A new statistic for picking out non-Gaussianity in the CMB     

Alex Lewin  reas Albrecht  João Magueijo 《Monthly notices of the Royal Astronomical Society》1999,302(1):131-138

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Paleolimnological investigation of the effects of post-1970 reductions of acidic deposition on an acidified Adirondack lake     

Sheena P. Majewski  B.F. Cumming 《Journal of Paleolimnology》1999,21(2):207-213

A 40-cm sediment core from Big Moose Lake (Adirondack Mountains, New York, U.S.A.) was analyzed for recent changes in chrysophyte composition of chrysophyte species to assess if legislated reductions of sulphur emissions have resulted in changes in biological composition and inferred lakewater pH in this lake. This core, taken in September 1994, had a record of stratigraphic changes in chrysophyte assemblages remarkably similar to those in 210Pb-dated sediment cores taken in 1983 and 1988. Abrupt changes in chrysophyte stratigraphy were used to date the newest sediment core by stratigraphic correlation. We observed relatively constant composition of chrysophyte species and inferred-pH values in post-1970 sediments, which suggests that there has been little change in lakewater pH values despite the reductions in sulfate deposition since 1970 in the Adirondacks. These results are consistent with recent monitoring measurements in the Adirondacks. Further research is necessary to ascertain the applicability of these findings to other lakes in the Adirondacks and to determine the reasons for the lack of recovery.  相似文献   

Low-Cloud Feedbacks from Cloud-Controlling Factors: A Review     

Stephen A. Klein  Alex Hall  Joel R. Norris  Robert Pincus 《Surveys in Geophysics》2017,38(6):1307-1329

The response to warming of tropical low-level clouds including both marine stratocumulus and trade cumulus is a major source of uncertainty in projections of future climate. Climate model simulations of the response vary widely, reflecting the difficulty the models have in simulating these clouds. These inadequacies have led to alternative approaches to predict low-cloud feedbacks. Here, we review an observational approach that relies on the assumption that observed relationships between low clouds and the “cloud-controlling factors” of the large-scale environment are invariant across time-scales. With this assumption, and given predictions of how the cloud-controlling factors change with climate warming, one can predict low-cloud feedbacks without using any model simulation of low clouds. We discuss both fundamental and implementation issues with this approach and suggest steps that could reduce uncertainty in the predicted low-cloud feedback. Recent studies using this approach predict that the tropical low-cloud feedback is positive mainly due to the observation that reflection of solar radiation by low clouds decreases as temperature increases, holding all other cloud-controlling factors fixed. The positive feedback from temperature is partially offset by a negative feedback from the tendency for the inversion strength to increase in a warming world, with other cloud-controlling factors playing a smaller role. A consensus estimate from these studies for the contribution of tropical low clouds to the global mean cloud feedback is 0.25 ± 0.18 W m^?2 K^?1 (90% confidence interval), suggesting it is very unlikely that tropical low clouds reduce total global cloud feedback. Because the prediction of positive tropical low-cloud feedback with this approach is consistent with independent evidence from low-cloud feedback studies using high-resolution cloud models, progress is being made in reducing this key climate uncertainty.  相似文献   

A UML‐based Representation of Spatio‐Temporal Evolution in Road Network Data     

Alex Lohfink  Duncan McPhee  Mark Ware 《Transactions in GIS》2010,14(6):853-872

Geographic features change over time, this change being the result of some kind of event. Most database systems used in GIS are relational in nature, capturing change by exhaustively storing all versions of data, or updates replace previous versions. This stems from the inherent difficulty of modelling geographic objects and associated data in relational tables, and this is compounded when the necessary time dimension is introduced to represent how these objects evolve. This article describes an object‐oriented (OO) spatio‐temporal conceptual data model called the Feature Evolution Model (FEM), which can be used for the development of a spatio‐temporal database management system (STDBMS). Object versioning techniques developed in the fields of Computer Aided Design (CAD) and engineering design are utilized in the design. The model is defined using the Unified Modelling Language (UML), and exploits the expressiveness of OO technology by representing both geographic entities and events as objects. Further, the model overcomes the limitations inherent in relational approaches in representing aggregation of objects to form more complex, compound objects. A management object called the evolved feature maintains a temporally ordered list of references to features thus representing their evolution. The model is demonstrated by its application to road network data.  相似文献