Doppler Radar Wind Data Assimilation with HIRLAM 3DVAR

Lindskog, Magnus; Salonen, Kirsti; Järvinen, Heikki; Michelson, Daniel

doi:10.1175/1520-0493(2004)132<1081:drwdaw>2.0.co;2

Cited by 60 publications

(60 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The spatial averaging has a tendency to smooth the observed wind field and to effectively average out random errors. Details of the averaging procedure can be found in (Lindskog et al, 2004).…”

Section: Datamentioning

confidence: 99%

“…The variational data-assimilation technique provides a framework for appropriately relating the model variables to observed quantities, such as Doppler-radar radial winds (e.g. Lindskog et al, 2004;Sun and Crook, 1997). Direct use of the Doppler-radar radial winds has the benefit of making use of the nonlinear information about the wind field.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Bias estimation of Doppler‐radar radial‐wind observations

Salonen

Järvinen

Eresmaa

et al. 2007

Quart J Royal Meteoro Soc

Self Cite

View full text Add to dashboard Cite

Doppler radars provide measurements of the radar radial wind component at high spatial and temporal resolution. The variational data-assimilation framework enables direct use of these measurements in numerical weather prediction models. Bias estimation of Doppler-radar radial winds requires special attention because of the azimuthal scanning strategy. Calculation of the bias statistic over all azimuthal directions results in a near-zero value even in the presence of systematic differences between the measured and modelled wind speed and direction. This paper describes a method for bias estimation of Doppler-radar radial-wind observations. Intercomparison between the estimated biases of Doppler-radar and radiosonde wind observations reveals that the wind speed and direction biases are of comparable magnitude.

show abstract

Section: Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bias estimation of Doppler‐radar radial‐wind observations

Salonen

Järvinen

Eresmaa

et al. 2007

Quart J Royal Meteoro Soc

Self Cite

View full text Add to dashboard Cite

show abstract

“…Improvements to forecasts for these lead times are now being sought through the assimilation into mesoscale models of surface rain rates derived from radar reflectivity using latent heat nudging methods (Macpherson et al, 1996) and variational techniques in which model 'reflectivity' is compared with actual measured reflectivity (Sun and Crook, 2001). More recently, Doppler radar radial winds have also been assimilated into NWP models as vertical wind profiles derived from Velocity Azimuth Display (VAD) analysis (Benjamin et al, 2004) and using variational techniques; see Crook (1997, 1998), Crook and Sun (2004), Lindskog et al(2004), Gao (1999Gao ( , 2006 and Qiu et al (2006).…”

Section: Introductionmentioning

confidence: 99%

Assimilation of Doppler radial winds into a 3D‐Var system: Errors and impact of radial velocities on the variational analysis and model forecasts

Rihan

Collier

Ballard

et al. 2008

Quart J Royal Meteoro Soc

View full text Add to dashboard Cite

A pre-processing approach to the assimilation of Doppler radar radial wind data into a high resolution Numerical Weather Prediction (NWP) model is described. We discuss the types of errors which might occur in radar radial winds. The construction of simulated high resolution radar data containing such errors is described. Examples of these data are presented and compared with actual radar data from the Chilbolton S-band radar located in central southern England. A new approach to specifying the radial velocity observation error is proposed based upon the radial gradient of the velocity along the pulse volume. The production of 'super-observations' for input to a 3D-Var assimilation system is discussed. Impact of the assimilation of Doppler velocities on the 3D-Var analysis and on the model forecasts, for two case-studies, are shown.

show abstract

“…Caumont et al, 2006a) and Doppler radar radial winds (e.g. Sun and Crook, 1997;Lindskog et al, 2004). Observation modelling is a key element for data assimilation of such observations.…”

Section: Introductionmentioning

confidence: 99%

Doppler radar radial wind data in NWP model validation

Salonen¹,

Järvinen²,

Järvenoja³

et al. 2008

Meteorological Applications

View full text Add to dashboard Cite

Validation of mesoscale numerical weather prediction models calls for high-resolution observations. Conventional data sources, such as radiosonde data, provide a reliable benchmark but their spatial resolution is insufficient for model validation in the kilometric scale. Doppler radar radial wind observations are used in this study as an alternative data source for model validation. Data assimilation system in general, and observation modelling in particular, are used as a toolbox for validation.Two versions of the High Resolution Limited Area Model (HIRLAM), which differ only in the formulation of the surface stress direction, are validated over a period of 1 month. The observation minus background (OmB) statistics advocate the merits of using high-resolution radar data as model validation material. It is demonstrated that subtle differences in model versions due to different parameterization details can be distinguished with high statistical confidence.

show abstract

Doppler Radar Wind Data Assimilation with HIRLAM 3DVAR

Cited by 60 publications

References 21 publications

Bias estimation of Doppler‐radar radial‐wind observations

Bias estimation of Doppler‐radar radial‐wind observations

Assimilation of Doppler radial winds into a 3D‐Var system: Errors and impact of radial velocities on the variational analysis and model forecasts

Doppler radar radial wind data in NWP model validation

Contact Info

Product

Resources

About