Abstract. The concept of targeted observations was implemented during field experiments such as FASTEX, NORPEX or WSRP in order to cope with some predictability problems. The techniques of targeting used at that moment (adjointbased or ensemble transform methods) lead to quite disappointing results: the efficiency of the additional observations deployed over sensitive areas did not turn out to remain consistent from one case to another. The influence of targeted observations on the forecasts could sometimes consist of strong improvements, or sometimes strong degradations. It turns out that the latter failure explains why the concept of optimal sampling arose. The efficiency of adaptive sampling appears to depend on the assimilation scheme that deals with the observations. It is then very useful to integrate the nature of the assimilation algorithm, as well as the deployment of the conventional network of observations (redundancy issues between targeted and conventional network) in the definition of the sensitive pattern to be sampled. Therefore, we chose the tool of the sensitivity to observations to allow us to test such an approach. The sensitivity to targeted observations (that utilizes the adjoint of the linearized NWP model and the adjoint of the assimilation operator) seems to be a suitable tool to obtain an insight into the tricky issue of the optimization of the sampling strategies.To understand better the intrinsic patterns and the influence of the 3D-Var assimilation scheme on the sensitive structures to be sampled, we present here some detailed results on a FASTEX targeting case. We focus on the dropsondes deployed by the Gulfstream IV (jet-aircraft) along its first flight during Intense Observing Period 17 that started on the 17 February 1997. The sensitivity to observation is used as a diagnostic tool for studing targeting from a critical point of view. It is shown that assimilation processes can have an important effect on the classical sensitivity fields, and particularly on their vertical extension. For example, in the studied case, the classical sensitivity fields remain at a lower level than 400 hPa, whereas the sensitivity to observationsCorrespondence to: T. Bergot (Thierry.Bergot@meteo.fr) stretches up to 250 hPa. However, the maximum values can be found at approximately 700 hPa in both sensitivity fields.The studied case shows that the efficiency of observations depends not only on the sensitivity but also on the deviations between the observations and the background field. An example of the use of this diagnosis for comparing the relative efficiency of different kinds of observations is also presented. This work points out that it is very complicated to optimize the efficiency of adaptive observations, and that the assimilation of an entire set of observations (both conventional and adaptive network) needs to be considered.

SUMMARYThe adjoint sensitivity to observations which is based on the adjoint operator of the variational assimilation process is used here on ten cases of the Fronts and Atlantic Storm-Track EXperiment (FASTEX), conducted in January and February 1997. It is used as a diagnostic tool allowing one to indicate which TIROS-N (Television Infrared Observation Satellite) Operational Vertical Sounder (TOVS) channels have an in uence on the forecast of mid-latitude lows. In order to study the effects of the observations on the modi cation of the forecast from the guess, a particular cost function has been chosen: the energy of the difference between the forecast derived from the guess and the one resulting from the analysis. The rst part of the paper deals with the sensitivity to the assimilated TOVS observations for the intensive observation period 17 of FASTEX. Then, the in uence of TOVS data is compared with one of the other conventional datasets assimilated at the same time. After that, these results are generalized in an overview of the ten studied cases. This study highlights that the Microwave Sounder Unit and clear sky or partly cloudy High-resolution Infra-Red Sounder have the larger in uence of the TOVS observations on the modi cation of the forecast. However, the other conventional data have a larger absolute contribution than the TOVS ones.

Abstract.Adaptive observation is an approach to improving the quality of numerical weather forecasts through the optimization of observing networks. It is sometimes referred to as Data Targeting (DT). This approach has been applied to high impact weather during specific field campaigns in the past decade. Adaptive observations may involve various types of observations, including either specific research observing platforms or routine observing platforms employed in an adaptive way. The North-Atlantic TReC 2003 and the EURORISK-PREVIEW 2008 exercises focused on the North-Atlantic and Western Europe areas using mainly routine observing systems. These campaigns also included Mediterranean cases.The most recent campaign, DTS-MEDEX-2009, is the first campaign in which the DT method has been used to address exclusively Mediterranean high impact weather events. In this campaign, which is an important stage in the MEDEX development, only operational radiosonde stations and commercial aircraft data (AMDAR) have provided additional observations. Although specific diagnostic studies are needed to assess the impact of the extra-observations on forecast skill and demonstrate the effectiveness of DTS-MEDEX-2009, some preliminary findings can be deduced from a survey of this targeting exercise.After a description of the data targeting system and some illustrations of particular cases, this paper attempts some comparisons of additional observation needs (through effectively deployed radio-soundings) with sensitivity climatologies in the Mediterranean. The first step towards a sensitivity climatology for Mediterranean cases of high imCorrespondence to: A. Jansa (ajansac@aemet.es) pact weather is indirectly given by the frequency of extrasoundings launched from the network of radiosonde stations involved in the DTS-MEDEX-2009 campaign.

SUMMARYA new adjoint-based method to find the optimal deployment of targeted observations, called Kalman Filter Sensitivity (KFS), is introduced. The major advantage of this adjoint-based method is that it allows direct computation of the reduction of the forecast-score error variance that would result from future deployment of targeted observations. This method is applied in a very simple one-dimensional context, and is then compared to other adjoint-based products, such as classical gradients and gradients with respect to observations. The major conclusion is that the deployment of targeted observation is strongly constrained by the aspect ratio between the length-scale of the sensitivity area and the length-scale of the analysis-error covariance matrix. This very simple example also clearly illustrates that the reduction of forecast-error variance is stronger for assimilation schemes which have a smaller characteristic length-scale. Finally, the KFS technique is applied in a diagnostic way (i.e. once the observations are done) to four FASTEX cases. For these cases, the reduction of the forecasterror variance is in agreement with the efficiency of targeted observations as previously studied. A preliminary step towards an operational use has been performed on FASTEX IOP18, and results seem to validate the KFS approach of targeting.

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