Search

A crucial factor influencing the mass balance of the West Antarctic Ice Sheet is the Amundsen Sea Low (ASL), a climatological low‐pressure region situated off the West Antarctic coast. However, albeit the deepening of the ASL since the 1950s has been attributed to anthropogenic forcing, the multi‐decadal variability of the ASL remains poorly understood, because of a lack of long observations. Here, we apply a newly developed data assimilation method to reconstruct the ASL over 1870–2000. We study the forced and internal variability of the ASL using our new reconstruction in concert with existing large ensembles of climate model simulations. Our findings robustly demonstrate that an atmospheric teleconnection originating from the tropical Indo‐Pacific is the main driver of ASL variability at the multi‐decadal time scale, with resemblance to the Interdecadal Pacific Oscillation. Since the mid‐20th century, anthropogenic forcing has emerged as a dominant contributor to the strengthening of the ASL. Plain Language Summary: Changes in the West Antarctic Ice Sheet mass balance (i.e., the difference between the gain and loss of ice mass) are partly influenced by large‐scale winds, and in particular, a climatological low‐pressure feature located off the West Antarctic coast called the Amundsen Sea Low (ASL). Yet, although the long‐term strengthening of the ASL since the mid‐20th century has been demonstrated to be related to anthropogenic forcing, our understanding of the variability of the ASL on time‐scales of decades is poorly known. In this paper, we therefore investigate the origins of this variability since 1870, and quantify the relative contributions of human‐caused climate changes and natural variability of the climate system. For this purpose, we use several ensembles of model simulations as well as new climate reconstructions that combine paleoclimate records with model simulations using a statistical method. Our results indicate that the multi‐decadal variability of the ASL is strongly driven by tropical variability in the Indo‐Pacific through atmospheric connections between this region and the Amundsen Sea. Our reconstruction, when compared with a large ensemble of model simulations, indicates that since 1950, human‐induced climate forcing has become a dominant driver of long‐term ASL variability, contributing equally to tropical variability. Key Points: The large‐scale atmospheric circulation in West Antarctica exhibits a strong multi‐decadal variability superimposed by a 20th‐century trendThe multi‐decadal variability of this large‐scale atmospheric circulation is strongly governed by the Indo‐Pacific tropical variabilitySince 1950, anthropogenic forcing has emerged as a key driver of the long‐term change of this atmospheric circulation [ABSTRACT FROM AUTHOR]

Sea ice is an important and complex component of the Earth system and is considered a sensitive indicator of climate change. The seasonal sea ice cycle regulates the exchange of heat and salinity, altering the energy balance between high and low latitudes as well as the ocean and atmospheric circulation. The accurate representation of Antarctic sea ice has been considered a hot topic in the climate modelling community and lacks conclusive answers. In this paper, we evaluated the ability of 11 climate models from Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6) to simulate the sea ice seasonal cycle in Antarctica in terms of area (SIA) and concentration (SIC), as well as the improvements in the most recent models' version, submitted to CMIP6. The results indicated that all models are able to accurately capture the seasonal cycle of the Antarctic SIA, with the minimum (maximum) occurring in February (September). In the Weddell Sea, Amundsen Sea, Bellingshausen Sea, and the Ross Sea, the simulated sea ice concentration revealed a large and systematic bias in February when compared to observations. In September, a large and systematic bias was found nearby the Southern Ocean's northern limit in the Polar Front. Several CMIP6 models exhibited slight improvements on the SIA and SIC estimate over the previous version (CMIP5). All models indicated a significant sea ice loss in the coming years as a response to CO2 forcing. Despite the advancements in the sea ice representation, our findings show that the models are still unable to accurately represent the regional sea ice changes [ABSTRACT FROM AUTHOR]

Since the early 1990s the Pacific Walker circulation shows a multi‐decadal strengthening, which contradicts future model projections. Whether this trend, evident in many climate indices especially before the 2015 El Niño, reflects the coupled ocean‐atmosphere response to global warming or the negative phase of the Pacific Decadal Oscillation (PDO) remains debated. Here we show that sea surface temperature trends during 1980–2020 are dominated by three signals: a spatially uniform warming trend, a negative PDO pattern, and a Northern Hemisphere‐Indo‐West Pacific warming pattern. The latter pattern, which closely resembles the transient ocean thermostat‐like response to global warming emerging in a subset of CMIP6 models, shows cooling in the central‐eastern equatorial Pacific but warming in the western Pacific and tropical Indian Ocean. Together with the PDO, this pattern drives the Walker circulation strengthening in the equatorial band. Historical simulations appear to underestimate this pattern, contributing to the models' inability to replicate the Walker cell strengthening. Plain Language Summary: This paper investigates the observed changes in the tropical Pacific during the satellite era, including the recent decadal strengthening of the atmospheric zonal circulation—the Walker cell. We aim to understand the extent to which these changes represent a forced response to rising CO2 concentrations versus natural variability. We apply an approach in which we decompose the observed sea surface temperature trends into three components—a pattern associated with the Pacific Decadal Oscillation, which is part of natural variability, a uniform warming pattern, and a residual pattern. This residual pattern shows a remarkable resemblance to a forced ocean thermostat‐like transient response generated in some of the climate models, characterized by equatorial Pacific (EP) cooling, and a broad warming of the Northern Hemisphere, and the Indian Ocean and West Pacific. These results challenge studies arguing that the recent strengthening of the Pacific Walker cell can be explained simply by multi‐decadal natural variability in the tropics. Furthermore, the inability of climate models at large to fully capture this forced pattern with historical forcing puts into focus the reliability of future projections of climate change in the tropical Pacific, specifically the timing of emergence of the eastern EP warming. Key Points: A multi‐decadal strengthening of the Pacific Walker cell is observed in a wide range of indices, especially after 1990A Northern Hemisphere ‐ Indo West Pacific warming sea surface temperature pattern, which differs from the Pacific Decadal Oscillation, is evident since 1980This pattern resembles a forced response to abrupt CO2 forcing, emerging in a subset of climate models, and contributes to the Walker circulation strenthening [ABSTRACT FROM AUTHOR]

Statistical downscaling methods (SDMs) are techniques used to downscale and/or bias‐correct climate model results to regional or local scales. The European network VALUE developed a framework to evaluate and inter‐compare SDMs. One of VALUE's experiments is the perfect predictor experiment that uses reanalysis predictors to isolate downscaling skill. Most evaluation papers for SDMs employ simple statistical diagnostics and do not follow a process‐based rationale. Thus, in this paper, a process‐based evaluation has been conducted for the more than 40 participating model output statistics (MOS, mostly bias correction) and perfect prognosis (PP) methods, for temperature and precipitation at 86 weather stations across Europe. The SDMs are analysed following the so‐called "regime‐oriented" technique, focussing on relevant features of the atmospheric circulation at large to local scales. These features comprise the North Atlantic Oscillation, blocking and selected Lamb weather types and at local scales the bora wind and the western Iberian coastal‐low level jet. The representation of the local weather response to the selected features depends strongly on the method class. As expected, MOS is unable to generate process sensitivity when it is not simulated by the predictors (ERA‐Interim). Moreover, MOS often suffers from an inflation effect when a predictor is used for more than one station. The PP performance is very diverse and depends strongly on the implementation. Although conditioned on predictors that typically describe the large‐scale circulation, PP often fails in capturing the process sensitivity correctly. Stochastic generalized linear models supported by well‐chosen predictors show improved skill to represent the sensitivities. [ABSTRACT FROM AUTHOR]

Californian hydroclimate is strongly seasonal and prone to severe water shortages. Recent changes in climate trends have induced shifts in seasonality, thus exacerbating droughts, wildfires, and adverse water shortage effects on the environment and economy. Previous studies have examined the timing of the seasonal cycle shifts mainly as temperature driven earlier onset of the spring season. In this paper, we address quantitative changes in the onset, amounts, and termination of the precipitation season over the past 6 decades, as well as the large‐scale atmospheric circulation underpinning the seasonal cycle changes. We discover that the onset of the rainy season has been progressively delayed since the 1960s, and as a result the precipitation season has become shorter and sharper in California. The progressively later onset of the rainy season is shown to be related to the summer circulation pattern extending into autumn across the North Pacific, in particular, a delay in the strengthening of the Aleutian Low and later southward displacement of the North Pacific westerlies. Plain Language Summary: The rainy season over California is projected to show a distinct sharpening of the mean seasonal cycle, with winter precipitation increasing, and both autumn and spring precipitation decreasing. Our analysis of the past 6 decades of data for California suggests autumn decrease is already underway. A delayed start of the rainy season of 27 days since 1960s can exacerbate seasonal droughts and prolong the wildfire season. This delay occurs due to a number of conditions that controls precipitation: the summer circulation pattern has been extending throughout November across the North Pacific, and the wintertime strengthening of the Aleutian Low is delayed. Accordingly, the southward migration of the North Pacific jet stream as well as extratropical storm tracks are delayed, which marks the start of the California rainy season, are delayed. More work, using climate models, will be needed to provide a better understanding of atmospheric conditions across the North America and the North Pacific. However, our findings provide observational evidence for the projected rainfall change over California and inform ongoing discussion about the drying/wetting tendencies of the rainy season in California. Key Points: Rainfall data over the last 6 decades suggests a progressively delayed onset to the rainy season over CaliforniaA corresponding delay occurs in the transition from summer to wintertime circulation over the North PacificObserved autumn trends appear consistent with projected future shortening of the California rainy season [ABSTRACT FROM AUTHOR]

Climate projections for the UK exhibit substantial uncertainty, and this uncertainty is a hindrance to robust and timely decision making on both adaptation and mitigation policy issues. A large part of the uncertainty is associated with dynamical changes of the regional atmospheric circulation rather than thermodynamic changes which are better constrained by model simulations. Of particular importance for the UK is the extent to which the North Atlantic jet will change over coming decades and the impact this will have on weather and climate in the region. In this article, we propose the use of jet‐based storylines for assessing and communicating uncertainty in climate projections for the UK, wherein changes in each impact are explicitly conditioned on changes in the North Atlantic jet. This approach provides a framework for evaluating the impacts associated with a range of plausible future climate outcomes for the UK, including outcomes that may not be well represented in the current generation of climate models, and for communicating these potential outcomes. We construct a simple yet useful set of future jet storylines for both summer and winter and for 2°C and 4°C global warming levels and illustrate the utility of the approach by evaluating the impact of each jet storyline on future changes in UK precipitation. In doing so, we demonstrate that the relationships between the jet and UK precipitation are consistent between observed interannual variability and projected changes. This finding increases our confidence in projecting changes in UK precipitation associated with each storyline. [ABSTRACT FROM AUTHOR]

The persistent inter‐model spread in the response of global‐mean surface temperature to increased CO2 (known as the "Equilibrium Climate Sensitivity," or "ECS") is a crucial problem across model generations. This work examines the influence of the models' present‐day atmospheric circulation climatologies, and the accompanying climatological cloud radiative effects, in explaining that spread. We analyze the Coupled Model Intercomparison Project Phase 6 (CMIP6) models and find that they simulate a more poleward, and thus more realistic, edge of the Hadley cell (HC) in the Southern Hemisphere than the CMIP5 models, although the climatological shortwave cloud radiative effects are similar in the two generations of models. A few CMIP5 models with extreme equatorward biases in the HC edge exhibited high ECS due to strong Southern midlatitude shortwave cloud radiative warming in response to climate change, suggesting an ECS dependence on HC position. We find that such constraint no longer holds for the CMIP6 models, due to the absence of models with extreme HC climatologies. In spite of this, however, the CMIP6 models show an increased spread in ECS, with more models in the high ECS range. In addition, an improved representation of the climatological jet dynamics does not lead to a new emergent constraint in the CMIP6 models either. [ABSTRACT FROM AUTHOR]

In this study, 28 climate models from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and 32 models from the sixth phase (CMIP6) have been evaluated for their ability to simulate large‐scale atmospheric circulations (using rainfall, wind fields, geopotential height, temperature, and moisture flux convergence) for the summer monsoon in Southeast Asia. Using a multi‐criteria decision making technique, models have been ranked based on 25 metrics which compare their performances with observation data. Results indicate a better representation of annual rainfall cycles as well as spatial pattern by CMIP6 models compared to CMIP5. Though majority of the models from both CMIPs show late onset and early retreat of the rainy season, CMIP6 GCMs simulate the onset, retreat, and the length of the rainy season closer to the observation. Large‐scale circulation patterns evaluated using spatial correlation and root mean square error (RMSE) show improvements in CMIP6 across all metrics, especially for the moisture flux convergence. Performances for large‐scale circulation are generally reflected in rainfall simulation; however, few models showed that better simulations of rainfall do not exclusively depend on their performance for large‐scale variables. Overall, CMIP6 models are found to be superior to CMIP5 models in simulating rainfall and large‐scale circulation, which is likely attributable to CMIP6 model's higher spatial resolutions, increased number of vertical levels, improved atmospheric and land surface parameterization, etc. Finally, subsets of optimal models from CMIP5 and CMIP6 that proved to be better at representing the summer monsoons in the study area are identified. These models are recommended to develop robust future projections that can be used for climate change impact and adaptation studies. [ABSTRACT FROM AUTHOR]

Natural climate variability poses a limit to the confidence in regional climate projections, particularly for the near‐term. Therefore, the next decades are of importance for regional impact studies and the development of regional adaptation plans. This article presents results from an ensemble of regional climate model simulations (years 1996–2005 and 2026–2035) that are used to examine the effects of both anthropogenic forcing and natural variability associated with the Pacific Decadal Oscillation (PDO) on near‐term climate projections for the Hawaiian Islands. The Community Earth System Model Large Ensemble (CESM‐LE) is used in conjunction with the Weather Research and Forecasting (WRF) model for downscaling. The climate responses to the PDO and anthropogenic forcing are isolated and analyzed separately. In response to anthropogenic forcing, significant increases in surface air temperature, of ∼0.8 K, are projected at low elevations. Stronger warming, of up to 1.3 K, is seen at higher elevation areas. Future climate simulations show significant increases in wet season rainfall, of ∼10%–20%, along the windward slopes of Big Island and Maui. Rainfall patterns during the positive PDO phase are projected to reverse in sign, leading to drier conditions, by ∼10%–30%, at many locations. Future climate simulations show daily rainfall extremes will increase, by up to ∼10%–15%, at many locations. Daily temperature extremes are also projected to increase significantly, by up to 1.4 K. Overall, results indicate that natural variability will continue to contribute to uncertainty in near‐term rainfall projections for the Hawaiian Islands, masking the forced signal. Plain Language Summary: This project studies how temperature and precipitation will change across the Hawaiian Islands in the near future due to human‐induced causes (e.g., burning coal and other fossil fuels). This is done by comparing climate model simulations for two 10‐year periods (1996–2005 vs. 2026–2035). Further, this research evaluates how natural climate variations affect Hawaiian climate. The main analysis concentrates on an important type of natural climate variability in the North Pacific, the Pacific Decadal Oscillation. This research implements dynamical downscaling, that is, a regional climate model is used to refine global climate model simulations in order to better capture the local weather patterns in Hawai'i. We find that land and ocean temperatures across the Hawaiian Islands region will become warmer due to human‐induced causes. We also find that rainfall will likely increase for some areas of Hawai'i, particularly the mountain slopes, posing an increased risk for flooding. The simulations reveal that natural climate variability will continue to contribute to near‐term climate variations in this region. While the natural climate variability limits our confidence in the projected rainfall changes, it is hoped that our findings will assist decision makers across the State of Hawai'i in creating climate adaptation plans. Key Points: Significant increases in near‐surface temperature and sea surface temperature are projected across the Hawaiian Islands regionSignificant increases in mean and extreme rainfall are projected for some areas of the islandsNatural decadal variability will continue to mask the forced signal in near‐term rainfall projections for the Hawaiian Islands [ABSTRACT FROM AUTHOR]

Given uncertainty in the processes involved in polar amplification, elucidating the role of poleward heat and moisture transport is crucial. The Polar Amplification Model Intercomparison Project (PAMIP) permits robust separation of the effects of sea ice loss from sea surface warming under climate change. We utilize a moist isentropic circulation framework that accounts for moisture transport, condensation, and eddy transport, in order to analyze the circulation connecting the mid‐latitudes and the Arctic. In PAMIP's atmospheric general circulation model experiments, prescribed sea ice loss reduces poleward heat transport (PHT) by warming the returning moist isentropic circulation at high latitudes, while prescribed warming of the ocean surface increases PHT by strengthening the moist isentropic circulation. Inter‐model spread of PHT into the Arctic reflects the tug‐of‐war between sea‐ice and surface‐warming effects. Plain Language Summary: A major conundrum in current climate science is to understand what Arctic changes imply for the climate and environment in mid‐latitude regions. The Polar Amplification Model Intercomparison Project (PAMIP) designed a set of climate model experiments to specifically answer this question in a carefully designed, idealized framework. PAMIP's approach is to separate historic and projected climate change into parts associated with Arctic sea ice loss and ocean surface warming and investigate how these two contributions can influence the atmosphere. To isolate these effects, only models can be used, because, in reality, sea ice loss and ocean surface warming are strongly linked together. This letter focuses on what the PAMIP experiments imply for the transport and redistribution of heat and moisture in the atmosphere. In PAMIP, we learn that Arctic sea ice loss causes the atmosphere to reduce the transport of dry and cold air away from the Arctic while ocean warming causes more transport of moist warm air toward the Arctic. These two effects are in a tug‐of‐war, suggesting that climate change can cause a mix of competing impacts on the global energy transport from the tropics to the Arctic. Key Points: Sea ice loss exports static energy from the Arctic by warming the equatorward branch of the global mass circulationSea surface warming imports static energy into the Arctic by increasing the mid‐latitude mass transport, overwhelming the sea ice effectThere is more spread amongst models for the effect of sea‐surface warming than for sea ice loss [ABSTRACT FROM AUTHOR]

The Svalbard Archipelago has undergone rapid warming in the recent decades leading to warmer and wetter winter conditions. This study relates the present (2013–2018) 2 m temperature, precipitation, and rain‐on‐snow (ROS) climate in Svalbard to different atmospheric circulation (AC) types utilizing the high‐resolution numerical weather prediction model Application of Research to Operations at Mesoscale (AROME)‐Arctic. We find that the 2 m median temperatures vary most across AC types in winter and spring and in summer they vary the least. In all seasons the 10th percentile 2 m temperatures are above 0°C with southwesterly AC types over Svalbard. In comparison, the relationship between AC type and precipitation varies more spatially, with most accumulated precipitation and highest median precipitation intensities with onshore flow over open water. Our results suggest that sea ice explains a large part of the local variability in both 2 m temperature and precipitation. In the studied period ROS is a frequent phenomenon up to 150 m above sea level (ASL) on land, with most events in the southwestern parts of the archipelago (57 cases during five winter seasons). ROS events in winter occur predominantly with AC types from the southerly sector or during a low‐pressure center/trough passage. The southwesterly cyclonic AC type, with a low‐pressure center west of Svalbard, is the most frequent AC type for ROS events. In addition to being the most frequent, the southwesterly AC has the largest spatial coverage of ROS. Plain Language Summary: The Svalbard Archipelago has undergone rapid warming in the recent decades leading to warmer and wetter winter conditions. This study relates the present (2013–2018) 2 m temperature, precipitation, and rain‐on‐snow (ROS) climate to different atmospheric circulation (AC) types utilizing the high‐resolution numerical weather prediction model Application of Research to Operations at Mesoscale (AROME)‐Arctic. We found that winter and spring 2 m median temperatures vary most across AC types and in summer they vary the least. Our results suggest that sea ice explains a large part of the local variability in both 2 m temperature and precipitation. In the studied period ROS is a frequent phenomenon up to 150 m ASL on land, with most events in the southwestern parts of the archipelago (57 cases during five winter seasons). The majority of these events occur in southwesterly cyclonic AC type, with a low‐pressure center west of Svalbard. In addition to being the most frequent, the southwesterly AC has the largest spatial coverage of ROS. Key Points: Winter and spring temperature and precipitation conditions in Svalbard are most sensitive to the synoptic flow directionAt the northern and eastern parts of Svalbard the precipitation intensity appears to depend on upstream sea ice conditionsRain‐on‐snow events in Svalbard have the largest spatial coverage under southwesterly synoptic flow [ABSTRACT FROM AUTHOR]

The Max Planck Institute Grand Ensemble (MPI‐GE) is the largest ensemble of a single comprehensive climate model currently available, with 100 members for the historical simulations (1850–2005) and four forcing scenarios. It is currently the only large ensemble available that includes scenario representative concentration pathway (RCP) 2.6 and a 1% CO2 scenario. These advantages make MPI‐GE a powerful tool. We present an overview of MPI‐GE, its components, and detail the experiments completed. We demonstrate how to separate the forced response from internal variability in a large ensemble. This separation allows the quantification of both the forced signal under climate change and the internal variability to unprecedented precision. We then demonstrate multiple ways to evaluate MPI‐GE and put observations in the context of a large ensemble, including a novel approach for comparing model internal variability with estimated observed variability. Finally, we present four novel analyses, which can only be completed using a large ensemble. First, we address whether temperature and precipitation have a pathway dependence using the forcing scenarios. Second, the forced signal of the highly noisy atmospheric circulation is computed, and different drivers are identified to be important for the North Pacific and North Atlantic regions. Third, we use the ensemble dimension to investigate the time dependency of Atlantic Meridional Overturning Circulation variability changes under global warming. Last, sea level pressure is used as an example to demonstrate how MPI‐GE can be utilized to estimate the ensemble size needed for a given scientific problem and provide insights for future ensemble projects. Key Points: The 100‐member MPI‐GE is currently the largest publicly available ensemble of a comprehensive climate modelMPI‐GE currently has the most forcing scenarios of all large ensemble projects: RCP2.6, RCP4.5, RCP8.5, and 1% CO2The power of MPI‐GE is to estimate the forced response and internal variability, including changing variability, to unprecedented precision [ABSTRACT FROM AUTHOR]

Relaxation experiments with the atmosphere model from European Centre for Medium‐range Weather Forecasts are analyzed to understand influence of lower latitudes (south of about 52 °N) on climate variability and change over the Arctic region. Interannual variability of the Arctic troposphere is impacted strongly by both the tropics and the midlatitudes. In general, the link in winter is stronger than that in summer. Furthermore, the tropics and midlatitudes have different preferred pathways by which they influence the Arctic. Trend analysis suggests that winter surface warming trends over the Arctic are driven strongly by the local sea ice‐atmospheric interaction. Warming at higher altitudes is strongly tied to remote non‐Arctic drivers, with some local amplification. Summer warming trends in northeastern Canada and Greenland are driven strongly by sea surface temperature/sea ice changes and partly by the tropics. The summer warming in northern Europe and western Russia is more strongly driven by the midlatitudes. Plain Language Summary: This study analyzes model output from relaxation experiments, in which the atmosphere at lower latitudes is nudged toward reanalysis data, to understand influences of tropics and midlatitudes on the Arctic atmosphere in terms of variability and trends. Our results demonstrate that the Arctic atmospheric circulation in terms of interannual variability can be relatively well constrained by lower latitudes. Generally, lower‐latitude forcing of the Arctic is stronger in winter than in summer. However, the Arctic temperature variability is less well constrained, owning possibly to poorly constrained local cloud/radiation feedback. In terms of the recent warming trends in the Arctic region, the surface warming is more strongly related to the local sea ice‐atmosphere interaction during winter. The warming at higher altitudes is strongly driven by remote processes. The summer warming is located mainly over the land areas and the driving factors are region dependent. Key Points: The atmospheric circulation in both the tropics and midlatitudes has a strong impact on the Arctic atmospheric circulationThe midlatitudes play an important role in driving the recent Arctic warming above the atmospheric boundary layerRecent summer warming in northeastern Canada‐Greenland (northern Europe and western Russia) is strongly driven by SST/sea ice (midlatitudes) [ABSTRACT FROM AUTHOR]

Antarctic snowfall consists of frequent clear‐sky precipitation and heavier falls from intrusions of maritime airmasses associated with amplified planetary waves. We investigate the importance of different precipitation events using the output of the RACMO2 model. Extreme precipitation events consisting of the largest 10% of daily totals are shown to contribute more than 40% of the total annual precipitation across much of the continent, with some areas receiving in excess of 60% of the total from these events. The greatest contribution of extreme precipitation events to the annual total is in the coastal areas and especially on the ice shelves, with the Amery Ice Shelf receiving 50% of its annual precipitation in less than the 10 days of heaviest precipitation. For the continent as a whole, 70% of the variance of the annual precipitation is explained by variability in precipitation from extreme precipitation events, with this figure rising to over 90% in some areas. Plain Language Summary: The Antarctic ice sheet is extremely important because of its possible contribution to sea level rise and through the climate records than can be reconstructed using chemical signals locked in the ice. The mass of the ice sheet is constantly changing because of the ice gained by snowfall and the loss of ice at the margins via iceberg calving and melt through contact with relatively warm water masses. The amount of snow falling on the Antarctic is highly variable and dependent on the meteorological conditions over the Southern Ocean and the penetration of marine air into the interior. We show that extreme snowfall events, defined at the heaviest 10% of daily precipitation amounts, contribute a high percentage of the annual snowfall and are the main factor controlling the year‐to‐year variability of snowfall across the continent. This has implications for the reconstruction of past climate records using data from ice cores and the selection of future ice core drilling sites. Key Points: Extreme precipitation events explain 70% of the interannual variance of Antarctic snowfallExtreme precipitation events are particularly important over western West Antarctica and on the Ross and Amery Ice ShelvesTropical climate variability is important in modulating the frequency of extreme precipitation events in the West Antarctic sector [ABSTRACT FROM AUTHOR]

Arabian Sea (AS) warming has been significantly accelerated since the 1990s, in particular in the spring season. Here we link the AS warming changes to the Atlantic multidecadal oscillation (AMO). A set of Atlantic pacemaker experiments with a slab mixed‐layer ocean model successfully reproduces the AS spring multidecadal variability and its connection with the AMO. An atmospheric teleconnection from the Atlantic to the AS in the preceding winter and associated thermodynamic air‐sea feedback is found to be important. The teleconnection can be reestablished by the atmospheric model when the AMO sea surface temperature (SST) and its trans‐basin footprint over the western Pacific are prescribed simultaneously. The western Pacific SST warming associated with the AMO positive phase induces a Gill‐type Rossby wave over the AS, showing anomalously low pressures and converging southerlies that weaken winter northerlies. Thus, the wind‐evaporation‐SST feedback results in and maintains the AS warm SST anomalies to the subsequent spring. Plain Language Summary: The rapid warming of the Arabian Sea (AS) since the 1990s not only has significant impacts on the monsoon climate change and extreme weather events (flood, heat wave, and cyclone) in Arabian Peninsula and Indian subcontinent but also poses increasingly severe risks of damage to the coastal and marine ecosystems. However, the cause of this recent acceleration of AS warming remains unclear. Here using observations and atmosphere‐ocean coupled models, we link the observed AS warming changes to the Atlantic multidecadal oscillation (AMO) and show that more than 70% of AS multidecadal variability can be explained by the AMO. This Atlantic‐AS teleconnection involves atmosphere‐ocean interactions across multiple ocean basins, with a contribution from the western Pacific (WP). The SST footprint of the AMO over the WP acts as a relay for the effect of the AMO on the AS by exciting an atmospheric teleconnection and subsequently thermodynamic feedbacks over the AS. The concurrent cold‐to‐warm phase shift of the AMO and its WP SST footprint since the 1990s contribute constructively to the rapid warming of the AS. Our results highlight an unexpected multiple‐basin interaction at decadal timescales, which plays a key role in the attribution of historical regional SST warming. Key Points: The observed Arabian Sea warming changes (slowdown and acceleration) are linked to the Atlantic multidecadal oscillation for the first timeThe teleconnection involves air‐sea interactions across multiple ocean basins, with a contribution from western Pacific that acts as a relayThe decadal phase shift of Atlantic‐Western Pacific trans‐basin variability since the 1990s contributes to the rapid warming of Arabian Sea [ABSTRACT FROM AUTHOR]

Analysis of observations indicates that there was a significant decadal change in summer (June–August) mean rainfall over South Asia and Southeast Asia across the mid‐1990s, which is characterized by less rainfall over central‐northern India and northern Indo‐China Peninsula. This study investigates impacts of anthropogenic forcing on the observed decadal change across the mid‐1990s. A set of experiments using the coupled atmosphere‐ocean‐mixed‐layer model MetUM‐GOML2 has been performed to quantify the relative roles of changes in anthropogenic greenhouse gases and anthropogenic aerosols (AA). Results indicate a dominant role of anthropogenic changes in the observed decadal changes. Separately, the changes in greenhouse gases forcing play an important role in the reduction of rainfall over central‐northern India through the changes of atmospheric circulation (i.e., the local Hadley circulation and the Walker circulation), with additional contribution from changes in AA forcing. The changes in AA forcing dominate the reduction of rainfall over northern Indo‐China Peninsula due to high‐pressure anomalies over northern South Asia and the western subtropical Pacific. These high‐pressure anomalies are induced by the surface cooling, mainly via aerosol‐radiation interaction that decreases downward clear‐sky shortwave radiation over South Asia during summer and aerosol‐radiation interaction and aerosol‐cloud interaction that decrease downward shortwave radiation over the western subtropical Pacific during presummer seasons. Key Points: Anthropogenic forcing plays a dominant role for the decadal change of the SASM across the mid‐1990sGHG forcing plays an important role in the reduction of rainfall over central‐northern India via weakening the Walker circulationAA forcing dominates the reduction of rainfall over the northern Indo‐China Peninsula due to high‐pressure anomalies [ABSTRACT FROM AUTHOR]

The hindcast data of Pusan National University coupled general circulation model (PNU CGCM), a participant model of the Asia‐Pacific Economic Cooperation Climate Center (APCC) Multi‐Model Ensemble Climate Prediction System, and August–October sea‐surface temperature (SST) in the northern Barents–Kara Sea (BKI) and the sea‐ice extent (SIE) in the Chukchi Sea (East Siberian Sea index [ESI]) are used for predicting 20 × 20‐km‐resolution anomalous surface air temperature at 2‐m height (aT2m) over Mongolia for boreal winter. For this purpose, area‐averaged surface air temperature (TI) and sea‐level pressure (SLP) over Mongolia are defined. Then four large‐scale indices, TImdl and SHImdl obtained from PNU CGCM, and TIMLR and SHIMLR obtained from multiple linear regressions on BKI and ESI, are incorporated using the artificial neural network (ANN) method for the prediction and statistical downscaling to obtain the monthly and seasonal 20 × 20‐km‐resolution aT2m over Mongolia in winter. An additional statistical method, which uses BKI and ESI as predictors of TI and SHI together with dynamic prediction by the CGCM, is used because of the relatively low skill of seasonal predictions by most of the state‐of‐the‐art models and the multi‐model ensemble systems over high‐latitude landlocked Eurasian regions such as Mongolia. The results show that the predictabilities of monthly and seasonal 20 × 20‐km‐resolution aT2m over Mongolia in winter are improved by applying ANN to both statistical and dynamical predictions compared to utilizing only dynamic prediction. The predictability gained by the proposed method is also demonstrated by the probabilistic forecast implying that the method forecasts aT2m over Mongolia in winter reasonably well. Winter climatologies of T2m (colour, °C) and SLP (contour, hPa) from observation (1981–2015). Rectangle areas indicate domains for TI and SHI. [ABSTRACT FROM AUTHOR]

Abstract: Glacial‐interglacial cycles are often described as an amplified global response of the climate to perturbations in solar radiation caused by oscillations of Earth's orbit. However, it remains unclear whether internal feedbacks are large enough to account for the radically different glacial and interglacial states. Here we provide support for an alternative view: Glacial‐interglacial states are multiple equilibria of the climate system that exist for the same external forcing. We show that such multiple equilibria resembling glacial and interglacial states can be found in a complex coupled general circulation model of the ocean‐atmosphere‐sea ice system. The multiple states are sustained by ice‐albedo feedback modified by ocean heat transport and are not caused by the bistability of the ocean's overturning circulation. In addition, expansion/contraction of the Southern Hemisphere ice pack over regions of upwelling, regulating outgassing of CO2 to the atmosphere, is the primary mechanism behind a large pCO2 change between states. [ABSTRACT FROM AUTHOR]

Urban heat island (UHI) and climate change belong to two separate scientific fields within meteorology nowadays. Climate change, however, may affect the characteristics of UHI as well. Various atmospheric macrocirculation conditions determine the frequency of certain weather conditions at a given area, thus they influence the frequency of the occurrence of conditions advantageous for UHI development. In the present research, the time series data of conditions advantageous for UHI (advantageous meteorological conditions [AMC]) were determined in the case of Debrecen (Hungary) and similar patterns existing in the AMC time series were searched in those of North Atlantic Oscillation, East Atlantic Oscillation, East Atlantic (EA)/Western Russia (WR) Pattern and Scandinavian Oscillation indices for the period between 1961 and 2010 using Gábor–Morlet wavelet transformations. Several significantly coherent oscillations were found. The occurrence frequency of AMC can be approximated from macrocirculation conditions in these periods, according to the concept of heat island. These estimations are consistent with the calculated AMC time series. This proves that there is some relationship between macrocirculation and heat island development. Based on the results, using seasonal and climate models the changes of UHIs at seasonal and climatic scales may become predictable. [ABSTRACT FROM AUTHOR]

Precipitation falling in the Snowy Mountains region of south‐east Australia is a critical resource—providing water for hydroelectricity, as well as irrigated agriculture and environmental flows throughout the economically important Murray River system. Improved understanding of the drivers of precipitation variability is therefore a key research aim. Focussing on synoptic types responsible for delivering precipitation ≥10 mm per day, an analysis is presented of the large‐scale atmospheric circulation drivers (“teleconnections”) of seasonal synoptic type frequency using cross‐wavelet and boosted regression tree methods. Results demonstrate that relationships are not stationary over the period 1900–2012, and complex interactions between teleconnections and synoptic atmospheric circulation drive precipitation variability. Importantly, we demonstrate that teleconnections do not act in isolation. Relationships with the tropical Pacific Ocean are shown to be key drivers of synoptic types associated not only with the dominant tropical moisture pathways to the Snowy Mountains, but also with extra‐tropical sources. Tropical sea surface temperatures are therefore shown to drive synoptic type frequency and facilitate the dominance of synoptic types with tropical moisture sources, most notability since the 1950s. [ABSTRACT FROM AUTHOR]

In this study, the stochastic deep convection parameterization of Plant and Craig (PC) is implemented in the Community Atmospheric Model version 5 (CAM5) to incorporate the stochastic processes of convection into the Zhang-McFarlane (ZM) deterministic deep convective scheme. Its impacts on deep convection, shallow convection, large-scale precipitation and associated dynamic and thermodynamic fields are investigated. Results show that with the introduction of the PC stochastic parameterization, deep convection is decreased while shallow convection is enhanced. The decrease in deep convection is mainly caused by the stochastic process and the spatial averaging of input quantities for the PC scheme. More detrained liquid water associated with more shallow convection leads to significant increase in liquid water and ice water paths, which increases large-scale precipitation in tropical regions. Specific humidity, relative humidity, zonal wind in the tropics, and precipitable water are all improved. The simulation of shortwave cloud forcing (SWCF) is also improved. The PC stochastic parameterization decreases the global mean SWCF from −52.25 W/m2 in the standard CAM5 to −48.86 W/m2, close to −47.16 W/m2 in observations. The improvement in SWCF over the tropics is due to decreased low cloud fraction simulated by the stochastic scheme. Sensitivity tests of tuning parameters are also performed to investigate the sensitivity of simulated climatology to uncertain parameters in the stochastic deep convection scheme. [ABSTRACT FROM AUTHOR]