Indiana University-Purdue University Indianapolis (IUPUI) / The Indian summer monsoon (ISM) is the dominant hydrometeorological phenomenon that provides the majority of precipitation to southern Asia and southeastern Tibet specifically. Reliable projections of ISM rainfall are critical for water management and hinge on our understanding of the drivers of the monsoon system and how these drivers will be impacted by climate change. Because instrumental climate records are limited in space and time, natural climate archives are required to understand how the ISM varied in the past in response to changes in climatic boundary climate conditions. Lake sediments are high-resolution natural paleoclimate archive that are widely distributed across the Tibetan Plateau, making them useful for investigating long-term precipitation trends and their response to climatic boundary conditions. To investigate changes in monsoon intensity during the Holocene, three lakes were sampled along an east-west transect in southeastern Tibet: Galang Co, Nir’Pa Co, and Cuobu. Paleoclimate records from each lake were developed using isotopic (leaf wax hydrogen isotopes; δ2H), sedimentological, and geochemical proxies of precipitation and lake levels. Sediments were sampled at high temporal frequencies, with most proxies resolved at decadal scales, to capture multi-decadal to millennial-scale variability in monsoon intensity and local hydroclimate conditions. The ISM was strongest in the early Holocene as evidenced by leaf-wax n-alkane δ2H at both Cuobu and Galang Co corresponding with Cuobu’s higher lake levels and effective moisture. Monsoon intensity declined at Cuobu and Galang Co around 6 ka which corresponds to reduced riverine sediment influxes at Cuobu and deeper lake levels at Galang Co. The antiphase relationship between lake levels and monsoon intensity at Galang Co is attributed to air temperatures and effective moisture, with a warmer and drier local hydroclimate driving early Holocene low lake levels. The late Holocene ISM was more variable with wet and dry periods, as seen in the Nir’Pa Co lake level and leaf wax n-alkane δ2H record. These records demonstrate coherent drivers of synoptic and local hydroclimate that account for Holocene ISM expression across the southeastern Tibetan Plateau, indicating possible drivers of future monsoon expression under climate change.

The Indian summer monsoon (ISM) is one of the largest climate systems on earth and impacts the livelihood of nearly 40% of the world’s population. Despite dedicated efforts, a comprehensive picture of monsoon variability has proved elusive largely due to the absence of long term high resolution records, spatial inhomogeneity of the monsoon precipitation, and the complex forcing mechanisms (solar insolation, internal teleconnections for e.g., El Niño-Southern Oscillation, tropical-midlatitude interactions). My work aims to improve the understanding of monsoon variability through generation of long term high resolution palaeoclimate data from climatically sensitive regions in the ISM and westerlies domain. To achieve this aim I have (i) identified proxies (sedimentological, geochemical, isotopic, and mineralogical) that are sensitive to environmental changes; (ii) used the identified proxies to generate long term palaeoclimate data from two climatically sensitive regions, one in NW Himalayas (transitional westerlies and ISM domain in the Spiti valley and one in the core monsoon zone (Lonar lake) in central India); (iii) undertaken a regional overview to generate “snapshots” of selected time slices; and (iv) interpreted the spatial precipitation anomalies in terms of those caused by modern teleconnections. This approach must be considered only as the first step towards identifying the past teleconnections as the boundary conditions in the past were significantly different from today and would have impacted the precipitation anomalies. As the Spiti valley is located in the in the active tectonic orogen of Himalayas, it was essential to understand the role of regional tectonics to make valid interpretations of catchment erosion and detrital influx into the lake. My approach of using integrated structural/morphometric and geomorphic signatures provided clear evidence for active tectonics in this area and demonstrated the suitability of these lacustrine sediments as palaleoseismic archives. The investigations on the lacustrine outcrops in Spiti valley also provided information on changes in seasonality of precipitation and occurrence of frequent and intense periods (ca. 6.8-6.1 cal ka BP) of detrital influx indicating extreme hydrological events in the past. Regional comparison for this time slice indicates a possible extended “break-monsoon like” mode for the monsoon that favors enhanced precipitation over the Tibetan plateau, Himalayas and their foothills. My studies on surface sediments from Lonar lake helped to identify environmentally sensitive proxies which could also be used to interpret palaeodata obtained from a ca. 10m long core raised from the lake in 2008. The core encompasses the entire Holocene and is the first well dated (by 14C) archive from the core monsoon zone of central India. My identification of authigenic evaporite gaylussite crystals within the core sediments provided evidence of exceptionally drier conditions during 4.7-3.9 and 2.0-0.5 cal ka BP. Additionally, isotopic investigations on these crystals provided information on eutrophication, stratification, and carbon cycling processes in the lake. / Der Indische Sommer Monsun (ISM) ist eines der bedeutendsten Klimaphänomene auf der Erde und hat großen Einfluss auf die Lebensbedingungen und -grundlagen von nahezu 40% der Weltbevölkerung. Trotz großer Bemühungen ist es bisher nicht gelungen ein genaues und umfassendes Verständnis der Monsun-Variabilität zu gewinnen. Hauptgründe dafür sind das Fehlen von langjährigen und hochaufgelösten Klimazeitreihen, räumlichen Inhomogenitäten in den Niederschlagsverteilungen und die Komplexität der treibenden klimatischen Mechanismen (Sonneneinstrahlung, interne Wechselwirkungen des Klimasystems, wie z.B. zwischen Tropen und mittleren Breiten oder die Auswirkungen der El Niño Oszillation). Die Zielsetzung der hier vorgestellten Arbeit ist ein verbessertes Verständnis der Monsun-Variabilität zu entwickeln, auf Basis von hochaufgelösten und weit reichenden Paläoklimazeitreihen aus klimasensitiven Regionen des ISM und der Westwindzone. Um die Zielsetzung umzusetzen habe ich: (i) Proxys identifiziert (sedimentologische, geochemische, isotopische, und mineralogische), die empfindlich auf Umweltveränderungen reagieren; (ii) die identifizierten Proxys zur Erzeugung von langjährigen Paläoklima-Daten für zwei klimasensible Regionen verwendet, eine im NW des Himalaja (Übergangs-Westwindzone und ISM Gebiet von Spity Valley) und eine in der Kernzone des Monsun (Lonar-See) in Zentralindien; (iii) Übersichts-"Momentaufnahmen" der regionalen klimatischen Bedingungen für ausgewählte Zeitpunkte der Vergangenheit erzeugt; und (iv) räumliche Niederschlagsanomalien in Hinblick auf heutige Wechselbeziehungen im Klimasystem interpretiert. Dieser Ansatz stellt allerdings nur einen ersten Schritt zur Identifizierung von paläoklimatischen Wechselbeziehungen im Monsunsystem dar, da sich die Randbedingungen in der Vergangenheit deutlich von den heutigen unterscheiden und diese einen signifikanten Einfluss auf die Niederschlagsanomalien haben. Da das Spity Valley im tektonisch aktiven Himalaja-Orogen lokalisiert ist, ist es von entscheidender Bedeutung die regionalen tektonischen Prozesse zu verstehen, um Erosionsvorgänge des Einzugsgebiets und die Einfuhr von Detritus in den See korrekt interpretieren zu können. Mein Ansatz der Nutzung kombinierter strukturell/morphometrischer und geomorphologischer Charakteristiken lieferte klare Beweise für aktive Tektonik im untersuchten Gebiet und demonstrierte damit die Eignung dieser lakustrinen Sedimente als paläoseismisches Archiv. Die Untersuchung lakustriner Aufschlüsse in Spity Valley lieferte auch Informationen saisonale Änderung der Niederschlagsverteilung sowie das Auftreten von häufigen und intensiven Perioden (ca. 6,8-6,1 cal ka BP) detritischer Einfuhr, welche auf extreme hydrologische Ereignisse in der Vergangenheit schließen lässt. Ein regionaler Vergleich dieser Periode deutet auf einen möglicherweise erweiterten „break-monsoon-like“ Modus für den Monsun hin, welcher hohe Niederschläge über dem Tibetischen Plateau, dem Himalaja und seinen Gebirgsausläufern begünstigt. Meine Studien an den Oberflächensedimenten des Lonar-Sees haben dazu beigetragen umweltsensitive Proxys zu identifizieren, die auch zur Interpretation von Paläodaten von einem ca. 10 m langen Sedimentkern genutzt wurden, der 2008 erbohrt wurde. Der Kern umfasst das gesamte Holozän und stellt das erste gut 14C-datierte Archiv aus der Kernmonsunzone Zentralindiens dar. Die Identifizierung von authigenen Evaporit-Kristallen (Gaylussite) innerhalb der Sedimente liefert einen Beweis für ungewöhnlich trockene Bedingungen in den Perioden zwischen 4,7-3,9 und 2,0-0,5 cal ka BP. Darüber hinaus lieferten Isotopen-Untersuchungen dieser Kristalle Informationen zur Eutrophierung, Stratifikation und zum Kohlenstoff-Kreislauf des Sees.

abstract: The Dhofar Cloud Forest is one of the most diverse ecosystems on the Arabian Peninsula. As part of the South Arabian Cloud Forest that extends from southern Oman to Yemen, the cloud forest is an important center of endemism and provides valuable ecosystem services to those living in the region. There have been various claims made about the health of the cloud forest and its surrounding region, the most prominent of which are: 1) variability of the Indian Summer Monsoon threatens long-term vegetation health, and 2) human encroachment is causing deforestation and land degradation. This dissertation uses three independent studies to test these claims and bring new insight about the biodiversity of the cloud forest. Evidence is presented that shows that the vegetation dynamics of the cloud forest are resilient to most of the variability in the monsoon. Much of the biodiversity in the cloud forest is dominated by a few species with high abundance and a moderate number of species at low abundance. The characteristic tree species include Anogeissus dhofarica and Commiphora spp. These species tend to dominate the forested regions of the study area. Grasslands are dominated by species associated with overgrazing (Calotropis procera and Solanum incanum). Analysis from a land cover study conducted between 1988 and 2013 shows that deforestation has occurred to approximately 8% of the study area and decreased vegetation fractions are found throughout the region. Areas around the city of Salalah, located close to the cloud forest, show widespread degradation in the 21st century based on an NDVI time series analysis. It is concluded that humans are the primary driver of environmental change. Much of this change is tied to national policies and development priorities implemented after the Dhofar War in the 1970’s. / Dissertation/Thesis / Doctoral Dissertation Geography 2015

To identify extreme changes in the dynamics of the Indian Summer Monsoon (ISM) in the past, I propose a new approach based on the quantification of fluctuations of a nonlinear similarity measure, to identify regimes of distinct dynamical complexity in short time series. I provide an analytical derivation for the relationship of the new measure with the dynamical invariants such as dimension and Lyapunov exponents of the underlying system. A statistical test is also developed to estimate the significance of the identified transitions. Our method is justified by uncovering bifurcation structures in several paradigmatic models, providing more complex transitions compared with traditional Lyapunov exponents. In a real world situation, we apply the method to identify millennial-scale dynamical transitions in Pleistocene proxy records of the south Asian summer monsoon system. We infer that many of these transitions are induced by the external forcing of solar insolation and are also affected by internal forcing on Monsoonal dynamics, i.e., the glaciation cycles of the Northern Hemisphere and the onset of the tropical Walker circulation. Although this new method has general applicability, it is particularly useful in analysing short palaeo-climate records. Rainfall during the ISM over the Indian subcontinent occurs in form of enormously complex spatiotemporal patterns due to the underlying dynamics of atmospheric circulation and varying topography. I present a detailed analysis of summer monsoon rainfall over the Indian peninsular using Event Synchronization (ES), a measure of nonlinear correlation for point processes such as rainfall. First, using hierarchical clustering I identify principle regions where the dynamics of monsoonal rainfall is more coherent or homogenous. I also provide a method to reconstruct the time delay patterns of rain events. Moreover, further analysis is carried out employing the tools of complex network theory. This study provides valuable insights into the spatial organization, scales, and structure of the 90th and 94th percentile rainfall events during the ISM (June to September). I furthermore analyse the influence of different critical synoptic atmospheric systems and the impact of the steep Himalayan topography on rainfall patterns. The presented method not only helps in visualising the structure of the extremeevent rainfall fields, but also identifies the water vapor pathways and decadal-scale moisture sinks over the region. Furthermore a simple scheme based on complex networks is presented to decipher the spatial intricacies and temporal evolution of monsoonal rainfall patterns over the last six decades. Some supplementary results on the evolution of monsoonal rainfall extremes over the last sixty years are also presented. / Um Extremereignisse in der Dynamik des indischen Sommermonsuns (ISM) in der geologischen Vergangenheit zu identifizieren, schlage ich einen neuartigen Ansatz basierend auf der Quantifikation von Fluktuationen in einem nichtlinearen Ähnlichkeitsmaß vor. Dieser reagiert empfindlich auf Zeitabschnitte mit deutlichen Veränderungen in der dynamischen Komplexität kurzer Zeitreihen. Ein mathematischer Zusammenhang zwischen dem neuen Maß und dynamischen Invarianten des zugrundeliegenden Systems wie fraktalen Dimensionen und Lyapunovexponenten wird analytisch hergeleitet. Weiterhin entwickle ich einen statistischen Test zur Schätzung der Signifikanz der so identifizierten dynamischen Übergänge. Die Stärken der Methode werden durch die Aufdeckung von Bifurkationsstrukturen in paradigmatischen Modellsystemen nachgewiesen, wobei im Vergleich zu den traditionellen Lyapunovexponenten eine Identifikation komplexerer dynamischer Übergänge möglich ist. Wir wenden die neu entwickelte Methode zur Analyse realer Messdaten an, um ausgeprägte dynamische Veränderungen auf Zeitskalen von Jahrtausenden in Klimaproxydaten des südasiatischen Sommermonsunsystems während des Pleistozäns aufzuspüren. Dabei zeigt sich, dass viele dieser Übergänge durch den externen Einfluss der veränderlichen Sonneneinstrahlung, sowie durch dem Klimasystem interne Einflussfaktoren auf das Monsunsystem (Eiszeitzyklen der nördlichen Hemisphäre und Einsatz der tropischenWalkerzirkulation) induziert werden. Trotz seiner Anwendbarkeit auf allgemeine Zeitreihen ist der diskutierte Ansatz besonders zur Untersuchung von kurzen Paläoklimazeitreihen geeignet. Die während des ISM über dem indischen Subkontinent fallenden Niederschläge treten, bedingt durch die zugrundeliegende Dynamik der atmosphärischen Zirkulation und topographische Einflüsse, in äußerst komplexen, raumzeitlichen Mustern auf. Ich stelle eine detaillierte Analyse der Sommermonsunniederschläge über der indischen Halbinsel vor, die auf Ereignissynchronisation (ES) beruht, einem Maß für die nichtlineare Korrelation von Punktprozessen wie Niederschlagsereignissen. Mit hierarchischen Clusteringalgorithmen identifiziere ich zunächst Regionen mit besonders kohärenten oder homogenen Monsunniederschlägen. Dabei können auch die Zeitverzögerungsmuster von Regenereignissen rekonstruiert werden. Darüber hinaus führe ich weitere Analysen auf Basis der Theorie komplexer Netzwerke durch. Diese Studien ermöglichen wertvolle Einsichten in räumliche Organisation, Skalen und Strukturen von starken Niederschlagsereignissen oberhalb der 90% und 94% Perzentilen während des ISM (Juni bis September). Weiterhin untersuche ich den Einfluss von verschiedenen, kritischen synoptischen Systemen der Atmosphäre sowie der steilen Topographie des Himalayas auf diese Niederschlagsmuster. Die vorgestellte Methode ist nicht nur geeignet, die Struktur extremer Niederschlagsereignisse zu visualisieren, sondern kann darüber hinaus über der Region atmosphärische Transportwege von Wasserdampf und Feuchtigkeitssenken auf dekadischen Skalen identifizieren.Weiterhin wird ein einfaches, auf komplexen Netzwerken basierendes Verfahren zur Entschlüsselung der räumlichen Feinstruktur und Zeitentwicklung von Monsunniederschlagsextremen während der vergangenen 60 Jahre vorgestellt.

Recent years witnessed a vast advent of stalagmites as palaeoclimate archives. The multitude of geochemical and physical proxies and a promise of a precise and accurate age model greatly appeal to palaeoclimatologists. Although substantial progress was made in speleothem-based palaeoclimate research and despite high-resolution records from low-latitudinal regions, proving that palaeo-environmental changes can be archived on sub-annual to millennial time scales our comprehension of climate dynamics is still fragmentary. This is in particular true for the summer monsoon system on the Indian subcontinent. The Indian summer monsoon (ISM) is an integral part of the intertropical convergence zone (ITCZ). As this rainfall belt migrates northward during boreal summer, it brings monsoonal rainfall. ISM strength depends however on a variety of factors, including snow cover in Central Asia and oceanic conditions in the Indic and Pacific. Presently, many of the factors influencing the ISM are known, though their exact forcing mechanism and mutual relations remain ambiguous. Attempts to make an accurate prediction of rainfall intensity and frequency and drought recurrence, which is extremely important for South Asian countries, resemble a puzzle game; all interaction need to fall into the right place to obtain a complete picture. My thesis aims to create a faithful picture of climate change in India, covering the last 11,000 ka. NE India represents a key region for the Bay of Bengal (BoB) branch of the ISM, as it is here where the monsoon splits into a northwestward and a northeastward directed arm. The Meghalaya Plateau is the first barrier for northward moving air masses and receives excessive summer rainfall, while the winter season is very dry. The proximity of Meghalaya to the Tibetan Plateau on the one hand and the BoB on the other hand make the study area a key location for investigating the interaction between different forcings that governs the ISM. A basis for the interpretation of palaeoclimate records, and a first important outcome of my thesis is a conceptual model which explains the observed pattern of seasonal changes in stable isotopes (d18O and d2H) in rainfall. I show that although in tropical and subtropical regions the amount effect is commonly called to explain strongly depleted isotope values during enhanced rainfall, alone it cannot account for observed rainwater isotope variability in Meghalaya. Monitoring of rainwater isotopes shows no expected negative correlation between precipitation amount and d18O of rainfall. In turn I find evidence that the runoff from high elevations carries an inherited isotopic signature into the BoB, where during the ISM season the freshwater builds a strongly depleted plume on top of the marine water. The vapor originating from this plume is likely to memorize' and transmit further very negative d18O values. The lack of data does not allow for quantication of this plume effect' on isotopes in rainfall over Meghalaya but I suggest that it varies on seasonal to millennial timescales, depending on the runoff amount and source characteristics. The focal point of my thesis is the extraction of climatic signals archived in stalagmites from NE India. High uranium concentration in the stalagmites ensured excellent age control required for successful high-resolution climate reconstructions. Stable isotope (d18O and d13C) and grey-scale data allow unprecedented insights into millennial to seasonal dynamics of the summer and winter monsoon in NE India. ISM strength (i. e. rainfall amount) is recorded in changes in d18Ostalagmites. The d13C signal, reflecting drip rate changes, renders a powerful proxy for dry season conditions, and shows similarities to temperature-related changes on the Tibetan Plateau. A sub-annual grey-scale profile supports a concept of lower drip rate and slower stalagmite growth during dry conditions. During the Holocene, ISM followed a millennial-scale decrease of insolation, with decadal to centennial failures resulting from atmospheric changes. The period of maximum rainfall and enhanced seasonality corresponds to the Holocene Thermal Optimum observed in Europe. After a phase of rather stable conditions, 4.5 kyr ago, the strengthening ENSO system dominated the ISM. Strong El Nino events weakened the ISM, especially when in concert with positive Indian Ocean dipole events. The strongest droughts of the last 11 kyr are recorded during the past 2 kyr. Using the advantage of a well-dated stalagmite record at hand I tested the application of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to detect sub-annual to sub-decadal changes in element concentrations in stalagmites. The development of a large ablation cell allows for ablating sample slabs of up to 22 cm total length. Each analyzed element is a potential proxy for different climatic parameters. Combining my previous results with the LAICP- MS-generated data shows that element concentration depends not only on rainfall amount and associated leaching from the soil. Additional factors, like biological activity and hydrogeochemical conditions in the soil and vadose zone can eventually affect the element content in drip water and in stalagmites. I present a theoretical conceptual model for my study site to explain how climatic signals can be transmitted and archived in stalagmite carbonate. Further, I establish a first 1500 year long element record, reconstructing rainfall variability. Additionally, I hypothesize that volcanic eruptions, producing large amounts of sulfuric acid, can influence soil acidity and hence element mobilization. / Stalagmiten erfuhren in den letzten Jahren vermehrt Aufmerksamkeit als bedeutende Paläoklima- Archive. Paläoklimatologen sind beeindruckt von der grossen Zahl geochemischer und physikalischer Indikatoren (Proxies) und der Möglichkeit, präzise absolute Altersmodelle zu erstellen. Doch obwohl substantielle Fortschritte in der speleothem-basierten Klimaforschung gemacht wurden, und trotz hochaufgelöster Archive aus niederen Breiten, welche zeigen, das Umweltveränderungen auf Zeitskalen von Jahren bis Jahrtausenden archiviert und rekonstruiert werden können, bleibt unser Verständnis der Klimadynamik fragmentarisch. Ganz besonders gilt dies für den Indischen Sommermonsun (ISM) auf dem Indischen Subkontinent. Der ISM ist heute als ein integraler Bestandteil der intertropischen Konvergenzzone verstanden. Sobald dieser Regengürtel während des borealen Sommer nordwärts migriert kann der ISM seine feuchten Luftmassen auf dem Asiatischen Festland entladen. Dabei hängt die Stärke des ISM von einer Vielzahl von Faktoren ab. Zu diesen gehören die Schneedicke in Zentralasien im vorhergehenden Winter und ozeanische Bedingungen im Indischen und Pazifschen Ozean. Heute sind viele dieser Faktoren bekannt. Trotzdem bleiben deren Mechanismen und internen Verbindungen weiterhin mysteriös. Versuche, korrekte Vorhersagen zu Niederschlagsintensität und Häufigkeit oder zu Dürreereignissen zu erstellen ähneln einem Puzzle. All die verschiedenen Interaktionen müssen an die richtige Stelle gelegt werden, um ein sinnvolles Bild entstehen zu lassen. Meine Dissertation versucht, ein vertrauenswürdiges Bild des sich wandelnden Holozänen Klimas in Indien zu erstellen. NE Indien ist eine Schlüsselregion für den östlichen Arm des ISM, da sich hier der ISM in zwei Arme aufteilt, einen nordwestwärts und einen nordostwärts gerichteten. Das Meghalaya Plateau ist das erste Hindernis für die sich nordwärts bewegenden Luftmassen und erhält entsprechend exzessive Niederschläge während des Sommers. Die winterliche Jahreszeit dagegen ist sehr trocken. Die Nähe zum Tibetplateau einerseits und der Bucht von Bengalen andererseits determinieren die Schlüsselposition dieser Region für das Studium der Interaktionen der den ISM beeinflussenden Kräfte. Ein Fundament für die Interpretation der Paläoklimarecords und ein erstes wichtiges Ergebnis meiner Arbeit ist ein konzeptuelles Modell, welches die beobachteten saisonalen Veränderungen stabiler Isotope (d18O und d2H) im Niederschlag erklärt. Ich zeige, das obwohl in tropischen und subtropischen Regionen meist der amount effect zur Erklärung stark negativer Isotopenwerte während starker Niederschläge herangezogen wird, dieser allein nicht ausreicht, um die Isotopenvariabilität im Niederschlag Meghalaya's zu erklären. Die Langzeitbeobachtung der Regenwasserisotopie zeigt keine negative Korrelation zwischen Niederschlagsmenge und d18O. Es finden sich Hinweise, das der Abfluss aus den Hochgebirgsregionen Tibets und des Himalaya eine Isotopensignatur an das Oberflächenwasser der Bucht von Bengalen vererbt. Dort bildet sich aus isotopisch stark abgereicherten Wässern während des ISM eine Süsswasserlinse aus. Es ist wahrscheinlich, das Wasserdampf, der aus dieser Linse stammt, ein Isotopensignal aufgeprägt bekommt, welches abgereichertes d18O weitertransportiert. Der Mangel an Daten lässt es bisher leider nicht zu, quantitative Aussagen über den Einfluss dieses plume effect' auf Niederschläge in Meghalaya zu treffen. Es lässt sich allerdings vermuten, das dieser Einfluss auf saisonalen wie auch auf langen Zeitskalen variabel ist, abhängig vom Abfluss und der Quellencharacteristik. Der Fokus meiner Arbeit liegt in der Herauslösung klimatischer Signale aus nordostindischen Stalagmiten. Hohe Urankonzentrationen in diesen Stalagmiten erlaubt eine exzellente Alterskontrolle, die für hochauflösende Klimarekonstruktionen unerlässlich ist. Die stabilen Isotope (d18O und d13C), sowie Grauwertdaten, erlauben einmalige Einblicke in die Dynamik des Sommer und auch des Wintermonsun in NE Indien. Die ISM Stärke (d. h. Niederschlagsmenge) wird in Veränderungen in den d18Ostalagmites reflektiert. Das d13C Signal, welches Tropfratenänderungen speichert, dient als potenter Indikator für winterliche Trockenheitsbedingungen. Es zeigt Ähnlichkeit zu temperaturabhängigen Veränderungen auf dem Tibetplateau. Das sub-annuell aufgelöste Grauwertprofil stärkt das Konzept, das verminderte Tropfraten und langsameres Stalagmitenwachstum eine Folge von Trockenheit sind. Während des Holozäns folgte der ISM der jahrtausendelangen Verringerung der Insolation. Es finden sich aber ebenso rapide Anomalien, die aus atmosphärischen Veränderungen resultieren. Die Phase des höchsten Niederschlages und erhöhter Saisonalität korrespondiert mit dem Holozänen Thermalen Maximum. Nach einer Phase einigermassen stabilen Bedingungen begann vor ca. 4500 Jahren ENSO einen zunehmenden Einfluss auf den ISM auszuüben. Starke El Nino Ereignisse schwächen den ISM, besonders wenn diese zeitgleich mit positiven Indian Ocean Dipole Ereignissen auftreten. Die stärksten Dürren des gesamten Holozäns traten in den letzten 2000 Jahren auf. Um zusätzliche Informationen aus den hervorragenden Proben zu gewinnen nutzte ich die Vorteile der laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Diese erlaubt die Detektion sub-annueller bis sub-dekadischer Elementkonzentrationsveränderungen in Stalagmiten. Mittels einer neu entwickelten Ablationszelle konnten Proben von maximal 22 cm Länge untersucht werden. Jedes analysierte Element ist ein potentieller Träger einer Klimainformation. Die Kombination der früheren Ergebnisse mit denen der LA-IPC-MS zeigt, das die Elementkonzentrationen nicht nur von Niederschlagsveränderungen und assoziiertem Auswaschen aus dem Boden abhängen. Zusätzlich können auch die biologische Aktivität und hydrogeochemische Bedingungen in der vadosen Zone Einfluss auf die Elementzusammensetzung im Tropfwasser und in den Stalagmiten haben. Darum entwickelte ich ein theoretisches Modell für meinen Standort, um zu klären, wie Klimasignale von der Atmosphäre in die Höhle transportiert werden können. Ein anschliessend rekonstruierter 1500 Jahre langer Proxyrecord zeigt Niederschlagsvariabilität an. Zudem besteht die Möglichkeit, das Vulkaneruptionen, welche grosse Mengen an Schwefelsäure produzieren, eine Bodenversauerung verursachen und damit die Elementmobilisierung verstärken können.

This thesis investigates the relationship between climate, agriculture and social change in South Asia’s Bronze Age urban Indus Civilisation. Specifically, my research tests the hypothesis that an abrupt weakening of the Indian Summer Monsoon ca 2100 cal BC led to increasing crop water stress, and hence potentially contributed to the Civilisation’s decline by reducing food supply. This hypothesis is frequently invoked in discussions of the Civilisation’s end, yet until now, has not been empirically tested. Using material excavated from several Indus settlements, this study uses a novel combination of isotopic techniques to directly test the connection between climate change and agricultural stress. These techniques are first, oxygen isotope analysis of faunal bones and teeth; and second, stable carbon isotope analysis of crop remains. The oxygen analyses provide detailed records of monsoon intensity at a local, human scale, while the carbon analyses provide an empirical test of whether crop water stress increased. Applied in parallel across a diverse suite of Indus sites, these techniques together provide an archaeologically and ecologically-nuanced analysis of climatic impacts. The archaeological analyses are supported by a methodological study, which investigates how water status relates to the stable carbon isotope signature in barley (Hordeum vulgare) and the Indian jujube (Ziziphus mauritiana) along a climatic transect in north-western India today. Overall, the isotopic results suggest that at the sites sampled here, climate change probably had minimal impacts on crop water availability. This does not necessarily mean that climate change had no impacts on agriculture across the greater Indus sphere, and indeed there are hints that there may have been climatic stress in more vulnerable settings. However, at the sites studied here, any hydrological consequences of climate change—including the 4.2 ka event—appear to have had neither a lasting nor a pervasive impact on the adequacy of crop water supply. This is an important finding, and necessitates a clear refinement of how we think about climatic sensitivity, climatic vulnerability, and climatic impacts across—and indeed beyond—the greater Indus.

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The land–atmosphere interactions and the coupling between climate and land surface hydrological processes are gaining interest in the recent past. The increased knowledge in hydro climatology and the global hydrological cycle, with terrestrial and atmospheric feedbacks, led to the utilization of the climate variables and atmospheric tele-connections in modeling the hydrological processes like rainfall and runoff. Numerous statistical and dynamical models employing different combinations of predictor variables and mathematical equations have been developed on this aspect. The relevance of predictor variables is usually measured through the observed linear correlation between the predictor and the predictand. However, many predictor climatic variables are found to have been switching the relationships over time, which demands a replacement of these variables. The unsatisfactory performance of both the statistical and dynamical models demands a more authentic method for assessing the dependency between the climatic variables and hydrologic processes by taking into account the nonlinear causal relationships and the instability due to these nonlinear interactions. The most obvious cause for limited predictability in even a perfect model with high resolution observations is the nonlinearity of the hydrological systems [Bloschl and Zehe, 2005]. This is mainly due to the chaotic nature of the weather and its sensitiveness to initial conditions [Lorenz, 1963], which restricts the predictability of day-to-day weather to only a few days or weeks. The present thesis deals with developing association rules to extract the causal relationships between the climatic variables and rainfall and to unearth the frequent predictor patterns that precede the extreme episodes of rainfall using a time series data mining algorithm. The inherent nonlinearity and uncertainty due to the chaotic nature of hydrologic processes (rainfall and runoff) is modeled through a nonlinear prediction method. Methodologies are developed to increase the predictability and reduce the predictive uncertainty of chaotic hydrologic series. A data mining algorithm making use of the concepts of minimal occurrences with constraints and time lags is used to discover association rules between extreme rainfall events and climatic indices. The algorithm considers only the extreme events as the target episodes (consequents) by separating these from the normal episodes, which are quite frequent and finds the time-lagged relationships with the climatic indices, which are treated as the antecedents. Association rules are generated for all the five homogenous regions of India (as defined by Indian Institute of Tropical Meteorology) and also for All India by making use of the data from 1960-1982. The analysis of the rules shows that strong relationships exist between the extreme rainfall events and the climatic indices chosen, i.e., Darwin Sea Level Pressure (DSLP), North Atlantic Oscillation (NAO), Nino 3.4 and Sea Surface Temperature (SST) values. Validation of the rules using data for the period 1983-2005, clearly shows that most of the rules are repeating and for some rules, even if they are not exactly the same, the combinations of the indices mentioned in these rules are the same during validation period with slight variations in the representative classes taken by the indices. The significance of treating rainfall as a chaotic system instead of a stochastic system for a better understanding of the underlying dynamics has been taken up by various studies recently. However, an important limitation of all these approaches is the dependence on a single method for identifying the chaotic nature and the parameters involved. In the present study, an attempt is made to identify chaos using various techniques and the behaviour of daily rainfall series in different regions. Daily rainfall data of three regions with contrasting characteristics (mainly in the spatial area covered), Malaprabha river basin, Mahanadi river basin and All India for the period 1955 to 2000 are used for the study. Auto-correlation and mutual information methods are used to determine the delay time for the phase space reconstruction. Optimum embedding dimension is determined using correlation dimension, false nearest neighbour algorithm and also nonlinear prediction methods. The low embedding dimensions obtained from these methods indicate the existence of low dimensional chaos in the three rainfall series considered. Correlation dimension method is repeated on the phase randomized and first derivative of the data series to check the existence of any pseudo low-dimensional chaos [Osborne and Provenzale, 1989]. Positive Lyapunov exponents obtained prove the exponential divergence of the trajectories and hence the unpredictability. Surrogate data test is also done to further confirm the nonlinear structure of the rainfall series. A limit in predictability in chaotic system arises mainly due to its sensitivity to the infinitesimal changes in its initial conditions and also due to the ineffectiveness of the model to reveal the underlying dynamics of the system. In the present study, an attempt is made to quantify these uncertainties involved and thereby improve the predictability by adopting a nonlinear ensemble prediction. A range of plausible parameters is used for generating an ensemble of predictions of rainfall for each year separately for the period 1996 to 2000 using the data till the preceding year. For analyzing the sensitiveness to initial conditions, predictions are made from two different months in a year viz., from the beginning of January and June. The reasonably good predictions obtained indicate the efficiency of the nonlinear prediction method for predicting the rainfall series. Also, the rank probability skill score and the rank histograms show that the ensembles generated are reliable with a good spread and skill. A comparison of results of the three regions indicates that although they are chaotic in nature, the spatial averaging over a large area can increase the dimension and improve the predictability, thus destroying the chaotic nature. The predictability of the chaotic daily rainfall series is improved by utilizing information from various climatic indices and adopting a multivariate nonlinear ensemble prediction. Daily rainfall data of Malaprabha river basin, India for the period 1955 to 2000 is used for the study. A multivariate phase space is generated, considering a climate data set of 16 variables. The redundancy, if any, of this atmospheric data set is further removed by employing principal component analysis (PCA) method and thereby reducing it to 8 principal components (PCs). This multivariate series (rainfall along with 8 PCs) are found to exhibit a low dimensional chaotic nature with dimension 10. Nonlinear prediction is done using univariate series (rainfall alone) and multivariate series for different combinations of embedding dimensions and delay times. The uncertainty in initial conditions is thus addressed by reconstructing the phase space using different combinations of parameters. The ensembles generated from multivariate predictions are found to be better than those from univariate predictions. The uncertainty in predictions is reduced or in other words, the predictability is improved by adopting multivariate nonlinear ensemble prediction. The restriction on predictability of a chaotic series can thus be reduced by quantifying the uncertainty in the initial conditions and also by including other possible variables, which may influence the system. Even though, the sensitivity to initial conditions limit the predictability in chaotic systems, a prediction algorithm capable of resolving the fine structure of the chaotic attractor can reduce the prediction uncertainty to some extent. All the traditional chaotic prediction methods are based on local models since these methods model the sudden divergence of the trajectories with different local functions. Conceptually, global models are ineffective in modeling the highly unstable structure of the chaotic attractor [Sivakumar et al., 2002a]. This study focuses on combining a local learning wavelet analysis (decomposition) model with a global feedforward neural network model and its implementation on phase space prediction of chaotic streamflow series. The daily streamflow series at Basantpur station in Mahanadi basin, India is found to exhibit a chaotic nature with dimension varying from 5-7. Quantification of uncertainties in future predictions are done by creating an ensemble of predictions with wavelet network using a range of plausible embedding dimension and delay time. Compared with traditional local approximation approach, the total predictive uncertainty in the streamflow is reduced when modeled with wavelet networks for different lead times. Localization property of wavelets, utilizing different dilation and translation parameters, helps in capturing most of the statistical properties of the observed data. The need for bringing together the characteristics of both local and global approaches to model the unstable yet ordered chaotic attractor is clearly demonstrated.

The ENSO-monsoon system is known to have a biennial component. Here we show using high resolution satellite data, mainly daily rainfall and sea surface temperature (SST) from the Tropical Rainfall Measuring Mission (TRMM), and daily scatterometer surface winds from QuickSCAT, that there is a clear biennial oscillation (TBO) in summer monsoon rainfall over Central India – Bay of Bengal (Cl-BoB) and the far west Pacific in the period 1999-2005. Summer (JJAS) mean rainfall oscillates between high and low values in alternate years; the rainfall is high in the odd years 1999, 2001, 2003, and 2005, and low in even years 2000, 2002 and 2004. The amplitude of the oscillation is significant, as measured against the long term standard deviation of seasonal rain based on 1979-2005 Global Precipitation Climatology Project (GPCP) data. We find that the TBO in rainfall is associated with TBO of SST over the tropical Indian, west Pacific and Atlantic Oceans in different seasons. There is no TBO in east Pacific SST, and no strong El Nino in this period. The TBO of SST is related to change in evaporation due to TBO of surface wind speed. A TBO of the surface branch of the Walker circulation in the eastern Indian and western Pacific basins is clearest in the autumn season during 1999-2005. There is a clear relation between a large-amplitude TBO of winter surface air temperature over north Asia associated with TBO of the Arctic oscillation (AO), and the TBO of summer monsoon rainfall. High rainfall over CI-BoB lin summer is followed by a relatively high value of the AO Index, and warm air termperature over north Asia in the succeeding winter. The Inter Tropical Convergence Zone(ITCZ) over the central Pacific and Atlantic Oceans shift north by about two degrees when the northern hemisphere is warm, reminiscent of the behaviour of the climate system of ENSO, decadal and palaeoclimate time scales. In this thesis we document the biennial oscillation of monsoon rain and its spatial structure in the recent period, and its relation with biennial oscillation of surface climate over the global tropics and extratropical regions. The existence of TBO in the tropical Atlantic, and its relation with the monsoon, is a new finding. We demonstrate that the interannual variability of the summer monsoon during 1999-2005, including the drought of 2002, is part of a pervasive TBO of global surface climate.

Indian summer monsoon (ISM) is an important component of the tropical climate system, known for its regular seasonality and abundance of rainfall over the country. The droughts and floods associated with the year-to-year variation of the average seasonal rainfall have devastating effect on people, agriculture and economy of this region. The demand for prediction of seasonal monsoon rainfall, therefore, is overwhelming. A number of attempts to predict the seasonal mean monsoon have been made over a century, but neither dynamical nor empirical models provide skillful forecasts of the extremes of the monsoon such as the unprecedented drought of 2002. This study investigates the problems and prospects of extended range monsoon prediction. An evaluation of the potential predictability of the ISM with the aid of an ensemble of Atmospheric General Circulation Model (AGCM) simulations indicates that the interannual variability (IAV) of ISM is contributed equally by the slow boundary forcing (‘externally’ forced variability) and the inherent climate noise (‘internal’ variability) in the atmosphere. Success in predicting the ISM would depend on our ability to extract the predictable signal from a background of noise of comparable amplitude. This would be possible only if the ‘external’ variability is separable from the ‘internal’ variability. A serious effort has been made to understand and isolate the sea surface temperature (SST) forced component of ISM variability that is not strongly influenced by the ‘internal’ variability. In addition, we have investigated to unravel the mechanism of generation of ‘internal’ IAV so that the method of isolating it from forced variability may be found. Since the primary forcing mechanism of the monsoon is the large-scale meridional gradient of deep tropospheric heat sources, large-scale changes in tropospheric temperature (TT) due to the boundary forcing can induce interannual variations of the timing and duration of the monsoon season. The concept of interannually varying monsoon season is introduced here, with the onset and withdrawal of monsoon definitions based on the reversal of meridional gradient of TT between north and south. This large scale definition of the monsoon season is representative of the planetary scale influence of the El Ni˜no Southern Oscillation (ENSO) on monsoon through the modification of TT and the cross equatorial pressure gradient over the ISM region. A sig- nificant relationship between ENSO and monsoon, that has remained steady over the decades, is discovered by which an El Ni˜no (La Ni˜na) delays (advances) the onset, advances (delays) the withdrawal and suppresses (enhances) the strength of the monsoon. The integral effect of the meridional gradient of TT from the onset to withdrawal proves to be a useful index of seasonal monsoon which isolates the boundary forced signal from the influence of internal variations that has remained steady even in the recent decades. However, consistent with the estimates of potential predictability, the boundary forced variability isolated with the above definitions explains only about 50% of the total interannual variability of ISM. Detailed diagnostics of the onset and withdrawal processes are performed to understand how the ENSO forcing modifies the onset and withdrawal, and thus the seasonal mean monsoon. It is found that during an El Ni˜no, the onset is delayed due to the enhanced adiabatic subsidence that inhibits vertical mixing of sensible heating from the warm landmass during pre-monsoon months, and the withdrawal is advanced due to the horizontal advective cooling. This link between ENSO and monsoon is realized through the advective processes associated with the stationary waves in the upper troposphere set up by the tropical ENSO heating. The remaining 50% of the monsoon IAV is governed by internal processes. To unravel the mechanism of the generation of internal IAV, we perform another set of AGCM simulations, forced with climatological monthly mean SSTs, to extract the pure internal IAV. We find that the spatial structure of the intraseasonal oscillations (ISOs) in these simulations has significant projection on the spatial structure of the seasonal mean and a common spatial mode governs both intraseasonal and interannual variability. Statistical average of ISO anomalies over the season (seasonal ISO bias) strengthens or weakens the seasonal mean. It is shown that interannual anomalies of seasonal mean are closely related to the seasonal mean of intraseasonal anomalies and explain about 50% of the IAV of the seasonal mean. The seasonal mean ISO bias arises partly due to the broadband nature of the ISO spectrum, allowing the intraseasonal time series to be aperiodic over the season and partly due to a non-linear process where the amplitude of ISO activity is proportional to the seasonal bias of ISO anomalies. The later relationship is a manifestation of the binomial character of the rainfall time series. The remaining part of IAV may arise due to the complex land-surface processes, scale interactions, etc. We also find that the ISOs over the ISM region are not significantly modulated by the Pacific and Indian Ocean SST variations. Thus, even with a perfect prediction of SST, only about 50% of the observed IAV of ISM could be predicted with the best model in forced mode. Even so, prediction of all India rainfall (AIR) representing the average conditions of the whole country and the season may not always serve the purposes of monsoon forecasting. One reason is the large inhomogeneities in the rainfall distribution during a normal seasonal monsoon. Agriculture and hydrological sector could benefit more if provided with regional scale forecasts of active/break spells 2-3 weeks ahead. Therefore, we advocate an alternative strategy to the seasonal prediction. Here, we present a method to estimate the potential predictability of active and break conditions from daily rainfall and circulation from observations for the recent 24 years. We discover that transitions from break to active conditions are much more chaotic than those from active to break, a fundamental property of the monsoon ISOs. The potential predictability limit of monsoon breaks (∼20 days) is significantly higher than that of the active conditions (∼10 days). An empirical real- time forecasting strategy to predict the sub-seasonal variations of monsoon up to 4 pentads (20 days) in advance is developed. The method is physically based, with the consideration that the large-scale spatial patterns and slow evolution of monsoon intraseasonal variations possess some similarity in their evolutions from one event to the other. This analog method is applied on NOAA outgoing longwave radiation (OLR) pentad mean data which is available on a near real time basis. The elimination of high frequency variability and the use of spatial and temporal analogs produces high and useful skill of predictions over the central and northern Indian region for a lead-time of 4-5 pentads. An important feature of this method is that, unlike other empirical methods to forecast monsoon ISOs, this uses minimal time filtering to avoid any possible end-point effects, and hence it has immense potential for real-time applications.