Role of Observational Errors in Optimum Interpolation Analysis

Bergman, Kenneth H.

doi:10.1175/1520-0477-59.12.1603

Cited by 19 publications

(8 citation statements)

References 10 publications

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Section: Basic Theory Of Oi-based Multi-source Merging Methodsmentioning

confidence: 99%

“…As a powerful method, Optimal Interpolation (OI) is widely used in data merging (e.g., Gandin 1965;Bergman 1978;Daly 1991;Xie and Xiong 2011;Shen et al 2014;Pan et al 2015. Bergman (1978) and Xie and Xiong (2011) given the relatively compact description of the theory of the IO method. The basic idea is to take an irregular distribution of observations of precipitation quality and obtain the best possible estimate of a precipitation field at a regular network of grid points through minimizing the mean square interpolation error for a large ensemble of analysis situations (Bergman 1978).…”

Section: Basic Theory Of Oi-based Multi-source Merging Methodsmentioning

confidence: 99%

“…Bergman (1978) and Xie and Xiong (2011) given the relatively compact description of the theory of the IO method. The basic idea is to take an irregular distribution of observations of precipitation quality and obtain the best possible estimate of a precipitation field at a regular network of grid points through minimizing the mean square interpolation error for a large ensemble of analysis situations (Bergman 1978). According to Bergman (1978) and Xie and Xiong (2011), the analyzed precipitation value, A k , also called the final merged precipitation value, at a target grid box ( k ) under the OI framework is obtained by adjusting the first guess value ( F k ) at the grid box using observations (i.e.…”

Section: Basic Theory Of Oi-based Multi-source Merging Methodsmentioning

confidence: 99%

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UKGrsHP: a UK high-resolution gauge–radar–satellite merged hourly precipitation analysis dataset

Lewis

et al. 2020

Clim Dyn

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There is an urgent need for high-quality and high-spatial-resolution hourly precipitation products around the globe, including the UK. Although hourly precipitation products exist for the UK, these either contain large errors, or are insufficient in spatial resolution. An efficient way to solve this is to develop a merged precipitation product that combines the information and benefits from multiple data sources, improving both the spatial resolution and accuracy of hourly precipitation estimates over the UK. In this study, we develop a UK high-resolution gauge-radar-satellite merged hourly precipitation analysis: the UKGrsHP. It covers the UK from 12.5° W to 3.5° E, 49° N-60° N, with a spatial resolution of 0.01° × 0.01° in latitude/ longitude (equivalent to 1 km resolution in the mid-latitudes). An optimal interpolation (OI)-based multi-source merging scheme with compound strategy is developed and tested for producing the UKGrsHP. Three input data sources are used: gauge analysis data interpolated from 1903 quality-controlled hourly observations, the UK Nimrod radar precipitation analysis and the GSMaP global satellite precipitation analysis. Using independent tests against ~ 220 independent gauge observations on 1 year's experimental UKGrsHP, covering the period from January to December 2014, we find that the final merged data performs better than three individual precipitation analyses used as inputs. A full version of the UKGrsHP starting in April 2004 is now under production, which will have wide applications in climate services and scientific research across multiple disciplines.

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Section: Basic Theory Of Oi-based Multi-source Merging Methodsmentioning

confidence: 99%

Section: Basic Theory Of Oi-based Multi-source Merging Methodsmentioning

confidence: 99%

Section: Basic Theory Of Oi-based Multi-source Merging Methodsmentioning

confidence: 99%

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UKGrsHP: a UK high-resolution gauge–radar–satellite merged hourly precipitation analysis dataset

Lewis

et al. 2020

Clim Dyn

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“…Gridded data sets prepared twice daily by the National Meteorological Center (NMC) of the U.S. National Weather Service were used. In September 1978, in preparation for the FGGE year, NMC switched from the Hough spectral analysis (Flattery, 1970) to optimum interpolation (Bergman, 1978: McPherson et al, 1979). An improvement in certain characteristics of the NMC gridded data apparently occurred at this time.…”

Section: The Data Setmentioning

confidence: 99%

Available potential energy in the northern hemisphere during the FGGE year

Min

Horn²

1982

Tellus A: Dynamic Meteorology and Oceanography

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Northern Hemispheric twice daily data from the First GARP Global Experiment (FGGE) year are used to compare available potential energy estimates obtained using the so-called exact (isentropic) form of the equations with two commonly used approximate (isobaric) forms. The two approximate forms, one using a fixed lapse rate and the other a lapse rate which varies in the vertical, overestimate the total available potential energy except in mid-summer.The greatest difference between the exact and approximate forms is in the eddy term, which is considerably smaller in the approximate forms, especially in spring and summer. Partitioning the eddy term into its standing and transient components shows that in the exact form the standing component exceeds the transient term. This is in contrast to the approximate form in which the transient term is the larger in every month except July. The latitudinal and monthly variations of the standing and transient terms show different patterns, especially in the standing component. In the approximate form the latitude of maximum standing eddy values is near 60" N in winter but shifts equatorward to about 30° N and decreases in summer. While the exact form shows a weak winter maximum near 60° N, the dominant maximum develops near 20" N in spring and shifts poleward to about 30° N and increases in summer.The hemispheric distribution of the vertically integrated grid point values from which the eddy available potential energy was calculated and the standard deviation of these twice daily values produce results which show that the exact form values better conform to the pattern of cyclone activity than the approximate form. In general, the results indicate that the exact form of the available potential energy equations should be more extensively used in diagnostic work.

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“…It is important to note that the Global W'eather Experiment is the first major effort of data producers to provide their own systematic quality control indicators (qualitative and quantitative, where possible) with the data. This practice adds a new dimension of responsibility for data producers and lends itself to the optimal interpolation analysis routines that are now in use (e.g., see Bergman, 1978). Those indicators that were appended to the TIROS-N sounding allow the user to be wary of the "bad apples" in the otherwise good TIROS-N sounding "barrel."…”

Section: Operational Polar Orbiting Satellitesmentioning

confidence: 99%

The Global Weather Experiment II. The Second Special Observing Period

Fleming¹,

Kaneshige²,

McGovern³

et al. 1979

Bulletin of the American Meteorological Society

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During the Second Special Observing Period of May and June 1979, the Global Weather Experiment reached a peak. At this time the largest concentration of resources ever assembled was deployed to meet the challenge of observing the atmosphere and oceans to an unprecedented degree. This article outlines this effort and highlights the various observing systems involved in this effort-in particular the quantity of observations gathered from each major system.

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Role of Observational Errors in Optimum Interpolation Analysis

Cited by 19 publications

References 10 publications

UKGrsHP: a UK high-resolution gauge–radar–satellite merged hourly precipitation analysis dataset

UKGrsHP: a UK high-resolution gauge–radar–satellite merged hourly precipitation analysis dataset

Available potential energy in the northern hemisphere during the FGGE year

The Global Weather Experiment II. The Second Special Observing Period

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