Generating surfaces of daily meteorological variables over large regions of complex terrain
TLDR
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.About:
This article is published in Journal of Hydrology.The article was published on 1997-03-15 and is currently open access. It has received 1309 citations till now.read more
Citations
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Journal ArticleDOI
Developing a continental-scale measure of gross primary production by combining MODIS and AmeriFlux data through Support Vector Machine approach
Feihua Yang,Feihua Yang,Kazuhito Ichii,Kazuhito Ichii,Michael A. White,Hirofumi Hashimoto,Hirofumi Hashimoto,Andrew Michaelis,Andrew Michaelis,Petr Votava,Petr Votava,A-Xing Zhu,A-Xing Zhu,Alfredo Huete,Steven W. Running,Ramakrishna R. Nemani +15 more
TL;DR: In this article, the authors used meteorological and flux data from the AmeriFlux network and Support Vector Machine (SVM), an inductive machine learning technique, to develop and apply a predictive GPP model for the conterminous U.S. by integrating the 2004 SVM GPP with the MOD17 GPP algorithm.
Journal ArticleDOI
Global solar radiation in Central European lowlands estimated by various empirical formulae
TL;DR: In this article, seven methods for estimating daily global radiation, R G, were tested in the Central Europe case study area (lowlands of Austria and the Czech Republic) assuming that no measured global radiation data for parameterisation are available, i.e. with all empirical coefficients required by the selected methods being obtained from previously published studies.
Journal ArticleDOI
Scaling snow observations from the point to the grid element: Implications for observation network design
Noah P. Molotch,Roger C. Bales +1 more
TL;DR: In this article, the spatial distribution of snow water equivalent (SWE) within 16-, 4-, and 1-km2 grid elements surrounding six snow telemetry (SNOTEL) stations in the Rio Grande headwaters was characterized using field observations of snowpack properties, satellite data, binary regression tree models, and a spatially distributed net radiation/temperature index snowpack mass balance model.
OtherDOI
PRMS-IV, the precipitation-runoff modeling system, version 4
Steven L. Markstrom,R. Steven Regan,Lauren E. Hay,Roland J. Viger,Richard M.T. Webb,Robert A. Payn,Jacob H. LaFontaine +6 more
TL;DR: In this paper, the authors propose a solution to solve the problem of the problem: this paper...,.. ].. ).. )... ;.
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Interpolation of temperature in a mountainous region using nonlinear profiles and non-Euclidean distances
TL;DR: In this article, a nonlinear parametric function is used to model nonlinearities in the vertical thermal profile at the scale of major basins, and a distance weighting scheme with a non-Euclidean metric that accounts for terrain effects on the spatial representativity of measurements.
References
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A Statistical-Topographic Model for Mapping Climatological Precipitation over Mountainous Terrain
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.
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A general model of forest ecosystem processes for regional applications I. Hydrologic balance, canopy gas exchange and primary production processes
TL;DR: In this paper, an ecosystem process model is described that calculates the carbon, water and nitrogen cycles through a forest ecosystem, which uses leaf area index (lai) to quantify the forest structure important for energy and mass exchange, and represents a key simplification for regional scale applications.
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On the relationship between incoming solar radiation and daily maximum and minimum temperature
TL;DR: In this article, a relationship between atmospheric transmittance and the daily range of air temperature is developed, where the relationship is Tt = A[1 −exp(exp(BΔTc)] where Tt is the daily total atmospherictransmittance, ΔT is the average air temperature, and A, B, and C are empirical coefficients, determined for a particular location from measured solar radiation data.