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Meteorological and oceanographic data from ships of opportunity are the largest contributor to the world’s ocean surface database and thus are extensively used to estimate the change in climatic properties over the world’s oceans during the previous 150 years. The importance of these data for climate change studies underscores the need to fully understand the error associated with averages of these data. The sampling error problem is especially acute for ship data due to the fact that ships are moving platforms and, thus, report observations from constantly varying locations with time. This paper develops a theoretical framework for assessing the averaged sampling error associated with monthly, 1°×1° latitude-longitude box averaged ship data. It should be noted that the time-space distribution of ships within the averaging domain strongly affects the sampling error. This is shown in our derivation. The framework developed here can be used to improve upon existing methods for estimating the sampling error associated with three-dimensional box averages of meteorological and oceanographic data obtained from ship records. The framework is complimentary to existing methods of assessing biases and random error due to instrumentation, recording, etc. It is demonstrated mathematically that the uncertainty due to incomplete sampling is primarily a trade off between of the number of observations and their relative locations within the box as well as the inherent time-space correlation structure of the variable of interest. This work differs from other studies in that the three-dimensional interdependence of data is taken into account in deriving an expression for the sampling error. [ABSTRACT FROM AUTHOR]

A crop simulation model must first be capable of representing the actual performance of crops grown in any region before it can be applied to the prediction of climate variability and change impacts. A cropping systems model (CropSyst) simulations of crop productivity in the sub-Saharan Central African (using Cameroon as the case study) region, under the current climate were compared with observed yields of maize, sorghum, groundnut, bambara groundnut and soybean from eight sites. The model produced both over-and-under estimates, but with a mean percentage difference of only –2.8%, ranging from –0.6% to –4.5%. Based on these results, we judged the CropSyst simulations sufficiently reliable to justify use of the model in assessing crop growth vulnerability to climatic changes in Cameroon and else where. [ABSTRACT FROM AUTHOR]

Across the Greenland–Scotland ridge there is a continuous flow of cold dense water, termed ‘overflow’, from the Nordic seas to the Atlantic Ocean. This is a main contributor to the production of North Atlantic Deep Water that feeds the lower limb of the Atlantic meridional overturning circulation, which has been predicted to weaken as a consequence of climate change. The two main overflow branches pass the Denmark Strait and the Faroe Bank channel. Here we combine results from direct current measurements in the Faroe Bank channel for 1995–2005 with an ensemble hindcast experiment for 1948–2005 using an ocean general circulation model. For the overlapping period we find a convincing agreement between model simulations and observations on monthly to interannual timescales. Both observations and model data show no significant trend in volume transport. In addition, for the whole 1948–2005 period, the model indicates no persistent trend in the Faroe Bank channel overflow or in the total overflow transport, in agreement with the few available historical observations. Deepening isopycnals in the Norwegian Sea have tended to decrease the pressure difference across the Greenland–Scotland ridge, but this has been compensated for by the effect of changes in sea level. In contrast with earlier studies, we therefore conclude that the Faroe Bank channel overflow, and also the total overflow, did not decrease consistently from 1950 to 2005, although the model does show a weakening total Atlantic meridional overturning circulation as a result of changes south of the Greenland–Scotland ridge. [ABSTRACT FROM AUTHOR]

Dominating wind patterns around Norway may change due to climate warming. This could affect transport of polluted air masses and precipitation. Here, we study relations between reactive nitrogen wet deposition and air mass transport during summer and winter expressed in the form of climate indices, at seven sites in Southern Norway for the period 1980-2005. Atmospheric nitrate concentrations decreased with 0 to 50% in the period, particularly at sites with little precipitation, and mostly during 1990-2005. For comparison, reported reductions in emissions of oxidised nitrogen in Europe in 1989-2003 were 23%. Climate indices explained up to 36% of the variation in winter nitrate deposition at the western and northern sites - and also explained 60% of the variation in winter precipitation (R=0.77). This suggests that the variation in nitrate wet deposition is closely related to variation in precipitation, and that the climate indices seem to also partly control the variation in atmospheric nitrate concentrations (R=-0.45 at coastal sites). At the coastal sites, local air temperature was highly correlated (R=0.84) with winter nitrate deposition, suggesting that warm, humid winter weather results in increased wet nitrate deposition. For ammonia the pattern was similar, but this compound is more influenced by local sources. Expected severe increase in precipitation in western and northern regions as a consequence of climate change suggest that nitrogen deposition in these areas will increase under global warming if emissions are held constant. [ABSTRACT FROM AUTHOR]

The role of meteorology, hydrology and atmospheric deposition on the temporal pattern of SO4 and NO3 concentrations was investigated for three streams draining alpine catchments in Northern Italy. The study sites lie on a gradient of atmospheric fluxes of SO4 and NO3 (from about 50 to 80 meqm-2 y-1, and from 40 to 90 meqm-2 y-1, respectively). As a consequence of the increasing N input, the three catchments are also representative of aggrading levels of N saturation. Different methods of statistical analysis were applied to monthly data for the period 1997-2005 to identify which variables (temperature, precipitation, hydrology, SO4 and NO3 deposition) were the main predictors of water chemistry and its change in time. Hydrological changes and snow cover proved to be the main confounding factors in the response to atmospheric deposition in the River Masino catchment. Its particular characteristics (small catchment area, rapid flushing during runoff and thin soil cover) meant that this site responded without a significant delay to SO4 deposition decrease. It also showed a clear seasonal pattern of NO3 concentration, in response to hydrology and biological uptake in the growing season. The selected driving variables failed to model the water chemistry at the other study sites. Nevertheless, temperature, especially extreme values, turned out to be important in both SO4 and NO3 export from the catchments. This result might be largely explained by the effect of warm periods on temperature-dependent processes such as mineralization, nitrification and S desorption. Our findings suggest that surface waters in the alpine area will be extremely sensitive to a climate warming scenario: higher temperatures and increasing frequency of drought could exacerbate the effects of high chronic N deposition. [ABSTRACT FROM AUTHOR]

A 10 000-yr unforced simulation with the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mark 2 coupled global climatic model has been used to investigate the occurrence of heat waves over the globe. Results are presented for both seasonal (summer mean) and daily heat waves. Geographical distributions of the occurrence rates of these heat waves are shown for various magnitudes of surface temperature anomalies. The heat waves have specific geographical preferences with regions where relatively frequent, intense, and long-lasting heat waves occur. Time series over all 10 000 yr of the heat waves for the selected model grid boxes illustrate the differing temporal variabilities at these locations, as well as identifying the occurrences of extreme heat waves. To this end, the observed European heat wave of 2003 was simulated remarkably well in its overall characteristics; it occurs once in this simulation. Heat waves for various continental locations are shown to occur as isolated spatial and temporal events, and not as part of larger-scale systems over continental-size domains, suggesting stochastic forcing as a contributor to the initiation of the heat waves. Regional plots of selected heat waves at monthly intervals illustrated the considerable spatial variability, progression, and variation in the intensity of the heat waves. Comparison of year-long daily surface temperature anomalies for heat-wave years for simulated and observed conditions at individual model grid boxes indicated substantial agreement, while spatial plots permitted the progress of a short-term heat wave over the United States to be followed. Multidecadal time series plots of intense heat waves also showed basic similarities between the simulation and observations, despite the brevity of the latter. The simulated time series suggest that more extreme heat waves than currently are observed, owing to the brevity of the observations, may be a possibility as a consequence solely of natural variability. An examination of the physical processes associated with a heat wave showed mutually consistent climatic relationships, such that a heat wave was associated with reduced rainfall and consequently reduced soil moisture content, evaporation, and cloud cover, and increased insolation at the surface. These combined changes created the surface temperature increase intrinsic to the heat wave. All heat waves examined for different regions experienced negative rainfall anomalies prior to a heat wave. The cause of these rainfall anomalies was not readily apparent. While an ENSO influence on heat waves is shown to exist in the simulation, not all ENSO events produce heat waves, suggesting that stochastic influences may determine when a major heat wave occurs in conjunction with these events. The limitations of the adequacy of the model ENSO may, however, have had an influence in this regard. [ABSTRACT FROM AUTHOR]

The article discusses the photographic documentation of poor observation sites within the U.S. Historical Climate Reference Network (USHCN) with respect to monitoring long-term surface air temperature trends. The objectives of the USHCN are outlined. The primary source of surface observations used to construct the long-term global surface temperature analyses has been National Oceanic and Atmospheric Administration stations, which include first-order stations and a subset of NOAA Cooperative Observer Program sites that compose the USHCN. The COOP Network has long served as the main climate observation network in the U.S., with once daily measurements of temperature, precipitation and sometimes snowfall made by depth volunteers using equipment supplied and maintained by NOAA.