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  • 1
    Monograph available for loan
    Monograph available for loan
    Comparisation of medium range forecasts made with models using spectral or finite difference techniques in the horizontal (1981)
    Bracknell : ECMWF
    Associated volumes
    Details Availability
    Call number: MOP Per 409(23)
    In: Technical report
    Type of Medium: Monograph available for loan
    Pages: III, 96 S.
    Series Statement: Technical report / European Centre for Medium Range Weather Forecasts 23
    URL: http://www.ecmwf.int/publications/library/ecpublications/_pdf/tr/tr23.pdf
    Location: MOP - must be ordered
    Branch Library: GFZ Library
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  • 2
    Electronic Resource
    Electronic Resource
    Climate response to smoke from the burning oil wells in Kuwait (1991)
    [s.l.] : Nature Publishing Group
    Nature 351 (1991), S. 367-371 
    Details
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] The response of the global climate system to smoke from burning oil wells in Kuwait is investigated in a series of numerical experiments using a coupled atmosphere–ocean general circulation model with an interactive soot transport model and extended radiation scheme. The results show a ...
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1038/351367a0
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  • 3
    Electronic Resource
    Electronic Resource
    Monte Carlo climate change forecasts with a global coupled ocean-atmosphere model (1994)
    Springer
    Climate dynamics 10 (1994), S. 1-19 
    Details
    ISSN: 1432-0894
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract Four time-dependent greenhouse warming experiments were performed with the same global coupled atmosphere-ocean model, but with each simulation using initial conditions from different “snapshots” of the control run climate. The radiative forcing — the increase in equivalent CO2 concentrations from 1985–2035 specified in the Intergovernmental Panel on Climate Change (IPCC) scenario A — was identical in all four 50-year integrations. This approach to climate change experiments is called the Monte Carlo technique and is analogous to a similar experimental set-up used in the field of extended range weather forecasting. Despite the limitation of a very small sample size, this approach enables the estimation of both a mean response and the “between-experiment” variability, information which is not available from a single integration. The use of multiple realizations provides insights into the stability of the response, both spatially, seasonally and in terms of different climate variables. The results indicate that the time evolution of the global mean warming signal is strongly dependent on the initial state of the climate system. While the individual members of the ensemble show considerable variation in the pattern and amplitude of near-surface temperature change after 50 years, the ensemble mean climate change pattern closely resembles that obtained in a 100-year integration performed with the same model. In global mean terms, the climate change signals for near surface temperature, the hydrological cycle and sea level significantly exceed the variability among the members of the ensemble. Due to the high internal variability of the modelled climate system, the estimated detection time of the global mean temperature change signal is uncertain by at least one decade. While the ensemble mean surface temperature and sea level fields show regionally significant responses to greenhouse-gas forcing, it is not possible to identify a significant response in the precipitation and soil moisture fields, variables which are spatially noisy and characterized by large variability between the individual integrations.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00210333
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  • 4
    Electronic Resource
    Electronic Resource
    The North Atlantic Oscillation as an indicator for greenhouse-gas induced regional climate change (1999)
    Springer
    Climate dynamics 15 (1999), S. 953-960 
    Details
    ISSN: 1432-0894
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract The time-dependent variability of the North Atlantic Oscillation is examined in an observational data set and several model data sets with greenhouse-gas-induced external forcings. The index of the North Atlantic Oscillation state is derived from the time series of mean latitudinal position and central pressure of the Icelandic Low and the Azores High considering the synchronous meridional shifting of the two pressure systems. While the North Atlantic Oscillation is characterized by intensive interannual variability, the low-pass filtered index time series shows a decadal component with a time scale of about 50 y within almost 120 y of observation. Since the late 1960s we observe a positive trend and a transition to a strong positive phase of the phenomenon indicative of a pre-dominantly zonal circulation over the North Atlantic. This trend occurs equally in the observations and all examined model data sets with increasing greenhouse-gas-concentration and atmosphere-ocean coupling. We find statistical evidence that the radiative forcing by increasing CO2 concentration has a significant influence on the simulated variability of the North Atlantic Oscillation on time scales of 60 y and longer, independent of the initial conditions and the model version. The seasonal response is strongest in late summer and winter. The interannual variability of the North Atlantic Oscillation states on time scales less than 10 y decreases synchronously with the positive trend of its decadal-mean state implying a stabilization of its present and future zonal state.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s003820050324
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  • 5
    Electronic Resource
    Electronic Resource
    Simulation of the influence of solar radiation variations on the global climate with an ocean-atmosphere general circulation model (1997)
    Springer
    Climate dynamics 13 (1997), S. 757-767 
    Details
    ISSN: 1432-0894
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract.  Two simulations with a global coupled ocean-atmosphere circulation model have been carried out to study the potential impact of solar variability on climate. The Hoyt and Schatten estimate of solar variability from 1700 to 1992 has been used to force the model. Results indicate that the near-surface temperature simulated by the model is dominated by the long periodic solar fluctuations (Gleissberg cycle), with global mean temperatures varying by about 0.5 K. Further results indicate that solar variability and an increase in greenhouse gases both induce to a first approximation a comparable pattern of surface temperature change, i.e., an increase of the land-sea contrast. However, the solar-induced warming pattern in annual means and summer is more centered over the subtropics, compared to a more uniform warming associated with the increase in greenhouse gases. The observed temperature rise over the most recent 30 and 100 years is larger than the trend in the solar forcing simulation during the same period, indicating a strong likelihood that, if the model forcing and response is realistic, other factors have contributed to the observed warming. Since the pattern of the recent observed warming agrees better with the greenhouse warming pattern than with the solar variability response, it is likely that one of these factors is the increase of the atmospheric greenhouse gas concentration.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s003820050196
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  • 6
    Electronic Resource
    Electronic Resource
    The seasonal cycle in coupled ocean-atmosphere general circulation models (2000)
    Springer
    Climate dynamics 16 (2000), S. 775-787 
    Details
    ISSN: 1432-0894
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract  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.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s003820000081
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  • 7
    Electronic Resource
    Electronic Resource
    Periodically synchronously coupled integrations with the atmosphere-ocean general circulation model ECHAM3/LSG (1998)
    Springer
    Climate dynamics 14 (1998), S. 249-266 
    Details
    ISSN: 1432-0894
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract  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.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s003820050221
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  • 8
    Electronic Resource
    Electronic Resource
    Monte Carlo climate change forecasts with a global coupled ocean-atmosphere model (1994)
    Springer
    Climate dynamics 10 (1994), S. 1-19 
    Details
    ISSN: 1432-0894
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract. Four time-dependent greenhouse warming experiments were performed with the same global coupled atmosphere-ocean model, but with each simulation using initial conditions from different ”snapshots" of the control run climate. The radiative forcing – the increase in equivalent CO2 concentrations from 1985–2035 specified in the Intergovernmental Panel on Climate Change (IPCC) scenario A – was identical in all four 50-year integrations. This approach to climate change experiments is called the Monte Carlo technique and is analogous to a similar experimental set-up used in the field of extended range weather forecasting. Despite the limitation of a very small sample size, this approach enables the estimation of both a mean response and the ”between-experiment" variability, information which is not available from a single integration. The use of multiple realizations provides insights into the stability of the response, both spatially, seasonally and in terms of different climate variables. The results indicate that the time evolution of the global mean warming signal is strongly dependent on the initial state of the climate system. While the individual members of the ensemble show considerable variation in the pattern and amplitude of near-surface temperature change after 50 years, the ensemble mean climate change pattern closely resembles that obtained in a 100-year integration performed with the same model. In global mean terms, the climate change signals for near surface temperature, the hydrological cycle and sea level significantly exceed the variability among the members of the ensemble. Due to the high internal variability of the modelled climate system, the estimated detection time of the global mean temperature change signal is uncertain by at least one decade. While the ensemble mean surface temperature and sea level fields show regionally significant responses to greenhouse-gas forcing, it is not possible to identify a significant response in the precipitation and soil moisture fields, variables which are spatially noisy and characterized by large variability between the individual integrations.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s003820050032
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  • 9
    Electronic Resource
    Electronic Resource
    A climate change simulation starting from 1935 (1995)
    Springer
    Climate dynamics 11 (1995), S. 71-84 
    Details
    ISSN: 1432-0894
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract Due to restrictions in the available computing resources and a lack of suitable observational data, transient climate change experiments with global coupled ocean-atmosphere models have been started from an initial state at equilibrium with the present day forcing. The historical development of greenhouse gas forcing from the onset of industrialization until the present has therefore been neglected. Studies with simplified models have shown that this “cold start” error leads to a serious underestimation of the anthropogenic global warming. In the present study, a 150-year integration has been carried out with a global coupled ocean-atmosphere model starting from the greenhouse gas concentration observed in 1935, i.e., at an early time of industrialization. The model was forced with observed greenhouse gas concentrations up to 1985, and with the equivalent C02 concentrations stipulated in Scenario A (“Business as Usual”) of the Intergovernmental Panel on Climate Change from 1985 to 2085. The early starting date alleviates some of the cold start problems. The global mean near surface temperature change in 2085 is about 0.3 K (ca. 10%) higher in the early industrialization experiment than in an integration with the same model and identical Scenario A greenhouse gas forcing, but with a start date in 1985. Comparisons between the experiments with early and late start dates show considerable differences in the amplitude of the regional climate change patterns, particularly for sea level. The early industrialization experiment can be used to obtain a first estimate of the detection time for a greenhouse-gas-induced near-surface temperature signal. Detection time estimates are obtained using globally and zonally averaged data from the experiment and a long control run, as well as principal component time series describing the evolution of the dominant signal and noise modes. The latter approach yields the earliest detection time (in the decade 1990–2000) for the time-evolving near-surface temperature signal. For global-mean temperatures or for temperatures averaged between 45°N and 45°S, the signal detection times are in the decades 2015–2025 and 2005–2015, respectively. The reduction of the “cold start” error in the early industrialization experiment makes it possible to separate the near-surface temperature signal from the noise about one decade earlier than in the experiment starting in 1985. We stress that these detection times are only valid in the context of the coupled model's internally-generated natural variability, which possibly underestimates low frequency fluctuations and does not incorporate the variance associated with changes in external forcing factors, such as anthropogenic sulfate aerosols, solar variability or volcanic dust.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00211674
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  • 10
    Electronic Resource
    Electronic Resource
    A climate change simulation starting from 1935 (1995)
    Springer
    Climate dynamics 11 (1995), S. 71-84 
    Details
    ISSN: 1432-0894
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract. Due to restrictions in the available computing resources and a lack of suitable observational data, transient climate change experiments with global coupled ocean-atmosphere models have been started from an initial state at equilibrium with the present day forcing. The historical development of greenhouse gas forcing from the onset of industrialization until the present has therefore been neglected. Studies with simplified models have shown that this "cold start" error leads to a serious underestimation of the anthropogenic global warming. In the present study, a 150-year integration has been carried out with a global coupled ocean-atmosphere model starting from the greenhouse gas concentration observed in 1935, i.e., at an early time of industrialization. The model was forced with observed greenhouse gas concentrations up to 1985, and with the equivalent CO2 concentrations stipulated in Scenario A ("Business as Usual") of the Intergovernmental Panel on Climate Change from 1985 to 2085. The early starting date alleviates some of the cold start problems. The global mean near surface temperature change in 2085 is about 0.3 K (ca. 10%) higher in the early industrialization experiment than in an integration with the same model and identical Scenario A greenhouse gas forcing, but with a start date in 1985. Comparisons between the experiments with early and late start dates show considerable differences in the amplitude of the regional climate change patterns, particularly for sea level. The early industrialization experiment can be used to obtain a first estimate of the detection time for a greenhouse-gas-induced near-surface temperature signal. Detection time estimates are obtained using globally and zonally averaged data from the experiment and a long control run, as well as principal component time series describing the evolution of the dominant signal and noise modes. The latter approach yields the earliest detection time (in the decade 1990–2000) for the time-evolving near-surface temperature signal. For global-mean temperatures or for temperatures averaged between 45° N and 45° S, the signal detection times are in the decades 2015–2025 and 2005–2015, respectively. The reduction of the "cold start" error in the early industrialization experiment makes it possible to separate the near-surface temperature signal from the noise about one decade earlier than in the experiment starting in 1985. We stress that these detection times are only valid in the context of the coupled model's internally-generated natural variability, which possibly underestimates low frequency fluctuations and does not incorporate the variance associated with changes in external forcing factors, such as anthropogenic sulfate aerosols, solar variability or volcanic dust.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s003820050061
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