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  • American Meteorological Society  (3)
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  • American Meteorological Society  (3)
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  • 1
    Online Resource
    Online Resource
    Derivation of New Daily Rainfall Values from TAO 1-Min Rain Gauge Data
    American Meteorological Society ; 2022
    In:  Journal of Atmospheric and Oceanic Technology Vol. 39, No. 11 ( 2022-11), p. 1729-1749
    Details
    In: Journal of Atmospheric and Oceanic Technology, American Meteorological Society, Vol. 39, No. 11 ( 2022-11), p. 1729-1749
    Abstract: Daily rainfall accumulation estimates have been derived from 1-min volume data collected via self-syphon rain gauges deployed in the Tropical Atmosphere–Ocean (TAO) array of oceanographic buoys. The underlying high-resolution volume data were obtained directly from the Global Tropical Moored Buoy Array (GTMBA) Project Office of NOAA/Pacific Marine Environmental Laboratory. The derived accumulations have been incorporated into the Pacific Rainfall (PACRAIN) database as estimated daily values to augment existing sea level oceanic rainfall records gathered using traditional rain gauges. They have also been included in the PACRAIN historical, monthly gridded rainfall product. The methodology presented, which employs differencing of least squares–regressed sensor levels about 0000 UTC and rain gauge syphon events, is shown to offer improved error characteristics over the methodology used to compute previously published GTMBA rain rates. In particular, the PACRAIN method yields larger coefficients of determination and smaller standard errors than the duplicated GTMBA method when applied to synthetic rainfall data with noise magnitude and decorrelation times encompassing those observed in the real 1-min data. These results are shown to be consistent with mathematical expectations. Sources of instrument and catchment errors, as well as evaporation, are discussed in the context of their potential effects on accumulation estimates for periods of a day or longer. Significance Statement In this paper, we describe the derivation of daily rainfall amounts from raw rain gauge data obtained from buoy-mounted rain gauges. These new accumulation estimates expand the store of rainfall estimates from locations approximating the open-ocean conditions of the tropical Pacific Ocean. The derivation technique we describe exhibits better performance than the method used to generate previously published estimates using the same dataset.
    Type of Medium: Online Resource
    ISSN: 0739-0572 , 1520-0426
    URL: Article
    DOI: 10.1175/JTECH-D-22-0011.1
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2022
    detail.hit.zdb_id: 2021720-1
    detail.hit.zdb_id: 48441-6
    Location Call Number Limitation Availability
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Gridded Monthly Rainfall Estimates Derived from Historical Atoll Observations
    American Meteorological Society ; 2019
    In:  Journal of Atmospheric and Oceanic Technology Vol. 36, No. 4 ( 2019-04), p. 671-687
    Details
    In: Journal of Atmospheric and Oceanic Technology, American Meteorological Society, Vol. 36, No. 4 ( 2019-04), p. 671-687
    Abstract: To provide an analysis tool for areal rainfall estimates, 1° gridded monthly sea level rainfall estimates have been derived from historical atoll rainfall observations contained in the Pacific Rainfall (PACRAIN) database. The PACRAIN database is a searchable repository of in situ rainfall observations initiated and maintained by the University of Oklahoma and supported by a research grant from the National Oceanic and Atmospheric Administration (NOAA)/Climate Program Office/Ocean Observing and Monitoring. The gridding algorithm employs ordinary kriging, a standard geostatistical technique, and selects for nonnegative estimates and for local estimation neighborhoods yielding minimum kriging variance. This methodology facilitates the selection of fixed-size neighborhoods from available stations beyond simply choosing the closest stations, as it accounts for dependence between estimator stations. The number of stations used for estimation is based on bias and standard error exhibited under cross estimation. A cross validation is conducted, comparing estimated and observed rains, as well as theoretical and observed standard errors for the ordinary kriging estimator. The conditional bias of the kriging estimator and the predictive value of kriging standard errors, with respect to observed standard errors, are discussed. Plots of the gridded rainfall estimates are given for sample El Niño and La Niña cases and standardized differences between the estimates produced here and the merged monthly rainfall estimates published by the Global Precipitation Climatology Project (GPCP) are shown and discussed.
    Type of Medium: Online Resource
    ISSN: 0739-0572 , 1520-0426
    URL: Article
    DOI: 10.1175/JTECH-D-18-0140.1
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2019
    detail.hit.zdb_id: 2021720-1
    detail.hit.zdb_id: 48441-6
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    Online Resource
  • 3
    Online Resource
    Online Resource
    Tractable Analytic Expressions for the Wind Speed Probability Density Functions Using Expansions of Orthogonal Polynomials
    American Meteorological Society ; 2012
    In:  Journal of Applied Meteorology and Climatology Vol. 51, No. 7 ( 2012-07), p. 1310-1320
    Details
    In: Journal of Applied Meteorology and Climatology, American Meteorological Society, Vol. 51, No. 7 ( 2012-07), p. 1310-1320
    Abstract: The use of the two-parameter Weibull function as an estimator of the wind speed probability density function (PDF) is known to be problematic when a high accuracy of fit is required, such as in the computation of the wind power density function. Various types of nonparametric kernels can provide excellent fits to wind speed histograms but cannot provide tractable analytical expressions. Analytic expressions for the wind speed PDF are needed for many applications, particularly in the downscaling of model or satellite wind speed estimates to the regional or point scale. It is demonstrated that the judicious use of an expansion of orthogonal polynomials can produce more accurate estimates of the wind speed PDF than relatively simply parametric functions, such as the commonly used Weibull function. This study examines four such expansions applied to two different surface wind speed datasets in Oklahoma. The results indicate that the accuracy of fit of a given expansion is strongly related to how close the basis weight function in an expansion resembles the wind speed histogram. It is shown that this basis function, which is the first term in the expansion, acts as a first “best guess” to the true wind speed PDF and that the additional terms act to “adjust” the fit to converge on the true density function. The results indicate that appropriately chosen orthogonal polynomials can provide an excellent fit and are quite tractable.
    Type of Medium: Online Resource
    ISSN: 1558-8424 , 1558-8432
    URL: Article
    DOI: 10.1175/JAMC-D-11-0236.1
    RVK:
    UA 4547
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2012
    detail.hit.zdb_id: 2227779-1
    detail.hit.zdb_id: 2227759-6
    Location Call Number Limitation Availability
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