Study of Climate Variability Patterns at Different Scales – A Complex Network Approach

Das Klimasystem der Erde besteht aus zahlreichen interagierenden Teilsystemen, die sich über verschiedene Zeitskalen hinweg verändern, was zu einer äußerst komplizierten räumlich-zeitlichen Klimavariabilität führt. Das Verständnis von Prozessen, die auf verschiedenen räumlichen und zeitlichen Skalen ablaufen, ist ein entscheidender Aspekt bei der numerischen Wettervorhersage. Die Variabilität des Klimas, ein sich selbst konstituierendes System, scheint in Mustern auf großen Skalen organisiert zu sein. Die Verwendung von Klimanetzwerken hat sich als erfolgreicher Ansatz für die Erkennung der räumlichen Ausbreitung dieser großräumigen Muster in der Variabilität des Klimasystems erwiesen. In dieser Arbeit wird mit Hilfe von Klimanetzwerken gezeigt, dass die Klimavariabilität nicht nur auf größeren Skalen (Asiatischer Sommermonsun, El Niño/Southern Oscillation), sondern auch auf kleineren Skalen, z.B. auf Wetterzeitskalen, in Mustern organisiert ist. Dies findet Anwendung bei der Erkennung einzelner tropischer Wirbelstürme, bei der Charakterisierung binärer Wirbelsturm-Interaktionen, die zu einer vollständigen Verschmelzung führen, und bei der Untersuchung der intrasaisonalen und interannuellen Variabilität des Asiatischen Sommermonsuns. Schließlich wird die Anwendbarkeit von Klimanetzwerken zur Analyse von Vorhersagefehlern demonstriert, was für die Verbesserung von Vorhersagen von immenser Bedeutung ist. Da korrelierte Fehler durch vorhersagbare Beziehungen zwischen Fehlern verschiedener Regionen aufgrund von zugrunde liegenden systematischen oder zufälligen Prozessen auftreten können, wird gezeigt, dass Fehler-Netzwerke helfen können, die räumlich kohärenten Strukturen von Vorhersagefehlern zu untersuchen. Die Analyse der Fehler-Netzwerk-Topologie von Klimavariablen liefert ein erstes Verständnis der vorherrschenden Fehlerquelle und veranschaulicht das Potenzial von Klimanetzwerken als vielversprechendes Diagnoseinstrument zur Untersuchung von Fehlerkorrelationen.The Earth’s climate system consists of numerous interacting subsystems varying over a multitude of time scales giving rise to highly complicated spatio-temporal climate variability. Understanding processes occurring at different scales, both spatial and temporal, has been a very crucial problem in numerical weather prediction. The variability of climate, a self-constituting system, appears to be organized in patterns on large scales. The climate networks approach has been very successful in detecting the spatial propagation of these large scale patterns of variability in the climate system. In this thesis, it is demonstrated using climate network approach that climate variability is organized in patterns not only at larger scales (Asian Summer Monsoon, El Niño-Southern Oscillation) but also at shorter scales, e.g., weather time scales. This finds application in detecting individual tropical cyclones, characterizing binary cyclone interaction leading to a complete merger, and studying the intraseasonal and interannual variability of the Asian Summer Monsoon. Finally, the applicability of the climate network framework to understand forecast error properties is demonstrated, which is crucial for improvement of forecasts. As correlated errors can arise due to the presence of a predictable relationship between errors of different regions because of some underlying systematic or random process, it is shown that error networks can help to analyze the spatially coherent structures of forecast errors. The analysis of the error network topology of a climate variable provides a preliminary understanding of the dominant source of error, which shows the potential of climate networks as a very promising diagnostic tool to study error correlations

Ocean ensemble forecasting. Part I: Ensemble Mediterranean winds from a Bayesian hierarchical model

A Bayesian hierarchical model (BHM) is developed to estimate surface vector wind (SVW) fields and associated uncertainties over the Mediterranean Sea. The BHM–SVW incorporates data-stage inputs from analyses and forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) and SVW retrievals from the QuikSCAT data record. The process-model stage of the BHM–SVW is based on a Rayleigh friction equation model for surface winds. Dynamical interpretations of posterior distributions of the BHM–SVW parameters are discussed. Ten realizations from the posterior distribution of the BHM–SVW are used to force the data-assimilation step of an experimental ensemble ocean forecast system for the Mediterranean Sea in order to create a set of ensemble initial conditions. The sequential data-assimilation method of the Mediterranean forecast system (MFS) is adapted to the ensemble implementation. Analyses of sample ensemble initial conditions for a single data-assimilation period in MFS are presented to demonstrate the multivariate impact of the BHM–SVW ensemble generation methodology. Ensemble initial-condition spread is quantified by computing standard deviations of ocean state variable fields over the ten ensemble members. The methodological findings in this article are of two kinds. From the perspective of statistical modelling, the process-model development is more closely related tophysicalbalances than inpreviousworkwithmodels for the SVW.Fromthe ocean forecast perspective, the generation of ocean ensemble initial conditions via BHM is shown to be practical for operational implementation in an ensemble ocean forecast system. Phenomenologically, ensemble spread generated via BHM–SVW occurs on ocean mesoscale time- and space-scales, in close association with strong synoptic-scale wind-forcing events. A companion article describes the impacts of the BHM–SVW ensemble method on the ocean forecast in comparisons with more traditional ensemble methods

Advances in Hurricane Research

This book provides a wealth of new information, ideas and analysis on some of the key unknowns in hurricane research. Topics covered include the numerical prediction systems for tropical cyclone development, the use of remote sensing methods for tropical cyclone development, a parametric surface wind model for tropical cyclones, a micrometeorological analysis of the wind as a hurricane passes over Houston, USA, the meteorological passage of numerous tropical cyclones as they pass over the South China Sea, simulation modelling of evacuations by motorised vehicles in Alabama, the influence of high stream-flow events on nutrient flows in the post hurricane period, a reviews of the medical needs, both physical and psychological of children in a post hurricane scenario and finally the impact of two hurricanes on Ireland. Hurricanes discussed in the various chapters include Katrina, Ike, Isidore, Humberto, Debbie and Charley and many others in the North Atlantic as well as numerous tropical cyclones in the South China Sea

Characteristics of tropical cyclones in the North Atlantic and East Pacific.

In this dissertation, I present a series of investigations to expand our understanding of TCs in the East Pacific and North Atlantic basins. First, I developed and applied a climatological tool that quickly and succinctly displays the spread of historical TC tracks for any point in the North Atlantic basin. This tool is useful in all parts of a basin because it is derived from prior storm motion trajectories and summarily captures the historical synoptic and mesoscale steering patterns. It displays the strength of the climatological signal and allow for rapid qualitative comparison between historical TC tracks and NWP models. Second, I have used a robust statistical technique to quantify the relationships between fifteen different metrics of TC activity in nine ocean basins and twelve climate indices of the leading modes of atmospheric and oceanic variability. In a thorough, encyclopedic manner, over 12,000 Spearman rank correlation coefficients were calculated and examined to identify relationships between TCs and their environment. This investigation was not limited to the East Pacific or North Atlantic, and new climatic associations were found between seasonal levels of TC activity and the major climate indices across the nine basins. This information is critical to forecasters, economists, actuaries, energy traders, and societal planners who apply knowledge of levels of TC activity on intraseasonal to interdecadal timescales. The statistics are also valuable to climatologists seeking to understand how regional TC frequency will change as the global climate warms. Third, I have examined the leading intraseasonal mode of atmospheric and oceanic variability, the Madden-Julian Oscillation (MJO), and discovered statistically significant relationships with the frequency of TC genesis, intensification, and landfall over the nine basins. Like the significance of the longer-period oscillations to the frequency of TC activity on intraseasonal and longer timescales, these results are highly relevant to the problem of short-term (one- to two-week) predictability of TC activity. These three investigations demonstrate the utility of historical datasets across a wide range of applications, from short-term forecasting to climate studies. In this way, the results highlighted in this dissertation represent a significant and positive contribution to meteorology. Collectively, they reveal multiple characteristics of TCs in the East Pacific and North Atlantic and provide greater understanding of the complex interactions between TCs and their surrounding larger-scale environment

MADDEN-JULIAN OSCILLATION AND SEA SURFACE TEMPERATURE INTERACTIONS IN A MULTI-SCALE FRAMEWORK

The ocean-atmosphere coupling can play a role in initiating and sustaining the Madden-Julian Oscillations (MJOs), which are the major intraseasonal oscillations in the atmosphere. In this thesis, the oceanic influence on MJOs is studied with reanalysis products, numerical models, and idealized theoretical models. The energy sources for MJOs are calculated with NCEP reanalysis. The perturbed potential energy is found to be the most important energy source for most MJO events. In some MJO events, the sea surface is warmed due to the reduced latent heat flux during the suppressed phase of MJOs. As a result, warm sea surface temperature anomalies (SSTAs) occur, which appear to prolong the life time of these MJO events. In a minority of the MJO events, warm SSTAs can drive the atmosphere actively and trigger MJO events. In these events, the warm SSTAs are attributable to the internal oceanic processes influenced by the warm Indonesian Throughflow (ITF), which spreads from the southeastern Indian Ocean to the western Indian Ocean and modifies the subtle balance between stratification and mixing in the western Indian Ocean. In addition, during the transit period between monsoon seasons, a few MJO events are sustained by the energy obtained from the mean kinetic energy. Since the MJO events have different energy sources, their mechanisms should be considered in the context of these energy sources. While the spatial scale of the SSTAs in the Indian Ocean is only of order 100 km, the scale of MJOs is of order 1000 km, raising the potential for interactions between the oceanic and the atmospheric oscillations with different scales and this is demonstrated to be possible with analytical solutions to idealized linear governing equations. With a reasonable choice of parameters, the meso-scale oceanic and the large-scale atmospheric oscillations can interact with each other and lead to unstable waves in the intraseasonal band in this linear coupled model. The coupling and frequency shifts between oscillations with different scales and the atmospheric/oceanic responses to small variations in the external forcing are also tested with numerical models. Incorporating the oceanic influence on MJOs and the multi-scale interaction appropriately in a numerical model is supposed to help improve the simulation and forecast of MJOs. The hypothesis of multi-scale interaction is also expected to have wide applications in other studies, in addition to the MJO-SST interaction. The theoretical and numerical approach adopted here should also serve as a prototype for enhancing the process understanding of intraseasonal variability and lead to improved predictive understanding

Impacts of the Changing Pacific on North American Drought, Atmospheric Rivers, and Explosive Cyclones

The impacts of specific weather events can vary greatly from year to year. Much of these impacts depend heavily on the frequency of impactful weather which is constrained by the state of the climate system each year. This research focuses largely on the impacts that climate oscillations from year-to-year or even from decade-to-decade have on the frequency of impactful weather. There are numerous examples of impactful weather that impact North America, but this work focuses on drought in the western United States, atmospheric rivers in Northern California and rapidly developing winter storms along the east coast. While seemingly disparate events, there is much overlap in the mechanisms by which variations in the ocean and atmosphere can impact the frequency of these impactful events. Most of these mechanisms involve the tropical Pacific Ocean, which acts as a major driving force for the state of the atmosphere over North America and the resulting frequency of weather extremes

Northwest Australian Tropical Cyclones: Variability and Seasonal Prediction

Global teleconnections, involving geopotential height, air temperature, and sea surface temperature, are found for the interannual variability of tropical cyclone (TC) activity in Northwest-Australian (NWAUS) basin of the Southeast Indian Ocean (105-135&deg; E). The NWAUS basin averages 5.5 TCs per year, 42 TC days, and 3 TC landfalls. Additionally, a wavelet analysis yields wavelet power maximum in the 4-6 year and the decadal time periods for both yearly TC frequency and TC days. To identify significant correlates, the global atmospheric and oceanic parameters mentioned above were correlated with the TC frequency and TC days from the Woodside Petroleum Ltd. TC data set. Large correlations were obtained between the NWAUS TC frequency and the following variables: Apr-Jun 700-hPa geopotential heights over North America (r ~ -0.64), May-Jul 850-hPa geopotential heights over the south Indian Ocean (r ~ 0.60), May-Jul 850-hPa air temperature (r ~ -0.63), Jun-Aug 925-hPa geopotential heights over the south Atlantic Ocean (r ~ -0.65), and Jun-Aug 925-hPa geopotential heights over the Eastern Pacific Ocean (r ~ -0.59). The collinearity among the five correlates are generally less than magnitude 0.4. Additionally, large correlations were obtained between the NWAUS TC days and the following variables: Jan-Mar 100-hPa v-component of the wind over the Southern Pacific Ocean (r ~ 0.52), Apr-Jun 850-hPa geopotential heights over North America (r ~ -0.58), and Jul-Sep 1000-hPa geopotential heights over the South Altanic Ocean (r ~ -0.7). These variables can be utilized as seasonal predictors for the upcoming TC season in terms of frequency and days with a lead-time of at least three months for TC frequency and two months for TC days. This set of seasonal predictors includes, intra-basin, inter-basin, and cross-hemispheric regions, unlike previous Australian TC activity studies, which stress the primacy of ENSO. Here it is noted that the traditional Nino 3.4 and Nino 4 regions were not highly correlated with the NWAUS TC activity (< magnitude 0.5). No local predictors based on SST, geopotential height, or air temperature resulted from the correlation analysis. The predictors are used in a multiple linear regression model for forecasting the coming seasons number of TCs and TC days. Finally, both prediction schemes are then compared to forecasts made using persistence, climatology, and random forecasts to determine if they perform better than these reference forecasts

The global monsoon system: research and forecast

The main objective of this workshop was to provide a forum for discussion between researchers and forecasters on the current status of monsoon forecasting and on priorities and opportunities for monsoon research. WMO hopes that through this series of quadrennial workshops, the following goals can be accomplished: (a) to update forecasters on the latest reseach findings and forecasting technology; (b) to update researchers on monsoon analysis and forecasting; (c) to identify basic and applied research priorities and opportunities; (d) to identify opportunities and priorities for acquiring observations; (e) to discuss the approach of a web-based training document in order to update forecasters on developments of direct relevance to monsoon forecasting