐level free troposphere (950–700 hPa). Importantly, the atmospheric responses to ECS‐Kuroshio warming penetrated the deep troposphere (to approximately 300 hPa), suggesting an enhancement of deep convection. Furthermore, ECS‐Kuroshio warming likely strengthened the overlying atmospheric low pressure, resulting in wind convergence enhancement. The findings clarified the important role of the ECS‐Kuroshio in driving East Asian climate change amid global warming. Plain Language Summary: In response to global warming, East Asian summer precipitation is increasing along with an increase in extreme precipitation events, which poses a significant threat to agriculture and economic development. Understanding the mechanisms underlying the increased precipitation trend in East Asia is crucial for sustainable human development in this region. The findings of this study revealed that East Asian precipitation induced by the Meiyu‐Baiu rainband has intensified continuously during the past four decades, particularly in the marine areas around the East China Sea (ECS) and the south of Japan. We further established that the continuous increase in sea surface temperature over the Kuroshio in the ECS, which was related to global warming, strengthened the atmospheric low‐pressure system overlying the current, contributing to an increase in rainfall around the ECS. The findings of this study highlighted the important role of the Kuroshio Current in influencing climate change in East Asia. Key Points: The Meiyu‐Baiu rainband in June intensified over the marine areas around the Kuroshio and south of Japan during 1979–2022The intensified Meiyu‐Baiu rainband was caused mainly by the wind convergence accompanied by enhanced deep convectionKuroshio warming in the East China Sea likely intensified the Meiyu‐Baiu rainband by a pressure adjustment mechanism [ABSTRACT FROM AUTHOR]

Terrestrial carbon fluxes are crucial to the global carbon cycle. Quantification of terrestrial carbon fluxes over the Tibetan Plateau (TP) has considerable uncertainties due to the unique ecosystem and climate and scarce flux observations. This study evaluated our recent improvement of terrestrial flux parameterization in the weather research and forecasting model coupled with the vegetation photosynthesis and respiration model (WRF-VPRM) in terms of reproducing observed net ecosystem exchange (NEE), gross ecosystem exchange (GEE), and ecosystem respiration (ER) over the TP. The improvement of VPRM relative to the officially released version considers the impact of water stress on terrestrial fluxes, making it superior to the officially released model due to its reductions in bias, root mean square error (RMSE), and ratio of standard deviation (RSD) of NEE to 0.850 μmol·m−2·s−1, 0.315 μmol·m−2·s−1, and 0.001, respectively. The improved VPRM also affects GEE simulation, increasing its RSD to 0.467 and decreasing its bias and RMSE by 1.175 and 0.324 μmol·m−2·s−1, respectively. Furthermore, bias and RMSE for ER were lowered to −0.417 and 0.954 μmol·m−2·s−1, with a corresponding increase in RSD by 0.6. The improved WRF-VPRM simulation indicates that eastward winds drive the transfer of lower CO2 concentrations from the eastern to the central and western TP and the influx of low-concentration CO2 inhibits biospheric CO2 uptake. The use of an improved WRF-VPRM in this study helps to reduce errors, improve our understanding of the role of carbon flux cycle over the TP, and ultimately reduce uncertainty in the carbon flux budget. [ABSTRACT FROM AUTHOR]

Cloud and convection strongly modulate atmospheric energy budgets, but the latter's responses often vary across timescales because of complex interactions between fast and slow processes. Here, based on atmospheric model simulations at intermediate state between weather and climate timescales, we investigate how the responses in the global‐mean atmospheric energy budgets evolve over time after simultaneously perturbing various cloud‐scale processes. We find that the responses in radiative and sensible heat fluxes converge much more rapidly compared to condensation heat associated with precipitation, which is attributed to the compensating feedback effects of precipitation on longwave cooling and shortwave heating. Because of energy conservation, uncertainty in long‐term precipitation simulations can be substantially reduced by constraining the fast processes of radiative and sensible heat fluxes. These findings can help economize on computational resources required for model tuning and serve as a crucial link between the convective‐scale and equilibrium‐state outcomes within the model. Plain Language Summary: Cloud and convection occurring on short timescales can interact with processes that require much longer time to respond to small perturbations in the climate system, making it extremely difficult to understand the sources of uncertainty in climate modeling. Here, with an atmospheric model, we investigate how the simulated global‐mean atmospheric energy budgets gradually evolve over time when various cloud‐scale processes are simultaneously perturbed. We find that the responses in radiative and sensible heat fluxes converge much more rapidly compared to condensation heat associated with precipitation. As a result, a substantial reduction in uncertainty regarding long‐term precipitation simulations can be achieved by constraining the radiative and sensible heat fluxes at shorter timescales, in accordance with energy conservation principles. Our results can help modelers economize on computational resources required for model tuning and serve as a crucial link between the model physics parameterization community and the model application community. Key Points: The responses in radiative and sensible heat fluxes converge much more rapidly compared to precipitationThe rapid radiative response is attributed to the compensating feedback effects of precipitation on longwave cooling and shortwave heatingConstraining the fast processes of radiative and sensible heat fluxes can alleviate uncertainty in long‐term precipitation simulations [ABSTRACT FROM AUTHOR]

Quantification of land surface–atmosphere fluxes of carbon dioxide (CO 2) and their trends and uncertainties is essential for monitoring progress of the EU27 + UK bloc as it strives to meet ambitious targets determined by both international agreements and internal regulation. This study provides a consolidated synthesis of fossil sources (CO 2 fossil) and natural (including formally managed ecosystems) sources and sinks over land (CO 2 land) using bottom-up (BU) and top-down (TD) approaches for the European Union and United Kingdom (EU27 + UK), updating earlier syntheses (Petrescu et al., 2020, 2021). Given the wide scope of the work and the variety of approaches involved, this study aims to answer essential questions identified in the previous syntheses and understand the differences between datasets, particularly for poorly characterized fluxes from managed and unmanaged ecosystems. The work integrates updated emission inventory data, process-based model results, data-driven categorical model results, and inverse modeling estimates, extending the previous period 1990–2018 to the year 2020 to the extent possible. BU and TD products are compared with the European national greenhouse gas inventory (NGHGI) reported by parties including the year 2019 under the United Nations Framework Convention on Climate Change (UNFCCC). The uncertainties of the EU27 + UK NGHGI were evaluated using the standard deviation reported by the EU member states following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), originate from within-model uncertainty related to parameterization as well as structural differences between models. By comparing the NGHGI with other approaches, key sources of differences between estimates arise primarily in activities. System boundaries and emission categories create differences in CO 2 fossil datasets, while different land use definitions for reporting emissions from land use, land use change, and forestry (LULUCF) activities result in differences for CO 2 land. The latter has important consequences for atmospheric inversions, leading to inversions reporting stronger sinks in vegetation and soils than are reported by the NGHGI. For CO 2 fossil emissions, after harmonizing estimates based on common activities and selecting the most recent year available for all datasets, the UNFCCC NGHGI for the EU27 + UK accounts for 926 ± 13 Tg C yr -1 , while eight other BU sources report a mean value of 948 [ 937,961 ] Tg C yr -1 (25th, 75th percentiles). The sole top-down inversion of fossil emissions currently available accounts for 875 Tg C in this same year, a value outside the uncertainty of both the NGHGI and bottom-up ensemble estimates and for which uncertainty estimates are not currently available. For the net CO 2 land fluxes, during the most recent 5-year period including the NGHGI estimates, the NGHGI accounted for - 91 ± 32 Tg C yr -1 , while six other BU approaches reported a mean sink of - 62 [ -117,-49 ] Tg C yr -1 , and a 15-member ensemble of dynamic global vegetation models (DGVMs) reported - 69 [ -152,-5 ] Tg C yr -1. The 5-year mean of three TD regional ensembles combined with one non-ensemble inversion of - 73 Tg C yr -1 has a slightly smaller spread (0th–100th percentiles of [ -135,+45 ] Tg C yr -1), and it was calculated after removing net land–atmosphere CO 2 fluxes caused by lateral transport of carbon (crop trade, wood trade, river transport, and net uptake from inland water bodies), resulting in increased agreement with the NGHGI and bottom-up approaches. Results at the category level (Forest Land, Cropland, Grassland) generally show good agreement between the NGHGI and category-specific models, but results for DGVMs are mixed. Overall, for both CO 2 fossil and net CO 2 land fluxes, we find that current independent approaches are consistent with the NGHGI at the scale of the EU27 + UK. We conclude that CO 2 emissions from fossil sources have decreased over the past 30 years in the EU27 + UK, while land fluxes are relatively stable: positive or negative trends larger (smaller) than 0.07 (- 0.61) Tg C yr -2 can be ruled out for the NGHGI. In addition, a gap on the order of 1000 Tg C yr -1 between CO 2 fossil emissions and net CO 2 uptake by the land exists regardless of the type of approach (NGHGI, TD, BU), falling well outside all available estimates of uncertainties. However, uncertainties in top-down approaches to estimate CO 2 fossil emissions remain uncharacterized and are likely substantial, in addition to known uncertainties in top-down estimates of the land fluxes. The data used to plot the figures are available at 10.5281/zenodo.8148461 (McGrath et al., 2023). [ABSTRACT FROM AUTHOR]

During the summer–autumn (July–October, Jul–Oct) period of 2022, the Yangtze River Basin (YRB) of China experienced an extreme meteorological drought, with Jul–Oct containing the lowest precipitation in the YRB since 1979. The possible causes of this drought were analyzed in the present study. Surprisingly, unlike many previous drought events, we found that this event was not characterized by a consistent atmospheric circulation anomaly regime throughout the entire drought period. Instead, two distinct circulation patterns were responsible for the precipitation deficit in two different stages, i.e., July–August (Jul–Aug) and September–October (Sep–Oct). In Jul–Aug, the YRB precipitation deficit primarily resulted from an intensified and northward-shifted East Asian subtropical jet, which allowed for an extremely northwestward shift of western Pacific subtropical highs, leading to an anomalous descending motion. Such circulation patterns in Jul–Aug originated from the dispersion of Rossby waves upstream from central Asia and Europe. Meanwhile, in Sep–Oct, the YRB drought was primarily attributed to a low-level cyclonic anomaly over the western North Pacific, which was closely associated with frequent tropical cyclones traveling across this region. Observational analysis and a model ensemble hindcast suggest that atmospheric internal variabilities dominated the drought process, while the SSTA, particularly the La Niña event, played a limited role. Therefore, this long-lasting extreme YRB meteorological drought was largely driven by the relay effects of different atmospheric internal variabilities in Jul–Aug and Sep–Oct, respectively, which shows limited model predictability and poses a great challenge for operational climate predictions. [ABSTRACT FROM AUTHOR]

Earth system models (ESMs) can help to improve the understanding of climate-induced cryospheric–hydrological impacts in complex mountain regions, such as High Mountain Asia (HMA). Coarse ESM grids, however, have difficulties in representing cryospheric–hydrological processes that vary over short distances in complex mountainous environments. Variable-resolution (VR) ESMs can help to overcome these limitations through targeted grid refinement. This study investigates the ability of the VR Community Earth System Model (VR-CESM) to simulate cryospheric–hydrological variables such as the glacier surface mass balance (SMB) over HMA. To this end, a new VR grid is generated, with a regional grid refinement up to 7 km over HMA. Two coupled atmosphere–land simulations are run for the period 1979–1998. The second simulation is performed with an updated glacier cover dataset and includes snow and glacier model modifications. Comparisons are made to gridded outputs derived from a globally uniform 1 ∘ CESM grid, observation-, reanalysis-, and satellite-based datasets, and a glacier model forced by a regional climate model (RCM). Climatological biases are generally reduced compared to the coarse-resolution CESM grid, but the glacier SMB is too negative relative to observation-based glaciological and geodetic mass balances, as well as the RCM-forced glacier model output. In the second simulation, the SMB is improved but is still underestimated due to cloud cover and temperature biases, missing model physics, and incomplete land–atmosphere coupling. The outcomes suggest that VR-CESM could be a useful tool to simulate cryospheric–hydrological variables and to study climate change in mountainous environments, but further developments are needed to better simulate the SMB of mountain glaciers. [ABSTRACT FROM AUTHOR]

The unexpected emergence of the 2019 coronavirus disease (COVID‐19) pandemic resulted in anthropogenic emissions changes, which have significant consequences for the regional and global climate. However, the long‐term impacts of emission reductions and recovery scenarios on regional climate change in China remain unknown. We use the COVID Model Intercomparison Project (CovidMIP) simulations to project climate change in China in the mid‐21st century under four recovery emission pathways in the post‐COVID era. We found that the temporary emission cut during the COVID‐19 lockdown under the 2‐year‐blip scenario has limited long‐term impact on regional climate change. Anthropogenic emissions are reduced under moderate and stringent greening recovery pathways, leading to reductions of 0.17 ± 0.09°C and 0.35 ± 0.10°C in surface air temperature (SAT) relative to the SSP2‐4.5 baseline in China, respectively. Although the reduction of greenhouse gas emissions decreases SAT, the simultaneous enhanced surface solar radiation due to reduced aerosol concentrations partly offsets the GHG‐induced cooling. Additionally, the weakened aerosol‐cloud interactions associated with reduced aerosols increase the national precipitation by 1.30 ± 0.88 mm month−1 (1.63 ± 1.11%) and 1.91 ± 0.60 mm month−1 (2.39 ± 0.77%) in two green scenarios. As a comparison, regional precipitation decreases by 0.40 ± 0.53 mm month−1 (0.50 ± 0.66%) in the fossil‐based recovery scenario. Therefore, long‐term climate change is more dominated by the emission recovery pathways rather than short‐term emission reduction during the pandemic for China. Plain Language Summary: The COVID‐19 pandemic led to reductions in CO2 and aerosol emissions globally during 2020. This has substantial implications for climate at both the regional and global scales. Here, we use the simulations from CovidMIP to project climate change in China by the midcentury under different COVID‐19 recovery emission pathways. We find that the short‐term emission reduction during the pandemic has limited impacts on the long‐term climate change, which is more dominated by the emission recovery after the pandemic. Under the greening recovery pathway similar to carbon neutrality, reduced CO2 mitigates warming while reduced aerosols increase precipitation in China compared to the baseline climate. Key Points: Short‐term emission reduction during the pandemic has limited impacts on the long‐term climate changeThe cooling from reduced greenhouse gas is partly offset by the warming from reduced aerosols under the greening recovery pathwaysWeakened aerosol‐cloud interactions increase precipitation in China under a carbon neutral pathway [ABSTRACT FROM AUTHOR]

General circulation models (GCMs) are limited in their representation of regional climates. Thus, the selection and downscaling of the most suitable models for regional/local studies are crucial prior to climate change impact studies. This study addressed the selection and downscaling of GCM models from 100 ensembles each from the Shared Socioeconomic Pathways (SSP4.5 and SSP8.5) emission scenarios from the CMIP6 archive using an advanced envelop-based selection approach for Northern Nigeria. We used 2021–2050 as the short-term and 2051–2080 as the long-term study periods. The selection approach revealed that CanESM5 models are more skilful in simulating the warm and wet season, while HadGEM3-GC31-LL in the warm and dry season, whereas MPI-ESM1-2-HR and MPI-ESM1-2-LR are skilful in the cold and dry season. Furthermore, we downscaled the three most skilled models from each season and calculated their spatial averages over Northern Nigeria to provide a more precise illustration of the temperature and precipitation patterns. Under the SSP4.5 emission scenario, the ensemble mean of the downscaled and the (raw) GCMs projected about 13% (8–17%) and 20% (11–35%) increase in average annual precipitation during the short-term and long-term periods, respectively. Similarly, for SSP8.5, the models projected about 23% (5–38%) and 41% (29–60%) increase in the average annual precipitation during short-term and long-term periods respectively. For the temperature, under SSP4.5, the GCMs projected a 1.1 °C (0.26–1.6 °C) and 2.5 °C (0.87–4.04 °C) increase in average annual temperature for short-term and long-term periods respectively. Similarly, an increase of 1.2 °C (0.01–1.78 °C) and 2.7 °C (0.01–4.3 °C) is projected for SSP8.5 during the short-term and long-term periods respectively. These findings can be used for climate impact studies in the region. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) is critical to the terrestrial ecosystem carbon cycle and global climate change. The carbon cycle model coupled with microbial processes can improve the projection of SOC. However, it remains unclear whether microbial models are superior to multiple terrestrial carbon cycle models and how large the simulation uncertainties of SOC are. Therefore, we simulate the spatial patterns of global SOC by the MIMICS (explicit nonlinear microbial carbon cycle model) and the DCC (implicit linear carbon cycle model), compare the SOC with that of the CMIP6 MME (multi‐model ensemble) and the observation to obtain the uncertainties of SOC, and analyze the sensitivity of the parameters in the two models. The results show that the SOC simulated by the MIMICS is 1615.4 ± 54.3 PgC, which is higher than that of the DCC (668.5 ± 102.1 PgC), the CMIP6 MME (1443.7 ± 795.8 PgC), and the observation (1519.1 PgC). The SOC of the DCC and MIMICS are regulated by NPP, and that of DCC is more sensitive to climate, while that of MIMICS is mainly influenced by the Michaelis–Menten equation and microbial carbon use efficiency. We reveal the spatial patterns of uncertainty in global SOC simulated by the explicit and implicit microbial processes of multiple terrestrial carbon cycle models. Unfortunately, neither the DCC, the MIMICS nor the CMIP6 MME simulate SOC satisfactorily, especially in the high latitudes of the Northern Hemisphere, and the simulation of SOC in this region needs to be improved. [ABSTRACT FROM AUTHOR]

Long-term variations in the translation speed of tropical cyclones (TCs) in the South China Sea (SCS) are examined based on five TC datasets from different institutions. TC translation speed during the TC peak season in the SCS shows an evident rhythm of interdecadal change throughout 1977-2020. This interdecadal change in TC translation speed in the SCS can be well reproduced by a newly developed trajectory model. The model results indicate that the interdecadal change in TC translation speed is primarily due to an interdecadal change in the steering flow in the SCS. Such an interdecadal change in the steering flow is closely related to an east-west shift of the subtropical high in the western North Pacific (WNP) ocean basin, which may be driven by the zonal sea surface temperature (SST) gradient between the north Indian (NI) andWNP ocean basins. A new index of the zonal SST gradient is proposed, which is shown to be effective for indicating the interdecadal change in east-west shift of subtropical high, and thus, the TC translation speed in the SCS. [ABSTRACT FROM AUTHOR]

Based on reanalysis datasets and sea‐ice sensitivity experiments, this study has pointed out that the autumn sea ice loss in East Siberian‐Chukchi‐Beaufort (EsCB) Seas significantly increases the frequency of winter extreme low temperature over western‐central China. Autumn sea ice loss warms the troposphere and generates anticyclonic anomaly over the Arctic region 1 month later. Under the effects of synoptic eddy‐mean flow interaction and anomalous upward propagated planetary wave 2, the Arctic anticyclonic anomaly strengthens and develops toward Greenland‐Northern Europe, accompanied by a weakened stratospheric polar vortex. In winter, following intra‐seasonal downward propagation of stratospheric anomalies, the Northern European positive geopotential height anomalies enhance and expand downstream within 7 days, favoring Arctic cold air east of Novaya Zemlya southward (the hyperpolar path) accumulating in Siberia around Lake Baikal. In the subsequent 2–3 days, these cold anomalies rapidly intrude western‐central China and induce abrupt sharp cooling, thus more frequent extreme low temperature there. In contrast, the role of autumn Barents‐Kara (BK) sea ice loss exhibits quite different features, mainly favoring northwestern, northeastern and eastern China to experience increased frequency of extreme low temperature in winter. Plain Language Summary: Arctic sea ice change not only regulates the local ecosystem but extends its influences into mid‐even low‐latitudes through several complicated physical processes. Sea ice variation in EsCB Seas exhibits an increased amplitude and more crucial role in climate change under global warming. The new findings hinted that autumn EsCB sea ice decrease would significantly promote western‐central China to experience more frequent winter extreme low temperature. In responses, an Arctic anticyclonic anomaly occurs 1 month later and develops toward Greenland‐Northern Europe due to synoptic eddy‐mean flow interaction. Enhanced upward propagated planetary wave 2 and associated wave‐mean flow interaction maintains the tropospheric Arctic anomalies and weakens the stratospheric polar vortex. When entering winter, following intra‐seasonal downward propagated stratospheric anomalies, the Northern European anticyclonic anomaly strengthens downstream within 7 days, favoring Arctic cold air east of Novaya Zemlya rapidly invading western‐central China (the hyperpolar path) and sudden sharp cooling. Our results have understood how autumn EsCB sea ice loss contributes to extreme low temperature in China, including possible physical mechanisms and cold air pathways, unlike previous work focusing on BK Seas and winter‐mean temperature change. It provides a new factor and theoretical foundations for predicting winter extreme low temperature. Key Points: Autumn East Siberian‐Chukchi‐Beaufort sea ice loss favors cold air east of Novaya Zemlya invading western‐central China, thus more frequent extreme low temperatureSynoptic eddy‐mean flow interaction and anomalous upward planetary wave 2 provide favorable anticyclonic anomaly for extreme events outburstIntra‐seasonal downward propagated stratospheric anomalies are vital for the Ural anticyclonic anomaly to develop downstream within 7 days [ABSTRACT FROM AUTHOR]

Clear‐air turbulence (CAT) is hazardous to aircraft and is projected to intensify in response to future climate change. However, our understanding of past CAT trends is currently limited, being derived largely from outdated reanalysis data. Here we analyze CAT trends globally during 1979–2020 in a modern reanalysis data set using 21 diagnostics. We find clear evidence of large increases around the midlatitudes at aircraft cruising altitudes. For example, at an average point over the North Atlantic, the total annual duration of light‐or‐greater CAT increased by 17% from 466.5 hr in 1979 to 546.8 hr in 2020, with even larger relative changes for moderate‐or greater CAT (increasing by 37% from 70.0 to 96.1 hr) and severe‐or‐greater CAT (increasing by 55% from 17.7 to 27.4 hr). Similar increases are also found over the continental USA. Our study represents the best evidence yet that CAT has increased over the past four decades. Plain Language Summary: Turbulence is unpleasant to fly through in an aircraft. Strong turbulence can even injure air passengers and flight attendants. An invisible form called clear‐air turbulence (CAT) is predicted to become more frequent because of climate change. Here we analyze modern atmospheric data based on four decades of observations (1979–2020) to investigate whether CAT has already started to increase. We use 21 different turbulence calculations to ensure our results are as reliable as possible. We find clear evidence of large CAT increases in various places around the world at aircraft cruising altitudes since satellites began observing the atmosphere. For example, at a typical point over the North Atlantic, the upward trend is such that the strongest category of CAT was 55% more frequent in 2020 than 1979. Our study represents the best evidence yet that CAT has increased over the past four decades, consistent with the expected effects of climate change. Key Points: Clear‐air turbulence (CAT) diagnosed from reanalysis data has increased over the satellite eraThe increases are largest over the USA and North Atlantic, which are both busy flight regionsSevere‐or‐greater CAT increased the most, becoming 55% more frequent in 2020 than 1979 [ABSTRACT FROM AUTHOR]

Purpose: The sensitivity of wildland plants to temperature can be directly measured using experimental manipulations of temperature in situ. We show that soil surface temperature and plant density (per square meter) have a significant impact on the germination, growth, and phenology of Bromus tectorum L., cheatgrass, a short-statured invasive winter-annual grass, and assess a new experimental temperature manipulation method: the application of black and white gravel to warm and cool the soil surface. Methods: We monitored height, seed production, and phenological responses of cheatgrass, seeded into colored gravel at low and high densities at two sites in the western USA: Boise, ID and Cheyenne, WY. Soil surface temperature and volumetric water content were measured to assess treatment effects on soil surface microclimate. Results: Black gravel increased mean temperatures of the surface soil by 1.6 and 2.6 °C compared to white gravel in Cheyenne and Boise, respectively, causing 21–24 more days with soil temperatures > 0 °C, earlier cheatgrass germination, and up to 2.8-fold increases in cheatgrass height. Higher seeding density of cheatgrass led to 1.4-fold taller plants on black gravel plots at both sites, but not white gravel at the Boise site, indicating a possible thermal benefit or reduction of water demand due to plant clustering in warmer treatments. Conclusions: Manipulating soil-surface albedo altered the soil microclimate and thus growth and phenology of cheatgrass, whose life history and growth form confer a strong dependency on soil-surface conditions. [ABSTRACT FROM AUTHOR]

Climate change is one of the most important challenges of the modern era. The aims of this study were assessed (1) the climatological analysis for two periods: far-past (1979-1998) and near past (1999-2018) over the United Arab Emirates, (2) statistical evaluation of ERA5-reanalysis dataset against climatic historical reference period, and (3) investigate heatwave indices and their characteristics over the UAE from 1979 to 2050 using CORDEX model at RCP4.5 scenarios. Results showed that the effects of climatic changes appeared to be clear on the temperature and precipitation within the UAE. Temperature increased by 1.15 °C between 1979 and 2018, and therefore the annual average rainfall decreased by -81.5 mm within the same time period. Slight difference in temperature between observation and ERA5 clearly shown a strong positive correlation, on the contrary, precipitation is shown significantly high error values because of the plurality of climate and its variability between tropical semi-arid and desert climate. The number, frequency, duration, magnitude and amplitude of heat waves accelerates from the beginning of the study period in 1979 and continues to increase until the end of study at year 2050 in UAE. By studying thermal comfort, it was found that most of the population suffers from thermal discomfort and reaches severe stress in July and August. Two main types of heat wave impacts have so far been underlined: divorce cases and road accidents. However, this list is not exhaustive, as wider social impacts may occur during heat wave events. [ABSTRACT FROM AUTHOR]

In this study, we developed a regional coupled model for the western North Pacific (WNP) and East Asian region. The atmospheric/oceanic component of the coupled model was the Weather Research and Forecasting and the Regional Ocean Modeling System, coupled through the National Center for Atmospheric Research Coupler version 7 (CPL7). An evaluation is provided through the simulation of the climatology and interannual variability of the summer monsoon climate from 1982 to 2015. The coupled model is also compared with a solely atmospheric run, which is driven by the observed sea surface temperature (SST) as the surface boundary. The results show that the coupled model has good capability in modeling the climate in the WNP and East Asian domain, including the climatology of summer precipitation and circulation, the subseasonal (month‐to‐month) variation in the western Pacific subtropical high and associated precipitation, and the seasonal cycle of the East Asian rain belt. One merit of this model is its ability to simulate the northward and eastward shift from early to late summer. With respect to the interannual variability, the model captures the spatial pattern of the leading mode of summer precipitation, with a north–south dipole mode in the studied region. The model also reproduces the larger SST variability in the northern part of this region. The temporal correlation coefficient between the coupled simulation and observation was 0.70 for the precipitation and 0.53 for the SST leading mode. The coupled model also captures the precipitation–SST relationship, which results from reasonably considering the air–sea coupling processes in the coupled run. Plain Language Summary: Due to the resolution of global models is relatively coarse and cannot describe the regional features, especially in the monsoon regions, regional climate model is an essential solution for regional climate simulation and projection. Compared with atmospheric alone model which is driven by prescribed sea surface temperature, regional air‐sea coupled model can describe reasonably the air‐sea coupling processes and has better performance. In this study, an regional coupled model is developed based on the Community Earth System Model coupler version 7 framework. Based on our analysis, the regional coupled model reasonably reproduced most key characteristics in the East Asian monsoon region. In addition to being used in regional climate simulation and projection, it can also be conveniently coupled with global models through the coupler 7. Thus with this useful tool in future we can develop global‐regional two‐way coupling simulation system for climate predictions and projections. Key Points: A regional coupled model is developed for East Asia and western North Pacific region based on Community Earth System Model frameworkClimatology and interannual variability of the summer monsoon climate have been evaluatedThe model can well capture the climatological northward and eastward movements of the western Pacific subtropical high from June to August [ABSTRACT FROM AUTHOR]

Heavy precipitation is a challenging phenomenon with high impact on human lives and infrastructure, and thus a better modelling of its characteristics can improve understanding and simulation at climate timescales. The achievement of convection-permitting modelling (CPM) resolutions (Δx<4 km) has brought relevant advancements in its representation. However, further research is needed on how the very high resolution and switching-off of the convection parameterization affects the representation of processes related to heavy precipitation. In this study, we evaluate reanalysis-driven simulations for the greater Alpine area over the period 2000–2015 and assess the differences in representing heavy precipitation and other model variables in a CPM setup with a grid size of 3 km and a regional climate model (RCM) setup at 25 km resolution using the COSMO-CLM model. We validate our simulations against high-resolution observations (E-OBS (ENSEMBLES observations), HYRAS (Hydrometeorologische Rasterdatensätze), MSWEP (Multi-Source Weighted-Ensemble Precipitation), and UWYO (University of Wyoming)). The study presents a revisited version of the precipitation severity index (PSI) for severe event detection, which is a useful method to detect severe events and is flexible for prioritizing long-lasting events and episodes affecting typically drier areas. Furthermore, we use principal component analysis (PCA) to obtain the main modes of heavy precipitation variance and the associated synoptic weather types (WTs). The PCA showed that four WTs suffice to explain the synoptic situations associated with heavy precipitation in winter, due to stationary fronts and zonal flow regimes. Whereas in summer, five WTs are needed to classify the majority of heavy precipitation events. They are associated with upper-level elongated troughs over western Europe, sometimes evolving into cutoff lows, or with winter-like situations of strong zonal circulation. The results indicate that CPM represents higher precipitation intensities, better rank correlation, better hit rates for extremes detection, and an improved representation of heavy precipitation amount and structure for selected events compared to RCM. However, CPM overestimates grid point precipitation rates, which agrees with findings in past literature. CPM systematically represents more precipitation at the mountain tops. However, the RCMs may show large intensities in other regions. Integrated water vapour and equivalent potential temperature at 850 hPa are systematically larger in RCM compared to CPM in heavy precipitation situations (up to 2 mm and 3 K, respectively) due to wetter mid-level conditions and an intensified latent heat flux over the sea. At the ground level, CPM emits more latent heat than RCM over land (15 W m -2), bringing larger specific humidity north of the Alps (1 g kg -1) and higher CAPE (convective available potential energy) values (100 J kg -1). RCM, on the contrary simulates a wetter surface level over Italy and the Mediterranean Sea. Surface temperatures in RCM are up to 2 ∘ C higher in RCM than in CPM. This causes outgoing longwave radiation to be larger in RCM compared to CPM over those areas (10 W m -2). Our analysis emphasizes the improvements of CPM for heavy precipitation modelling and highlights the differences against RCM that should be considered when using COSMO-CLM climate simulations. [ABSTRACT FROM AUTHOR]

We simulate climate variations in the past 250 million years (Myr), using the fully coupled Community Earth System Model version 1.2.2 (CESM1.2.2) with the Community Atmosphere Model version 4 (CAM4). Three groups of simulations are performed, each including 26 simulations, with a 10‐million‐year interval. The Control group is constrained by paleogeography, increasing solar radiation, and reconstructed global mean surface temperatures (GMSTs) by tuning CO2 concentrations. No ice sheets are prescribed for all simulations except for the pre‐industrial (PI) simulation in which modern geography, ice sheets and vegetation are used. Simulated zonal mean surface temperatures are always higher than those of proxy reconstructions in the tropics, but lower than those of proxy reconstructions at middle latitudes. The relative importance of individual contributing factors for surface temperature variations in the past 250 Myr is diagnosed, using the energy‐balance analysis. Results show that greenhouse gases are the major driver in regulating GMST variations, with a maximum contribution of 12.2°C. Varying surface albedo contributes to GMST variations by 3.3°C. Increasing solar radiation leads to GMST increases by 1.5°C. Cloud radiative effects have relatively weak impacts on GMST variations, less than ±0.8°C. For comparison, two groups of sensitivity simulations are performed. One group has the CO2 concentration fixed at 10 times the PI value, and the other group has fixed CO2 concentration of 10 times the PI value and fixed solar radiation at the present‐day value, showing that varying both paleogeography and solar constant and varying paleogeography alone result in GMST changes by 7.3°C and 5.6°C, respectively. Plain Language Summary: The climate system has experienced drastic changes in the past 250 million years (Myr). A warm climate state was associated with the Pangea supercontinent (∼250 to 200 million years ago [Ma]). Climate became cooler in the middle and late Jurassic (∼174–145 Ma) during the breakup of the supercontinent. It warmed again in the late Cretaceous (∼100–66 Ma) and started cooling in the early Eocene (∼56 Ma) when fragmented continental plates reassembled. In the present study, we simulate climate variations in the past 250 Myr, using a fully coupled atmosphere‐ocean climate model. Three groups of simulations are performed, and each group includes 26 snapshot simulations, with a time interval of 10 million years. The simulation results demonstrate that greenhouse gases are the major driver in regulating global mean surface temperature (GMST) variations, and varying paleogeography also has important impacts on GMST variations through the surface albedo effect. In addition, cloud fraction and its radiative effects vary over different paleogeography and warm‐cool climate states. Key Points: Climate evolution in the past 250 million years is simulated using the fully coupled climate model CESM1.2.2 (CAM4) every 10 million yearsGreenhouse gases are the major factor in regulating surface temperature variations in the past 250 million yearsChanges of continental configurations have significant contributions to surface temperature variations over tectonic timescales [ABSTRACT FROM AUTHOR]

Indian Ocean sea surface temperatures impact precipitation across the basin through coupled ocean‐atmosphere responses to changes in climate. To understand the hydroclimate response over the western Indian Ocean and equatorial east Africa to different forcing mechanisms, we present four new proxy reconstructions from core VM19‐193 (2.98°N, 51.47°E) that span the last 250 ky. Sub‐surface water temperatures (Sub‐T; TEX86) show strong precessional (23 ky) variability that is primarily influenced by maximum incoming solar radiation (insolation) during the Northern Hemisphere spring season, likely indicating that local insolation dominates the upper water column at this tropical location over time. Leaf waxes, on the other hand, reflect two different precipitation signals: δ13Cwax (in phase with boreal fall insolation) is likely reflecting vegetation changes in response to local rainfall over east Africa, whereas δDprecip (primarily driven by boreal summer insolation) represents changes in regional circulation associated with the summer monsoon. Glacial‐interglacial changes in ocean temperatures support glacial shelf exposure over the Maritime Continent in the eastern Indian Ocean and the subsequent weakening of the Indian Walker Circulation as a mechanism driving 100 ky climate variability across the tropical Indo‐Pacific. Additionally, the 100 ky spectral power in δDprecip supports a basin‐wide weakening of summer monsoon circulation in response to glacial climates. Overall, the proxy records from VM19‐193 indicate that both precession and glacial‐interglacial cycles exert control over hydroclimate at this tropical location. Key Points: New multi‐proxy reconstructions from the tropical western Indian Ocean show both precession and glacial‐interglacial variabilityA new precipitation isotope record likely reflects large‐scale Indian summer monsoon circulation changes over timeGlacial‐scale changes in upper water column structure across the Indian Ocean support shelf exposure as a primary hydroclimate influence [ABSTRACT FROM AUTHOR]

African and South American (ASA) wildfires account for more than 70 % of global burned areas and have strong connection to local climate for sub-seasonal to seasonal wildfire dynamics. However, representation of the wildfire–climate relationship remains challenging due to spatiotemporally heterogenous responses of wildfires to climate variability and human influences. Here, we developed an interpretable machine learning (ML) fire model (AttentionFire_v1.0) to resolve the complex controls of climate and human activities on burned areas and to better predict burned areas over ASA regions. Our ML fire model substantially improved predictability of burned areas for both spatial and temporal dynamics compared with five commonly used machine learning models. More importantly, the model revealed strong time-lagged control from climate wetness on the burned areas. The model also predicted that, under a high-emission future climate scenario, the recently observed declines in burned area will reverse in South America in the near future due to climate changes. Our study provides a reliable and interpretable fire model and highlights the importance of lagged wildfire–climate relationships in historical and future predictions. [ABSTRACT FROM AUTHOR]

Comprehensive assessment of climate datasets is important for communicating to stakeholders model projections and associated uncertainties. Uncertainties can arise not only from assumptions and biases within the model but also from external factors such as computational constraint and data processing. To understand sources of uncertainties in global variable-resolution (VR) dynamical downscaling, we produced a regional climate dataset using the Model for Prediction Across Scales dynamical core coupled to the Community Atmosphere Model version 5.4 (CAM-MPAS). This document provides technical details of the model configuration, simulations, computational requirements, post-processing, and data archive of the experimental CAM-MPAS downscaling data. The CAM-MPAS model is configured with VR meshes featuring higher resolutions over North America, as well as quasi-uniform resolution meshes across the globe. The dataset includes multiple uniform- (240 and 120 km) and variable-resolution (50–200, 25–100, and 12–46 km) simulations for both the present-day (1990–2010) and future (2080–2100) periods, closely following the protocol of the North American Coordinated Regional Climate Downscaling Experiment. A deviation from the protocol is the pseudo-warming experiment for the future period, using the ocean boundary conditions produced by adding the sea surface temperature and sea ice changes from the low resolution version of the Max Planck Institute Earth System Model in the Coupled Model Intercomparison Project phase five to the present-day ocean state from a reanalysis product. Some unique aspects of global VR models are evaluated to provide background knowledge to data users and to explore good practices for modelers who use VR models for regional downscaling. In the coarse-resolution domain, strong resolution-sensitivity of the hydrological cycles exists over the tropics but does not appear to affect the mid-latitude circulations in the Northern Hemisphere including the downscaling target of North America. The pseudo-warming experiment leads to similar responses of large-scale circulations to the imposed radiative and boundary forcings in the CAM-MPAS and MPI models, but their climatological states in the historical period differ over various regions including North America. Such differences are carried to the future period, suggesting the importance of the base state climatology. Within the refined domain, precipitation statistics improve with higher resolutions, and such statistical inference is verified to be negligibly influenced by horizontal remapping during post-processing. Limited (≈ 50 % slower) throughput of the current code is found on a recent many-core/wide-vector High Performance Computing system, which limits the lengths of the 12–46 km simulations and indirectly affects the uncertainty from sampling. Our experience shows that global and technical aspects of VR downscaling framework require further investigations to reduce uncertainties for regional refinement. [ABSTRACT FROM AUTHOR]

Decadal climate predictions, obtained by constraining the initial condition of a dynamical model through a truthful estimate of the observed climate state, provide an accurate assessment of near-term climate change and are a useful tool to inform decision-makers on future climate-related risks. Here we present results from the CMIP6 (Coupled Model Intercomparison Project Phase 6) Decadal Climate Prediction Project (DCPP) decadal hindcasts produced with the operational CMCC (Euro-Mediterranean Center on Climate Change) decadal prediction system (DPS), based on the fully coupled CMCC-CM2-SR5 dynamical model. A 20-member suite of 10-year retrospective forecasts, initialized every year from 1960 to 2020, is performed using a full-field initialization strategy. The predictive skill for key variables is assessed and compared with the skill of an ensemble of non-initialized historical simulations so as to quantify the added value of the initialization. In particular, the CMCC DPS is able to skillfully reproduce past climate surface and subsurface temperature fluctuations over large parts of the globe. The North Atlantic Ocean is the region that benefits the most from initialization, with the largest skill enhancement occurring over the subpolar region compared to historical simulations. On the other hand, the predictive skill over the Pacific Ocean rapidly decays with forecast time, especially over the North Pacific. In terms of precipitation, the skill of the CMCC DPS is significantly higher than that of the historical simulations over a few specific regions, including the Sahel, northern Eurasia, and over western and central Europe. The Atlantic multidecadal variability is also skillfully predicted, and this likely contributes to the skill found over remote areas through downstream influence, circulation changes, and teleconnections. Considering the relatively small ensemble size, a remarkable prediction skill is also found for the North Atlantic Oscillation, with maximum correlations obtained in the 1–9 lead year range. Systematic errors also affect the forecast quality of the CMCC DPS, featuring a prominent cold bias over the Northern Hemisphere, which is not found in the historical runs, suggesting that, in some areas, the adopted full-field initialization strategy likely perturbs the equilibrium state of the model climate quite significantly. The encouraging results obtained in this study indicate that climate variability over land can be predictable over a multiyear range, and they demonstrate that the CMCC DPS is a valuable addition to the current generation of DPSs. This stresses the need to further explore the potential of the near-term predictions, further improving future decadal systems and initialization methods, with the aim to provide a reliable tool to inform decision-makers on how regional climate will evolve in the next decade. [ABSTRACT FROM AUTHOR]

Here we present hydrological and vegetation paleo-data extracted from 28 sites in West Africa from 5 ∘ S to 19 ∘ N and the past1000/PMIP4 IPSL-CM6A-LR climate model simulations covering the 850–1850 CE period to document the environmental and climatic changes that occurred during the Little Ice Age (LIA). The comparison between paleo-data and model simulations shows a clear contrast between the area spanning the Sahel and the savannah in the north, characterized by widespread drought, and the equatorial sites in the south, where humid conditions prevailed. Particular attention was paid to the Sahel, whose climatic evolution was characterized by a progressive drying trend between 1250 and 1850 CE. Three major features are highlighted: (1) the detection of two early warning signals around 1170 and 1240 CE preceding the onset of the LIA drying trend; (2) a tipping point at 1800–1850 CE characterized by a rainfall drop and an environmental degradation in the Sahel; and (3) a succession of drying events punctuating the LIA, the major one of which was dated to around 1600 CE. The climatic long-term evolution of the Sahel is associated with a gradual southward displacement of the Inter-Tropical Convergence Zone induced by the radiative cooling impacts of major volcanic eruptions that have punctuated the last millennium. [ABSTRACT FROM AUTHOR]

This study investigates changes in linkages between atmospheric blocking and winter (December–February) cold spells over the Pacific-North America region in two large-ensembles of Canadian Earth System Models (CanESM2 and CanESM5 under high-emission scenarios). The two ensembles show decreases in winter blocking frequency over the North Pacific from 1981–2010 baseline to 2071–2100, with larger decreases in CanESM5 (− 3.08%/decade) than CanESM2 (− 1.73%/decade). Using a time-invariant (stationary) threshold estimated from the baseline to define cold days, the two ensembles project a decline in cold spell events as future air temperature increases; the occasional occurrence of cold spell events is still projected to occur at the end of the century. Using a time-dependent (nonstationary) climatological threshold, CanESM2 and CanESM5 ensembles project modest decreases in cold spell days over North America (− 2.0 and − 2.3%/decade). With the nonstationary threshold, the two ensembles project decreases in winter cold spell frequency during blocking, with larger decreases in CanESM5 (13%) than CanESM2 (3%) for 2071–2100 period compared to the baseline. The two ensembles display similar blocking-cold spell linkages between the baseline and future periods; however, the linkage is weaker and exhibits larger uncertainty in the future. Moreover, temperature advection and net heat flux anomalies during blocking are generally weaker for the future period, resulting in weaker impacts on North American cold spells with larger uncertainty associated with increases in internal-variability. [ABSTRACT FROM AUTHOR]

Recent Arctic warming has fuelled interest in the weather and climate of the polar regions and how this interacts with lower latitudes. Several interesting theories of polar-midlatitude linkages involve Rossby wave propagation as a key process even though the meridional gradient in planetary vorticity, crucial for these waves, is weak at high latitudes. Here we review some basic theory and suggest that Rossby waves can indeed explain some features of polar variability, especially when relative vorticity gradients are present. We suggest that large-scale polar flow can be conceptualised as a mix of geostrophic turbulence and Rossby wave propagation, as in the midlatitudes, but with the balance tipped further in favour of turbulent flow. Hence, isolated vortices often dominate but some wavelike features remain. As an example, quasi-stationary or weakly westward-propagating subpolar anomalies emerge from statistical analysis of observed data, and these are consistent with some role for wave propagation. The noted persistence of polar cyclones and anticyclones is attributed in part to the weakened effects of wave dispersion, the mechanism responsible for the decay of midlatitude anomalies in downstream development. We also suggest that the vortex-dominated nature of polar dynamics encourages the emergence of annular mode structures in principal component analyses of extratropical circulation. Finally, we consider how Rossby waves may be triggered from high latitudes. The linear mechanisms known to balance localised heating at lower latitudes are shown to be less efficient in the polar regions. Instead, we suggest the direct response to sea ice loss often manifests as a heat low, with radiative cooling balancing the heating. If the relative vorticity gradient is favourable this does have the potential to trigger a Rossby wave response, although this will often be weak compared to waves forced from lower latitudes. [ABSTRACT FROM AUTHOR]

Human activity have caused significant increase in greenhouse gas (GHG) concentration and land use and land cover change (LULCC), which can in turn affect regional and global climate. We investigate the relative contributions of increased GHG concentration and LULCC to the precipitation and surface air temperature (SAT) in Asia through three dynamical downscaling simulations with different land cover maps and GHG concentrations. The results suggest that the increased GHG concentration leads to an increase (decrease) in precipitation over East Asia and Southeast Asia (South Asia) in spring and winter. Over Southeast Asia and the Bay of Bengal, LULCC induced a significant decrease in precipitation in autumn and winter, and the change is greater than that induced by GHG. Moreover, the enhanced GHG concentration generally leads to a decrease in dry days or light rain days and an increase in heavy rain days over the land area. However, LULCC‐induced changes in extreme precipitation are generally weak. The increased GHG concentration induces a significant increase of 1–3°C in the SAT throughout the year. LULCC plays a more important role than the increased GHG concentration in modulating the SAT over South Asia, Southeast Asia, and East Asia throughout the year. The increased GHG concentration and LULCC cause a broader range of changes in the daily temperature frequency. The anomalous warm event of 8–10°C increases by 1–1.5 days per season in the middle latitude regions in boreal spring due to the increased GHG concentration. LULCC also leads to an increase in high‐temperature events except central Asia. [ABSTRACT FROM AUTHOR]

The interactions between El Niño‐Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) are known to have great implications for global climate variability and seasonal climate predictions. Observational analysis suggests that the ENSO–IOD inter‐basin connection is time‐varying and related to the Atlantic Multidecadal Oscillation (AMO) with weakened ENSO–IOD relationship corresponding to AMO warm phases. A suite of Atlantic pacemaker simulations successfully reproduces the decadal fluctuations in ENSO–IOD relationship and its link to the AMO. The warm sea surface temperature (SST) anomalies associated with the AMO drive a series of Indo‐Pacific mean climate changes through tropical‐wide teleconnections, including the La Niña‐like mean SST cooling over the central Pacific and the deepening of mean thermocline depth in the eastern Indian Ocean. By modulating ocean–atmosphere feedback strength, those mean state changes decrease both ENSO amplitude and the Indian Ocean sensitivity to ENSO forcing, therefore decoupling the IOD from ENSO. Plain Language Summary: The El Niño‐Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) are two most important interannual climate signals exciting world‐wide climate and socioeconomic impacts. Their interactions are known to have great implications for global climate variability and seasonal climate predictions. However, the ENSO–IOD relationship is time‐varying and show prominent decadal fluctuations. Such changes in ENSO–IOD relationship are associated with the decadal variation in IOD teleconnections and predictability. The prediction skill of IOD is high when the ENSO–IOD relationship is strong, and vice versa. But it remains unknown what controls the decadal modulation of Indo‐Pacific inter‐basin connection. Our findings suggest that the Atlantic Multidecadal Oscillation (AMO) may modulate the ENSO–IOD inter‐basin connection. The AMO sea surface temperature anomalies drive a series of Indo‐Pacific mean climate changes through tropical‐wide teleconnections. Those mean state changes further influence both ENSO amplitude and the Indian Ocean sensitivity to ENSO forcing, thereby modulating the ENSO–IOD relationship. This study advances our understandings on inter‐basin and cross‐scale interactions in the climate system. Key Points: The inter‐basin connection between El Niño‐Southern Oscillation (ENSO) and Indian Ocean Dipole is time‐varying and controlled by the remote Atlantic Multidecadal Oscillation (AMO)The AMO sea surface temperature anomalies drive a series of Indo‐Pacific mean climate changes through tropical‐wide teleconnectionsThe AMO induced mean state changes influence both ENSO amplitude and the Indian Ocean sensitivity to ENSO forcing [ABSTRACT FROM AUTHOR]

Increased flood risks have been projected, but with large uncertainties, in the Kabul River Basin (Afghanistan and Pakistan). To place future changes in a long‐term perspective, we produce a 382‐year precipitation reconstruction for the basin using seven tree‐ring chronologies of old‐growth conifers from the Hindu Kush Mountains, a monsoon‐shadow area. The reconstruction proves robust over rigorous cross‐validations (R2 = 0.60, RE = 0.60, CE = 0.53). The full reconstruction (1637–2018) reveals a steady decline in the low end of the precipitation distribution, implying increasing drought risks. We show that droughts are getting more severe, shorter, and more frequent, interspersed with more frequent pluvials in the past century. Drought risks, compounded with projected flood intensification, pose significant threats for this transboundary river. Therefore, future water management needs to account for both flood and drought risks and be informed by long‐term hydroclimatic variability. Plain Language Summary: The Kabul River is a transboundary river spanning eastern Afghanistan and northern Pakistan. It is an important tributary of the Indus, one of the world's largest rivers with intensive water withdrawals for human use. With climate change, the Kabul River is projected to have more frequent and larger floods, but the projections are very uncertain. To have a better understanding of these future projections, we need to look at how the region's climate has changed in the past. Tree rings are a valuable source of information to serve that need. Using old‐growth conifers from the Hindu Kush Mountains, western Himalaya, we reconstruct four centuries of precipitation (rainfall) history for the Kabul River Basin. From the reconstruction, we observe that dry years are getting drier. Thus, the risks of severe droughts are increasing. Prolonged droughts are being replaced by shorter but more frequent ones, and periods of sustained high precipitation are also becoming more frequent. When seen in combination with earlier reports, our results imply that the Kabul River Basin is facing both floods and drought risks, and these are significant threats to the water security of the basin. Key Points: Robust, skillful precipitation reconstruction of the Kabul River Basin from tree ringsSteady decline in the low end of the precipitation distribution implies increasing drought risksProlonged droughts are being replaced by shorter, more frequent ones, interspersed with more frequent pluvials [ABSTRACT FROM AUTHOR]

The Far-Infrared Radiation Mobile Observation System (FIRMOS) is a Fourier transform spectroradiometer developed to support the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) satellite mission by validating measurement methods and instrument design concepts, both in the laboratory and in field campaigns. FIRMOS is capable of measuring the downwelling spectral radiance emitted by the atmosphere in the spectral band from 100 to 1000 cm-1 (10–100 µ m in wavelength), with a maximum spectral resolution of 0.25 cm-1. We describe the instrument design and its characterisation and discuss the geophysical products obtained by inverting the atmospheric spectral radiance measured during a campaign from the high-altitude location of Mount Zugspitze in Germany, beside the Extended-range Atmospheric Emitted Radiance Interferometer (E-AERI), which is permanently installed at the site. Following the selection of clear-sky scenes, using a specific algorithm, the water vapour and temperature profiles were retrieved from the FIRMOS spectra by applying the Kyoto protocol and Informed Management of the Adaptation (KLIMA) code. The profiles were found in very good agreement with those provided by radiosondes and by the Raman lidar operating from the Zugspitze Schneefernerhaus station. In addition, the retrieval products were validated by comparing the retrieved Integrated Water Vapour values with those obtained from the E-AERI spectra. Finally, we found that the trends for the temperature, and the water vapour profiles over time were in good agreement with those provided by ERA5 reanalysis. [ABSTRACT FROM AUTHOR]

Convection‐permitting climate modelling is a promising avenue for climate change research and services especially in mountainous regions. Work is required to evaluate the results of high‐resolution simulations against relevant observations, and put them in a broader context against coarser resolution modelling frameworks. Here we evaluate numerical simulations with the convection‐permitting regional climate model CNRM‐AROME ran at 2.5 km horizontal resolution over a large pan‐Alpine domain in the European Alps, using either the ERA‐Interim or climate model output as boundary conditions. This study analyses annual and seasonal characteristics of 2 m temperature, total precipitation, solid fraction of precipitation and snow depth at the scale of the French Alps under past and future climate conditions. The results are compared with the local reanalysis S2M, and raw or adjusted, with the ADAMONT method, simulations of the regional climate model CNRM‐ALADIN driven either by the ERA‐Interim reanalysis or the CNRM‐CM5 global climate model. The study highlights generally similar differences in past and future climate between the datasets, as well as obstacles to the use of some CNRM‐AROME outputs as they stand. These consist of excessive accumulation of snow on the ground above 1,800 m a.s.l., as well as lower temperature values at same elevations than the S2M reanalysis and the ADAMONT‐adjusted outputs. Besides these obstacles, CNRM‐AROME simulations present several advantages compared to the raw CNRM‐ALADIN outputs. Among them, a significantly smaller cold bias, more realistic values of accumulated precipitations, as well as a better representation of the spatial variability of the different variables investigated, which always stand closer to the reference data than in the CNRM‐ALADIN outputs. As suggested by many studies, CNRM‐AROME could even produce more realistic accumulated precipitations at high elevation than the S2M reanalysis taken as our reference and consequently than the ADAMONT‐adjusted projections, but the lack of a reliable set of high‐resolution observations at high elevation remains an obstacle to their evaluation. [ABSTRACT FROM AUTHOR]

The intraseasonal meridional wave trains are the major features of East Asia summer monsoon (EASM), but the complete physical pictures of dynamic pathways from tropical and mid‐high latitudes and their climate impacts have not been fully illustrated. With NCEP‐DOE Reanalysis‐II daily data set, two boreal summer intraseasonal meridional oscillations (ISMOs) are isolated and identified by extended EOF of zonal wind anomalies along the coast of East Asia on 10‐ to 30‐day timescale, that is, ISMO1 and ISMO2. They both demonstrate obvious quasi‐biweekly oscillations with an equivalent barotropic structure in troposphere, and ISMO1 represents the southward propagating wave train with large variances in upper level, which is initiated from the West Europe and primarily forced by the soil moisture anomalies over mid‐high latitudes of Eurasian continent, whereas ISMO2 propagates northward in mid‐lower troposphere from the tropical western North Pacific to East Asia that is closely related to BSISO2. The two ISMOs are capable of explaining a large fraction of the total intraseasonal variances of EASM, wherein, ISMO1 is responsible for a meridional dipole pattern of precipitation anomalies over eastern China, while ISMO2 has major influence in southern China. Generally, ISMO‐caused changes of extreme precipitation probability are in good accordance with the spatial pattern of its related 10‐ to 30‐day intraseasonal precipitation anomalies. Since ISMO1 and ISMO2 can clearly separate the tropical and extratropical‐origin meridional oscillations and further have robust influences on precipitation over East Asia, they can be used as the new monitoring and predicting factors to the intraseasonal variations of EASM and their associated extreme precipitation. Key Points: Two intraseasonal meridional oscillations (ISMOs) over East Asia are identified with equivalent barotropic structure and biweekly periodISMOs can be forced by the tropical convection and the mid‐high latitude land surface and propagate northward and southward, respectivelyISMOs represent a large fraction of intraseasonal climate variations over East Asia and have significant impact on extreme precipitation [ABSTRACT FROM AUTHOR]

Although it is an integral part of global change, most of the research addressing the effects of climate change on forests have overlooked the role of environmental pollution. Similarly, most studies investigating the effects of air pollutants on forests have generally neglected the impacts of climate change. We review the current knowledge on combined air pollution and climate change effects on global forest ecosystems and identify several key research priorities as a roadmap for the future. Specifically, we recommend (1) the establishment of much denser array of monitoring sites, particularly in the South Hemisphere; (2) further integration of ground and satellite monitoring; (3) generation of flux‐based standards and critical levels taking into account the sensitivity of dominant forest tree species; (4) long‐term monitoring of N, S, P cycles and base cations deposition together at global scale; (5) intensification of experimental studies, addressing the combined effects of different abiotic factors on forests by assuring a better representation of taxonomic and functional diversity across the ~73,000 tree species on Earth; (6) more experimental focus on phenomics and genomics; (7) improved knowledge on key processes regulating the dynamics of radionuclides in forest systems; and (8) development of models integrating air pollution and climate change data from long‐term monitoring programs. [ABSTRACT FROM AUTHOR]

Accurate and reliable precipitation data with high spatial and temporal resolution are essential in studying climate variability, water resources management, and hydrological forecasting. A range of global precipitation data are available to this end, but how well these capture actual precipitation remains unknown, particularly for mountain regions where ground stations are sparse. We examined the performance of three global high‐resolution precipitation products for capturing precipitation over Central Asia, a hotspot of climate change, where reliable precipitation data are particularly scarce. Specifically, we evaluated MSWEP, CHIRPS, and GSMAP against independent gauging stations for the period 1985–2015. Our results show that MSWEP and CHIRPS outperformed GSMAP for wetter periods (i.e., winter and spring) and wetter locations (150–600 mm·year−1), lowlands, and mid‐altitudes (0–3,000 m), and regions dominated by winter and spring precipitation. MSWEP performed best in representing temporal precipitation dynamics and CHIRPS excelled in capturing the volume and distribution of precipitation. All precipitation products poorly estimated precipitation at higher elevations (>3,000 m), in drier areas (<150 mm), and in regions characterized by summer precipitation. All products accurately detected dry spells, but their performance decreased for wet spells with increasing precipitation intensity. In sum, we find that CHIRPS and MSWEP provide the most reliable high‐resolution precipitation estimates for Central Asia. However, the high spatial and temporal heterogeneity of the performance call for a careful selection of a suitable product for local applications considering the prevailing precipitation dynamics, climatic, and topographic conditions. [ABSTRACT FROM AUTHOR]

Identifying general circulation models (GCMs) that represent the climate of a specific area is crucial for climate change studies. However, the uncertainties in GCMs caused by computational constraints, such as coarser resolution, physical parameterizations, initializations, and model structures, make it imperative to identify a representative individual or group of GCM for a climate impact study. An advanced envelope-based multi-criteria selection approach was used to identify a subset of the most appropriate future GCMs in the Upper Awash Basin (UAB). The skill accounting is based on (1) the range of projected mean changes of climate variables, (2) range of variability in climate extremes, and (3) model run performance to represent historical climate data. Statistical Downscaling and bias correction were made for the selected model runs. The downscaled and bias-corrected monthly values for precipitation are expected to increase from 0.42 to 2.82% in mid-century and 0.15 to 3.79% by the end century, considering the SSP4.5 scenario. For SSP8.5, it increases from 1.45 to 5.51% and 2.57 to 9.78% in the respective periods. Likewise, under the SSP4.5 forcing scenario, the monthly average air temperature projected to be warmer, which increased from 0.68 to 1.5 °C during mid-century and 0.09 to 1.92 °C end-of-century. Meanwhile, for SSP8.5, the projection indicates an increment of 0.19 to 1.98 °C under mid-century and 2.37 to 7.00 °C end-century. The projected change of future precipitation and temperature in the study basin increases the precipitation intensities, wet days and dry spells due to high-temperature increment. [ABSTRACT FROM AUTHOR]

Multiple studies have considered whether increased anthropogenic CO2 will affect the wind speeds and turbulence associated with the winter North Atlantic polar‐front jet stream in the upper atmosphere. Key questions are whether any effects can already be seen and, if so, can they be seen independent of computer models of the atmosphere. In this study we use two reanalyses, NCEP/NCAR and the ECMWF ERA5, and two large observational archives, AMDAR/ACARS and the Global Aircraft Data Set (GADS), to try to answer these questions for the period 2002–2020 when automated aircraft observations were plentiful over the North Atlantic. We focus on eastbound, New York to London, flights. No significant increase appears in reanalyses during the last roughly 40 years (1979–2020) which is our best estimate for the modern satellite era. In contrast, for the last roughly 20 years (2002–2020) both the ERA5 reanalysis (2.5% per year) and the GADS archive (1.2% to 1.4% per year) show a statistically significant rise in the wind speed in the North Atlantic jet streak exit region. These results must be considered in the context of atmospheric oscillations, changes to the North Atlantic Track System (NATS), and the effects of aircraft step climbs. We estimate that up to 0.5% of the rise may be due to improvements in the NATS operations and an unknown additional amount may be due to the substantial increase in automated aircraft observations starting in 1997. We also examine the impact of aircraft observations on one's confidence in drawing conclusions from secular changes in the reanalyses. For turbulence, the Light turbulence trends are not statistically significant. Our confidence in the turbulence results is more limited since these observations reflect medium‐term changes in tactical and strategic aircraft operational procedures as well as the underlying prevalence of turbulence. [ABSTRACT FROM AUTHOR]

Genetic adaptation to future environmental conditions is crucial to help species persist as the climate changes. Genome scans are powerful tools to understand adaptive landscapes, enabling us to correlate genetic diversity with environmental gradients while disentangling neutral from adaptive variation. However, low gene flow can lead to both local adaptation and highly structured populations, and is a major confounding factor for genome scans, resulting in an inflated number of candidate loci.Here, we compared candidate locus detection in a marine mollusc (Onithochiton neglectus), taking advantage of a natural geographical contrast in the levels of genetic structure between its populations. O. neglectus is endemic to New Zealand and distributed throughout an environmental gradient from the subtropical north to the subantarctic south. Due to a brooding developmental mode, populations tend to be locally isolated. However, adult hitchhiking on rafting kelp increases connectivity among southern populations.We applied two genome scans for outliers (Bayescan and PCAdapt) and two genotype–environment association (GEA) tests (BayeScEnv and RDA). To limit issues with false positives, we combined results using the geometric mean of q‐values and performed association tests with random environmental variables. This novel approach is a compromise between stringent and relaxed approaches widely used before, and allowed us to classify candidate loci as low confidence or high confidence.Genome scans for outliers detected a large number of significant outliers in strong and moderately structured populations. No high‐confidence GEA loci were detected in the context of strong population structure. However, 86 high‐confidence loci were associated predominantly with latitudinally varying abiotic factors in the less structured southern populations. This suggests that the degree of connectivity driven by kelp rafting over the southern scale may be insufficient to counteract local adaptation in this species.Our study supports the expectation that genome scans may be prone to errors in highly structured populations. Nonetheless, it also empirically demonstrates that careful statistical controls enable the identification of candidate loci that invite more detailed investigations. Ultimately, genome scans are valuable tools to help guide further research aiming to determine the potential of non‐model species to adapt to future environments. [ABSTRACT FROM AUTHOR]