Adaptive bias correction for satellite data in a numerical weather prediction system

Auligné, Thomas; McNally, A. P.; Dee, Dick

doi:10.1002/qj.56

Cited by 302 publications

(243 citation statements)

References 12 publications

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“…For microwave instruments, biases are inferred as functions of predictors including the scan angle, the surface wind speed and the layer thickness, though the exact set of predictors is channel dependent. Bias coefficients are derived within the analysis system using variational bias correction (VarBC, Dee, 2004;Auligné et al, 2007). There are no cloud-related predictors and the bias correction is not intended to represent cloud-or precipitation-dependent biases.…”

Section: Ecmwf Systemmentioning

confidence: 99%

Improved scattering radiative transfer for frozen hydrometeors at microwave frequencies

2014

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Abstract. To simulate passive microwave radiances in allsky conditions requires better knowledge of the scattering properties of frozen hydrometeors. Typically, snow particles are represented as spheres and their scattering properties are calculated using Mie theory, but this is unrealistic and, particularly in deep-convective areas, it produces too much scattering in mid-frequencies (e.g. 30-50 GHz) and too little scattering at high frequencies (e.g. 150-183 GHz). These problems make it hard to assimilate microwave observations in numerical weather prediction (NWP) models, particularly in situations where scattering effects are most important, such as over land surfaces or in moisture sounding channels. Using the discrete dipole approximation to compute scattering properties, more accurate results can be generated by modelling frozen particles as ice rosettes or simplified snowflakes, though hexagonal plates and columns often give worse results than Mie spheres. To objectively decide on the best particle shape (and size distribution) this study uses global forecast departures from an NWP system (e.g. observation minus forecast differences) to indicate the quality of agreement between model and observations. It is easy to improve results in one situation but worsen them in others, so a rigorous method is needed: four different statistics are checked; these statistics are required to stay the same or improve in all channels between 10 GHz and 183 GHz and in all weather situations globally. The optimal choice of snow particle shape and size distribution is better across all frequencies and all weather conditions, giving confidence in its physical realism. Compared to the Mie sphere, most of the systematic error is removed and departure statistics are improved by 10 to 60 %. However, this improvement is achieved with a simple "one-size-fits-all" shape for snow; there is little additional benefit in choosing the particle shape according to the precipitation type. These developments have improved the accuracy of scattering radiative transfer sufficiently that microwave all-sky assimilation is being extended to land surfaces, to higher frequencies and to sounding channels.

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Section: Ecmwf Systemmentioning

confidence: 99%

Improved scattering radiative transfer for frozen hydrometeors at microwave frequencies

2014

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“…Radiance data is the primary contributor to NWP assimilation schemes. However, biases in satellite measurements-especially in the higher stratosphere-are of particular concern, as this may have an adverse effect on weather forecasts, even for near-term forecasts [Auligné et al, 2007].…”

Section: 1002/2014jd021632mentioning

confidence: 99%

Evaluation of wind and temperature profiles from ECMWF analysis on two hemispheres using volcanic infrasound

et al. 2014

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In this paper, we evaluate vertical wind and temperature profiles that are produced by the European Centre for Medium‐Range Weather Forecasts (ECMWF) atmospheric analysis. The evaluation is carried out on both hemispheres: we make use of stratospheric infrasound arrivals from Mount Etna (37°N) and Mount Yasur (22°S). The near‐continuous, high activity of both volcanoes permits the study of stratospheric propagation along well‐defined paths with a time resolution ranging from hours to multiple years. Infrasound observables are compared to theoretical estimates obtained from acoustic propagation modeling using the ECMWF analysis. While a first‐order agreement is found for both hemispheres, we report on significant discrepancies around some of the equinox periods and other intervals during which the atmosphere is in a state of transition and dynamical oscillations of the atmosphere dominate over the general circulation. We present an inversion study in which we make use of measured trace velocity estimates to estimate first‐order effective sound speed model updates in a Bayesian framework. Deviations from the a priori models around the stratopause up to 10% (≈ 30 m s−1) are estimated. Such updates are in line with the results from comparisons between ECMWF analysis and observations from lidar and microwave Doppler spectroradiometer facilities that were colocated during the course of the 2012–2013 Atmospheric dynamics Research and InfraStructure in Europe (ARISE) measurement campaign.

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“…The random error has been added to the observations after the background quality control. The coefficients of the variational scheme for the satellite radiances bias-correction [Auligné et al, 2007] have been computed independently for each member in order to slightly decrease the correlation between the ensemble members. The sea surface temperature is also perturbed with a simple Gaussian low-resolution perturbation with variance equal to the monthly SST climatological anomaly.…”

Section: Limited-area Ensemble Variational Assimilation With Unperturmentioning

confidence: 99%

Ensemble variational assimilation for the representation of background error covariances in a high‐latitude regional model

Storto¹,

Randriamampianina²

2010

J. Geophys. Res.

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[1] Statistical objective analysis requires the explicit specification of the observation and background error covariances. This paper deals with the estimation of the latter within a high-latitude regional model. Four different approaches have been adopted to simulate the error evolution in the analysis and forecast steps of the model: i) the largely-adopted NMC method, applied to both a winter and a summer season data set, ii) global ensemble analyses projected forward to the 6-hour forecast range by the limited-area model itself, iii) limited-area ensemble variational assimilation with unperturbed lateral boundary conditions (LBCs) and iv) limited-area ensemble variational assimilation with perturbed lateral boundary conditions. The structure of the four background error covariance matrices was extensively compared. It turned out that the NMC-derived standard deviations had stronger amplitude at the large scales, especially in the lower troposphere, compared to those derived using the ensemble technique, and much broader horizontal and large-scale vertical correlations. The contribution of lateral boundary perturbations is shown to be significant. Moreover, neglecting these LBCs perturbations contributes to unrealistic features, such as artificial small variances near the boundaries, which tend to spuriously propagate towards the inner area. Furthermore, humidity variances and associated cross-covariances tend to be weaker in the ensemble assimilation experiments, in particular when lateral boundary conditions are not perturbed. A onemonth assimilation period allowed us to evaluate the impact of the different background error statistics on the forecasts: wind, geopotential and partly temperature are clearly benefiting from the use of ensemble-based background error covariances; humidity skill scores are noticeably improved when background error covariances from limited-area ensemble assimilation were used. The seasonality of the background error structures was also investigated, and it was found non-negligible for the performance of the data assimilation and forecast systems.Citation: Storto, A., and R. Randriamampianina (2010), Ensemble variational assimilation for the representation of background error covariances in a high-latitude regional model,

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Adaptive bias correction for satellite data in a numerical weather prediction system

Cited by 302 publications

References 12 publications

Improved scattering radiative transfer for frozen hydrometeors at microwave frequencies

Improved scattering radiative transfer for frozen hydrometeors at microwave frequencies

Evaluation of wind and temperature profiles from ECMWF analysis on two hemispheres using volcanic infrasound

Ensemble variational assimilation for the representation of background error covariances in a high‐latitude regional model

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