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Spatial Interpolation (spatial + interpolation)
Selected AbstractsModelling lake stage and water balance of Lake Tana, EthiopiaHYDROLOGICAL PROCESSES, Issue 25 2009Yirgalem A. Chebud Abstract The level of Lake Tana, Ethiopia, fluctuates annually and seasonally following the patterns of changes in precipitation. In this study, a mass balance approach is used to estimate the hydrological balance of the lake. Water influx from four major rivers, subsurface inflow from the floodplains, precipitation, outflow from the lake constituting river discharge and evapotranspiration from the lake are analysed on monthly and annual bases. Spatial interpolation of precipitation using rain gauge data was conducted using kriging. Outflow from the lake was identified as the evaporation from the lake's surface as well as discharge at the outlet where the Blue Nile commences. Groundwater inflow is estimated using MODular three-dimensional finite-difference ground-water FLOW model software that showed an aligned flow pattern to the river channels. The groundwater outflow is considered negligible based on the secondary sources that confirmed the absence of lake water geochemical mixing outside of the basin. Evaporation is estimated using Penman's, Meyer's and Thornwaite's methods to compare the mass balance and energy balance approaches. Meteorological data, satellite images and temperature perturbation simulations from Global Historical Climate Network of National Oceanographic and Atmospheric Administration are employed for estimation of evaporation input parameters. The difference of the inflow and outflow was taken as storage in depth and compared with the measured water level fluctuations. The study has shown that the monthly and annually calculated lake level replicates the observed values with root mean square error value of 0·17 and 0·15 m, respectively. Copyright © 2009 John Wiley & Sons, Ltd. [source] GEOSTATISTICAL ESTIMATION OF HORIZONTAL HYDRAULIC CONDUCTIVITY FOR THE KIRKWOOD-COHANSEY AQUIFER,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 1 2004Vikram M. Vyas ABSTRACT: The Kirkwood-Cohansey aquifer has been identified as a critical source for meeting existing and expected water supply needs for southern New Jersey. Several contaminated sites exist in the region; their impact on the aquifer has to be evaluated using ground water flow and transport models. Ground water modeling depends on availability of measured hydrogeologic data (e.g., hydraulic conductivity, for parameterization of the modeling runs). However, field measurements of such critical data have inadequate spatial density, and their locations are often clustered. The goal of this study was to research, compile, and geocode existing data, then use geostatistics and advanced mapping methods to develop a map of horizontal hydraulic conductivity for the Kirkwood-Cohansey aquifer. Spatial interpolation of horizontal hydraulic conductivity measurements was performed using the Bayesian Maximum Entropy (BME) Method implemented in the BMELib code library. This involved the integration of actual measurements with soft information on likely ranges of hydraulic conductivity at a given location to obtain estimate maps. The estimation error variance maps provide an insight into the uncertainty associated with the estimates, and indicate areas where more information on hydraulic conductivity is required. [source] Spatial interpolation of GPS integrated water vapour measurements made in the Swiss AlpsMETEOROLOGICAL APPLICATIONS, Issue 1 2007June Morland Abstract The 31 stations in the Swiss GPS network are located at altitudes between 330 and 3584 m and have provided hourly Integrated Water Vapour (IWV) measurements since November 2000. A correction based on an exponential relationship is proposed for the decrease in IWV with altitude. The scale height depends on the ratio of IWV measured at Jungfraujoch (3584 m) to that measured at Payerne (498 m). An additional coefficient, dependent on the east-west and north-south spatial differences in the IWV, improves the fit to the data. The IWV at heights between 750 and 3500 m was estimated from GPS measurements at Payerne and compared with the Payerne radiosounding. The altitude correction introduced an additional bias of 0.2 to 0.4 mm between GPS and radiosonde. The IWV was normalized to 500 m and the increases and decreases due to the passage of a series of frontal systems between 11 and 14 January 2004 were mapped. A four-year climatology of IWV normalized to 500 m showed that the Alpine stations are more moist in spring, summer and autumn than the stations in the Swiss plains to the north of the Alps. This was attributed to more moist Mediterranean air being blocked by the Alps. Copyright © 2007 Royal Meteorological Society [source] Temporal analysis of spatial covariance of SO2 in EuropeENVIRONMETRICS, Issue 4 2007Marco Giannitrapani Abstract In recent years, the number of applications of spatial statistics has enormously increased in environmental and ecological sciences. A typical problem is the sampling of a pollution field, with the common objective of spatial interpolation. In this paper, we present a spatial analysis across time, focusing on sulphur dioxide (SO2) concentrations monitored from 1990 to 2001 at 125 sites across Europe. Four different methods of trend estimation have been used, and comparisons among them are shown. Spherical, Exponential and Gaussian variograms have been fitted to the residuals and compared. Time series analyses of the range, sill and nugget have been undertaken and a suggestion for defining a unique spatial correlation matrix for the overall time period of analysis is proposed. Copyright © 2006 John Wiley & Sons, Ltd. [source] Space,time modeling of rainfall dataENVIRONMETRICS, Issue 6 2004Luis Guillermo Coca Velarde Abstract Climate variables assume non-negative values and are often measured as zero. This is just the case when the rainfall level, in the dry season, is measured in a specified place. Then, the stochastic modeling demands the inclusion of a probability mass point at the zero level, and the resulting model is a mixture of a continuous and a Bernoulli distribution. In this article, spatial conditional autoregressive effects dealing with the idea that neighbors present similar responses is considered and the response level is modeled in two stages. The aim is to consider spatial interpolation and prediction of levels in a Bayesian context. Data on weekly rainfall levels measured in different stations at the central region of Brazil, an area with two well-marked seasons, will be used as an example. A method for comparing models, based on the deviance function, is also implemented. The main conclusion is that the use of space,time models improves the modeling of hydrological and climatological variables, allowing the inclusion of real life considerations such as the influence of other covariates, space dependence and time effects such as seasonality. Copyright © 2004 John Wiley & Sons, Ltd. [source] A high frequency kriging approach for non-stationary environmental processesENVIRONMETRICS, Issue 5 2001Montserrat Fuentes Abstract Emission reductions were mandated in the Clean Air Act Amendments of 1990 with the expectation that they would result in major reductions in the concentrations of atmospherically transported pollutants. The emission reductions are intended to reduce public health risks and to protect sensitive ecosystems. To determine whether the emission reductions are having the intended effect on atmospheric concentrations, monitoring data must be analyzed taking into consideration the spatial structure shown by the data. Maps of pollutant concentrations and fluxes are useful over different geopolitical boundaries, to discover when, where, and to what extent the U.S. Nation's air quality is improving or declining. Since the spatial covariance structure shown by the data changes with location, the standard kriging methodology for spatial interpolation cannot be used because it assumes stationarity of the process. We present a new methodology for spatial interpolation of non-stationary processes. In this method the field is represented locally as a stationary isotropic random field, but the parameters of the stationary random field are allowed to vary across space. A procedure for interpolation is presented that uses an expression for the spectral density at high frequencies. New fitting algorithms are developed using spectral approaches. In cases where the data are distributed exactly or approximately on a lattice, it is argued that spectral approaches have potentially enormous computational benefits compared with maximum likelihood. The methods are extended to interpolation questions using approximate Bayesian approaches to account for parameter uncertainty. We develop applications to obtain the total loading of pollutant concentrations and fluxes over different geo-political boundaries. Copyright © 2001 John Wiley & Sons, Ltd. [source] Improving interpolation of daily precipitation for hydrologic modelling: spatial patterns of preferred interpolatorsHYDROLOGICAL PROCESSES, Issue 23 2009Daniel Kurtzman Abstract Detailed hydrologic models require high-resolution spatial and temporal data. This study aims at improving the spatial interpolation of daily precipitation for hydrologic models. Different parameterizations of (1) inverse distance weighted (IDW) interpolation and (2) A local weighted regression (LWR) method in which elevation is the explanatory variable and distance, elevation difference and aspect difference are weighting factors, were tested at a hilly setting in the eastern Mediterranean, using 16 years of daily data. The preferred IDW interpolation was better than the preferred LWR scheme in 27 out of 31 validation gauges (VGs) according to a criteria aimed at minimizing the absolute bias and the mean absolute error (MAE) of estimations. The choice of the IDW exponent was found to be more important than the choice of whether or not to use elevation as explanatory data in most cases. The rank of preferred interpolators in a specific VG was found to be a stable local characteristic if a sufficient number of rainy days are averaged. A spatial pattern of the preferred IDW exponents was revealed. Large exponents (3) were more effective closer to the coast line whereas small exponents (1) were more effective closer to the mountain crest. This spatial variability is consistent with previous studies that showed smaller correlation distances of daily precipitation closer to the Mediterranean coast than at the hills, attributed mainly to relatively warm sea-surface temperature resulting in more cellular convection coastward. These results suggest that spatially variable, physically based parameterization of the distance weighting function can improve the spatial interpolation of daily precipitation. Copyright © 2009 John Wiley & Sons, Ltd. [source] Radar-guided interpolation of climatological precipitation dataINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 2 2009Arthur T. DeGaetano Abstract A refined approach for interpolating daily precipitation accumulations is presented, which combines radar-based information to characterize the spatial distribution and gross accumulation of precipitation with observed daily rain-gauge data to adjust for spatially varying errors in the radar estimates. Considering the rain gauge observations to be true values at each measurement location, daily radar errors are calculated at these points. These errors are then interpolated back to the radar grid, providing a spatially varying daily adjustment that can be applied across the radar domain. In contrast to similar techniques that are employed at hourly intervals to adjust radar-rainfall estimates operationally, this refined approach is intended to provide high-spatial-resolution precipitation data for climatological purposes, such as drought and environmental monitoring, retrospective impact analyses, and (when time series of sufficient length become available) assessment of temporal precipitation variations at high-spatial-resolution. Compared to the Multisensor Precipitation Estimators (MPEs) used operationally, the refined method yields lower cross-validated interpolation errors regardless of season or daily precipitation amount. Comparisons between cross-validated radar estimates aggregated to monthly totals with operational (non-cross-validated) Parameter-elevation Regressions on Independent Slopes Model (PRISM) precipitation estimates are also favourable. The new method provides a radar-based alternative to similar climatologies based on the spatial interpolation of gauge data alone (e.g. PRISM). Copyright © 2008 Royal Meteorological Society [source] A comparison of spatial interpolation methods to estimate continuous wind speed surfaces using irregularly distributed data from England and WalesINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 7 2008W. Luo Abstract Seven methods of spatial interpolation were compared to determine their suitability for estimating daily mean wind speed surfaces, from data recorded at nearly 190 locations across England and Wales. The eventual purpose of producing such surfaces is to help estimate the daily spread of pathogens causing crop diseases as they move across regions. The interpolation techniques included four deterministic and three geostatistical methods. Quantitative assessment of the continuous surfaces showed that there was a large difference between the accuracy of the seven interpolation methods and that the geostatistical methods were superior to deterministic methods. Further analyses, testing the reliability of the results, showed that measurement accuracy, density, distribution and spatial variability had a substantial influence on the accuracy of the interpolation methods. Independent wind speed data from ten other dates were used to confirm the robustness of the best interpolation methods. © Crown copyright 2007. Reproduced with the permission of Her Majesty's Stationery Office. Published by John Wiley & Sons, Ltd. [source] The generation of monthly gridded datasets for a range of climatic variables over the UKINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 8 2005Matthew Perry Abstract Monthly or annual 5 km × 5 km gridded datasets covering the UK are generated for the 1961,2000 period, for 36 climatic parameters. As well as the usual elements of temperature, rainfall, sunshine, cloud, wind speed, and pressure, derived temperature variables (such as growing-season length, heating degree days, and heat and cold wave durations) and further precipitation variables (such as rainfall intensity, maximum consecutive dry days, and days of snow, hail and thunder) are analysed. The analysis process uses geographical information system capabilities to combine multiple regression with inverse-distance-weighted interpolation. Geographic and topographic factors, such as easting and northing, terrain height and shape, and urban and coastal effects, are incorporated either through normalization with regard to the 1961,90 average climate, or as independent variables in the regression. Local variations are then incorporated through the spatial interpolation of regression residuals. For each of the climatic parameters, the choice of model is based on verification statistics produced by excluding a random set of stations from the analysis for a selection of months, and comparing the observed values with the estimated values at each point. This gives some insight into the significance, direction, and seasonality of factors affecting different climate elements. It also gives a measure of the accuracy of the method at predicting values between station locations. The datasets are being used for the verification of climate modelling scenarios and are available via the Internet. © Crown Copyright 2005. Reproduced with the permission of Her Majesty's Stationery Office. Published by John Wiley & Sons, Ltd. [source] The influence of natural conditions on the spatial variation of climate in Lapland, northern FinlandINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 9 2003Andrea Vajda Abstract At high latitudes in Lapland, near the climatological timberline, forestry and other environmental research require detailed information about the spatial variation of climate. In this study, the influence of local geographical factors on the climate in northern Finland (Lapland), as well as the applicability of the kriging interpolation method in the case of detailed spatial resolution, were examined. The spatial analysis of mean, maximum, minimum temperatures, length of the frost-free season, degree-days and daily range was made using a 1 km × 1 km resolution. The time period used was 1971,2000. We studied whether taking account of external forcing, such as lake coverage and altitude, would improve the accuracy of spatial interpolation of climatological parameters. The geographical factors of coordinates, elevation, lakes and sea influence on the regional features of the climate were examined. According to the results of this study, only geographical position and local relief have a significant influence on regional climate in Lapland. The effect of lakes and sea seems to be secondary. Copyright © 2003 Royal Meteorological Society [source] Erratum: Three-dimensional spatial interpolation of surface meteorological observations from high-resolution local networks.METEOROLOGICAL APPLICATIONS, Issue 4 20082008; 15:3 33, Cristian Lussana, Francesco Uboldi, Marta Salvati Journal of Meteorological Applications The original article to which this Erratum refers was published in Journal of Meteorological Applications, 2008; 15:3 331,345 [source] Three-dimensional spatial interpolation of surface meteorological observations from high-resolution local networksMETEOROLOGICAL APPLICATIONS, Issue 3 2008Francesco Uboldi Abstract An objective analysis technique is applied to a local, high-resolution meteorological observation network in the presence of complex topography. The choice of optimal interpolation (OI) makes it possible to implement a standard spatial interpolation algorithm efficiently. At the same time OI constitutes a basis to develop, in perspective, a full multivariate data assimilation scheme. In the absence of a background model field, a simple and effective de-trending procedure is implemented. Three-dimensional correlation functions are used to account for the orographic distribution of observing stations. Minimum-scale correlation parameters are estimated by means of the integral data influence (IDI) field. Hourly analysis fields of temperature and relative humidity are routinely produced at the Regional Weather Service of Lombardia. The analysis maps show significant informational content even in the presence of strong gradients and infrequent meteorological situations. Quantitative evaluation of the analysis fields is performed by systematically computing their cross validation (CV) scores and by estimating the analysis bias. Further developments concern the implementation of an automatic quality control procedure and the improvement of error covariance estimation. Copyright © 2008 Royal Meteorological Society [source] The use of Geographic Information Systems in climatology and meteorology: COST 719METEOROLOGICAL APPLICATIONS, Issue 1 2005Izabela Dyras The COST Action 719 started in 2001 and presently 20 European countries are participating. The main objectives of the Action are to establish interfaces between GIS and meteorological data, assess the availability, contents and accessibility of meteorological and climatological data sets and encourage and foster European co-operation. The tasks are carried out within three working groups concentrated on issues such as data access and availability, methods of spatial interpolation and developing recommendations for standardised GIS applications. The applications that have been adopted mainly focus on three parameters, i.e. precipitation, temperature and energy balance for which three demonstration projects have been formulated. It is expected that the Action will result in recommendations for better and more cost-effective production of state-of-the-art meteorological and climatological information. Also an improvement of the co-operation between European countries in the application of GIS in the field of meteorology, climatology and environmental sciences should be achieved together with better-trained personnel within the operational and scientific divisions of national meteorological services. Additionally, the development of a visualisation system for climate data sets for internet applications is under preparation. This paper provides information concerning the work in progress on the demonstration projects made within COST 719. Copyright © 2005 Royal Meteorological Society. [source] Small-scale precipitation variability in the Alps: Climatology in comparison with semi-idealized numerical simulationsTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 636 2008G. Zängl Abstract This study examines small-scale precipitation patterns in a north-Alpine region, and their dependence on the freezing level and on the crest-level (700 hPa) wind direction and speed. On the one hand, measurements from a uniquely dense operational rain-gauge network are analyzed for a period of 15 years (1991--2005). Information on the ambient atmospheric fields was extracted from climate-mode MM5 simulations driven with ECMWF (re-analysis data. On the other hand, high-resolution semi-idealized MM5 simulations have been conducted, combining realistic topography with idealized atmospheric fields. The atmospheric flow parameters have been chosen to be representative of those used to classify the observational data, focusing on atmospheric conditions conducive to stratiform, orographically enhanced precipitation in the region under consideration. The results of the data analysis indicate a pronounced tendency for local precipitation maxima in the lee of individual mountain ridges, whereas the variability between stations in the centre of wider valleys and stations on the windward foot of individual ridges is comparatively small. This points towards a strong contribution of local precipitation enhancement due to the seeder--feeder mechanism, combined with downstream advection of the precipitating hydrometeors by the ambient winds. The data analysis also reveals that strong winds and high temperatures tend to shift the precipitation field towards the interior of the Alps, whereas low temperatures and weak winds favour precipitation maxima near the northern edge of the Alps. The semi-idealized simulations are consistent with these findings, but their quantitative agreement with the observed precipitation patterns depends on the ambient flow conditions. The closest agreement is found for atmospheric conditions conducive to strong orographic lifting, for which our present idealized flow fields were designed. Lower skill is obtained for conditions not dominated by orographic lifting, which implies that future work should include a generalization of the idealized flow fields. Nevertheless, precipitation patterns generated with semi-idealized simulations seem to be very promising to support the spatial interpolation of point measurements (such as are needed for precipitation climatologies), which currently is usually based on statistical methods rather than physically motivated structures. Copyright © 2008 Royal Meteorological Society [source] | |||||||||||||