A weather generator for current and future climate conditions
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1 Research Collection Doctoral Thesis A weather generator for current and future climate conditions Author(s): Keller, Denise E. Publication Date: 2015 Permanent Link: Rights / License: In Copyright - Non-Commercial Use Permitted This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use. ETH Library
2 DISS. ETH NO A WEATHER GENERATOR FOR CURRENT AND FUTURE CLIMATE CONDITIONS A thesis submitted to attain the degree of DOCTOR OF SCIENCES of ETH ZURICH (Dr. sc. ETH Zurich) presented by DENISE ESTHER KELLER MSc ETH in Atmospheric and Climate Science, ETH Zurich born on citizen of Kemmental (TG), Switzerland accepted on the recommendation of Prof. Dr. R. Knutti, examiner Prof. Dr. C. Appenzeller, co-examiner Prof. Dr. H. J. Fowler, co-examiner Dr. A. M. Fischer, co-examiner 2015
3 Abstract Given the expected changes in the climate system over the 21 st century, the need for reliable future projections is continuously growing. Today s regional climate models (RCMs) typically provide information about possible future climate change at a spatial resolution of kilometres. However, in light of climate adaptation planning, this resolution is often too coarse for direct use in climate impact models. Hence, further statistical downscaling of climate model data is necessary, in particular over complex topography, where unresolved local-scale dynamics and processes are of great importance. For many impact models it is crucial that the downscaled time-series are spatially consistent among different sites. In this sense, multi-site weather generators (WGs) are appealing downscaling tools. They allow the simulation of multiple realizations of possible future time-series consistent with the local weather characteristics and expected future changes thereof. For this purpose, a Wilks-type multi-site precipitation generator has been implemented. The precipitation generator was validated under current climate conditions over the catchment of the river Thur, a typical Alpine river catchment in the Swiss Alps. The precipitation generator does well in capturing mean characteristics of the local precipitation climates. In many regards, it brings substantial added value over single-site models. To simulate future daily weather time-series (precipitation, minimum and maximum temperature) for Switzerland, the multi-site precipitation model was extended to a multivariate WG and perturbed with change factors derived from RCM projections from the ENSEMBLES project. The WG was calibrated over a network of 26 measurement stations over the time-period and run under future climate conditions for the timeperiod assuming the A1B emission scenario. The downscaled time-series were compared to future time-series that were inferred with a delta-change approach. The analysis of different temperature-based climate indices revealed in the mean similar results for the WG and the delta-change approach. Major differences are found as expected, in terms of indices sensitive to changes in the temporal structure, such as mean dry and wet spell lengths or warm spells. Precipitation changes from the regional climate models were further analysed over Switzerland in terms of future changes in the seasonal wet day frequency and intensity, changes in the partitioning of convective and large-scale precipitation and in terms of i
4 changes in the spell lengths. The models project a summer drying all over Switzerland, which is mainly due to a decrease in the number of wet days. This decrease has also an influence on the temporal structure of dry and wet spell lengths. For the summer, the multi-model ensemble projects an increase in the multi-day dry spells at the expense of multi-day wet spells. Finally, in a preliminary study the potentials and limitations of applying synthetic weather data to impact models were assessed under current climate conditions. For this purpose the synthetic weather data are tested at the example of to two different hydrological models, simulating river runoff over the catchment of the Alpine river Thur. The knowledge gained from this work helps to improve our understanding of the applicability of synthetic weather data for impact models in general. ii
5 Zusammenfassung In Anbetracht der zu erwartenden Änderungen im Klimasystem bis zum Ende des 21. Jahrhunderts, nimmt der Bedarf an verlässlichen zukünftigen Klimaprojektionen stetig zu. Heutige regionale Klimamodelle liefern Informationen zum möglichen Klimawandel auf einer räumlichen Skala von Kilometern. Für die Planung von Anpassungsmassnahmen gegen den Klimawandel mit Hilfe von Klimawirkungsmodellen ist diese räumliche Auflösung jedoch meist zu grob. Aus diesem Grund werden Daten von Klimamodellen mit statistischen Methoden auf die gewünschte räumliche Skala herunterskaliert. Dies ist besonders relevant in Regionen mit komplexer Topographie, da dort lokale Prozesse eine wichtige Rolle spielen. Für viele Anwendungen von Klimawirkungsmodellen ist es zentral, dass die herunterskalierten Zeitreihen räumlich konsistent sind. In diesem Zusammenhang sind räumlich konsistente Wettergeneratoren attraktive stochastische Methoden für die Erzeugung von lokalen Zeitreihen. Sie ermöglichen die Simulation einer Vielzahl von Realisierungen möglicher künftiger Zeitreihen unter Berücksichtigung der lokalen Charakteristika des Klimas und deren künftigen Veränderungen. Zu diesem Zweck wurde ein räumlich konsistenter Niederschlagsgenerator nach Wilks implementiert. Dieser Generator wurde über dem hydrologischen Einzugsgebiet der Thur für das heutige Klima validiert. Das Modell erweist sich für die Simulation des lokalen mittleren Niederschlagsklimas als geeignet. In vielen Aspekten bringt es Mehrwert gegenüber einem Modell, welches die räumliche Korrelationsstruktur nicht explizit berücksichtigt. Das entwickelte Niederschlagsmodell wurde um ein Temperaturmodell erweitert, sodass auch Zeitreihen der Tagesminimumtemperatur und der Tagesmaximumtemperatur simuliert werden können. Um Sequenzen von zukünftigem täglichem Wetter über der Schweiz zu modellieren, wurden anschliessend die Modellparameter mit Änderungsfaktoren aus regionalen Klimamodellen aus dem ENSEMBLES Projekt gestört. Der Wettergenerator wurde an 26 Messstationen über dem Zeitraum kalibriert. Danach wurden die Änderungsfaktoren benutzt, um die zukünftigen Bedingungen für den Zeitraum unter Annahme des A1B-Emissionsszenarios zu simulieren. Die auf diese Weise herunterskalierten Zeitreihen wurden mit einem einfacheren Ansatz verglichen, bei welchem lediglich mittlere Änderungen auf die Beobachtungsdaten geschlagen werden. Die Analyse verschiedener temperaturbasierter Klimaindikatoren zeigte, dass beide Methoden für iii
6 Durchschnittswerte ähnliche Resultate liefern. Die bedeutendsten Unterschiede sind wie erwartet bei jenen Grössen zu finden, welche zeitliche Abhängigkeiten beinhalten, wie z.b. mittlere Dauer von Trocken-, Nass- oder auch Hitzeperioden. In einer zusätzlichen Studie wurden Änderungen im Niederschlag über der Schweiz in regionalen Klimamodellen detaillierter untersucht. Hierbei wurden die saisonalen Änderungssignale in Niederschlagshäufigkeit und -intensität aufgeteilt. Ebenso wurden konvektive und stratiforme Niederschläge getrennt betrachtet und die Dauer von Trocken- und Nassperioden untersucht. Die Modelle projizieren eine Austrocknung im Sommer über der gesamten Schweiz, welche hauptsächlich auf einen Rückgang in der Anzahl Nasstage zurückzuführen ist. Dieser Rückgang beeinträchtigt auch die zeitliche Abfolge und die Länge von Trocken- und Nassperioden. Für den Sommer zeigen die Modelle im Mittel eine Zunahme von persistenten Trockenphasen auf Kosten von längeren Nassperioden. In einer vorläufigen Studie wurden das Potential und die Limitierungen für den Einsatz von synthetischen Wetterdaten in Klimawirkungsmodellen untersucht. Dazu wurden die mit dem Wettergenerator erzeugten Zeitreihen in zwei hydrologischen Modellen über dem Einzugsgebiet der Thur verwendet, um deren Abfluss zu simulieren. Die daraus gewonnenen Erkenntnisse können dazu beitragen, die Anwendbarkeit solcher Daten in Klimawirkungsmodellen besser zu verstehen. iv
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