Effective and Equitable Dissemination of Seasonal-to-Interannual Climate Forecasts: Policy Implications from the Peruvian Fishery during El Niño 1997–98

The development of seasonal-to-interannual climate predictions has spurred widespread claims that the dissemination of such forecasts will yield benefits for society. Based on the use as well as non-use of forecasts in the Peruvian fishery during the 1997–98 El Niño event, weidentify: (1) potential constraints on the realization of benefits, such aslimited access to and understanding of information, and unintended reactions; (2) theneed for an appropriately detailed definition of societal benefit, considering whose welfare counts as a benefit among groups such as labor, industry, consumers, citizens of different regions, and future generations.We argue that consideration of who benefits, and an understanding of potential socioeconomic constraints and how they might be addressed, should be brought to bear on forecast dissemination choices. We conclude with examples of relevant dissemination choices made using this process.     

Origin of the northern Indus Fan and Murray Ridge, Northern Arabian Sea: interpretation from seismic and magnetic imaging

The nature and origin of the sediments and crust of the Murray Ridge System and northern Indus Fan are discussed. The uppermost unit consists of Middle Miocene to recent channel–levee complexes typical of submarine fans. This unit is underlain by a second unit composed of hemipelagic to pelagic sediments deposited during the drift phase after the break-up of India–Seychelles–Africa. A predrift sequence of assumed Mesozoic age occurring only as observed above basement ridges is composed of highly consolidated rocks. Different types of the acoustic basement were detected, which reflection seismic pattern, magnetic anomalies and gravity field modeling indicate to be of continental character. The continental crust is extremely thinned in the northern Indus Fan, lacking a typical block-faulted structure. The Indian continent–ocean transition is marked on single MCS profiles by sequences of seaward-dipping reflectors (SDR). In the northwestern Arabian Sea, the Indian plate margin is characterized by several phases of volcanism and deformation revealed from interpretation of multichannel seismic profiles and magnetic anomalies. From this study, thinned continental crust spreads between the northern Murray Ridge System and India underneath the northern Indus Fan.     

Size Scaling of Cross Correlation Between Multiple Variables

Reservoir models have large uncertainty because of spatial variability and limited sample data. The ultimate aim is to use simultaneously all available data sources to reduce uncertainty and provide reliable reservoir models for resource assessment and flow simulation. Seismic impedance or some other attribute provides a key source of data for reservoir modeling. These seismic data are at a coarser scale than the hard well data and it not an exact measurement of facies proportions or porosity. A requirement for data integration is the cross-covariance between the well and seismic data.The size-scaling behavior of the cross correlation for different measurement scales was nvestigated. The size-scaling relationship is derived theoretically and validated by numerical studies (including an example with real data). The limit properties of the cross-correlation coefficient when the averaging volume becomes large is shown. After some averaging volume, the volume-dependent cross-correlation coefficient reaches a limit value. This plateau value is controlled mainly by the large-scale behavior of the cross and direct variograms.The cross correlation can increase or decrease with volume support depending on the relative importance of long- and short-scale covariance structures. If the direct and cross variograms are proportional, there is no change in the cross correlation as the averaging volume changes. Our study shows that the volume-dependent cross-correlation coefficient is sensitive to the shape of the cross variogram and differences between the direct variograms of the well data and seismic data.     

Variability and climate sensitivity of fast ice extent in the north-eastern Kara Sea

This work investigates the temporal and spatial variation of shore-fast ice extent in the north-eastern part of the Kara Sea during 1953-1990 and its sensitivity to interannual variability of the regional climate. The area of fast ice in spring months shows a bimodal distribution. This indicates the existence of two different regimes of fast ice formation driven by the system of prevailing winds. The westward wind transport during the cold season gives larger fast ice extent while the eastward wind transport suppresses the expansion of fast ice. There is a significant correlation (ca. −0.55) between the average winter temperature and the area of fast ice. Linear trends for time records of shore-fast ice area in spring show a decrease during 1953-1990. This decrease is most pronounced in April: the mean fast ice area in April is 12% lower in 1988-1990 compared to 1953-55. A comparison of fast ice regimes for two particular years–1979 and 1985–revealed a significant influence of cyclone activity on fast ice development over the course of the cold season. It is shown that partial break-ups of fast ice in spring 1985 are associated with the passage of cyclones across the area of fast ice.     

Single-grain zircon dating of the metamorphic and granitic rocks from the Biscayarhalvøya-Holtedahlfonna zone, north-west Spitsbergen

The Biscayarhalvøya-Holtedahlfonna zone (BHZ) in north-western Spitsbergen is a north-south trending, narrow horst, with crystalline basement rocks exposed under a Devonian unconformity. Previous K-Ar, ⁴⁰Ar/³⁹Ar and Rb-Sr analyses have confirmed the occurrence of Caledonian thermal events, and Grenvillian ages have been obtained by conventional zircon U-Pb and single-zircon Pb evaporation methods. A total of 55 zircon grains from three samples (an augen metagranite, a micaceous schist and a granitic neosome of migmatite) have been analysed by the single-zircon Pb evaporation method. The grains with the age range of ca. 950-1100 My (million years) are the major component in all three samples, suggesting tectono-thermal activity in that period. The detrital versus resorption orgin of the rounded shapes of these grains from the granitic neosome is not clear yet. Therefore, the ages of the migmatization and of the sedimentary protoliths are not concluded. The youngest presumed detrital grain from the granitic neosome is 1060 My old. The metagranite, cutting the Richarddalen unit, yielded grains with an age of ca. 950 Mya. A granite dyke with an age range of 955-968 My cuts the Biscayarhuken unit in the northern Liefdefjorden area. These indicate the sedimentary protoliths of the Richarddalen and Biscayarhuken units are pre-Neoproterozoic. The youngest detrital zircon ages of ca. 940 My indicate Neoproterozoic sedimentary protoliths of the Solanderfjellet micaceous schists. A significant population of zircon grains with an age range of 1600-1900 My in all three samples suggests a wide exposure of these rocks in the source areas during Meso- and Neoproterozoic times. Several Archean ages have also been obtained. The results are generally conformable with those obtained from north-western Spitsbergen.     

Stepwise Conditional Transformation for Simulation of Multiple Variables

Most geostatistical studies consider multiple-related variables. These relationships often show complex features such as nonlinearity, heteroscedasticity, and mineralogical or other constraints. These features are not handled by the well-established Gaussian simulation techniques. Earth science variables are rarely Gaussian. Transformation or anamorphosis techniques make each variable univariate Gaussian, but do not enforce bivariate or higher order Gaussianity. The stepwise conditional transformation technique is proposed to transform multiple variables to be univariate Gaussian and multivariate Gaussian with no cross correlation. This makes it remarkably easy to simulate multiple variables with arbitrarily complex relationships: (1) transform the multiple variables, (2) perform independent Gaussian simulation on the transformed variables, and (3) back transform to the original variables. The back transformation enforces reproduction of the original complex features. The methodology and underlying assumptions are explained. Several petroleum and mining examples are used to show features of the transformation and implementation details.