Very high resolution interpolated climate surfaces for global land areas.
TL;DR: 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.
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University of Melbourne1, Stony Brook University2, City University of New York3, Princeton University4, University of Lausanne5, University of California, Berkeley6, University of Alaska Fairbanks7, National Institute of Water and Atmospheric Research8, Commonwealth Scientific and Industrial Research Organisation9, University of São Paulo10, University of Missouri11, Consejo Nacional de Ciencia y Tecnología12, University of Kansas13, Landcare Research14, AT&T15, McGill University16, James Cook University17, Swiss Federal Institute for Forest, Snow and Landscape Research18
TL;DR: This work compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date and found that presence-only data were effective for modelling species' distributions for many species and regions.
Abstract: Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.
7,589 citations
TL;DR: In this paper, the authors created a new dataset of spatially interpolated monthly climate data for global land areas at a very high spatial resolution (approximately 1 km2), including monthly temperature (minimum, maximum and average), precipitation, solar radiation, vapour pressure and wind speed, aggregated across a target temporal range of 1970-2000, using data from between 9000 and 60,000 weather stations.
Abstract: We created a new dataset of spatially interpolated monthly climate data for global land areas at a very high spatial resolution (approximately 1 km2). We included monthly temperature (minimum, maximum and average), precipitation, solar radiation, vapour pressure and wind speed, aggregated across a target temporal range of 1970–2000, using data from between 9000 and 60 000 weather stations. Weather station data were interpolated using thin-plate splines with covariates including elevation, distance to the coast and three satellite-derived covariates: maximum and minimum land surface temperature as well as cloud cover, obtained with the MODIS satellite platform. Interpolation was done for 23 regions of varying size depending on station density. Satellite data improved prediction accuracy for temperature variables 5–15% (0.07–0.17 °C), particularly for areas with a low station density, although prediction error remained high in such regions for all climate variables. Contributions of satellite covariates were mostly negligible for the other variables, although their importance varied by region. In contrast to the common approach to use a single model formulation for the entire world, we constructed the final product by selecting the best performing model for each region and variable. Global cross-validation correlations were ≥ 0.99 for temperature and humidity, 0.86 for precipitation and 0.76 for wind speed. The fact that most of our climate surface estimates were only marginally improved by use of satellite covariates highlights the importance having a dense, high-quality network of climate station data.
7,558 citations
Cites background or methods or result from "Very high resolution interpolated c..."
...This ordering is similar to what was reported for previously published climate surfaces (New et al., 2002; Hijmans et al., 2005; Table S3)....
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...Station data were checked for correspondence between their reported elevation and the elevation obtained from a global elevation raster data (Hijmans et al., 2005)....
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...Although scanning for large residuals is helpful for identifying individual outlying stations, this method may not be effective for discovering systematic errors in datasets (Hijmans et al., 2005)....
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...We looked for such systematic discrepancies by visually comparing our first-pass climate surfaces with those previously published (New et al., 1999; Hijmans et al., 2005)....
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...Regional surfaces were merged by weighting estimates in overlapping regions inversely proportional to distance from each region’s border (New et al., 2002, Hijmans et al., 2005)....
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TL;DR: These new risk maps and infection estimates provide novel insights into the global, regional and national public health burden imposed by dengue and will help to guide improvements in disease control strategies using vaccine, drug and vector control methods, and in their economic evaluation.
Abstract: Dengue is a systemic viral infection transmitted between humans by Aedes mosquitoes. For some patients, dengue is a life-threatening illness. There are currently no licensed vaccines or specific therapeutics, and substantial vector control efforts have not stopped its rapid emergence and global spread. The contemporary worldwide distribution of the risk of dengue virus infection and its public health burden are poorly known. Here we undertake an exhaustive assembly of known records of dengue occurrence worldwide, and use a formal modelling framework to map the global distribution of dengue risk. We then pair the resulting risk map with detailed longitudinal information from dengue cohort studies and population surfaces to infer the public health burden of dengue in 2010. We predict dengue to be ubiquitous throughout the tropics, with local spatial variations in risk influenced strongly by rainfall, temperature and the degree of urbanization. Using cartographic approaches, we estimate there to be 390 million (95% credible interval 284-528) dengue infections per year, of which 96 million (67-136) manifest apparently (any level of disease severity). This infection total is more than three times the dengue burden estimate of the World Health Organization. Stratification of our estimates by country allows comparison with national dengue reporting, after taking into account the probability of an apparent infection being formally reported. The most notable differences are discussed. These new risk maps and infection estimates provide novel insights into the global, regional and national public health burden imposed by dengue. We anticipate that they will provide a starting point for a wider discussion about the global impact of this disease and will help to guide improvements in disease control strategies using vaccine, drug and vector control methods, and in their economic evaluation.
7,238 citations
Cites background from "Very high resolution interpolated c..."
...India19,20 alone contributed 34% (33 [24-44] million infections) of the global total....
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TL;DR: In this article, the authors developed a geographical information system to identify Koppen's climate types based on monthly temperature and rainfall data from 2,950 weather stations in Brazil, and the results are presented as maps, graphs, diagrams and tables, allowing users to interpret the occurrence of climate types in Brazil.
Abstract: Koppen's climate classification remains the most widely used system by geographical and climatological societies across the world, with well recognized simple rules and climate symbol letters. In Brazil, climatology has been studied for more than 140 years, and among the many proposed methods Koppen 0 s system remains as the most utilized. Considering Koppen's climate classification importance for Brazil (geography, biology, ecology, meteorology, hydrology, agronomy, forestry and environmental sciences), we developed a geographical information system to identify Koppen's climate types based on monthly temperature and rainfall data from 2,950 weather stations. Temperature maps were spatially described using multivariate equations that took into account the geographical coordinates and altitude; and the map resolution (100 m) was similar to the digital elevation model derived from Shuttle Radar Topography Mission. Patterns of rainfall were interpolated using kriging, with the same resolution of temperature maps. The final climate map obtained for Brazil (851,487,700 ha) has a high spatial resolution (1 ha) which allows to observe the climatic variations at the landscape level. The results are presented as maps, graphs, diagrams and tables, allowing users to interpret the occurrence of climate types in Brazil. The zones and climate types are referenced to the most important mountains, plateaus and depressions, geographical landmarks, rivers and watersheds and major cities across the country making the information accessible to all levels of users. The climate map not only showed that the A, B and C zones represent approximately 81%, 5% and 14% of the country but also allowed the identification of Koppen's climates types never reported before in Brazil.
7,134 citations
Cites methods from "Very high resolution interpolated c..."
...Moreover, SÁ JUNIOR et al. (2012), using data from Worldclim (HIJMANS et al., 2005), found the Aw climate in a region much higher at altitudes greater than 1,000 m. Northern Espirito Santo has Aw mapped in the Coastal Plains until the perimeter with the Minas Gerais Figure 8: Monthly temperature and rainfall for Brazilian locations representing each type of Köppen0s climate....
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...Moreover, SÁ JUNIOR et al. (2012), using data from Worldclim (HIJMANS et al., 2005), found the Aw climate in a region much higher at altitudes greater than 1,000 m. Northern Espirito Santo has Aw mapped in the Coastal Plains until the perimeter with the Minas Gerais Figure 8: Monthly temperature…...
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...(2012), using data from Worldclim (HIJMANS et al., 2005), found the Aw climate in a region much higher at altitudes greater than 1,000 m....
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TL;DR: The Variable Infiltration Capacity model, a novel blending procedure incorporating the spatial correlation structure of CCD-estimates to assign interpolation weights, is presented and it is shown that CHIRPS can support effective hydrologic forecasts and trend analyses in southeastern Ethiopia.
Abstract: The Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset builds on previous approaches to ‘smart’ interpolation techniques and high resolution, long period of record precipitation estimates based on infrared Cold Cloud Duration (CCD) observations. The algorithm i) is built around a 0.05° climatology that incorporates satellite information to represent sparsely gauged locations, ii) incorporates daily, pentadal, and monthly 1981-present 0.05° CCD-based precipitation estimates, iii) blends station data to produce a preliminary information product with a latency of about 2 days and a final product with an average latency of about 3 weeks, and iv) uses a novel blending procedure incorporating the spatial correlation structure of CCD-estimates to assign interpolation weights. We present the CHIRPS algorithm, global and regional validation results, and show how CHIRPS can be used to quantify the hydrologic impacts of decreasing precipitation and rising air temperatures in the Greater Horn of Africa. Using the Variable Infiltration Capacity model, we show that CHIRPS can support effective hydrologic forecasts and trend analyses in southeastern Ethiopia.
2,895 citations
References
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TL;DR: In this article, a multistep process based on non-parametric statistics and an alternative way of relating two time series through correlation analysis is presented, which uses the year-to-year change in the variable under consideration (e.g. temperature) as the basis for correlation.
Abstract: Most techniques used to adjust climatological time series for inhomogeneities require a homogeneous reference series for comparison with each time series being evaluated. However, creating homogeneous reference series from data with unknown inhomogeneities presents many obstacles. Although a truly homogeneous reference series may, in fact, not be obtainable, in this article we present a method that has proven successful at minimizing inhomogeneities in the creation of reference climatological time series. The method utilizes a multistep process based on non-parametric statistics and an alternative way of relating two time series through correlation analysis. This alternative uses the year-to-year change in the variable under consideration (e.g. temperature) as the basis for correlation.
271 citations
"Very high resolution interpolated c..." refers methods in this paper
...For some stations, “adjusted” data that had been through homogeneity control procedures were used (Peterson and Easterling, 1994; Easterling and Peterson, 1995)....
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Book•
01 Jan 1999
TL;DR: In this article, the authors examined statistical approaches for interpolating climatic data over large regions, providing a brief introduction to interpolation techniques for climate variables of use in agricultural research, as well as general recommendations for future research to assess interpolation technique.
Abstract: This paper examines statistical approaches for interpolating climatic data over large regions, providing a brief introduction to interpolation techniques for climate variables of use in agricultural research, as well as general recommendations for future research to assess interpolation techniques. Three approaches—1) inverse distance weighted averaging (IDWA), 2) thin plate smoothing splines and 3) co-kriging—were evaluated for a 20,000 km2 square area covering the state of Jalisco, Mexico. Taking into account valued error prediction, data assumptions, and computational simplicity, we recommend use of thin-plate smoothing splines for interpolating climate variables.
246 citations
Additional excerpts
...We chose this method because it has been used in other global studies (New et al., 1999, 2002), performed well in comparative tests of multiple interpolation techniques (Hartkamp et al., 1999; Jarvis and Stuart, 2001), and because it is computationally efficient and easy to run....
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...Other approaches include Inverse Distance Weighting and Kriging (see Hartkamp et al., 1999, for an overview)....
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TL;DR: In producing version 2 of the global historical climatology network's (GHCN) temperature data sets, a variety of quality control tests were evaluated and a specialized suite of procedures was developed.
Abstract: All geophysical data bases need some form of quality assurance. Otherwise, erroneous data points may produce faulty analyses. However, simplistic quality control procedures have been known to contribute to erroneous conclusions by removing valid data points that were more extreme than the data set compilers expected. In producing version 2 of the global historical climatology network's (GHCN's) temperature data sets, a variety of quality control tests were evaluated and a specialized suite of procedures was developed. Quality control traditionally relies primarily on checks for outliers from both a time series and spatial perspective, the latter accomplished by comparisons with neighbouring stations. This traditional approach was used, and it was determined that there are many data problems that require additional tests to detect. In this paper a suite of quality control tests are justified and documented and applied to this global temperature data base, emphasizing the logic and limitations of each test. © 1998 Royal Meteorological Society.
244 citations
"Very high resolution interpolated c..." refers methods in this paper
...The GHCN data set has undergone the most explicit quality control (Peterson et al., 1997)....
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TL;DR: In this paper, the sequence of daily maximum and minimum temperatures for 1976 was interpolated over England and Wales to a resolution of 1 km using partial thin plate splines, ordinary kriging, trend surface, and an automatic inverse-distance-weighted method of interpolation.
Abstract: In a comparative experiment, the sequence of daily maximum and minimum temperatures for 1976 was interpolated over England and Wales to a resolution of 1 km using partial thin plate splines, ordinary kriging, trend surface, and an automatic inverse-distance-weighted method of interpolation. A “level playing field” for comparing the estimation accuracies was established through the incorporation of a consistent set of guiding variables in all interpolators. Once variables were included to guide the interpolators, differences in estimation accuracy among partial thin plate splines, ordinary kriging, and inverse distance weighting results were not significant although the performance of trend surface analysis was poorer. Best accuracies were achieved using partial thin plate splines, with jackknife cross-validation root-mean-square errors of 0.8°C for an annual series of daily maximum temperatures and 1.14°C for daily minimum temperatures. The results from this study suggest that sole reliance on th...
190 citations
"Very high resolution interpolated c..." refers background or methods in this paper
...Additional independent variables could also be included (Jarvis and Stuart, 2001)....
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...WMO did extensive quality control on these data (WMO, 1996)....
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...We chose this method because it has been used in other global studies (New et al., 1999, 2002), performed well in comparative tests of multiple interpolation techniques (Hartkamp et al., 1999; Jarvis and Stuart, 2001), and because it is computationally efficient and easy to run....
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01 Jan 2004
TL;DR: In this paper, the authors compare the relative differences between SRTM and carthographically generated DEMs at the sub-catchment scale, and evaluate the effectiveness of a hole-filling algorithm.
Abstract: Introduction 1 Methods 2 Results and Discussion 2 Ecuador SRTM DEM versus GROPO30 2 Introduction 2 Methods 3 Results and discussion 3 Honduras SRTM DEM versus 1:50,000 cartographically derived DEM 5 Introduction 5 Methods 6 Results and discussion 6 Conclusions 10 Dapa case study: Absolute and relative differences between DEMs at the sub-catchment scale 10 Introduction 10 Methods 10 Results and discussion 11 Conclusions 16 Tambito case study: Evaluation of a hole-filling algorithm 16 Introduction 16 Methods 16 Results and discussion 18 Conclusions 21 The hydrologically significant differences between SRTM and carthographically generated DEMs 21 Introduction 21 Methods 22 Results and discussion 22 Conclusions 28 Overall Conclusions 28 References 29 1 Introduction Topography is basic to many earth surface processes. It is used in analyses in ecology, hydrology, agriculture, climatology, geology, pedology, geomorphology, and many others, as a means both of explaining processes and of predicting them through modeling. Our capacity to understand and model these processes depends on the quality of the topographic data that are available. Most countries have much of the land surface covered by cartographic maps at varying scales and of varying accuracies. In most tropical countries, these maps are produced through manual interpretation of stereo pairs of aerial photos, and in some cases the topographic data can be erroneous or missing where cloud was present. With the advent of satellite imagery covering the globe, various global datasets of topography have been produced, of increasingly better resolution, from 10 arc-minutes (approximately 18 km at the equator) to 30 arc-seconds (approximately 1 km at the equator) using the United States Geological Survey (USGS) product, GTOPO30. This topography dataset was widely used for almost a decade, mainly for broadscale assessments. However, the 1-km spatial resolution prevented its use in modeling more detailed earth surface processes, especially in fields such as hydrology, pedology, or small-scale geomorphology. Researchers in these areas had to rely on local maps for the topography. Digitization or photogrammetry, time-consuming and costly processes, was needed to produce high-resolution digital elevation models (DEMs). In 2003, the National Aeronautics and Space Administration (NASA) released the Shuttle Radar Topography Mission (SRTM) dataset for some regions, with 3 arc-second resolution for the globe, and 1 arc-second for the United States. This giant leap forward in spatial resolution for DEMs with global coverage is likely to change the way in which related research can be performed and applied, bringing local catchment …
170 citations
"Very high resolution interpolated c..." refers background in this paper
...For most parts of the world, this data set provides a dramatic improvement in the availability of high-quality and high-resolution elevation data (Jarvis et al., 2004)....
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