Development and Testing of Single‐Parameter Precipitation Distributions

Selker, John S.; Haith, Douglas A.

doi:10.1029/wr026i011p02733

Cited by 44 publications

(36 citation statements)

References 11 publications

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“…Selker and Haith (1990) showed that for 33 United States climate stations east of the Rocky Mountains, the Weibull distribution is superior to other distributions. For wet days the precipitation amount is generated by…”

Section: Amount Of Daily Precipitationmentioning

confidence: 99%

“…ClimGen has the capability to automate the task of parameterizing the historical weather data. Also, while their fi ndings may be location specifi c, Selker and Haith (1990) concluded that the use of a Weibull distribution to represent daily precipitation amounts, as is in Climgen, is superior to other probability distribution functions. The ClimGen developers claim the spline approach is an improvement over the one-term Fourier series used by many other weather generators to model seasonal variations in climate data.…”

Section: Selection Of Climate Generatormentioning

confidence: 99%

“…A simple analysis was performed to address this issue by examining ClimGen's application of both the Weibull distribution function (Selker and Haith, 1990) and its spline smoothing function. The analysis consisted of identifying the top and bottom 3%, 6%, 9%, and 12% of annual precipitation levels and comparing them with the same percentiles in the historical data set.…”

Section: Evaluation Of Climgen's Performancementioning

confidence: 99%

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Evaluation of Weather Generator ClimGen for Southern Ontario

McKague¹,

Rudra²,

Ogilvie³

et al. 2005

Canadian Water Resources Journal

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Modelling of soil water systems has become an important tool for water quality management and source water protection. Application of such models requires long-term continuous weather data from several weather stations distributed across the watershed. However, historic weather data often have missing records, large gaps in data or the length of the record may not be suffi cient to include fl ood or drought conditions of interest. This has led to the development and use of weather generation procedures and tools. In this paper, the weather generator ClimGen has been evaluated for generation of daily precipitation, air temperature, solar radiation, wind speed, and relative humidity for southern Ontario conditions. The comparison of simulated weather data with 30 years of weather data for six stations indicated that ClimGen performed with reasonable accuracy with some limitations in generating rainfall intensities and solar radiation, particularly for the winter months.Résumé : La modélisation des réserves d'eau du sol est devenue un important outil de gestion de la qualité de l'eau et de protection de l'eau à la source. L'application de ces modèles exige des données météorologiques à long terme provenant de plusieurs stations météorologiques réparties dans l'ensemble du bassin hydrographique. Cependant, les données météorologiques historiques s'accompagnent souvent de graves lacunes statistiques, entre autres des enregistrements manquants. Il arrive parfois également que la durée de l'enregistrement ne soit pas suffi sante pour qu'il soit possible d'inclure les conditions de sécheresse et de crue qui revêtent de l'intérêt. Ces lacunes ont mené à l'élaboration et à l'utilisation d'une procédure et d'outils de génération de conditions météorologiques. Dans la présente communication, le générateur de données climatiques ClimGen a été évalué pour la génération de données sur les précipitations quotidiennes, la température de l'air, le rayonnement solaire, la vitesse du vent et l'humidité relative pour les conditions du Sud de l'Ontario. La comparaison des données atmosphériques simulées avec des données atmosphériques échelonnées sur 30 ans pour six stations a révélé que ClimGen a produit des résultats d'une exactitude raisonnable, bien que l'on ait constaté certaines limitations dans la génération de données sur l'intensité pluviale et le rayonnement solaire, en particulier pour les mois d'hiver.

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Section: Amount Of Daily Precipitationmentioning

confidence: 99%

Section: Selection Of Climate Generatormentioning

confidence: 99%

Section: Evaluation Of Climgen's Performancementioning

confidence: 99%

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Evaluation of Weather Generator ClimGen for Southern Ontario

McKague¹,

Rudra²,

Ogilvie³

et al. 2005

Canadian Water Resources Journal

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“…(6). The inverse CDF of Weibull distribution is based on the single-parameter Weibull distribution estimated by Selker and Haith (1990).…”

Section: Rainfall Amountmentioning

confidence: 99%

Producing Daily and Embedded Hourly Rainfall Data Using a Novel Weather Generator

Tung¹,

Lien²,

Liao³

2013

Terr. Atmos. Ocean. Sci.

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The number of worldwide extreme drought and flood events has risen significantly in recent years. Many studies confer that climate change may cause more intensive and extreme events. Simulating the impact of climate change often requires weather data as inputs to assessment models. Stochastic weather generators have been developed to produce weather data with the same temporal resolution based on the outputs of GCMs. Reservoir simulation normally uses operational rules in daily and hourly time steps for water supply and flood reduction, respectively. Simulating consecutive drought and flood events simultaneously requires a weather generator to produce different temporal resolution data. This work develops a continuous weather generator to generate daily and hourly precipitation data for regular wet days and severe storms, respectively. Daily rainfall data is generated for regular wet days using Exponential distribution or Weibull distribution, while the total rainfall data for severe storms is generated using the Pearson type III or Log Pearson type III distribution. Moreover, hourly rainfall is determined based on generated hyetographs. Simulation results indicate that the proposed continuous weather generator can generate daily and hourly rainfall reasonably. The proposed weather generator is thus highly promising for use in evaluating how climate change impacts reservoir operations that are significantly influenced by more frequent and intensive consecutive drought and flood events.

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“…If it is a wet day, the rainfall amount is generated based on a single-parameter Weibull distribution (Selker and Haith 1990) .…”

Section: P W W If Previous Day Is Wet Daymentioning

confidence: 99%

Climate Change Impact Assessment for Sustainable Water Quality Management

Tung¹,

Lee²,

Liao³

et al. 2012

Terr. Atmos. Ocean. Sci.

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The goal of sustainable water quality management is to keep total pollutant discharges from exceeding the assimilation capacity of a water body. Climate change may influence streamflows, and further alter assimilation capacity and degrade river sustainability. The purposes of this study are to evaluate the effect of climate change on sustainable water quality management and design an early warning indicator to issue warnings on river sustainability. A systematic assessment procedure is proposed here, including a weather generation model, the streamflow component of GWLF, QUAL2E, and an optimization model. The Touchen creek in Taiwan is selected as the study area. Future climate scenarios derived from projections of four global climate models (GCMs) and two pollutant discharge scenarios, as usual and proportional to population, are considered in this study.The results indicate that streamflows may very likely increase in humid seasons and decrease in arid seasons, respectively. The reduction of streamflow in arid seasons may further degrade water quality and assimilation capacity. In order to provide warnings to trigger necessary adaptation strategies, an early warning indicator is designed and its 30-year moving average is calculated. Finally, environmental monitoring systems and methods to prioritize adaptation strategies are discussed for further studies in the future.

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Development and Testing of Single‐Parameter Precipitation Distributions

Cited by 44 publications

References 11 publications

Evaluation of Weather Generator ClimGen for Southern Ontario

Evaluation of Weather Generator ClimGen for Southern Ontario

Producing Daily and Embedded Hourly Rainfall Data Using a Novel Weather Generator

Climate Change Impact Assessment for Sustainable Water Quality Management

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