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A review of many studies published since the late 1920s reveals that the main driving mechanisms responsible for the early-twentieth-century Arctic warming (ETCAW) are not fully recognized. The main obstacle seems to be our limited knowledge about the climate of this period and some forcings. A deeper knowledge based on greater spatial and temporal resolution data is needed. The article provides new (or improved) knowledge about surface air temperature (SAT) conditions (including their extreme states) in the Arctic during the ETCAW. Daily and subdaily data have been used (mean daily air temperature, maximum and minimum daily temperature, and diurnal temperature range). These were taken from 10 individual years (selected from the period 1934–50) for six meteorological stations representing parts of five Arctic climatic regions. Standard SAT characteristics were analyzed (monthly, seasonal, and yearly means), as were rarely investigated aspects of SAT characteristics (e.g., number of characteristic days, day-to-day temperature variability, and the onset, end, and duration of thermal seasons). The results were compared with analogical calculations done for data taken from the contemporary Arctic warming (CAW) period (2007–16). The Arctic experienced warming between the ETCAW and the CAW. The magnitude of warming was greatest in the Pacific (2.7°C) and Canadian Arctic (1.9°C) regions. A shortening of winter and lengthening of summer were noted. Furthermore, the climate was also a little more continental (except the Russian Arctic) and less stable (greater day-to-day variability and diurnal temperature range) during the ETCAW than during the CAW. Significance Statement: It is well established that human activity (particularly increased greenhouse gas emissions) is the primary driving mechanism of the recent dramatic warming in the Arctic. However, the causes of a similar warming here in the first half of the twentieth century remain uncertain. The limited knowledge about the climate of that period—which mainly results from the low resolution of data—is a significant obstacle to a definitive determination of the forcing mechanisms. Therefore, the main aim of our paper is to improve our understanding of specific aspects of weather and climate (including extremes) using long-term series of daily and subdaily data that have rarely been applied for this purpose. This new, more comprehensive knowledge about the historical Arctic climate should allow the scientific community (particularly climate modelers) to better validate both climate models and reanalysis products and, consequently, to more precisely identify the causes of the early-twentieth-century Arctic warming. [ABSTRACT FROM AUTHOR]

Climate change impact research and risk assessment require accurate estimates of the climate change signal (CCS). Raw climate model data include systematic biases that affect the CCS of high-impact variables such as daily precipitation and wind speed. This paper presents a novel, general, and extensible analytical theory of the effect of these biases on the CCS of the distribution mean and quantiles. The theory reveals that misrepresented model intensities and probability of nonzero (positive) events have the potential to distort raw model CCS estimates. We test the analytical description in a challenging application of bias correction and downscaling to daily precipitation over alpine terrain, where the output of 15 regional climate models (RCMs) is reduced to local weather stations. The theoretically predicted CCS modification well approximates the modification by the bias correction method, even for the station–RCM combinations with the largest absolute modifications. These results demonstrate that the CCS modification by bias correction is a direct consequence of removing model biases. Therefore, provided that application of intensity-dependent bias correction is scientifically appropriate, the CCS modification should be a desirable effect. The analytical theory can be used as a tool to 1) detect model biases with high potential to distort the CCS and 2) efficiently generate novel, improved CCS datasets. The latter are highly relevant for the development of appropriate climate change adaptation, mitigation, and resilience strategies. Future research needs to focus on developing process-based bias corrections that depend on simulated intensities rather than preserving the raw model CCS. [ABSTRACT FROM AUTHOR]

Recent observations and model studies of the earth’s radiative energy balance have focused attention on the earth’s top of atmosphere (TOA) energy balance. This is the balance between the shortwave energy absorbed by the earth, which is represented by a spatially and temporally averaged absorbed flux , and the emitted longwave energy, which is represented by the corresponding averaged emitted flux . The TOA average net flux FN is defined as the difference between the two over the averaged area and time, which may be a local, regional, or global average. A global nonzero net flux represents a measure of imbalance between the energy being absorbed and emitted by the earth for the time interval in question. It is of interest to ask what the natural variability of the net flux might be and whether, during times of climate change, signals of important climate change processes might be detected against this natural background variation; examples of these signals include evidence of ocean heat storage, the effects of El Niño, and the radiative effects of volcanic eruptions. In this paper, the authors review the significance of the net flux, survey the observational evidence from a range of satellite instruments over several decades, and analyze some of the most recent observations from the Clouds and the Earth’s Radiant Energy System (CERES) program to determine what signals and what natural variability might be expected in the TOA net flux. Based on this analysis, the use of broadband radiation measurements for global climate change studies can be assessed. [ABSTRACT FROM AUTHOR]

This paper examines variations of the surface air temperature (SAT) over China and the globe in the twentieth century simulated by 19 coupled climate models driven by historical natural and anthropogenic forcings. Most models perform well in simulating both the global and the Northern Hemispheric mean SAT evolutions of the twentieth century. The inclusion of natural forcings improves the simulation, in particular for the first half of the century. The reproducibility of the SAT averaged over China is lower than that of the global and hemispheric averages, but it is still acceptable. The contribution of natural forcings to the SAT over China in the first half of the century is not as robust as that to the global and hemispheric averages. No model could successfully produce the reconstructed warming over China in the 1920s. The prescribed natural and anthropogenic forcings in the coupled climate models mainly produce the warming trends and the decadal- to interdecadal-scale SAT variations with poor performances at shorter time scales. The prominent warming trend in the last half of the century over China and its acceleration in recent decades are weakly simulated. There are discrepancies between the simulated and observed regional features of the SAT trend over China. Few models could produce the summertime cooling over the middle part of eastern China (27°–36°N), while two models acceptably produce the meridional gradients of the wintertime warming trends, with north China experiencing larger warming. Limitations of the current state-of-the-art coupled climate models in simulating spatial patterns of the twentieth-century SAT over China cast a shadow upon their capability toward projecting credible geographical distributions of future climate change through Intergovernmental Panel on Climate Change (IPCC) scenario simulations. [ABSTRACT FROM AUTHOR]

Processes in the climate system that can either amplify or dampen the climate response to an external perturbation are referred to as climate feedbacks. Climate sensitivity estimates depend critically on radiative feedbacks associated with water vapor, lapse rate, clouds, snow, and sea ice, and global estimates of these feedbacks differ among general circulation models. By reviewing recent observational, numerical, and theoretical studies, this paper shows that there has been progress since the Third Assessment Report of the Intergovernmental Panel on Climate Change in (i) the understanding of the physical mechanisms involved in these feedbacks, (ii) the interpretation of intermodel differences in global estimates of these feedbacks, and (iii) the development of methodologies of evaluation of these feedbacks (or of some components) using observations. This suggests that continuing developments in climate feedback research will progressively help make it possible to constrain the GCMs’ range of climate feedbacks and climate sensitivity through an ensemble of diagnostics based on physical understanding and observations. [ABSTRACT FROM AUTHOR]

The present study examines variations in summertime (July–September) tropical cyclone (TC) activity over East Asia during the period 1951–2003. To represent TC activity, a total of 853 TC best tracks for the period were converted to TC passage frequencies (TPFs) within 5° × 5° latitude–longitude grids; TPFs are defined as the percentage values obtained by dividing the number of TC appearances in each grid box by the total number of TCs each year. Empirical orthogonal function analysis of the TPF showed three leading modes: two tropical modes that represent the long-term trend and the relationship with ENSO and one midlatitude mode that oscillates between south of Korea and southeast of Japan with an interannual time scale. The latter proved to be the most remarkable climatic fluctuation of summertime TC activity in the midlatitudes and is referred to as the East Asian dipole pattern (EADP) in this paper. Anomalous atmospheric flows directly connected to the EADP are an enhanced anticyclonic (cyclonic) circulation centering around Japan when the TPF is high south of Korea (southeast of Japan), thereby showing an equivalent barotropic structure in the entire troposphere. This regional circulation anomaly varies in conjunction with the zonally oriented quasi-stationary Rossby wave train in the upper troposphere. This wave train is meridionally trapped in the vicinity of the summer-mean jet stream; therefore, the mean jet stream alters its internal meandering structure according to the phase of the wave train. [ABSTRACT FROM AUTHOR]

Tropical warm pools appear as the primary mode in the distribution of tropical sea surface temperature (SST). Most previous studies have focused on the role of atmospheric processes in homogenizing temperatures in the warm pool and establishing the observed statistical SST distribution. In this paper, a hierarchy of models is used to illustrate both oceanic and atmospheric mechanisms that contribute to the establishment of tropical warm pools. It is found that individual atmospheric processes have competing effects on the SST distribution: atmospheric heat transport tends to homogenize SST, while the spatial structure of atmospheric humidity and surface wind speeds tends to remove homogeneity. The latter effects dominate, and under atmosphere-only processes there is no warm pool. Ocean dynamics counter this effect by homogenizing SST, and it is argued that ocean dynamics is fundamental to the existence of the warm pool. Under easterly wind stress, the thermocline is deep in the west and shallow in the east. Because of this, poleward Ekman transport of water at the surface, compensated by equatorward geostrophic flow below and linked by equatorial upwelling, creates a cold tongue in the east but homogenizes SST in the west, creating a warm pool. High clouds may also homogenize the SST by reducing the surface solar radiation over the warmest water, but the strength of this feedback is quite uncertain. Implications for the role of these processes in climate change are discussed. [ABSTRACT FROM AUTHOR]

This paper shows analytically that a reanalysis made with a frozen model can detect the warming trend due to an increase of greenhouse gases within the atmosphere at its full strength (at least 95% level) after a short transient (less than 100 analysis cycles). The analytical proof is obtained by taking into consideration the following three possible deficiencies in the model used to create first-guess fields: (i) the physical processes responsible for the observed trend (e.g., an increase of greenhouse gases) are completely absent from the model, (ii) the first-guess fields are affected by an initial drift caused by the imbalance between the model equilibrium and the analysis that contains trends due to the observations, and (iii) the model used in the reanalysis has a constant model bias. The imbalance contributes to a systematic reduction in the reanalysis trend compared to the observations. The analytic derivation herein shows that this systematic reduction can be very small (less than 5%) when the observations are available for twice-daily assimilation. Moreover, the frequent analysis cycle is essential to compensate for the impact due to relatively poor space coverage of the observational network, which effectively yields smaller weights assigned to observations in a global data assimilation system. Other major issues about using reanalysis for a long-term trend analysis, particularly the impact of the major changes in the global observing system that took place in the 1950s and in 1979, are not addressed. Here it is merely proven mathematically that using a frozen model in a reanalysis does not cause significant harm to the fidelity of the long-term trend in the reanalysis. [ABSTRACT FROM AUTHOR]

Precipitation in China is controlled by a combination of multiple weather systems and is susceptible to their spatiotemporal variability under climate warming. Based on the daily precipitation dataset developed by the China Meteorological Administration and ERA5 6-hourly data from 1979 to 2018, we detected tropical cyclones, extratropical cyclones, and fronts affecting mainland China of an altitude less than 1500 m using objective methods and identified their individually associated precipitation. We quantified climatological characteristics of precipitation associated with these three meteorological causes and their proportion of precipitation totals, and evaluated their relative contribution to change in precipitation. Results show that precipitation associated with tropical cyclones (TCP), extratropical cyclones (ETCP), and fronts (FRTP) accounted for 3.0%, 21.2%, and 20.4% of the total precipitation in China, and constituted the largest percentage in August, June, and January, respectively. The total proportion of these three types of precipitation exceeded 50% in more than 55% of China's regions. The high-value regions of corresponding precipitation were directly related to the locations of frequent occurrences of these weather systems. TCP and FRTP increased over the past four decades, while ETCP decreased. The western part of Northeast China and the middle and upper reaches of the Yangtze River show precipitation decreases, 37.8% of which is contributed by ETCP decreases. Precipitation increased in most regions of China during the dry season, 34.1% of which is contributed by FRTP increases. Among them, Northeast (Northwest) China significantly increased it precipitation by 14.4% decade−1 (21.8% decade−1), 33.6% (51.3%) of which is contributed by FRTP increases. [ABSTRACT FROM AUTHOR]

Recent international efforts at communicating climate change have begun using the notion of a climate indicator-a climate-related metric that can be used to track changes in the Earth system over time. Based upon a recently developed global-scale classification of daily air masses, this research examines the trends and variability in the frequencies of these air masses and then utilizes them to develop two nontraditional climate indicators: a warm/cool index (WCI) and a global extremes index (GEI). Results show that both indices trend significantly upward over the 40-yr period of record, indicating an increase in warm-based air masses (WCI) and extreme air masses (GEI). The two indices also exhibit a moderate (GEI) to strong (WCI) association with the global mean temperature record, multiple near-surface climate variables, and other existing climate indicators over that same time, showing promise as global indicators. Shorter-term variability in these indices also show a linear relationship between the WCI and changes in the Atlantic multidecadal oscillation and a nonlinear relationship between GEI and El Niño-Southern Oscillation. While many published climate indicators are based upon a single variable, and/or are regional in scope, the two indices presented herein are unique in that they are representative of the trends in the multivariate (and extreme, in the case of the GEI) weather conditions that are experienced near Earth's surface, while also being global in scope. [ABSTRACT FROM AUTHOR]

Here we explore the relationship between the global climatological characteristics of tropical cyclones (TCs) in climate models and the modeled large-scale environment across a large number of models. We consider the climatology of TCs in 30 climate models with a wide range of horizontal resolutions. We examine if there is a systematic relationship between the climatological diagnostics for the TC activity [number of tropical cyclones (NTC) and accumulated cyclone energy (ACE)] by hemisphere in the models and the environmental fields usually associated with TC activity, when examined across a large number of models. For low-resolution models, there is no association between a conducive environment and TC activity, when integrated over space (tropical hemisphere) and time (all years of the simulation). As the model resolution increases, for a couple of variables, in particular vertical wind shear, there is a statistically significant relationship in between the models' TC characteristics and the environmental characteristics, but in most cases the relationship is either nonexistent or the opposite of what is expected based on observations. It is important to stress that these results do not imply that there is no relationship between individual models' environmental fields and their TC activity by basin with respect to intraseasonal or interannual variability or due to climate change. However, it is clear that when examined across many models, the models' mean state does not have a consistent relationship with the models' mean TC activity. Therefore, other processes associated with the model physics, dynamical core, and resolution determine the climatological TC activity in climate models. [ABSTRACT FROM AUTHOR]

The Cenozoic climate of tropical South America was fundamental to the development of its biota, the most biodiverse on Earth. No previous studies have explicitly addressed how the very different atmospheric composition and Atlantic geometry during the early Eocene (approximately 55 million years ago) may have affected South American climate. At that time, the Atlantic Ocean was approximately half of its current width and the CO2 concentration of Earth's atmosphere ranged from ~550 to ~1500 ppm or even higher. Climate model simulations were performed to examine the effects of these major state changes on the climate of tropical South America. Reducing the width of the Atlantic by approximately half produces significant drying relative to modern climate. Drying is only partly offset by an enhancement of precipitation due to the higher CO2 of the early Eocene. The main mechanism for drier conditions is simple. Low-level air crosses the tropical Atlantic from North Africa in much less time for a narrower Atlantic (2 days) than for the modern Atlantic (~6 days); as a result, much less water is evaporated into the air and thus there is far lower moisture imported to the continent in the Eocene simulation than in the modern control. The progressive wetting (during the mid- to late Cenozoic) of the Amazon due to the widening Atlantic and the rising Andes, only partly offset by decreasing CO2 values, may have been partly responsible for the accumulating biodiversity of this region. [ABSTRACT FROM AUTHOR]

Mineral dust acts both as a tracer and a forcing agent of climate change. Past dust variability, imprinted in paleodust records from natural archives, offers the unique opportunity to reconstruct the global dust cycle within a range of possibilities that plausibly encompass future variations in response to climate change and land-cover and land-use changes. Dust itself has direct and indirect feedbacks on the climate system, through impacts on the atmosphere radiative budget and the carbon cycle. Starting from well-constrained reconstructions of the present and past dust cycle, we focus on quantifying dust direct impacts on the atmospheric radiation. We discuss the intrinsic effects of dust onto climate, and how changes in the global dust budget and surface conditions modulate the effective impacts on surface temperatures and precipitation. Most notably, the presence of dust tends to enhance the West African monsoon and warm the Arctic. We also highlight how different choices in terms of dust optical properties and size distributions may yield opposite results, and what are the observational constraints we can use to make an informed choice of model parameters. Finally, we discuss how dust variability might have influenced ongoing climate transitions in the past. In particular we found that a reduction in dust load, along with a reduced cryosphere cover, acted to offset Arctic warming during the deglaciation, potentially playing a role in shaping the Northern Hemisphere deglacial dynamics. [ABSTRACT FROM AUTHOR]

Given the recent changes in the Arctic sea ice, understanding the effects of the resultant polar warming on the global climate is of great importance. However, the interaction between the Arctic and midlatitude circulation involves a complex chain of mechanisms, which leaves state-of-the-art general circulation models unable to represent this interaction unambiguously. This study uses an idealized general circulation model to provide a process-based understanding of the sensitivity of the midlatitude circulation to the location of high-latitude warming. A simplified atmosphere is simulated with a single zonally localized midlatitude storm track, which is analogous to the storm tracks in the Northern Hemisphere. It is found that even small changes in the position of the forcing relative to that storm track can lead to very different responses in the midlatitude circulation. More specifically, it is found that heating concentrated in one region may cause a substantially stronger global response compared to when the same amount of heating is distributed across all longitudes at the same latitude. Linear interference between climatological and anomalous flow is an important component of the response, but it does not explain differences between different longitudes of the forcing. Feedbacks from atmospheric transient eddies are found to be associated with this strong response. A dependence between the climatological jet latitude and the jet response to polar surface heating is found. These results can be used to design and interpret experiments with complex state-of-the-art models targeted at Arctic–midlatitude interactions. [ABSTRACT FROM AUTHOR]

Here, we present the climatology of the planetary boundary layer depth in 18 contemporary general circulation models (GCMs) in simulations of the late-twentieth-century climate that were part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). We used a bulk Richardson methodology to establish the boundary layer depth from the 6-hourly synoptic-snapshot data available in the CMIP5 archives. We present an ensemble analysis of the climatological mean, diurnal cycle, and seasonal cycle of the boundary layer depth in these models and compare it to the climatologies from the ECMWF ERA-Interim reanalysis. Overall, we find that the CMIP5 models do a reasonably good job of reproducing the distribution of mean boundary layer depth, although the geographical patterns vary considerably between models. However, the models are biased toward weaker diurnal and seasonal cycles in the boundary layer depth and generally produce much deeper boundary layers at night and during the winter than are found in the reanalysis. These biases are likely to reduce the ability of these models to accurately represent other properties of the diurnal and seasonal cycles, and the sensitivity of these cycles to climate change. [ABSTRACT FROM AUTHOR]

Regional hydroclimate changes on decadal time scales contain substantial natural variability. This presents a challenge for the detection of anthropogenically forced hydroclimate changes on these spatiotemporal scales because the signal of anthropogenic changes is modest, compared to the noise of natural variability. However, previous studies have shown that this signal-to-noise ratio can be greatly improved in a large model ensemble where each member contains the same signal but different noise. Here, using multiple state-of-the-art large ensembles from two climate models, the authors quantitatively assess the detectability of anthropogenically caused decadal shifts in precipitation-minus-evaporation (PmE) mean state against natural variability, focusing on North America during 2000–50. Anthropogenic forcing is projected to cause detectable (signal larger than noise) shifts in PmE mean state relative to the 1950–99 climatology over 50%–70% of North America by 2050. The earliest detectable signals include, during November–April, a moistening over northeastern North America and a drying over southwestern North America and, during May–October, a drying over central North America. Different processes are responsible for these signals. Changes in submonthly transient eddy moisture fluxes account for the northeastern moistening and central drying, while monthly atmospheric circulation changes explain the southwestern drying. These model findings suggest that despite the dominant role of natural internal variability on decadal time scales, anthropogenic shifts in PmE mean state can be detected over most of North America before the middle of the current century. [ABSTRACT FROM AUTHOR]

Heat waves are climate extremes having significant environmental and social impacts. However, there is no universally accepted definition of a heat wave. The major goal of this study is to compare characteristics of continental U.S. warm season (May-September) heat waves defined using four different variables-temperature itself and three variables incorporating atmospheric moisture-all for differing intensity and duration requirements. To normalize across different locations and climates, daily intensity is defined using percentiles computed over the 1979-2013 period. The primary data source is the U.S. Historical Climatological Network (USHCN), with humidity data from the North American Regional Reanalysis (NARR) also tested and utilized. The results indicate that heat waves defined using daily maximum temperatures are more frequent and persistent than when based on minimum temperatures, with substantial regional variations in behavior. For all four temperature variables, heat waves based on daily minimum values have greater spatial coherency than for daily maximum values. Regionally, statistically significant upward trends (1979-2013) in heat wave frequency are identified, largest when based on daily minimum values, across variables. Other notable differences in behavior include a higher frequency of heat waves based on maximum temperature itself than for variables that include humidity, while daily minimum temperatures show greater similarity across all variables in this regard. Overall, the study provides a baseline to compare with results from climate model simulations and projections, for examining differing regional and large-scale circulation patterns associated with U.S. summer heat waves and for examining the role of land surface conditions in modulating regional variations in heat wave behavior. [ABSTRACT FROM AUTHOR]

It is one of the most robust projected responses of climate models to the increase of atmospheric CO2 concentration that the Arctic experiences a rapid warming with a magnitude larger than the rest of the world. While many processes are proposed as important, the relative contribution of individual processes to the Arctic warming is not often investigated systematically. Feedbacks are quantified in two different versions of an atmosphere-ocean GCM under idealized transient experiments based on an energy balance analysis that extends from the surface to the top of the atmosphere. The emphasis is placed on the largest warming from late autumn to early winter (October-December) and the difference from other seasons. It is confirmed that dominating processes vary with season. In autumn, the largest contribution to the Arctic surface warming is made by a reduction of ocean heat storage and cloud radiative feedback. In the annual mean, on the other hand, it is the albedo feedback that contributes the most, with increasing ocean heat uptake to the deeper layers working as a negative feedback. While the qualitative results are robust between the two models, they differ quantitatively, indicating the need for further constraint on each process. Ocean heat uptake, lower tropospheric stability, and low-level cloud response probably require special attention. [ABSTRACT FROM AUTHOR]

Temporal variability of meteorological variables and extreme weather events is projected to increase in many regions of the world during the next century. Artificial experiments using process-oriented terrestrial ecosystem models make it possible to isolate effects of temporal variability from effects of gradual climate change on terrestrial ecosystem functions and the system state. Such factorial experiments require two long-term climate datasets: 1) a control dataset that represents observed and projected climate and 2) a dataset with the same long-term mean as the control dataset but with altered short-term variability. Using a bias correction method, various climate datasets spanning different periods are harmonized and then combined with the control dataset with consistent time series for Europe during 1901-2100. Then, parameters of a distribution transformation function are estimated for individual meteorological variables to derive the second climate dataset, which has similar long-term means but reduced temporal variability. The transformation conserves the number of rainy days within a month and the shape of the daily meteorological data distributions, which is important to ensure that, for example, drought duration does not modify the suitability of localized vegetation type to precipitation regimes. The median absolute difference between daily data of both datasets is 5% to 20%. On average, decadal extreme values are reduced by 2% to 35%. Driving a terrestrial ecosystem model with both climate datasets shows a general higher gross primary production under reduced temporal climate variability. This effect of climate variability on productivity demonstrates the potential of the climate datasets for studying various effects of temporal variability on ecosystem state and functions over large domains. [ABSTRACT FROM AUTHOR]

Understanding the long-term change of extreme temperature events is important to the detection and attribution of climate change. It is unclear, however, how much effect urbanization has had on trends of the extreme temperature indices series constructed based on the commonly used datasets on a subcontinental scale. Applying a homogenized daily temperature dataset of the national reference climate stations and basic meteorological stations, and a rural station network previously developed, urbanization effects on trends of extreme temperature indices in mainland China for the time period 1961-2008 are evaluated. It is found that 1) the country-averaged annual- and seasonal-mean extreme temperature indices series generally experience statistically significant trends; 2) annual-mean urbanization effects in the country as a whole are statistically significant for daily minimum temperature (Tmin), maximum temperature (Tmax), and mean temperature of Tmin and Tmax (Tavg), reaching 0.070°, 0.023°, and 0.047°C (10 yr)−1, respectively, with the largest values for annual-mean Tmin occurring in north China; 3) annual- and seasonal-mean urbanization effects for the declining diurnal temperature range (DTR) are highly significant, and the largest seasonal-mean DTR decline because of urbanization occurs in winter and spring; 4) annual-mean urbanization effects for the lowest Tmin, summer days, tropical nights, and frost days series are significant, but an insignificant urbanization effect is detected for icing days series; 5) urbanization has led to a highly significant decline of annual cold nights at a rate of −1.485 days (10 yr)−1 and a highly significant increase of annual warm nights at a rate of 2.264 days (10 yr)−1. Although urbanization effects are also significant for cold days and warm days, they are relatively smaller, and 6) the smallest absolute values of annual-mean urbanization effects for most of the indices series are found to dominantly appear during 1966-76, a well-known deurbanization period resulting from the Cultural Revolution. [ABSTRACT FROM AUTHOR]

An ensemble of simulations from different versions of the Community Atmosphere Model in the Community Earth System Model (CESM) is used to investigate the processes responsible for the intermodel spread in climate sensitivity. In the CESM simulations, the climate sensitivity spread is primarily explained by shortwave cloud feedbacks on the equatorward flank of the midlatitude storm tracks. Shortwave cloud feedbacks have been found to explain climate sensitivity spread in previous studies, but the location of feedback differences was in the subtropics rather than in the storm tracks as identified in CESM. The cloud-feedback relationships are slightly stronger in the winter hemisphere. The spread in climate sensitivity in this study is related both to the cloud-base state and to the cloud feedbacks. Simulated climate sensitivity is correlated with cloud-fraction changes on the equatorward side of the storm tracks, cloud condensate in the storm tracks, and cloud microphysical state on the poleward side of the storm tracks. Changes in the extent and water content of stratiform clouds (that make up cloud feedback) are regulated by the base-state vertical velocity, humidity, and deep convective mass fluxes. Within the storm tracks, the cloud-base state affects the cloud response to CO2-induced temperature changes and alters the cloud feedbacks, contributing to climate sensitivity spread within the CESM ensemble. [ABSTRACT FROM AUTHOR]

This study examines the long-range dependency, climate noise characteristics, and nonlinear temperature trends of eight Antarctic stations from the Reference Antarctic Data for Environmental Research (READER) dataset. Evidence is shown that Antarctic temperatures are long-range dependent. To identify possible nonlinear trends, the ensemble empirical mode decomposition (EEMD) method is used, and then the question of whether the observed trends can arise from internal atmospheric fluctuations is examined. To answer this question, surrogate data are generated from two paradigmatic null models: a standard first-order autoregressive process representing a short-range dependent process and a fractional integrated process representing a long-range dependent process. It is found that three of the eight stations show statistically significant trends when tested against the short-range dependent process while only the Faraday--Vernadsky station temperature time series shows a significant trend when tested against the long-range dependent null model. All other considered stations show no trends that are statistically significant against the two null models, and thus they can be explained by internal atmospheric variability. These results imply that more attention should be given to assessing the correlation structure of climate time series. [ABSTRACT FROM AUTHOR]

The Global Land–Atmosphere Coupling Experiment (GLACE) built a framework to estimate the strength of the land–atmosphere interaction across many weather and climate models. Within this framework, GLACE-type experiments are performed with a single atmospheric model coupled to three different land models. The precipitation time series is decomposed into three frequency bands to investigate the large-scale connection between external forcing, precipitation variability and predictability, and land–atmosphere coupling strength. It is found that coupling to different land models or prescribing subsurface soil moisture does not change the global pattern of precipitation predictability and variability too much. However, the regional impact of soil moisture can be highlighted by calculating the land–atmosphere coupling strength, which shows very different patterns for the three models. The estimated precipitation predictability and land–atmosphere coupling strength is mainly associated with the low-frequency component of precipitation (periods beyond 3 weeks). Based on these findings, the land–atmosphere coupling strength is conceptually decomposed into the impact of low-frequency external forcing and the impact of soil moisture. Because most models participating in GLACE have overestimated the low-frequency component of precipitation, a calibration to the GLACE-estimated land–atmosphere coupling strength is performed. The calibrated coupling strength is generally weaker, but the global pattern does not change much. This study provides an important clarification of land–atmosphere coupling strength and increases the understanding of the land–atmosphere interaction. [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) changes constitute a major indicator and driver of climate changes induced by greenhouse gas increases. The objective of the present study is to investigate the role played by the detailed structure of the SST change on the large-scale atmospheric circulation and the distribution of precipitation. For that purpose, simulations from the Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL-CM4) are used where the carbon dioxide (CO2) concentration is doubled. The response of IPSL-CM4 is characterized by the same robust mechanisms affecting the other coupled models in global warming simulations, that is, an increase of the hydrological cycle accompanied by a global weakening of the large-scale circulation. First, purely atmospheric simulations are performed to mimic the results of the coupled model. Then, specific simulations are set up to further study the underlying atmospheric mechanisms. These simulations use different prescribed SST anomalies, which correspond to a linear decomposition of the IPSL-CM4 SST changes in global, longitudinal, and latitudinal components. The simulation using a globally uniform increase of the SST is able to reproduce the modifications in the intensity of the hydrological cycle or in the mean upward mass flux, which also characterize the double CO2 simulation with the coupled model. But it is necessary (and largely sufficient) to also take into account the zonal-mean meridional structure of the SST changes to represent correctly the changes in the Hadley circulation strength or the zonal-mean precipitation changes simulated by the coupled model, even if these meridional changes by themselves do not change the mean thermodynamical state of the tropical atmosphere. The longitudinal SST anomalies of IPSL-CM4 also have an impact on the precipitation and large-scale tropical circulation and tend to introduce different changes over the Pacific and Atlantic Oceans. The longitudinal SST changes are demonstrated to have a smaller but opposite effect from that of the meridional anomalies on the Hadley cell circulations. Results indicate that the uncertainties in the simulated meridional patterns of the SST warming may have major consequences on the assessment of the changes of the Hadley circulation and zonal-mean precipitation in future climate projections. [ABSTRACT FROM AUTHOR]

A synoptic climatological weather classification scheme incorporating both surface and upper-air data is developed for the central United States based on an automated two-step cluster analysis. It employs daily NCEP–NCAR reanalysis data over all seasons of 57 yr (1948–2004) in creating synoptic types from surface and upper-air (925, 850, 700, and 500 hPa) temperature and humidity data as well as sea level pressure, geopotential heights, and winds aloft. The cluster analysis creates 10 synoptic types exhibiting distinct seasonal preferences, with three each that occur primarily in summer and winter, and four that occur primarily in winter and the transition seasons, particularly spring. The typing scheme generates synoptic patterns largely characterized by distinctive surface circulations, baroclinic vertical structure, and thermal advection. Interannual variations occur in the frequencies of the synoptic types, some of which are out of phase with each other. The annual frequencies of two winter synoptic types, associated respectively with strong zonal and meridional flow, are highly correlated (r ≫ 0.63–0.73) to the phase of the Pacific–North American teleconnection pattern, while Niño-3.4 equatorial Pacific sea surface temperatures are linked to a synoptic type producing low pressure around the Gulf Coast. [ABSTRACT FROM AUTHOR]

Aspects of the tropical atmospheric response to El Niño related to the global energy and water cycle are examined using satellite retrievals from the Tropical Rainfall Measuring Mission and the Advanced Microwave Scanning Radiometer-E and simulations from the Goddard Institute for Space Studies (GISS) general circulation model (GCM). The El Niño signal is extracted from climate fields using a linear cross-correlation technique that captures local and remote in-phase and lagged responses. Passive microwave and radar precipitation anomalies for the 1997/98 and 2002/03 El Niños and the intervening La Niña are highly correlated, but anomalies in stratiform–convective rainfall partitioning in the two datasets are not. The GISS GCM produces too much rainfall in general over ocean and too little over land. Its atmospheric response to El Niño is weaker and decays a season too early. Underestimated stratiform rainfall fraction (SRF) and convective downdraft mass flux in the GISS GCM and excessive shallow convective and low stratiform cloud result in latent heating that peaks at lower altitudes than inferred from the data. The GISS GCM also underestimates the column water vapor content throughout the Tropics, which causes it to overestimate outgoing longwave radiation. The response of both quantities to interannual Hadley circulation anomalies is too weak. The GISS GCM’s Walker circulation also exhibits a weak remote response to El Niño, especially over the Maritime Continent and western Indian Ocean. This appears to be a consequence of weak static stability due to the model’s lack of upper-level stratiform anvil heating, excessive low-level heating, and excessive dissipation due to cumulus momentum mixing. Our results suggest that parameterizations of mesoscale updrafts, convective downdrafts, and cumulus-scale pressure gradient effects on momentum transport are keys to a reasonable GISS GCM simulation of tropical interannual variability. [ABSTRACT FROM AUTHOR]

It is argued that simulations of the twentieth century performed with coupled global climate models with specified historical changes in external radiative forcing can be interpreted as climate hindcasts. A simple Bayesian method for postprocessing such simulations is described, which produces probabilistic hindcasts of interdecadal temperature changes on large spatial scales. Hindcasts produced for the last two decades of the twentieth century are shown to be skillful. The suggestion that skillful decadal forecasts can be produced on large regional scales by exploiting the response to anthropogenic forcing provides additional evidence that anthropogenic change in the composition of the atmosphere has influenced the climate. In the absence of large negative volcanic forcing on the climate system (which cannot presently be forecast), it is predicted that the global mean temperature for the decade 2000–09 will lie above the 1970–99 normal with a probability of 0.94. The global mean temperature anomaly for this decade relative to 1970–99 is predicted to be 0.35°C with a 5%–95% confidence range of 0.21°–0.48°C. [ABSTRACT FROM AUTHOR]

The performance of the atmospheric component of the new Hadley Centre Global Environmental Model (HadGEM1) is assessed in terms of its ability to represent a selection of key aspects of variability in the Tropics and extratropics. These include midlatitude storm tracks and blocking activity, synoptic variability over Europe, and the North Atlantic Oscillation together with tropical convection, the Madden–Julian oscillation, and the Asian summer monsoon. Comparisons with the previous model, the Third Hadley Centre Coupled Ocean–Atmosphere GCM (HadCM3), demonstrate that there has been a considerable increase in the transient eddy kinetic energy (EKE), bringing HadGEM1 into closer agreement with current reanalyses. This increase in EKE results from the increased horizontal resolution and, in combination with the improved physical parameterizations, leads to improvements in the representation of Northern Hemisphere storm tracks and blocking. The simulation of synoptic weather regimes over Europe is also greatly improved compared to HadCM3, again due to both increased resolution and other model developments. The variability of convection in the equatorial region is generally stronger and closer to observations than in HadCM3. There is, however, still limited convective variance coincident with several of the observed equatorial wave modes. Simulation of the Madden–Julian oscillation is improved in HadGEM1: both the activity and interannual variability are increased and the eastward propagation, although slower than observed, is much better simulated. While some aspects of the climatology of the Asian summer monsoon are improved in HadGEM1, the upper-level winds are too weak and the simulation of precipitation deteriorates. The dominant modes of monsoon interannual variability are similar in the two models, although in HadCM3 this is linked to SST forcing, while in HadGEM1 internal variability dominates. Overall, analysis of the phenomena considered here indicates that HadGEM1 performs well and, in many important respects, improves upon HadCM3. Together with the improved representation of the mean climate, this improvement in the simulation of atmospheric variability suggests that HadGEM1 provides a sound basis for future studies of climate and climate change. [ABSTRACT FROM AUTHOR]

Interannual and multidecadal extremes in Atlantic hurricane activity are shown to result from a coherent and interrelated set of atmospheric and oceanic conditions associated with three leading modes of climate variability in the Tropics. All three modes are related to fluctuations in tropical convection, with two representing the leading multidecadal modes of convective rainfall variability, and one representing the leading interannual mode (ENSO). The tropical multidecadal modes are shown to link known fluctuations in Atlantic hurricane activity, West African monsoon rainfall, and Atlantic sea surface temperatures, to the Tropics-wide climate variability. These modes also capture an east–west seesaw in anomalous convection between the West African monsoon region and the Amazon basin, which helps to account for the interhemispheric symmetry of the 200-hPa streamfunction anomalies across the Atlantic Ocean and Africa, the 200-hPa divergent wind anomalies, and both the structure and spatial scale of the low-level tropical wind anomalies, associated with multidecadal extremes in Atlantic hurricane activity. While there are many similarities between the 1950–69 and 1995–2004 periods of above-normal Atlantic hurricane activity, important differences in the tropical climate are also identified, which indicates that the above-normal activity since 1995 does not reflect an exact return to conditions seen during the 1950s–60s. In particular, the period 1950–69 shows a strong link to the leading tropical multidecadal mode (TMM), whereas the 1995–2002 period is associated with a sharp increase in amplitude of the second leading tropical multidecadal mode (TMM2). These differences include a very strong West African monsoon circulation and near-average sea surface temperatures across the central tropical Atlantic during 1950–69, compared with a modestly enhanced West African monsoon and exceptionally warm Atlantic sea surface temperatures during 1995–2004. It is shown that the ENSO teleconnections and impacts on Atlantic hurricane activity can be substantially masked or accentuated by the leading multidecadal modes. This leads to the important result that these modes provide a substantially more complete view of the climate control over Atlantic hurricane activity during individual seasons than is afforded by ENSO alone. This result applies to understanding differences in the “apparent” ENSO teleconnections not only between the above- and below-normal hurricane decades, but also between the two sets of above-normal hurricane decades. [ABSTRACT FROM AUTHOR]

Climatological planetary albedo obtained from the International Satellite Cloud Climatology Project (ISCCP) D-series flux dataset is broken down into contributions from the surface and atmosphere in cryosphere regions. The atmosphere accounts for much more of climatological planetary albedo (≥75%) than the surface at all times of the year. The insignificance of the surface contribution over highly reflective cryosphere regions is attributed mostly to the damping effect of the atmosphere. The overlying atmosphere attenuates the surface’s contribution to climatological planetary albedo by reducing the number of solar photons initially reaching the surface and the number of photons initially reflected by the surface that actually reach the top of the atmosphere. The ISCCP datasets were also used to determine the relative contributions of the surface and atmosphere to seasonal and interannual planetary albedo variability in cryosphere regions. Even damped by the atmosphere to the same degree as in the climatological case, the surface contribution dominates the variability in planetary albedo on seasonal and interannual time scales. The surface accounts for about 75% of the change in climatological planetary albedo from one season to another with similar zenith angle and more than 50% of its interannual variability at nearly all times of the year, especially during seasons with extensive snow and sea ice extent. The dominance of the surface in planetary albedo variability is because surface albedo variability associated with snow and ice fluctuations is significantly larger than atmospheric albedo variability due to cloud fluctuations. The large effect of snow and ice variations on planetary albedo variability suggests that if cloud fields do not change much in a future warmer climate, a retreat of snow cover or sea ice would lead to a significant increase in net incoming solar radiation, resulting in an enhancement of high-latitude climate sensitivity. [ABSTRACT FROM AUTHOR]

The dominant air–sea feedbacks that are at play in the tropical Atlantic are revisited, using the 1958–2002 NCEP reanalysis. To separate between different modes of variability and distinguish between cause and effect, a lagged rotated maximum covariance analysis (MCA) of monthly sea surface temperature (SST), wind, and surface heat flux anomalies is performed. The dominant mode is the ENSO-like zonal equatorial SST mode, which has its maximum amplitude in boreal summer and is a strongly coupled ocean–atmosphere mode sustained by a positive feedback between wind and SST. The turbulent heat flux feedback is negative, except west of 25°W where it is positive, but countered by a negative radiative feedback associated with the meridional displacement of the ITCZ. As the maximum covariance patterns change little between lead and lag conditions, the in-phase covariability between SST and the atmosphere can be used to infer the atmospheric response to the SST anomaly. The second climate mode involves an SST anomaly in the tropical North Atlantic, which is primarily generated by the surface heat flux and, in boreal winter, wind changes off the coast of Africa. After it has been generated, the SST anomaly is sustained in the deep Tropics by the positive wind–evaporation–SST feedback linked to the wind response to the SST. However, north of about 10°N where the SST anomaly is largest, the wind response is weak and the heat flux feedback is negative, thus damping the SST anomaly. As the in-phase maximum covariance patterns primarily reflect the atmospheric forcing of the SST, simultaneous correlations cannot be used to describe the atmospheric response to the SST anomaly, except in the deep Tropics. Using instead the maximum covariance patterns when SST leads the atmosphere reconciles the results of recent atmospheric general circulation model experiments with the observations. [ABSTRACT FROM AUTHOR]

The Northern Hemisphere annular mode (NAM) accounts for a significant fraction of the extratropical wintertime atmospheric variability. The dynamics of NAM events have been studied on monthly time scales, but little is known about the physical mechanisms that give rise to NAM variability on shorter time scales. Composite diagnostic analyses based on daily NAM indices are performed with a goal of identifying the dominant processes responsible for the growth and decay of large-amplitude positive and negative NAM events on short intraseasonal time scales. Transformed Eulerian mean, piecewise potential vorticity inversions, and regional Plumb flux diagnoses are employed to deduce the proximate forcings of the zonal-mean wind tendency during maturing and declining NAM stages. A remarkable degree of reverse symmetry is observed between the zonal-mean dynamical evolution of positive and negative NAM events. Anomalous equatorward and downward (poleward and upward) Eliassen–Palm fluxes are observed during the maturation of positive (negative) NAM events, consistent with index of refraction considerations and an indirect downward stratospheric influence. The associated patterns of anomalous wave driving provide the primary forcing of the zonal wind tendency field. Spectral analyses reveal that both the stratospheric and tropospheric patterns of wave driving are primarily due to low-frequency planetary-scale eddies. Regional wave activity flux diagnoses further illustrate that this wave-driving pattern represents the zonal-mean manifestation of planetary-scale anomalies over the North Atlantic that are linked to local anomalies in stationary wave forcing. The decay of NAM events coincides with the collapse in the pattern of anomalous stationary wave forcing over the North Atlantic region. Our diagnostic results indicate that both (i) synoptic eddies and (ii) direct downward stratospheric forcing provide second-order reinforcing contributions to the intraseasonal dynamical evolution of NAM events. [ABSTRACT FROM AUTHOR]

The homogeneity of the ECMWF 40-yr Re-Analysis (ERA-40) is assessed. This is done by comparing ERA-40 data with results from the NCEP–NCAR reanalysis and also by investigating a known relationship between a modeled (latent heat flux) and an external (SST) quantity. The direct comparison between the two reanalyses reveals a lot of inhomogeneities. They occur mainly in the Southern Hemisphere and before 1980. While observational density was sufficient to effectively constrain the models in the Northern Hemisphere, it was not in the Southern Hemisphere. From the investigation of the relationship between latent heat flux and SST it is found that, because of an increasing amount of data, the reanalysis results become more reliable toward the end of the reanalysis period (approximately after 1980). When using the reanalysis data to investigate climate change issues care has to be taken not to confuse the inhomogeneities with real changes. [ABSTRACT FROM AUTHOR]

The Luzon Strait transport (LST) from the Pacific into the South China Sea (SCS) is examined using results from a high-resolution ocean general circulation model. The LST from the model has a mean value of 2.4 Sv (Sv ≡ 106 m³ s-4) and reaches its seasonal maximum (6.1 Sv westward) in winter and seasonal minimum (0.9 Sv eastward) in summer. Both the annual mean and seasonal variation of LST compare favorably with earlier observations. On an interannual time scale, LST tends to be higher during El Niño years and lower during La Niña years, with its maximum (minimum) leading the mature phase of El Niño (La Niña) by 1 month. The interannual variation of LST appears to be oppositely phased with the Kuroshio transport east of Luzon, indicating a possible nonlinear hysteresis of the Kuroshio as a driving mechanism of LST. For the annual average, water leaving the SCS in the south is of higher temperature than that with LST, thus producing a cooling advection in the upper 405 m equivalent to a surface heat flux of −19 W m-2. Most of this cooling advection is balanced by the atmospheric heating (17 W m-2). From late spring to early fall, surface heat flux is the primary heating process; only a small part of the heat content change can be explained by heat advection. But, in winter, heat advection seems to be the only important process responsible for the cooling in the upper layer of the SCS. The interannual variation of the upper-layer heat content has a strong signature of ENSO, cooling in the development of El Niño and warming in the development of La Niña. An oceanic connection is revealed, in which LST seems to be a key process conveying the impact of the Pacific ENSO into the SCS. [ABSTRACT FROM AUTHOR]

The separate climate effects of middle-atmospheric and tropospheric CO2 doubling have been simulated and analyzed with the ECHAM middle-atmosphere climate model. To this end, the CO2 concentration has been separately doubled in the middle-atmosphere, the troposphere, and the entire atmosphere, and the results have been compared to a control run. During NH winter, the simulated uniformly doubled CO2 climate shows an increase of the stratospheric residual circulation, a small warming in the Arctic lower stratosphere, a weakening of the zonal winds in the Arctic middle-atmosphere, an increase of the NH midlatitude tropospheric westerlies, and a poleward shift of the SH tropospheric westerlies. The uniformly doubled CO2 response in most regions is approximately equal to the sum of the separate responses to tropospheric and middle-atmospheric CO2 doubling. The increase of the stratospheric residual circulation can be attributed for about two-thirds to the tropospheric CO2 doubling and one-third to the middle-atmospheric CO2 doubling. This increase contributes to the Arctic lower-stratospheric warming and, through the thermal wind relationship, to the weakening of the Arctic middle-atmospheric zonal wind. The increase of the tropospheric NH midlatitude westerlies can be attributed mainly to the middle-atmospheric CO2 doubling, indicating the crucial importance of the middle-atmospheric CO2 doubling for the tropospheric climate change. Results from an additional experiment show that the CO2 doubling above 10 hPa, which is above the top of many current GCMs, also causes significant changes in the tropospheric climate. [ABSTRACT FROM AUTHOR]

The remote impact of tropical Pacific and North Atlantic climate forcing on the tropical Atlantic sea surface temperature variability is assessed using both a traditional statistical correlation method and a model-aided dynamic method. Consistently, both assessment methods suggest that the remote impact contributes to nearly half of the variance of the tropical Atlantic sea surface temperature variability at interannual and decadal time scales. In the meantime, the other half of the sea surface temperature variability is generated predominantly in the tropical Atlantic climate system, with local ocean–atmosphere coupling playing a critical role. Furthermore, the leading sea surface temperature variability modes seem also to originate predominantly internally in the tropical Atlantic climate system. The main effect of the remote impact is therefore an enhancement of the variance of these variability modes. This model study also shows some differences between the statistical and dynamic assessment methods, which may have implications on the methodology of the assessment as well as the dynamics of the system. [ABSTRACT FROM AUTHOR]

Four global coupled climate models with different combinations of atmosphere, ocean, land surface, and sea ice components are compared in idealized forcing (1% CO2 increase) experiments. The four models are the Climate System Model (CSM), the Parallel Climate Model (PCM), the PCM/CSM Transition Model (PCTM), and the Community Climate System Model (CCSM). The hypothesis is posed that models with similar atmospheric model components should show a similar globally averaged dynamically coupled response to increasing CO2 in spite of different ocean, sea ice, and land formulations. Conversely, models with different atmospheric components should be most different in terms of the coupled globally averaged response. The two models with the same atmosphere and sea ice but different ocean components (PCM and PCTM) have the most similar response to increasing CO2, followed closely by CSM with comparable atmosphere and different ocean and sea ice from either PCM or PCTM. The fourth model, CCSM, has a different response from the other three and, in particular, is different from PCTM in spite of having the same ocean and sea ice but different atmospheric model component. These results support the hypothesis that, to a greater degree than the other components, the atmospheric model “manages” the relevant global feedbacks including sea ice albedo, water vapor, and clouds. The atmospheric model also affects the meridional overturning circulation in the ocean, as well as the ocean heat uptake characteristics. This is due to changes in surface fluxes of heat and freshwater that affect surface density in the ocean. For global sensitivity measures, the ocean, sea ice, and land surface play secondary roles, even though differences in these components can be important for regional climate changes. [ABSTRACT FROM AUTHOR]