A climate change simulation starting from 1935

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.     

The Tornquist Zone, a north east inclining lithospheric transition at the south western margin of the Baltic Shield: Revealed through a nonlinear teleseismic tomographic inversion

From July 1996 to August 1997 the TOR project operated 130 seismographs in North Germany, Denmark and South Sweden, with the aim of collecting signals from local, regional and teleseismic earthquakes. This data set is particularly interesting since the seismic antenna crosses the most significant geological boundary in Europe, the Tornquist Zone, which in the northern part is the border between the Baltic Shield and the younger European lithosphere. Previous studies have shown significant physical changes in the crust and upper mantle across this transition zone, including two independent teleseismic tomographic studies of the TOR data set. But these two studies disagree on the orientation of the slope of the transition. Both studies used an iterative linearized inversion method. We will in this work Preprint submitted to Elsevier Science 27 July 2005 present an inversion based on Bayesian statistics, where the solution space is examined in order to study a very large number of tomographic solutions and to examine the solution uniqueness and uncertainty. The method is applied to measurements of 3345 relative teleseismic P-phase travel times from 48 teleseismic earthquakes with good azimuthal coverage with respect to the great circle arc of the TOR array. We find the lithospheric transition to be a north east inclination of around 30° to 45° off vertical.     

Simulation of the influence of solar radiation variations on the global climate with an ocean-atmosphere general circulation model

 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. Received: 14 October 1996 / Accepted: 9 May 1997     

Climate variability/change and attitude to adaptation technologies: a pilot study among selected rural farmers’ communities in Nigeria

Understanding climate variability and change is essential for designing adaptation policies and strategies to deal with the impacts of climate change on the agricultural sector. This Paper aims at assessing climate variability/change, the perception of rural farmers on climate change and preferred  adaptation strategies among the farmers in some selected farming communities in Nigeria. The study thus used both meteorology data and social survey, to examine variability/change in climate and factors determining the adaptation techniques adopts by rural farmers. The results show a relatively uniform temperatures and some seasonal variations in recent years (diurnal range of temperature is about 10 °C) but the rainfall shows much more seasonal variations. The rainfall has relatively undeviating trend from 1981 to 1996 but the trend appears to be upwards from the year 1997 to 2010. About 72.8% participants responded in the affirmative that climate is changing but there appears to be a significant relationship between the length of farming experiences and farmers’ perceptions of climate change adaptation techniques. Water-related (about 53%) and nutrient related (about 52%) technologies appear to have a high preference among the farmers. The major driver that determines farmers’ preference for climate change adaptation techniques is their incomes and experiences.