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Journal ArticleDOI

Very high resolution interpolated climate surfaces for global land areas.

01 Dec 2005-International Journal of Climatology (Wiley-Blackwell)-Vol. 25, Iss: 15, pp 1965-1978

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.
Topics: Spatial variability (54%), Elevation (53%), Weather station (53%), Spatial ecology (51%)
Citations
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Journal ArticleDOI
01 Apr 2006-Ecography
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.

6,718 citations


Journal ArticleDOI
Samir Bhatt1, Peter W. Gething1, Oliver J. Brady1, Jane P. Messina1  +19 moreInstitutions (9)
25 Apr 2013-Nature
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.

6,040 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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Journal ArticleDOI
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.

5,047 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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Journal ArticleDOI
Stephen E. Fick1, Robert J. Hijmans1Institutions (1)
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.

4,104 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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Journal ArticleDOI
TL;DR: A novel jackknife validation approach is developed and tested to assess the ability to predict species occurrence when fewer than 25 occurrence records are available and the minimum sample sizes required to yield useful predictions remain difficult to determine.
Abstract: Aim: Techniques that predict species potential distributions by combining observed occurrence records with environmental variables show much potential for application across a range of biogeographical analyses. Some of the most promising applications relate to species for which occurrence records are scarce, due to cryptic habits, locally restricted distributions or low sampling effort. However, the minimum sample sizes required to yield useful predictions remain difficult to determine. Here we developed and tested a novel jackknife validation approach to assess the ability to predict species occurrence when fewer than 25 occurrence records are available. Location: Madagascar. Methods: Models were developed and evaluated for 13 species of secretive leaf-tailed geckos (Uroplatus spp.) that are endemic to Madagascar, for which available sample sizes range from 4 to 23 occurrence localities (at 1 km2 grid resolution). Predictions were based on 20 environmental data layers and were generated using two modelling approaches: a method based on the principle of maximum entropy (Maxent) and a genetic algorithm (GARP). Results: We found high success rates and statistical significance in jackknife tests with sample sizes as low as five when the Maxent model was applied. Results for GARP at very low sample sizes (less than c. 10) were less good. When sample sizes were experimentally reduced for those species with the most records, variability among predictions using different combinations of localities demonstrated that models were greatly influenced by exactly which observations were included. Main conclusions: We emphasize that models developed using this approach with small sample sizes should be interpreted as identifying regions that have similar environmental conditions to where the species is known to occur, and not as predicting actual limits to the range of a species. The jackknife validation approach proposed here enables assessment of the predictive ability of models built using very small sample sizes, although use of this test with larger sample sizes may lead to overoptimistic estimates of predictive power. Our analyses demonstrate that geographical predictions developed from small numbers of occurrence records may be of great value, for example in targeting field surveys to accelerate the discovery of unknown populations and species. © 2007 The Authors.

2,291 citations


Cites methods from "Very high resolution interpolated c..."

  • ...FEWS precipitation data were considered advantageous over estimates derived by interpolation from weather station records (e.g. Hijmans et al., 2005), since merging data from multiple sources has been shown to reduce bias and random error significantly compared to individual precipitation data…...

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  • ...Eleven temperature-derived variables were extracted from the WorldClim data base (Hijmans et al., 2005; http://www.worldclim.org/), which is a set of global climate layers generated through interpolation of climate data from weather stations on a 30¢¢ grid (c. 1 km2 resolution)....

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References
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Journal ArticleDOI
Timothy D. Mitchell1, Philip Jones1Institutions (1)
Abstract: A database of monthly climate observations from meteorological stations is constructed. The database includes six climate elements and extends over the global land surface. The database is 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 inhomogeneities with opposite signs in different seasons. The method includes the development of reference series using neighbouring stations. Information from different sources about a single station may be combined, even without an overlapping period, using a reference series. Thus, a longer station record may be obtained and fragmentation of records reduced. The reference series also enables 1961–90 normals to be calculated for a larger proportion of stations. The station anomalies are interpolated onto a 0.5° grid covering the global land surface (excluding Antarctica) and combined with a published normal from 1961–90. Thus, climate grids are constructed for nine climate variables (temperature, diurnal temperature range, daily minimum and maximum temperatures, precipitation, wet-day frequency, frost-day frequency, vapour pressure, and cloud cover) for the period 1901–2002. This dataset is known as CRU TS 2.1 and is publicly available (http://www.cru.uea.ac.uk/). Copyright  2005 Royal Meteorological Society.

3,906 citations


"Very high resolution interpolated c..." refers background in this paper

  • ...…we have made significant progress, additional efforts to compile and capture climate data are needed to improve spatial and temporal coverage of the available climate data and quality control (Mitchell and Jones, 2005), and interpolation methods can be further refined to better use these data....

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Journal ArticleDOI
23 May 2002-Climate Research
Abstract: We describe the construction of a 10' latitude/longitude data set of mean monthly sur- face climate over global land areas, excluding Antarctica The climatology includes 8 climate ele- ments —precipitation, wet-day frequency, temperature, diurnal temperature range, relative humid- ity, sunshine duration, ground frost frequency and windspeed—and was interpolated from a data set of station means for the period centred on 1961 to 1990 Precipitation was first defined in terms of the parameters of the Gamma distribution, enabling the calculation of monthly precipitation at any given return period The data are compared to an earlier data set at 05o latitude/longitude resolution and show added value over most regions The data will have many applications in applied climatology, biogeochemical modelling, hydrology and agricultural meteorology and are available through the International Water Management Institute World Water and Climate Atlas (http://wwwiwmiorg) and the Climatic Research Unit (http://wwwcruueaacuk)

2,099 citations


"Very high resolution interpolated c..." refers background or methods or result in this paper

  • ...We aggregated the climate surfaces to a 10 arc min resolution to illustrate the benefits of higher resolution surfaces and to compare our results to those of New et al. (2002)....

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  • ...25: 1965–1978 (2005) resolution was chosen because it is the highest resolution global climate data set that was available before our study (New et al., 2002) and in order to compare with that data set....

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  • ...Within-grid cell variation in elevation was evaluated by mapping the range of elevations of the 3 arc s resolution grid cells within each 30 arc s cell....

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  • ...Other differences are related to the use of a different set of weather stations, and, no doubt, to some residual errors in our data set and that of New et al. (2002)....

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  • ...Our surfaces have a 30 arc s spatial resolution; this is equivalent to about 0.86 km2 at the equator and less elsewhere and commonly referred to as ‘1-km’ resolution....

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Journal ArticleDOI
Mark New1, Mike Hulme1, Phil Jones1Institutions (1)
01 Mar 1999-Journal of Climate
Abstract: The construction of a 0.5° lat × 0.5° long surface climatology of global land areas, excluding Antarctica, is described. The climatology 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. The climate surfaces have been constructed from a new dataset of station 1961–90 climatological normals, numbering between 19 800 (precipitation) and 3615 (wind speed). The station data were interpolated as a function of latitude, longitude, and elevation using thin-plate splines. The accuracy of the interpolations are assessed using cross validation and by comparison with other climatologies. This new climatology represents an advance over earlier published global terrestrial climatologies in that it is strictly constrained to the period 1961–90, describes an extended suite of surface climate variables, explicitly incorporates elevation...

1,834 citations


"Very high resolution interpolated c..." refers background or methods in this paper

  • ...For many applications, data at a fine (≤1 km2) spatial resolution are necessary to capture environmental variability that can be partly lost at lower resolutions, particularly in mountainous and other areas with steep climate gradients....

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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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  • ...Leemans and Cramer (1991) and New et al. (1999) created important earlier data sets, at a spatial resolution of 0.5° (55.6 km at the equator)....

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  • ...This database includes monthly mean (3084 stations), minimum and maximum (both 2504 stations) temperature and precipitation (4261 stations)....

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Journal ArticleDOI
Abstract: A method for generating daily surfaces of temperature, precipitation, humidity, and radiation over large regions of complex terrain is presented. Required inputs include digital elevation data and observations of maximum temperature, minimum temperature and precipitation from ground-based meteorological stations. Our method is based on the spatial convolution of a truncated Gaussian weighting filter with the set of station locations. Sensitivity to the typical heterogeneous distribution of stations in complex terrain is accomplished with an iterative station density algorithm. Spatially and temporally explicit empirical analyses of the relationships of temperature and precipitation to elevation were performed, and the characteristic spatial and temporal scales of these relationships were explored. A daily precipitation occurrence algorithm is introduced, as a precursor to the prediction of daily precipitation amount. Surfaces of humidity (vapor pressure deficit) are generated as a function of the predicted daily minimum temperature and the predicted daily average daylight temperature. Daily surfaces of incident solar radiation are generated as a function of Sun-slope geometry and interpolated diurnal temperature range. The application of these methods is demonstrated over an area of approximately 400 000 detailed illustration of the parameterization process. A cross-validation analysis was performed, comparing predicted and observed daily and annual average values. Mean absolute errors (MAE) for predicted annual average maximum and minimum temperature were 0.7°C and 1.2°C, with biases of +0.1°C and −0.1°C, respectively. MAE for predicted annual total precipitation was 13.4 cm, or, expressed as a percentage of the observed annual totals, 19.3%. The success rate for predictions of daily precipitation occurrence was 83.3%. Particular attention was given to the predicted and observed relationships between precipitation frequency and intensity, and they were shown to be similar. We tested the sensitivity of these methods to prediction grid-point spacing, and found that areal averages were unchanged for grids ranging in spacing from 500 m to 32 km. We tested the dependence of the results on timestep, and found that the temperature prediction algorithms scale perfectly in this respect. Temporal scaling of precipitation predictions was complicated by the daily occurrence predictions, but very nearly the same predictions were obtained at daily and annual timesteps.

1,253 citations


"Very high resolution interpolated c..." refers background or methods in this paper

  • ...…sets of high-resolution climate surfaces for the conterminous United States: the 1- km-resolution Daymet database of means for 1980–1997 (http://www.daymet.org/; Thornton et al., 1997) and the 2.5 arc min (∼5 km) PRISM climate database for 1970–2000 (http://www.ocs.orst.edu/; Daly et al., 2002)....

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  • ...Thornton et al. (1997) used a truncated Gaussian weighting filter in combination with spatially and temporally explicit empirically determined relationships of temperature and precipitation to elevation....

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  • ...…for the United * Correspondence to: Robert J. Hijmans, Museum of Vertebrate Zoology, University of California, 3101 Valley Life Sciences Building, Berkeley, CA, USA; e-mail: rhijmans@berkeley.edu Copyright 2005 Royal Meteorological Society States (http://www.daymet.org/; Thornton et al., 1997)....

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  • ...We then used SPLINA to build continuous climate surfaces for the training data and interrogated these surfaces for the locations of the test data....

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  • ...Weather station data were assembled from a large number of sources: (1) The Global Historical Climate Network Dataset (GHCN) version 2....

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Journal ArticleDOI
06 Sep 2002-Climate Research
Abstract: The demand for spatial climate data in digital form has risen dramatically in recent years. In response to this need, a variety of statistical techniques have been used to facilitate the pro- duction of GIS-compatible climate maps. However, observational data are often too sparse and unrepresentative to directly support the creation of high-quality climate maps and data sets that truly represent the current state of knowledge. An effective approach is to use the wealth of expert knowl- edge on the spatial patterns of climate and their relationships with geographic features, termed 'geospatial climatology', to help enhance, control, and parameterize a statistical technique. Described here is a dynamic knowledge-based framework that allows for the effective accumulation, application, and refinement of climatic knowledge, as expressed in a statistical regression model known as PRISM (parameter-elevation regressions on independent slopes model). The ultimate goal is to develop an expert system capable of reproducing the process a knowledgeable climatologist would use to create high-quality climate maps, with the added benefits of consistency and repeata- bility. However, knowledge must first be accumulated and evaluated through an ongoing process of model application; development of knowledge prototypes, parameters and parameter settings; test- ing; evaluation; and modification. This paper describes the current state of a knowledge-based framework for climate mapping and presents specific algorithms from PRISM to demonstrate how this framework is applied and refined to accommodate difficult climate mapping situations. A weighted climate-elevation regression function acknowledges the dominant influence of elevation on climate. Climate stations are assigned weights that account for other climatically important factors besides elevation. Aspect and topographic exposure, which affect climate at a variety of scales, from hill slope to windward and leeward sides of mountain ranges, are simulated by dividing the terrain into topographic facets. A coastal proximity measure is used to account for sharp climatic gradients near coastlines. A 2-layer model structure divides the atmosphere into a lower boundary layer and an upper free atmosphere layer, allowing the simulation of temperature inversions, as well as mid-slope precipitation maxima. The effectiveness of various terrain configurations at producing orographic precipitation enhancement is also estimated. Climate mapping examples are presented.

1,012 citations


"Very high resolution interpolated c..." refers background or methods in this paper

  • ...GHCN has data for precipitation (20 590 stations), mean temperature (7280 stations), and minimum and maximum temperature (4966 stations)....

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  • ...We then used SPLINA to build continuous climate surfaces for the training data and interrogated these surfaces for the locations of the test data....

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  • ...…sets of high-resolution climate surfaces for the conterminous United States: the 1- km-resolution Daymet database of means for 1980–1997 (http://www.daymet.org/; Thornton et al., 1997) and the 2.5 arc min (∼5 km) PRISM climate database for 1970–2000 (http://www.ocs.orst.edu/; Daly et al., 2002)....

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  • ...Daly et al. (2002) used the PRISM method, which allows for incorporation of expert knowledge about the climate and can be particularly useful when data points are sparse....

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Performance
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No. of citations received by the Paper in previous years
YearCitations
202219
20211,289
20201,515
20191,643
20181,767
20171,803