Estimation of the spatial rainfall distribution using inverse distance weighting (IDW) in the middle of Taiwan

Chen, Fengwen; Liu, Chen‐Wuing

doi:10.1007/s10333-012-0319-1

Cited by 495 publications

(202 citation statements)

References 20 publications

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“…By establishing a minimum number of known locations to be included in the analysis, IDW limits its sensitivity to outliers and ensures the robustness of the interpolation. This interpolation method has been extensively used to retrieve continuous representations of a variety of environmental variables such as precipitation, temperature, or elevation from point data (Chen and Liu, 2012;Didari et al, 2012;Schwendel et al, 2012). While more sophisticated statistical interpolation methods, such as kriging, exist, their more severe assumptions cannot be always met and their increasing complexity commonly requires a larger number of empirical parameters.…”

Section: Fire Spread Estimation Methodsmentioning

confidence: 99%

Multi-scale influence of vapor pressure deficit on fire ignition and spread in boreal forest ecosystems

Sedano

Randerson

2014

Biogeosciences

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Abstract. Climate-driven changes in the fire regime within boreal forest ecosystems are likely to have important effects on carbon cycling and species composition. In the context of improving fire management options and developing more realistic scenarios of future change, it is important to understand how meteorology regulates different aspects of fire dynamics, including ignition, daily fire spread, and cumulative annual burned area. Here we combined ModerateResolution Imaging Spectroradiometer (MODIS) active fires (MCD14ML), MODIS imagery (MOD13A1) and ancillary historic fire perimeter information to produce a data set of daily fire spread maps for Alaska during 2002-2011. This approach provided a spatial and temporally continuous representation of fire progression and a precise identification of ignition and extinction locations and dates for each wildfire. The fire-spread maps were analyzed with daily vapor pressure deficit (VPD) observations from the North American Regional Reanalysis (NARR) and lightning strikes from the Alaska Lightning Detection Network (ALDN). We found a significant relationship between daily VPD and likelihood that a lightning strike would develop into a fire ignition. In the first week after ignition, above average VPD increased the probability that fires would grow to large or very large sizes. Strong relationships also were identified between VPD and burned area at several levels of temporal and spatial aggregation. As a consequence of regional coherence in meteorology, ignition, daily fire spread, and fire extinction events were often synchronized across different fires in interior Alaska. At a regional scale, the sum of positive VPD anomalies during the fire season was positively correlated with annual burned area during the NARR era ; R 2 = 0.45). Some of the largest fires we mapped had slow initial growth, indicating opportunities may exist for suppression efforts to adaptively manage these forests for climate change. The results of our spatiotemporal analysis provide new information about temporal and spatial dynamics of wildfires and have implications for modeling the terrestrial carbon cycle.

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Section: Fire Spread Estimation Methodsmentioning

confidence: 99%

Multi-scale influence of vapor pressure deficit on fire ignition and spread in boreal forest ecosystems

Sedano

Randerson

2014

Biogeosciences

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“…In simple arithmetic averaging, the missing data are obtained by arithmetically averaging data of the 2 to 5 closest weather stations around a station (Tang et al, 1996;Xia et al, 1999;De Silva et al, 2007). Inverse distance weighting utilizes the distances from the target station of 2 to 5 neighbour stations, giving more weight to data from the nearest weather station (Tang et al, 1996;Xia et al, 1999;De Silva et al, 2007;Chen and Liu, 2012). The multiple regression model employs step-wise regression to determine the coefficients for all the significant neighbour stations (Makhuvha et al, 1997;Xia et al, 1999), while the normal ratio method utilizes the correlation between the neighbour and target 467 station as well as the number of paired datasets as the weight in estimating values at the target station (Tang et al, 1996;De Silva et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of an inverse distance weighting method for patching daily and dekadal rainfall over the Free State Province, South Africa

Moeletsi¹,

Shabalala²,

Nysschen³

et al. 2016

WSA

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Climate data recorded by national meteorological agencies is either incomplete or faulty for some periods due to a number of reasons. Multi-functional utilization of climate data in complete form necessitates the filling of these gaps. In this study an inverse distance weighting (IDW) method was used to estimate rainfall utilizing neighbouring station data in the Free State Province of South Africa. Six weather stations evenly distributed across the province, and with data for 1950 to 2008, were used to evaluate this patching IDW approach at daily and dekadal time steps. Coefficient of determination (r 2 ), mean absolute error (MAE) and mean bias error (MBE) were the statistics used in the assessment. Firstly, the study conducted a sensitivity analysis of the IDW exponent (p) which showed that the best results are obtained when p is either 2 or 2.5. The estimated values at all six stations were highly correlated with the measured rainfall data with an overall r 2 value exceeding 0.70 for both daily and dekadal estimates. MAE showed low miscalculations with values with an average of 1 mm per day and 4.4 mm per dekad. MBE was very low for both daily and dekadal evaluations but the disaggregated data showed underestimation of the IDW mostly for daily rainfall exceeding 10 mm. Thus, IDW methodology proved to be an acceptable approach for estimating both daily and dekadal rainfall in the Free State Province.

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“…Dentro de estos métodos se pueden citar aquellos basados en la estadística, como el análisis de regresión múltiple; otros que emplean técnicas de interpolación espacial, como el inverso de la distancia al cuadrado; y unos que se basan en fórmulas empíricas que se expresan como proporciones respecto de la precipitación registrada, como lo hace el método de la razón normal. La interpolación espacial se considera un enfoque adecuado para la imputación de datos faltantes en series de precipitación diaria [4][5][6][7][8], siendo los métodos ponderados los de mayor uso y aceptación [7].…”

Section: Introductionunclassified

“…Estas técnicas corresponden a Distancia inversa ponderada [4][5][6][7][8], Coeficiente de correlación ponderado [7], Exponencial inverso ponderado [7], Medida estadística ponderada [6] y Radio normal ponderado…”

Section: Introductionunclassified

Imputación de Datos en Series de Precipitación Diaria Caso de Estudio Cuenca del Río Quindío

Reinoso¹

2015

ingeniare

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En este artículo se presentan los resultados obtenidos por la aplicaciónde cinco técnicas de imputación de datos en series de precipitación diaria para ocho estaciones que tienen aferencia sobre la cuenca del río Quindío, localizada en la zona central colombiana. Con el propósito de preservar la generación de valores de precipitación igual a cero, se consideró el cálculo de probabilidades empíricas a partir de una cadena de Markov de primer orden. Las técnicas fueron implementadas en un algoritmo iterativo, en el que los valores faltantes fueron iniciados con la precipitación promedio diaria. El algoritmo se ejecuta recursivamente sustituyendo los valores estimados en la corrida anterior, finaliza cuando la diferencia máxima entre dos iteraciones sucesivas es menor que un valor fijado previamente. Los datos imputados por la técnica de distanciaestadística ponderada conservan adecuadamente las medidas de tendencia central de la serie temporal de precipitación diaria condatos faltantes.

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Estimation of the spatial rainfall distribution using inverse distance weighting (IDW) in the middle of Taiwan

Cited by 495 publications

References 20 publications

Multi-scale influence of vapor pressure deficit on fire ignition and spread in boreal forest ecosystems

Multi-scale influence of vapor pressure deficit on fire ignition and spread in boreal forest ecosystems

Evaluation of an inverse distance weighting method for patching daily and dekadal rainfall over the Free State Province, South Africa

Imputación de Datos en Series de Precipitación Diaria Caso de Estudio Cuenca del Río Quindío

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