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Climate Datasets (climate + dataset)
Selected AbstractsThe tick Ixodes ricinus: distribution and climate preferences in the western PalaearcticMEDICAL AND VETERINARY ENTOMOLOGY, Issue 2 2006A. ESTRADA-PEÑA Abstract In this study, multivariate spatial clustering on monthly normalized difference vegetation index (NDVI) maps is used to classify ecological regions over the western Palaearctic. This classification is then used to delineate the distribution and climate preferences of populations (clades) of the tick Ixodes ricinus L. (Acari: Ixodidae) from a geographically extensive dataset of tick records and a gridded 2.5-km resolution climate dataset. Using monthly layers of the NDVI, regions of similar ecological attributes were defined and nine populations with significant differences in critical climate parameters (P < 0.005) were detected. Grouping of tick records according to other categories, such as political divisions, a 4°× 4° grid overlying the study area, or the CORINE) and USGS) vegetation classification schemes did not provided significantly separated populations (P= 0.094,0.304). Factor analysis and hierarchical tree clustering provided an ecological overview of these tick clades: two Mediterranean and one Scandinavian (western) clades are clearly separated from a node that includes clades of different parts of central Europe and the British Isles, with contrasting affinities between the different clades. The capture records of these ecologically separated clades produce a clear bias when bioclimate envelope modelling is applied to the mapping of habitat suitability for the tick in the western Palaearctic. The best-performing methods (Cohen's kappa = 0.834,0.912) use partial models developed with data from each ecoregion, which are then overlapped over the region of study. It is concluded that the use of ecologically derived ecoregions is an objective step in assessing the presence of ecologically different clades, and provides a guide in the development of data partitioning for habitat suitability modelling. [source] Evaluating the impacts of climate and elevated carbon dioxide on tropical rainforests of the western Amazon basin using ecosystem models and satellite dataGLOBAL CHANGE BIOLOGY, Issue 1 2010HIROFUMI HASHIMOTO Abstract Forest inventories from the intact rainforests of the Amazon indicate increasing rates of carbon gain over the past three decades. However, such estimates have been questioned because of the poor spatial representation of the sampling plots and the incomplete understanding of purported mechanisms behind the increases in biomass. Ecosystem models, when used in conjunction with satellite data, are useful in examining the carbon budgets in regions where the observations of carbon flows are sparse. The purpose of this study is to explain observed trends in normalized difference vegetation index (NDVI) using climate observations and ecosystem models of varying complexity in the western Amazon basin for the period of 1984,2002. We first investigated trends in NDVI and found a positive trend during the study period, but the positive trend in NDVI was observed only in the months from August to December. Then, trends in various climate parameters were calculated, and of the climate variables considered, only shortwave radiation was found to have a corresponding significant positive trend. To compare the impact of each climate component, as well as increasing carbon dioxide (CO2) concentrations, on evergreen forests in the Amazon, we ran three ecosystem models (CASA, Biome-BGC, and LPJ), and calculated monthly net primary production by changing a climate component selected from the available climate datasets. As expected, CO2 fertilization effects showed positive trends throughout the year and cannot explain the positive trend in NDVI, which was observed only for the months of August to December. Through these simulations, we demonstrated that the positive trend in shortwave radiation can explain the positive trend in NDVI observed for the period from August to December. We conclude that the positive trend in shortwave radiation is the most likely driver of the increasing trend in NDVI and the corresponding observed increases in forest biomass. [source] Interpreting variability in global SST data using independent component analysis and principal component analysisINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 3 2010Seth Westra Abstract Component extraction techniques are used widely in the analysis and interpretation of high-dimensional climate datasets such as global sea surface temperatures (SSTs). Principal component analysis (PCA), a frequently used component extraction technique, provides an orthogonal representation of the multivariate dataset and maximizes the variance explained by successive components. A disadvantage of PCA, however, is that the interpretability of the second and higher components may be limited. For this reason, a Varimax rotation is often applied to the PCA solution to enhance the interpretability of the components by maximizing a simple structure. An alternative rotational approach is known as independent component analysis (ICA), which finds a set of underlying ,source signals' which drive the multivariate ,mixed' dataset. Here we compare the capacity of PCA, the Varimax rotation and ICA in explaining climate variability present in globally distributed SST anomaly (SSTA) data. We find that phenomena which are global in extent, such as the global warming trend and the El Niño-Southern Oscillation (ENSO), are well represented using PCA. In contrast, the Varimax rotation provides distinct advantages in interpreting more localized phenomena such as variability in the tropical Atlantic. Finally, our analysis suggests that the interpretability of independent components (ICs) appears to be low. This does not diminish the statistical advantages of deriving components that are mutually independent, with potential applications ranging from synthetically generating multivariate datasets, developing statistical forecasts, and reconstructing spatial datasets from patchy observations at multiple point locations. Copyright © 2009 Royal Meteorological Society [source] The development of a new set of long-term climate averages for the UKINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 8 2005Matthew Perry Abstract Monthly and annual long-term average datasets of 13 climate variables are generated for the periods 1961,90 and 1971,2000 using a consistent analysis method. Values are produced for each station in the Met Office's observing network and for a rectangular grid of points covering the UK at a horizontal spacing of 1 km. The variables covered are mean, maximum, minimum, grass minimum and soil temperature, days of air and ground frost, precipitation, days with rain exceeding 0.2 and 1 mm, sunshine, and days with thunder and snow cover. Gaps in the monthly station data are filled with estimates obtained via regression relationships with a number of well-correlated neighbours, and long-term averages are then calculated for each site. Gridded datasets are created by inverse-distance-weighted interpolation of regression residuals obtained from the station averages. This method does not work well for days of frost, thunder and snow, so an alternative approach is used. This involves first producing a grid of values for each month from the available station data. The gridded long-term average datasets are then obtained by averaging the monthly grids. The errors associated with each stage in the process are assessed, including verification of the gridding stage by leaving out a set of stations. The estimation of missing values allows a dense network of stations to be used, and this, along with the range of independent variables used in the regression, allows detailed and accurate climate datasets and maps to be produced. The datasets have a range of applications, and the maps are freely available through the Met Office Website. © Crown Copyright 2005. Reproduced with the permission of Her Majesty's Stationery Office. Published by John Wiley & Sons, Ltd. [source] Historical instrumental climate data for Australia,quality and utility for palaeoclimatic studies,JOURNAL OF QUATERNARY SCIENCE, Issue 7 2006Neville Nicholls Abstract The quality and availability of climate data suitable for palaeoclimatic calibration and verification for the Australian region are discussed and documented. Details of the various datasets, including problems with the data, are presented. High-quality datasets, where such problems are reduced or even eliminated, are discussed. Many climate datasets are now analysed onto grids, facilitating the preparation of regional-average time series. Work is under way to produce such high-quality, gridded datasets for a variety of hitherto unavailable climate data, including surface humidity, pan evaporation, wind, and cloud. An experiment suggests that only a relatively small number of palaeoclimatic time series could provide a useful estimate of long-term changes in Australian annual average temperature. Copyright © 2006 John Wiley & Sons, Ltd. [source] | ||||||||||