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Recent studies have shown that global warming and associated sea-surface temperature (SST) changes may trigger an important rainfall increase in southeastern South America (SESA) during the austral summer (December-January-February, DJF). The goal of this paper is to provide some insight into processes which may link global and SESA changes. For this purpose, a 'two-way nesting' system coupling interactively the regional and global versions of the LMDZ4 atmospheric model is used to study the response to prescribed SST changes. The regional model is a variable-grid version of the global model, with a zoom focused over South America. An ensemble of simulations forced by distinct patterns of DJF SST changes has been carried out using a decomposition of full SST changes into their longitudinal and latitudinal components. The full SST changes are based on projections for the end of the twenty-first century from a multi-model ensemble of WCRP/CMIP3. Results confirm the presence of a major rainfall dipole structure, characterized by an increase in SESA and a decrease in the South Atlantic Convergence Zone region. Rainfall changes found in the WCRP/CMIP3 models are largely explained as a response of this dipole structure to the zonally-asymmetric (or longitudinal) component of SST changes. The rainfall response to the zonal-mean (or latitudinal) SST changes (including the global warming signal itself) shows an opposite contribution. The processes explaining the role of zonally-asymmetric SST changes involve remote effects of SST warming over the equatorial Indian and Pacific oceans inducing an atmospheric wave-train extended across the South Pacific into South America. [ABSTRACT FROM AUTHOR]

Coupled ocean-atmosphere general circulation models (GCMs) lack sufficient resolution to model the regional detail of changes to mean circulation and rainfall with projected climate warming. In this paper, changes in mean circulation and rainfall in GCMs are compared to those in a variable resolution regional climate model, the Conformal Cubic Atmospheric Model (CCAM), under a high greenhouse gas emissions scenario. The study site is Tasmania, Australia, which is positioned within the mid-latitude westerlies of the southern hemisphere. CCAM projects a different response in mean sea level pressure and mid-latitude westerly circulation to climate warming to the GCMs used as input, and shows greater regional detail of the boundaries between regions of increasing and decreasing rainfall. Changes in mean circulation dominate the mean rainfall response in western Tasmania, whereas changes to rainfall in the East Coast are less related to mean circulation changes. CCAM projects an amplification of the dominant westerly circulation over Tasmania and this amplifies the seasonal cycle of wet winters and dry summers in the west. There is a larger change in the strength than in the incidence of westerly circulation and rainfall events. We propose the regional climate model displays a more sensitive atmospheric response to the different rates of warming of land and sea than the GCMs as input. The regional variation in these results highlight the need for dynamical downscaling of coupled general circulation models to finely resolve the influence of mean circulation and boundaries between regions of projected increases and decreases in rainfall. [ABSTRACT FROM AUTHOR]

Increasing concentrations of atmospheric CO influence climate, terrestrial biosphere productivity and ecosystem carbon storage through its radiative, physiological and fertilization effects. In this paper, we quantify these effects for a doubling of CO using a low resolution configuration of the coupled model NCAR CCSM4. In contrast to previous coupled climate-carbon modeling studies, we focus on the near-equilibrium response of the terrestrial carbon cycle. For a doubling of CO, the radiative effect on the physical climate system causes global mean surface air temperature to increase by 2.14 K, whereas the physiological and fertilization on the land biosphere effects cause a warming of 0.22 K, suggesting that these later effects increase global warming by about 10 % as found in many recent studies. The CO-fertilization leads to total ecosystem carbon gain of 371 Gt-C (28 %) while the radiative effect causes a loss of 131 Gt-C (~10 %) indicating that climate warming damps the fertilization-induced carbon uptake over land. Our model-based estimate for the maximum potential terrestrial carbon uptake resulting from a doubling of atmospheric CO concentration (285-570 ppm) is only 242 Gt-C. This highlights the limited storage capacity of the terrestrial carbon reservoir. We also find that the terrestrial carbon storage sensitivity to changes in CO and temperature have been estimated to be lower in previous transient simulations because of lags in the climate-carbon system. Our model simulations indicate that the time scale of terrestrial carbon cycle response is greater than 500 years for CO-fertilization and about 200 years for temperature perturbations. We also find that dynamic changes in vegetation amplify the terrestrial carbon storage sensitivity relative to a static vegetation case: because of changes in tree cover, changes in total ecosystem carbon for CO-direct and climate effects are amplified by 88 and 72 %, respectively, in simulations with dynamic vegetation when compared to static vegetation simulations. [ABSTRACT FROM AUTHOR]

In the present paper the effect of an abrupt change of the atmospheric radiative forcing is investigated by means of a global climate model that includes a mixed layer ocean. In assessing if, under such a change, the model response has a bifurcation point, the steady solution is studied for a sudden decrease of CO concentration from its actual value. It is found that there is a critical threshold for CO content below which the model ends up to a snowball Earth. It occurs for a few percentage changes of CO concentration around the threshold because the model strongly depends on the relationship among atmospheric temperature, water vapor content and the sudden ice-albedo feedback activation, even in the subtropical regions. Moreover, results suggest that the transition to ice-covered Earth is clearly favoured when Q-flux corrections (i.e. the parameterization of ocean heat transports) are removed. [ABSTRACT FROM AUTHOR]

The water vapour feedback probably makes the largest contribution to climate sensitivity, and the second-largest contribution to its uncertainty, in the sense of disagreement between General Circulation Models (GCMs, the most physically detailed models of climate we have). Yet there has been no quantification of it which allows these differences to be attributed physically with the aim of constraining the true value. This paper develops a new breakdown of the non-cloud LW (longwave) response to climate change, which avoids the problems of the conventional breakdown, and applies it to a set of 4 GCMs. The basic physical differences are that temperature is used as the vertical coordinate, and relative humidity as the humidity variable. In this framework the different GCMs' feedbacks look more alike, consistent with our understanding that their water vapour responses are physically very similar. Also, in the global mean all the feedback components have the same sign, allowing us to conveniently attribute the overall response fractionally (e.g. about 60% from the 'partly-Simpsonian' component). The systematic cancellation between different feedback components in the conventional breakdown is lost, so now a difference in a feedback component actually contributes to a difference in climate sensitivity, and the differences between these GCMs in the non-cloud LW part of this can be traced to differences in formulation, mean climate and climate change response. Physical effects such as those due to variations in the formulation of LW radiative transfer become visible. Differences in the distribution of warming no longer dominate comparison of GCMs. The largest component depends locally only on the GCM's mean climate, so it can in principle be calculated for the real world and validated. However, components dependent on the climate change response probably account for most of the variation between GCMs. The effect of simply changing the humidity variable in the conventional breakdown is also examined. It gives some of this improvement-the loss of the cancellations that leave the conventional breakdown of no use to understand differences between GCMs' climate sensitivities-but not the link to mean climate. [ABSTRACT FROM AUTHOR]

The North Pacific Oscillation (NPO) recently (re-)emerged in the literature as a key atmospheric mode in Northern Hemisphere climate variability, especially in the Pacific sector. Defined as a dipole of sea level pressure (SLP) between, roughly, Alaska and Hawaii, the NPO is connected with downstream weather conditions over North America, serves as the atmospheric forcing pattern of the North Pacific Gyre Oscillation (NPGO), and is a potential mechanism linking extratropical atmospheric variability to El Niño events in the tropical Pacific. This paper explores further the forcing dynamics of the NPO and, in particular, that of its individual poles. Using observational data and experiments with a simple atmospheric general circulation model (AGCM), we illustrate that the southern pole of the NPO (i.e., the one near Hawaii) contains significant power at low frequencies (7-10 years), while the northern pole (i.e., the one near Alaska) has no dominant frequencies. When examining the low-frequency content of the NPO and its poles separately, we discover that low-frequency variations (periods >7 years) of the NPO (particularly its subtropical node) are intimately tied to variability in central equatorial Pacific sea surface temperatures (SSTs) associated with the El Niño-Modoki/Central Pacific Warming (CPW) phenomenon. This result suggests that fluctuations in subtropical North Pacific SLP are important to monitor for Pacific low-frequency climate change. Using the simple AGCM, we also illustrate that variability in central tropical Pacific SSTs drives a significant fraction of variability of the southern node of the NPO. Taken together, the results highlight important links between secondary modes (i.e., CPW-NPO-NPGO) in Pacific decadal variability, akin to already established relationships between the primary modes of Pacific climate variability (i.e., canonical El Niño, the Aleutian Low, and the Pacific Decadal Oscillation). [ABSTRACT FROM AUTHOR]

Medicanes, strong mesoscale cyclones with tropical-like features, develop occasionally over the Mediterranean Sea. Due to the scarcity of observations over sea and the coarse resolution of the long-term reanalysis datasets, it is difficult to study systematically the multidecadal statistics of sub-synoptic medicanes. Our goal is to assess the long-term variability and trends of medicanes, obtaining a long-term climatology through dynamical downscaling of the NCEP/NCAR reanalysis data. In this paper, we examine the robustness of this method and investigate the value added for the study of medicanes. To do so, we performed several climate mode simulations with a high resolution regional atmospheric model (CCLM) for a number of test cases described in the literature. We find that the medicanes are formed in the simulations, with deeper pressures and stronger winds than in the driving global NCEP reanalysis. The tracks are adequately reproduced. We conclude that our methodology is suitable for constructing multi-decadal statistics and scenarios of current and possible future medicane activities. [ABSTRACT FROM AUTHOR]

The main aim of this paper is to evaluate the Advanced Research Weather Research and Forecasting (WRF) regional model in simulating the precipitation over southern Africa during austral summer. The model's ability to reproduce the southern African mean climate and its variability around this mean state was evaluated by using the two-tier approach of specifying sea surface temperature (SST) to WRF and by using the one-tier approach of coupling the WRF with a simple mixed-layer ocean model. The boundary conditions provided by the reanalysis-II data were used for the simulations. Model experiments were conducted for twelve austral summers from DJF1998-99 to DJF2009-10. The experiments using both the two-tier and one-tier approaches simulated the spatial and temporal distributions of the precipitation realistically. However, both experiments simulated negative biases over Mozambique. Furthermore, analysis of the wet and dry spells revealed that the one-tier approach is superior to the two-tier approach. Based on the analysis of the surface temperature and the zonal wind shear it is noted that the simple mixed-layer ocean model coupled to WRF can be effectively used in place of two-tier WRF to simulate the climate of southern Africa. This is an important result because specification of SST at higher temporal resolutions in the subtropics is the most difficult task in the two-tier approach for most regional prediction models. The one-tier approach with the simple mixed-layer model can effectively reduce the complicacy of finding good SST predictions. [ABSTRACT FROM AUTHOR]

This paper aims at characterizing how different key cloud properties (cloud fraction, cloud vertical distribution, cloud reflectance, a surrogate of the cloud optical depth) vary as a function of the others over the tropical oceans. The correlations between the different cloud properties are built from 2 years of collocated A-train observations (CALIPSO-GOCCP and MODIS) at a scale close to cloud processes; it results in a characterization of the physical processes in tropical clouds, that can be used to better understand cloud behaviors, and constitute a powerful tool to develop and evaluate cloud parameterizations in climate models. First, we examine a case study of shallow cumulus cloud observed simultaneously by the two sensors (CALIPSO, MODIS), and develop a methodology that allows to build global scale statistics by keeping the separation between clear and cloudy areas at the pixel level (250, 330 m). Then we build statistical instantaneous relationships between the cloud cover, the cloud vertical distribution and the cloud reflectance. The vertical cloud distribution indicates that the optically thin clouds (optical thickness <1.5) dominate the boundary layer over the trade wind regions. Optically thick clouds (optical thickness >3.4) are composed of high and mid-level clouds associated with deep convection along the ITCZ and SPCZ and over the warm pool, and by stratocumulus low level clouds located along the East coast of tropical oceans. The cloud properties are analyzed as a function of the large scale circulation regime. Optically thick high clouds are dominant in convective regions (CF > 80 %), while low level clouds with low optical thickness (<3.5) are present in regimes of subsidence but in convective regimes as well, associated principally to low cloud fractions (CF < 50 %). A focus on low-level clouds allows us to quantify how the cloud optical depth increases with cloud top altitude and with cloud fraction. [ABSTRACT FROM AUTHOR]

This paper presents an evaluation of the multi-model simulations for the 4th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) in terms of their ability to simulate the ERA40 circulation types over the Euro-Atlantic region in winter season. Two classification schemes, k-means and SANDRA, have been considered to test the sensitivity of the evaluation results to the classification procedure. The assessment allows establishing different rankings attending spatial and temporal features of the circulation types. Regarding temporal characteristics, in general, all AR4 models tend to underestimate the frequency of occurrence. The best model simulating spatial characteristics is the UKMO-HadGEM1 whereas CCSM3, UKMO-HadGEM1 and CGCM3.1(T63) are the best simulating the temporal features, for both classification schemes. This result agrees with the AR4 models ranking obtained when having analysed the ability of the same AR4 models to simulate Euro-Atlantic variability modes. This study has proved the utility of applying such a synoptic climatology approach as a diagnostic tool for models' assessment. The ability of the models to properly reproduce the position of ridges and troughs and the frequency of synoptic patterns, will therefore improve our confidence in the response of models to future climate changes. [ABSTRACT FROM AUTHOR]

Marine Isotope Stage (MIS) 13, an interglacial about 500,000 years ago, is unique due to an exceptionally strong East Asia summer monsoon (EASM) occurring in a relatively cool climate with low greenhouse gas concentrations (GHG). This paper attempts to find one of the possible mechanisms for this seeming paradox. Simulations with an Earth System model LOVECLIM show that the presence of ice sheets over North America and Eurasia during MIS-13 induces a positive phase of the winter North Atlantic Oscillation (NAO) like feature. The ocean having a longer memory than the atmosphere, the oceanic anomalies associated with NAO persists until summer. The signals of summer NAO are transmitted to East Asia to reinforce the monsoon there through the stationary waves excited at the Asian Jet entrance. The geopotential height shows clearly a mid-latitude wave train with positive anomalies over the eastern Mediterranean/Caspian Sea and the Okhotsk Sea and a negative anomaly over Lake Baikal. This reinforces the effect of the high-latitude wave train induced independently by the Eurasian ice sheet topography as shown in previous study. These features reinforce the Meiyu front and enhance the precipitation over East Asia. The results obtained from LOVECLIM are further confirmed by an atmospheric general circulation model, ARPEGE. [ABSTRACT FROM AUTHOR]

This paper provides a synoptic view of extreme monsoon floods on all the nine large rivers of South Asia and their association with the excess (above-normal) monsoon rainfall periods. Annual maximum flood series for 18 gauging stations spread over four countries (India, Pakistan, Bangladesh and Nepal) and long-term monsoon rainfall data were analyzed to ascertain whether the extreme floods were clustered in time and whether they coincided with multi-decade excess monsoon rainfall epochs at the basin level. Simple techniques, such as the Cramer's t-test, regression and Mann-Kendall (MK) tests and Hurst method were used to evaluate the trends and patterns of the flood and rainfall series. MK test reveals absence of any long-term tendency in all the series. However, the Cramer's t test and Hurst-Mandelbrot rescaled range statistic provide evidence that both rainfall and flood time series are persistent. Using the Cramer's t-test the excess monsoon epochs for each basin were identified. The excess monsoon periods for different basins were found to be highly asynchronous with respect to duration as well as the beginning and end. Three main conclusions readily emerge from the analyses. Extreme floods (>90th percentile) in South Asia show a tendency to cluster in time. About three-fourth of the extreme floods have occurred during the excess monsoon periods between ~1840 and 2000 AD, implying a noteworthy link between the two. The frequency of large floods was higher during the post-1940 period in general and during three decades (1940s, 1950s and 1980s) in particular. [ABSTRACT FROM AUTHOR]

Surface temperatures are projected to increase 3-4°C over much of Africa by the end of the 21st century. Precipitation projections are less certain, but the most plausible scenario given by the Intergovernmental Panel on Climate Change (IPCC) is that the Sahel and East Africa will experience modest increases (~5%) in precipitation by the end of the 21st century. Evapotranspiration (E) is an important component of the water, energy, and biogeochemical cycles that impact several climate properties, processes, and feedbacks. The interaction of E with climate change drivers remains relatively unexplored in Africa. In this paper, we examine the trends in E, precipitation (P), daily maximum temperature (T), and daily minimum temperature (T) on a seasonal basis using a 31 year time series of variable infiltration capacity (VIC) land surface model (LSM) E. The VIC model captured the magnitude, variability, and structure of observed runoff better than other LSMs and a hybrid model included in the analysis. In addition, we examine the inter-correlations of E, P, T, and T to determine relationships and potential feedbacks. Unlike many IPCC climate change simulations, the historical analysis reveals substantial drying over much of the Sahel and East Africa during the primary growing season. In the western Sahel, large increases in daily maximum temperature appear linked to E declines, despite modest rainfall recovery. The decline in E and latent heating in this region could lead to increased sensible heating and surface temperature, thus establishing a possible positive feedback between E and surface temperature. [ABSTRACT FROM AUTHOR]

Surface wind speed is a key climatic variable of interest in many applications, including assessments of storm-related infrastructure damage and feasibility studies of wind power generation. In this work and a companion paper (van der Kamp et al. ), the relationship between local surface wind and large-scale climate variables was studied using multiple regression analysis. The analysis was performed using monthly mean station data from British Columbia, Canada and large-scale climate variables (predictors) from the NCEP-2 reanalysis over the period 1979-2006. Two regression-based methodologies were compared. The first relates the annual cycle of station wind speed to that of the large-scale predictors at the closest grid box to the station. It is shown that the relatively high correlation coefficients obtained with this method are attributable to the dominant influence of region-wide seasonality, and thus contain minimal information about local wind behaviour at the stations. The second method uses interannually varying data for individual months, aggregated into seasons, and is demonstrated to contain intrinsically local information about the surface winds. The dependence of local wind speed upon large-scale predictors over a much larger region surrounding the station was also explored, resulting in 2D maps of spatial correlations. The cross-validated explained variance using the interannual method was highest in autumn and winter, ranging from 30 to 70% at about a dozen stations in the region. Reasons for the limited predictive skill of the regressions and directions for future progress are reviewed. [ABSTRACT FROM AUTHOR]

One obstacle on the way to a comprehensive spatial reconstruction of regional temperature changes over the past centuries is the sparseness of long winter temperature records. This paper reconstructs a proxy record of April and November-December temperatures in south-central Finland for the interval from 1836 to 1872 from breakup and freeze-up dates and ice-cover duration of a lake. Emphasis is on detecting the suitable winter months and quantifying the calibrations with measured temperatures (1873-2002). The calibration slope for the breakup date (0.158°C/day) is larger than for freeze-up date (0.119°C/day) or duration (0.090°C/day). A comparison with results from other proxy records shows that the slope may depend also on the geographical site. Trend analyses of the full temperature records (1836-2002) indicate the existence of minor change-points at around 1867 (April temperature) and 1874 (November-December temperature), with warming rates thereafter of 1.67°C per century (April) and 1.16°C per century (November-December). Spectral analyses reveal peaks in the band between 2 and 5 year period, which may point to influences of the North Atlantic Oscillation, and less power in the decadal band (up to 42 year period). [ABSTRACT FROM AUTHOR]

This paper investigates the impact of the Madden-Julian Oscillation (MJO) on the diurnal cycle of rainfall over the western Maritime Continent during the austral summer. For this purpose, cyclostationary empirical orthogonal function analysis is applied to the tropical rainfall measuring mission rain rate and the Japanese Reanalysis-25 data for the period 1998-2008. The real-time multivariate MJO index by Wheeler and Hendon (Mon Wea Rev 132:1917-1932, ) is adopted to define the intensity and the phase of MJO. It is demonstrated that the hourly maximum rain rate over the domain tends to increase when convectively active phase of MJO approaches the Maritime Continent. In contrast, the hourly maximum rain rate tends to decrease when convectively suppressed phase of MJO resides over the region. The changes in the rain rate due to MJO differ over the ocean and the land. This difference is the greatest when the MJO is in the mature stage. Throughout the day during this stage, terrestrial rain rates show minimum values while diurnally varying oceanic rain rates record maximum values. Thus, precipitation becomes more intense in the morning over the Java Sea and is weakened in the evening over Borneo and Sumatra during the mature stage of MJO. During the decaying stage of MJO over the Maritime Continent, the diurnal cycle of precipitation weakens significantly over the ocean but only weakly over land. Analyses suggest that the anomalous lower level winds accompanied by MJO interact with the monsoonal flow over the Maritime Continent. Westerlies induced by MJO convection in the mature stage are superimposed on the monsoonal westerlies over the equator and increase wind speed mainly over the Java Sea due to the blocking effect of orography. Mountainous islands induce flow bifurcation, causing near-surface winds to converge mainly over the oceanic channels between two islands. As a result, heat flux release from the ocean to the atmosphere is enhanced by the increased surface wind resulting in instability as described in the wind-induced surface heat exchange mechanism. This may contribute to heavy rainfall over the Java Sea in the morning during the mature stage. On the other hand, convergence and vertical velocity over the islands, which play important roles in inducing nighttime rainfall, tend to be weak in the evening during the mature stage of MJO. Strong westerlies arising from MJO and the seasonal flow during the mature stage tend to interrupt convergence over islands. This interruption of convergence by MJO gives rise to decreased rain rates over the land regions. [ABSTRACT FROM AUTHOR]

A series of recent papers showed that sea surface temperature (SST) anomalies in the south equatorial tropical Atlantic modulate the interannual variability of the African and Indian monsoon rainfall. Physically this teleconnection can be explained by a simple Gill-Matsuno mechanism. In this work, the output from five different models chosen within the CMIP3 (Coupled Model Intercomparison Project version 3) ensemble of coupled general circulation models (CGCMs) are analyzed to investigate how state-of-the-art CGCMs represent the impact of the South Tropical Atlantic (STA) SSTs on the Indian and African region. Using a correlation-regression technique, it is found that four out of the five models display a teleconnection between STA and Indian region which is generally weaker than in the observations but in agreement in the rainfall field pattern. This teleconnection is also noticeable in the ensemble mean of the five models. Over Africa, however, the significant changes in rainfall displayed in the observation are properly caught by only one of the CGCMs. Additionally, none of the models reproduces the symmetric upper-level wind response around the Equator seen over the Indian Ocean in the observations and all have significant biases also in the surface pressure field response to the tropical Atlantic SSTs. Nonetheless the STA response, particularly over the southern hemisphere, is indicative of the Gill-Matsuno-type mechanism identified in previous studies using idealized experiments with atmospheric GCMs and observational data. With a suite of atmospheric-only GCM integrations it is shown that the differences in amplitude and pattern are not only due to the strong biases and reduced variabilities of the CGCMs over the tropical Atlantic but they are also caused by the different physical parameterizations used in models. [ABSTRACT FROM AUTHOR]

Black carbon aerosols absorb solar radiation and decrease planetary albedo, and thus can contribute to climate warming. In this paper, the dependence of equilibrium climate response on the altitude of black carbon is explored using an atmospheric general circulation model coupled to a mixed layer ocean model. The simulations model aerosol direct and semi-direct effects, but not indirect effects. Aerosol concentrations are prescribed and not interactive. It is shown that climate response of black carbon is highly dependent on the altitude of the aerosol. As the altitude of black carbon increases, surface temperatures decrease; black carbon near the surface causes surface warming, whereas black carbon near the tropopause and in the stratosphere causes surface cooling. This cooling occurs despite increasing planetary absorption of sunlight (i.e. decreasing planetary albedo). We find that the trend in surface air temperature response versus the altitude of black carbon is consistent with our calculations of radiative forcing after the troposphere, stratosphere, and land surface have undergone rapid adjustment, calculated as 'regressed' radiative forcing. The variation in climate response from black carbon at different altitudes occurs largely from different fast climate responses; temperature dependent feedbacks are not statistically distinguishable. Impacts of black carbon at various altitudes on the hydrological cycle are also discussed; black carbon in the lowest atmospheric layer increases precipitation despite reductions in solar radiation reaching the surface, whereas black carbon at higher altitudes decreases precipitation. [ABSTRACT FROM AUTHOR]

The objective of this work is to evaluate climate simulations over South America using the regional Eta Model driven by four members of an ensemble of the UK Met Office Hadley Centre HadCM3 global model. The Eta Model has been modified with the purpose of performing long-term decadal integrations and has shown to reproduce 'present climate'-the period 1961-1990-reasonably well when forced by HadCM3. The global model lateral conditions with a resolution of 2.5° latitude × 3.75° longitude were provided at a frequency of 6 h. Each member of the global model ensemble has a different climate sensitivity, and the four members were selected to span the range of uncertainty encompassed by the ensemble. The Eta Model nested in the HadCM3 global model was configured with 40-km horizontal resolution and 38 layers in the vertical. No large-scale internal nudging was applied. Results are shown for austral summer and winter at present climate defined as 1961-90. The upper and low-level circulation patterns produced by the Eta-CPTEC/HadCM3 experiment set-up show good agreement with reanalysis data and the mean precipitation and temperature with CRU observation data. The spread in the downscaled mean precipitation and temperature is small when compared against model errors. On the other hand, the benefits in using an ensemble is clear in the improved representation of the seasonal cycle by the ensemble mean over any one realization. El Niño and La Niña years were identified in the HadCM3 member runs based on the NOAA Climate Prediction Center criterion of sea surface temperature anomalies in the Niño 3.4 area. The frequency of the El Niño and La Niña events in the studied period is underestimated by HadCM3. The precipitation and temperature anomalies typical of these events are reproduced by most of the Eta-CPTEC/HadCM3 ensemble, although small displacements of the positions of the anomalies occur. This experiment configuration is the first step on the implementation of Eta-CPTEC/HadCM3 upcoming experiments on climate change studies that are discussed in a companion paper. [ABSTRACT FROM AUTHOR]

This paper presents an assessment of the seasonal prediction skill of current global circulation models, with a focus on the two-meter air temperature and precipitation over the Southeast United States. The model seasonal hindcasts are analyzed using measures of potential predictability, anomaly correlation, Brier skill score, and Gerrity skill score. The systematic differences in prediction skill of coupled ocean-atmosphere models versus models using prescribed (either observed or predicted) sea surface temperatures (SSTs) are documented. It is found that the predictability and the hindcast skill of the models vary seasonally and spatially. The largest potential predictability (signal-to-noise ratio) of precipitation anywhere in the United States is found in the Southeast in the spring and winter seasons. The maxima in the potential predictability of two-meter air temperature, however, reside outside the Southeast in all seasons. The largest deterministic hindcast skill over the Southeast is found in wintertime precipitation. At the same time, the boreal winter two-meter air temperature hindcasts have the smallest skill. The large wintertime precipitation skill, the lack of corresponding two-meter air temperature hindcast skill, and a lack of precipitation skill in any other season are features common to all three types of models (atmospheric models forced with observed SSTs, atmospheric models forced with predicted SSTs, and coupled ocean-atmosphere models). Atmospheric models with observed SST forcing demonstrate a moderate skill in hindcasting spring-and summertime two-meter air temperature anomalies, whereas coupled models and atmospheric models forced with predicted SSTs lack similar skill. Probabilistic and categorical hindcasts mirror the deterministic findings, i.e., there is very high skill for winter precipitation and none for summer precipitation. When skillful, the models are conservative, such that low-probability hindcasts tend to be overestimates, whereas high-probability hindcasts tend to be underestimates. [ABSTRACT FROM AUTHOR]

At the National Centers for Environmental Prediction (NCEP), a reanalysis of the atmosphere, ocean, sea ice and land over the period 1979-2009, referred to as the climate forecast system reanalysis (CFSR), was recently completed. The oceanic component of CFSR includes many advances: (a) the MOM4 ocean model with an interactive sea-ice, (b) the 6 h coupled model forecast as the first guess, (c) inclusion of the mean climatological river runoff, and (d) high spatial (0.5° × 0.5°) and temporal (hourly) model outputs. Since the CFSR will be used by many in initializing/validating ocean models and climate research, the primary motivation of the paper is to inform the user community about the saline features in the CFSR ocean component, and how the ocean reanalysis compares with in situ observations and previous reanalysis. The net ocean surface heat flux of the CFSR has smaller biases compared to the sum of the latent and sensible heat fluxes from the objectively analyzed air-sea fluxes (OAFlux) and the shortwave and longwave radiation fluxes from the International Satellite Cloud Climatology Project (ISCCP-FD) than the NCEP/NCAR reanalysis (R1) and NCEP/DOE reanalysis (R2) in both the tropics and extratropics. The ocean surface wind stress of the CFSR has smaller biases and higher correlation with the ERA40 produced by the European Centre for Medium-Range Weather Forecasts than the R1 and R2, particularly in the tropical Indian and Pacific Ocean. The CFSR also has smaller errors compared to the QuickSCAT climatology for September 1999 to October 2009 than the R1 and R2. However, the trade winds of the CFSR in the central equatorial Pacific are too strong prior to 1999, and become close to observations once the ATOVS radiance data are assimilated in late 1998. A sudden reduction of easterly wind bias is related to the sudden onset of a warm bias in the eastern equatorial Pacific temperature around 1998/1999. The sea surface height and top 300 m heat content (HC300) of the CFSR compare with observations better than the GODAS in the tropical Indian Ocean and extratropics, but much worse in the tropical Atlantic, probably due to discontinuity in the deep ocean temperature and salinity caused by the six data streams of the CFSR. In terms of climate variability, the CFSR provides a good simulation of tropical instability waves and oceanic Kelvin waves in the tropical Pacific, and the dominant modes of HC300 that are associated with El Nino and Southern Oscillation, Indian Ocean Dipole, Pacific Decadal Oscillation and Atlantic Meridional Overturning Circulation. [ABSTRACT FROM AUTHOR]

The CNRM atmospheric general circulation model Arpege-Climat is relaxed towards atmospheric reanalyses outside the 10°S-32°N 30°W-50°E domain in order to disentangle the regional versus large-scale sources of climatological biases and interannual variability of the West African monsoon (WAM). On the one hand, the main climatological features of the monsoon, including the spatial distribution of summer precipitation, are only weakly improved by the nudging, thereby suggesting the regional origin of the Arpege-Climat biases. On the other hand, the nudging technique is relatively efficient to control the interannual variability of the WAM dynamics, though the impact on rainfall variability is less clear. Additional sensitivity experiments focusing on the strong 1994 summer monsoon suggest that the weak sensitivity of the model biases is not an artifact of the nudging design, but the evidence that regional physical processes are the main limiting factors for a realistic simulation of monsoon circulation and precipitation in the Arpege-Climat model. Sensitivity experiments to soil moisture boundary conditions are also conducted and highlight the relevance of land-atmosphere coupling for the amplification of precipitation biases. Nevertheless, the land surface hydrology is not the main explanation for the model errors that are rather due to deficiencies in the atmospheric physics. The intraseasonal timescale and the model internal variability are discussed in a companion paper. [ABSTRACT FROM AUTHOR]

This paper analyzes surface climate variability in the climate forecast system reanalysis (CFSR) recently completed at the National Centers for Environmental Prediction (NCEP). The CFSR represents a new generation of reanalysis effort with first guess from a coupled atmosphere-ocean-sea ice-land forecast system. This study focuses on the analysis of climate variability for a set of surface variables including precipitation, surface air 2-m temperature (T2m), and surface heat fluxes. None of these quantities are assimilated directly and thus an assessment of their variability provides an independent measure of the accuracy. The CFSR is compared with observational estimates and three previous reanalyses (the NCEP/NCAR reanalysis or R1, the NCEP/DOE reanalysis or R2, and the ERA40 produced by the European Centre for Medium-Range Weather Forecasts). The CFSR has improved time-mean precipitation distribution over various regions compared to the three previous reanalyses, leading to a better representation of freshwater flux (evaporation minus precipitation). For interannual variability, the CFSR shows improved precipitation correlation with observations over the Indian Ocean, Maritime Continent, and western Pacific. The T2m of the CFSR is superior to R1 and R2 with more realistic interannual variability and long-term trend. On the other hand, the CFSR overestimates downward solar radiation flux over the tropical Western Hemisphere warm pool, consistent with a negative cloudiness bias and a positive sea surface temperature bias. Meanwhile, the evaporative latent heat flux in CFSR appears to be larger than other observational estimates over most of the globe. A few deficiencies in the long-term variations are identified in the CFSR. Firstly, dramatic changes are found around 1998-2001 in the global average of a number of variables, possibly related to the changes in the assimilated satellite observations. Secondly, the use of multiple streams for the CFSR induces spurious jumps in soil moisture between adjacent streams. Thirdly, there is an inconsistency in long-term sea ice extent variations over the Arctic regions between the CFSR and other observations with the CFSR showing smaller sea ice extent before 1997 and larger extent starting in 1997. These deficiencies may have impacts on the application of the CFSR for climate diagnoses and predictions. Relationships between surface heat fluxes and SST tendency and between SST and precipitation are analyzed and compared with observational estimates and other reanalyses. Global mean fields of surface heat and water fluxes together with radiation fluxes at the top of the atmosphere are documented and presented over the entire globe, and for the ocean and land separately. [ABSTRACT FROM AUTHOR]

In this paper, lead-time and spatial dependence in skill for prediction of monthly mean climate variability is analyzed. The analysis is based on a set of extensive hindcasts from the Climate Forecast System at the National Centers for Environmental Prediction. The skill characteristics of initialized predictions is also compared with the AMIP simulations forced with the observed sea surface temperature (SST) to quantify the role of initial versus boundary conditions in the prediction of monthly means. The analysis is for prediction of monthly mean SST, precipitation, and 200-hPa height. The results show a rapid decay in skill with lead time for the atmospheric variables in the extratropical latitudes. Further, after a lead-time of approximately 30-40 days, the skill of monthly mean prediction is essentially a boundary forced problem, with SST anomalies in the tropical central/eastern Pacific playing a dominant role. Because of the larger contribution from the atmospheric internal variability to monthly time-averages (compared to seasonal averages), skill for monthly mean prediction associated with boundary forcing is also lower. The analysis indicates that the prospects of skillful prediction of monthly means may remain a challenging problem, and may be limited by inherent limits in predictability. [ABSTRACT FROM AUTHOR]

The main goal of this paper is to shed additional light on the reciprocal dynamical linkages between mid-latitude Southern Hemisphere climate and the El Niño-Southern Oscillation (ENSO) signal. While our analysis confirms that ENSO is a dominant source of interannual variability in the Southern Hemisphere, it is also suggested here that subtropical dipole variability in both the Southern Indian and Atlantic Oceans triggered by Southern Hemisphere mid-latitude variability may also provide a controlling influence on ENSO in the equatorial Pacific. This subtropical forcing operates through various coupled air-sea feedbacks involving the propagation of subtropical sea surface temperature (SST) anomalies into the deep tropics of the Atlantic and Indian Oceans from boreal winter to boreal spring and a subsequent dynamical atmospheric response to these SST anomalies linking the three tropical basins at the beginning of the boreal spring. This atmospheric response is characterized by a significant weakening of the equatorial Atlantic and Indian Inter-Tropical Convergence Zone (ITCZ). This weakened ITCZ forces an equatorial 'cold Kelvin wave' response in the middle to upper troposphere that extends eastward from the heat sink regions into the western Pacific. By modulating the vertical temperature gradient and the stability of the atmosphere over the equatorial western Pacific Ocean, this Kelvin wave response promotes persistent zonal wind and convective anomalies over the western equatorial Pacific, which may trigger El Niño onset at the end of the boreal winter. These different processes explain why South Atlantic and Indian subtropical dipole time series indices are highly significant precursors of the Niño34 SST index several months in advance before the El Niño onset in the equatorial Pacific. This study illustrates that the atmospheric internal variability in the mid-latitudes of the Southern Hemisphere may significantly influence ENSO variability. However, this surprising relationship is observed only during recent decades, after the so-called 1976/1977 climate regime shift, suggesting a possible linkage with global warming or decadal fluctuations of the climate system. [ABSTRACT FROM AUTHOR]

The accurate representation of rainfall in models of global climate has been a challenging task for climate modelers owing to its small space and time scales. Quantifying this variability is important for comparing simulations of atmospheric behavior with real time observations. In this regard, this paper compares both the statistical and dynamically forced aspects of precipitation variability simulated by the high-resolution (36 km) Nested Regional Climate Model (NRCM), with satellite observations from the Tropical Rainfall Measuring Mission (TRMM) 3B42 dataset and simulations from the Community Atmosphere Model (CAM) at T85 spatial resolution. Six years of rainfall rate data (2000-2005) from within the Tropics (30°S-30°N) have been used in the analysis and results are presented in terms of long-term mean rain rates, amplitude and phase of the annual cycle and seasonal mean maps of precipitation. Our primary focus is on characterizing the annual cycle of rainfall over four land regions of the Tropics namely, the Indian Monsoon, the Amazon, Tropical Africa and the North American monsoon. The lower tropospheric circulation patterns are analyzed in both the observations and the models to identify possible causes for biases in the simulated precipitation. The 6-year mean precipitation simulated by both models show substantial biases throughout the global Tropics with NRCM/CAM systematically underestimating/overestimating rainfall almost everywhere. The seasonal march of rainfall across the equator, following the motion of the sun, is clearly seen in the harmonic vector maps. The timing of peak rainfall (phase) produced by NRCM is in closer agreement with the observations compared to CAM. However like the long-time mean, the magnitude of seasonal mean rainfall is greatly underestimated by NRCM throughout the Tropical land mass. Some of these regional biases can be attributed to erroneous circulation and moisture surpluses/deficits in the lower troposphere in both models. Overall, the results seem to indicate that employing a higher spatial resolution (36 km) does not significantly improve simulation of precipitation. We speculate that a combination of several physics parameterizations and lack of model tuning gives rise to the observed differences between NRCM and the observations. [ABSTRACT FROM AUTHOR]

The Andes Cordillera acts as regional 'Water Towers' for several countries and encompasses a wide range of ecosystems and climates. Several hydroclimatic changes have been described for portions of the Andes during recent years, including glacier retreat, negative precipitation trends, an elevation rise in the 0° isotherm, and changes in regional streamflow regimes. The Temperate-Mediterranean transition (TMT) zone of the Andes (35.5°-39.5°S) is particularly at risk to climate change because it is a biodiversity hotspot with heavy human population pressure on water resources. In this paper we utilize a new tree-ring network of Austrocedrus chilensis to reconstruct past variations in regional moisture in the TMT of the Andes by means of the Palmer Drought Severity Index (PDSI). The reconstruction covers the past 657 years and captures interannual to decadal scales of variability in late spring-early summer PDSI. These changes are related to the north-south oscillations in moisture conditions between the Mediterranean and Temperate climates of the Andes as a consequence of the latitudinal position of the storm tracks forced by large-scale circulation modes. Kernel estimation of occurrence rates reveals an unprecedented increment of severe and extreme drought events during the last century in the context of the previous six centuries. Moisture conditions in our study region are linked to tropical and high-latitude ocean-atmospheric forcing, with PDSI positively related to Niño-3.4 SST during spring and strongly negatively correlated with the Antarctic Oscillation (AAO) during summer. Geopotential anomaly maps at 500-hPa show that extreme dry years are tightly associated with negative height anomalies in the Ross-Amundsen Seas, in concordance with the strong negative relationship between PDSI and AAO. The twentieth century increase in extreme drought events in the TMT may not be related to ENSO but to the positive AAO trend during late-spring and summer resulting from a gradual poleward shift of the mid-latitude storm tracks. This first PDSI reconstruction for South America demonstrates the highly significant hindcast skill of A. chilensis as an aridity proxy. [ABSTRACT FROM AUTHOR]

In this paper we use a coupled ocean-atmosphere model to investigate the impact of the interruption of Agulhas leakage of Indian ocean water on the tropical Atlantic, a region where strong coupled ocean-atmosphere interactions occur. The effect of a shut down of leakage of Indian ocean water is isolated from the effect of a collapse of the MOC. In our experiments, the ocean model is forced with boundary conditions in the southeastern corner of the domain that correspond to no interocean exchange of Indian ocean water into the Atlantic. The southern boundary condition is taken from the Levitus data and ensures an MOC in the Atlantic. Within this configuration, instead of warm and salty Indian ocean water temperature (cold) and salinity (fresh) anomalies of southern ocean origin propagate into the South Atlantic and eventually reach the equatorial region, mainly in the thermocline. This set up mimics the closure of the 'warm water path' in favor of the 'cold water path'. As part of the atmospheric response, there is a northward shift of the intertropical convergence zone (ITCZ). The changes in trade winds lead to reduced Ekman pumping in the equatorial region. This leads to a freshening and warming of the surface waters along the equator. Especially in the Cold Tongue region, the cold and fresh subsurface anomalies do not reach the surface due to the reduced upwelling. The anomaly signals are transported by the equatorial undercurrent and spread away from the equator within the thermocline. Part of the anomaly eventually reaches the Tropical North Atlantic, where it affects the Guinea Dome. Surprisingly, the main effect at the surface is small on the equator and relatively large at the Guinea Dome. In the atmosphere, the northward shift of the ITCZ is associated with a band of negative precipitation anomalies and higher salinities over the Tropical South Atlantic. An important implication of these results is that the modified water characteristics due to a shut down of the Agulhas leakage remain largely unaffected when crossing the equatorial Atlantic and therefore can affect the deepwater formation in the North Atlantic. This supports the hypothesis that the Agulhas leakage is an important source region for climate change and decadal variability of the Atlantic. [ABSTRACT FROM AUTHOR]

This paper reports on a method using composites for studying synoptic conditions of a series of windstorm events selected on the basis of maximum wind speeds in Switzerland. The composite storm-averaged conditions indicate how flow fields, as well as related surface conditions, are organised so as to produce high wind speeds near the surface. On average, high winds in Switzerland, mainly generated by transient synoptic-scale eddies, are characterised by a minimum in the mean sea level pressure field over southern Norway, anticyclonic conditions south of 35°N and a steep pressure gradient over continental western Europe. The geopotential aloft has a predominant zonal structure, producing high winds between 45°N and 50°N over the eastern Atlantic and further inland; the jet stream has its maximum speed at 50°N over the Celtic Sea and Brittany at 250 hPa. Close to the surface, large temperature contrasts between the warm waters of the Atlantic Ocean and Mediterranean Sea and the cooler continent are diagnosed. The results thus obtained differ to those produced by other methods based on the analysis of deep cyclones or of strong vorticity in the northern North Atlantic Ocean basin. Differences of the composite mean synoptic conditions for current (1961-1990) and future climate (2071-2100) as simulated by the Global Climate Model HadAM3H in the context of the EU PRUDENCE project indicate that windstorms in a warmer world are generated by a subtle modification of the atmospheric baroclinicity, especially over the ocean and where greater ocean-continent temperature contrasts are simulated during winters. However, there are no signs of reduced storm activity as the climate warms by the end of the twenty-first century. [ABSTRACT FROM AUTHOR]

This paper describes atmospheric general circulation model climate change experiments in which the Arctic sea-ice thickness is either fixed to 3 m or somewhat more realistically parameterized in order to take into account essentially the spatial variability of Arctic sea-ice thickness, which is, to a first approximation, a function of ice type (perennial or seasonal). It is shown that, both at present and at the end of the twenty-first century (under the SRES-A1B greenhouse gas scenario), the impact of a variable sea-ice thickness compared to a uniform value is essentially limited to the cold seasons and the lower troposphere. However, because first-year ice is scarce in the Central Arctic today, but not under SRES-A1B conditions at the end of the twenty-first century, and because the impact of a sea-ice thickness reduction can be masked by changes of the open water fraction, the spatial and temporal patterns of the effect of sea-ice thinning on the atmosphere differ between the two periods considered. As a consequence, not only the climate simulated at a given period, but also the simulated Arctic climate change over the twenty-first century is affected by the way sea-ice thickness is prescribed. [ABSTRACT FROM AUTHOR]

Recent studies have shown that changes in global mean precipitation are larger for solar forcing than for CO2 forcing of similar magnitude. In this paper, we use an atmospheric general circulation model to show that the differences originate from differing fast responses of the climate system. We estimate the adjusted radiative forcing and fast response using Hansen’s “fixed-SST forcing” method. Total climate system response is calculated using mixed layer simulations using the same model. Our analysis shows that the fast response is almost 40% of the total response for few key variables like precipitation and evaporation. We further demonstrate that the hydrologic sensitivity, defined as the change in global mean precipitation per unit warming, is the same for the two forcings when the fast responses are excluded from the definition of hydrologic sensitivity, suggesting that the slow response (feedback) of the hydrological cycle is independent of the forcing mechanism. Based on our results, we recommend that the fast and slow response be compared separately in multi-model intercomparisons to discover and understand robust responses in hydrologic cycle. The significance of this study to geoengineering is discussed. [ABSTRACT FROM AUTHOR]

This paper introduces an original method for climate change detection, called temporal optimal detection method. The method consists in searching for a smooth temporal pattern in the observations. This pattern can be either the response of the climate system to a specific forcing or to a combination of forcings. Many characteristics of this new method are different from those of the classical “optimal fingerprint” method. It allows to infer the spatial distribution of the detected signal, without providing any spatial guess pattern. The spatial properties of the internal climate variability doesn’t need to be estimated either. The estimation of such quantities being very challenging at regional scale, the proposed method is particularly well-suited for such scale. The efficiency of the method is illustrated by applying it on real homogenized datasets of temperatures and precipitation over France. A multimodel detection is performed in both cases, using an ensemble of atmosphere-ocean general circulation models for estimating the temporal patterns. Regarding temperatures, new results are highlighted, especially by showing that a change is detected even after removing the uniform part of the warming. The sensitivity of the method is discussed in this case, relatively to the computation of the temporal patterns and to the choice of the model. The method also allows to detect a climate change signal in precipitation. This change impacts the spatial distribution of the precipitation more than the mean over the domain. The ability of the method to provide an estimate of the spatial distribution of the change following the prescribed temporal patterns is also illustrated. [ABSTRACT FROM AUTHOR]

A number of general circulation model studies have assessed the impact of degradation of the land surface in the Sahel, mostly with idealized degradation scenarios. This paper builds on the previous research by testing the sensitivity of Mesoscale Convective Systems (MCS) and associated rainfall amounts to observed vegetation changes using a regional atmospheric model. Over the last 20 years, the vegetation in the Sahel has recovered from the drought in the 1980s and vegetation cover values have increased up to 20%. The sensitivity for both a vegetation increase and a decrease by these realistic amounts is investigated. The model simulations span 42 days of the rainy season and are centred over the region of the Hydrological and Atmospheric Pilot Experiment in the Sahel (HAPEX-Sahel), of which the data are used to evaluate model results. The model is able to correctly reproduce rainfall amounts and atmospheric profiles. Total precipitation is found to be insensitive to the applied vegetation changes, but the latter do have an impact on the rainfall patterns and the location of MCS. The model results indicate that the change in vegetation cover influences the MCS in two different ways: Firstly, the vegetation change is found to affect the surface fluxes and this in turn is found to affect the Convective Available Potential Energy (CAPE) and thereby the strength of the convective systems. The relation between vegetation cover and CAPE turns out to be affected by the time in-between precipitation events. Secondly, a change in atmospheric dynamics, especially the mid-tropospheric zonal flow, is modelled as response to a change in the spatial temperature and humidity distribution. Both mechanisms are likely to play a role in determining the characteristics of the rainfall pattern. [ABSTRACT FROM AUTHOR]

Differences in the radiative feedback from clouds account for much of the variation in climate sensitivity amongst General Circulation Models (GCMs). Therefore metrics of model performance which are demonstrated to be relevant to the cloud response to climate change form an important contribution to the overall evaluation of GCMs. In this paper we demonstrate an alternative method for assigning model data to observed cloud regimes obtained from clustering histograms of cloud amount in joint cloud optical depth—cloud top pressure classes. The method removes some of the subjectivity that exists in previous GCM cloud clustering studies. We apply the method to ten GCMs submitted to the Cloud Feedback Model Intercomparison Project (CFMIP), evaluate the simulated cloud regimes and analyse the climate change response in the context of these regimes. We also propose two cloud regime metrics, one of which is specifically targeted at assessing GCMs for the purpose of obtaining the global cloud radiative response to climate change. Most of the global variance in the cloud radiative response between GCMs is due to low clouds, with 47% arising from the stratocumulus regime and 18% due to the regime characterised by clouds undergoing transition from stratocumulus to cumulus. This result is found to be dominated by two structurally similar GCMs. The shallow cumulus regime, though widespread, has a smaller contribution and reduces the variance. For the stratocumulus and transition regimes, part of the variance results from a large model spread in the radiative properties of the regime in the control simulation. Comparison with observations reveals a systematic bias for both the stratocumulus and transition regimes to be overly reflective. If this bias was corrected with all other aspects of the response unchanged, the variance in the low cloud response would reduce. The response of some regimes with high cloud tops differ between the GCMs. These regimes are simulated too infrequently in a few of the models. If the frequency in the control simulation were more realistic and changes within the regimes were unaltered, the variance in the cloud radiative response from high-top clouds would increase. As a result, use of observations of the mean present-day cloud regimes suggests that whilst improvements in the simulation of the cloud regimes would impact the climate sensitivity, the inter-model variance may not reduce. When the cloud regime metric is calculated for the GCMs analysed here, only one model is on average consistent with observations within their uncertainty (and even this model is not consistent with the observations for all regimes), indicating scope for improvement in the simulation of cloud regimes. [ABSTRACT FROM AUTHOR]

Results from multiple model simulations are used to understand the tropical sea surface temperature (SST) response to the reduced greenhouse gas concentrations and large continental ice sheets of the last glacial maximum (LGM). We present LGM simulations from the Paleoclimate Modelling Intercomparison Project, Phase 2 (PMIP2) and compare these simulations to proxy data collated and harmonized within the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface Project (MARGO). Five atmosphere–ocean coupled climate models (AOGCMs) and one coupled model of intermediate complexity have PMIP2 ocean results available for LGM. The models give a range of tropical (defined for this paper as 15°S–15°N) SST cooling of 1.0–2.4°C, comparable to the MARGO estimate of annual cooling of 1.7 ± 1°C. The models simulate greater SST cooling in the tropical Atlantic than tropical Pacific, but interbasin and intrabasin variations of cooling are much smaller than those found in the MARGO reconstruction. The simulated tropical coolings are relatively insensitive to season, a feature also present in the MARGO transferred-based estimates calculated from planktonic foraminiferal assemblages for the Indian and Pacific Oceans. These assemblages indicate seasonality in cooling in the Atlantic basin, with greater cooling in northern summer than northern winter, not captured by the model simulations. Biases in the simulations of the tropical upwelling and thermocline found in the preindustrial control simulations remain for the LGM simulations and are partly responsible for the more homogeneous spatial and temporal LGM tropical cooling simulated by the models. The PMIP2 LGM simulations give estimates for the climate sensitivity parameter of 0.67°–0.83°C per Wm−2, which translates to equilibrium climate sensitivity for doubling of atmospheric CO2 of 2.6–3.1°C. [ABSTRACT FROM AUTHOR]

This paper analyzes the spatial dependence of annual diurnal temperature range (DTR) trends from 1950–2004 on the annual climatology of three variables: precipitation, cloud cover, and leaf area index (LAI), by classifying the global land into various climatic regions based on the climatological annual precipitation. The regional average trends for annual minimum temperature ( T min) and DTR exhibit significant spatial correlations with the climatological values of these three variables, while such correlation for annual maximum temperature ( T max) is very weak. In general, the magnitude of the downward trend of DTR and the warming trend of T min decreases with increasing precipitation amount, cloud cover, and LAI, i.e., with stronger DTR decreasing trends over drier regions. Such spatial dependence of T min and DTR trends on the climatological precipitation possibly reflects large-scale effects of increased global greenhouse gases and aerosols (and associated changes in cloudiness, soil moisture, and water vapor) during the later half of the twentieth century. [ABSTRACT FROM AUTHOR]

In climate science, an anomaly is the deviation of a quantity from its annual cycle. There are many ways to define annual cycle. Traditionally, this annual cycle is taken to be an exact repeat of itself year after year. This stationary annual cycle may not reflect well the intrinsic nonlinearity of the climate system, especially under external forcing. In this paper, we re-examine the reference frame for anomalies by re-examining the annual cycle. We propose an alternative reference frame for climate anomalies, the modulated annual cycle (MAC) that allows the annual cycle to change from year to year, for defining anomalies. In order for this alternative reference frame to be useful, we need to be able to define the instantaneous annual cycle: we therefore also introduce a new method to extract the MAC from climatic data. In the presence of a MAC, modulated in both amplitude and frequency, we can then define an alternative version of an anomaly, this time with respect to the instantaneous MAC rather than a permanent and unchanging AC. Based on this alternative definition of anomalies, we re-examine some familiar physical processes: in particular SST re-emergence and ENSO phase locking to the annual cycle. We find that the re-emergence mechanism may be alternatively interpreted as an explanation of the change of the annual cycle instead of an explanation of the interannual to interdecadal persistence of SST anomalies. We also find that the ENSO phase locking can largely be attributed to the residual annual cycle (the difference of the MAC and the corresponding traditional annual cycle) contained in the traditional anomaly, and, therefore, can be alternatively interpreted as a part of the annual cycle phase locked to the annual cycle itself. In addition to the examples of reinterpretation of physics of well known climate phenomena, we also present an example of the implications of using a MAC against which to define anomalies. We show that using MAC as a reference framework for anomaly can bypass the difficulty brought by concepts such as “decadal variability of summer (or winter) climate” for understanding the low-frequency variability of the climate system. The concept of an amplitude and frequency modulated annual cycle, a method to extract it, and its implications for the interpretation of physical processes, all may contribute potentially to a more consistent and fruitful way of examining past and future climate variability and change. [ABSTRACT FROM AUTHOR]

Climate changes affect the abundance, geographic extent, and floral composition of vegetation, which are reflected in the pollen rain. Sediment cores taken from lakes and peat bogs can be analysed for their pollen content. The fossil pollen records provide information on the temporal changes in climate and palaeo-environments. Although the complexity of the variables influencing vegetation distribution requires a multi-dimensional approach, only a few research projects have used GIS to analyse pollen data. This paper presents a new approach to palynological data analysis by combining GIS and spatial modelling. Eastern Colombia was chosen as a study area owing to the migration of the forest–savanna boundary since the last glacial maximum, and the availability of pollen records. Logistic regression has been used to identify the climatic variables that determine the distribution of savanna and forest in eastern Colombia. These variables were used to create a predictive land-cover model, which was subsequently implemented into a GIS to perform spatial analysis on the results. The palynological data from the study area were incorporated into the GIS. Reconstructed maps of past vegetation distribution by interpolation showed a new approach of regional multi-site data synthesis related to climatic parameters. The logistic regression model resulted in a map with 85.7% predictive accuracy, which is considered useful for the reconstruction of future and past land-cover distributions. The suitability of palynological GIS application depends on the number of pollen sites, the distribution of the pollen sites over the area of interest, and the degree of overlap of the age ranges of the pollen records. [ABSTRACT FROM AUTHOR]

The radiative feedback from clouds remains the largest source of variation in climate sensitivity amongst general circulation models (GCMs). A cloud clustering methodology is applied to six contemporary GCMs in order to provide a detailed intercomparison and evaluation of the simulated cloud regimes. By analysing GCMs in the context of cloud regimes, processes related to particular cloud types are more likely to be evaluated. In this paper, the mean properties of the global cloud regimes are evaluated, and the cloud response to climate change is analysed in the cloud-regime framework. Most of the GCMs are able to simulate the principal cloud regimes, however none of the models analysed have a good representation of trade cumulus in the tropics. The models also share a difficulty in simulating those regimes with cloud tops at mid-levels, with only ECHAM5 producing a regime of tropical cumulus congestus. Optically thick, high top cloud in the extra-tropics, typically associated with the passage of frontal systems, is simulated considerably too frequently in the ECHAM5 model. This appears to be a result of the cloud type persisting in the model after the meteorological conditions associated with frontal systems have ceased. The simulation of stratocumulus in the MIROC GCMs is too extensive, resulting in the tropics being too reflective. Most of the global-mean cloud response to doubled CO2 in the GCMs is found to be a result of changes in the cloud radiative properties of the regimes, rather than changes in the relative frequency of occurrence (RFO) of the regimes. Most of the variance in the global cloud response between the GCMs arises from differences in the radiative response of frontal cloud in the extra-tropics and from stratocumulus cloud in the tropics. This variance is largely the result of excessively high RFOs of specific regimes in particular GCMs. It is shown here that evaluation and subsequent improvement in the simulation of the present-day regime properties has the potential to reduce the variance of the global cloud response, and hence climate sensitivity, amongst GCMs. For the ensemble of models considered in this study, the use of observations of the mean present-day cloud regimes suggests a potential reduction in the range of climate sensitivity of almost a third. [ABSTRACT FROM AUTHOR]

This paper analyzes the soil–atmosphere feedbacks and uncertainties under current (1960–1990) and plausible future climate conditions (2070–2100, using the A2 greenhouse gases emission scenario). For this purpose, two vegetation descriptions differing only in the grassland and grass-with-trees proportion in some parts of the domain have been created. The combination of these two different climate scenarios and two vegetation descriptions defines four different 30-year experiments, which have been completed using a regional climate model. The domain is centered around the Mediterranean basin and covers most of Europe. The study focuses on the summer season when there are major differences between the two vegetation descriptions and when the impact of land–surface processes on precipitation is largest. Present climate experiments show large evapotranspiration differences over areas where vegetation changes have taken place. Precipitation increases (up to 3 mm day−1 in some regions) follow evapotranspiration increases, although with a more complex spatial structure. These results indicate a high sensitivity at regional scales of summer precipitation processes to vegetation changes. Future climate simulations show very similar changes to those observed in the current climate experiments. This indicates that the impacts of climate change are relatively independent to the land-cover descriptions used in this study. [ABSTRACT FROM AUTHOR]

The aim of this work is to assess potential future Antarctic surface mass balance changes, the underlying mechanisms, and the impact of these changes on global sea level. To this end, this paper presents simulations of the Antarctic climate for the end of the twentieth and twenty-first centuries. The simulations were carried out with a stretched-grid atmospheric general circulation model, allowing for high horizontal resolution (60 km) over Antarctica. It is found that the simulated present-day surface mass balance is skilful on continental scales. Errors on regional scales are moderate when observed sea surface conditions are used; more significant regional biases appear when sea surface conditions from a coupled model run are prescribed. The simulated Antarctic surface mass balance increases by 32 mm water equivalent per year in the next century, corresponding to a sea level decrease of 1.2 mm year−1 by the end of the twenty-first century. This surface mass balance increase is largely due to precipitation changes, while changes in snow melt and turbulent latent surface fluxes are weak. The temperature increase leads to an increased moisture transport towards the interior of the continent because of the higher moisture holding capacity of warmer air, but changes in atmospheric dynamics, in particular off the Antarctic coast, regionally modulate this signal. [ABSTRACT FROM AUTHOR]

Evaluating the response of climate to greenhouse gas forcing is a major objective of the climate community, and the use of large ensemble of simulations is considered as a significant step toward that goal. The present paper thus discusses a new methodology based on neural network to mix ensemble of climate model simulations. Our analysis consists of one simulation of seven Atmosphere–Ocean Global Climate Models, which participated in the IPCC Project and provided at least one simulation for the twentieth century (20c3m) and one simulation for each of three SRES scenarios: A2, A1B and B1. Our statistical method based on neural networks and Bayesian statistics computes a transfer function between models and observations. Such a transfer function was then used to project future conditions and to derive what we would call the optimal ensemble combination for twenty-first century climate change projections. Our approach is therefore based on one statement and one hypothesis. The statement is that an optimal ensemble projection should be built by giving larger weights to models, which have more skill in representing present climate conditions. The hypothesis is that our method based on neural network is actually weighting the models that way. While the statement is actually an open question, which answer may vary according to the region or climate signal under study, our results demonstrate that the neural network approach indeed allows to weighting models according to their skills. As such, our method is an improvement of existing Bayesian methods developed to mix ensembles of simulations. However, the general low skill of climate models in simulating precipitation mean climatology implies that the final projection maps (whatever the method used to compute them) may significantly change in the future as models improve. Therefore, the projection results for late twenty-first century conditions are presented as possible projections based on the “state-of-the-art” of present climate modeling. First, various criteria were computed making it possible to evaluate the models’ skills in simulating late twentieth century precipitation over continental areas as well as their divergence in projecting climate change conditions. Despite the relatively poor skill of most of the climate models in simulating present-day large scale precipitation patterns, we identified two types of models: the climate models with moderate-to-normal (i.e., close to observations) precipitation amplitudes over the Amazonian basin; and the climate models with a low precipitation in that region and too high a precipitation on the equatorial Pacific coast. Under SRES A2 greenhouse gas forcing, the neural network simulates an increase in precipitation over the La Plata basin coherent with the mean model ensemble projection. Over the Amazonian basin, a decrease in precipitation is projected. However, the models strongly diverge, and the neural network was found to give more weight to models, which better simulate present-day climate conditions. In the southern tip of the continent, the models poorly simulate present-day climate. However, they display a fairly good convergence when simulating climate change response with a weak increase south of 45°S and a decrease in Chile between 30 and 45°S. Other scenarios (A1B and B1) strongly resemble the SRES A2 trends but with weaker amplitudes. [ABSTRACT FROM AUTHOR]

The CSIRO Mark 2 coupled global climatic model has been used to generate a 10,000-year simulation for ‘present’ climatic conditions. The model output has been analysed to identify sustained climatic fluctuations, such as those attributed to the Medieval Warm Period (MWP) and the Little Ice Age (LIA). Since no external forcing was permitted during the model run all such fluctuations are attributed to naturally occurring climatic variability associated with the nonlinear processes inherent in the climatic system. Comparison of simulated climatic time series for different geographical locations highlighted the lack of synchronicity between these series. The model was found to be able to simulate climatic extremes for selected observations for century timescales, as well as identifying the associated spatial characteristics. Other examples of time series simulated by the model for the USA and eastern Russia had similar characteristics to those attributed to the MWP and the LIA, but smaller amplitudes, and clearly defined spatial patterns. A search for the frequency of occurrence of specified surface temperature anomalies, defined via duration and mean value, revealed that these were primarily confined to polar regions and northern latitudes of Europe, Asia and North America. Over the majority of the oceans and southern hemisphere such climatic fluctuations could not be sustained, for reasons explained in the paper. Similarly, sustained sea–ice anomalies were mainly confined to the northern hemisphere. An examination of mechanisms associated with the sustained climatic fluctuations failed to identify a role for the North Atlantic Oscillation, the El Niño-Southern Oscillation or the Pacific Decadal Oscillation. It was therefore concluded that these fluctuations were generated by stochastic processes intrinsic to the nonlinear climatic system. While a number of characteristics of the MWP and the LIA could have been partially caused by natural processes within the climatic system, the inability of the model to reproduce the observed hemispheric mean temperature anomalies associated with these events indicates that external forcing must have been involved. Essentially the unforced climatic system is unable to sustain the generation of long-term climatic anomalies. [ABSTRACT FROM AUTHOR]

In this paper we present results of a numerical study using the NASA finite-volume GCM to elucidate a plausible mechanism for aerosol impact on the Asian summer monsoon involving interaction with physical processes over the Tibetan Plateau (TP). During the pre-monsoon season of March–April, dusts from the deserts of western China, Afghanistan/Pakistan, and the Middle East are transported into and stacked up against the northern and southern slopes of the TP. The absorption of solar radiation by dust heats up the elevated surface air over the slopes. On the southern slopes, the atmospheric heating is reinforced by black carbon from local emission. The heated air rises via dry convection, creating a positive temperature anomaly in the mid-to-upper troposphere over the TP relative to the region to the south. In May through early June in a manner akin to an “elevated heat pump”, the rising hot air forced by the increasing heating in the upper troposphere, draws in warm and moist air over the Indian subcontinent, setting the stage for the onset of the South Asia summer monsoon. Our results suggest that increased dust loading coupled with black carbon emission from local sources in northern India during late spring may lead to an advance of the rainy periods and subsequently an intensification of the Indian summer monsoon. The enhanced rainfall over India is associated with the development of an aerosol-induced large-scale sea level pressure anomaly pattern, which causes the East Asia ( Mei-yu) rain belt to shift northwestward, suppressing rainfall over East Asia and the adjacent oceanic regions. [ABSTRACT FROM AUTHOR]

The Caspian Sea is the largest enclosed body of water on earth, covering approximately 4×105 km2 and sharing its coast with five countries (Iran, Azerbaijan, Kazakhstan, Russia and Turkmenistan). Because it has no outlet to the ocean the Caspian Sea level (CSL) has undergone rapid shifts in response to climatic forcings, and these have been devastating for the surrounding countries. In this paper we present the initial results of a modeling effort aimed at building a regional climate model for the Caspian Sea basin suitable to study the response of the CSL to interdecadal climate variability and anthropogenic climate change. Simulations are performed using the International Centre for Theoretical Physics (ICTP) regional climate model RegCM at a 50 km grid spacing for the period 1948–1990. During this period an abrupt shift occurred in the sea level after 1977, when the CSL rose about two meters until the early 1990s. Using a simple equation of hydrologic balance for the Caspian Sea basin to predict the CSL, we show that the model is able to reproduce the observed CSL changes at interannual to multidecadal scales. The correlation coefficient between the simulated and observed annual CSL changes is 0.91 and the model is able to reproduce the abrupt shift in CSL which occurred after 1977. Analysis of the climatologies before and after 1977 indicate that the CSL rise was mostly due to an increase in precipitation over the northern basin and a decrease in evaporation over the sea, primarily during the warm season. We plan to apply our model to the investigation of the response of the CSL to anthropogenic climate forcings. [ABSTRACT FROM AUTHOR]

There is considerable interest in the potential impact of climate change on the feasibility and predictability of renewable energy sources including wind energy. This paper presents dynamically downscaled near-surface wind fields and examines the impact of climate change on near-surface flow and hence wind energy density across northern Europe. It is shown that: Simulated wind fields from the Rossby Centre coupled Regional Climate Model (RCM) (RCAO) with boundary conditions derived from ECHAM4/OPYC3 AOGCM and the HadAM3H atmosphere-only GCM exhibit reasonable and realistic features as documented in reanalysis data products during the control period (1961–1990). The near-surface wind speeds calculated for a climate change projection period of 2071–2100 are higher than during the control run for two IPCC emission scenarios (A2, B2) for simulations conducted using boundary conditions from ECHAM4/OPYC3. The RCAO simulations conducted using boundary conditions from ECHAM4/OPYC3 indicate evidence for a small increase in the annual wind energy resource over northern Europe between the control run and climate change projection period and for more substantial increases in energy density during the winter season. However, the differences between the RCAO simulations for the climate projection period and the control run are of similar magnitude to differences between the RCAO fields in the control period and the NCEP/NCAR reanalysis data. Additionally, the simulations show a high degree of sensitivity to the boundary conditions, and simulations conducted using boundary conditions from HadAM3H exhibit evidence of slight declines or no change in wind speed and energy density between 1961–1990 and 2071–2100. Hence, the uncertainty of the projected wind changes is relatively high. [ABSTRACT FROM AUTHOR]

The Canadian Centre for Climate Modelling and Analysis (CCCma) global coupled model is used to investigate the potential climate effects of increasing greenhouse gas (GHG) concentrations and changes in sulfate aerosol loadings. The forcing scenario adopted closely resembles that of Mitchell et al. for both the greenhouse gas and aerosol components. Its implementation in the model and the resulting changes in forcing are described. Five simulations of 200 years in length, nominally for the years 1900 to 2100, are available for analysis. They consist of a control simulation without change in forcing, three independent simulations with the same greenhouse gas and aerosol changes, and a single simulation with greenhouse gas only forcing. Simulations of the evolution of temperature and precipitation from 1900 to the present are compared with available observations. Temperature and precipitation are primary climate variables with reasonable temporal and spatial coverage in the observational record for the period. The simulation of potential climate change from the present to the end of the twenty-first century, based on projected GHG and aerosol forcing changes, is discussed in a companion paper. For the historical period dealt with here, the GHG and aerosol forcing has changed relatively little compared to the forcing changes projected to the end of the twenty-first century. Nevertheless, the forced climate signal for temperature in the model is reasonably consistent with the observed global mean temperature from the instrumental record. This is true also for the trend in zonally averaged temperature as a function of latitude and for some aspects of the geographical and regional distributions of temperature. Despite the modest change in overall forcing, the difference between GHG+aerosol and GHG-only forcing is discernible in the temperature response for this period. Changes in precipitation, on the other hand, are much less evident in both the instrumental and simulated record. There is an apparent increasing trend in average precipitation in both the observations and the model results over that part of the land for which observations are available. Regional and geographical changes and trends (which are less affected by sampling considerations), if they exist, are masked by the large natural variability of precipitation in both model and observations. [ABSTRACT FROM AUTHOR]

This study looks at the evolution of trends in the dynamic sea level (DSL) component of sea-level rise for the North Atlantic (18°–67° N), primarily over the twenty-first century but with some analysis extending to 2300. We use an 18-member climate model ensemble of projections under medium and high greenhouse gas scenarios. We find that the long-term trend pattern (1950–2099) tends to be indicated in the early twenty-first century: 14 (11) of the 18 models have pattern correlations between this period and 1993–2022 of > 0.5 under the medium (high) greenhouse gas scenario. Whether a particular 1993–2022 DSL trend indicates the long-term trend in our ensemble can be assessed from concurrent changes in the Atlantic Meridional Overturning Circulation (AMOC) at 30° N: those cases with larger AMOC weakening trends have high DSL-trend pattern correlations. This suggests that the observed AMOC (or a proxy for that) could indicate whether observed DSL trends are likely to be a constraint on projections, provided suitable AMOC trend indicators can be determined. More generally, North Atlantic DSL and the AMOC show a similar evolution of measures of their successive 30-year trends (with these being projection-onto-a-pattern and the ratio with the long-term trend, respectively), both in the ensemble mean and for individual models. Model-to-model differences in this evolution indicate that the changing DSL and AMOC trends are more interconnected than solely the common influence of external forcings associated with the climate-change scenario. Model simulations extending to 2300 indicate that the twenty-first century trend patterns do not generally persist into subsequent centuries, as has been shown in previous studies. [ABSTRACT FROM AUTHOR]

Climate change is imminent and threatens the largest watershed in the world, the Amazon basin. As general circulation models may fail to represent cloud-scale phenomena, precipitation in a changing climate under global warming is still a factor of great uncertainty, especially in Tropical regions. In this study, we used long-term high-resolution simulations from a global cloud-resolving model under the scope of the Coupled Model Intercomparison Project (CMIP6) to verify the climate change impacts on the mesoscale convective systems (MCSs) over the Amazon basin. We generated a complete spatial, temporal, and statistical characterization of the MCSs for the past (1950–1960), present (2000–2010), and near-future (2040–2050). We found that MCSs are a critical mechanism for precipitation, especially in austral winter. The simulations are consistent with the observed precipitation and MCSs patterns over the Amazon basin, indicating that MCSs are less frequent compared to the past and are expected to continuously decline in the near-future. Most decreases are projected from September to December, while an increase between June to August, mainly in the southern portion of the Amazon basin. In addition, the investigation presented here shows the great potential of using a global cloud-resolving model under the CMIP6 scope to investigate mesoscale systems in a warming climate. [ABSTRACT FROM AUTHOR]