Laboratory for
Climatology and Remote Sensing

Abstract:

Konzentrierende Solarsysteme können einen sehr großen Teil der zukünftigen Strom- und Wärmeerzeugung leisten. Die Technik dieser Systeme steht kurz vor der Markteinführung, da die Stromgestehungskosten beinahe konkurrenzfähig geworden sind. Eine zentrale Größe ist dabei die Direkt-Normal-Strahlung, sozusagen der "Brennstoff" solcher Kraftwerke, die einen sehr hohen Einfluss auf deren Leistung und Stromerträge hat. Konzentrierende Solarkraftwerke sind eine Großinvestition, bei der schon in der Planungsphase eine Risiko- und Kostenreduktion angestrebt wird. Daher müssen heute Aussagen über die vorhandenen Strahlungsressourcen gemacht werden, um in Zukunft Solarenergie wirtschaftlich nutzen zu können. Die vorliegende Arbeit erarbeitet ein operationelles Verfahren, das mit Hilfe von sichtabaren und infraroten Daten des geostationären Satelliten Meteosat und Atmosphärendaten für Ozon, Wasserdampf und Aerosol mittels eines Parametrisierungsmodells die stündliche Direkt-Normal-Strahlung berechnet. Diese kann für große Regionen, Länder oder einzelne Standorte innerhalb des Sichtbereiches des Satelliten Meteosat in einer räumlichen Auflösung von bis zu 5km x 5km für Zeitreihen bis zu 20 Jahren bestimmt werden. Die so gewonnenen Informationen der verfügbaren Strahlungsressource sind ein wichtiger Bestandteil bei der Planung und Auslegung von konzentrierenden Solarkraftwerken und bei der Abschätzung des Strahlungspotenzials einer Region.

Abstract:

A new satellite-based technique for rainfall retrieval in high spatio-temporal resolution (3 km, 15 min) for Iran is presented. The algorithm is based on the infrared bands of the Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager (MSG SEVIRI). Random forest models using microwave-only rainfall information of the Integrated Multi-SatEllite Retrieval for the Global Precipitation Measurement (GPM) (IMERG) product as a reference were developed to (i) delineate the rainfall area and (ii) to assign the rainfall rate. The method was validated against independent microwave-only GPM IMERG rainfall data not used for model training. Additionally, the new technique was validated against completely independent gauge station data. The validation results show a promising performance of the new rainfall retrieval technique, especially when compared to the GPM IMERG IR-only rainfall product. The standard verification scored an average Heidke Skill Score of 0.4 for rain area delineation and an average R between 0.1 and 0.7 for rainfall rate assignment, indicating uncertainties for the Lut Desert area and regions with high altitude gradients.

Abstract:

[1] Previous studies of clouds over the Tibetan Plateau (TiP) were subject to limitations. Surface observations are scarce, and satellite retrievals are not well adapted to the peculiar conditions of the TiP. For the most comprehensive existing cloud data set, provided by the International Satellite Cloud Climatology Project (ISCCP), issues were reported for the TiP. It also lacks sufficient spatiotemporal resolution for this topographically complex region. With the Indian Ocean Data Coverage service, European Organisation for the Exploitation of Meteorological Satellites provides a Meteosat data set between 1998 and 2008. The resolution of around 6?km at the study area is sufficient even for complex terrain. Based on this data set and on products of the active sensor onboard CloudSat, we develop a novel gross-cloud retrieval for the TiP using logistic regression models. The approach maintains the original Meteosat resolution. Validation against independent CloudSat data reveals good performance. The approach also outperforms the ISCCP pixel level (DX) data set. The resulting data set is the first for the TiP that provides cloud information with sufficient resolution for both day and night. Patterns of cloud frequencies during winter, premonsoon, and monsoon seasons are analyzed. Strong diurnal forcing is found for the plateau. Peaks of cloud frequencies above the slopes occur during afternoon, while they are delayed in the valleys, where high cloud frequencies persist throughout the nights. Above the lower parts of the southern foothills of the Himalayas cloud frequencies were for the first time found to increase until the early morning. Katabatic flows are suspected to be responsible for this pattern by initiating the formation of mesoscale convective systems.