Estimation of Synoptic and Mesoscale Forecast Error Covariances in a Limited-Area Model

Berre, Loïk

doi:10.1175/1520-0493(2000)128<0644:eosamf>2.0.co;2

Cited by 164 publications

(231 citation statements)

References 14 publications

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“…This figure is available in colour online at www.interscience.wiley.com/journal/qj of observations as the ones used operationally in the ALADIN-France model (Montmerle et al, 2007;Yan et al, 2009), including observations from radiosoundings, screen-level stations, buoy, ship and aircraft measurements, wind profilers, horizontal winds from atmospheric motion vectors (AMVs) and the QuickSCAT scatterometers, infrared radiances from the Advanced Tiros Operational Vertical Sounder (ATOVS) and the Spinning Enhanced Visible and InfraRed Imager (SEVIRI). The background-error covariance matrix shares also the same multivariate formulation as in ALADIN-France (Berre, 2000). The background-error statistics have been calculated using an ensemble-based method , with a six-member ensemble of AROME forecasts carried out over two 15 d periods; the initial and lateral boundary conditions were provided by an ensemble of perturbed ARPEGE/ALADIN-France assimilation ensemble .…”

Section: Assimilation Experimentsmentioning

confidence: 99%

The benefit of GPS zenith delay assimilation to high‐resolution quantitative precipitation forecasts: a case‐study from COPS IOP 9

Yan

Ducrocq

Jaubert

et al. 2009

Quart J Royal Meteoro Soc

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ABSTRACT:The benefit of assimilating high spatial and temporal resolution Global Positioning System (GPS) zenith tropospheric delay (ZTD) observations within a high-resolution numerical weather prediction (NWP) system is evaluated during IOP 9 of the Convective and Orographically-induced Precipitation Study (COPS) campaign. In the framework of the international COPS field experiment, which took place from June to August 2007, a dense GPS network was deployed in the Vosges mountain region in eastern France and in the Black Forest region in southwestern Germany.GPS ZTD observations collected during the COPS field campaign, in addition to the European operational GPS data, are assimilated into the AROME/3D-Var system. We investigate the impact of assimilating these GPS ZTD observations on the forecast of convective systems that travelled over eastern France during the three days of COPS IOP 9 (18-20 July 2007). The results show a clear positive impact on short-range quantitative precipitation forecasts when GPS ZTD observations are assimilated. The impact is most important on 19 July 2007 (IOP 9b). The present study benefits from additional validation measurements collected during the COPS campaign. In particular we find that the assimilation of ZTD data induces changes in the low-to-middle tropospheric water vapour vertical structure that are consistent with water vapour measurements from radiosonde and airborne lidar.As most of the improvement is gained by assimilating GPS ZTD observations from the European operational GPS network, this study opens up encouraging horizons for the assimilation of GPS ZTD in new high-resolution operational NWP systems.

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Section: Assimilation Experimentsmentioning

confidence: 99%

The benefit of GPS zenith delay assimilation to high‐resolution quantitative precipitation forecasts: a case‐study from COPS IOP 9

Yan

Ducrocq

Jaubert

et al. 2009

Quart J Royal Meteoro Soc

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“…The spreading in space is handled suitably by the application of horizontal and vertical correlations. From studies such as, Berre (2000Berre ( ), Ž agar et al (2005, Berre et al (2006), Caron and Fillion (2010), one can find the role of balance constraints across different analysis variables. However, in different latitude regions, little is known about the contribution of different analysis variables towards the balanced part of other variables.…”

Section: Introductionmentioning

confidence: 99%

Balance characteristics of multivariate background error covariances and their impact on analyses and forecasts in tropical and Arctic regions

Chen

Rizvi

Huang

et al. 2013

Meteorol Atmos Phys

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For variational data assimilation, the background error covariance matrix plays a crucial role because it is strongly linked with the local meteorological features, and is especially dominated by error correlations between different analysis variables. Multivariate background error (MBE) statistics have been generated for two regions, namely the Tropics (covering Indonesia and its neighborhood) and the Arctic (covering high latitudes). Detailed investigation has been carried out for these MBE statistics to understand the physical processes leading to the balance (defined by the forecasts error correlations) characteristics between mass and wind fields for the low and high latitudes represented by these two regions. It is found that in tropical regions, the unbalanced (full balanced) part of the velocity potential (divergent part of wind) contributes more to the balanced part of the temperature, relative humidity, and surface pressure fields as compared with the stream function (rotational part of wind). However, the exact opposite happens in the Arctic. For both regions, the unbalanced part of the temperature field is the main contributor to the balanced part of the relative humidity field. Results of single observation tests and six-hourly data assimilation cycling experiments are consistent with the respective balance part contributions of different fields in the two regions. This study provides an understanding of the contrasting dynamical balance relationship that exists between the mass and wind fields in high-and low-latitude regions. The study also examines the impact of MBE on Weather Research and Forecasting model forecasts for the two regions.

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“…The background-error formulation for the HIRLAM variational data assimilation Lindskog et al, 2001) is based on a multivariate statistically determined balance constraint (Berre, 2000) with specific humidity as the assimilation control variable for moisture:…”

Section: A Multivariate Moisture Balance Formulationmentioning

confidence: 99%

“…In order to illustrate the effects of the new moisture assimilation, simulated observation experiments were carried out and compared with equivalent experiments using the reference assimilation based on specific humidity as the assimilation control variable and the moisture balance formulation of Berre (2000). The simulated observation assimilation experiments were carried out with a single iteration in the outer minimization loop.…”

Section: Simulated Observation Assimilation Experimentsmentioning

confidence: 99%

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Use of a nonlinear pseudo‐relative humidity variable in a multivariate formulation of moisture analysis

Gustafsson

Þorsteinsson

Stengel

et al. 2011

Quart J Royal Meteoro Soc

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We present a reformulation of the humidity part of the HIRLAM (HIgh-Resolution Limited-Area Model) variational data assimilation. The purpose is to rectify some of the shortcomings of the present formulation which uses specific humidity, q, as an assimilation control variable with homogeneous and static covariances. One problem is that specific humidity forecast errors tend to have a non-Gaussian probability distribution, in particular near saturation and near zero humidity. In addition, the variance of the distribution tends to change in space and time due to the dependency of the water vapour saturation pressure on temperature. A modified pseudo-relative humidity variable has been adapted to the statistical balance background constraint, including the associated moisture balance formulation. Background-error statistics for the new moisture control variable and the moisture-related balances were derived, taking differences between forecasts valid at the same time as a proxy for background forecast errors. The background-error statistics were compared with the corresponding statistics for specific humidity as the moisture assimilation control variable. In connection with the nonlinearity of the change of the variable, it was noted that specified background-error standard deviations were chosen to be substantially reduced for nearly dry and saturated states, which can raise difficulties. The impact of the new moisture assimilation control variable is illustrated with simulated observation experiments as well as data assimilation experiments using real observations, for one summer month and one winter month in a 4D-Var assimilation cycle using two outer

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Estimation of Synoptic and Mesoscale Forecast Error Covariances in a Limited-Area Model

Cited by 164 publications

References 14 publications

The benefit of GPS zenith delay assimilation to high‐resolution quantitative precipitation forecasts: a case‐study from COPS IOP 9

The benefit of GPS zenith delay assimilation to high‐resolution quantitative precipitation forecasts: a case‐study from COPS IOP 9

Balance characteristics of multivariate background error covariances and their impact on analyses and forecasts in tropical and Arctic regions

Use of a nonlinear pseudo‐relative humidity variable in a multivariate formulation of moisture analysis

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