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Elevation

About: Elevation is a research topic. Over the lifetime, 5503 publications have been published within this topic receiving 115328 citations. The topic is also known as: geometric height.


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Journal ArticleDOI
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.

17,977 citations

Journal ArticleDOI
TL;DR: In this article, the authors present an analytical model that distributes point measurements of monthly and annual precipitation to regularly spaced grid cells in midlatitude regions, using a combination of climatological and statistical concepts to analyze orographic precipitation.
Abstract: The demand for climatological precipitation fields on a regular grid is growing dramatically as ecological and hydrological models become increasingly linked to geographic information systems that spatially represent and manipulate model output. This paper presents an analytical model that distributes point measurements of monthly and annual precipitation to regularly spaced grid cells in midlatitude regions. PRISM (Precipitation-elevation Regressions on Independent Slopes Model) brings a combination of climatological and statistical concepts to the analysis of orographic precipitation. Specifically, PRISM 1) uses a digital elevation model (DEM) to estimate the “orographic” elevations of precipitation stations; 2) uses the DEM and a windowing technique to group stations onto individual topographic facets; 3) estimates precipitation at a DEM grid cell through a regression of precipitation versus DEM elevation developed from stations on the cell's topographic facet; and 4) when possible, calculates...

2,770 citations

Journal ArticleDOI
TL;DR: In this paper, the authors used the PRISM (Parameter-elevation relationships on independent slopes model) interpolation method to develop data sets that reflected, as closely as possible, the current state of knowledge of spatial climate patterns in the United States.
Abstract: Spatial climate data sets of 1971–2000 mean monthly precipitation and minimum and maximum temperature were developed for the conterminous United States These 30-arcsec (∼800-m) grids are the official spatial climate data sets of the US Department of Agriculture The PRISM (Parameter-elevation Relationships on Independent Slopes Model) interpolation method was used to develop data sets that reflected, as closely as possible, the current state of knowledge of spatial climate patterns in the United States PRISM calculates a climate–elevation regression for each digital elevation model (DEM) grid cell, and stations entering the regression are assigned weights based primarily on the physiographic similarity of the station to the grid cell Factors considered are location, elevation, coastal proximity, topographic facet orientation, vertical atmospheric layer, topographic position, and orographic effectiveness of the terrain Surface stations used in the analysis numbered nearly 13 000 for precipitation and 10 000 for temperature Station data were spatially quality controlled, and short-period-of-record averages adjusted to better reflect the 1971–2000 period PRISM interpolation uncertainties were estimated with cross-validation (C-V) mean absolute error (MAE) and the 70% prediction interval of the climate–elevation regression function The two measures were not well correlated at the point level, but were similar when averaged over large regions The PRISM data set was compared with the WorldClim and Daymet spatial climate data sets The comparison demonstrated that using a relatively dense station data set and the physiographically sensitive PRISM interpolation process resulted in substantially improved climate grids over those of WorldClim and Daymet The improvement varied, however, depending on the complexity of the region Mountainous and coastal areas of the western United States, characterized by sparse data coverage, large elevation gradients, rain shadows, inversions, cold air drainage, and coastal effects, showed the greatest improvement The PRISM data set benefited from a peer review procedure that incorporated local knowledge and data into the development process Copyright © 2008 Royal Meteorological Society

2,447 citations

Journal ArticleDOI
TL;DR: The method handles artificial pits introduced by data collection systems and extracts only the major drainage paths and its performance appears to be consistent with the visual interpretation of drainage patterns from elevation contours.
Abstract: The extraction of drainage networks from digital elevation data is important for quantitative studies in geomorphology and hydrology. A method is presented for extracting drainage networks from gridded elevation data. The method handles artificial pits introduced by data collection systems and extracts only the major drainage paths. Its performance appears to be consistent with the visual interpretation of drainage patterns from elevation contours.

2,167 citations

Journal ArticleDOI
TL;DR: In this article, the authors developed expressions for calculating the ratios (mapping functions) of the "line of sight" hydrostatic and wet atmospheric path delays to their corresponding zenith delays at radio wavelengths for elevation angles down to 3°.
Abstract: I have developed expressions for calculating the ratios (mapping functions) of the “line of sight” hydrostatic and wet atmospheric path delays to their corresponding zenith delays at radio wavelengths for elevation angles down to 3°. The coefficients of the continued fraction representation of the hydrostatic mapping function depend on the latitude and height above sea level of the observing site and on the day of the year; the dependence of the wet mapping function is only on the site latitude. By comparing with mapping functions calculated from radiosonde profiles for sites at latitudes between 43°S and 75°N, the hydrostatic mapping function is seen to be more accurate than, and of comparable precision to, mapping functions currently in use, which are parameterized in terms of local surface meteorology. When the new mapping functions are used in the analysis of geodetic very long baseline interferometry (VLBI) data, the estimated lengths of baselines up to 10,400 km long change by less than 5 mm as the minimum elevation of included data is reduced from 12° to 3°. The independence of the new mapping functions from surface meteorology, while having comparable accuracy and precision to those that require such input, makes them particularly valuable for those situations where surface meteorology data are not available.

1,499 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20225
2021267
2020295
2019352
2018276
2017271