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This paper examines the possible influence of external forcings on observed changes in precipitation extremes in the mid-to-high latitudes of Asia during 1958–2012 and attempts to identify particular extreme precipitation indices on which there are better chances to detect the influence of external forcings. We compare a recently compiled dataset of observed extreme indices with those from phase 5 of the Coupled Model Intercomparison Project (CMIP5) simulations using an optimal fingerprinting method. We consider six indices that characterize different aspects of extreme precipitation, including annual maximum amount of precipitation falling in 1 day (Rx1day) or 5 days (Rx5day), the total amount of precipitation from the top 5% or top 1% daily amount on wet days, and the fraction of the annual total precipitation from these events. For single-signal analysis, the fingerprints of external forcings including anthropogenic agents are robustly detected in most studied extreme indices over all Asia and for midlatitude Asia but not for high-latitude Asia. For two-signal analysis, anthropogenic influence is detectable in these indices over Asia at 5% or slightly less than 5% significance level, whereas natural influence is not detectable. In high-latitude Asia, anthropogenic influence is detected only in a fractional index, representing a stark contrast to the midlatitude and full Asia results. We find relatively smaller internal variability and thus higher signal-to-noise ratio in the fractional indices when compared with the other ones. Our results point to the need for studying precipitation extreme indices that are less affected by internal variability while still representing the relevant nature of precipitation extremes to improve the possibility of detecting a forced signal if one is present in the data. [ABSTRACT FROM AUTHOR]

Ninety-five percent of climate models contributing to phase 5 of the Coupled Model Intercomparison Project (CMIP5) project early summer [October–December (OND)] rainfall declines over subtropical southern Africa by the end of the century, under all emissions forcing pathways. The intermodel consensus underlies the Intergovernmental Panel on Climate Change (IPCC) assessment that rainfall declines are "likely" and implies that significant climate change adaptation is needed. However, model consensus is not necessarily a good indicator of confidence, especially given that there is an order of magnitude difference in the scale of rainfall decline among models in OND (from <10 mm season−1 to ~100 mm season−1), and that the CMIP5 ensemble systematically overestimates present-day OND precipitation over subtropical southern Africa (in some models by a factor of 2). In this paper we investigate the uncertainty in the OND drying signal by evaluating the climate mechanisms that underlie the diversity in model rainfall projections. Models projecting the highest-magnitude drying simulate the largest increases in tropospheric stability over subtropical southern Africa associated with anomalous upper-level subsidence, reduced evaporation, and amplified surface temperature change. Intermodel differences in rainfall projections are in turn related to the large-scale adjustment of the tropical atmosphere to emissions forcing: models with the strongest relative warming of the northern tropical sea surface temperatures compared to the tropical mean warming simulate the largest rainfall declines. The models with extreme rainfall declines also tend to simulate large present-day biases in rainfall and in atmospheric stability, leading the authors to suggest that projections of high-magnitude drying require further critical attention. [ABSTRACT FROM AUTHOR]

This paper scrutinizes the zonal oscillation of the western North Pacific subtropical high (WNPSH) via diagnosing its two extreme phases, which are defined by the top 10% strongest (positive phase) and the weakest (negative phase) WNPSH index (WNPSHI) days during summers in 1979–2016. Key findings include the following: a tripole pattern consisting of intensified (weakened) precipitation over the Maritime Continent and the East Asian summer monsoon regions, and suppressed (strengthened) precipitation over the western North Pacific summer monsoon region during positive (negative) WNPSH phases; a westward movement of WNPSH-induced precipitation anomalies that subsequently affects eastern China, Japan, and the Korean Peninsula at different time lags; an OLR–vorticity pattern explained by atmospheric responses to thermal sources is suggested to drive the oscillation; and the competitive interaction of local air–sea feedbacks, especially during the positive phase. In addition, moderate-to-strong positive correlations between the WNPSHI and the Niño-3.4 index are found on 1–2-, 2–3-, and 3–6-yr time scales; both exhibit decadal shifts to a higher-frequency mode, suggesting the intensification of both the zonal WNPSH oscillation and the ENSO under the changing climate and their close interdecadal association. A nonlinear quasi-biennial WNPSH–ENSO relationship is identified: the positive (negative) WNPSH phase sometimes occurs during 1) a decaying El Niño (La Niña) in the preceding summer/autumn, and/or 2) a developing La Niña (El Niño) in the current summer/autumn. A full ENSO transition from moderate-to-strong El Niño to La Niña is often seen during the positive phase, offering potential in predicting ENSO events and extreme WNPSH phases and thereby the summer monsoon rainfall in East Asia. [ABSTRACT FROM AUTHOR]

This paper shows that joint temperature-precipitation information over a global domain provides a more accurate estimate of aerosol forced responses in climate models than does any other combination of temperature, precipitation, or sea level pressure. This fact is demonstrated using a new quantity called potential detectability, which measures the extent to which a forced response can be detected in a model. In particular, this measure can be evaluated independently of observations and therefore permits efficient exploration of a large number of variable combinations before performing optimal fingerprinting on observations. This paper also shows that the response to anthropogenic aerosol forcing can be separated from that of other forcings using only spatial structure alone, leaving the time variation of the response to be inferred from data, thereby demonstrating that temporal information is not necessary for detection. The spatial structure of the forced response is derived by maximizing the signal-to-noise ratio. For single variables, the north-south hemispheric gradient and equator-to-pole latitudinal gradient are important spatial structures for detecting anthropogenic aerosols in some models but not all. Sea level pressure is not an independent detection variable because it is derived partly from surface temperature. In no case does sea level pressure significantly enhance potential detectability beyond that already possible using surface temperature. Including seasonal or land-sea contrast information does not significantly enhance detectability of anthropogenic aerosol responses relative to annual means over global domains. [ABSTRACT FROM AUTHOR]

Future projections of precipitation at regional scales are vital to inform climate change adaptation activities. Therefore, is it important to quantify projected changes and associated uncertainty, and understand model processes responsible. This paper addresses these challenges for southern Africa and the adjacent Indian Ocean focusing on the local wet season. Precipitation projections for the end of the twenty-first century indicate a pronounced dipole pattern in the CMIP5 multimodel mean. The dipole indicates future wetting (drying) to the north (south) of the climatological axis of maximum rainfall, implying a northward shift of the ITCZ and south Indian Ocean convergence zone that is not consistent with a simple "wet get wetter" pattern. This pattern is most pronounced in early austral summer, suggesting a later and shorter wet season over much of southern Africa. Using a decomposition method we determine physical mechanisms underlying this dipole pattern of projected change, and the associated intermodel uncertainty. The projected dipole pattern is largely associated with the dynamical component of change indicative of shifts in the location of convection. Over the Indian Ocean, this apparent northward shift in the ITCZ may reflect the response to changes in the north-south SST gradient over the Indian Ocean, consistent with a "warmest get wetter" mechanism. Over land subtropical drying is relatively robust, particularly in the early wet season. This has contributions from dynamical shifts in the location of convection, which may be related to regional SST structures in the southern Indian Ocean, and the thermodynamic decline in relative humidity. Implications for understanding and potentially constraining uncertainty in projections are discussed. [ABSTRACT FROM AUTHOR]

The IPCC Fifth Assessment Report highlighted large uncertainty in European precipitation changes in the coming century. This paper investigates the sources of intermodel differences using CMIP5 model European precipitation data. The contribution of atmospheric circulation to differences in precipitation trends is investigated by applying cluster analysis to daily mean sea level pressure (MSLP) data. The resulting classification is used to reconstruct monthly precipitation time series, thereby isolating the component of precipitation variability directly related to atmospheric circulation. Reconstructed observed precipitation and reconstructions of simulated historical and projection data are well correlated with the original precipitation series, showing that circulation variability accounts for a substantial fraction of European precipitation variability. Removing the reconstructed precipitation from the original precipitation leaves a residual component related to noncirculation effects (and any small remaining circulation effects). Intermodel spread in residual future European precipitation trends is substantially reduced compared to the spread of the original precipitation trends. Uncertainty in future atmospheric circulation accounts for more than half of the intermodel variance in twenty-first-century precipitation trends for winter months for both northern and southern Europe. Furthermore, a substantial part of this variance is related to different forced dynamical responses in different models and is therefore potentially reducible. These results highlight the importance of understanding future changes in atmospheric dynamics in achieving more robust projections of regional climate change. Finally, the possible dynamical mechanisms that may drive the future differences in regional circulation and precipitation are illustrated by examining simulated teleconnections with tropical precipitation. [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]

This paper examines the controls on global precipitation that are evident in the transient experiments conducted using coupled climate models collected for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). The change in precipitation, water vapor, clouds, and radiative heating of the atmosphere evident in the 1% increase in carbon dioxide until doubled (1pctto2x) scenario is examined. As noted in other studies, the ensemble-mean changes in water vapor as carbon dioxide is doubled occur at a rate similar to that predicted by the Clausius–Clapeyron relationship. The ratio of global changes in precipitation to global changes in water vapor offers some insight on how readily increased water vapor is converted into precipitation in modeled climate change. This ratio ℇ is introduced in this paper as a gross indicator of the global precipitation efficiency under global warming. The main findings of this paper are threefold. First, increases in the global precipitation track increase atmospheric radiative energy loss and the ratio of precipitation sensitivity to water vapor sensitivity is primarily determined by changes to this atmospheric column energy loss. A reference limit to this ratio is introduced as the rate at which the emission of radiation from the clear-sky atmosphere increases as water vapor increases. It is shown that the derived efficiency based on the simple ratio of precipitation to water vapor sensitivities of models in fact closely matches the sensitivity derived from simple energy balance arguments involving changes to water vapor emission alone. Second, although the rate of increase of clear-sky emission is the dominant factor in the change to the energy balance of the atmosphere, there are two important and offsetting processes that contribute to ℇ in the model simulations studied: One involves a negative feedback through cloud radiative heating that acts to reduce the efficiency; the other is the global reduction in sensible heating that counteracts the effects of the cloud feedback and increases the efficiency. These counteracting feedbacks only apply on the global scale. Third, the negative cloud radiative heating feedback occurs through reductions of cloud amount in the middle troposphere, defined as the layer between 680 and 440 hPa, and by slight global cloud decreases in the lower troposphere. These changes act in a manner to expose the warmer atmosphere below to high clouds, thus resulting in a net warming of the atmospheric column by clouds and a negative feedback on the precipitation. [ABSTRACT FROM AUTHOR]

An important goal of the Climate Variability and Predictability (CLIVAR) research on the American monsoon systems is to determine the sources and limits of predictability of warm season precipitation, with emphasis on weekly to interannual time scales. This paper reviews recent progress in the understanding of the American monsoon systems and identifies some of the future challenges that remain to improve warm season climate prediction. Much of the recent progress is derived from complementary international programs in North and South America, namely, the North American Monsoon Experiment (NAME) and the Monsoon Experiment South America (MESA), with the following common objectives: 1) to understand the key components of the American monsoon systems and their variability, 2) to determine the role of these systems in the global water cycle, 3) to improve observational datasets, and 4) to improve simulation and monthly-to-seasonal prediction of the monsoons and regional water resources. Among the recent observational advances highlighted in this paper are new insights into moisture transport processes, description of the structure and variability of the South American low-level jet, and resolution of the diurnal cycle of precipitation in the core monsoon regions. NAME and MESA are also driving major efforts in model development and hydrologic applications. Incorporated into the postfield phases of these projects are assessments of atmosphere–land surface interactions and model-based climate predictability experiments. As CLIVAR research on American monsoon systems evolves, a unified view of the climatic processes modulating continental warm season precipitation is beginning to emerge. [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]

Subgrid variability in rainfall distribution has been widely recognized as an important factor to include in the representation of land surface hydrology within climate models. In this paper, using West Africa as a case study, the impact of the subgrid variability in rainfall interception on the modeling of the biosphere--atmosphere system is investigated. According to the authors' results, when neglecting the rainfall spatial variability, even if the impact on the total evapotranspiration is negligible, significant errors may result in the representation of surface hydrological processes and surface energy balance. These findings are consistent with the results of previous studies. However, in this paper, this issue is further explored and it is demonstrated that the extent of the resulting errors is not limited to the land surface processes. They extend to the atmosphere via the low-level cloud feedback to impact solar radiation, boundary layer energy, atmospheric circulation, and the distribution of precipitation. The same errors also propagate into the biosphere through vegetation dynamics and can eventually lead to a significantly different biosphere--atmosphere equilibrium state. This study provides a good example for the need to have physical realism in modeling the subgrid variability and most other details of the complex biosphere-- atmosphere--ocean system. [ABSTRACT FROM AUTHOR]

Subgrid variability in rainfall distribution has been widely recognized as an important factor to include in the representation of land surface hydrology within climate models. In this paper, using West Africa as a case study, the impact of the subgrid variability in rainfall interception on the modeling of the biosphere--atmosphere system is investigated. According to the authors results, when neglecting the rainfall spatial variability, even if the impact on the total evapotranspiration is negligible, significant errors may result in the representation of surface hydrological processes and surface energy balance. These findings are consistent with the results of previous studies. However, in this paper, this issue is further explored and it is demonstrated that the extent of the resulting errors is not limited to the land surface processes. They extend to the atmosphere via the low-level cloud feedback to impact solar radiation, boundary layer energy, atmospheric circulation, and the distribution of precipitation. The same errors also propagate into the biosphere through vegetation dynamics and can eventually lead to a significantly different biosphere--atmosphere equilibrium state. This study provides a good example for the need to have physical realism in modeling the subgrid variability and most other details of the complex biosphere-- atmosphere--ocean system. [ABSTRACT FROM AUTHOR]

The intertropical convergence zone (ITCZ) has been the focus of considerable research in recent years, with much of this work concerned with how the latitude of maximum tropical precipitation responds to natural climate variability and to radiative forcing. The width of the ITCZ, however, has received little attention despite its importance for regional climate and for understanding the general circulation of the atmosphere. This paper investigates the ITCZ width in simulations with an idealized general circulation model over a wide range of climates. The ITCZ, defined as the tropical region where there is time-mean ascent, displays rich behavior as the climate varies, widening with warming in cool climates, narrowing in temperate climates, and maintaining a relatively constant width in hot climates. The mass and energy budgets of the Hadley circulation are used to derive expressions for the area of the ITCZ relative to the area of the neighboring descent region, and for the sensitivity of the ITCZ area to changes in climate. The ITCZ width depends primarily on four quantities: the net energy input to the tropical atmosphere, the advection of moist static energy by the Hadley circulation, the transport of moist static energy by transient eddies, and the gross moist stability. Different processes are important for the ITCZ width in different climates, with changes in gross moist stability generally having a weak influence relative to the other processes. The results are likely to be useful for analyzing the ITCZ width in complex climate models and for understanding past and future climate change in the tropics. [ABSTRACT FROM AUTHOR]

Solar radiation management (SRM) has been proposed as a form of geoengineering to reduce the climate effects of anthropogenic greenhouse gas emissions. Modeling studies have concluded that SRM, through a reduction in total solar irradiance by approximately 2%, roughly compensates for global mean temperature changes from a doubling of carbon dioxide concentrations. This paper examines the impact of SRM on the terrestrial hydrologic cycle using the Community Land Model, version 4, coupled to the Community Atmosphere Model, version 4, with reductions in solar radiation relative to simulations with present-day and elevated CO2 concentrations. There are significant global and regional impacts due to vegetation-climate interactions that are not compensated when reductions in total solar irradiance of 1%, 2%, and 3% are imposed on top of a doubling of present-day CO2 concentrations. Water cycling slows down under SRM, including decreases in global mean precipitation and evapotranspiration. Changes in runoff and soil moisture are spatially and temporally variable, with implications for local water availability. In the tropics, evapotranspiration decreases because of increases in vegetation water use efficiency. In northern midlatitudes, soil moisture increases when evapotranspiration decreases, with some exceptions during boreal summer. Changes in soil evaporation influence water cycling in the southern subtropics, rather than changes in transpiration. The hydrologic response to SRM is nonlinear, with global mean decreases greater than expected. These results imply that SRM may not compensate for higher greenhouse gas concentrations when one considers land-atmosphere interactions. [ABSTRACT FROM AUTHOR]

This paper investigates climate change signals of Southern Hemisphere (SH) moisture flux simulated by three members of one CMIP3 coupled atmosphere-ocean general circulation model (AOGCM) and a multimodel ensemble of CMIP5 simulations. Generally, flux changes are dominated by increased atmospheric moisture due to temperature increase in the future climate projections. An approach is presented to distinguish between thermodynamical and dynamical influences on moisture flux. Furthermore, a physical interpretation of the transport changes due to dynamics is investigated by decomposing atmospheric waves into different length scales and temporal variations. Signals of moisture flux are compared with fluctuations of geopotential height fields as well as climate signals of extratropical cyclones. Moisture flux variability in the synoptic length scale with temporal variations shorter than 8 days can be assigned to the SH storm track. Climate change signals of these atmospheric waves show a distinctive poleward shift. This can be attributed to the climate change signal of extratropical cyclones. Furthermore, the climate change signal of atmospheric waves can be better understood if strong cyclones that intensify especially on the Eastern Hemisphere are taken into account. Antarctic net precipitation is calculated by means of the vertically integrated moisture flux. Future projections show increasing signals of net precipitation, whereas the dynamical part of net precipitation decreases. This can be understood by means of the low-variability component of synoptic-scale waves, which show a decreasing signal, especially off the coast of West Antarctica. This is shown to be due to changing variability of the Amundsen-Bellingshausen Seas low. [ABSTRACT FROM AUTHOR]

Simulations from a regional climate model (RCM) as part of a superensemble experiment were compared with observations of surface meteorological variables over the western United States. The RCM is the Hadley Centre Regional Climate Model, version 3, with improved physics parameterizations (HadRM3P) run at 25-km resolution and nested within the Hadley Centre Atmosphere Model, version 3 (HadAM3P). Overall, the means of seasonal temperature were well represented in the simulations; 95% of grid points were within 2.7°, 2.4°, and 3.6°C of observations in winter, spring, and summer, respectively. The model was too warm over most of the domain in summer except central California and southern Nevada. HadRM3P produced more extreme temperatures than observed. The overall magnitude and spatial pattern of precipitation were well characterized, though HadRM3P exaggerated the orographic enhancement along the coastal mountains, Cascade Range, and Sierra Nevada. HadRM3P produced warm/dry northwest, cool/wet southwest U.S. patterns associated with El Niño. However, there were notable differences, including the locations of the transition from warm (dry) to cool (wet) in the anomaly fields when compared with observations, though there was disagreement among observations. HadRM3P simulated the observed spatial pattern of mean annual temperature more faithfully than any of the RCM-GCM pairings in the North American Regional Climate Change Assessment Program (NARCCAP). Errors in mean annual precipitation from HadRM3P fell within the range of errors of the NARCCAP models. Last, this paper provided examples of the size of an ensemble required to detect changes at the local level and demonstrated the effect of parameter perturbation on regional precipitation. [ABSTRACT FROM AUTHOR]

The need to draw climate-related inferences from historical data makes understanding the biases and errors in these data critical. While climate data are collected at point-level monitoring sites, they are often postprocessed by averaging sites within a geographic area to align the data to a grid, easing analysis and visualization. Although this aggregation generally provides reasonable estimates of the mean, its use can be problematic for characterizing the full distribution of climate measures. Specifically, the process of averaging point-level data up to grid level can lead to inconsistencies, particularly when the grid box is heterogeneous and extremes are of interest. Point-level data are measured at individual points, while gridded data are the averaged product of many measurements within a larger spatial area. Because of this aggregation, point-level and grid-level distributions differ in many fundamental properties, such as their shape, skew, and tail behavior. This paper highlights these differences and their effects on analyses pertaining to current climatological questions. Mathematical relationships are derived to link the distributions of grid-level climate measures to the distributions of point-level climate measures using the notion of effective sample size. Then, these relationships are leveraged to propose a correction factor to use when modeling higher moments and extreme events. [ABSTRACT FROM AUTHOR]

This paper presents projected changes in temperature and precipitation extremes in China by the end of the twenty-first century based on the Coupled Model Intercomparison Project phase 5 (CMIP5) simulations. The temporal changes and their spatial patterns in the Expert Team on Climate Change Detection and Indices (ETCCDI) indices under the RCP4.5 and RCP8.5 emission scenarios are analyzed. Compared to the reference period 1986-2005, substantial changes are projected in temperature and precipitation extremes under both emission scenarios. These changes include a decrease in cold extremes, an increase in warm extremes, and an intensification of precipitation extremes. The intermodel spread in the projection increases with time, with wider spread under RCP8.5 than RCP4.5 for most indices, especially at the subregional scale. The difference in the projected changes under the two RCPs begins to emerge in the 2040s. Analyses based on the mixed-effects analysis of variance (ANOVA) model indicate that by the end of the twenty-first century, at the national scale, the dominant contributor to the projection uncertainty of most temperature-based indices, and some precipitation extremes [including maximum 1-day precipitation (RX1day) and maximum 5-day precipitation (RX5day), and total extremely wet day total amount (R95p)], is the difference in emission scenarios. By the end of the twenty-first century, model uncertainty is the dominant factor at the regional scale and for the other indices. Natural variability can also play very important role. [ABSTRACT FROM AUTHOR]

The importance of investigating regional climate changes associated with degrees of global warming is increasingly being recognized, but the majority of relevant research has been based on multimodel ensembles (MMEs) from the Coupled Model Intercomparison Project (CMIP). This has left two important questions unanswered: Are there plausible futures which are not represented by the models in CMIP? And, how would regional climates evolve under enhanced global warming, beyond 4°C? In this paper, two perturbed physics ensembles (PPEs) are used to address these issues with reference to African precipitation. Examination of model versions that generate warming greater than 4°C in the twenty-first century shows that changes in African precipitation are enhanced gradually, even to high global temperatures; however, there may be nonlinearities that are not incorporated here due to limited model complexity. The range of projections from the PPEs is compared to data from phases 3 and 5 of CMIP (CMIP3 and CMIP5), revealing regional differences. This is partly the result of implausible model versions, but the PPE dataset can be justifiably constrained given its size and systematic nature, highlighting an additional advantage over MMEs. After applying constraints, the PPEs still show changes that are outside the range of CMIP, most prominently strong dry signals in west equatorial Africa and the Sahel, implying that MMEs may underestimate risks for these regions. Analysis of African precipitation changes therefore demonstrates that regional assessments that rely on CMIP3 and CMIP5 may overlook uncertainties associated with model parameterizations and pronounced warming. More systematic approaches are needed for conservative estimates of danger. [ABSTRACT FROM AUTHOR]

The NCAR Community Earth System Model (CESM) now includes an atmospheric component that extends in altitude to the lower thermosphere. This atmospheric model, known as the Whole Atmosphere Community Climate Model (WACCM), includes fully interactive chemistry, allowing, for example, a self-consistent representation of the development and recovery of the stratospheric ozone hole and its effect on the troposphere. This paper focuses on analysis of an ensemble of transient simulations using CESM1(WACCM), covering the period from the preindustrial era to present day, conducted as part of phase 5 of the Coupled Model Intercomparison Project. Variability in the stratosphere, such as that associated with stratospheric sudden warmings and the development of the ozone hole, is in good agreement with observations. The signals of these phenomena propagate into the troposphere, influencing near-surface winds, precipitation rates, and the extent of sea ice. In comparison of tropospheric climate change predictions with those from a version of CESM that does not fully resolve the stratosphere, the global-mean temperature trends are indistinguishable. However, systematic differences do exist in other climate variables, particularly in the extratropics. The magnitude of the difference can be as large as the climate change response itself. This indicates that the representation of stratosphere-troposphere coupling could be a major source of uncertainty in climate change projections in CESM. [ABSTRACT FROM AUTHOR]

The response over West Africa to uniform warming of the Atlantic Ocean is analyzed using idealized simulations with a regional climate model. With warming of 1 and 1.5 K, rainfall rates increase by 30%-50% over most of West Africa. With Atlantic warming of 2 K and higher, coastal precipitation increases but Sahel rainfall decreases substantially. This nonlinear response in Sahel rainfall is the focus of this analysis. Atlantic warming is accompanied by decreases in low-level geopotential heights in the Gulf of Guinea and in the large-scale meridional geopotential height gradient. This leads to easterly wind anomalies in the central Sahel. With Atlantic warming below 2 K, these easterly anomalies support moisture transport from the Gulf of Guinea and precipitation increases. With Atlantic warming over 2 K, the easterly anomalies reverse the westerly flow over the Sahel. The resulting dry air advection into the Sahel reduces precipitation. Increased low-level moisture provides moist static energy to initiate convection with Atlantic warming at 1.5 K and below, while decreased moisture and stable thermal profiles suppress convection with additional warming. In all simulations, the southerly monsoon flow onto the Guinean coast is maintained and precipitation in that region increases. The relevance of these results to the global warming problem is limited by the focus on Atlantic warming alone. However, confident prediction of climate change requires an understanding of the physical processes of change, and this paper contributes to that goal. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal method for estimating time-dependent climate change signals from general circulation models. The basic idea is to identify vectors that maximize the mean-square detection statistic derived from optimal fingerprinting techniques. The method also provides an objective and systematic procedure for identifying the limit to which a signal can be restricted in space and time without losing detectability. As an illustration, the method is applied to the Coupled Model Intercomparison Project, phase 3 multimodel dataset to determine the continental seasonal-mean anomaly in surface air temperature and precipitation that is most detectable, on average, in these models. Anomalies in seasonal-mean surface air temperature are detectable in all seasons by almost all models on all continents but Europe; seasonal-mean anomalies over Europe are undetectable for some models, though this does not preclude other expressions of the signal, such as those that include longer time averages or time-lag information, from being detectable. Detectability in seasonal-mean temperature is found not only for multidecadal warming trends but also for cooling after major volcanic eruptions. In contrast, seasonal-mean precipitation anomalies are detectable in only a few models for averages over 5 yr or more, suggesting that the signal should include more spatiotemporal detail to be detectable across more models. Nevertheless, of the precipitation anomalies that are detectable, the signal appears to be of two characters: a systematic trend and enhanced frequency of extreme values. These results derived from twentieth-century simulations appear to be consistent with previous studies based on twenty-first-century simulations with larger signal-to-noise ratios. [ABSTRACT FROM AUTHOR]

This paper applies a new field significance test to establish the existence and consistency of ENSO teleconnection patterns across models and observations. An ENSO teleconnection pattern is defined as a field of regression coefficients between an index of the tropical Pacific sea surface temperature and a field of variables such as surface air temperature or precipitation. The test is applied to boreal winter and summer in six continents using observations and hindcasts from the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) and the ENSEMBLE-based predictions of climate changes and their impacts (ENSEMBLES) projects. This comparison represents one of the most comprehensive and up-to-date assessments of the extent to which ENSO teleconnection patterns exist and can be reproduced by coupled models. Statistically significant ENSO teleconnection patterns are detected in both observations and models and in all continents and in both winter and summer seasons, except in two cases: 1) Europe (both seasons and variables), and 2) North America (both variables in boreal summer). Despite many ENSO teleconnection patterns being significant, however, the patterns do not necessarily agree between observations and models. The degree of agreement between models and observations is characterized as 'robust,' 'moderate,' or 'low.' Only Australia and South America are found to have robust agreement between ENSO teleconnection patterns, and then only for limited seasons and variables. Although many of our conclusions regarding teleconnection patterns conform to previous studies, there are exceptions, including the fact that the teleconnection for boreal winter precipitation is generally accepted to exist in Africa but in fact has only low agreement with model simulations, while that in Asia is not widely recognized to exist but is found to be significant and in moderate agreement with model teleconnections. [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]

Observations have indicated a trend of freshwater loss in the global western boundary current extension regions over several recent decades. In this paper, the coupled ocean--atmosphere response to the observed freshwater flux trend [[defined as evaporation minus precipitation (EmP)]] over the Kuroshio--Oyashio Extension (KOE) region is studied in a series of coupled model experiments. The model explicitly demonstrates that the positive EmP forcing in the KOE region can set up a cyclonic gyre straddling the subtropical and the subpolar gyre, which induces anomalous southward cold advection in the west and northward warm advection in the interior. This leads to the formation of a temperature dipole in the midlatitudes with a cooling in the west and a warming in the east. With the positive EmP forcing in the KOE, the response of the extratropical atmospheric circulation in the North Pacific sector is characterized by an equivalent barotropic low originating primarily from the western tropical Pacific changes and countered by the extratropical SST forcing. The positive EmP forcing also strengthens the tropical zonal SST gradient and thus ENSO through several competing processes including the surface-coupled wind--evaporative--SST (WES) mechanism, subduction of extratropical warm anomalies, and spinup of the density-driven meridional overturning circulation. Applications to recent Pacific climate changes are discussed. [ABSTRACT FROM AUTHOR]

Diagnostics performed with twentieth-century (1861–2000) ensemble integrations of the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1 (CM2.1) suggest that, during the developing phase, El Niño events that co-occur with the Indian Ocean Dipole Zonal Mode (IODZM; class 1) are stronger than those without (class 2). Also, during class 1 events coherent sea surface temperature (SST) anomalies develop in the Indonesian seas that closely follow the life cycle of IODZM. This study investigates the effect of these regional SST anomalies (equatorial Indian Ocean and Indonesian seas) on the amplitude of the developing El Niño. An examination of class 1 minus class 2 composites suggests two conditions that could lead to a strong El Niño in class 1 events: (i) during January, ocean–atmosphere conditions internal to the equatorial Pacific are favorable for the development of a stronger El Niño and (ii) during May–June, coinciding with the development of regional SST anomalies, an abrupt increase in westerly wind anomalies is noticeable over the equatorial western Pacific with a subsequent increase in thermocline and SST anomalies over the eastern equatorial Pacific. This paper posits the hypothesis that, under favorable conditions in the equatorial Pacific, regional SST anomalies may enable the development of a stronger El Niño. Owing to a wealth of feedbacks in CM2.1, solutions from a linear atmosphere model forced with May–June anomalous precipitation and anomalous SST from selected areas over the equatorial Indo-Pacific are examined. Consistent with our earlier study, the net Kelvin wave response to contrasting tropical Indian Ocean heating anomalies cancels over the equatorial western Pacific. In contrast, Indonesian seas SST anomalies account for about 60%–80% of the westerly wind anomalies over the equatorial western Pacific and also induce anomalous precipitation over the equatorial central Pacific. It is argued that the feedback between the precipitation and circulation anomalies results in an abrupt increase in zonal wind anomalies over the equatorial western Pacific. Encouraged by these results, the authors further examined the processes that cause cold SST anomalies over the Indonesian seas using an ocean model. Sensitivity experiments suggest that local wind anomalies, through stronger surface heat loss and evaporation, and subsurface upwelling are the primary causes. The present results imply that in coupled models, a proper representation of regional air–sea interactions over the equatorial Indo-Pacific warm pool may be important to understand and predict the amplitude of El Niño. [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]

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]

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]

This article presents ongoing efforts to understand interactions between the North American monsoon and society in order to develop applications for monsoon research in a highly complex, multicultural, and binational region. The North American monsoon is an annual precipitation regime that begins in early June in Mexico and progresses northward to the southwestern United States. The region includes stakeholders in large urban complexes, productive agricultural areas, and sparsely populated arid and semiarid ecosystems. The political, cultural, and socioeconomic divisions between the United States and Mexico create a broad range of sensitivities to climate variability as well as capacities to use forecasts and other information to cope with climate. This paper highlights methodologies to link climate science with society and to analyze opportunities for monsoon science to benefit society in four sectors: natural hazards management, agriculture, public health, and water management. A list of stakeholder needs and a calendar of decisions is synthesized to help scientists link user needs to potential forecasts and products. To ensure usability of forecasts and other research products, iterative scientist–stakeholder interactions, through integrated assessments, are recommended. These knowledge-exchange interactions can improve the capacity for stakeholders to use forecasts thoughtfully and inform the development of research, and for the research community to obtain feedback on climate-related products and receive insights to guide research direction. It is expected that integrated assessments can capitalize on the opportunities for monsoon science to inform decision making and, in the best instances, reduce regional climate vulnerabilities and enhance regional sustainability. [ABSTRACT FROM AUTHOR]

The snowpack in the central Andes (30°–37°S) is the primary source for streamflow in central Chile and central-western Argentina, but few published studies are available on snowpack variability in the region. This paper develops the first regional snowpack series (1951–2005) from Chilean and Argentinean snow course records. This series shows a strong regional signal, marked interannual variability, and a positive, though nonsignificant, linear trend. Correlations with local precipitation and temperature records reveal a marked association with conditions in central Chile. High snow accumulation is generally concurrent with El Niño events in the tropical Pacific, but only 5 of the 10 driest years coincided with La Niña events. Evaluation of 500-hPa geopotential height anomaly maps during extreme snow years highlights the crucial significance of tropospheric conditions in the subtropical and southeast Pacific in modulating snowfall. Correlations with gridded SST and SLP data and multiple regressions with large-scale climatic indices corroborate a Pacific ENSO-related influence largely concentrated during the austral winter months. This hampers the predictability of snowpack before the onset of the cold season. Annual and warm-season river discharges on both sides of the cordillera are significantly correlated with the regional snowpack record and show positive linear trends over the 1951–2004 common period, probably related to a greater frequency of above-average snowpacks during recent decades. Future demand and competition for water resources in these highly populated regions will require detailed information about temporal and spatial variations in snow accumulation over the Andes. The results indicate that the relationships between snowpack and atmospheric circulation patterns prior to the winter season are complex, and more detailed analyses are necessary to improve prediction of winter snowfall totals. [ABSTRACT FROM AUTHOR]

The Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mark 2 global coupled climatic model has been used to generate a 10 000-yr simulation of “present” climate. The resultant dataset has been used to investigate a number of aspects of extremes associated with annual mean rainfall. Multimillennial time series of normalized rainfall amounts for selected points are used to highlight secular variability, spatial variations, and the differences between pluvial and drought conditions. Global distributions are also presented for selected rainfall characteristics, including the frequency of occurrence of specified rainfall anomalies with annual durations, the frequency of occurrence of 5-yr sequences of specified rainfall anomalies, and the maximum and minimum normalized rainfall amounts attained in the simulation. Such features cannot be obtained from observations because of their limited duration. A case study is also made of a megadrought over the southwestern United States, together with an analysis of the associated causal mechanisms. Given the exclusion of all external forcing from the model, it is concluded that the extreme annual mean rainfall extremes presented in the paper are attributable to stochastic events. [ABSTRACT FROM AUTHOR]

In this paper, the ability of model outputs from the Intergovernmental Panel on Climate Change (IPCC) to describe the natural internal variability of precipitation observations is evaluated. The analysis is focused on the Iberian Peninsula for December–February (DJF). The study was performed with observed data from National Meteorological Institutes, reanalysis data from the National Centers for Environmental Prediction–National Center for Atmospheric Research, teleconnection indices, and model simulations. First, the seasonal cycle, mean winter pattern, and tendency for nine model simulations were evaluated. Then, four models were selected to obtain interannual variability and to diagnose the links between precipitation and large-scale circulation. This intercomparison is based on the modes obtained by the empirical orthogonal function (EOF) and spectral analyses to investigate the temporal properties of the most significant spatial patterns. The models well reproduce the observed seasonal cycle and the mean winter pattern; however, they poorly capture the interannual variability found in observed data. To ascertain the reasons for these results, features affecting the precipitation process are considered by analyzing the relationships with the dominant modes of large-scale atmospheric fields, such as sea level pressure, storm activity, jet stream, moisture flux, and teleconnection indices. The precipitation response to the mean flow suggests signs of potential seasonal predictability in DJF. [ABSTRACT FROM AUTHOR]

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

This paper explores changes in the principal components of observed energy budgets across the tropical Pacific in response to the strong 1998 El Niño event. Multisensor observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Visible and Infrared Scanner (VIRS), and precipitation radar (PR) instruments aboard TRMM are used to quantify changes in radiative and latent heating in the east and west Pacific in response to the different phases of the El Niño–Southern Oscillation. In periods of normal east–west SST gradients there is substantial heating in the west Pacific and cooling in the east, implying strong eastward atmospheric energy transport. During the active phase of the El Niño, both the east and west Pacific tend toward local radiative–convective equilibrium resulting in their temporary energetic decoupling. It is further demonstrated that the response of these regions to ENSO-induced SST variability is directly related to changes in the characteristics of clouds and precipitation in each region. Through quantitative analysis of the radiative and latent heating properties of shallow, midlevel, and deep precipitation events and an equivalent set of nonprecipitating cloud systems, times of reduced atmospheric heating are found to be associated with a shift toward shallow and midlevel precipitation systems and associated low-level cloudiness. The precipitation from such systems is typically less intense, and they do not trap outgoing longwave radiation as efficiently as their deeper counterparts, resulting in reduced radiative and latent heating of the atmosphere. The results also suggest that the net effect of precipitating systems on top-of-the-atmosphere (TOA) fluxes and the efficiency with which they heat the atmosphere and cool the surface exhibit strong dependence on their surroundings. The sensitivity of cloud radiative impacts to the atmospheric and surface properties they act to modify implies the existence of strong feedbacks whose representation may pose a significant challenge to the climate modeling community. [ABSTRACT FROM AUTHOR]

In this paper, the authors analyze simulations of present and future climates in the western United States performed with four regional climate models (RCMs) nested within two global ocean–atmosphere climate models. The primary goal here is to assess the range of regional climate responses to increased greenhouse gases in available RCM simulations. The four RCMs used different geographical domains, different increased greenhouse gas scenarios for future-climate simulations, and (in some cases) different lateral boundary conditions. For simulations of the present climate, RCM results are compared to observations and to results of the GCM that provided lateral boundary conditions to the RCM. For future-climate (increased greenhouse gas) simulations, RCM results are compared to each other and to results of the driving GCMs. When results are spatially averaged over the western United States, it is found that the results of each RCM closely follow those of the driving GCM in the same region in both present and future climates. This is true even though the study area is in some cases a small fraction of the RCM domain. Precipitation responses predicted by the RCMs in many regions are not statistically significant compared to interannual variability. Where the predicted precipitation responses are statistically significant, they are positive. The models agree that near-surface temperatures will increase, but do not agree on the spatial pattern of this increase. The four RCMs produce very different estimates of water content of snow in the present climate, and of the change in this water content in response to increased greenhouse gases. [ABSTRACT FROM AUTHOR]

Daily precipitation data from worldwide stations and gridded analyses and from 18 coupled global climate models are used to evaluate the models' performance in simulating the precipitation frequency, intensity, and the number of rainy days contributing to most (i.e., 67%) of the annual precipitation total. Although the models examined here are able to simulate the land precipitation amount well, most of them are unable to reproduce the spatial patterns of the precipitation frequency and intensity. For light precipitation (1–10 mm day-1), most models overestimate the frequency but produce patterns of the intensity that are in broad agreement with observations. In contrast, for heavy precipitation (>10 mm day-1), most models considerably underestimate the intensity but simulate the frequency relatively well. The average number of rainy days contributing to most of the annual precipitation is a simple index that captures the combined effects of precipitation frequency and intensity on the water supply. The different measures of precipitation characteristics examined in this paper reveal region-to-region differences in the observations and models of relevance for climate variability, water resources, and climate change. [ABSTRACT FROM AUTHOR]

The 1976 Pacific climate shift is examined, and its manifestations and significance in Alaskan climatology during the last half-century are demonstrated. The Pacific Decadal Oscillation index shifted in 1976 from dominantly negative values for the 25-yr time period 1951–75 to dominantly positive values for the period 1977–2001. Mean annual and seasonal temperatures for the positive phase were up to 3.1°C higher than for the negative phase. Likewise, mean cloudiness, wind speeds, and precipitation amounts increased, while mean sea level pressure and geopotential heights decreased. The pressure decrease resulted in a deepening of the Aleutian low in winter and spring. The intensification of the Aleutian low increased the advection of relatively warm and moist air to Alaska and storminess over the state during winter and spring. The regime shift is also examined for its effect on the long-term temperature trends throughout the state. The trends that have shown climatic warming are strongly biased by the sudden shift in 1976 from the cooler regime to a warmer regime. When analyzing the total time period from 1951 to 2001, warming is observed; however, the 25-yr period trend analyses before 1976 (1951–75) and thereafter (1977–2001) both display cooling, with a few exceptions. In this paper, emphasis is placed on the importance of taking into account the sudden changes that result from abrupt climatic shifts, persistent regimes, and the possibility of cyclic oscillations, such as the PDO, in the analysis of long-term climate change in Alaska. [ABSTRACT FROM AUTHOR]

This paper discusses a study of temperature and precipitation indices that may be suitable for the early detection of anthropogenic change in climatic extremes. Anthropogenic changes in daily minimum and maximum temperature and precipitation over land simulated with two different atmosphere–ocean general circulation models are analyzed. The use of data from two models helps to assess which changes might be robust between models. Indices are calculated that scan the transition from mean to extreme climate events within a year. Projected changes in temperature extremes are significantly different from changes in seasonal means over a large fraction (39%–66%) of model grid points. Therefore, the detection of changes in seasonal mean temperature cannot be substituted for the detection of changes in extremes. The estimated signal-to-noise ratio for changes in extreme temperature is nearly as large as for changes in mean temperature. Both models simulate extreme precipitation changes that are stronger than the corresponding changes in mean precipitation. Climate change patterns for precipitation are quite different between the models, but both models simulate stronger increases of precipitation for the wettest day of the year (4.1% and 8.8%, respectively, over land) than for annual mean precipitation (0% and 0.7%, respectively). A signal-to-noise analysis suggests that changes in moderately extreme precipitation should become more robustly detectable given model uncertainty than changes in mean precipitation. [ABSTRACT FROM AUTHOR]

Empirical downscaling procedures relate large-scale atmospheric features with local features such as station rainfall in order to facilitate local scenarios of climate change. The purpose of the present paper is twofold: first, a downscaling technique is used as a diagnostic tool to verify the performance of climate models on the regional scale; second, a technique is proposed for verifying the validity of empirical downscaling procedures in climate change applications. The case considered is regional seasonal precipitation in Romania. The downscaling model is a regression based on canonical correlation analysis between observed station precipitation and European-scale sea level pressure (SLP). The climate models considered here are the T21 and T42 versions of the Hamburg ECHAM3 atmospheric GCM run in 'time-slice' mode. The climate change scenario refers to the expected time of doubled carbon dioxide concentrations around the year 2050. The downscaling model is skillful for all seasons except spring. The general features of the large-scale SLP variability are reproduced fairly well by both GCMs in all seasons. The climate models reproduce the empirically determined precipitation-SLP link in winter, whereas the observed link is only partially captured for the other seasons. Thus, these models may be considered skillful with respect to regional precipitation during winter, and partially during the other seasons. Generally, applications of statistical downscaling to climate change scenarios have been based on the assumption that the empirical link between the large-scale and regional parameters remains valid under a changed climate. In this study, a rationale is proposed for this assumption by showing the consistency of the 2 x CO[sub2] GCM scenarios in winter, derived directly from the gridpoint data, with the regional scenarios obtained through empirical downscaling. Since the skill of the GCMs in regional terms is already established, it is... [ABSTRACT FROM AUTHOR]