In this paper, Science Operations Planning Expertise (SOPE) is defined as the expertise that is held by people who have the two following qualities. First they have both theoretical and practical experience in operations planning, in general, and in space science operations planning in particular. Second, they can be used, on request and at least, to provide with advice the teams that design and implement science operations systems in order to optimise the performance and productivity of the mission. However, the relevance and use of such SOPE early on during the Mission Design Phase (MDP) is not sufficiently recognised. As a result, science operations planning is often neglected or poorly assessed during the mission definition phases. This can result in mission architectures that are not optimum in terms of cost and scientific returns, particularly for missions that require a significant amount of science operations planning. Consequently, science operations planning difficulties and cost underestimations are often realised only when it is too late to design and implement the most appropriate solutions. In addition, higher costs can potentially reduce both the number of new missions and the chances of existing ones to be extended. Moreover, the quality, and subsequently efficiency, of SOPE can vary greatly. This is why we also believe that the best possible type of SOPE requires a structure similar to the ones of existing bodies of expertise dedicated to the data processing such as the International Planetary Data Alliance (IPDA), the Space Physics Archive Search and Extract (SPASE) or the Planetary Data System (PDS). Indeed, this is the only way of efficiently identifying science operations planning issues and their solutions as well as of keeping track of them in order to apply them to new missions. Therefore, this paper advocates for the need to allocate resources in order to both optimise the use of SOPE early on during the MDP and to perform, at least, a feasibility study of such a more structured SOPE. (C) 2011 COSPAR. Published by Elsevier Ltd. All rights reserved.

This paper is one of the components of a larger framework of activities whose purpose is to improve the performance and productivity of space mission systems, i.e. to increase both what can be achieved and the cost effectiveness of this achievement. Some of these activities introduced the concept of Functional Architecture Module (FAM); FAMs are basic blocks used to build the functional architecture of Plan Management Systems (PMS). They also highlighted the need to involve Science Operations Planning Expertise (SOPE) during the Mission Design Phase (MDP) in order to design and implement efficiently operation planning systems. We define SOPE as the expertise held by people who have both theoretical and practical experience in operations planning, in general, and in space science operations planning in particular. Using ESA’s methodology for studying and selecting science missions we also define the MDP as the combination of the Mission Assessment and Mission Definition Phases. However, there is no generic procedure on how to use FAMs efficiently and systematically, for each new mission, in order to analyse the cost and feasibility of new missions as well as to optimise the functional design of new PMS; the purpose of such a procedure is to build more rapidly and cheaply such PMS as well as to make the latter more reliable and cheaper to run. This is why the purpose of this paper is to provide an embryo of such a generic procedure and to show that the latter needs to be applied by people with SOPE during the MDP. The procedure described here proposes some initial guidelines to identify both the various possible high level functional scenarii, for a given set of possible requirements, and the information that needs to be associated with each scenario. It also introduces the concept of catalogue of generic functional scenarii of PMS for space science missions. The information associated with each catalogued scenarii will have been identified by the above procedure and will be relevant only for some specific mission requirements. In other words, each mission that shares the same type of requirements that lead to a list of specific catalogued scenarii can use this latter list of scenarii (regardless of whether the mission is a plasma, planetary, astronomy, etc. mission). The main advantages of such a catalogue are that it speeds-up the execution of the procedure and makes the latter more reliable. Ultimately, the information associated to each relevant scenario (from the catalogue or freshly generated by the procedure) will then be used by mission designers to make informed decisions, including the modification of the mission requirements, for any missions. In addition, to illustrate the use of such a procedure, the latter is applied to a case study, i.e. the Cross-Scale mission. One of the outcomes of this study is an initial set of generic functional scenarii. Finally, although border line with the above purpose of this paper, we also discuss multi-spacecraft specific issues and issues related to the on-board execution of the plan update system (PUS). In particular, we show that the operation planning cost of N spacecraft is not equal to N times the cost of 1 spacecraft and that on-board non-synchronised operation will not require inter-spacecraft communication. We also believe that on-board PUS should be made possible for all missions as a standard.

The number and complexity of systems that control Space Science Missions continues to increase. As a result, it is desirable to improve the efficiency of these systems and, in particular, their performance and their productivity. In this paper, we set out a strategy to achieve this goal. In order to talk about improving the Performance and Productivity of a system we need to discuss the functional architecture of the system. In order to make progress, our strategy is to develop a generic methodology that decomposes the functional architecture of a Space Science Mission System and uses this decomposition to identify areas where improvements can be made. This paper concentrates on the decomposition of one specific component, namely the Plan Management System. The purpose of the Plan Management System is to produce an operation plan that contains the directives that will operate the various nodes, i.e. physical parts, of the system such as the ground stations, the spacecraft, the instruments, or even human beings (when these are following specific instructions). In order to be generic, the decomposition of the Plan Management System must make no assumptions about the purpose and implementation choices that must ultimately be made. In order to describe a functional architecture, it must also make no assumptions about the nature and purpose of the nodes that the system will operate or the nodes on which it will run. In particular, it makes no assumptions as to whether the execution of the Plan Management System components is manual or automated or whether the functions will be executed on the ground or in space. The methodology is based on the key points that more than one functional architecture can be used to satisfy a given set of system requirements and that a one-fit-for-all functional architecture is impossible to achieve (due to the variety of requirements). Therefore, in developing the methodology, we use the concept of a Functional Architecture Module (FAM) to create the generic decomposition. The resulting Plan Management System architectures are constructed as an assembly of building blocks, the Functional Architecture Modules, which can call each other. We have identified seven modules of this kind. Specific requirements can allow, impose or forbid the use of particular modules so we discuss the criteria to decide whether a given module is relevant in a given situation. This can help current and future mission planning system designers who may wish to use the FAMs, or something equivalent, to design the functional architecture of their system(s). In addition, we propose seven practical steps to improve the performance and productivity during the design, implementation and execution of the Plan Management System. Finally, we would like to stress that this methodology is far from being abstract and is currently being used to develop generic (in the sense given above) planning tools and procedures. Indeed, FAMs facilitate the separation of generic systems requirements from implementation choices/constraints. Such a separation prevents prescriptive design and implementation.

The first of the Geostationary Earth Radiation Budget (GERB) instruments has been delivering data since 2003 and has been in regular operational service since February 2004. The validation of the data has proven challenging (see paper by Russell in these proceedings), but the first public release of the data took place in May 2006. Building on from the success of the first GERB instrument, three more have been built in order to provide a consistent climate dataset for well over a decade.This paper is an update of the one presented at the second MSG RAO workshop (Allan [11]). Some of the basic information about the instruments is repeated here to avoid the need for cross reference.

The Geostationary Earth Radiation Budget experiment (GERB) is an absolute radiometer measuring the reflected shortwave (SW) and emitted longwave (LW) radiation from the Earth, from the Meteosat-8 spacecraft. From these measurements, the radiative energy balance of the part of the Earth seen from this geosynchronous vantage point are derived every 15 minutes, with a sub-satellite spatial resolution of 48km. The paper will report on the operation of the instrument, the accuracy of the radiances and fluxes obtained, the status of the instrument calibration, and results of research into convective cloud radiative forcing, and aerosol-radiation interactions over Africa and the Atlantic. Introduction The Geostationary Earth Radiation Budget (GERB) sensor is an instrument of opportunity on the Meteosat-8 spacecraft. It is a broadband radiometer, measuring the reflected shortwave (SW) and emitted longwave (LW) radiation at the top of the atmosphere (TOA). The instrument and operations are described in detail in Harries et al. (2005) and a brief summary is given here. At the heart of the instrument is a 256-element detector array, aligned in the north-south direction, and a primary mirror rotating counter to the spacecraft spin direction. The detectors are sensitive to radiation from 0.32μm to ~100μm (TOTAL channel), and a quartz filter cuts out wavelengths above 4μm when measuring the SW channel. As the Earth comes into the field of view (FOV) of the sensor, the mirror directs a frozen beam of radiation to the detectors. A scan begins by observing the area of space adjacent to the earth and the location observed by the north-south detector array is moved by one pixel width in the east-west direction on subsequent rotations until space is viewed again on the other side of the Earth’s disk. A complete scan consists of 256x282 pixels in the SW and TOTAL channels, with a nadir resolution of ~50km. A combination of the space viewed and the internal blackbody observations are used to convert the instrument voltages to filtered TOTAL and SW radiances. The radiances are geolocated and rectified to a 256x256 pixel grid. These are then unfiltered to remove effects of the sensor spectral and spatial responses and the LW radiance field is produced by removing the SW signal from the TOTAL channel. To convert the radiances to fluxes, a scene identification process retrieves surface type and cloud properties from the SEVIRI narrowband channels. Angular dependency models derived from CERES-TRMM are used in the radiance to flux conversion process. The radiance and flux data products are then resolution-enhanced using the higherresolution SEVIRI data to a ~9km nadir resolution. Figure 1. TOTAL and SW scans prior to level 1.5 processing. Each scan consists of approximately 280 lines of 256 detector observations. The GERB instrument on board Meteosat-8 has been providing almost continuous data since 2003. The validation of these data is ongoing and the current results from validation are presented below. The official release of data for science users will take place following a reprocessing of the data collected to date, and remaining data issues are indicated. Also presented are results from ongoing research at Imperial College into cloud and aerosol radiative forcing using GERB, GERB-like and SEVIRI data. Validation Results The primary means of validation of GERB radiances and fluxes is through intercomparison with the Cloud and Earth’s Radiant Energy System (CERES) instruments on board the Terra and Aqua instruments. A special scanning mode is implemented for CERES data collection on a regular basis to maximise the number of coangular, co-located data points for this purpose. The results shown below use Edition 8 (Instantaneous ERBE-like TOA estimates) from CERES FM-2 on the Terra spacecraft. The CERES sensors have higher spatial resolution than GERB, to which some of the variance in the comparisons can be attributed. Figure 2. Comparison of GERB and CERES FM2 ES8 LW (left) and SW (right) radiances. The colours correspond to scene type: ocean (blue); cloud (purple); bright vegetation (green); and bright desert (red). The agreement between the sensors in the LW is excellent, with a CERES/GERB mean ratio of 0.998+/0.007 at the 95% confidence limit. Compensating differences have been identified, however, with warmer scenes having ratios >1 and colder scenes having ratios <1. These differences are due to different LW limits applied in the data processing and this disparity will be resolved during reprocessing. For SW radiances, the agreement is scene-dependent. The best results are over deserts, where the ratio is 0.980+/-0.006. As the scene being viewed becomes bluer, the ratio reduces, down to 0.931+/-0.009 for ocean observations. A revised spectral response to be used in reprocessing is expected to improve these discrepancies. A small detectorspecific dependence has also been identified, which may be due to inter-detector response differences. As each detector observes a very small latitude range due to the scanning procedure, this could also be due to differences in the mean scene viewed by each detector. This issue is under investigation. CERES-GERB SW filtered radiance comparison 0.9 0.92 0.94 0.96 0.98 1 1.02 1.04 All Ocean Dark Veg Bright Veg Dark Desert Bright Desert Cloudy CE RE S/ G ER B ra di an ce ra tio Figure 3. Separation of CERES/GERB SW radiance ratio according to scene type, showing agreement decreasing with blueness of scene. Radiance to flux conversion is the biggest source of error for radiation budget data. Due to GERB’s fixed geometry, any viewing angle-dependent errors in the ADMs will result in systematic biases, so analysis of ADM performance and research into improvements is ongoing to minimise this. Theoretical ADMs based on SBDART calculations and scene identification from SEVIRI IR channels are used in processing of GERB LW fluxes. Comparisons with the CERES LW fluxes show a mean ratio of 0.987 ± 0.002, with an indication of limb-darkening at the edge of the disk for the GERB fluxes and scene-dependent differences Validation studies of the GERB clear sky ocean fluxes seem to indicate diurnally varying errors in the application of the ADMs which result in a spurious diurnal signal in the fluxes (~ ±20Wm). Whether this is due to the CERES ADMs themselves, or to the way in which they are applied to the GERB data is under investigation. Data Release and Other Issues Large and time varying errors noted initially in the geolocation were due to inaccurate pointing information from Meteosat-8. The geolocation accuracy has been greatly improved by additional data made available by EUMETSAT to correct this information. Smaller systematic offsets (~1 pixel) can be corrected by tuning the instrument in-flight optical model used in processing. Planned improvements will allow the 0.1 pixel geolocation accuracy specification to be met, however it is unlikely that this will be achieved for the edition 1 release. Periods around local midnight have been shown to be affected by stray solar illumination when the sun is close to the instrument FOV. Significant contamination of Earth radiances occurs for 6-8 weeks before and after equinoxes. A new gain calculation has been introduced to minimise time periods affected by using running averages. This also removes contamination on the occasions when the moon is present in the space views used for converting voltages to radiances. A study of the straylight problem will be carried out in the future, and data affected will be flagged for the first data released. Detector response has been very stable since launch, overall. Detector 192 has not performed to specification since launch and the response of detectors 229-238 has been degraded since February 2005, due to a mechanical fault. Data affected from these detectors will also be flagged. Cloud Radiative Forcing Standard radiation budget monthly mean data products average over all cloud systems and weather regimes. This limits their application in regional scale studies of specific cloud regimes and in validation of numerical models. In order to study the effects of individual cloud types separately, previous methods include using daily averages of cloud and radiation data or radiative transfer modelling. Both cloud type and cloud radiative forcing (CRF) can vary strongly through the day, however, which can lead to incorrect attribution using diurnal mean quantities (fig. 4). Data which can resolve both day to day and diurnal variations is therefore required. The ‘GERB-like’ data shown here was produced by applying a narrowband-broadband conversion to SEVIRI channels, but the results are similar when pre-release GERB data was analysed. The EUMETSAT CLA cloud analysis product was used to identify low, mid and high-level clouds in a 15 minute snapshot at 3 hour intervals. Figure 4. a) Occurrence of low, mid and high level clouds on 1 June 2004 from SEVIRI CLA product. b) Breakdown of cloud fraction, SW CRF and LW CRF separated into cloud type for that day, showing that the large SW CRF signal would be incorrectly attributed to the more prevalent high cloud if daily mean quantities were used. The problem being addressed is summarised in figure 4 (a) and (b). Over the African convective region on the day shown (01/06/2004), a typical diurnal variation in cloud type and fraction is observed in the CLA product (fig. 4 (a)). As high clouds dominate the cloud cover in terms of time, the SW CRF effect due to low clouds present on this day would be incorrectly attributed to high clouds using the method described by Webb et al. (2001). In fact, the high clouds have a significant LW CRF, as they reduce LW TOA emission, but a smaller SW CRF than low cloud (fig. 4 (b)). Instantaneous CRF are attributed to a cloud type based on the CLA product. These are then averaged to produce a monthly time-step mean CRF corresponding to each cloud type which c

A Science Operation System (SOS) aims at generating a detailed and consolidated science operation plan to routinely operate the payload on board scientific spacecraft.In the context of discovery and competitiveness, which are the keywords in Europe's policies and programmes for space, we believe that a permanent mechanism would be beneficial to efficiently and continuously improve SOS performance and productivity.It should monitor and steer the content of the procedures used to design and implement SOS.It should also be run by the science operation community.We therefore propose that the European Space Agency finances a study that will aim to define the requirements of a cost-effective mechanism, such as a Consultative Committee for Science Operation System (CCSOS), allowing for the coordination of the exploitation of current and future SOS experiences.Based on our practical experience of SOS, we provide, in this paper, the requirements of the study.We also discuss the expected key study outputs as well as an example of what could be the CCSOS architecture and outputs.Finally, we are convinced that many elements of this discussion should also be relevant for non-scientific missions, i.e. for missions involving any sort of routine payload operations.

This paper reports on a new satellite sensor, the Geostationary Earth Radiation Budget (GERB) experiment. GERB is designed to make the first measurements of the Earth's radiation budget from geostationary orbit. Measurements at high absolute accuracy of the reflected sunlight from the Earth, and the thermal radiation emitted by the Earth are made every 15 min, with a spatial resolution at the subsatellite point of 44.6 km (north-south) by 39.3 km (east-west). With knowledge of the incoming solar constant, this gives the primary forcing and response components of the top-of-atmosphere radiation. The first GERB instrument is an instrument of opportunity on Meteosat-8, a new spin-stabilized spacecraft platform also carrying the Spinning Enhanced Visible and Infrared (SEVIRI) sensor, which is currently positioned over the equator at 3.5 degrees W. This overview of the project includes a description of the instrument design and its preflight and in-flight calibration. An evaluation of the instrument performance after its first year in orbit, including comparisons with data from the Clouds and the Earth's Radiant Energy System (CERES) satellite sensors and with Output from numerical models, are also presented. After a brief summary of the data processing system and data products, some of the scientific studies that are being undertaken using these early data are described. This marks the beginning of a decade or more of observations from GERB, as subsequent models will fly on each of the four Meteosat Second Generation satellites.

It is the role of a Science Operation Centre (SOC) to provide the technical support and expertise necessary to assist a science community to plan and operate the payload on board a robotic scientific spacecraft in an effective and efficient manner. This paper discusses the origin of the set-up and running costs, inherent to SOC activities, and what needs to be done to improve SOCs productivity. Examples of what is being done, currently, to reduce the costs are also provided. We believe that the search for further cost reduction will greatly benefit from a centralised co-ordination. Ultimately, the need to improve SOC productivity will undoubtedly lead to a redefinition of the role of the SOCs. We therefore propose what could be the future role of the SOCs and a strategy to identify the most effective ways of making the SOC evolves towards more productivity.

The first Geostationary Earth Radiation Budget (GERB) experiment was launched on the Meteostat Second Generation (MSG-1) satellite in August 2002. GERB exists to make high accuracy measurements from geostationary orbit of the outgoing components of the Earth radiation budget at high temporal resolution. The GERB pixel size is approximately 44 km at the sub-satellite point, but in the GERB processing the position of each pixel must be located to an accuracy of about one tenth of this. This is because of the need in the level 2 processing to co-locate the GERB data with data from the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) instrument on MSG. MSG is a spin-stabilised satellite, and since the time constant of the GERB detectors is relatively long, of order 4 milliseconds, a de-spin mirror is used to obtain a constant scene over the detector integration time. As a consequence, issues of timing, pointing and alignment all have to be taken into account when geolocating the GERB data. This paper will explain the geolocation method devised to meet the required accuracy, the problems encountered in the initial data from GERB and the solutions being employed to overcome these problems.

Geostationary Earth radiation budget (GERB) is an Announcement of Opportunity Instrument for EUMETSAT's Meteosat Second Generation (MSG) satellite. GERB will make accurate measurements of the Earth Radiation Budget from geostationary orbit, provide an absolute reference calibration for LEO Earth radiation budget instruments and allow studies of the energetics of atmospheric processes. By operating from geostationary orbit, measurements may be made many times a day, thereby providing essentially perfect diurnal sampling of the radiation balance between reflected and emitted radiance for that area of the globe within the field of view. GERB will thus complement other instruments which operate in low orbit and give complete global coverage, but with poor and biased time resolution. GERB measures infrared radiation in two wavelength bands: 0.32–4.0 and 0.32–30μm, with a pixel element size of 44km at sub-satellite point. This paper gives an overview of the project and concentrates on the design and development of the instrument and ground testing and calibration, and lessons learnt from a short time scale low-budget project. The instrument was delivered for integration on the MSG platform in April 1999 ready for the proposed launch in October 2000, which has now been delayed probably to early 2002. The ground segment is being undertaken by RAL and RMIB and produces near real-time data for meteorological applications in conjunction with the main MSG imager—SEVERI. Climate research and other applications which are being developed under a EU Framework IV pilot project will be served by fully processed data. Because of the relevance of the observations to climate change, it is planned to maintain an operating instrument in orbit for at least 3.5 years. Two further GERB instruments are being built for subsequent launches of MSG.

The antigenic characteristics of 20 primary cerebral lymphomas have been defined by their reactivity with a panel of monoclonal antibodies recognizing differentiation antigens of lymphocytes and other cell types. In 7 out of 20 cases (35%), immunohistological results were diagnostically crucial and this approach appeared almost to double the detection rate of brain lymphomas over a 10-year period. All 20 tumours were confirmed as B-cell neoplasms by the use of a monoclonal antibody (B-1) specific for B-lymphocytes, rather than by the demonstration of immunoglobulin production. Further immunophenotyping with antibody FMC7 indicated that the neoplastic B-cells had been 'arrested' at a relatively mature stage of differentiation. The importance of monoclonal antibody markers in the accurate diagnosis and characterization of primary cerebral lymphomas has now been established.

A panel of monoclonal antibodies including antibodies against neuroectodermal antigens, (UJ13A, UJ127.11, UJ181.4), leukocytes (2D1), intermediate filament antigens cytokeratin (LE61), Vimentin, Desmin (Labsystems, Helsinki, Finland), myoglobin, and neurofilament (155) antigens were assessed for their use as an adjunct to light microscopy in pediatric pathology, with particular emphasis on the "small round cell" tumors. One hundred thirty-four tumors were studied using immunofluorescence and immunoperoxidase techniques. The differentiation of neuroblastoma from lymphoma proved to have a clear-cut immunologic profile, as did the rhabdomyosarcomas, which showed consistent positivity with neuroectodermal antibody UJ13A and in positive binding with antidesmin. Ewing's sarcoma did not give a clear immunohistologic pattern with these antibodies. This panel was shown to have been a valuable aid to diagnosis in 12% of cases studied. The future use of such a panel for routine diagnostic use is discussed, but it is emphasized that the binding pattern of these tumors is often heterogeneous, and examination in conjunction with conventional histology is essential if the correct conclusions are to be made.

A panel of seven monoclonal antibodies has been used to characterise 164 cerebral and spinal tumours. These reagents have enabled rapid and accurate diagnosis of tumours to be made, particularly in cases where standard techniques have proved equivocal. On the basis of characteristic antigenic profiles of tumours, it has been possible to distinguish between gliomas, meningiomas, schwannomas, medulloblastomas, neuroblastomas, choroid plexus tumours, various metastatic deposits, and primary brain lymphomas. The reagents used in the study comprise antibodies binding to (a) most neuroectodermally derived tissues and tumours (UJ13A), (b) fetal brain and tumours of neuroblastic origin (UJ181.4), (c) schwannomas, normal and neoplastic neurones (UJ127.11), (d) glial cells (FD19), (e) epithelial cells (LE61), and (f) leucocytes (2D1). Some reagents, such as antibody A2B5, were less effective as diagnostic markers than originally suggested by previously described specificity. This monoclonal antibody reacted with both neuroectodermal and epithelial derived tumours. The panel of monoclonal antibodies was most useful in the diagnosis of tumours composed of small round cells, particularly lymphoma and neuroblastoma, but the pattern of reactivities allowed most of the central nervous system tumours to be accurately classified. This approach was a valuable adjunct to conventional histological techniques in about 20% of the cases examined.

A panel of monoclonal antibodies was systematically applied to cerebrospinal fluid from 17 patients with suspected neoplastic meningitis and the results were compared with those obtained from routine cytological preparations. The antibody panel consisted of markers for neuroectodermal tissue ( UJ13A ), epithelial cytokeratin ( LE61 ), leucocytes ( 2D1 ), and neoplastic neuroblasts ( UJ181 .4). Additional antibodies were used to refine diagnosis when indicated. Cerebrospinal fluid samples from 12 patients with non-neoplastic conditions were used as controls. The use of monoclonal antibodies gave a positive diagnosis in 16/17 cases and the cells were accurately categorised as carcinoma (5/6 cases), neuroectodermal tumour (8/8 cases), and lymphoma (3/3 cases). In the 14 cases examined by routine cytology, malignant cells were reported in 10 cases and accurately categorised in only 3/14 cases. Immunocytological testing of cerebrospinal fluid with an antibody panel has greatly increased the accuracy with which malignant cells can be identified and categorised.

Methode immunohistologique appliquee a la biopsie tumorale et aux preparations cytologiques de LCR. Radioimmunolocalisation in vivo (scintigraphie par anticorps monoclonal marque)