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In recent years, various early warning signals of critical transition have been presented, such as autocorrelation at lag 1 [AR(1)], variance, the propagator based on detrended fluctuation analysis (DFA-propagator), and so on. Many studies have shown that the climate system has the characteristics of long-term memory (LTM). Will the LTM characteristics of the climate system change as it approaches possible critical transition points? In view of this, the present paper first studies whether the LTM of several folding (folded bifurcation) models changes consistently as they approach their critical points slowly by the rescaled range (R/S) analysis. The results of numerical experiments show that when the control parameters of the folding model are close to its critical threshold, the Hurst exponent H exhibits an almost monotonic increase (significance level α = 0.05). We compare the performance of R/S with the existing indicators, including AR(1), variance, and DFA-propagator, and find that R/S is a perfectly valid alternative. When there is no extra false noise, AR(1) and variance have good early warning effects. After the addition of extra Gaussian white noise of different intensities, the values of AR(1) and variance change significantly. As a result, the DFA-propagator based on AR(1) calibration also changed significantly. Compared with the other three indicators, the early warning effect of H has stronger ability to resist the interference of external false signals. To further verify the validity of increasing H, paleoclimate reconstruction of Cariaco Basin sediment core grayscale record with long trends filtered out is studied by R/S analysis. The other three early warning signals are calculated in the same way. The data contain a well-known abrupt climate change: the transition between the Younger Dryas (YD) and the Holocene. We find that approximately 300 years before this abrupt climate change occurred, before 11.7 kyr BP, the LTM exponents for Cariaco Basin deglacial grayscale data present an obvious increasing trend at a significant level of α = 0.05. Meanwhile, the variation trend of H and DFA-propagator is basically similar. This shows that increasing H by R/S analysis is an effective early warning signal, which indicates that a dynamic system is approaching its possible critical transition points; H is a completely valid alternative signal for AR(1) and DFA-propagator. The main conclusion of this paper is based on numerical experiments. The precise relationship between H and the stability of the underlying state approaching the transition needs to be further studied. [ABSTRACT FROM AUTHOR]

ISCCP continues to quantify the global distribution and diurnal-to-interannual variations of cloud properties in a revised version. This paper summarizes assessments of the previous version, describes refinements of the analysis and enhanced features of the product design, discusses the few notable changes in the results, and illustrates the long-term variations of global mean cloud properties and differing high cloud changes associated with ENSO. The new product design includes a global, pixel-level product on a 0.1° grid, all other gridded products at 1.0°-equivalent equal area, separate satellite products with ancillary data for regional studies, more detailed, embedded quality information, and all gridded products in netCDF format. All the data products including all input data, expanded documentation, the processing code, and an operations guide are available online. Notable changes are 1) a lowered ice–liquid temperature threshold, 2) a treatment of the radiative effects of aerosols and surface temperature inversions, 3) refined specification of the assumed cloud microphysics, and 4) interpolation of the main daytime cloud information overnight. The changes very slightly increase the global monthly mean cloud amount with a little more high cloud and a little less middle and low cloud. Over the whole period, total cloud amount slowly decreases caused by decreases in cumulus/altocumulus; consequently, average cloud-top temperature and optical thickness have increased. The diurnal and seasonal cloud variations are very similar to earlier versions. Analysis of the whole record shows that high cloud variations, but not low clouds, exhibit different patterns in different ENSO events. Significance Statement: This paper reports on the evolution of the research goals and satellite cloud data products produced by ISCCP, a long-term international project, which is now fully operational. The growing length of record with 10-km and 3-h sampling makes possible studies of cloud variations from diurnal-to-weather scale (cloud process scale) to climate variation scale. In particular the length of record includes many examples of ENSO and is beginning to encompass the slower modes of ocean variation, allowing studies of the role of cloud feedbacks in coupling the atmosphere and ocean circulations. [ABSTRACT FROM AUTHOR]

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]

Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifthgeneration reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979-2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments. [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]

Traditionally, the daily average air temperature at a weather station is computed by taking the mean of two values, the maximum temperature (Tmax) and the minimum temperature (Tmin), over a 24-h period. These values form the basis for numerous studies of long-term climatologies (e.g., 30-yr normals) and recent temperature trends and changes. However, many first-order weather stations-such as those at airports-also record hourly temperature data. Using an average of the 24 hourly temperature readings to compute daily average temperature has been shown to provide a more precise and representative estimate of a given day's temperature. This study assesses the spatial variability of the differences in these two methods of daily temperature averaging [i.e., (Tmax 1 Tmin)/2; average of 24 hourly temperature values] for 215 first-order weather stations across the conterminous United States (CONUS) over the 30-yr period 1981-2010. A statistically significant difference is shown between the two methods, as well as consistent overestimation of temperature by the traditional method [(Tmax 1 Tmin)/2], particularly in southern and coastal portions of the CONUS. The explanation for the long-term difference between the two methods is the underlying assumption for the twice-daily method that the diurnal curve of temperature is symmetrical. Moreover, this paper demonstrates a spatially coherent pattern in the difference compared to the most recent part of the temperature record (2001-15). The spatial and temporal differences shown have implications for assessments of the physical factors influencing the diurnal temperature curve, as well as the exact magnitude of contemporary climate change. [ABSTRACT FROM AUTHOR]

This paper investigates changes in the tropical tropopause layer (TTL) in response to carbon dioxide increase and surface warming separately in an atmospheric general circulation model, finding that both effects lead to a warmer tropical tropopause. Surface warming also results in an upward shift of the tropopause. A detailed heat budget analysis is performed to quantify the contributions from different radiative and dynamic processes to changes in the TTL temperature. When carbon dioxide increases with fixed surface temperature, a warmer TTL mainly results from the direct radiative effect of carbon dioxide increase. With surface warming, the largest contribution to the TTL warming comes from the radiative effect of the warmer troposphere, which is partly canceled by the radiative effect of the moistening at the TTL. Strengthening of the stratospheric circulation following surface warming cools the lower stratosphere dynamically and radiatively via changes in ozone. These two effects are of comparable magnitudes. This circulation change is the main cause of temperature changes near 63 hPa but is weak near 100 hPa. Contributions from changes in convection and clouds are also quantified. These results illustrate the heat budget analysis as a useful tool to disentangle the radiative-dynamical-chemical-convective coupling at the TTL and to facilitate an understanding of intermodel difference. [ABSTRACT FROM AUTHOR]

In fields such as climate science, it is common to compile an ensemble of different simulators for the same underlying process. It is a striking observation that the ensemble mean often outperforms at least half of the ensemble members in mean squared error (measured with respect to observations). In fact, as demonstrated in the most recent IPCC report, the ensemble mean often outperforms all or almost all of the ensemble members across a range of climate variables. This paper shows that these could be mathematical results based on convexity and averaging but with implications for the properties of the current generation of climate simulators. [ABSTRACT FROM AUTHOR]

Few if any high-resolution (annually resolved) paleoclimate records are available for the Hawaiian Islands prior to ~1850 CE, after which some instrumental records start to become available. This paper shows how atmospheric teleconnection patterns between North America and the northeastern North Pacific (NNP) allow for reconstruction of Hawaiian Islands rainfall using remote proxy information from North America. Based on a newly available precipitation dataset for the state of Hawaii and observed and reconstructed December-February (DJF) sea level pressures (SLPs) in the North Pacific Ocean, the authors make use of a strong relationship between winter SLP variability in the northeast Pacific and corresponding DJF Hawaii rainfall variations to reconstruct and evaluate that season's rainfall over the period 1500-2012 CE. A general drying trend, though with substantial decadal and longer-term variability, is evident, particularly during the last ~160 years. Hawaiian Islands rainfall exhibits strong modulation by El Niño-Southern Oscillation (ENSO), as well as in relation to Pacific decadal oscillation (PDO)-like variability. For significant periods of time, the reconstructed large-scale changes in the North Pacific SLP field described here and by construction the long-term decline in Hawaiian winter rainfall are broadly consistent with long-term changes in tropical Pacific sea surface temperature (SST) based on ENSO reconstructions documented in several other studies, particularly over the last two centuries. Also noted are some rather large multidecadal fluctuations in rainfall (and hence in NNP SLP) in the eighteenth century of undetermined provenance. [ABSTRACT FROM AUTHOR]

A full understanding of the causes of the severe drought seen in the Sahel in the latter part of the twentieth-century remains elusive some 25 yr after the height of the event. Previous studies have suggested that this drying trend may be explained by either decadal modes of natural variability or by human-driven emissions (primarily aerosols), but these studies lacked a sufficiently large number of models to attribute one cause over the other. In this paper, signatures of both aerosol and greenhouse gas changes on Sahel rainfall are illustrated. These idealized responses are used to interpret the results of historical Sahel rainfall changes from two very large ensembles of fully coupled climate models, which both sample uncertainties arising from internal variability and model formulation. The sizes of these ensembles enable the relative role of human-driven changes and natural variability on historic Sahel rainfall to be assessed. The paper demonstrates that historic aerosol changes are likely to explain most of the underlying 1940-80 drying signal and a notable proportion of the more pronounced 1950-80 drying. [ABSTRACT FROM AUTHOR]

The primary focus of this paper is the analysis of the roles of long-term increases in carbon dioxide (CO2) and sea surface temperatures (used as indicators of climate change) and man-made halocarbons (indicators of chemical ozone depletion linked to halogens) in explaining the observed trend of ozone in the tropical lower stratosphere and implications for related variables including temperature and tropopause height. Published estimates indicate a decrease of approximately 10% in observed ozone concentrations in this region between 1979 and 2005. Using a coupled chemistry–climate atmosphere model forced by observed sea surface temperatures and surface concentrations of long-lived greenhouse gases and halocarbons, the authors show that the simulations display substantial decreases in tropical ozone that compare well in both latitudinal and vertical structure with those observed. Based on sensitivity simulations, the analysis indicates that the decreases in the lower stratospheric (85–50 hPa) tropical ozone distribution are mostly associated with increases in CO2 and sea surface temperatures, in contrast to those at higher latitudes, which are largely driven by halocarbon increases. Factors influencing temperature trends and tropopause heights in this region are also probed. It is shown that the modeled temperature trends in the lower tropical stratosphere are also associated with increases in CO2 and sea surface temperatures. Following the analysis of lower stratospheric tropical temperature trends, the secondary focus of this paper is on related changes in tropopause height. Much of the simulated tropopause rise in the tropical zone as measured by tropopause height is found to be linked to increases in sea surface temperatures and CO2, while increases in halocarbons dominate the tropopause height changes in the subtropics near 30°; both drivers thus affect different regions of the simulated changes in the position of the tropopause. Finally, it is shown that halocarbon increases dominate the changes in the width of the region where modeled total ozone displays tropical character (as indicated by low values of the column abundance). Hence the findings suggest that climate changes and halocarbon changes make different contributions to different metrics used to characterize tropical change. [ABSTRACT FROM AUTHOR]

The dominant interannual El Niño–Southern Oscillation (ENSO) phenomenon and the short length of climate observation records make it difficult to study long-term climate variations in the spatiotemporal domain. Based on the fact that the ENSO signal spreads to remote regions and induces delayed climate variation through atmospheric teleconnections, an ENSO-removal method is developed through which the ENSO signal can be approximately removed at the grid box level from the spatiotemporal field of a climate parameter. After this signal is removed, long-term climate variations are isolated at mid- and low latitudes in the climate parameter fields from observed and reanalysis datasets. This paper addresses the long-term global warming trend (GW); a companion paper concentrates on Pacific pan-decadal variability (PDV). The warming that occurs in the Pacific basin (approximately 0.4 K in the twentieth century) is much weaker than in surrounding regions and the other two ocean basins (approximately 0.8 K). The modest warming in the Pacific basin is likely due to its dynamic nature on the interannual and decadal time scales and/or the leakage of upper ocean water through the Indonesian Throughflow. Based on the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) and the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40), a comprehensive atmospheric structure associated with the GW trend is given. Significant discrepancies exist between the two datasets, especially in the tightly coupled dynamics and water vapor fields. The dynamics fields based on NCEP–NCAR, which show a change in the Walker Circulation, are consistent with the GW change in the surface temperature field. However, intensification in the Hadley Circulation is associated with GW trend in ERA-40 instead. [ABSTRACT FROM AUTHOR]

This paper reviews the observational and theoretical basis for the prediction of seasonal-to-interannual (S/I) climate variability in the Atlantic sector. The emphasis is on the large-scale picture rather than on regional details. The paper is divided into two main parts: a discussion of the predictability of the North Atlantic Oscillation (NAO)—the dominant pattern of variability in the North Atlantic—and a review of the tropical Atlantic prediction problem. The remote effects of El Niño are also mentioned as an important factor in Atlantic climate variability. Only a brief discussion is provided on the subject of South Atlantic climate predictability. Because of its chaotic dynamical nature, the NAO and its related rainfall and temperature variability, while highly significant over Europe and North America, are largely unpredictable. This also affects the predictive skill over the tropical Atlantic, because the NAO interferes with the remote influence of El Niño. That said, there appears to be an insufficiently understood, marginal signal in the NAO behavior that may be predictable and thus useful to certain end users. It is manifested in the deviation of the NAO temporal behavior from first-order autoregressive behavior. Tropical Atlantic climate variability centers on the sensitivity of the marine ITCZ to remote forcing from the equatorial Pacific and interactions with underlying sea surface temperature (SST) variability. Both mechanisms are potentially predictable—that is, given the underlying SSTs and the strength of El Niño, one could determine with a high degree of skill the anomalies in ITCZ position and intensity. However, local SSTs are easily affected by largely unpredictable North and South Atlantic phenomena, such as the NAO. In addition, the local ocean–atmosphere coupling in the Atlantic acts on relatively short time scales. Thus, in reality the level of skill indicated by forced model simulations are difficult to achieve. The use of coupled models may improve the prospects of tropical Atlantic prediction. [ABSTRACT FROM AUTHOR]

In this paper the progress made in producing predictions of the Normalized Difference Vegetation Index (NDVI) over Kenya in the Greater Horn of Africa (GHA) for the October–December (OND) season is discussed. Several studies have identified a statistically significant relationship between rainfall and NDVI in the region. Predictability of seasonal rainfall by global climate models (GCMs) during the OND season over the GHA has also been established as being among the best in the world. Information was extracted from GCM seasonal prediction output using statistical transformations. The extracted information was then used in the prediction of NDVI. NDVI is a key variable for management of various climate-sensitive problems. For example, it has been shown to have the potential to predict environmental conditions associated with Rift Valley Fever (RVF) viral activity and this is referred to throughout the paper as a motivation for the study. RVF affects humans and livestock and is particularly economically important in the GHA. The establishment of predictability for NDVI in this paper is therefore part of a methodology that could ultimately generate information useful for managing RVF in livestock in the GHA. It has been shown that NDVI can be predicted skillfully over the GHA with a 2–3-month lead time. Such information is crucial for tailoring forecast information to support RVF monitoring and prediction over the region, as well as many other potential applications (e.g., livestock forage estimation). More generally, the Famine Early Warning System (FEWS), a project of the U.S. Agency for International Development (USAID) and the National Aeronautics and Space Administration (NASA) and other specialized technical centers routinely use NDVI images to monitor environmental conditions worldwide. The high predictability for NDVI established in this paper could therefore supplement the routine monitoring of environmental conditions for a wide range of applications. [ABSTRACT FROM AUTHOR]

A currently popular idea is that El Niño–Southern Oscillation (ENSO) can be viewed as a linear deterministic system forced by noise representing processes with periods shorter than ENSO. Also, there is observational evidence to suggest that the Madden–Julian oscillation (MJO) acts to trigger and/or amplify the warm phase of ENSO in this way. The feedback of the slower process, ENSO, to higher-frequency atmospheric phenomena, of which a large part of the variability in the intraseasonal band is due to the MJO, has received little attention. This paper considers the hypothesis that the probability of an El Niño event is modified by high MJO activity and that, in turn, the MJO is regulated by ENSO activity. If this is indeed the case, then viewing ENSO as a low-frequency oscillation forced by additive stochastic noise would not present a complete picture. This paper tests the above hypothesis using a stochastically forced intermediate coupled model by allowing ENSO to directly influence the stochastic forcing. The model response to a variety of stochastic forcing types is found to be sensitive to the type of forcing applied. When the model is operated beyond its intrinsic Hopf bifurcation, its probability distribution function (PDF) is fundamentally altered when the stochastic forcing is changed from additive to multiplicative. The model integration period also influences the shape of the PDF, which is also compared to the PDF derived from observations. It is found that multiplicative stochastic forcing reproduces some measures of the observations better than the additive stochastic forcing. [ABSTRACT FROM AUTHOR]

A number of recent papers have argued that the mechanical energy budget of the ocean places constraints on how the thermohaline circulation is driven. These papers have been used to argue that climate models, which do not specifically account for the energy of mixing, potentially miss a very important feedback on climate change. This paper reexamines the question of what energetic arguments can teach us about the climate system and concludes that the relationship between energetics and climate is not straightforward. By analyzing the buoyancy transport equation, it is demonstrated that the large-scale transport of heat within the ocean requires an energy source of around 0.2 TW to accomplish vertical transport and around 0.4 TW (resulting from cabbeling) to accomplish horizontal transport. Within two general circulation models, this energy is almost entirely supplied by surface winds. It is also shown that there is no necessary relationship between heat transport and mechanical energy supply. [ABSTRACT FROM AUTHOR]

Barry Saltzman was a giant in the fields of meteorology and climate science. A leading figure in the study of weather and climate for over 40 yr, he has frequently been referred to as the “father of modern climate theory.” Ahead of his time in many ways, Saltzman made significant contributions to our understanding of the general circulation and spectral energetics budget of the atmosphere, as well as climate change across a wide spectrum of time scales. In his endeavor to develop a unified theory of how the climate system works, he played a role in the development of energy balance models, statistical dynamical models, and paleoclimate dynamical models. He was a pioneer in developing meteorologically motivated dynamical systems, including the progenitor of Lorenz’s famous chaos model. In applying his own dynamical-systems approach to long-term climate change, he recognized the potential for using atmospheric general circulation models in a complimentary way. In 1998, he was awarded the Carl-Gustaf Rossby medal, the highest honor of the American Meteorological Society “for his life-long contributions to the study of the global circulation and the evolution of the earth’s climate.” In this paper, the authors summarize and place into perspective some of the most significant contributions that Barry Saltzman made during his long and distinguished career. This short review also serves as an introduction to the papers in this special issue of the Journal of Climate dedicated to Barry’s memory. [ABSTRACT FROM AUTHOR]

Although it is critical to assess the accuracy of attribution studies, the fraction of attributable risk (FAR) cannot be directly assessed from observations since it involves the probability of an event in a world that did not happen, the 'natural' world where there was no human influence on climate. Instead, reliability diagrams (usually used to compare probabilistic forecasts to the observed frequencies of events) have been used to assess climate simulations employed for attribution and by inference to evaluate the attribution study itself. The Brier score summarizes this assessment of a model by the reliability diagram. By constructing a modeling framework where the true FAR is already known, this paper shows that Brier scores are correlated to the accuracy of a climate model ensemble's calculation of FAR, although only weakly. This weakness exists because the diagram does not account for accuracy of simulations of the natural world. This is better represented by two reliability diagrams from early and late in the period of study, which would have, respectively, less and greater anthropogenic climate forcing. Two new methods are therefore proposed for assessing the accuracy of FAR, based on using the earlier observational period as a proxy for observations of the natural world. It is found that errors from model-based estimates of these observable quantities are strongly correlated with errors in the FAR estimated in the model framework. These methods thereby provide new observational estimates of the accuracy in FAR. [ABSTRACT FROM AUTHOR]

This paper explores the effects from averaging weather station data onto a grid on the first four statistical moments of daily minimum and maximum surface air temperature (SAT) anomalies over the entire globe. The Global Historical Climatology Network-Daily (GHCND) and the Met Office Hadley Centre GHCND (HadGHCND) datasets from 1950 to 2010 are examined. The GHCND station data exhibit large spatial patterns for each moment and statistically significant moment trends from 1950 to 2010, indicating that SAT probability density functions are non-Gaussian and have undergone characteristic changes in shape due to decadal variability and/or climate change. Comparisons with station data show that gridded averages always underestimate observed variability, particularly in the extremes, and have altered moment trends that are in some cases opposite in sign over large geographic areas. A statistical closure approach based on the quasi-normal approximation is taken to explore SAT's higher-order moments and point correlation structure. This study focuses specifically on relating variability calculated from station data to that from gridded data through the moment equations for weighted sums of random variables. The higher-order and nonlinear spatial correlations up to the fourth order demonstrate that higher-order moments at grid scale can be determined approximately by functions of station pair correlations that tend to follow the usual Kolmogorov scaling relation. These results can aid in the development of constraints to reduce uncertainties in climate models and have implications for studies of atmospheric variability, extremes, and climate change using gridded observations. [ABSTRACT FROM AUTHOR]

This paper provides a review of atmospheric circulation and sea surface temperature (SST) conditions that are associated with meteorological drought on the seasonal time scale in the Greater Horn of Africa (the region 10°S-15°N, 30°-52°E). New findings regarding a post-1998 increase in drought frequency during the March-May (MAM) 'long rains' are also reported. The period 1950-2010 is emphasized, although rainfall and SST data from 1901-2010 are used to place the recent long rains decline in a multidecadal context. For the latter case, climate model simulations and isolated basin SST experiments are also utilized. Climatologically, rainfall exhibits a unimodal June-August (JJA) maximum in west-central Ethiopia with a generally bimodal [MAM and October-December (OND) maxima] distribution in locations to the south and east. Emphasis will be on these three seasons. SST anomalies in the tropical Pacific and Indian Oceans show the strongest association with drought during OND in locations having a bimodal annual cycle, with weaker associations during MAM. The influence of the El Niño-Southern Oscillation (ENSO) phenomenon critically depends on its ability to affect SSTs outside the Pacific. Salient features of the anomalous atmospheric circulation during drought events in different locations and seasons are discussed. The post-1998 decline in the long rains is found to be driven strongly (although not necessarily exclusively) by natural multidecadal variability in the tropical Pacific rather than anthropogenic climate change. This conclusion is supported by observational analyses and climate model experiments, which are presented. [ABSTRACT FROM AUTHOR]

Recent advances in the collection and analysis of paleoclimate data have provided significant insights into preinstrumental environmental events and processes, enabling a greater understanding of long-term environmental change and associated hydroclimatic risks. Unfortunately, it is often the case that there is a dearth of readily available paleoclimate data from regions where such insights and long-term data are most needed. The Murray-Darling basin (MDB), known as Australia's 'food bowl,' is an example of such a region where currently there are very limited in situ paleoclimate data available. While previous studies have utilized paleoclimate proxy records of large-scale climate mechanisms to infer preinstrumental MDB hydroclimatic variability, there is a lack of studies that utilize Australian terrestrial proxy records to garner similar information. Given the immediate need for improved understanding of MDB hydroclimatic variability, this paper identifies key locations in Australia where existing and as yet unrealized paleoclimate records will be most useful in reconstructing such information. To identify these key locations, rainfall relationships between MDB and non-MDB locations were explored through correlations and principal component analysis. An objective analysis using optimal interpolation was then used to pinpoint the most strategic locations to further develop proxy records and gain insights into the benefits of obtaining this additional information. The findings reveal that there is potential for the future assembly of high-resolution paleoclimate records in Australia capable of informing MDB rainfall variability, in particular southeast Australia and central-northern Australia. This study highlights the need for further investment in the development of these potential proxy sources to subsequently enable improved assessments of long-term hydroclimatic risks. [ABSTRACT FROM AUTHOR]

This paper summarizes the results of an intercomparison project with Earth System Models of Intermediate Complexity (EMICs) undertaken in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). The focus is on long-term climate projections designed to 1) quantify the climate change commitment of different radiative forcing trajectories and 2) explore the extent to which climate change is reversible on human time scales. All commitment simulations follow the four representative concentration pathways (RCPs) and their extensions to year 2300. Most EMICs simulate substantial surface air temperature and thermosteric sea level rise commitment following stabilization of the atmospheric composition at year-2300 levels. The meridional overturning circulation (MOC) is weakened temporarily and recovers to near-preindustrial values in most models for RCPs 2.6-6.0. The MOC weakening is more persistent for RCP8.5. Elimination of anthropogenic CO2 emissions after 2300 results in slowly decreasing atmospheric CO2 concentrations. At year 3000 atmospheric CO2 is still at more than half its year-2300 level in all EMICs for RCPs 4.5-8.5. Surface air temperature remains constant or decreases slightly and thermosteric sea level rise continues for centuries after elimination of CO2 emissions in all EMICs. Restoration of atmospheric CO2 from RCP to preindustrial levels over 100-1000 years requires large artificial removal of CO2 from the atmosphere and does not result in the simultaneous return to preindustrial climate conditions, as surface air temperature and sea level response exhibit a substantial time lag relative to atmospheric CO2. [ABSTRACT FROM AUTHOR]

As an additional classification to Köppen's climate classification for polar (E) climates, the Polar Marine (EM) climate was presented nearly five decades ago and is revisited in this paper. The EM climate was traced to the North Atlantic, North Pacific, and Southern Ocean and recognized as wet, cloudy, and windy, especially during winter. These areas by definition are encompassed by monthly mean air temperatures of −6.7°C (20°F) and 10°C (50°F) in the coldest and warmest months of the annual cycle, respectively. Here three global reanalyses [ECMWF Interim Re-Analysis (ERA-Interim), Climate Forecast System Reanalysis (CFSR), and Japan Meteorological Agency (JMA) 25-yr reanalysis (JRA-25)] are used to produce a modern depiction of EM climate. General agreement is found between original and new EM boundaries, for which the poleward boundary can be approximated by the winter sea ice maximum and the equatorward boundary by the warmest month SSTs. Variability of these parameters is shown to largely dictate the EM area. A downward trend in global EM areal extent for 1979-2010 (−42.4 × 109 m2 yr−1) is dominated by the negative Northern Hemisphere (NH) EM trend (−45.7 × 109 m2 yr−1), whereas the Southern Hemisphere (SH) EM areal trend is insignificant. This observed reduction in NH EM areal extent of roughly 20% over the past three decades, largely from losses at the equatorward boundaries of these biologically rich EM zones, may not be fully compensated by poleward shifts in the EM environment due to projected warming and sea ice decline in the twenty-first century. [ABSTRACT FROM AUTHOR]

Constraining the low-frequency (LF) behavior of general circulation models (GCMs) requires reliable observational estimates of LF variability. This two-part paper presents multiproxy reconstructions of Niño-3.4 sea surface temperature over the last millennium, applying two techniques [composite plus scale (CPS) and hybrid regularized expectation maximization (RegEM) truncated total least squares (TTLS)] to a network of tropical, high-resolution proxy records. This first part presents the data and methodology before evaluating their predictive skill using frozen network analysis (FNA) and pseudoproxy experiments. The FNA results suggest that about half of the Niño-3.4 variance can be reconstructed back to A.D. 1000, but they show little LF skill during certain intervals. More variance can be reconstructed in the interannual band where climate signals are strongest, but this band is affected by dating uncertainties (which are not formally addressed here). The CPS reliably estimates interannual variability, while LF fluctuations are more faithfully reconstructed with RegEM, albeit with inevitable variance loss. The RegEM approach is also tested on representative pseudoproxy networks derived from two millennium-long integrations of a coupled GCM. The pseudoproxy study confirms that reconstruction skill is significant in both the interannual and LF bands, provided that sufficient variance is exhibited in the target Niño-3.4 index. It also suggests that FNA severely underestimates LF skill, even when LF variability is strong, resulting in overly pessimistic performance assessments. The centennial-scale variance of the historical Niño-3.4 index falls somewhere between the two model simulations, suggesting that the network and methodology presented here would be able to capture the leading LF variations in Niño-3.4 for much of the past millennium, with the caveats noted above. [ABSTRACT FROM AUTHOR]

Previous studies have indicated a widespread decline in snowpack over Utah accompanied by a decline in the snow-precipitation ratio while anecdotal evidence claims have been put forward that measured changes in Utah's snowpack are spurious and do not reflect actual change. Using two distinct lines of investigation, this paper further analyzes the winter precipitation regime in the state of Utah. First, by means of observation-based, gridded daily temperature, precipitation, and remotely sensed data, as well as utilizing a climatological rain-snow threshold (RST) temperature method, the precipitation regime of Utah was scrutinized. Second, a comprehensive synoptic analysis was conducted as an alternate means that is independent from surface observations. It was found that the proportion of winter (January-March) precipitation falling as snow has decreased by 9% during the last half century, a combined result from a significant increase in rainfall and a minor decrease in snowfall. Meanwhile, observed snow depth across Utah has decreased and is accompanied by consistent decreases in snow cover and surface albedo. Weather systems with the potential to produce precipitation in Utah have decreased in number with those producing snowfall decreasing at a considerably greater rate. Further circulation analysis showed that an anomalous anticyclone has developed over western North America, which acts to reduce the frequency of cyclone waves impacting Utah. Combined with the increased precipitation, this feature suggests that the average precipitation per event has intensified with more of it falling as rain than as snow. Trends in the hydroclimate such as these have implications for present and future regional water policy in the state of Utah. [ABSTRACT FROM AUTHOR]

This paper addresses several hypotheses designed to explain why AOGCM simulations of future climate in the third phase of the Coupled Model Intercomparison Project (CMIP3) feature an intensified reduction of precipitation over the Meso-America (MA) region. While the drying is consistent with an amplification of the subtropical high pressure cells and an equatorward contraction of convective regions due to the ''upped ante'' for convection in a warmer atmosphere, the physical mechanisms behind the intensity and robustness of the MA drying signal have not been fully explored. Regional variations in sea surface temperature (SST) warming may play a role. First, SSTs over the tropical North Atlantic (TNA) do not warm as much as the surrounding ocean. The troposphere senses a TNA that is cooler than the tropical Pacific, potentially exciting a Gill-type response, increasing the strength of the North Atlantic subtropical high. Second, the warm ENSO-like state simulated in the eastern tropical Pacific could decrease precipitation over MA, as warm ENSO events are associated with drying over MA. The authors use the International Centre for Theoretical Physics (ICTP) AGCM to investigate the effects of these regional SST warming variations on the projected drying over MA. First, the change of SSTs [Special Report on Emissions Scenarios (SRES) A1B''s Twentieth-Century Climate in Coupled Model (A1B-20C)] in the ensemble average of the CMIP3 models is applied to determine if the ICTP AGCM can replicate the future drying. Then the effects of 1) removing the reduced warming over the TNA, 2) removing the warm ENSO-event-like pattern in the eastern tropical Pacific, and 3) applying uniform SST warming throughout the tropics are tested. The ICTP AGCM can reproduce the general pattern and amount of precipitation over MA. Simulations in which the CMIP3 A1B-20C ensemble-average SSTs are added to climatological SSTs show drying of more than 20%% over the MA region, similar to the CMIP3 ensemble average. Replacing the relatively cooler SSTs over the TNA excites a Gill response consistent with an off-equatorial heating anomaly, showing that the TNA relative cooling is responsible for about 16%% (31%%) of the drying in late spring (early summer). The warm ENSO-like SST pattern over the eastern Pacific also affects precipitation over the MA region, with changes of 19%% and 31%% in March--June (MMJ) and June--August (JJA), respectively. This work highlights the importance of understanding even robust signals in the CMIP3 future scenario simulations, and should aid in the design and analysis of future climate change studies over the region. [ABSTRACT FROM AUTHOR]

In this paper a detailed global climatology of wind-sea and swell parameters, based on the 45-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) wave reanalysis is presented. The spatial pattern of the swell dominance of the earth''s oceans, in terms of the wave field energy balance and wave field characteristics, is also investigated. Statistical analysis shows that the global ocean is strongly dominated by swell waves. The interannual variability of the wind-sea and swell significant wave heights, and how they are related to the resultant significant wave height, is analyzed over the Pacific, Atlantic, and Indian Oceans. The leading modes of variability of wind sea and swell demonstrate noticeable differences, particularly in the Pacific and Atlantic Oceans. During the Northern Hemisphere winter, a strong north--south swell propagation pattern is observed in the Atlantic Ocean. Statistically significant secular increases in the wind-sea and swell significant wave heights are found in the North Pacific and North Atlantic Oceans. [ABSTRACT FROM AUTHOR]

This paper examines characteristic changes in North Pacific sea surface temperature (SST) variability during the boreal winter (December--February) for two subperiods (1956--88 and 1977--2009) during which the 1976/77 and the 1988/89 climate transitions occurred. It is found that the Pacific decadal oscillation (PDO)-like SST variability plays a dominant role in the 1976/77 climate transition, while both the North Pacific Gyre Oscillation (NPGO)-like and PDO-like SST variability contribute to the 1988/89 climate transition. Furthermore, the leading mode changes from PDO-like SST variability during the period 1956--88 to NPGO-like SST variability during the period 1977--2009, indicative of an enhancement of NPGO-like SST variability since 1988. Changes in sea level pressure across the 1976/77 climate transition project strongly onto the Aleutian low pressure system. But sea level pressure changes across the 1988/89 climate transition project primarily onto the North Pacific Oscillation, which is associated with remote changes in the Arctic Oscillation over the polar region as well. This contributes to enhancing the NPGO-like SST variability after 1988. The authors also analyze the output from an ensemble of Tropical Ocean and Global Atmosphere (TOGA) experiments in which the observed SSTs are inserted only at grid points in the tropics between 20°°S and 20°°N. The results indicate that the changes in the North Pacific atmosphere in the 1976/77 climate transition are mostly due to the tropics, whereas those in the 1988/89 climate transition are not. [ABSTRACT FROM AUTHOR]

When the climate system experiences time-dependent external forcing (e.g., from increases in greenhouse gas and aerosol concentrations), there are two inherent limits on the gain in skill of decadal climate predictions that can be attained from initializing with the observed ocean state. One is the classical initial-value predictability limit that is a consequence of the system being chaotic, and the other corresponds to the forecast range at which information from the initial conditions is overcome by the forced response. These limits are not caused by model errors; they correspond to limits on the range of useful forecasts that would exist even if nature behaved exactly as the model behaves. In this paper these two limits are quantified for the Community Climate System Model, version 3 (CCSM3), with several 40-member climate change scenario experiments. Predictability of the upper-300-m ocean temperature, on basin and global scales, is estimated by relative entropy from information theory. Despite some regional variations, overall, information from the ocean initial conditions exceeds that from the forced response for about 7 yr. After about a decade the classical initial-value predictability limit is reached, at which point the initial conditions have no remaining impact. Initial-value predictability receives a larger contribution from ensemble mean signals than from the distribution about the mean. Based on the two quantified limits, the conclusion is drawn that, to the extent that predictive skill relies solely on upper-ocean heat content, in CCSM3 decadal prediction beyond a range of about 10 yr is a boundary condition problem rather than an initial-value problem. Factors that the results of this study are sensitive and insensitive to are also discussed. [ABSTRACT FROM AUTHOR]

Vegetation around the Daihai Lake, northern China, is very sensitive to climate changes. In this paper, pollen-based quantitative climate reconstructions using three methods [weighted averaging partial least squares method (WAPLS), modern analog technique (MAT), and pollen response surface method (PRS)] were conducted to obtain robust reconstructions of Holocene climate changes in the Daihai Lake area. The result obtained by the three methods all consistently show the annual precipitation to have been 50–100 mm lower in the early Holocene, 100–200 mm higher in the Mid-Holocene, and 50–100 mm lower again in the late Holocene than at present. The WAPLS and the MAT methods also show quasi-synchronous oscillations of the mean annual temperature (Ta); 1°–2°C lower in the Early Holocene and 1°–3°C higher in the Mid-Holocene than today. The time period from 6200 to 5100 cal yr BP was the wettest and the warmest interval, with an annual precipitation (Pa) greater than 550 mm and mean annual temperature Ta higher than 6.5°C. Several cold and dry events can be identified to occur about 8200, 6000, and 4400 cal yr BP, with an annual precipitation less than 400 mm and a mean annual temperature colder than 4.5°C, respectively. The mean temperature of the warmest month (Tw) as reconstructed using both WAPLS and MAT methods was relatively stable during the Holocene, fluctuating about ±2°C relative to the present level, but the PRS method suggests more varied Tw values in both amplitude and frequency. After 1500 cal yr BP, no consistent pattern can be observed from these three different analyses, probably because of the impact of intensified human disturbances on the natural vegetation. The fluctuations of annual precipitation (Pa) correspond to that observed in Dongge Cave in southern China. The differences might be linked to Indian monsoon and East Asia monsoon climates or caused by the different degree of dating precision, different temporal resolution, and different sensitive response of climate proxies to the climate variations. [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]

The climate observations at Orcadas represent the only southern high-latitude site where data span more than a century, and its daily measurements are presented for the first time in this paper. Although limited to a single station, the observed warming trends are among the largest found anywhere on the earth, facilitating the study of changes in extreme temperatures as well as averages. Factors that may influence Antarctic climate include natural variability; changes in greenhouse gases; and, since about the mid-1970s, the development of the ozone hole. The seasonality of observed warming and its temporal evolution during the century are both key for interpretations of Antarctic climate change. No statistically significant climate trends are observed at Orcadas from 1903 to 1950. However, statistically significant warming is evident at Orcadas throughout all four seasons of the year since 1950. Particularly in austral fall and winter, the warming of the cold extremes (coldest 5% and 10% of days) substantially exceeds the warming of the mean or of the warmest days, providing a key indicator for cold season Antarctic climate change studies. Trends in the summer season means and extremes since 1970 are approximately twice as large as those observed earlier, supporting suggestions of additional regional warming in that season because of the effects of ozone depletion on the circulation. Further, in the spring and summer seasons, significant mean warming also occurred prior to the development of the Antarctic ozone hole (i.e., 1950–70), supporting an important role for processes other than ozone depletion, such as greenhouse gas increases, for the climate changes. [ABSTRACT FROM AUTHOR]

A simple model is developed that predicts climatological rainfall, vertical motion, and diabatic heating profiles over the tropical oceans given the sea surface temperature (SST), using statistical relationships deduced from the 40-yr ECMWF Re-Analysis (ERA-40). The model allows for two modes of variability in the vertical motion profiles: a shallow mode responsible for all “boundary layer” convergence between 850 hPa and the surface, and a deep mode with no boundary layer convergence. The model is based on the argument expressed in the authors’ companion paper that boundary layer convergence can be usefully viewed as a forcing on deep convection, not just a result thereof. The shallow mode is either specified from satellite observations or modeled using a simple mixed-layer model that has SST as well as 850-hPa geopotential height, winds, and temperature as boundary conditions. The deep-mode amplitude is empirically shown to be proportional to a simple measure of conditional instability in convecting regions, and is determined by the constraint that radiative cooling must balance adiabatic warming in subsidence regions. This two-mode model is tested against a reanalysis-derived dry static energy budget and in a reanalysis-independent framework based on satellite-derived surface convergence and using SST as a proxy for conditional instability. It can predict the observed annual mean and seasonal cycle of rainfall, vertical motion, and diabatic heating profiles across the tropical oceans with significantly more skill than optimized predictions using a thresholded linear relationship with SST. In most warm-ocean regions, significant rainfall only occurs in regions of monthly-mean boundary layer convergence. In such regions, deep-mode amplitude and rainfall increase linearly with SST, with an additional rainfall contribution from the shallow mode directly tied to boundary layer convergence. This second contribution is significant mainly in the east and central Pacific ITCZ, where it is responsible for that region’s “bottom-heavy” vertical-velocity, diabatic heating, and cloud profiles. [ABSTRACT FROM AUTHOR]

Perturbations to the carbon cycle could constitute large feedbacks on future changes in atmospheric CO2 concentration and climate. This paper demonstrates how carbon cycle feedback can be expressed in formally similar ways to climate feedback, and thus compares their magnitudes. The carbon cycle gives rise to two climate feedback terms: the concentration–carbon feedback, resulting from the uptake of carbon by land and ocean as a biogeochemical response to the atmospheric CO2 concentration, and the climate–carbon feedback, resulting from the effect of climate change on carbon fluxes. In the earth system models of the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP), climate–carbon feedback on warming is positive and of a similar size to the cloud feedback. The concentration–carbon feedback is negative; it has generally received less attention in the literature, but in magnitude it is 4 times larger than the climate–carbon feedback and more uncertain. The concentration–carbon feedback is the dominant uncertainty in the allowable CO2 emissions that are consistent with a given CO2 concentration scenario. In modeling the climate response to a scenario of CO2 emissions, the net carbon cycle feedback is of comparable size and uncertainty to the noncarbon–climate response. To quantify simulated carbon cycle feedbacks satisfactorily, a radiatively coupled experiment is needed, in addition to the fully coupled and biogeochemically coupled experiments, which are referred to as coupled and uncoupled in C4MIP. The concentration–carbon and climate–carbon feedbacks do not combine linearly, and the concentration–carbon feedback is dependent on scenario and time. [ABSTRACT FROM AUTHOR]

During periods of light surface wind, a warm stable layer forms at the ocean surface with a maximum sea surface temperature (SST) in the early afternoon. The diurnal SST amplitude (DSA) associated with these diurnal warm layers (DWLs) can reach several degrees and impact the tropical climate variability. This paper first presents an approach to building a daily time series of the DSA over the tropics between 1979 and 2002. The DSA is computed over 2.5° of latitude–longitude regions using a simple DWL model forced by hourly-interpolated surface radiative and turbulent fluxes given by the 40-yr ECMWF Re-Analysis (ERA-40). One advantage of this approach is the homogeneity of the results given by the relative homogeneity of ERA-40. The approach is validated at the global scale using empirical DWL models reported in the literature and the Surface Velocity Program (SVP) drifters of the Marine Environmental Data Service (MEDS). For the SVP dataset, a new technique is introduced to derive the diurnal variation of the temperature from raw measurements. This DWL time series is used to analyze the potential role of DWLs in the variability of the tropical climate. The perturbation of the surface fluxes by DWLs can give a cooling of the ocean mixed layer as large as 2.5 K yr-1 in some tropical regions. On a daily basis, this flux perturbation is often above 10 W m-2 and sometimes exceeds 50 W m-2. DWLs can be organized on regions up to a few thousand kilometers and can persist for more than 5 days. It is shown that strong DWLs develop above the equatorial Indian Ocean during the suppressed phase of the intraseasonal oscillation (ISO). DWLs may trigger large-scale convective events and favor the eastward propagation of the ISO convective perturbation during boreal winter. This study also suggests that the simple approach presented here may be used as a DWL parameterization for atmospheric general circulation models. [ABSTRACT FROM AUTHOR]

Climate model simulations consistently show that surface temperature over land increases more rapidly than over sea in response to greenhouse gas forcing. The enhanced warming over land is not simply a transient effect caused by the land–sea contrast in heat capacities, since it is also present in equilibrium conditions. This paper elucidates the transient adjustment processes over time scales of days to weeks of the surface and tropospheric climate in response to a doubling of CO2 and to changes in sea surface temperature (SST), imposed separately and together, using ensembles of experiments with an atmospheric general circulation model. These adjustment processes can be grouped into three stages: immediate response of the troposphere and surface processes (day 1), fast adjustment of surface processes (days 2–5), and adjustment of the whole troposphere (days 6–20). Some land surface warming in response to doubled CO2 (with unchanged SSTs) occurs immediately because of increased downward longwave radiation. Increased CO2 also leads to reduced plant stomatal resistance and hence restricted evaporation, which increases land surface warming in the first day. Rapid reductions in cloud amount lead in the next few days to increased downward shortwave radiation and further warming, which spreads upward from the surface, and by day 5 the surface and tropospheric response is statistically consistent with the equilibrium value. Land surface warming in response to imposed SST change (with unchanged CO2) is slower. Tropospheric warming is advected inland from the sea, and over land it occurs at all levels together rather than spreading upward from the surface. The atmospheric response to prescribed SST change in about 20 days is statistically consistent with the equilibrium value, and the warming is largest in the upper troposphere over both land and sea. The land surface warming involves reduction of cloud cover and increased downward shortwave radiation, as in the experiment with CO2 change, but in this case it is due to the restriction of moisture supply to the land (indicated by reduced soil moisture), whereas in the CO2 forcing experiment it is due to restricted evaporation despite increased moisture supply (indicated by increased soil moisture). The warming over land in response to SST change is greater than over the sea and is the dominant contribution to the land–sea warming contrast under enhanced CO2 forcing. [ABSTRACT FROM AUTHOR]

Since 1951, late spring (May) rainfall over southeastern China (SEC) has decreased by more than 30% from its long-term average, in contrast to a rainfall increase in boreal summer. The dynamics have yet to be fully determined. This paper shows that as the Indo-Pacific enters into a La Niña phase, significant negative mean sea level pressure (MSLP) anomalies grow over the Indian Ocean and the western Pacific sector. The associated large-scale southwesterly anomalies transport moisture to the nearby South China Sea and the SEC region, contributing to a higher rainfall. A presence of a Philippine Sea anticyclonic (PSAC) pattern, arising from a decaying El Niño, strengthens the rain-conducive flow to SEC, but it is not a necessary condition. During the past decades, an increase in protracted El Niño events accompanied by a reduction in La Niña episodes has contributed to the May rainfall decline. The extent to which climate change is contributing is discussed. [ABSTRACT FROM AUTHOR]

As the climate changes, changes in static stability, meridional temperature gradients, and availability of moisture for latent heat release may exert competing effects on the energy of midlatitude transient eddies. This paper examines how the eddy kinetic energy in midlatitude baroclinic zones responds to changes in radiative forcing in simulations with an idealized moist general circulation model. In a series of simulations in which the optical thickness of the longwave absorber is varied over a wide range, the eddy kinetic energy has a maximum for a climate with mean temperature similar to that of present-day earth, with significantly smaller values both for warmer and for colder climates. In a series of simulations in which the meridional insolation gradient is varied, the eddy kinetic energy increases monotonically with insolation gradient. In both series of simulations, the eddy kinetic energy scales approximately linearly with the dry mean available potential energy averaged over the baroclinic zones. Changes in eddy kinetic energy can therefore be related to the changes in the atmospheric thermal structure that affect the mean available potential energy. [ABSTRACT FROM AUTHOR]

The Arctic region has exhibited dramatic changes in recent times. Many of these are intimately tied up with synoptic activity, but little research has been undertaken on how the characteristics of Arctic cyclones have changed. This paper presents a comprehensive analysis of Arctic (here defined as the domain north of 70°N) cyclones diagnosed with the Melbourne University cyclone tracking scheme applied to the 40-yr ECMWF Re-Analysis (ERA-40) and the NCEP–NCAR (NCEP1) and NCEP–Department of Energy (DOE) Atmospheric Model Intercomparison Project (AMIP)-II (NCEP2) reanalysis sets (the last two extending to the end of 2006). A wide variety of cyclone characteristics is presented as befits these complex features. In winter the highest density of cyclones is found between Norway and Svalbard and to the east to the Barents and Kara Seas, and significant numbers are found in the central Arctic. In summer the greatest frequencies are found in the central Arctic. The total number of cyclones identified in the ERA-40 record exceeds those in the two NCEP compilations. The mean size of cyclones shows similar maxima in the central Arctic in both winter and summer. By contrast, the greatest mean system depth in winter (in excess of 8 hPa) is found to the southeast of Greenland, although average depths exceed 6 hPa over a considerable portion of the basin. In summer the deepest cyclones are found in the central portion of the Arctic. The analysis shows that the total number of cyclones in winter exceeds that in summer, a result in contrast to earlier studies. This difference comes about primarily due to the greater numbers of “open strong” systems in winter in all reanalyses. Cyclones in this category are associated with very active synoptic situations; it is of importance that they be included in cyclone counts but would not be considered in many cyclone identification schemes. Since 1979 neither the ERA-40 nor the NCEP2 sets show significant trends in any of the cyclone variables considered. However, over the entire record starting in 1958 the NCEP1 reanalysis exhibits a significant increase in summer cyclone frequency (due mainly to the increase in closed strong systems). Both NCEP1 and ERA-40 also reveal significant increases in the number of summer closed strong cyclones, as well as in their mean depth and intensity in that season. Interannual variations in Arctic cyclone numbers are closely related to the Arctic Oscillation (AO) index in the full reanalyses records. An even stronger relationship is found between the AO and the number of deep cyclones. These relationships have still held in the last decade when the AO has returned to more normal values but the summer and fall sea ice extent has continued to decrease. [ABSTRACT FROM AUTHOR]

Reliable projections of future changes in local precipitation extremes are essential for informing policy decisions regarding mitigation and adaptation to climate change. In this paper, the extent to which the natural variability of the climate affects one’s ability to project the anthropogenically forced component of change in daily precipitation extremes across Europe is examined. A three-member ensemble of the Hadley Centre Regional Climate Model (HadRM3H) is used and a statistical framework is applied to estimate the uncertainty due to the full spectrum of climate variability. In particular, the results and understanding presented here suggest that annual to multidecadal natural variability may contribute significant uncertainty. For this ensemble projection, extreme precipitation changes at the grid-box level are found to be discernible above climate noise over much of northern and central Europe in winter, and parts of northern and southern Europe in summer. The ability to quantify the change to a reasonable level of accuracy is largely limited to regions in northern Europe. In general, where climate noise has a significant component varying on decadal time scales, single 30-yr climate change projections are insufficient to infer changes in the extreme tail of the underlying precipitation distribution. In this context, the need for ensembles of integrations is demonstrated and the relative effectiveness of spatial pooling and averaging for generating robust signals of extreme precipitation change is also explored. The key conclusions are expected to apply more generally to other models and forcing scenarios. [ABSTRACT FROM AUTHOR]

The extent to which the climate will change due to an external forcing depends largely on radiative feedbacks, which act to amplify or damp the surface temperature response. There are a variety of issues that complicate the analysis of radiative feedbacks in global climate models, resulting in some confusion regarding their strengths and distributions. In this paper, the authors present a method for quantifying climate feedbacks based on “radiative kernels” that describe the differential response of the top-of-atmosphere radiative fluxes to incremental changes in the feedback variables. The use of radiative kernels enables one to decompose the feedback into one factor that depends on the radiative transfer algorithm and the unperturbed climate state and a second factor that arises from the climate response of the feedback variables. Such decomposition facilitates an understanding of the spatial characteristics of the feedbacks and the causes of intermodel differences. This technique provides a simple and accurate way to compare feedbacks across different models using a consistent methodology. Cloud feedbacks cannot be evaluated directly from a cloud radiative kernel because of strong nonlinearities, but they can be estimated from the change in cloud forcing and the difference between the full-sky and clear-sky kernels. The authors construct maps to illustrate the regional structure of the feedbacks and compare results obtained using three different model kernels to demonstrate the robustness of the methodology. The results confirm that models typically generate globally averaged cloud feedbacks that are substantially positive or near neutral, unlike the change in cloud forcing itself, which is as often negative as positive. [ABSTRACT FROM AUTHOR]

Eight earth system models of intermediate complexity (EMICs) are used to project climate change commitments for the recent Intergovernmental Panel on Climate Change’s (IPCC’s) Fourth Assessment Report (AR4). Simulations are run until the year 3000 a.d. and extend substantially farther into the future than conceptually similar simulations with atmosphere–ocean general circulation models (AOGCMs) coupled to carbon cycle models. In this paper the following are investigated: 1) the climate change commitment in response to stabilized greenhouse gases and stabilized total radiative forcing, 2) the climate change commitment in response to earlier CO2 emissions, and 3) emission trajectories for profiles leading to the stabilization of atmospheric CO2 and their uncertainties due to carbon cycle processes. Results over the twenty-first century compare reasonably well with results from AOGCMs, and the suite of EMICs proves well suited to complement more complex models. Substantial climate change commitments for sea level rise and global mean surface temperature increase after a stabilization of atmospheric greenhouse gases and radiative forcing in the year 2100 are identified. The additional warming by the year 3000 is 0.6–1.6 K for the low-CO2 IPCC Special Report on Emissions Scenarios (SRES) B1 scenario and 1.3–2.2 K for the high-CO2 SRES A2 scenario. Correspondingly, the post-2100 thermal expansion commitment is 0.3–1.1 m for SRES B1 and 0.5–2.2 m for SRES A2. Sea level continues to rise due to thermal expansion for several centuries after CO2 stabilization. In contrast, surface temperature changes slow down after a century. The meridional overturning circulation is weakened in all EMICs, but recovers to nearly initial values in all but one of the models after centuries for the scenarios considered. Emissions during the twenty-first century continue to impact atmospheric CO2 and climate even at year 3000. All models find that most of the anthropogenic carbon emissions are eventually taken up by the ocean (49%–62%) in year 3000, and that a substantial fraction (15%–28%) is still airborne even 900 yr after carbon emissions have ceased. Future stabilization of atmospheric CO2 and climate change requires a substantial reduction of CO2 emissions below present levels in all EMICs. This reduction needs to be substantially larger if carbon cycle–climate feedbacks are accounted for or if terrestrial CO2 fertilization is not operating. Large differences among EMICs are identified in both the response to increasing atmospheric CO2 and the response to climate change. This highlights the need for improved representations of carbon cycle processes in these models apart from the sensitivity to climate change. Sensitivity simulations with one single EMIC indicate that both carbon cycle and climate sensitivity related uncertainties on projected allowable emissions are substantial. [ABSTRACT FROM AUTHOR]

Uncertainties in observed records of atmospheric temperature aloft remain poorly quantified. This has resulted in considerable controversy regarding signals of climate change over recent decades from temperature records of radiosondes and satellites. This work revisits the problems associated with the removal of inhomogeneities from the historical radiosonde temperature records, and provides a method for quantifying uncertainty in an adjusted radiosonde climate record due to the subjective choices made during the data homogenization. This paper presents an automated homogenization method designed to replicate the decisions made by manual judgment in the generation of an earlier radiosonde dataset [i.e., the Hadley Centre radiosonde temperature dataset (HadAT)]. A number of validation experiments have been conducted to test the system performance and impact on linear trends. Using climate model data to simulate biased radiosonde data, the authors show that limitations in the homogenization method are sufficiently large to explain much of the tropical trend discrepancy between HadAT and estimates from satellite platforms and climate models. This situation arises from the combination of systematic (unknown magnitude) and random uncertainties (of order 0.05 K decade-1) in the radiosonde data. Previous assessment of trends and uncertainty in HadAT is likely to have underestimated the systematic bias in tropical mean temperature trends. This objective assessment of radiosonde homogenization supports the conclusions of the synthesis report of the U.S. Climate Change Science Program (CCSP), and associated research, regarding potential bias in tropospheric temperature records from radiosondes. [ABSTRACT FROM AUTHOR]

In this paper, a series of observing system simulation experiments (OSSEs) are used to study the design of a proposed array of instrumented moorings in the Indian Ocean (IO) outlined by the IO panel of the Climate Variability and Predictability (CLIVAR) Project. Fields of the Ocean Topography Experiment (TOPEX)/Poseidon (T/P) and Jason sea surface height (SSH) and sea surface temperature (SST) are subsampled to simulate dynamic height and SST data from the proposed array. Two different reduced-order versions of the Kalman filter are used to reconstruct the original fields from the simulated observations with the objective of determining the optimal deployment of moored platforms and to address the issue of redundancy and array simplification. The experiments indicate that, in terms of the reconstruction of SSH and SST, the location of the subjectively proposed array compareS favorably with the optimally defined one. The only significant difference between the proposed IO array and the optimal array is the lack of justification for increasing the latitudinal resolution near the equator (i.e., moorings 1.5°S and 1.5°N). An analysis of the redundancy also identifies the equatorial region as the one with the largest amount of redundant information. Thus, in the context of these fields, these results may help define the prioritization of its deployment or redefine the array to extend its latitudinal extent while maintaining the same amount of stations. [ABSTRACT FROM AUTHOR]

In this paper the extensive integrations produced for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) are used to examine the relationship between ENSO and monsoons at interannual and decadal time scales. The study begins with an analysis of the monsoon simulation in the twentieth-century integrations. Six of the 18 models were found to have a reasonably realistic representation of monsoon precipitation climatology. For each of these six models SST and anomalous precipitation evolution along the equatorial Pacific during El Niño events display considerable differences when compared to observations. Out of these six models only four [Geophysical Fluid Dynamics Laboratory Climate Model versions 2.0 and 2.1 (GFDL_CM_2.0 and GFDL_CM_2.1), Meteorological Research Institute (MRI) model, and Max Planck Institute ECHAM5 (MPI_ECHAM5)] exhibit a robust ENSO–monsoon contemporaneous teleconnection, including the known inverse relationship between ENSO and rainfall variations over India. Lagged correlations between the all-India rainfall (AIR) index and Niño-3.4 SST reveal that three models represent the timing of the teleconnection, including the spring predictability barrier, which is manifested as the transition from positive to negative correlations prior to the monsoon onset. Furthermore, only one of these three models (GFDL_CM_2.1) captures the observed phase lag with the strongest anticorrelation of SST peaking 2–3 months after the summer monsoon, which is partially attributable to the intensity of the simulated El Niño itself. The authors find that the models that best capture the ENSO–monsoon teleconnection are those that correctly simulate the timing and location of SST and diabatic heating anomalies in the equatorial Pacific and the associated changes to the equatorial Walker circulation during El Niño events. The strength of the AIR-Niño-3.4 SST correlation in the model runs waxes and wanes to some degree on decadal time scales. The overall magnitude and time scale for this decadal modulation in most of the models is similar to that seen in observations. However, there is little consistency in the phase among the realizations, suggesting a lack of predictability of the decadal modulation of the monsoon–ENSO relationship. The analysis was repeated for each of the four models using results from integrations in which the atmospheric CO2 concentration was raised to twice preindustrial values. From these “best” models in the double CO2 simulations there are increases in both the mean monsoon rainfall over the Indian subcontinent (by 5%–25%) and in its interannual variability (5%–10%). For each model the ENSO–monsoon correlation in the global warming runs is very similar to that in the twentieth-century runs, suggesting that the ENSO–monsoon connection will not weaken as global climate warms. This result, though plausible, needs to be taken with some caution because of the diversity in the simulation of ENSO variability in the coupled models that have been analyzed. Implications of the present results for monsoon prediction are discussed. [ABSTRACT FROM AUTHOR]

The detection and attribution of climate change in the observed record play a central role in synthesizing knowledge of the climate system. Unfortunately, the traditional method for detecting and attributing changes due to multiple forcings requires large numbers of general circulation model (GCM) simulations incorporating different initial conditions and forcing scenarios, and these have only been performed with a small number of GCMs. This paper presents an extension to the fingerprinting technique that permits the inclusion of GCMs in the multisignal analysis of surface temperature even when the required families of ensembles have not been generated. This is achieved by fitting a series of energy balance models (EBMs) to the GCM output in order to estimate the temporal response patterns to the various forcings. This methodology is applied to the very large Challenge ensemble of 62 simulations of historical climate conducted with the NCAR Community Climate System Model version 1.4 (CCSM1.4) GCM, as well as some simulations from other GCMs. Considerable uncertainty exists in the estimates of the parameters in fitted EBMs. Nevertheless, temporal response patterns from these EBMs are more reliable and the combined EBM time series closely mimics the GCM in the context of transient forcing. In particular, detection and attribution results from this technique appear self-consistent and consistent with results from other methods provided that all major forcings are included in the analysis. Using this technique on the Challenge ensemble, the estimated responses to changes in greenhouse gases, tropospheric sulfate aerosols, and stratospheric volcanic aerosols are all detected in the observed record, and the responses to the greenhouse gases and tropospheric sulfate aerosols are both consistent with the observed record without a scaling of the amplitude being required. The result is that the temperature difference of the 1996–2005 decade relative to the 1940–49 decade can be attributed to greenhouse gas emissions, with a partially offsetting cooling from sulfate emissions and little contribution from natural sources. The results support the viability of the new methodology as an extension to current analysis tools for the detection and attribution of climate change, which will allow the inclusion of many more GCMs. Shortcomings remain, however, and so it should not be considered a replacement to traditional techniques. [ABSTRACT FROM AUTHOR]

This review paper discusses the physical basis and the potential for decadal climate predictability over the Atlantic and its adjacent land areas. Many observational and modeling studies describe pronounced decadal and multidecadal variability in the Atlantic Ocean. However, it still needs to be quantified to which extent the variations in the ocean drive variations in the atmosphere and over land. In particular, although a clear impact of the Tropics on the midlatitudes has been demonstrated, it is unclear if and how the extratropical atmosphere responds to midlatitudinal sea surface temperature anomalies. Although the mechanisms behind the decadal to multidecadal variability in the Atlantic sector are still controversial, there is some consensus that some of the longer-term multidecadal variability is driven by variations in the thermohaline circulation. The variations in the North Atlantic thermohaline circulation appear to be predictable one to two decades ahead, as shown by a number of perfect model predictability experiments. The next few decades will be dominated by these multidecadal variations, although the effects of anthropogenic climate change are likely to introduce trends. Some impact of the variations of the thermohaline circulation on the atmosphere has been demonstrated in some studies so that useful decadal predictions with economic benefit may be possible. [ABSTRACT FROM AUTHOR]

The question of the impact of the Atlantic on North American (NA) seasonal prediction skill and predictability is examined. Basic material is collected from the literature, a review of seasonal forecast procedures in Canada and the United States, and some fresh calculations using the NCEP–NCAR reanalysis data. The general impression is one of low predictability (due to the Atlantic) for seasonal mean surface temperature and precipitation over NA. Predictability may be slightly better in the Caribbean and the (sub)tropical Americas, even for precipitation. The NAO is widely seen as an agent making the Atlantic influence felt in NA. While the NAO is well established in most months, its prediction skill is limited. Year-round evidence for an equatorially displaced version of the NAO (named ED_NAO) carrying a good fraction of the variance is also found. In general the predictability from the Pacific is thought to dominate over that from the Atlantic sector, which explains the minimal number of reported Atmospheric Model Intercomparison Project (AMIP) runs that explore Atlantic-only impacts. Caveats are noted as to the question of the influence of a single predictor in a nonlinear environment with many predictors. Skill of a new one-tier global coupled atmosphere–ocean model system at NCEP is reviewed; limited skill is found in midlatitudes and there is modest predictability to look forward to. There are several signs of enthusiasm in the community about using “trends” (low-frequency variations): (a) seasonal forecast tools include persistence of last 10 years’ averaged anomaly (relative to the official 30-yr climatology), (b) hurricane forecasts are based largely on recognizing a global multidecadal mode (which is similar to an Atlantic trend mode in SST), and (c) two recent papers, one empirical and one modeling, giving equal roles to the (North) Pacific and Atlantic in “explaining” variations in drought frequency over NA on a 20 yr or longer time scale during the twentieth century. [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]

Three interrelated climate phenomena are at the center of the Climate Variability and Predictability (CLIVAR) Atlantic research: tropical Atlantic variability (TAV), the North Atlantic Oscillation (NAO), and the Atlantic meridional overturning circulation (MOC). These phenomena produce a myriad of impacts on society and the environment on seasonal, interannual, and longer time scales through variability manifest as coherent fluctuations in ocean and land temperature, rainfall, and extreme events. Improved understanding of this variability is essential for assessing the likely range of future climate fluctuations and the extent to which they may be predictable, as well as understanding the potential impact of human-induced climate change. CLIVAR is addressing these issues through prioritized and integrated plans for short-term and sustained observations, basin-scale reanalysis, and modeling and theoretical investigations of the coupled Atlantic climate system and its links to remote regions. In this paper, a brief review of the state of understanding of Atlantic climate variability and achievements to date is provided. Considerable discussion is given to future challenges related to building and sustaining observing systems, developing synthesis strategies to support understanding and attribution of observed change, understanding sources of predictability, and developing prediction systems in order to meet the scientific objectives of the CLIVAR Atlantic program. [ABSTRACT FROM AUTHOR]