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Atmospheric rivers (ARs) that reach the complex terrain of High Mountain Asia (HMA) cause significant hydrological impacts for millions of people. While ARs are often associated with precipitation extremes and can cause floods and debris flows affecting populated communities, little is known about ARs that reach as far inland as HMA. This paper characterizes AR types and investigates dynamical mechanisms associated with the development of ARs that typically affect HMA. Combined empirical orthogonal function (cEOF) analysis using integrated water vapor transport (IVT) is applied to days where an AR reaches HMA. K-means cluster analysis applied to the first two principal components uncovered three subtypes of AR events with distinct synoptic characteristics during winter and spring months. The first subtype increases precipitation and IVT in Western HMA and is associated with a zonally oriented wave train propagating within the westerly jet waveguide. The second subtype is associated with enhanced southwesterly IVT, anomalous upper-level cyclonic circulation centered on 45 ∘ E, and precipitation in Northwestern HMA. The third subtype shows anomalous precipitation in Eastern HMA and southwesterly IVT across the Bay of Bengal. Interannual variations in the frequency of HMA ARs and relationships with various teleconnection patterns show that western HMA AR subtypes are sensitive to well-known remote large-scale climate factors, such as the El Niño Southern Oscillation, Arctic Oscillation, and the Siberian High. These results provide synoptic characterization of the three types of ARs that reach HMA and reveal the previously unexplored significance of their contribution to winter and spring precipitation. [ABSTRACT FROM AUTHOR]

Mesoscale convective systems (MCSs) are important warm-season precipitation systems in eastern China. However, our knowledge of their climatology and capability in their simulation is still insufficient. This paper examines their characteristics over the 2008–2017 warm seasons using convection-permitting climate simulations (CPCSs) with a 3-km grid spacing that explicitly resolves MCSs, as well as a high-resolution gauge-satellite merged precipitation product. An object-based tracking algorithm is applied to identify MCSs. Results indicate that the MCS genesis and occurrence are closely related to the progression of the East Asian monsoon and are modulated by the underlying topography. On average, about 243 MCSs are observed each season and contribute 19% and 47% to total and extreme warm-season precipitation. The climatological attributes and variabilities are reasonably reproduced in the CPCS. The major model deficiencies are excessive small MCS occurrence and overmuch MCS rainfall, consequently overestimating the precipitation contributions, whereas observational uncertainties may play a role too. Both the observed and simulated MCS precipitation feature a nocturnal or morning maximum and an eastward delayed diurnal peak east of the Tibetan Plateau, in contrast to the dominant afternoon peak of non-MCS precipitation. The favorable comparison with observations demonstrates the capability of CPCSs in simulating MCSs in the Asian monsoon climate, and its usefulness in projecting the future changes of MCSs under global warming. The finding that non-MCS precipitation is responsible for the high biased afternoon precipitation provides helpful guidance for further model improvement. [ABSTRACT FROM AUTHOR]

Gridded data products, for example interpolated daily measurements of precipitation from weather stations, are commonly used as a convenient substitute for direct observations because these products provide a spatially and temporally continuous and complete source of data. However, when the goal is to characterize climatological features of extreme precipitation over a spatial domain (e.g., a map of return values) at the native spatial scales of these phenomena, then gridded products may lead to incorrect conclusions because daily precipitation is a fractal field and hence any smoothing technique will dampen local extremes. To address this issue, we create a new "probabilistic" gridded product specifically designed to characterize the climatological properties of extreme precipitation by applying spatial statistical analysis to daily measurements of precipitation from the Global Historical Climatology Network over the contiguous United States. The essence of our method is to first estimate the climatology of extreme precipitation based on station data and then use a data-driven statistical approach to interpolate these estimates to a fine grid. We argue that our method yields an improved characterization of the climatology within a grid cell because the probabilistic behavior of extreme precipitation is much better behaved (i.e., smoother) than daily weather. Furthermore, the spatial smoothing innate to our approach significantly increases the signal-to-noise ratio in the estimated extreme statistics relative to an analysis without smoothing. Finally, by deriving a data-driven approach for translating extreme statistics to a spatially complete grid, the methodology outlined in this paper resolves the issue of how to properly compare station data with output from earth system models. We conclude the paper by comparing our probabilistic gridded product with a standard extreme value analysis of the Livneh gridded daily precipitation product. Our new data product is freely available on the Harvard Dataverse (https://bit.ly/2CXdnuj). [ABSTRACT FROM AUTHOR]

Dynamical downscaling (DD) consists in using archives of Coupled Global Climate Models (CGCM) simulations as the atmospheric and sea-surface boundary conditions (BC) to drive nested, Regional Climate Model (RCM) simulations. Biases in the CGCM-generated driving BC, however, can have detrimental impacts on RCM performance. It is well documented for the historical period that CGCM-simulated sea-surface temperatures (SST) suffer substantial biases, especially important near coastal regions. Assuming that these SST biases are time-invariant, they could in principle be subtracted from century-long CGCM projections before being used to drive RCMs. This paper investigates the performance of a 3-step DD approach as follows. The CGCM-simulated sea-surface temperatures (SST) are first empirically corrected by subtracting their systematic biases; the corrected SST are then used as ocean surface BC for an atmosphere-only GCM (AGCM) simulation; finally this AGCM simulation provides the atmospheric lateral BC to drive an RCM simulation. This is what we refer to as the 3-step approach CGCM–AGCM–RCM of DD, which can be compared to the traditional 2-step approach CGCM–RCM consisting of driving an RCM simulation directly by CGCM-generated BC. In this paper we compare the results obtained with the two approaches, for present and future climates under RCP8.5, using the fifth-generation Canadian Regional Climate Model (CRCM5) with a grid mesh of 0.22° over the North American CORDEX domain, driven by two CMIP5 models: the Canadian Earth System Model of the Canadian Centre for Climate modelling and analysis (CanESM2) and the Earth System Model of the Max-Planck-Institut für Meteorologie (MPI-ESM-MR). The results show that, in current climate, the seasonal-mean 2-m temperature fields simulated with the 3-step DD have generally smaller biases with respect to the observations than those simulated with the 2-step DD; in fact the performance of the 3-step DD simulations often approaches that of the reanalyses-driven simulation. For the seasonal-mean precipitation field, however, the differences between the two DD methods are not conclusive. Differences between the projected climate changes with the two DD methods vary substantially depending upon the variable being considered. Differences are particularly important for temperature: over the bulk of the North American continent, the 3-step DD projects more warming in winter and less in summer. This result highlights the nonlinearities of the climate system, and constitutes an additional measure of uncertainty with DD. [ABSTRACT FROM AUTHOR]

Using 30 years of hourly rain gauge records and reanalysis data, this paper reveals two types of heavy summer rainfall in central North China (CNC): the lasting mountain (LM) rainfall and the mountain-plain (MP) rainfall, and further explains their formation mechanisms. The evolutions of the rainfall are found to be closely connected to upper-tropospheric temperature anomalies. When upper-tropospheric warm (cold) anomalies dominate North China (the Japan Sea) and stretch down to lower layers, positive (negative) geopotential anomalies, which appear above the warm (cold) anomalies governed by hydrostatic equilibrium, extend from upper to lower troposphere. In the lower layers, evident low-level easterly anomalies form to the south (north) of the positive (negative) geopotential center, controlling the downstream of CNC and making convective systems difficult to progress eastward. Correspondingly, the low-level convergence and strong convection maintain in the west, and the rainfall persists over the mountains constituting the LM process. But when upper-tropospheric cold (warm) anomalies dominate the west (east) of 110°E and stretch down to lower layers, CNC is situated between an upstream trough and a downstream ridge. As the trough-ridge system progresses eastward, the low-level moisture tongue and strong convections in front of the trough move from the mountains to the plains, and the rainfall propagates downstream constituting the MP process. Results in this paper indicate that upper-tropospheric temperature has significant influence on the evolution of rainfall, and pay attention to its characteristics could provide helpful information in the analysis and forecasting of rainfall propagation. [ABSTRACT FROM AUTHOR]

The pre-summer rainy season (PSRS; April–June) is the period of most frequent strong precipitation in South China (SC). Persistent strong precipitation events (PSPEs) can cause greater loss of life and property than short-lived strong precipitation. This paper investigates extended-range signals near the tropopause preceding two persistent positive climatological intraseasonal oscillations (PPCISOs) in precipitation corresponding to two climatological PSPEs in SC during the PSRS, using the CISO analysis of isentropic potential vorticity (IPV). It is found that precursor signals can be better seen in IPV CISOs than in unfiltered IPV. The first rainfall PPCISO is caused by an eastward propagation of high-IPV CISOs along the dynamical tropopause originating from the Arctic region and west of the Tibetan Plateau. The second is the most persistent (13 days). Its high-IPV CISOs originate over the Arctic region and the tropical monsoon region, respectively, 20 or more days prior to the rainfall CISO peak. The west of the Tibetan Plateau and the northern region of the East Asian westerly jet near the tropopause are two transit points where extratropical high-IPV CISOs strengthen and then change their propagation direction. The southward high-IPV CISOs and the northward positive IPV CISO caused by the monsoon begin to interact about 10 days prior to rainfall peak. Since then, the interaction leads a narrow meridional positive PV channel on the inclined 345 K isentropic surface. A specific CISO pattern, characterized by an elongated high-IPV CISO isolated by three negative IPV CISOs (the South Asian, the Okhotsk and the western Pacific subtropical highs), is responsible for the long duration of the second rainfall PPCISO. [ABSTRACT FROM AUTHOR]

Recently, much attention has been devoted to better understand the internal modes of variability of the climate system. This is particularly important in mid-latitude regions like the North-Atlantic, which is characterized by a large natural variability and is intrinsically difficult to predict. A suitable framework for studying the modes of variability of the atmospheric circulation is to look for recurrent patterns, commonly referred to as Weather Regimes. Each regime is characterized by a specific large-scale atmospheric circulation pattern, thus influencing regional weather and extremes over Europe. The focus of the present paper is the study of the Euro-Atlantic wintertime Weather Regimes in the climate models participating to the PRIMAVERA project. We analyse here the set of coupled historical simulations (hist-1950), which have been performed both at standard and increased resolution, following the HighresMIP protocol. The models' performance in reproducing the observed Weather Regimes is assessed in terms of different metrics, focussing on systematic biases and on the impact of resolution. We also analyse the connection of the Weather Regimes with the Jet Stream latitude and blocking frequency over the North-Atlantic sector. We find that—for most models—the regime patterns are better represented in the higher resolution version, for all regimes but the NAO-. On the other side, no clear impact of resolution is seen on the regime frequency of occurrence and persistence. Also, for most models, the regimes tend to be more tightly clustered in the increased resolution simulations, more closely resembling the observed ones. However, the horizontal resolution is not the only factor determining the model performance, and we find some evidence that biases in the SSTs and mean geopotential field might also play a role. [ABSTRACT FROM AUTHOR]

An effective way of investigating the effects of tropical cyclones (TCs) on different spatial/temporal-scale environmental fields is to contrast the original circulation with the circulation from which the TCs have been removed. Although dynamical balance is required for analyzing TC contributions, the dynamic balance of TC-removed fields obtained by the existing TC removal method (which is widely used in the TC bogus procedure) is often ignored. In this paper, a TC removal method incorporating the potential vorticity (PV) inversion technique is proposed and its application to climate study is demonstrated. This method objectively detects the TCs' positive PV disturbance, which is strong with a deep structure and overwhelmingly dominates the relatively weak and thin negative PV disturbance. The TC-removed field is well-balanced due to the dynamic balance consideration in the PV inversion framework. This approach isolates TC vortices, which are stronger and have a wider range of impacts compared with the TC components derived by the existing removal methods. The TC-removed fields obtained by the existing and the proposed methods are profoundly different, especially in dynamic balance. The TC contribution to intraseasonal variance and seasonal mean circulation in the tropical western North Pacific is examined. The existence of TCs enhances the amplitude and propagation of intraseasonal oscillation and strengthens the seasonal mean circulations such as the low-level monsoon trough and upper-level anticyclone in the region. Whereas the existing and the proposed TC removal techniques yield consistent results, the proposed technique yields larger TC contributions to the seasonal-mean circulation and the amplitude and northward propagation tendency of intraseasonal oscillation. [ABSTRACT FROM AUTHOR]

This paper presents new modeling evidence showing the added value of high-resolution information from South America (SA) in the simulation of the Southern Hemisphere (SH) extratropical circulation. LMDZ, a coarse-resolution atmospheric global general circulation model constitutes the main tool for this investigation. Parallel to the control simulation, a two-way nesting (TWN) simulation of LMDZ is performed with an interactive coupling to the same model, but with a higher-resolution zoom over SA. The third simulation is a perfect boundary simulation for which re-analysis information from ERA-Interim is used to nudge LMDZ, but only over SA. Results indicate that enhanced resolution over SA improves the representation of the most important processes that influence extratropical eddy activity. The local improvement is followed by a better representation of the global extratropical circulation, especially in austral summer. The regional climate enhancement over SA has positive effects on simulation of the midlatitude jet position during the austral summer by significantly reducing the bias of the mean zonal kinetic energy outside the nudged zone. On the other hand, the wintertime general circulation outside the nudged-zone shows a limited bias-reduction for the regional-driven simulations, especially in the case of the TWN system. However, improvements of the TWN system compared to the control experiment are noticed in early stages of cyclone lifecycle, as it is identified in a better simulation of transient meridional heat transport and transient kinetic energy intensity. The findings of the present study suggest, thus, that improvements in resolution over SA effectively excite the simulation of the mean atmospheric circulation in the SH. [ABSTRACT FROM AUTHOR]

Anticyclones are one of the main synoptic features of the global midlatitudes, where they are associated with dry, settled conditions. Previous studies have identified southern Australia as a region where significant long-term changes have occurred in recent decades, including a decline in cool season rainfall and an increase in the frequency of anticyclones. This paper uses several reanalyses to assess the climatology, variability, trends and impacts of anticyclones in southern Australia and several subregions. A robust increase in the frequency of anticyclones in southern Australia is demonstrated between 1960–1979 and 1997–2014, particularly in southeast Australia and the Tasman Sea during the cool months of the year. At least 30% of the recent cool season rainfall decline in southeast Australia can be associated with an increased frequency of anticyclones in this region. However, there are no clear trends in anticyclone frequency near southwestern Western Australia, where long-term rainfall declines are due to changes in other weather systems. [ABSTRACT FROM AUTHOR]

How climate change will unfold in the years to come is a central topic in today's environmental debate, in particular at the regional level. While projections using large ensembles of global climate models consistently indicate a future decrease in summer precipitation over southern Europe and an increase over northern Europe, individual models substantially modulate these distinct signals of change in precipitation. So far model improvements and higher resolution from regional downscaling have not been seen as able to resolve these disagreements. In this paper we assess whether 2 decades of investments in large ensembles of downscaling experiments with regional climate model simulations for Europe have contributed to a more robust model assessment of the future climate at a range of geographical scales. We study climate change projections of European seasonal temperature and precipitation using an ensemble-suite comprised by all readily available pan-European regional model projections for the twenty-first-century, representing increasing model resolution from ~ 50 to ~ 12 km grid distance, as well as lateral boundary and sea surface temperature conditions from a variety of global model simulations. Employing a simple scaling with global mean temperature change we identify emerging robust signals of future seasonal temperature and precipitation changes also found to resemble current observed trends, where these are judged to be statistically significant. [ABSTRACT FROM AUTHOR]

Objective methods for identifying and quantifying atmospheric blocking have been developed over recent decades, primarily targeting North Atlantic blocks. Differences arise from these methods, leading to changes in the resultant blocking climatology. To understand these differences, and better inform future assessments built on quantitative detection of blocks, this paper examines blocking properties produced by three different objective detection algorithms over the global extratropics. Blocking criteria examined include 500 hPa geopotential height anomaly ( Z ∗ ), column-averaged potential vorticity anomaly ( P V ∗ ), and 500 hPa geopotential height gradient (AGP). Results are analyzed for blocking climatologies and for instantaneous blocking patterns, as well as distributions of block size, speed, duration, and distance traveled. The results emphasize physical characteristics of the flow field and the subsequent blocking regions that emerge; overall, P V ∗ and Z ∗ blocked regions often have higher pattern correlation and spatial similarity, though these two methods also display high agreement with AGP in some instances. Z ∗ finds the largest (and greatest number of) blocked regions, while P V ∗ -detected regions are smallest in all instances except Southern Hemisphere winter. In some cases, P V ∗ tracks a nearby jet streak, leading to differences with height-based algorithms. All three algorithms detect some questionable low-latitude blocks that are stationary and persist but do not impair zonal flow, although at different times. Therefore, careful consideration of the algorithm biases is important in future blocking studies. For example, linking extreme weather to detected blocking could vary substantially depending on the algorithm used. [ABSTRACT FROM AUTHOR]

We take advantage of ISCCP simulator data available for many models that participated in CMIP5, in order to introduce a framework for comparing model cloud output with corresponding ISCCP observations based on the cloud regime (CR) concept. Simplified global CRs are employed derived from the co-variations of three variables, namely cloud optical thickness, cloud top pressure and cloud fraction ( τ, p , CF). Following evaluation criteria established in a companion paper of ours (Jin et al. 2016), we assess model cloud simulation performance based on how well the simplified CRs are simulated in terms of similarity of centroids, global values and map correlations of relative-frequency-of-occurrence, and long-term total cloud amounts. Mirroring prior results, modeled clouds tend to be too optically thick and not as extensive as in observations. CRs with high-altitude clouds from storm activity are not as well simulated here compared to the previous study, but other regimes containing near-overcast low clouds show improvement. Models that have performed well in the companion paper against CRs defined by joint τ- p histograms distinguish themselves again here, but improvements for previously underperforming models are also seen. Averaging across models does not yield a drastically better picture, except for cloud geographical locations. Cloud evaluation with simplified regimes seems thus more forgiving than that using histogram-based CRs while still strict enough to reveal model weaknesses. [ABSTRACT FROM AUTHOR]

On the basis of climate zones classified by the number of days of the daily average temperature ≥ 10 °C (DT10) over China, the performance of the 9 CMIP5 climate models is evaluated in this paper. The results indicate that the CMCC-CMS and MPI-ESM-MR show higher skill than the other 7 models in simulating spatial pattern and its decadal change of climate zones over China. The simulation results for FGOALS-g2 and INM-CM4 both show relatively lower skill than the other 7 models. Meanwhile, the performance of multi-model ensemble in simulating climate zones over China is obviously better than the simulated result of any single model. So, it is a good way to simulate climate zones by multi-model ensemble to reduce some uncertainty of climate models. However, it is crucial to select appropriate ensemble members. Compared with 1960-2005, the climatic zones in China have an obvious trend of northward shift in 2021-2100. The range of southern sub-tropical belt expands to the most areas in the south of Yangtze River under RCP4.5 emission scenarios, and further extends to the north areas of Yangtze River with a maximum of 2-6° of latitude under RCP8.5 emission scenarios. Middle sub-tropical belt shifts gradually to the areas between Yellow River and north areas of the middle and lower reaches of the Yangtze River. Northern sub-tropical belt shifts northward to southeastern North China. Warm extra-tropical belt extends to the most of Northeast China, most of central Inner Mongolia, and northern Xinjiang under RCP8.5 emission scenarios. [ABSTRACT FROM AUTHOR]

Current climate models commonly overestimate precipitation over the Tibetan Plateau (TP), which limits our understanding of past and future water balance in the region. Identifying sources of such models’ wet bias is therefore crucial. The Himalayas is considered a major pathway of water vapor transport (WVT) towards the TP. Their steep terrain, together with associated small-scale processes, cannot be resolved by coarse-resolution models, which may result in excessive WVT towards the TP. This paper, therefore, investigated the resolution dependency of simulated WVT through the central Himalayas and its further impact on precipitation bias over the TP. According to a summer monsoon season of simulations conducted using the weather research forecasting (WRF) model with resolutions of 30, 10, and 2 km, the study found that finer resolutions (especially 2 km) diminish the positive precipitation bias over the TP. The higher-resolution simulations produce more precipitation over the southern Himalayan slopes and weaker WVT towards the TP, explaining the reduced wet bias. The decreased WVT is reflected mostly in the weakened wind speed, which is due to the fact that the high resolution can improve resolving orographic drag over a complex terrain and other processes associated with heterogeneous surface forcing. A significant difference was particularly found when the model resolution is changed from 30 to 10 km, suggesting that a resolution of approximately 10 km represents a good compromise between a more spatially detailed simulation of WVT and computational cost for a domain covering the whole TP. [ABSTRACT FROM AUTHOR]

El Niño Modoki events can be further classified into El Niño Modoki I and II in terms of their opposite impacts on southern China rainfall (Wang and Wang, J Clim 26:1322-1338, 2013) and the Indian Ocean dipole mode (Wang and Wang, Clim Dyn 42:991-1005, 2014). The present paper develops an index to identify the types of El Niño events. The El Niño Modoki II (MII) index is defined as the leading principle component of multivariate empirical orthogonal function analysis of the normalized El Niño Modoki index, Niño4 index and 850 hPa relative vorticity anomalies averaged near the Philippine Sea during autumn. The MII index exhibits dominant variations on interannual (2-3 and 4-5 years) and decadal (10-20 years) timescales. El Niño Modoki II events can be well identified by using the MII index value being larger than 1 standard deviation. Further analyses and numerical model experiments confirm that the MII index can portray the major oceanic and atmospheric features of El Niño Modoki II events. The constructed MII index along with previous ENSO indices can be used for classifying and identifying all types of El Niño events. Because of distinct impacts induced by different types of El Niño events, the implication of the present study is that climate prediction and future climate projection under global warming can be improved by using the MII index and other indices to identify the types of El Niño events. [ABSTRACT FROM AUTHOR]

The three-pattern decomposition of global atmospheric circulation (TPDGAC) partitions three-dimensional (3D) atmospheric circulation into horizontal, meridional and zonal components to study the 3D structures of global atmospheric circulation. This paper incorporates the three-pattern decomposition model (TPDM) into primitive equations of atmospheric dynamics and establishes a new set of dynamical equations of the horizontal, meridional and zonal circulations in which the operator properties are studied and energy conservation laws are preserved, as in the primitive equations. The physical significance of the newly established equations is demonstrated. Our findings reveal that the new equations are essentially the 3D vorticity equations of atmosphere and that the time evolution rules of the horizontal, meridional and zonal circulations can be described from the perspective of 3D vorticity evolution. The new set of dynamical equations includes decomposed expressions that can be used to explore the source terms of large-scale atmospheric circulation variations. A simplified model is presented to demonstrate the potential applications of the new equations for studying the dynamics of the Rossby, Hadley and Walker circulations. The model shows that the horizontal air temperature anomaly gradient (ATAG) induces changes in meridional and zonal circulations and promotes the baroclinic evolution of the horizontal circulation. The simplified model also indicates that the absolute vorticity of the horizontal circulation is not conserved, and its changes can be described by changes in the vertical vorticities of the meridional and zonal circulations. Moreover, the thermodynamic equation shows that the induced meridional and zonal circulations and advection transport by the horizontal circulation in turn cause a redistribution of the air temperature. The simplified model reveals the fundamental rules between the evolution of the air temperature and the horizontal, meridional and zonal components of global atmospheric circulation. [ABSTRACT FROM AUTHOR]

The ability of an ensemble of five regional climate models (hereafter RCMs) under Coordinated Regional Climate Downscaling Experiments-South Asia (hereafter, CORDEX-SA) in simulating the key features of present day near surface mean air temperature (Tmean) climatology (1970-2005) over the Himalayan region is studied. The purpose of this paper is to understand the consistency in the performance of models across the ensemble, space and seasons. For this a number of statistical measures like trend, correlation, variance, probability distribution function etc. are applied to evaluate the performance of models against observation and simultaneously the underlying uncertainties between them for four different seasons. The most evident finding from the study is the presence of a large cold bias (−6 to −8 °C) which is systematically seen across all the models and across space and time over the Himalayan region. However, these RCMs with its fine resolution perform extremely well in capturing the spatial distribution of the temperature features as indicated by a consistently high spatial correlation (greater than 0.9) with the observation in all seasons. In spite of underestimation in simulated temperature and general intensification of cold bias with increasing elevation the models show a greater rate of warming than the observation throughout entire altitudinal stretch of study region. During winter, the simulated rate of warming gets even higher at high altitudes. Moreover, a seasonal response of model performance and its spatial variability to elevation is found. [ABSTRACT FROM AUTHOR]

Climate change impact studies for the Northwest European Shelf (NWES) make use of various dynamical downscaling strategies in the experimental setup of regional ocean circulation models. Projected change signals from coupled and uncoupled downscalings with different domain sizes and forcing global and regional models show substantial uncertainty. In this paper, we investigate influences of the downscaling strategy on projected changes in the physical and biogeochemical conditions of the NWES. Our results indicate that uncertainties due to different downscaling strategies are similar to uncertainties due to the choice of the parent global model and the downscaling regional model. Downscaled change signals reveal to depend stronger on the downscaling strategy than on the model skills in simulating present-day conditions. Uncoupled downscalings of sea surface temperature (SST) changes are found to be tightly constrained by the atmospheric forcing. The incorporation of coupled air-sea interaction, by contrast, allows the regional model system to develop independently. Changes in salinity show a higher sensitivity to open lateral boundary conditions and river runoff than to coupled or uncoupled atmospheric forcings. Dependencies on the downscaling strategy for changes in SST, salinity, stratification and circulation collectively affect changes in nutrient import and biological primary production. [ABSTRACT FROM AUTHOR]

This study forms part II of two papers describing ECHAM6-FESOM, a newly established global climate model with a unique multi-resolution sea ice-ocean component. While part I deals with the model description and the mean climate state, here we examine the internal climate variability of the model under constant present-day (1990) conditions. We (1) assess the internal variations in the model in terms of objective variability performance indices, (2) analyze variations in global mean surface temperature and put them in context to variations in the observed record, with particular emphasis on the recent warming slowdown, (3) analyze and validate the most common atmospheric and oceanic variability patterns, (4) diagnose the potential predictability of various climate indices, and (5) put the multi-resolution approach to the test by comparing two setups that differ only in oceanic resolution in the equatorial belt, where one ocean mesh keeps the coarse ~1° resolution applied in the adjacent open-ocean regions and the other mesh is gradually refined to ~0.25°. Objective variability performance indices show that, in the considered setups, ECHAM6-FESOM performs overall favourably compared to five well-established climate models. Internal variations of the global mean surface temperature in the model are consistent with observed fluctuations and suggest that the recent warming slowdown can be explained as a once-in-one-hundred-years event caused by internal climate variability; periods of strong cooling in the model (‘hiatus’ analogs) are mainly associated with ENSO-related variability and to a lesser degree also to PDO shifts, with the AMO playing a minor role. Common atmospheric and oceanic variability patterns are simulated largely consistent with their real counterparts. Typical deficits also found in other models at similar resolutions remain, in particular too weak non-seasonal variability of SSTs over large parts of the ocean and episodic periods of almost absent deep-water formation in the Labrador Sea, resulting in overestimated North Atlantic SST variability. Concerning the influence of locally (isotropically) increased resolution, the ENSO pattern and index statistics improve significantly with higher resolution around the equator, illustrating the potential of the novel unstructured-mesh method for global climate modeling. [ABSTRACT FROM AUTHOR]

Previous studies in the literature show that the annual cycle of surface air temperature (SAT) is changing in both amplitude and phase, and the SAT departures from the annual cycle are long-term correlated. However, the classical definition of temperature anomalies is based on the assumption that the annual cycle is constant, which contradicts the fact of changing annual cycle. How to quantify the impact of the changing annual cycle on the long-term correlation of temperature anomaly variability still remains open. In this paper, a recently developed data adaptive analysis tool, the nonlinear mode decomposition (NMD), is used to extract and remove time-varying annual cycle to reach the new defined temperature anomalies in which time-dependent amplitude of annual cycle has been considered. By means of detrended fluctuation analysis, the impact induced by inter-annual variability from the time-dependent amplitude of annual cycle has been quantified on the estimation of long-term correlation of long historical temperature anomalies in Europe. The results show that the classical climatology annual cycle is supposed to lack inter-annual fluctuation which will lead to a maximum artificial deviation centering around 600 days. This maximum artificial deviation is crucial to defining the scaling range and estimating the long-term persistence exponent accurately. Selecting different scaling range could lead to an overestimation or underestimation of the long-term persistence exponent. By using NMD method to extract the inter-annual fluctuations of annual cycle, this artificial crossover can be weakened to extend a wider scaling range with fewer uncertainties. [ABSTRACT FROM AUTHOR]

In this paper we present the fifth generation of the INMCM climate model that is being developed at the Institute of Numerical Mathematics of the Russian Academy of Sciences (INMCM5). The most important changes with respect to the previous version (INMCM4) were made in the atmospheric component of the model. Its vertical resolution was increased to resolve the upper stratosphere and the lower mesosphere. A more sophisticated parameterization of condensation and cloudiness formation was introduced as well. An aerosol module was incorporated into the model. The upgraded oceanic component has a modified dynamical core optimized for better implementation on parallel computers and has two times higher resolution in both horizontal directions. Analysis of the present-day climatology of the INMCM5 (based on the data of historical run for 1979-2005) shows moderate improvements in reproduction of basic circulation characteristics with respect to the previous version. Biases in the near-surface temperature and precipitation are slightly reduced compared with INMCM4 as well as biases in oceanic temperature, salinity and sea surface height. The most notable improvement over INMCM4 is the capability of the new model to reproduce the equatorial stratospheric quasi-biannual oscillation and statistics of sudden stratospheric warmings. [ABSTRACT FROM AUTHOR]

Decadal predictions have a high profile in the climate science community and beyond, yet very little is known about their skill. Nor is there any agreed protocol for estimating their skill. This paper proposes a sound and coordinated framework for verification of decadal hindcast experiments. The framework is illustrated for decadal hindcasts tailored to meet the requirements and specifications of CMIP5 (Coupled Model Intercomparison Project phase 5). The chosen metrics address key questions about the information content in initialized decadal hindcasts. These questions are: (1) Do the initial conditions in the hindcasts lead to more accurate predictions of the climate, compared to un-initialized climate change projections? and (2) Is the prediction model's ensemble spread an appropriate representation of forecast uncertainty on average? The first question is addressed through deterministic metrics that compare the initialized and uninitialized hindcasts. The second question is addressed through a probabilistic metric applied to the initialized hindcasts and comparing different ways to ascribe forecast uncertainty. Verification is advocated at smoothed regional scales that can illuminate broad areas of predictability, as well as at the grid scale, since many users of the decadal prediction experiments who feed the climate data into applications or decision models will use the data at grid scale, or downscale it to even higher resolution. An overall statement on skill of CMIP5 decadal hindcasts is not the aim of this paper. The results presented are only illustrative of the framework, which would enable such studies. However, broad conclusions that are beginning to emerge from the CMIP5 results include (1) Most predictability at the interannual-to-decadal scale, relative to climatological averages, comes from external forcing, particularly for temperature; (2) though moderate, additional skill is added by the initial conditions over what is imparted by external forcing alone; however, the impact of initialization may result in overall worse predictions in some regions than provided by uninitialized climate change projections; (3) limited hindcast records and the dearth of climate-quality observational data impede our ability to quantify expected skill as well as model biases; and (4) as is common to seasonal-to-interannual model predictions, the spread of the ensemble members is not necessarily a good representation of forecast uncertainty. The authors recommend that this framework be adopted to serve as a starting point to compare prediction quality across prediction systems. The framework can provide a baseline against which future improvements can be quantified. The framework also provides guidance on the use of these model predictions, which differ in fundamental ways from the climate change projections that much of the community has become familiar with, including adjustment of mean and conditional biases, and consideration of how to best approach forecast uncertainty. [ABSTRACT FROM AUTHOR]

The interannual variation of Indian Ocean subtropical mode water (IOSTMW) subduction rate in the Southwest Indian Ocean from 1980 to 2007 is investigated in this paper based on Simple Ocean Data Assimilation (SODA) outputs. Climatology of subduction rate exceeds 75 m/year in the IOSTMW formation area. The renewal time of permanent pycnocline water mass based on the subduction rate is calculated for each density class: 3-6 years for IOSTMW (25.8 < σ < 26.2 kg m). Subduction rate in the Southwest Indian Ocean subtropical gyre exhibits a great year-to-year variability. This interannual variations of the IOSTMW subduction rate is primarily dominated by the lateral induction term, associated with the interannual variations of strong meridional gradient of winter mixed layer depth (MLD). The slope of the mixed layer depth in the mode water is closely linked to the large variations of deep late winter MLD in the mid-latitudes and negligible variations of shallow winter MLD in lower latitudes. It is further identified that the interannual variation of late winter MLD in this area is largely controlled by the latent and sensible heat flux components. The water volume of the permanent pycnocline in the IOSTMW distribution area is also found to show a significant interannual variability, and it is well correlated with the interannual variation of subduction rate. [ABSTRACT FROM AUTHOR]

Climate change projections are commonly based on multi-model ensembles of climate simulations. In this paper we consider the choice of bias models in Bayesian multimodel predictions. Buser et al. (Clim Res 44(2-3):227-241, 2010a) introduced a hybrid bias model which combines commonly used constant bias and constant relation bias assumptions. The hybrid model includes a weighting parameter which balances these bias models. In this study, we use a cross-validation approach to study which bias model or bias parameter leads to, in a specific sense, optimal climate change projections. The analysis is carried out for summer and winter season means of 2 m-temperatures spatially averaged over the IPCC SREX regions, using 19 model runs from the CMIP5 data set. The cross-validation approach is applied to calculate optimal bias parameters (in the specific sense) for projecting the temperature change from the control period (1961-2005) to the scenario period (2046-2090). The results are compared to the results of the Buser et al. (Clim Res 44(2-3):227-241, 2010a) method which includes the bias parameter as one of the unknown parameters to be estimated from the data. [ABSTRACT FROM AUTHOR]

This paper investigates the potential impact of 'idealized-but-realistic' land cover degradation on the late twentieth century Sahel drought using a regional climate model (RCM) driven with lateral boundary conditions (LBCs) from three different sources, including one re-analysis data and two global climate models (GCMs). The impact of land cover degradation is quantified based on a large number of control-and-experiment pairs of simulations, where the experiment features a degraded land cover relative to the control. Two different approaches of experimental design are tested: in the 1st approach, the RCM land cover degradation experiment shares the same LBCs as the corresponding RCM control, which can be derived from either reanalysis data or a GCM; with the 2nd approach, the LBCs for the RCM control are derived from a GCM control, and the LBCs for the RCM land cover degradation experiment are derived from a corresponding GCM land cover degradation experiment. When the 1st approach is used, results from the RCM driven with the three different sources of LBCs are generally consistent with each other, indicating robustness of the model response against LBCs; when the 2nd approach is used, the RCM results show strong sensitivity to the source of LBCs and the response in the RCM is dominated by the response of the driving GCMs. The spatiotemporal pattern of the precipitation response to land cover degradation as simulated by RCM using the 1st approach closely resembles that of the observed historical changes, while results from the GCMs and the RCM using the 2nd approach bear less similarity to observations. Compared with the 1st approach, the 2nd approach has the advantage of capturing the impact on large scale circulation, but has the disadvantage of being influenced by the GCMs' internal variability and any potential erroneous response of the driving GCMs to land degradation. The 2nd approach therefore requires a large ensemble to reduce the uncertainties derived from the driving GCMs. All RCM experiments based on the 1st approach produce a predominantly dry signal in West Africa throughout the year, with a dipole pattern found in the peak monsoon season that features a slight increase of precipitation over the Guinea Coast and strong decrease in the north; a similar spatiotemporal distribution is found for temperature changes, with warming (cooling) coinciding with precipitation decrease (increase). The model precipitation changes in West Africa are dominated by evapotranspiration changes in the north and by atmospheric moisture convergence changes in the south; in temperature changes, surface warming due to the decrease of evaporative cooling dominates over the albedo-induced radiative cooling. [ABSTRACT FROM AUTHOR]

The second West African Monsoon Modeling and Evaluation Project Experiment (WAMME II) is designed to improve understanding of the possible roles and feedbacks of sea surface temperature (SST), land use land cover change (LULCC), and aerosols forcings in the Sahel climate system at seasonal to decadal scales. The project's strategy is to apply prescribed observationally based anomaly forcing, i.e., 'idealized but realistic' forcing, in simulations by climate models. The goal is to assess these forcings' effects in producing/amplifying seasonal and decadal climate variability in the Sahel between the 1950s and the 1980s, which is selected to characterize the great drought period of the last century. This is the first multi-model experiment specifically designed to simultaneously evaluate such relative contributions. The WAMME II models have consistently demonstrated that SST forcing is a major contributor to the twentieth century Sahel drought. Under the influence of the maximum possible SST forcing, the ensemble mean of WAMME II models can produce up to 60 % of the precipitation difference during the period. The present paper also addresses the role of SSTs in triggering and maintaining the Sahel drought. In this regard, the consensus of WAMME II models is that both Indian and Pacific Ocean SSTs greatly contributed to the drought, with the former producing an anomalous displacement of the Intertropical Convergence Zone before the WAM onset, and the latter mainly contributes to the summer WAM drought. The WAMME II models also show that the impact of LULCC forcing on the Sahel climate system is weaker than that of SST forcing, but still of first order magnitude. According to the results, under LULCC forcing the ensemble mean of WAMME II models can produces about 40 % of the precipitation difference between the 1980s and the 1950s. The role of land surface processes in responding to and amplifying the drought is also identified. The results suggest that catastrophic consequences are likely to occur in the regional Sahel climate when SST anomalies in individual ocean basins and in land conditions combine synergistically to favor drought. [ABSTRACT FROM AUTHOR]

In order to construct climate quality long-term dust storm dataset, merged dust storm climatology in Phoenix is developed based on three data sources: regular meteorological records, in situ air quality measurements, and satellite remote sensing observations. The result presented in this paper takes into account the advantages of each dataset and integrates individual analyses demonstrated and presented in previous studies that laid foundation to reconstruct a consistent and continuous time series of dust frequency. A key for the merging procedure is to determine analysis criteria suitable for each individual data source. A practical application to historic records of dust storm activities over the Phoenix area is presented to illustrate detailed steps, advantages, and limitations of the newly developed process. Three datasets are meteorological records from the Sky Harbor station, satellite observed aerosol optical depth data from moderate resolution imaging spectroradiometer, and the U.S. Environmental Protection Agency Air Quality System particulate matter data of eight sites surrounding Phoenix. Our purpose is to construct dust climatology over the Phoenix region for the period 1948-2012. Data qualities of the reconstructed dust climatology are assessed based on the availability and quality of the input data. The period during 2000-2012 has the best quality since all datasets are well archived. The reconstructed climatology shows that dust storm activities over the Phoenix region have large interannual variability. However, seasonal variations show a skewed distribution with higher frequency of dust storm activities in July and August and relatively quiet during the rest of months. Combining advantages of all the available datasets, this study presents a merged product that provides a consistent and continuous time series of dust storm activities suitable for climate studies. [ABSTRACT FROM AUTHOR]

The West African monsoon intraseasonal variability has huge socio-economic impacts on local populations but understanding and predicting it still remains a challenge for the weather prediction and climate scientific community. This paper analyses an ensemble of simulations from six regional climate models (RCMs) taking part in the coordinated regional downscaling experiment, the ECMWF ERA-Interim reanalysis (ERAI) and three satellite-based and observationally-constrained daily precipitation datasets, to assess the performance of the RCMs with regard to the intraseasonal variability. A joint analysis of seasonal-mean precipitation and the total column water vapor (also called precipitable water- PW) suggests the existence of important links at different timescales between these two variables over the Sahel and highlights the relevance of using PW to follow the monsoon seasonal cycle. RCMs that fail to represent the seasonal-mean position and amplitude of the meridional gradient of PW show the largest discrepancies with respect to seasonal-mean observed precipitation. For both ERAI and RCMs, spectral decompositions of daily PW as well as rainfall show an overestimation of low-frequency activity (at timescales longer than 10 days) at the expense of the synoptic (timescales shorter than 10 days) activity. Consequently, the effects of the African Easterly Waves and the associated mesoscale convective systems are substantially underestimated, especially over continental regions. Finally, the study investigates the skill of the models with respect to hydro-climatic indices related to the occurrence, intensity and frequency of precipitation events at the intraseasonal scale. Although most of these indices are generally better reproduced with RCMs than reanalysis products, this study indicates that RCMs still need to be improved (especially with respect to their subgrid-scale parameterization schemes) to be able to reproduce the intraseasonal variance spectrum adequately. [ABSTRACT FROM AUTHOR]

Convection-permitting climate model are promising tools for improved representation of extremes, but the number of regions for which these models have been evaluated are still rather limited to make robust conclusions. In addition, an integrated interpretation of near-surface characteristics (typically temperature and precipitation) together with cloud properties is limited. The objective of this paper is to comprehensively evaluate the performance of a 'state-of-the-art' regional convection-permitting climate model for a mid-latitude coastal region with little orographic forcing. For this purpose, an 11-year integration with the COSMO-CLM model at Convection-Permitting Scale (CPS) using a grid spacing of 2.8 km was compared with in-situ and satellite-based observations of precipitation, temperature, cloud properties and radiation (both at the surface and the top of the atmosphere). CPS clearly improves the representation of precipitation, in especially the diurnal cycle, intensity and spatial distribution of hourly precipitation. Improvements in the representation of temperature are less obvious. In fact the CPS integration overestimates both low and high temperature extremes. The underlying cause for the overestimation of high temperature extremes was attributed to deficiencies in the cloud properties: The modelled cloud fraction is only 46 % whereas a cloud fraction of 65 % was observed. Surprisingly, the effect of this deficiency was less pronounced at the radiation balance at the top of the atmosphere due to a compensating error, in particular an overestimation of the reflectivity of clouds when they are present. Overall, a better representation of convective precipitation and a very good representation of the daily cycle in different cloud types were demonstrated. However, to overcome remaining deficiencies, additional efforts are necessary to improve cloud characteristics in CPS. This will be a challenging task due to compensating deficiencies that currently exist in 'state-of-the-art' models, yielding a good representation of average climate conditions. In the light of using the CPS models to study climate change it is necessary that these deficiencies are addressed in future research. [ABSTRACT FROM AUTHOR]

This paper provides a first overview of the performance of global climate models participating in the Coupled Model Inter-Comparison Project phase 5 (CMIP5) in simulating the upper troposphere and lower stratosphere (UTLS) temperatures. Temperature from CMIP5 models is evaluated with high resolution global positioning system radio occultation (GPSRO) constellation observing system for meteorology, ionosphere, and climate (COSMIC) data during the period of July 2006-December 2013. Future projections of 17 CMIP5 models based on the representative concentration pathway (RCP) 8.5 scenarios are utilized to assess model performance and to identify the biases in the temperature in the UTLS region at eight different pressure levels. The evaluations were carried out vertically, regionally, and globally to understand the temperature uncertainties in CMIP5 models. It is found that the CMIP5 models successfully reproduce the general features of temperature structure in terms of vertical, annual, and inter-annual variation. The ensemble mean of CMIP5 models compares well with the COSMIC GPSRO data with a mean difference of ±1 K. In the tropical region, temperature biases vary from one model to another. The spatial difference between COSMIC and ensemble mean reveals that at 100 hPa, the models show a bias of about ±2 K. With increase in altitude the bias decreases and turns into a cold bias over the tropical and Antarctic regions. The future projections of the CMIP5 models were presented during 2006-2099 under the RCP 8.5 scenarios. Projections show a warming trend at 300, 200, and 100 hPa levels over a wide region of 60°N-45°S. The warming decreases rapidly and becomes cooling with increase in altitudes by the end of twenty-first century. Significant cooling is observed at 30, 20, and 10 hPa levels. At 300/10 hPa, the temperature trend increases/decreases by ~0.82/0.88 K/decade at the end of twenty-first century under RCP 8.5 scenarios. [ABSTRACT FROM AUTHOR]

Glacier valleys across the Transantarctic Mountains are not properly taken into account in climate models, because of their coarse resolution. Nonetheless, glacier valleys control katabatic winds in this region, and the latter are thought to affect the climate of the Ross Sea sector, frsater formation to snow mass balance. The purpose of this paper is to investigate the role of the production of turbulent kinetic energy by the subgrid-scale orography in the Transantarctic Mountains using a 20-km atmospheric regional model. A classical orographic roughness length parametrization is modified to produce either smooth or rough valleys. A one-year simulation shows that katabatic winds in the Transantarctic Mountains are strongly improved using smooth valleys rather than rough valleys. Pressure and temperature fields are affected by the representation of the orographic roughness, specifically in the Transantarctic Mountains and over the Ross Ice Shelf. A smooth representation of escarpment regions shows better agreement with automatic weather station observations than a rough representation. This work stresses the need to improve the representation of subgrid-scale orography to simulate realistic katabatic flows. This paper also provides a way of improving surface winds in an atmospheric model without increasing its resolution. [ABSTRACT FROM AUTHOR]

This paper presents a comparison of principal component (PC) regression and regularized expectation maximization (RegEM) to reconstruct European summer and winter surface air temperature over the past millennium. Reconstruction is performed within a surrogate climate using the National Center for Atmospheric Research (NCAR) Climate System Model (CSM) 1.4 and the climate model ECHO-G 4, assuming different white and red noise scenarios to define the distortion of pseudoproxy series. We show how sensitivity tests lead to valuable “a priori” information that provides a basis for improving real world proxy reconstructions. Our results emphasize the need to carefully test and evaluate reconstruction techniques with respect to the temporal resolution and the spatial scale they are applied to. Furthermore, we demonstrate that uncertainties inherent to the predictand and predictor data have to be more rigorously taken into account. The comparison of the two statistical techniques, in the specific experimental setting presented here, indicates that more skilful results are achieved with RegEM as low frequency variability is better preserved. We further detect seasonal differences in reconstruction skill for the continental scale, as e.g. the target temperature average is more adequately reconstructed for summer than for winter. For the specific predictor network given in this paper, both techniques underestimate the target temperature variations to an increasing extent as more noise is added to the signal, albeit RegEM less than with PC regression. We conclude that climate field reconstruction techniques can be improved and need to be further optimized in future applications. [ABSTRACT FROM AUTHOR]

This paper analyzes the role of the Indian Ocean (IO) and the atmosphere biases in generating and sustaining large-scale precipitation biases over Central India (CI) during the Indian summer monsoon (ISM) in the climate forecast system version 2 (CFSv2) hindcasts that are produced by initializing the system each month from January 1982 to March 2011. The CFSv2 hindcasts are characterized by a systematic dry monsoon bias over CI that deteriorate with forecast lead-times and coexist with a wet bias in the tropical IO suggesting a large-scale interplay between coupled ocean-atmosphere and land biases. The biases evolving from spring-initialized forecasts are analyzed in detail to understand the evolution of summer biases. The northward migration of the Inter Tropical Convergence Zone (ITCZ) that typically crosses the equator in the IO sector during April in nature is delayed in the hindcasts when the forecast system is initialized in early spring. Our analyses show that the delay in the ITCZ coexists with wind and SST biases and the associated processes project onto the seasonal evolution of the coupled ocean-atmosphere features. This delay in conjunction with the SST and the wind biases during late spring and early summer contributes to excessive precipitation over the ocean and leading to a deficit in rainfall over CI throughout the summer. Attribution of bias to a specific component in a coupled forecast system is particularly challenging as seemingly independent biases from one component affect the other components or are affected by their feedbacks. In the spring-initialized forecasts, the buildup of deeper thermocline in association with warmer SSTs due to the enhanced Ekman pumping in the southwest IO inhibits the otherwise typical northward propagation of ITCZ in the month of April. Beyond this deficiency in the forecasts, two key ocean-atmosphere coupled mechanisms are identified; one in the Arabian Sea, where a positive windstress curl bias in conjunction with warmer SSTs lead to a weakening of Findlater jet and the other in the east equatorial IO where a remote forcing by the predominantly westerly bias in the western-central equatorial IO in the summer strengthen the seasonal downwelling Kelvin wave that in turn deepens the thermocline in the eastern IO. The equatorial Kelvin wave continues as a coastal Kelvin wave and disperses as Rossby waves off Sumatra and induces positive SST and precipitation biases in the eastern and southern Bay of Bengal. This study shows that the biases that first appear in winds lead to a cascade of coupled processes that exacerbate the subsequent biases by modulating the evolution of seasonal processes such as the annual Kelvin and Rossby waves and the cross-equatorial vertically integrated moisture transport. While this analysis does not offer any particular insights into improving the ISM forecasts, it is a foundational first step towards this goal. [ABSTRACT FROM AUTHOR]

This paper investigates the Atlantic Ocean influence on equatorial Pacific decadal variability. Using an ensemble of simulations, where the ICTPAGCM ('SPEEDY') is coupled to the NEMO/OPA ocean model in the Indo-Pacific region and forced by observed sea surface temperatures in the Atlantic region, it is shown that the Atlantic Multidecadal Oscillation (AMO) has had a substantial influence on the equatorial Pacific decadal variability. According to AMO phases we have identified three periods with strong Atlantic forcing of equatorial Pacific changes, namely (1) 1931-1950 minus 1910-1929, (2) 1970-1989 minus 1931-1950 and (3) 1994-2013 minus 1970-1989. Both observations and the model show easterly surface wind anomalies in the central Pacific, cooling in the central-eastern Pacific and warming in the western Pacific/Indian Ocean region in events (1) and (3) and the opposite signals in event (2). The physical mechanism for these responses is related to a modification of the Walker circulation because a positive (negative) AMO leads to an overall warmer (cooler) tropical Atlantic. The warmer (cooler) tropical Atlantic modifies the Walker circulation, leading to rising (sinking) and upper-level divergence (convergence) motion in the Atlantic region and sinking (rising) motion and upper-level convergence (divergence) in the central Pacific region. [ABSTRACT FROM AUTHOR]

Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)-two contrasting SD methods-in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector. [ABSTRACT FROM AUTHOR]

Mineral dusts present in the atmosphere can play an important role in climate over West Africa and surrounding regions. However, current understanding regarding how dust aerosols influence climate of West Africa is very limited. In this study, a regional climate model is used to investigate the potential climatic impacts of dust aerosols. Two sets of simulations driven by reanalysis and Earth System Model boundary conditions are performed with and without the representation of dust processes. The model, regardless of the boundary forcing, captures the spatial and temporal variability of the aerosol optical depth and surface concentration. The shortwave radiative forcing of dust is negative at the surface and positive in the atmosphere, with greater changes in the spring and summer. The presence of mineral dusts causes surface cooling and lower troposphere heating, resulting in a stabilization effect and reduction in precipitation in the northern portion of the monsoon close to the dust emissions region. This results in an enhancement of precipitation to the south. While dusts cause the lower troposphere to stabilize, upper tropospheric cooling makes the region more prone to intense deep convection as is evident by a simulated increase in extreme precipitation. In a companion paper, the impacts of dust emissions on future West African climate are investigated. [ABSTRACT FROM AUTHOR]

Researchers have proposed that a significant portion of the post-glacial rise in atmospheric CO could be due to the respiration of permafrost carbon stocks that formed over the course of glaciation. In this paper, we used the University of Victoria Earth System Climate Model v. 2.9 to simulate the deglacial and interglacial carbon cycle from the last glacial maximum to the present. The model's sensitivity to mid and high latitude terrestrial carbon storage is evaluated by including a 600 Pg C carbon pool parameterized to respire in concert with decreases in ice sheet surface area. The respiration of this stored carbon during the early stages of deglaciation had a large effect on the carbon cycle in these simulations, allowing atmospheric CO to increase by 40 ppmv in the model, with an additional 20 ppmv increase occurring in the case of a more realistic, prescribed CO radiative warming. These increases occurred prior to large-scale carbon uptake due to the reestablishment of boreal forests and peatlands in the proxy record (beginning in the early Holocene). Surprisingly, the large external carbon input to the atmosphere and oceans did not increase sediment dissolution and mean ocean alkalinity relative to a control simulation without the high latitude carbon reservoir. In addition, our simulations suggest that an early deglacial terrestrial carbon release may come closer to explaining some observed deglacial changes in deep-ocean carbonate concentrations than simulations without such a release. We conclude that the respiration of glacial soil carbon stores may have been an important contributor to the deglacial CO rise, particularly in the early stages of deglaciation. [ABSTRACT FROM AUTHOR]

The eastern United States is vulnerable to flooding from tropical cyclone rainfall. Understanding how both the frequency and intensity of this rainfall will change in the future climate is a major challenge. One promising approach is the dynamical downscaling of relatively coarse general circulation model results using higher-resolution regional climate models (RCMs). In this paper, we examine the frequency of landfalling tropical cyclones and associated rainfall properties over the eastern United States using Zetac, an 18-km resolution RCM designed for modeling Atlantic tropical cyclone activity. Simulations of 1980-2006 tropical cyclone frequency and rainfall intensity for the months of August-October are compared against results from previous studies and observation-based datasets. The 1980-2006 control simulations are then compared against results from three future climate scenarios: CMIP3/A1B (late twenty-first century) and CMIP5/RCP4.5 (early and late twenty-first century). In CMIP5 early and late twenty-first century projections, the frequency of occurrence of post-landfall tropical cyclones shows little net change over much of the eastern U.S. despite a decrease in frequency over the ocean. This reflects a greater landfalling fraction in CMIP5 projections, which is not seen in CMIP3-based projections. Average tropical cyclone rain rates over land within 500 km of the storm center increase by 8-17 % in the future climate projections relative to control. This is at least as much as expected from the Clausius-Clapeyron relation, which links a warmer atmosphere to greater atmospheric water vapor content. Over land, the percent enhancement of area-averaged rain rates from a given tropical cyclone in the warmer climate is greater for larger averaging radius (300-500 km) than near the storm, particularly for the CMIP3 projections. Although this study does not focus on attribution, the findings are broadly consistent with historical tropical cyclone rainfall changes documented in a recent observational study. The results may have important implications for future flood risks from tropical cyclones. [ABSTRACT FROM AUTHOR]

The North Atlantic Oscillation (NAO) exerts a major influence on the climate of the North Atlantic region. However, other atmospheric circulation modes (ACMs), such as the East Atlantic (EA) and Scandinavian (SCAND) patterns, also play significant roles. The dynamics of lakes on the Iberian Peninsula are greatly controlled by climatic parameters, but their relationship with these various ACMs has not been investigated in detail. In this paper, we analyze monthly meteorological and limnological long-term datasets (1950-2011 and 1992-2011, respectively) from two lakes on the northern and central Iberian Peninsula (Sanabria and Las Madres) to develop an understanding of the seasonal sensitivity of these freshwater systems to the NAO, EA and SCAND circulation modes. The limnological variability within Lake Sanabria is primarily controlled by fluctuations in the seasonal precipitation and wind, and the primary ACMs associated with the winter limnological processes are the NAO and the SCAND modes, whereas only the EA mode appears to weakly influence processes during the summer. However, Lake Las Madres is affected by precipitation, wind and, to a lesser extent, temperature, whereas the ACMs have less influence. Therefore, we aim to show that the lakes of the Iberian Peninsula are sensitive to these ACMs. The results presented here indicate that the lake dynamics, in some cases, have a higher sensitivity to variations in the ACMs than single local meteorological variables. However, certain local features, such as geography, lake morphology and anthropic influences, are crucial to properly record the signals of these ACMs. [ABSTRACT FROM AUTHOR]

China faces an increasing challenge in water resources in the coming decades; thus high-confidence climate projection is of particular importance for the country's future. In this paper, we evaluate the performance of a long high-resolution continuous simulation over China based on multiple observations and the corresponding historical simulation. The simulation is completed using the Weather Research and Forecasting (WRF) model driven by the Model for Interdisciplinary Research on Climate version 5 (MIROC5) in the context of the Coupled Model Intercomparison Project Phase 5. The results show that both MIROC5 and WRF can capture the distribution and variability of temperature over China, whereas WRF shows improvements, particularly for simulation of regional features. Compared with MIROC5, WRF can reproduce the spatial distribution, annual cycle, probability distribution, and seasonal evolution of the precipitation over mainland China and the sub-regions with better performance. The trend is of fundamental importance in the future projection estimations, and WRF shows better skill in simulating the annual mean precipitation trend. However, there is overestimation of precipitation in Southeast China while negative one in the middle latitude of China in WRF simulation, which can be traced back to model bias in atmospheric circulation and water vapor transportation in these regions. Several extreme climate indices are selected to further assess the model's performance in simulating climate extremes, WRF can well reproduce the main features with better model skill compared with MIROC5. The better performance of WRF indicates the necessity of the dynamical downscaling technique and the robustness of regional climate simulation in future regional climate projection over China. [ABSTRACT FROM AUTHOR]

The West Africa rainfall regime constitutes a considerable challenge for Regional Climate Models (RCMs) due to the complexity of dynamical and physical processes that characterise the West African Monsoon. In this paper, daily precipitation statistics are evaluated from the contributions to the AFRICA-CORDEX experiment from two ERA-Interim driven Canadian RCMs: CanRCM4, developed at the Canadian Centre for Climate Modelling and Analysis (CCCma) and CRCM5, developed at the University of Québec at Montréal. These modelled precipitation statistics are evaluated against three gridded observed datasets-the Global Precipitation Climatology Project (GPCP), the Tropical Rainfall Measuring Mission (TRMM), and the Africa Rainfall Climatology (ARC2)-and four reanalysis products (ECMWF ERA-Interim, NCEP/DOE Reanalysis II, NASA MERRA and NOAA-CIRES Twentieth Century Reanalysis). The two RCMs share the same dynamics from the Environment Canada GEM forecast model, but have two different physics' packages: CanRCM4 obtains its physics from CCCma's global atmospheric model (CanAM4), while CRCM5 shares a number of its physics modules with the limited-area version of GEM forecast model. The evaluation is focused on various daily precipitation statistics (maximum number of consecutive wet days, number of moderate and very heavy precipitation events, precipitation frequency distribution) and on the monsoon onset and retreat over the Sahel region. We find that the CRCM5 has a good representation of daily precipitation statistics over the southern Sahel, with spatial distributions close to GPCP dataset. Some differences are observed in the northern part of the Sahel, where the model is characterised by a dry bias. CanRCM4 and the ERA-Interim and MERRA reanalysis products overestimate the number of wet days over Sahel with a shift in the frequency distribution toward smaller daily precipitation amounts than in observations. Both RCMs and reanalyses have difficulties in reproducing the local onset date over the Sahel region. Nevertheless, the large-scale features of the monsoon precipitation evolution over West Africa are well reproduced by the RCMs, whereas the northern limit of the rainy bands is less accurately reproduced. Both RCMs exhibit an overall good representation of the local retreat index over the Sahel region. [ABSTRACT FROM AUTHOR]

This study examines the oceanic and atmospheric variability over the Intra-American Seas (IAS) from a 32-year integration of a 15-km coupled regional climate model consisting of the Regional Spectral Model (RSM) for the atmosphere and the Regional Ocean Modeling System (ROMS) for the ocean. It is forced at the lateral boundaries by National Centers for Environmental Prediction-Department of Energy (NCEP-DOE R-2) atmospheric global reanalysis and Simplified Ocean Data Assimilation global oceanic reanalysis. This coupled downscaling integration is a free run without any heat flux correction and is referred as the Regional Ocean-Atmosphere coupled downscaling of global Reanalysis over the Intra-American Seas (ROARS). The paper examines the fidelity of ROARS with respect to independent observations that are both satellite based and in situ. In order to provide a perspective on the fidelity of the ROARS simulation, we also compare it with the Climate Forecast System Reanalysis (CFSR), a modern global ocean-atmosphere reanalysis product. Our analysis reveals that ROARS exhibits reasonable climatology and interannual variability over the IAS region, with climatological SST errors less than 1 °C except along the coastlines. The anomaly correlation of the monthly SST and precipitation anomalies in ROARS are well over 0.5 over the Gulf of Mexico, Caribbean Sea, Western Atlantic and Eastern Pacific Oceans. A highlight of the ROARS simulation is its resolution of the loop current and the episodic eddy events off of it. This is rather poorly simulated in the CFSR. This is also reflected in the simulated, albeit, higher variance of the sea surface height in ROARS and the lack of any variability in the sea surface height of the CFSR over the IAS. However the anomaly correlations of the monthly heat content anomalies of ROARS are comparatively lower, especially over the Gulf of Mexico and the Caribbean Sea. This is a result of ROARS exhibiting a bias of underestimation (overestimation) of high (low) clouds. ROARS like CFSR is also able to capture the Caribbean Low Level Jet and its seasonal variability reasonably well. [ABSTRACT FROM AUTHOR]

Many coupled general circulation models (CGCMs) suffer from serious model bias in the zonal gradient of sea surface temperature (SST) in the equatorial Atlantic. The bias of the equatorial Atlantic SST (EASST) may affect the interannual variability of the equatorial Atlantic, which in turn may influence the state of the tropical Pacific. In this paper we investigate the impact of the bias and the interannual variability of the EASST on the tropical Pacific in a CGCM. To determine the impact of the interannual variability of the EASST on the tropical Pacific, we compare a run in a fully coupled mode (CTL run) and a run in which the EASST is nudged toward the climatological monthly mean of the SST in the CTL run, but full air-sea coupling is allowed elsewhere (AT_m run). We find that, when the interannual variability of the EASST is excluded, the thermocline depth in the eastern equatorial Pacific is deepened, and the amplitude of the El Niño/Southern Oscillation is reduced by 30 % compared to the CTL run. The impact of the bias of the EASST on the tropical Pacific is investigated by comparing the AT_m run and a run in which the EASST is nudged toward the observed climatological monthly mean SST (AT_o run). It is found that, when the bias of the EASST is removed (i.e. AT_o run), the Gill-Matsuno type response to the warm SST anomalies in the western equatorial Atlantic induces low-level cyclonic anomalies in the eastern South Pacific, which leads to a deeper thermocline and colder SST in the South Pacific as compared to AT_m. The colder SST in the South Pacific reduces the precipitation along the South Pacific convergence zone. Our results of the model experiments demonstrate the importance of the EASST to the tropical Pacific climate. [ABSTRACT FROM AUTHOR]

Land-sea surface air temperature (SAT) contrast, an index of tropospheric thermodynamic structure and dynamical circulation, has shown a significant increase in recent decades over East Asia during the boreal summer. In Part I of this two-part paper, observational data and the results of transient warming experiments conducted using coupled atmosphere-ocean general circulation models (GCMs) are analyzed to examine changes in land-sea thermal contrast and the associated atmospheric circulation over East Asia from the past to the future. The interannual variability of the land-sea SAT contrast over the Far East for 1950-2012 was found to be tightly coupled with a characteristic tripolar pattern of tropospheric circulation over East Asia, which manifests as anticyclonic anomalies over the Okhotsk Sea and around the Philippines, and a cyclonic anomaly over Japan during a positive phase, and vice versa. In response to CO increase, the cold northeasterly winds off the east coast of northern Japan and the East Asian rainband were strengthened with the circulation pattern well projected on the observed interannual variability. These results are commonly found in GCMs regardless of future forcing scenarios, indicating the robustness of the East Asian climate response to global warming. The physical mechanisms responsible for the increase of the land-sea contrast are examined in Part II. [ABSTRACT FROM AUTHOR]

Based on numerical experiments using the NCAR CAM3-CLM3 models, this paper examines the impact of soil moisture, vegetation, and sea surface temperature (SST) on the inter-annual variability of climate over land. For each element, two experiments are carried out, with the inter-annual variability preserved in one experiment and eliminated in the other. Differences in the standard deviation of the precipitation and air temperature at the inter-annual time scale are used to quantify the impacts from soil moisture dynamics, vegetation dynamics, and oceanic forcing. The impact of oceanic forcing is mainly limited to the Tropics, with the strongest signal in the equatorial zone, and moisture convergence is the key linkage between SST forcing and tropical precipitation. Soil moisture plays a significant role in climate variability during the rainy seasons of all semi-arid regions (which is consistent with many previous studies), and during the dry seasons of the humid Amazon. Evapotranspiration is identified as the main mechanism linking precipitation variability to soil moisture. Amazon is the only region where vegetation dynamics has a significant influence on precipitation variability. However, the impact of vegetation dynamics on temperature is strong over the US Great Plains in all four seasons and in the Amazon region during the dry and dry-to-wet transition seasons. [ABSTRACT FROM AUTHOR]

On a hemispheric scale, it is now well established that stratospheric ozone depletion has been the principal driver of externally forced atmospheric circulation changes south of the Equator in the last decades of the 20th Century. The impact of ozone depletion has been felt over the entire hemisphere, as reflected in the poleward drift of the midlatitude jet, the southward expansion of the summertime Hadley cell and accompanying precipitation trends deep into the subtropics. On a regional scale, however, surface impacts directly attributable to ozone depletion have yet to be identified. In this paper we focus on South Eastern South America (SESA), a region that has exhibited one of the largest wetting trends during the 20th Century. We study the impact of ozone depletion on SESA precipitation using output from 6 different climate models, spanning a wide range of complexity. In all cases we contrast pairs of model integrations with and without ozone depletion, but with all other forcings identically specified. This allows for unambiguous attribution of the computed precipitation trends. All 6 climate models consistently reveal that stratospheric ozone depletion results in a significant wetting of SESA over the period 1960-1999. Taken as a whole, these model results strongly suggest that the impact of ozone depletion on SESA precipitation has been as large as, and quite possibly larger than, the one caused by increasing greenhouse gases over the same period. [ABSTRACT FROM AUTHOR]

The possible change in the characteristics of weather in the future should be considered as important as the mean climate change because the increasing risk of extremes is related to the variability on daily time scales. The weather characteristics can be represented by the climatological mean interdiurnal (day-to-day) variability (MIDV). This paper first assessed the phase five of the Coupled Model Intercomparison Project coupled climate models’ capability to represent MIDV for the surface maximum and minimum temperature, surface wind speed and precipitation under the present climate condition. Based on the assessment, we selected three best models for projecting future change. We found that the future changes in MIDV are characterized by: (a) a marked reduction in surface maximum and minimum temperature over high latitudes during the cold season; (b) a stronger reduction in the surface minimum temperature than in the maximum temperature; (c) a reduction in surface wind speed over large parts of lands in Northern Hemisphere (NH) during NH spring; (d) a noticeable increase in precipitation in NH mid-high latitudes in NH spring and winter, and in particular over East Asia throughout most of the year. [ABSTRACT FROM AUTHOR]

This paper is dedicated to the analysis of winter cold spells over Western Europe in the simulations of the 5th phase of the Coupled Model Intercomparison Project (CMIP5). Both model biases and responses in a warming climate are discussed using historical simulations and the 8.5 W/m 2 Representative Concentration Pathway (RCP8.5) scenario, respectively on the 1979–2008 and 2070–2099 periods. A percentile-based index (10th percentile of daily minimum temperature, Q10) with duration and spatial extent criteria is used to define cold spells. Related diagnostics (intensity, duration, extent, and severity as a combination of the former three statistics) of 13 models are compared to observations and suggest that models biases on severity are mainly due to the intensity parameter rather than to duration and extent. Some hypotheses are proposed to explain these biases, that involve large-scale dynamics and/or radiative fluxes related to clouds. Evolution of cold spells characteristics by the end of the century is then discussed by comparing RCP8.5 and historical simulations. In line with the projected rise of mean temperature, “present-climate” cold spells (computed with the 1979–2008 10th percentile, Q10P) are projected to be much less frequent and, except in one model, less severe. When cold spells are defined from the future 10th percentile threshold (“future-climate” cold spells, Q10F), all models simulate a decrease of their intensity linearly related to the seasonal mean warming. Some insights are given to explain the inter-model diversity in the magnitude of the cold spells response. In particular, the snow-albedo feedback is suggested to play an important role, while for some models changes in large-scale dynamics are also not negligible. [ABSTRACT FROM AUTHOR]

This is the second of the two-part paper series on the analysis and evaluation of the Fifth phase of Coupled Model Intercomparison Project (CMIP5) simulation of contemporary climate as well as IPCC, AR5 Representative Concentrations Pathways (RCP), 4.5 and 8.5 scenarios projections of the Greater Horn of Africa (GHA) Climate. In the first part (Otieno and Anyah in Clim Dyn, ) we focused on the historical simulations, whereas this second part primarily focuses on future projections based on the two scenarios. Six Earth System Models (ESMs) from CMIP5 archive have been used to characterize projected changes in seasonal and annual mean precipitation, temperature and the hydrological cycle by the middle of twenty-first century over the GHA region, based on IPCC, 5th Assessment Report (AR5) RCP4.5 and RCP8.5 scenarios. Nearly all the models outputs analyzed reproduce the correct mean annual cycle of precipitation, with some biases among the models in capturing the correct peak of precipitation cycle, more so, March-April-May (MAM) seasonal rainfall over the equatorial GHA region. However, there is significant variation among models in projected precipitation anomalies, with some models projecting an average increase as others project a decrease in precipitation during different seasons. The ensemble mean of the ESMs indicates that the GHA region has been experiencing a steady increase in both precipitation and temperature beginning in the early 1980s and 1970s respectively in both RCP4.5 and RCP8.5 scenarios. Going by the ensemble means, temperatures are projected to steadily increase uniformly in all the seasons at a rate of 0.3/0.5 °C/decade under RCP4.5/8.5 scenarios over northern GHA region leading to an approximate temperature increase of 2/3 °C by the middle of the century. On the other hand, temperatures will likely increase at a rate of 0.3/0.4 °C/decade under RCP4.5/8.5 scenarios in both equatorial and southern GHA region leading to an approximate temperature increase of 2/2.5 °C by the middle of twenty-first century. Nonetheless, projected precipitation increase varied across seasons and sub-regions. With the exception of the equatorial region, that is projected to experience precipitation increase during DJF season, most sub-regions are projected to experience precipitation increase within their peak seasons, with the highest rate of increase experienced during DJF and OND seasons over southern and equatorial GHA regions respectively. Notably, as precipitation increases, the deficit (E < P) between evaporation (E) and precipitation (P) increased over the years, with a negatively skewed distribution. This generally implies that there is a high likelihood of an increased deficit in local moisture supply. This remarkable change in the general hydrological cycle (i.e. deficit in local moisture) is projected to be also coincident with intensified westerly anomaly influx from the Congo basin into the region. However, better understanding of the detailed changes in hydrological cycle will require comprehensive water budget analyses that require daily or sub-daily variables, and was not a specific focus of the present study. [ABSTRACT FROM AUTHOR]