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A dense monitoring network is vital for the reliable assessment of PM10 in different parts of an urban area. In this study, a new idea is employed for the re-construction of the 20 shut-down PM10 monitoring stations of Berlin. It endeavours to find the non-linear relationship between the hourly PM10 concentration of both the still operating and the shut-down PM10 monitoring stations by using a fuzzy modelling technique, called modified active learning method (MALM). In addition, the simulations were performed by using not only raw PM10 databases but also log-transformed PM10 databases for skewness reduction. According to the results of hourly PM10 simulation (root mean square error about 13.0 μg/m3, correlation coefficient 0.88), the shut-down stations have been appropriately simulated and the idea of dense monitoring network development by the re-construction of the shut-down stations was realised. The results of simulations using raw and log-transformed databases showed that data transformation has no significant effect on the performance of MALM in the simulation of shut-down PM10 stations. By the combination of the 11 still operating stations and the 20 re-constructed stations, a dense monitoring network was generated for Berlin and was utilised for the calculation of the reliable monthly and mean annual PM10 concentration for five different PM10 zones in Berlin (the suburban-background, urban-background, urban-traffic, rural-background and suburban-traffic areas). The results showed that the mean annual concentration of PM10 at the five zones increased by about 13.0% in 2014 (26.3 μg/m3) in comparison with 2013 (23.3 μg/m3). Furthermore, the mean annual concentration of PM10 in the traffic lanes of the suburban (2013 25.0 μg/m3, 2014 26.9 μg/m3) and urban (2013 27.7 μg/m3, 2014 31.3 μg/m3) areas is about 14 and 20% higher than the PM10 concentration of suburban-background (2013 21.3 μg/m3, 2014 24.5 μg/m3) and urban-background (2013 23.0 μg/m3, 2014 26.1 μg/m3) areas, respectively.

Paleoclimate data assimilation (DA) is a promising technique to systematically combine the information from climate model simulations and proxy records. Here, we investigate the assimilation of tree-ring-width (TRW) chronologies into an atmospheric global climate model using ensemble Kalman filter (EnKF) techniques and a process-based tree-growth forward model as an observation operator. Our results, within a perfect-model experiment setting, indicate that the "online DA" approach did not outperform the "off-line" one, despite its considerable additional implementation complexity. On the other hand, it was observed that the nonlinear response of tree growth to surface temperature and soil moisture does deteriorate the operation of the time-averaged EnKF methodology. Moreover, for the first time we show that this skill loss appears significantly sensitive to the structure of the growth rate function, used to represent the principle of limiting factors (PLF) within the forward model. In general, our experiments showed that the error reduction achieved by assimilating pseudo-TRW chronologies is modulated by the magnitude of the yearly internal variability in the model. This result might help the dendrochronology community to optimize their sampling efforts.

Sudden stratospheric warming (SSW) events are identified to investigate their influence on the equatorial tropospheric climate. Composite analysis of warming events from Era-Interim (1979–2013) record a cooling of the tropical lower stratosphere with corresponding changes in the mean meridional stratospheric circulation. A cooling of the upper troposphere induces enhanced convective activity near the equatorial region of the Southern Hemisphere and suppressed convective activity in the off-equatorial Northern Hemisphere. After selecting vortex splits, the see-saw pattern of convective activity in the troposphere grows prominent and robust.

The development of the East African Rift System (EARS) caused by tectonic forcing during the past 20 million years is believed to influence the regional climate in Africa. However, changes in the Earth's orbital parameters also have an influence on climate on these timescales. To analyze the influence of both tectonic and orbital forcing, we applied the non-hydrostatic regional climate model COSMO-CLM (COSMO model in Climate Mode, CCLM). The regional simulations are driven by different global simulations performed with the coupled ocean–atmosphere general circulation model ECHO-G. To analyze the impact of tectonic forcing a different topography representing a possible past stage of the development of the EARS is applied in the model. The results indicate that tectonic forcing has a strong impact on precipitation in Africa caused by circulation changes. To analyze the impact of orbital forcing, which means the impact of changing insolation patterns, we chose configurations of the Earth's orbit that result in significantly different patterns of insolation. One example is the orbital configuration of the last interglacial at 125,000 years before present, when the seasonality of insolation in the Northern Hemisphere was greatly enhanced, whereas in the Southern Hemisphere it was substantially weakened compared to preindustrial conditions. The simulation of this time slice shows a strong impact of orbital forcing on precipitation in large parts of Africa, caused by altered moisture transport. The application of a biome model helps in analyzing the impact of the two forcing factors on vegetation for a more direct comparison with proxy data.

In the early 1980s, Germany started a new era of modern Antarctic research. The Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWI) was founded and important research platforms such as the German permanent station in Antarctica, today called Neumayer III, and the research icebreaker Polarstern were installed. The research primarily focused on the Atlantic sector of the Southern Ocean. In parallel, the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) started a priority program ‘Antarctic Research’ (since 2003 called SPP-1158) to foster and intensify the cooperation between scientists from different German universities and the AWI as well as other institutes involved in polar research. Here, we review the main findings in meteorology and oceanography of the last decade, funded by the priority program. The paper presents field observations and modelling efforts, extending from the stratosphere to the deep ocean. The research spans a large range of temporal and spatial scales, including the interaction of both climate components. In particular, radiative processes, the interaction of the changing ozone layer with large-scale atmospheric circulations, and changes in the sea ice cover are discussed. Climate and weather forecast models provide an insight into the water cycle and the climate change signals associated with synoptic cyclones. Investigations of the atmospheric boundary layer focus on the interaction between atmosphere, sea ice and ocean in the vicinity of polynyas and leads. The chapters dedicated to polar oceanography review the interaction between the ocean and ice shelves with regard to the freshwater input and discuss the changes in water mass characteristics, ventilation and formation rates, crucial for the deepest limb of the global, climate-relevant meridional overturning circulation. They also highlight the associated storage of anthropogenic carbon as well as the cycling of carbon, nutrients and trace metals in the ocean with special emphasis on the Weddell Sea. DFG/SPP/1158

Results from 3 ½-yr experimental program of extended-range integrations of the ECMWF numerical weather prediction model are summarized. The topics discussed include: 1) The evolution of extended-range systematic errors and skill in forecasting large-scale weather regime transitions ; 2) The dependence of extended-range systematic error and skill on model horizontal resolution ; 3) Monthly mean forecast of tropical rainfall ; 4) Tropical/extratropical interaction, and the influence of tropical low-frequency variability on extratropical forecast skill ; 5) Ensemble forecasting, including the impact of ensemble averaging on forecast skill, and ensemble dispersion as a measure of forecast reliability ; and 6) Probabilistic forecasting using phase-space cluster analysis. Our results are broadly consistent with those from other major centers evaluating the feasibility of dynamical extended-range prediction. We believe that operational extende-range forecasting using the ECMWF model may be viable to day 20 – and possibly beyond – following further research on techniques for Monte Carlo forecasting, and when model systematic error in the tropics has been reduced significantly.

A set of 16 ensembles of time-lagged extended-range forecasts have been run at different times of year using the T63 version of the ECMWF operational model. Each ensemble was composed of 9 integrations from consecutive 6-hourly analyses. Theoretical properties of ensemble-mean skill and ensemble spread are studied using a simple model of error growth with a parametrization of the ECMWF model error. The impact of systematic error on the potential improvement in skill of the ensemble-mean forecast is discussed. The presence of model errors considerably reduces the gain from ensemble averaging. In practice, about a third of the ensemble-mean forecasts, at forecast days 11-20, were more skilful than both persistence and climate, and, in addition, were more skilful than the latest member of the ensemble. At days 21-30. only one of the ensemble-mean forecasts was similarly skilful. Whilst there is an overall hemispheric scale correlation between ensemble spread and skill, a substantial part of this reflects the impact of the annual cycle on both quantities. In the winter period, however, no clear spread/skill correlation was found. Within the winter period, there was considerable case-to-case variability in forecast skill. Of all the ensembles that of January 1986 was poorest, whereas that of February 1986 was one of the best. The different character of these two ensembles was shown by considering phase-space trajectories of the ensemble forecasts in the plane spanned by the two principal forecast EOFs of 500mb height. During the first 15 days, the trajectories of the January ensemble forecasts were consistent with each other, but not with the observed atmospheric trajectory (which was associated with the onset of blocking over Europe). During the last 15 days, as the January ensemble forecasts migrated from positive to negative PNA index, the trajectories dispersed quite strongly, becoming disordered. By contrast, the trajectories of the February forecasts remained mutually consistent and in agreement with the real atmosphere’s trajectory throughout most ot the forecast period.

This article details a correction to the article: Illing S, Kadow C, Oliver K, Cubasch U. MurCSS: A Tool for Standardized Evaluation of Decadal Hindcast Systems. Journal of Open Research Software. 2014; 2(1): e24. DOI: http://doi.org/10.5334/jors.bf

A global atmosphere–ocean model has been forced with topographic and orbital scenarios in order to evaluate the relative role of both factors for the past climate of East Africa. Forcing the model with a significantly reduced topography in Eastern and Southern Africa leads to a distinct increase in moisture transport from the Indian Ocean into the eastern part of the continent and increased precipitation in Eastern Africa. Simulations with step-wise reduced height show that this climate change occurs continuously with the change in topography, i.e., an abrupt change of local climatic features with a critical height is not found. Simulations of the last interglacial (at 125,000 years before present, i.e., the Eemian interglacial) and the last glacial inception (at 115,000 years before present) are used as examples for the role of orbital-induced changes in insolation. Here, changes in meridional temperature gradients lead to modifications in moisture transport of similar order of magnitude, but with different spatial and seasonal structure. For the Eemian interglacial, a distinct increase in summer moisture transport from the Atlantic deep into the continent at around 20°N is simulated.

Long-term transient simulations are carried out in an initial condition ensemble mode using a global coupled climate model which includes comprehensive ocean and stratosphere components. This model, which is run for the years 1860–2100, allows the investigation of the troposphere–stratosphere interactions and the importance of representing the middle atmosphere in climate-change simulations. The model simulates the present-day climate (1961–2000) realistically in the troposphere, stratosphere and ocean. The enhanced stratospheric resolution leads to the simulation of sudden stratospheric warmings; however, their frequency is underestimated by a factor of 2 with respect to observations. In projections of the future climate using the Intergovernmental Panel on Climate Change special report on emissions scenarios A2, an increased tropospheric wave forcing counteracts the radiative cooling in the middle atmosphere caused by the enhanced greenhouse gas concentration. This leads to a more dynamically active, warmer stratosphere compared with present-day simulations, and to the doubling of the number of stratospheric warmings. The associated changes in the mean zonal wind patterns lead to a southward displacement of the Northern Hemisphere storm track in the climate-change signal.

Climate simulations of the Eemian interglacial and the last glacial inception have been performed by forcing a coupled ocean-atmosphere general circulation model with insolation patterns of these periods. The parameters of the Earth's orbit have been set to conditions of 125 000 and 115 000 years before present (yr BP). Compared to today, these dates represent periods with enhanced and weakened seasonality of insolation in the northern hemisphere. Here we analyse the simulated change in northern hemisphere winter storm tracks. The change in the orbital configuration has a strong impact on the meridional temperature gradients and therefore on strength and location of the storm tracks. The North Atlantic storm track is strengthened, shifted northward and extends further to the east in the simulation for the Eemian at 125 kyr BP. As one consequence, the northern parts of Europe experience an increase in winter precipitation. The frequency of winter storm days increases over large parts of the North Atlantic including the British Isles and the coastal zones of north-western Europe. Opposite but weaker changes in storm track activity are simulated for 115 kyr BP.

We assess the detection and attribution (D&A) of climate engineering (CE) as a function of their duration after initiation. We employ “surrogate” climates where observations are mimicked by simulations. Unlike classical, stationary D&A, the null hypothesis for this analysis is the non-stationary gradual warming caused by continued greenhouse gas (GHG) forcing, which creates a number of theoretical and technical complications. Adapting D&A to this non-stationary setting requires several ad-hoc assumptions whose validity is analyzed and discussed. We study the stratospheric sulfur injection scenarios G3 and G4 of the GeoMIP project. For G3, which smoothly balances global warming with a corresponding cooling, the effect is smaller initially and harder to detect. Temperature and precipitation signals are detectable about a decade after commencing CE and attributable a few years later (details depending on model and scenario). The G4 scenario consists of a continuous injection of 5Tg SO2 (roughly 1/4 of the Pinatubo eruption per year), which represents a shock-like forcing that is easier and earlier detectable, just after a few years. Later into the century, uncertainty in GHG sensitivity increasingly dominates the background noise, hampering G4 detection. Spatio-temporal CE fingerprints produce more stable D&A results, with smoother dependence on time. Spatial resolution (within the range of a few spherical harmonics) is less relevant. We argue that especially for early detectability, climate predictions (with proper initialization from observations) are more promising. Many details depend on the choice of climate model for observation and fingerprint. We discuss the potential and limitation of using multi-model ensembles.

The climate system is excited by changes in the solar forcing caused by two effects: (a) by variations of the solar radiation caused by dynamical processes within the Sun, and (b) by changes in the orbital parameters of the Earth around the Sun. Numerical simulations with a three-dimensional coupled ocean–atmosphere climate model have been performed to investigate the sensitivity of the climate system to both kinds of changes in the forcing. The climate system responds to the (relatively) short term variations of the solar output variations with changes in the surface temperature of up to 2 K, but without any noticeable long lasting effect. The response to the changes in the orbital parameters is more dramatic: dependent if the orbital parameters correspond to the Eemian (a warm phase at around 125 kyr BP) or the one at 115 kyr BP (the onset of the last ice age), the simulation produces a warm state or the initiation of a cold climate. For the Eemian, the simulated climate agrees with the temperature distribution derived from pollen data. For the glacial inception, the model gradually builds up a large snow cover in the northern part of North America. � 2005 COSPAR. Published by Elsevier Ltd. All rights reserved.

Future climate changes over East Asia are studied from ensemble simulations of the coupled climate model ECHO-G, based on the Intergovernmental Panel on Climate Change (IPCC), Special Report on Emissions Scenarios (SRES) A2 and B2 scenarios. Three ensemble experiments are performed: the A2 scenario experiment with greenhouse-gas (GHG) plus sulfate aerosol forcing (referred to as A2), and the A2 and B2 scenario experiments, with GHG forcing only (A2G and B2G respectively). All experiments show that East Asian near surface temperature (T2m) and precipitation (PCP) will increase in the 21st century with larger amplitudes than global means. Seasonally varying changes are found as a larger warming in winter and fall and a stronger PCP in summer. Relative roles of large-scale and convective precipitations (LSP and CP) are analyzed extensively. A mass flux scheme with an adjustment closure is used for cumulus parameterization. In the global mean, LSP dominates total PCP increase whereas CP controls PCP reductions near the equator in December. January-February (DJF) and 30-40° S in June-July-August (JJA). The latter originates from a weakening of the northern winter Hadley circulation and an increased static stability in the Southern Hemisphere, supporting previous results. For the East Asian mean, the CP change explains most of the increase of total PCP in JJA while the LSP change plays a more critical role in DJF. The LSP increase over the North Pacific in DJF is well associated with strengthened [weakened] baroclinicity north [south] of 40°N, i.e., a poleward shift of storm track. Aerosol effects on East Asian climate change (A2 minus A2G patterns) are characterized by cooling and drying with patterns similar to those of the mean changes. This is inconsistent with localized features found in previous works, indicating large uncertainty in regional responses to aerosol forcing. A possible impact of GHG mitigation over the late 21st century (A2G minus B2G patterns) is more pronounced in T2m than in PCP changes, with similar patterns as in aerosol effects. Simulated CP and LSP contributions to PCP changes are insensitive to the aerosol effect as well as that of GHG mitigations.

Records from the past show that abrupt global change is the norm, not the exception, in the Earth System. Many recent changes-such as the globalization of the world's economy and the formation of the ozone hole over Antarctica-appear rapid even from the perspective of a single lifetime. What do we now know about the nature of abrupt changes in the Earth System and the probability that human actions could trigger them?

In this study, a minimum distance classification and forward feature selection technique are joined to determine the relationship between weather conditions and the increase of the risk of type A acute aortic dissection (AAD) events in Berlin. The results demonstrate that changes in the amount of cloudiness and air temperature are the most representative weather predictors among the studied parameters. A discrimination surface was developed for the prediction of AAD events 6 h ahead, and it is found that, under a specific amount of cloudiness and air temperature, the risk of AAD events in Berlin increases about 20 %.

The importance of air pollution monitoring networks in urban areas is well known because of their miscellaneous applications. At the beginning of the 1990s, Berlin had more than 40 particulate matter monitoring stations, whereas, by 2013, there were only 12 stations. In this study, a new and free–of–charge methodology for the densifying of the PM 10 monitoring network of Berlin is presented. It endeavors to find the non–linear relationship between the hourly PM 10 concentration of the still–operating PM 10 monitoring stations and the shut–down stations by using the Artificial Neural Network (ANN), and, consequently, the results of the shut–down stations were simulated and re–constructed. However, input–variables selection is a pre–requisite for any ANN simulation, and hence a new fuzzy–heuristic input selection has been developed and joined to the ANN for the simulation. The hourly PM 10 concentrations of the 20 shut–down stations were simulated and re–constructed. The mean error, bias and absolute error of the simulations were 27.7%, –0.03 (μg/m 3 ), and 7.4 (μg/m 3 ), respectively. Then, the simulated hourly PM 10 concentration data were converted to a daily scale and the performance of ANN models which were developed for the simulation of the daily PM 10 data were evaluated (correlation coefficient >0.94). These appropriate results imply the ability of the developed input selection technique to make the appropriate selection of the input variables, and it can be introduced as a new input variable selection for the ANN. In addition, a dense PM 10 monitoring network was developed by the combination of both the re–constructed (20 stations) and the current (12 stations) stations. This dense monitoring network was applied in order to determine a reliable mean annual PM 10 concentration in the different areas in Berlin in 2012.

Fingerprint techniques for the detection of anthropogenic climate change aim to distinguish the climate response to anthropogenic forcing from responses to other external influences and from internal climate variability. All these responses and the characteristics of internal variability are typically estimated from climate model data. We evaluate the sensitivity of detection and attribution results to the use of response and variability estimates from two different coupled ocean atmosphere general circulation models (HadCM2, developed at the Hadley Centre, and ECHAM3/LSG from the MPI fur Meteorologie and Deutsches Klimarechenzentrum). The models differ in their response to greenhouse gas and direct sulfate aerosol forcing and also in the structure of their internal variability. This leads to differences in the estimated amplitude and the significance level of anthropogenic signals in observed 50-year summer (June, July, August) surface temperature trends. While the detection of anthropogenic influence on climate is robust to intermodel differences, our ability to discriminate between the greenhouse gas and the sulfate aerosol signals is not. An analysis of the recent warming, and the warming that occurred in the first half of the twentieth century, suggests that simulations forced with combined changes in natural (solar and volcanic) and anthropogenic (greenhouse gas and sulfate aerosol) forcings agree best with the observations.

We examine the seasonal cycle of near-surface air temperature simulated by 17 coupled ocean-atmosphere general circulation models participating in the Coupled Model Intercomparison Project (CMIP). Nine of the models use ad hoc “flux adjustment” at the ocean surface to bring model simulations close to observations of the present-day climate. We group flux-adjusted and non-flux-adjusted models separately and examine the behavior of each class. When averaged over all of the flux-adjusted model simulations, near-surface air temperature falls within 2 K of observed values over the oceans. The corresponding average over non-flux-adjusted models shows errors up to ∼6 K in extensive ocean areas. Flux adjustments are not directly applied over land, and near-surface land temperature errors are substantial in the average over flux-adjusted models, which systematically underestimates (by ∼5 K) temperature in areas of elevated terrain. The corresponding average over non-flux-adjusted models forms a similar error pattern (with somewhat increased amplitude) over land. We use the temperature difference between July and January to measure seasonal cycle amplitude. Zonal means of this quantity from the individual flux-adjusted models form a fairly tight cluster (all within ∼30% of the mean) centered on the observed values. The non-flux-adjusted models perform nearly as well at most latitudes. In Southern Ocean mid-latitudes, however, the non-flux-adjusted models overestimate the magnitude of January-minus-July temperature differences by ∼5 K due to an overestimate of summer (January) near-surface temperature. This error is common to five of the eight non-flux-adjusted models. Also, over Northern Hemisphere mid-latitude land areas, zonal mean differences between July and January temperatures simulated by the non-flux-adjusted models show a greater spread (positive and negative) about observed values than results from the flux-adjusted models. Elsewhere, differences between the two classes of models are less obvious. At no latitude is the zonal mean difference between averages over the two classes of models greater than the standard deviation over models. The ability of coupled GCMs to simulate a reasonable seasonal cycle is a necessary condition for confidence in their prediction of long-term climatic changes (such as global warming), but it is not a sufficient condition unless the seasonal cycle and long-term changes involve similar climatic processes. To test this possible connection, we compare seasonal cycle amplitude with equilibrium warming under doubled atmospheric carbon dioxide for the models in our data base. A small but positive correlation exists between these two quantities. This result is predicted by a simple conceptual model of the climate system, and it is consistent with other modeling experience, which indicates that the seasonal cycle depends only weakly on climate sensitivity.

This paper discusses two aspects of climate modeling, the deep water formation in the North Atlantic and precipitation changes due to climate change caused by anthropogenic emissions of greenhouse gases. The deep water formation is strongly influenced by the precipitation, and the precipitation is affected by the concentration of the greenhouse gases in the atmosphere and by the atmospheric and oceanic circulation. The experiments discussed here have been performed independently to test the stability of the thermohaline circulation of the North Atlantic and to investigate changes in precipitation due to anthropogenic greenhouse gas emissions. The precipitation changes in a climate change environment are sufficient in some simulations to decrease the thermohaline circulation noticeably. However, it appears that the amount of freshwater needed to bring the circulation to a collapse is magnitudes larger than the anticipated change in precipitation due to anthropogenic activities within the next 100 years. The precipitation changes, on the other hand, might change regionally quite drastically towards more extreme situations, thereby putting additional stress on vegetation and enhancing soil erosion.

To estimate the effect of the solar variability on the climate, two estimates of the solar intensity variations during the last three centuries have been used as forcing in numerical simulations. The model employed to carry out the experiments was the same coupled global ocean-atmosphere model used in a number of studies to assess the effect of the anthropogenic greenhouse gases on climate. The near surface temperature and the tropospheric temperature distribution shows a clear response to the variability of the solar input. Even the thermohaline circulation reacts on the large amplitudes in the forcing. In the stratosphere, the response pattern is similar as in the observations, however, the 11-year cycle found in the forcing data does not excite an appreciable response. This might be due to the missing parameterisation of the increase in the UV-radiation at the solar cycle maximum and the connected increase of the stratospheric ozone concentration.

A new periodically synchronous coupling scheme has been applied to an atmosphere-ocean general circulation model. Due to a temporary switching off of the atmospheric model this scheme can considerably reduce computer requirements of coupled model experiments. In order to evaluate the new coupling scheme the model results are compared to corresponding synchronously coupled integrations. Experiments with fixed present-day CO2 concentration and a gradual increase of CO2 show a good reproduction of the mean state and the climate-change pattern, respectively. The deviations from the synchronously coupled experiments are in the range of the variability of the corresponding synchronously coupled runs. Due to the forcing during the ocean-only periods the short-term fluctuations are underestimated and the long-term variability is overestimated.

Cities demonstrate higher nocturnal temperatures than surrounding rural areas, which is called “urban heat island” (UHI) effect. Climate change projections also indicate increase in the frequency and intensity of heat waves, which will intensify the UHI effect. As megacity Tehran is affected by severe heatwaves in summer, this study investigates its UHI characteristics and suggests some feasible mitigation strategies in order to reduce the air temperature and save energy. Temperature monitoring in Tehran shows clear evidence of the occurrence of the UHI effect, with a peak in July, where the urban area is circa 6 K warmer than the surrounding areas. The mobile measurements show a park cool island of 6-7 K in 2 central parks, which is also confirmed by satellite images. The effectiveness of three UHI mitigation strategies high albedo material (HAM), greenery on the surface and on the roofs (VEG), and a combination of them (HYBRID) has been studied using simulation with the microscale model ENVI-met. All three strategies show higher cooling effect in the daytime. The average nocturnal cooling effect of VEG and HYBRID (0.92, 1.10 K) is much higher than HAM (0.16 K), although high-density trees show a negative effect on nocturnal cooling.

The changes in the surface energy fluxes calculated with a general circulation model under increased levels of carbon dioxide concentration are analyzed and related to the simulation of these fluxes under present-day conditions. It is shown that the errors in the simulated fluxes under present climate are often of similar or larger magnitude than the simulated changes of these quantities. A similar relationship may be found in climate change experiments of many GCMs. Although this does not imply that the projected changes of the fluxes are wrong, more accurate absolute values would improve confidence in GCM-simulated climate change scenarios. The global mean increase in the downward component of the longwave radiation, which is the direct greenhouse forcing at the surface, is on the order of 10 W m22 at the time of doubled carbon dioxide in a transient coupled atmosphere‐ocean scenario experiment. This is an amount similar to the underestimation of this quantity in the present-day simulations compared to surface observations. Thus, it is only with doubled carbon dioxide concentration that the simulated greenhouse forcing at the surface reaches the values observed at present. The simulated shortwave radiation budget at the surface is less affected by the increased levels of carbon dioxide than the longwave budget on the global scale. Regionally and seasonally, the changes in the incoming shortwave radiation at the surface can exceed 20 W m22, mainly due to changes in cloud amounts. The projected changes, however, are generally of smaller magnitude than the systematic errors in the control run at the majority of 720 observation sites. The positive feedback between excessive radiation and surface processes leading to excessive summer dryness and temperatures over continental surfaces in the control run is enhanced in the doubled carbon dioxide experiment, resulting in a massive increase in the projected surface temperature. In the high-resolution T106 time-slice scenario experiment performed in this study the global mean latent heat flux and associated intensity of the hydrological cycle is slightly decreased rather than increased with doubled carbon dioxide. A reduction in surface wind speed in the T106 scenario is suggested as a major factor for the reverse of sign. The improved representation of the orography with T106 resolution allows a better estimate of the projected changes of surface energy fluxes in mountain areas, as demonstrated for the European Alps.

A multi-fingerprint analysis is applied to the detection and attribution of anthropogenic climate change. While a single fingerprint is optimal for the detection of climate change, further tests of the statistical consistency of the detected climate change signal with model predictions for different candidate forcing mechanisms require the simultaneous application of several fingerprints. Model-predicted climate change signals are derived from three anthropogenic global warming simulations for the period 1880 to 2049 and two simulations forced by estimated changes in solar radiation from 1700 to 1992. In the first global warming simulation, the forcing is by greenhouse gas only, while in the remaining two simulations the direct influence of sulfate aerosols is also included. From the climate change signals of the greenhouse gas only and the average of the two greenhouse gas-plus-aerosol simulations, two optimized fingerprint patterns are derived by weighting the model-predicted climate change patterns towards low-noise directions. The optimized fingerprint patterns are then applied as a filter to the observed near-surface temperature trend patterns, yielding several detection variables. The space-time structure of natural climate variability needed to determine the optimal fingerprint pattern and the resultant signal-to-noise ratio of the detection variable is estimated from several multi-century control simulations with different CGCMs and from instrumental data over the last 136 y. Applying the combined greenhouse gas-plus-aerosol fingerprint in the same way as the greenhouse gas only fingerprint in a previous work, the recent 30-y trends (1966–1995) of annual mean near surface temperature are again found to represent a significant climate change at the 97.5% confidence level. However, using both the greenhouse gas and the combined forcing fingerprints in a two-pattern analysis, a substantially better agreement between observations and the climate model prediction is found for the combined forcing simulation. Anticipating that the influence of the aerosol forcing is strongest for longer term temperature trends in summer, application of the detection and attribution test to the latest observed 50-y trend pattern of summer temperature yielded statistical consistency with the greenhouse gas-plus-aerosol simulation with respect to both the pattern and amplitude of the signal. In contrast, the observations are inconsistent with the greenhouse-gas only climate change signal at a 95% confidence level for all estimates of climate variability. The observed trend 1943–1992 is furthermore inconsistent with a hypothesized solar radiation change alone at an estimated 90% confidence level. Thus, in contrast to the single pattern analysis, the two pattern analysis is able to discriminate between different forcing hypotheses in the observed climate change signal. The results are subject to uncertainties associated with the forcing history, which is poorly known for the solar and aerosol forcing, the possible omission of other important forcings, and inevitable model errors in the computation of the response to the forcing. Further uncertainties in the estimated significance levels arise from the use of model internal variability simulations and relatively short instrumental observations (after subtraction of an estimated greenhouse gas signal) to estimate the natural climate variability. The resulting confidence limits accordingly vary for different estimates using different variability data. Despite these uncertainties, however, we consider our results sufficiently robust to have some confidence in our finding that the observed climate change is consistent with a combined greenhouse gas and aerosol forcing, but inconsistent with greenhouse gas or solar forcing alone.

The ability of the current generation of climate models, in their long-term simulations, to replicate the observed atmospheric behaviour on a wide range of spatial and time scales provides support in applying these models to the greenhouse gas-induced climate change projections on regional scales. A series of long time-slice control experiments have been performed recently with the ECHAM3 atmospheric general circulation model at T21, T42 and T106 horizontal resolutions (30 years each with T21 and T42 and 5 years with T106). All these model experiments use a common sea-surface temperature climatology in their control experiment inferred from a coupled ocean‐atmosphere climate model (ECHAM1a LSG) experiment. In this paper, we examine the ability of the ECHAM3 model to simulate the Indian monsoon climatology at these three different horizontal resolutions. Because the Indian summer monsoon circulation evolves through a characteristic sequence of events, it is important that the climate models should be able to realistically portray these important features of the circulation over adequate spatial and time scales. We focus on the model’s simulation of selected variables representative of the thermal, dynamic and hydrological components in zonal mean cross-sections and area-averaged monthly as well as seasonal regional distributions. Generally, with respect to large-scale features of the circulation, the largest differences among the simulations occur at T42 relative to T21. At both T21 and T42 horizontal resolution, however, the model does not have a high degree of correspondence with observations as regards the spatial distribution of mean sea-level pressure, surface air temperature, 850 hPa winds and precipitation. On regional scales, T106 resolution best captures both the spatial and temporal characteristics of the Indian climatology. Both the diurnal and seasonal cycles of area-averaged surface air temperature over the region simulated by the model at T106 resolution are within 1 to 2C as compared with observed climatology. The development and migration of the monsoon trough over Central India and the adjoining Bay of Bengal during the monsoon season is best simulated at T106 resolution. There is a distinct improvement in the spatial distribution as well as the total area-averaged summer monsoon rainfall in the model simulations with finer resolution. Although the modelled and observed mean summer precipitation is similar in overall structure at T106 resolution, underestimation of the total seasonal rainfall in the model even at high resolution is a reflection of the sensitivity of simulated precipitation to local climate forcings, e.g. tropical convergence zone, and deficiencies of parameterization schemes for convection and land surface processes. # 1997 by the Royal Meteorological Society. Int. J. Climatol., 17: 847‐858 (1977)

The production of climate simulations using global coupled ocean–atmosphere models at high resolution is currently limited by computational expense and the long periods of integration that are necessary. A method of increasing the number of experiments that can be performed is the so-called time-slice technique. Using the Arpege-climat atmospheric model three 5-yr integrations of this type were run: a control and two integrations forced with sea surface temperatures derived from coupled model simulations of the transient response to increasing carbon dioxide. These coupled models are the ECHAM1 model of the Max-Planck Institute (Hamburg, Germany) and the U.K. Meteorological Office model of the Hadley Centre. The sensitivity of the response to the oceanic forcing is studied. The results are compared with the 10-yr mean atmospheric response of the coupled models at the time of the doubling of CO2. Global warmings ranging from 1.3 K to 1.9 K are obtained. Special attention is given to the modificati...

Simulations using global coupled climate models predict a climate change due to the increasing concentration of greenhouse gases and aerosols in the atmosphere. Both are associated with the burning of fossil fuels. There has been considerable debate if this postulated human influence is already evident. This paper gives an overview on some recent material on this question. One particular study using optimal fingerprints (Hegerl et al., 1996) is explained in more detail. In this study, an optimal fingerprint analysis is applied to temperature trend patterns over several decades. The results show the probability being less than 5% that the most recently observed 30 year trend is due to naturally occurring climate fluctuations. This result suggests that the present warming is caused by some external influence on climate, e.g. by the increasing concentrations of greenhouse gases and aerosols. More work is needed to address the uncertainties in the magnitude of naturally occurring climate fluctuations. Also, other external influences on climate need to be investigated to uniquely attribute the present climate change to the human influence.

Climates, Landsca Geophysical Mon © 2012. American 10.1029/2012GM The rise and fall of ancient cultures in drylands is mainly controlled by the availability of water. Where no perennial water sources are available, (ancient) cultures in drylands often depend on the availability of water by effective rainfall as a source for water-harvesting measures. These settlements are susceptible to climatic changes. The reconstruction of such climate-human interactions is constrained, as paleoclimatic proxy archives provide climatic information at most with annual or seasonal resolutions, which is often not a sufficient resolution to relate them to the reactions or adaptations of societies to climatic shifts. For the city of Naga (16°N 33°E) in the dry hinterland of the middle Nile River, we present precipitation data for the last 6500 years employing two different downscaling approaches. In time slice experiments, we simulated selected episodes using a spatially high-resolved atmosphere general circulation model. Furthermore, combining observed precipitation data and a simulation of a coupled ocean-atmosphere general circulation model, we attained statistically downscaled precipitation data for the last 6500 years. Our results indicate that the mean precipitation and the frequency of runoff-generating rainfall events decreased from 6000 until 2000 years B.P. Since then, no significant changes occurred. Thus, the foundation of Naga about 2500 years B.P. coincided with a time when rainfall was still more reliable and less variable. Alterations in orbital parameters (according to Milankovic theory) may have been a major reason for the abandonment of the city.

A strategy using statistically optimal fingerprints to detect anthropogenic climate change is outlined and applied to near-surface temperature trends. The components of this strategy include observations, information about natural climate variability, and a "guess pattern" representing the expected time-space pattern of anthropogenic climate change. The expected anthropogenic climate change is identified through projection of the observations onto an appropriate optimal fingerprint, yielding a scalar-detection variable. The statistically optimal fingerprint is obtained by weighting the components of the guess pattern (truncated to some small-dimensional space) toward low-noise directions. The null hypothesis that the observed climate change is part of natural climate variability is then tested. This strategy is applied to detecting a greenhouse-gas-induced climate change in the spatial pattern of nearsurface temperature trends defined for time intervals of 15-30 years. The expected pattern of climate change is derived from a transient simulation with a coupled ocean-atmosphere general circulation model. Global gridded near-surface temperature observations are used to represent the observed climate change. Information on the natural variability needed to establish the statistics of the detection variable is extracted from long control simulations of coupled ocean-atmosphere models and, additionally, from the observations themselves (from which an estimated greenhouse warming signal has been removed). While the model control simulations contain only variability caused by the internal dynamics of the atmosphere-ocean system, the observations additionally contain the response to various external forcings (e.g., volcanic eruptions, changes in solar radiation, and residual anthropogenic forcing). The resulting estimate of climate noise has large uncertainties but is qualitatively the best the authors can presently offer. The null hypothesis that the latest observed 20-yr and 30-yr trend of near-surface temperature (ending in 1994) is part of natural variability is rejected with a risk of less than 2.5 to 5 (the 5 level is derived from the variability of one model control simulation dominated by a questionable extreme event ). In other words, the probability that the warming is due to our estimated natural variability is less than 2.5 to 5. The increase in the signal-to-noise ratio by optimization of the fingerprint is of the order of 10-30 in most cases. The predicted signals are dominated by the global mean component; the pattern correlation excluding the global mean is positive but not very high. Both the evolution of the detection variable and also the pattern correlation results are consistent with the model prediction for greenhouse-gas-induced climate change. However, in order to attribute the observed warming uniquely to anthropogenic greenhouse gas forcing, more information on the climate's response to other forcing mechanisms (e.g., changes in solar radiation, volcanic, or anthropogenic sulfate aerosols) and their interaction is needed. It is concluded that a statistically significant externally induced warming has been observed, but our caveat that the estimate of the internal climate variability is still uncertain is emphasized.

An upwelling diffusion (UD) model has been fitted to the results of a globally coupled ocean atmosphere general circulation model (O/AGCM). In order to adequately simulate the results of the O/AGCM, the differential heating over land and ocean, the change of the upwelling rate with rising mixed-layer temperature and the climate adjustment of the O/AGCM evident in the control simulation had to be taken into account. Comparisons using the results of four O/AGCM perturbation experiments show that the timing of the adjustment in the O/AGCM control run differs from that in the perturbed runs. The UD model simulates the global mean temperature evolution, as calculated by the O/AGCM reasonably well. However, when time dependent upwelling is included, the UD model substantially overestimates the thermal expansion compared to this O/AGCM. Possible reasons for this overestimation have been identified.

The general circulation model ECHAM5 has been used to simulate the Indian monsoon and its variability during the Medieval Warm Period (MWP; 900–1100 AD), the Little Ice Age (LIA; 1515–1715 AD) and for recent climate (REC; 1800–2000 AD). The focus is on the analysis of external drivers and internal feedbacks leading to extreme rainfall events over India from interannual to multidecadal time scale. An evaluation of spatiotemporal monsoon patterns with present-day observation data is in agreement with other state-of-the-art monsoon modeling studies. The simulated monsoon intensity on multidecadal time scale is weakened (enhanced) in summer (winter) due to colder (warmer) SSTs in the Indian Ocean. Variations in solar insolation are the main drivers for these SST anomalies, verified by very strong temporal anticorrelations between Total Solar Irradiance and All-India-Monsoon-Rainfall in summer monsoon months. The external solar forcing is coupled and overlain by internal climate modes of the ocean (ENSO and IOD) with asynchronous intensities and lengths of periods. In addition, the model simulations have been compared with a relative moisture index derived from paleoclimatic reconstructions based on various proxies and archives in India. In this context, the Lonar record in Central India has been highlighted and evaluated the first time. The simulated relative annual rainfall anomalies in comparison to present-day climate are in agreement (disagreement) with the reconstructed moisture index for MWP (LIA) climate. In order to investigate the interannual monsoon variability with respect to monsoon failures, dry summer monsoon composites for 30-yr-long periods of MWP, LIA and REC have been further analysed. Within dry years of LIA, the summer rainfall over India and surrounding oceans is less than in MWP indicating stronger drying conditions due to a stronger summer solar insolation forcing coupled with variations in ENSO. To quantify the ECHAM5 simulated long-term drought conditions within Monsoon Asia, the Palmer Drought Severity Index has been additionally estimated for recent climate showing strong pattern correlation between global SST anomalies and EOF variability signal of the drought index, whereas the temporal relationship is weak.

In the Project on Solar Effects on Chemistry and Climate Including Ocean Interactions (ProSECCO) fundamental questions of the impact of solar variability on Earth have been investigated with improved climate system models and observations. On the decadal time scale, the atmospheric signature of the 11-year Schwabe cycle and the underlying mechanisms have been studied. This included the impact of variations in UV radiation and particle precipitation on stratospheric chemistry and ozone, as well as on the solar signal in the troposphere and on climate. On the centennial to millennium time scale, effects of solar variability on climate of different pre-industrial periods, focusing on the Maunder Minimum and the mid-Holocene, have been addressed.

Am 20. Februar 1995 meldeten es alle Nachrichtenagenturen: Mit 95prozentiger Wahrscheinlichkeit ist die in den Klimabeobachtungen verzeichnete globale Erwarmung um 0,7 °C seit Beginn der Industrialisierung anthropogenen Ursprungs. Dieses Ergebnis einer komplexen Analyse von Klimamodellrechnungen am Deutschen Klimarechenzentrum in Hamburg gab dessen Direktor Klaus Hasselmann an diesem Tag der Bundesregierung bekannt. Der folgende Beitrag von Mitarbeitern dieses Zentrums ist eine kritische Analyse der Methodik von Klimasimultationsrechnungen. Er beschreibt, wie man mit Hilfe von gekoppelten Ozean-Atmosphare-Modellen zu einer solchen Aussage gelangt, welche Probleme dabei auftreten und wo die Grenzen der heutigen Modelle liegen. (Red.)

Hamburg atmospheric general circulation model ECHAM3 at T106 resolution (1.125' lat.Aon.) has considerable skill in reproducing the observed seasonal reversal of mean sea level pressure, the location of the summer heat low as well as the position of the monsoon trough over the Indian subcontinent. The present-day climate and its seasonal cycle are realistically simulated by the model over this region. The model simulates the structure, intensity, frequency, movement and lifetime of monsoon depressions remarkably well. The number of monsoon depressions/storms simulated by the model in a year ranged from 5 to 12 with an average frequency of 8.4 yr-', not significantly different from the observed climatology. The model also simulates the interannual variability in the formation of depressions over the north Bay of Bengal during the summer monsoon season. In the warmer atmosphere under doubled CO2 conditions, the number of monsoon depressions/cyclonic storms forming in Indian seas in a year ranged from 5 to 11 with an average frequency of 7.6 yr-', not significantly different from those inferred in the control run of the model. However, under doubled CO2 conditions, fewer depressions formed in the month of June. Neither the lowest central pressure nor the maximum wind speed changes appreciably in monsoon depressions identified under simulated enhanced greenhouse conditions. The analysis suggests there will be no significant changes in the number and intensity of monsoon depressions in a warmer atmosphere.

[1] The Southern Hemisphere Westerly Winds (SWW) constitute an important zonal circulation system that dominates the dynamics of the Southern Hemisphere mid-latitudes. In the present study, we analyze results from two transient simulations (1630–2000 AD) conducted with the coupled atmosphere-ocean model EGMAM (ECHO-G with Middle Atmosphere Model): one simulation with fixed stratospheric ozone concentration, and one with solar-induced variations in stratospheric ozone content. The results suggest that during periods of lower solar activity, the annual-mean SWW tend to get weaker on their poleward side and shift towards the equator. The SWW shift is more intense and robust for the simulation with varying stratospheric ozone, suggesting an important influence of solar-induced stratospheric ozone variations on mid-latitude troposphere dynamics. Finally, we present proxy evidence from a high-resolution marine sediment core from the Chilean continental slope (41°S), which strongly supports the model result of an equatorward displacement of the SWW during the Maunder Minimum.

[1] In the paper “Solar influences on climate” by L. J. Gray et al. (Reviews of Geophysics, 48, RG4001, doi:10.1029/ 2009RG000282, 2010), Figures 19 and 23 are in error. In Figure 19, the C values in Figure 19 (middle) were incorrectly plotted. In Figure 23, the wrong figure was inadvertently uploaded and showed the temperature response rather than the ozone response as described in the caption. The correct Figures 19 and 23 appear here.

International audience; Climate change is expected to increase winter rainfall and flooding in many extratropical regions as evaporation and precipitation rates increase, storms become more intense and storm tracks move polewards. Here, we show how changes in stratospheric circulation could play a significant role in future climate change in the extratropics through an additional shift in the tropospheric circulation. This shift in the circulation alters climate change in regional winter rainfall by an amount large enough to significantly alter regional climate change projections. The changes are consistent with changes in stratospheric winds inducing a change in the baroclinic eddy growth rate across the depth of the troposphere. A change in mean wind structure and an equatorward shift of the tropospheric storm tracks relative to models with poor stratospheric resolution allows coupling with surface climate. Using the Atlantic storm track as an example, we show how this can double the predicted increase in extreme winter rainfall over Western and Central Europe compared to other current climate projections.

Results from a control integration and time-dependent greenhouse warming experiments performed with a coupled ocean-atmosphere model are analysed in terms of their signal-to-noise properties. The aim is to illustrate techniques for efficient description of the space-time evolution of signals and noise and to identify potentially useful components of a multivariate greenhouse-gas ''fingerprint''. The three 100-year experiments analysed here simulate the response of the climate system to a step-function doubling Of CO2 and to the time-dependent greenhouse-gas increases specified in Scenarios A (''Business as Usual'') and D (''Draconian Measures'') of the Intergovernmental Panel on Climate Change (IPCC). If signal and noise patterns are highly similar, the separation of the signal from the natural variability noise is difficult. We use the pattern correlation between the dominant Empirical Orthogonal Functions (EOFs) of the control run and the Scenario A experiment as a measure of the similarity of signal and noise patterns. The EOF 1 patterns of signal and noise are least similar for near-surface temperature and the vertical structure of zonal winds, and are most similar for sea level pressure (SLP). The dominant signal and noise modes of precipitable water and stratospheric/tropospheric temperature contrasts show considerable pattern similarity. Despite the differences in forcing history, a highly similar EOF 1 surface temperature response pattern is found in all three greenhouse warming experiments. A large part of this similarity is due to a common land-sea contrast component of the signal. To determine the degree to which the signal is contaminated by the natural variability (and/or drift) of the control run, we project the Scenario A data onto EOFs 1 and 2 of the control. Signal contamination by the EOF 1 and 2 modes of the noise is lowest for near-surface temperature, a situation favorable for detection. The signals for precipitable water, SLP, and the vertical structure of zonal temperature and zonal winds are significantly contaminated by the dominant noise modes. We use cumulative explained spatial variance, principal component time series, and projections onto EOFs in order to investigate the time evolution of the dominant signal and noise modes. In the case of near-surface temperature, a single pattern emerges as the dominant signal component in the second half of the Scenario A experiment. The projections onto EOFs 1 and 2 of the control run indicate that Scenario D has a large common variability and/or drift component with the control run. This common component is also apparent between years 30 and 50 of the Scenario A experiment, but is small in the 2 x CO2 integration. The trajectories of the dominant Scenario A and control run modes evolve differently, regardless of the basis vectors chosen for projection, thus making it feasible to separate signal and noise within the first two decades of the experiments. For Scenario D it may not be possible to discriminate between the dominant signal and noise modes until the final 2-3 decades of the 100-year integration.

[1] The potential role of the stratosphere for the 11-year solar cycle signal in the Pacific region is investigated by idealized simulations using a coupled atmosphere-ocean general circulation model. The model includes a detailed representation of the stratosphere and accounts for changes in stratospheric heating rates from prescribed time dependent variations of ozone and spectrally high resolved solar irradiance. Three transient simulations are performed spanning 21 solar cycles each. The simulations use slightly different ozone perturbations representing uncertainties of solar induced ozone variations. The model reproduces the main features of the 20th century observed solar response. A persistent mean sea level pressure response to solar forcing is found for the eastern North Pacific extending over North America. Moreover, there is evidence for a La Nina-like response assigned to solar maximum conditions with below normal SSTs in the equatorial eastern Pacific, reduced equatorial precipitation, enhanced off-equatorial precipitation and an El Nino-like response a couple of years later, thus confirming the response to solar forcing at the surface seen in earlier studies. The amplitude of the solar signal in the Pacific region depends to a great extent on the choice of the centennial period averaged.

[1] The variability in the number of major sudden stratospheric warmings (SSWs) is analyzed in a multi-century simulation under constant forcing using a stratosphere resolving atmosphere-ocean general circulation model. A wavelet-analysis of the SSW time series identifies significantly enhanced power at a period of 52 years. The coherency of this signal with tropospheric and oceanic parameters is investigated. The strongest coherence is found with the North Atlantic ocean-atmosphere heat-flux from November to January. Here, an enhanced heat-flux from the ocean into the atmosphere is related to an increase in the number of SSWs. Furthermore, a correlation is found with Eurasian snow cover in October and the number of blockings in October/November. These results suggest that the multi-decadal variability is generated within the ocean-troposphere-stratosphere system. A two-way interaction of the North Atlantic and the atmosphere buffers and amplifies stratospheric anomalies, leading to a coupled multi-decadal mode.

[1] Transient climate simulations are performed covering the period from 1630 to 2000. A vertically extended version of a coupled atmosphere-ocean general circulation model is used, including a detailed representation of the stratosphere. One simulation is driven by changes in total solar irradiance due to solar activity as well as volcanic eruptions and changes in greenhouse gas (GHG) concentrations. A second simulation additionally includes changes in short-wave heating due to prescribed photochemical changes in ozone. The simulations are compared with reconstructions and other simulations employing less resolved stratosphere. The inclusion of the higher resolved stratosphere plays only a moderate role for the simulated climate variability on the hemispheric scale. Larger implications are found for regional scales. Both simulations reveal a shift of the North Atlantic Oscillation toward a more positive phase from the Maunder Minimum to present day, mainly attributed to anthropogenic increase in concentration of well-mixed GHG. Increase in GHG is related to a more disturbed stratospheric polar vortex resulting in an only moderate strengthening of tropospheric westerlies over Europe compared with the tropospheric version of the model. On multidecadal to centennial time scales the stratospheric solar forcing substantially contributes to the climate change signal in the stratosphere, and there is clear evidence for an impact on the tropospheric circulation.

The development of this review article has evolved from work carried out by an international team of the International Space Science Institute (ISSI), Bern, Switzerland, and from work carried out under the auspices of Scientific Committee on Solar Terrestrial Physics (SCOSTEP) Climate and Weather of the Sun‐Earth System (CAWSES‐1). The support of ISSI in providing workshop and meeting facilities is acknowledged, especially support from Y. Calisesi and V. Manno. SCOSTEP is acknowledged for kindly providing financial assistance to allow the paper to be published under an open access policy. L.J.G. was supported by the UK Natural Environment Research Council (NERC) through their National Centre for Atmospheric Research (NCAS) Climate program. K.M. was supported by a Marie Curie International Outgoing Fellowship within the 6th European Community Framework Programme. J.L. acknowledges support by the EU/FP7 program Assessing Climate Impacts on the Quantity and Quality of Water (ACQWA, 212250) and from the DFG Project Precipitation in the Past Millennium in Europe (PRIME) within the Priority Program INTERDYNAMIK. L.H. acknowledges support from the U.S. NASA Living With a Star program. G.M. acknowledges support from the Office of Science (BER), U.S. Department of Energy, Cooperative Agreement DE‐FC02‐97ER62402, and the National Science Foundation. We also wish to thank Karin Labitzke and Markus Kunze for supplying an updated Figure 13, Andrew Heaps for technical support, and Paul Dickinson for editorial support. Part of the research was carried out under the SPP CAWSES funded by GFG. J.B. was financially supported by NCCR Climate–Swiss Climate Research.

An intercomparison is undertaken of the tropical behavior of 17 coupled ocean-atmosphere models in which at least one component may be termed a general circulation model (GCM). The aim is to provide a taxonomy—a description and rough classification—of behavior across the ensemble of models, focusing on interannual variability. The temporal behavior of the sea surface temperature (SST) field along the equator is presented for each model, SST being chosen as the primary variable for intercomparison due to its crucial role in mediating the coupling and because it is a sensitive indicator of climate drift. A wide variety of possible types of behavior are noted among the models. Models with substantial interannual tropical variability may be roughly classified into cases with propagating SST anomalies and cases in which the SST anomalies develop in place. A number of the models also exhibit significant drift with respect to SST climatology. However, there is not a clear relationship between climate drift and the presence or absence of interannual oscillations. In several cases, the mode of climate drift within the tropical Pacific appears to involve coupled feedback mechanisms similar to those responsible for El Niño variability. Implications for coupled-model development and for climate prediction on seasonal to interannual time scales are discussed. Overall, the results indicate considerable sensitivity of the tropical coupled ocean-atmosphere system and suggest that the simulation of the warm-pool/cold-tongue configuration in the equatorial Pacific represents a challenging test for climate model parameterizations.

[1] While it is well understood that thermal expansion dominates global mean steric sea level rise, climate models show large differences in spatial patterns. This study aims to decompose regional steric sea level rise in the North Atlantic into thermal and saline effects in a fully coupled model. In contrast to other studies we focus on the differences between two climate change scenarios and establish a link between the sea level changes and the differences in the response of the overturning circulation. While overturning is reduced in the phase of the greenhouse gas increase, differences between the scenarios are not significant until the stabilization in the 22nd century. The influence from thermosteric and halosteric contributions on the meridional density gradient is of the same size during the increase of greenhouse gas concentrations. The haline effect becomes prominent afterwards, reducing the meridional density gradient and preventing the overturning from recovery.

[1] During the SAMUM field campaign in southern Morocco in May and June 2006 density currents generated by evaporative cooling after convective precipitation were frequently observed at the Sahara side of the Atlas Mountain chain. The associated strong surface cold-air outflow during such events has been observed to lead to dust mobilization in the foothills. Here a regional model system is used to simulate a density current case on 3 June 2006 and the subsequent dust emission. The model studies are performed with different parameterization schemes for convection, and with different horizontal model grid resolutions to examine to which extent the model system can be used for reproducing dust emissions in this region. The effect of increasing the horizontal model grid resolution from 14 km to 2.8 km on the strength on the density currents and thus on dust emission is smaller than the differences due to different convection parameterization schemes in this case study. While the results in reproducing the observed density current at the Atlas Mountain varied with different convection parameterizations, the most realistic representation of the density current is obtained at 2.8 km grid resolution at which no parameterization of deep convection is needed.

The influence of horizontal resolution on model systematic error and skill scores are examined for both winter and summer seasons from a set of extended-range integrations of the European Centre for Medium Range Weather Forecasts (ECMWF) numerical weather prediction model. the forecast data are composed of 24 30-day integrations, two per month from successive 12 GMT operational analyses, from April 1985 to March 1986 at four (triangular truncation) horizontal spectral resolutions of T21, T42, T63 and T106. Systematic errors in wind, temperature, heat and momentum fluxes are discussed, both in the tropics and extratropics. Dynamical reasons for differences between various model resolutions and between simulations and observations are proposed. Diagnosis of model systematic error is aided by comparing zonal-mean diagnostics of the observed flow in the northern hemisphere winter and southern hemisphere winter. the impact of resolution on regional simulations of rainfall during the Indian and African monsoons is also discussed. In the extratropical troposphere, the behaviour of the T21 model is quite distinct from the higher-resolution models. the southern hemisphere flow is weak, and in both hemispheres horizontal momentum fluxes are severely underestimated. the systematic errors of the T42, T63 and T106 models are quite similar to each other in the extratropical troposphere. Errors at these higher resolutions resemble the observed difference (in zonal-mean wind, temperature and eddy fluxes) between diagnostics in the northern hemisphere winter and southern hemisphere winter, suggesting that orographic forcing in this version of the ECMWF model is inadequate, despite the inclusion of envelope orography. In the extratropical stratosphere, the behaviours of the T21 and T42 models resemble each other, both having a cold polar bias, apparently associated with inadequate dynamical heating and therefore relaxation to radiative equilibrium. This in turn is related to insufficient Rossby wave focusing into the polar vortex at T21 and T42. the T63 and T106 resolution integrations have much smaller stratospheric cold-pole biases. In the tropics, there are serious systematic errors at all resolutions; however, some of these mean errors increase with increasing resolution. These include the global divergent and nondivergent wind errors, and more regional simulations such as the monsoon flow, where simulation of diabatic heating associated with convective activity is crucial. Since the local values of moisture flux convergence at T106 are effectively much noisier than the larger-scale values of such fluxes used to drive the convection scheme at T21, it is speculated that diabatic heating fields are more likely to project onto the relevant tropical meteorological modes at low model resolution. On the other hand, it is shown that the ability to resolve local orographic features is important in accurately simulating local tropical precipitation maxima over land. Despite having smaller systematic errors in the northern hemisphere, 10-day mean T21 model anomaly correlation coefficient scores were worse than those of higher-resolution models, at least up to day 20. However, there was no indication that the higher-resolution models had significantly different extended-range skill characteristics. On the other hand, the increase of tropical systematic error with increasing horizontal resolution may indicate that the potential of higher-resolution models in extended-range prediction may be underestimated in this study. the asymptotic spread between forecasts initialized 24 hours apart indicated that all models substantially underestimated low-frequency variability (by up to 50% in the extended summer period). Bearing in mind the computational burden of longer timescale integrations with complex numerical models of the atmosphere, the evidence presented in this paper suggests that the T106 resolution may be unnecessarily high for both extended-range forecasting, and for climate simulation studies. However, at present, the cost of integrating at T63 resolution may also be excessive for many climate studies. It would appear from our analysis, that in the troposphere the behaviour of the T42 model is comparable with the higher-resolution models, and is a satisfactory compromise for many purposes, particularly bearing in mind the impact of resolution on tropical systematic errors. However, it would appear that the extreme sensitivity of the 1985/86 ECMWF model climate drift to resolution in the range between T21 and T42, and the apparent inability of the ECMWF T21 model to simulate the correct internal nonlinear dynamics of the extratropics, make questionable its use for climate studies at resolution lower than T42.

A coupled ocean-atmosphere general circulation model was used to perform multicentennial climate simulations of the Eemian interglacial and the subsequent glacial inception. The simulations are performed as equilibrium experiments with orbital parameters and greenhouse gas concentrations set to values of 125000 and 115000 years before present (BP). These dates represent periods with enhanced and weakened seasonal cycles of insolation on the northern hemisphere. Significant changes in seasonal temperatures are simulated in particular for the continental areas of the northern hemisphere. Comparisons with pollen-based reconstructions of European temperatures show that the model simulates realistic spatial temperature patterns for the warm phase of the Eemian. For 115 000 years BP, the reduction in summer insolation leads to a perennial snow coverage over parts of North America, which is continuously expanding. Together with a continuous increase of Arctic sea ice volume, this results in a long-term cooling trend. Consistent with geological records, the snow accumulation starts in north-eastern Canada. In this region, southward winds transport cold Arctic air onto the continent.