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Ad Stoffelen

Abstract

The absolute calibration of the backscatter signal of a scatterometer is essential for the retrieval of optimum-quality geophysical products. The European Space Agency targeted a specification of 0.2 dB for the accuracy of the European Remote Sensing Satellite scatterometers. A radiometric error of this amount leads to a wind speed error of roughly 0.25 m s−1. An interbeam bias of the same amount may lead to notable wind direction effects. In this paper, a method is discussed to obtain an accurate calibration of a scatterometer over the ocean using an accurate backscatter-to-wind transfer function and collocated winds from a numerical weather prediction model. The method is estimated to be accurate to a precision of 0.1 dB. It can be used for instrument monitoring, and application of the calibration results has a demonstrable and beneficial impact on the wind inversion.

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Ad Stoffelen
and
David Anderson

Abstract

The geophysical interpretation of the radar measurements from the ERS-1 scatterometer, called σ 0, is considered. An important tool in the interpretation of the data is the visualization of the triplets of radar backscatter in measurement space. For a given position (or node) across the swath it is shown that the measured triplets of σ 0 are distributed around a well-defined “conical” surface and hence that the signal largely depends on just two geophysical parameters, which can be taken to be wind speed and direction. In general, the scatter of triplets is comparable to the instrumental measurement noise of 0.2 dB, which corresponds to an uncertainty in vector wind of only 0.5 m s−1. In extreme meteorological conditions, a small number of anomalous triplets is found, but these can be identified by their distance from the conical surface and flagged or rejected by the authors’ quality control procedure.

The prelaunch transfer function developed by the European Space Agency (ESA), denoted CMOD2, is shown to give a poor representation of the conical surface, with typical errors an order of magnitude larger than instrumental noise. Its sensitivity to both wind speed and direction needs revision in order to fit the backscatter characteristics, as quantified in this paper. A fourth-order harmonic appeared essential to provide the particular shape of the conical surface. The full specification of a new transfer function, known as CMOD4, adopted by ESA on 24 February 1993 has been derived by Stoffelen and Anderson.

An inversion algorithm, based on Bayes’ probability theorem, is developed that takes account of the a priori known distribution of measured backscatter triplets in measurement space, in contrast to previous inversion algorithms that have implicitly assumed a uniform distribution. To keep the transfer function as simple as possible and to optimize the inversion procedure, it is shown to be advantageous to operate in a transformed space: z = (σ 0)0.625.

The conical surface on which the data lie consists of two closely overlapping sheaths, which results, after the inversion, in two wind vector solutions of roughly opposite direction and almost equal probability. Visualization of this data surface shows clearly that there is little possibility of removing the above directional ambiguity from backscatter data alone: external information, for example, from a numerical weather forecast model is needed to resolve the ambiguity. A wind direction skill parameter, useful in the ambiguity removal, is introduced, based on the position of a measured triplet relative to the cone.

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Siebren de Haan
and
Ad Stoffelen

Abstract

In this paper the beneficial impacts of high-resolution (in space and time) wind and temperature observations from aircraft on very short-range numerical weather forecasting are presented. The observations are retrieved using the tracking and ranging radar from the air traffic control facility at Schiphol Airport, Amsterdam, the Netherlands. This enhanced surveillance radar tracks all aircraft in sight every 4 s, generating one million wind and temperature observations per day in a radius of 270 km around the radar. Nowcasting applications will benefit from improved three-dimensional wind fields. When these observations are assimilated into a numerical model with an hourly update cycle, the short-range three-dimensional wind field forecasts match the observations better than those from an operational forecast cycle, which is updated every 3 h. The positive impact on wind in the first hours of the forecast gradually turns into a neutral impact, when compared to other wind and temperature observations. The timeliness of the forecasts combined with the high resolution of the observations are the main reasons for the observed nowcasting benefits. All in all, the assimilation of high-resolution wind (and temperature) observations is found to be beneficial for nowcasting and short-range forecasts up to 2–3 h.

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Bernd Dieter Becker
,
Hervé Roquet
, and
Ad Stoffelen

A database for study of the impact of Doppler wind lidar data on numerical weather prediction in Observation System Simulation Experiments was created. Five Doppler wind lidar scenarios, TIROS Operational Vertical Sounder, Advanced TIROS Operational Vertical Sounder, Advanced Scatterometer, and all conventional observation types with a realistic distribution in time and space have been successfully simulated. A 30-day run of the ECMWF forecast model was used as a physically sound reference state. This “true” atmospheric state was sampled at the observation positions and times. The simulated true variables were mapped onto the “measured” variables, and a mix of random and gross errors with realistic statistical characteristics was added. The simulated observations were validated by comparison with existing data where available.

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Karim Houchi
,
Ad Stoffelen
,
Gert-Jan Marseille
, and
Jos De Kloe

Abstract

Quality control (QC) is among the most important steps in any data processing. These steps are elaborated for high-vertical-resolution radiosonde datasets that were gathered and analyzed to study atmospheric winds. The database is composed of different radiosonde wind-finding systems (WFSs), including radio theodolite, Loran C, and GPS. Inspection of this database, particularly for wind, wind shear, and ascent height increments (dz), showed a nonnegligible amount of outliers in radio theodolite data as compared to the two other WFSs, thus denoting quality differences between the various systems. An effective statistical QC (SQC) is then developed to isolate and eliminate outliers from the more realistic observations. Improving the accuracy of the radio theodolite WFS is critical to the derivation of the vertical motion and the vertical gradients of the horizontal wind—that is, wind shear—mainly because of the direct dependence of these quantities on dz. Based on the climatological distribution of the quality-controlled dz, a new approach is suggested to estimate these wind quantities for radio theodolite data. The approach is validated with the high-quality modern WFSs (Loran C and GPS). Although initially of reduced quality, applying SQC and using the climatological mean dz of 12-s smoothed radio theodolite profiles shows very good improvement in the climatological wind analyses of radio theodolite WFSs. Notably, the climatologies of ascent rate, vertical motion, horizontal wind, and vertical shear now look comparable for the various WFSs. Thus, the SQC processing steps prove essential and may be extended to other variables and measurement systems.

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Jur Vogelzang
,
Ad Stoffelen
,
Anton Verhoef
,
John de Vries
, and
Hans Bonekamp

Abstract

A two-dimensional variational ambiguity removal technique (2DVAR) is presented. It first makes an analysis based on the ambiguous scatterometer wind vector solutions and a model forecast, and next selects the ambiguity closest to the analysis as solution. 2DVAR is applied on SeaWinds scatterometer data and its merits for nowcasting applications are shown in a general statistical comparison with model forecasts and buoy observations, and in a number of case studies. The sensitivity of 2DVAR to changes in the parameters of its underlying error model is studied. It is shown that observational noise in the nadir swath of SeaWinds is effectively suppressed by application of 2DVAR in combination with the multisolution scheme (MSS). MSS retains the local wind vector probability density function after inversion, rather than only a limited number of ambiguous solutions. As a consequence, the influence of the background increases, but this can be mitigated by switching off variational quality control. A case study on an extratropical cyclone of hurricane force intensity observed with SeaWinds at 25-km resolution shows that reliable wind estimates can be obtained for wind speeds up to 40 m s−1 and more. At 25 km, the results of 2DVAR with MSS compare better with buoy measurements than with the ECMWF model. At 100-km resolution this is reversed, proving that 2DVAR retrieves small-scale features absent in the ECMWF model.

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Nedjeljka Žagar
,
Ad Stoffelen
,
Gert-Jan Marseille
,
Christophe Accadia
, and
Peter Schlüssel

Abstract

This paper deals with the dynamical aspect of variational data assimilation in the tropics and the role of the background-error covariances in the observing system simulation experiments for the tropics. The study uses a model that describes the horizontal structure of the potential temperature and wind fields in regions of deep tropical convection. The assimilation method is three- and four-dimensional variational data assimilation. The background-error covariance model for the assimilation is a multivariate model that includes the mass–wind couplings representative of equatorial inertio-gravity modes and equatorial Kelvin and mixed Rossby–gravity modes in addition to those representative of balanced equatorial Rossby waves. Spectra of the background errors based on these waves are derived from the tropical forecast errors of the European Centre for Medium-Range Weather Forecasts (ECMWF) model.

Tropical mass–wind (im)balances are illustrated by studying the potential impact of the spaceborne Doppler wind lidar (DWL) Atmospheric Dynamic Mission (ADM)-Aeolus, which measures horizontal line-of-sight (LOS) wind components. Several scenarios with two DWLs of ADM-Aeolus type are compared under different flow conditions and using different assumptions about the quality of the background-error covariances.

Results of three-dimensional variational data assimilation (3DVAR) illustrate the inefficiency of multivariate assimilation in the tropics. The consequence for the assimilation of LOS winds is that the missing part of the wind vector can hardly be reconstructed from the mass-field observations and applied balances as in the case of the midlatitudes.

Results of four-dimensional variational data assimilation (4DVAR) show that for large-scale tropical conditions and using reliable background-error statistics, differences among various DWL scenarios are not large. As the background-error covariances becomes less reliable, horizontal scales become smaller and the flow becomes less zonal, the importance of obtaining information about the wind vector increases. The added value of another DWL satellite increases as the quality of the background-error covariances deteriorates and it can be more than twice as large as in the case of reliable covariances.

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Ad Stoffelen
,
Gert-Jan Marseille
,
Erik Andersson
, and
David G. H. Tan
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Ad Stoffelen
,
Jean Pailleux
,
Erland Källén
,
J. Michael Vaughan
,
Lars Isaksen
,
Pierre Flamant
,
Werner Wergen
,
Erik Andersson
,
Harald Schyberg
,
Alain Culoma
,
Roland Meynart
,
Martin Endemann
, and
Paul Ingmann

The prime aim of the Atmospheric Dynamics Mission is to demonstrate measurements of vertical wind profiles from space. Extensive studies conducted by the European Space Agency over the past 15 years have culminated in the selection of a high-performance Doppler wind lidar based on direct-detection interferometric techniques. Such a system, with a pulsed laser operating at 355-nm wavelength, would utilize both Rayleigh scattering from molecules and Mie scattering from thin cloud and aerosol particles; measurement of the residual Doppler shift from successive levels in the atmosphere provides the vertical wind profiles. The lidar would be accommodated on a satellite flying in a sun-synchronous orbit, at an altitude of ~400 km, providing near-global coverage; target date for launch is in 2007. Processing of the backscatter signals will provide about 3000 globally distributed wind profiles per day, above thick clouds or down to the surface in clear air, at typically 200-km separation along the satellite track. Such improved knowledge of the global wind field is crucial to many aspects of climate research and weather prediction. Knowledge over large parts of the Tropics and major oceans is presently quite incomplete—leading to major difficulties in studying key processes in the climate system and in improving numerical simulations and predictions; progress in climate modeling is indeed intimately linked to progress in numerical weather prediction. The background studies, potential impact on climate and weather prediction, choice of measurement specifications, and the lidar technology are discussed.

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Ad Stoffelen
,
Angela Benedetti
,
Régis Borde
,
Alain Dabas
,
Pierre Flamant
,
Mary Forsythe
,
R. Michael Hardesty
,
Lars Isaksen
,
Erland Källén
,
Heiner Körnich
,
Tsengdar Lee
,
Oliver Reitebuch
,
Michael Rennie
,
Lars-Peter Riishøjgaard
,
Harald Schyberg
,
Anne Grete Straume
, and
Michael Vaughan
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