A Predictability Study Using Geostationary Satellite Wind Observations during NORPEX

Gelaro, Ronald; Reynolds, Carolyn A.; Langland, Rolf H.; Rohaly, G. D.

doi:10.1175/1520-0493(2001)129<3789:apsugs>2.0.co;2

Cited by 47 publications

(23 citation statements)

References 24 publications

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“…However, there is no indication that the analysis adaptation mainly corrects for model deficiencies rather than for realistic flow-dependent error structures. Singular vector computations indicate that locations of error growth show a large similarity for different models, for example, Gelaro et al (2000). This indicates a flow dependency rather than a model dependency.…”

Section: Summary Conclusion and Discussionmentioning

confidence: 99%

Sensitivity Observing System Experiment (SOSE)—a new effective NWP-based tool in designing the global observing system

Marseille

Stoffelen

Barkmeijer

2008

Tellus A: Dynamic Meteorology and Oceanography

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A B S T R A C TLacking an established methodology to test the potential impact of prospective extensions to the global observing system (GOS) in real atmospheric cases we developed such a method, called Sensitivity Observing System Experiment (SOSE). For example, since the GOS is non uniform it is of interest to investigate the benefit of complementary observing systems filling its gaps. In a SOSE adjoint sensitivity structures are used to define a pseudo true atmospheric state for the simulation of the prospective observing system. Next, the synthetic observations are used together with real observations from the existing GOS in a state-of-the-art Numerical Weather Prediction (NWP) model to assess the potential added value of the new observing system. Unlike full observing system simulation experiments (OSSE), SOSE can be applied to real extreme events that were badly forecast operationally and only requires the simulation of the new instrument. As such SOSE is an effective tool, for example, to define observation requirements for extensions to the GOS. These observation requirements may serve as input for the design of an operational network of prospective observing systems. In a companion paper we use SOSE to simulate potential future space borne Doppler Wind Lidar (DWL) scenarios and assess their capability to sample meteorologically sensitive areas not well captured by the current GOS, in particular over the Northern Hemisphere oceans.

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Section: Summary Conclusion and Discussionmentioning

confidence: 99%

Sensitivity Observing System Experiment (SOSE)—a new effective NWP-based tool in designing the global observing system

Marseille

Stoffelen

Barkmeijer

2008

Tellus A: Dynamic Meteorology and Oceanography

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“…For example, Gelaro et al (1999) showed that the impact of the additional observations during the FASTEX campaign occurs primarily as a result of changes to the analysis in the subspace of the leading SVs. Similarly, Gelaro et al (2000), although they did not attempt to estimate that added value of targeted observations, concluded that most of the improvement induced by satellite data over the northern Pacific during the NORPEX campaign resulted from changes to the analysis that project onto the leading SVs at the initial time.…”

Section: Discussionmentioning

confidence: 99%

The value of observations. II: The value of observations located in singular‐vector‐based target areas

Buizza

Cardinali

Kelly

et al. 2007

Quart J Royal Meteoro Soc

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Data-assimilation experiments have been run in seven different configurations for two seasons to assess the value of observations taken in target regions identified either using singular vectors (SVs) or randomly, and located over the Pacific or the Atlantic Oceans. The value has been measured by the relative short-range forecast error reduction in downstream areas, specifically a North American region for observations taken in the Pacific Ocean, and a European region for observations taken in the Atlantic Ocean.Overall, results have indicated (1) that observations taken in SV-target areas are on average more valuable than observations taken in randomly selected areas, (2) that it is important that the daily set of singular vectors are used to compute the target areas, and (3) that the value of targeted observations depends on the region, the season and the baseline observing system. If the baseline observing system is data-void over the ocean, then the average value of observations taken in SV-target areas is very high. Considering for example winter 2004, SV-targeted observations over the Pacific (Atlantic) reduce the day-2 forecasts error of 500 hPa geopotential height forecasts in the verification region by 27.5% (19.1%), compared to 15.7% (14.9%) for observations taken in random areas. By contrast, if the baseline observing system is data-rich over the ocean, then the average value of observations taken in SV-target areas is rather small. Considering for example winter 2004, it has been estimated that adding SV-targeted observations over the Pacific (Atlantic) would reduce, on average, the day-2 forecasts error in the verification region by 4.0% (2.0%), compared to 0.5% (1.7%) for observations in random areas. These average results have been confirmed by single-case investigations, and by a careful examination of time series of forecast errors.These results indicate that more accurate assimilation systems that can exploit the potential value of localized observations are needed to increase the average return of investments in targeting field experiments. Copyright The value of targeted observationsIn the past decade, field experiments have been organized to assess the impact of extra observations, taken in some specific, case-dependent target areas identified using objective and subjective methods, on (mainly shortrange) forecast accuracy. These campaigns, organized following a proposal at a workshop in 1995 (Snyder, 1996) The general conclusions of these campaigns (see e.g. Langland (2005) for a review of issues in targeted observing) were that in most of the cases the impact of the targeted observations was positive, and that on average the impact was small, with maximum error reductions in some specific cases for variables such as mean-sea-level pressure of about 10-15%. For example, considering observations targeted using singular vectors in five cases of the FASTEX campaign, Montani et al. (1999) concluded that the forecast impact was more evident if the verification area coincided with the ...

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“…The existing methods for adaptive observations include the singular vector technique (PALMER et al, 1998;BUIZZA and MONTANI, 1999;BERGOT et al, 1999;GELARO et al 1999GELARO et al , 2000BERGOT, 2001), the quasilinear inverse approach (PU et al, 1997;PU and KALNAY, 1999), gradient and sensitivity approaches (BERGOT et al, 1999;LANGLAND et al, 1999;BAKER and DALEY, 2000), ensemble spread techniques (LORENZ and EMANUEL, 1998;HANSEN and SMITH, 2000;MORSS, 1998;MORSS et al, 2001), the ensemble transform technique SZUNYOGH et al, 1999), and the ensemble transform Kalman filter MAJUM-statistics from an ensemble Kalman filter coupled to a quasigeostrophic model. They underscored the importance of accurate estimates of the backgrounderror covariance matrix through using different data assimilation schemes.…”

Section: Introductionmentioning

confidence: 99%

Ensemble-Based Observation Targeting for Improving Ozone Prediction in Houston and the Surrounding Area

Bei

Zhang

Nielsen‐Gammon

2011

Pure Appl. Geophys.

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This study examines the effectiveness of targeted meteorological observations for improving ozone prediction in Houston and the surrounding area based on perfect-model simulation experiments. Supplementary observations are targeted for the location that has the highest impact factor (maximum Kalman gain) estimated from an ensemble and is expected to minimize ozone forecast uncertainty at the verification time. It is found that the observational impact factor field varies with time and is sensitive to ensemble resolutions and physics parameterizations. The efficiency of observation targeting is further examined through assimilating observations in areas with different impact factors using an ensemble Kalman filter. It is found that the ensemble sensitivity analysis is capable of locating supplementary observations that may reduce meteorological and ozone forecast error, but not as effectively as expected.

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A Predictability Study Using Geostationary Satellite Wind Observations during NORPEX

Cited by 47 publications

References 24 publications

Sensitivity Observing System Experiment (SOSE)—a new effective NWP-based tool in designing the global observing system

Sensitivity Observing System Experiment (SOSE)—a new effective NWP-based tool in designing the global observing system

The value of observations. II: The value of observations located in singular‐vector‐based target areas

Ensemble-Based Observation Targeting for Improving Ozone Prediction in Houston and the Surrounding Area

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