Journal ArticleDOI
Very high resolution interpolated climate surfaces for global land areas.
Robert J. Hijmans,Susan E. Cameron,Susan E. Cameron,Juan L. Parra,Peter G. Jones,Andy Jarvis +5 more
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In this paper, the authors developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution).Abstract:
We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered from a variety of sources and, where possible, were restricted to records from the 1950–2000 period. We used the thin-plate smoothing spline algorithm implemented in the ANUSPLIN package for interpolation, using latitude, longitude, and elevation as independent variables. We quantified uncertainty arising from the input data and the interpolation by mapping weather station density, elevation bias in the weather stations, and elevation variation within grid cells and through data partitioning and cross validation. Elevation bias tended to be negative (stations lower than expected) at high latitudes but positive in the tropics. Uncertainty is highest in mountainous and in poorly sampled areas. Data partitioning showed high uncertainty of the surfaces on isolated islands, e.g. in the Pacific. Aggregating the elevation and climate data to 10 arc min resolution showed an enormous variation within grid cells, illustrating the value of high-resolution surfaces. A comparison with an existing data set at 10 arc min resolution showed overall agreement, but with significant variation in some regions. A comparison with two high-resolution data sets for the United States also identified areas with large local differences, particularly in mountainous areas. Compared to previous global climatologies, ours has the following advantages: the data are at a higher spatial resolution (400 times greater or more); more weather station records were used; improved elevation data were used; and more information about spatial patterns of uncertainty in the data is available. Owing to the overall low density of available climate stations, our surfaces do not capture of all variation that may occur at a resolution of 1 km, particularly of precipitation in mountainous areas. In future work, such variation might be captured through knowledgebased methods and inclusion of additional co-variates, particularly layers obtained through remote sensing. Copyright 2005 Royal Meteorological Society.read more
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Journal ArticleDOI
Carbon sequestration potential of second-growth forest regeneration in the Latin American tropics
Robin L. Chazdon,Robin L. Chazdon,Eben N. Broadbent,Danaë M. A. Rozendaal,Danaë M. A. Rozendaal,Danaë M. A. Rozendaal,Frans Bongers,Angelica M. Almeyda Zambrano,T. Mitchell Aide,Patricia Balvanera,Justin M. Becknell,Vanessa K. Boukili,Pedro H. S. Brancalion,Dylan Craven,Dylan Craven,Jarcilene S. Almeida-Cortez,George A. L. Cabral,Ben de Jong,Julie S. Denslow,Daisy H. Dent,Daisy H. Dent,Saara J. DeWalt,Juan Manuel Dupuy,Sandra M. Durán,Mário M. Espírito-Santo,María C. Fandiño,Ricardo Gomes César,Jefferson S. Hall,José Luis Hernández-Stefanoni,Catarina C. Jakovac,Catarina C. Jakovac,André Braga Junqueira,André Braga Junqueira,Deborah K. Kennard,Susan G. Letcher,Madelon Lohbeck,Madelon Lohbeck,Miguel Martínez-Ramos,Paulo Eduardo dos Santos Massoca,Jorge A. Meave,Rita C. G. Mesquita,Francisco Mora,Rodrigo Muñoz,Robert Muscarella,Robert Muscarella,Yule Roberta Ferreira Nunes,Susana Ochoa-Gaona,Edith Orihuela-Belmonte,Marielos Peña-Claros,Eduardo A. Pérez-García,Daniel Piotto,Jennifer S. Powers,Jorge Rodríguez-Velázquez,Isabel Eunice Romero-Pérez,Jorge Ruiz,Jorge Ruiz,Juan Saldarriaga,Arturo Sanchez-Azofeifa,Naomi B. Schwartz,Marc K. Steininger,Nathan G. Swenson,María Uriarte,Michiel van Breugel,Michiel van Breugel,Michiel van Breugel,Hans van der Wal,Hans van der Wal,Maria das Dores Magalhães Veloso,Hans F. M. Vester,Ima Célia Guimarães Vieira,Tony Vizcarra Bentos,G. Bruce Williamson,G. Bruce Williamson,Lourens Poorter +73 more
TL;DR: This study estimates the age and spatial extent of lowland second-growth forests in the Latin American tropics and model their potential aboveground carbon accumulation over four decades to guide national-level forest-based carbon mitigation plans.
Journal ArticleDOI
Spatial variation of crop yield response to climate change in East Africa
TL;DR: In this article, the authors use high-resolution methods to generate characteristic daily weather data for a combination of different future emission scenarios and climate models to drive detailed simulation models of the maize and bean crops.
Journal ArticleDOI
Temperature variation makes ectotherms more sensitive to climate change.
Krijn P. Paaijmans,Krijn P. Paaijmans,Rebecca L. Heinig,Rebecca A. Seliga,Justine I. Blanford,Simon Blanford,Courtney C. Murdock,Matthew B. Thomas +7 more
TL;DR: Using a mosquito as a model organism, it is found that temperature fluctuation reduces rate processes such as development under warm conditions, increases processes under cool conditions, and reduces both the optimum and the critical maximum temperature.
Journal ArticleDOI
Rainfall Erosivity in Europe
Panos Panagos,Cristiano Ballabio,Pasquale Borrelli,Katrin Meusburger,Andreas Klik,Svetla Rousseva,Melita Perčec Tadić,Silas Michaelides,Michaela Hrabalíková,Preben Olsen,Juha Aalto,Mónika Lakatos,Anna Rymszewicz,Alexandru Dumitrescu,Santiago Beguería,Christine Alewell +15 more
TL;DR: The erosivity density (erosivity normalised to annual precipitation amounts) was the highest in Mediterranean regions which implies high risk for erosive events and floods, and Gaussian Process Regression has been used to interpolate the R-factor station values to a European rainfall erOSivity map at 1 km resolution.
Journal ArticleDOI
Maxent modeling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticola in New Caledonia
Sunil Kumar,Thomas J. Stohlgren +1 more
TL;DR: A novel method called maximum entropy distribution modeling or Maxent is used for predicting potential suitable habitat for Canacomyrica monticola, a threatened and endangered tree species in New Caledonia, using small number of occurrence records.
References
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Journal ArticleDOI
An improved method of constructing a database of monthly climate observations and associated high-resolution grids
Timothy D. Mitchell,Philip Jones +1 more
TL;DR: In this paper, a database of monthly climate observations from meteorological stations is constructed and checked for inhomogeneities in the station records using an automated method that refines previous methods by using incomplete and partially overlapping records and by detecting inhomalities with opposite signs in different seasons.
Journal ArticleDOI
A high-resolution data set of surface climate over global land areas
TL;DR: In this paper, the construction of a 10' latitude/longitude data set of mean monthly sur-face climate over global land areas, excluding Antarctica, was described, which includes 8 climate conditions: precipitation, wet-day frequency, temperature, diurnal temperature range, relative humid-ity, sunshine duration, ground frost frequency and windspeed.
Journal ArticleDOI
Representing Twentieth-Century Space–Time Climate Variability. Part I: Development of a 1961–90 Mean Monthly Terrestrial Climatology
Mark New,Mike Hulme,Phil Jones +2 more
TL;DR: In this article, a 0.5° lat × 0. 5° long surface climatology of global land areas, excluding Antarctica, is described, which represents the period 1961-90 and comprises a suite of nine variables: precipitation, wet-day frequency, mean temperature, diurnal temperature range, vapor pressure, sunshine, cloud cover, ground frost frequency, and wind speed.
Journal ArticleDOI
Generating surfaces of daily meteorological variables over large regions of complex terrain
TL;DR: In this paper, a method for generating daily surfaces of temperature, precipitation, humidity, and radiation over large regions of complex terrain is presented, based on the spatial convolution of a truncated Gaussian weighting filter with the set of station locations.
Journal ArticleDOI
A knowledge-based approach to the statistical mapping of climate
TL;DR: In this article, the authors present a knowledge-based framework for climate mapping using a statistical regression model known as PRISM (parameter-elevation regressions on independent slopes model).
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