Climate over eastern Asia is mainly characterized by the East-Asian summer monsoon (EASM), the related formation of the quasi-stationary Changma-Baiu-Meiyu frontal system, and the occurrence of tropical cyclones (TC). Possible changes of the EASM under enhance greenhouse gas concentrations could have high impact on society and economy of one of the most densely populated regions of the globe.
Regional decision processes for the development of suitable adaptation strategies or the timely initiation of related mitigation efforts in East Asia will strongly depend on robust and comprehensive information about future near-term as well as long-term potential changes in the climate system. Based on physical process understanding, it is important to quantify the regional effects of global or hemispheric scale phenomena for both, the scientific community to understand potential changes and the impact community (incl. decision makers) to act proactively in the most suitable manner. The three most important aspects in this context are the provision of a) relevant, timely, and b) comprehensive information about potential changes as well as c) information about the quality of the confidence in the information.
MUDEX aims to analyse and assess the decadal to multi-decadal variability of important climate drivers affecting the East Asian region and related extremes. The main goals are to i) evaluate decadal to multi-decadal variability in state-of-the-art climate models and the responsible meteorological drivers, ii) to assess possible changes under enhanced greenhouse gas concentrations and iii) assess in how far climate change signals are influenced by decadal to multi-decadal variability.
This study will be embedded in the project FOREX (Fostering Regional Decision Making by the Assessment of Uncertainties of Future Regional Extremes and their Linkage to Global Climate System Variability for China and East Asia), which is part of the Met Office CSSP China project funded by the Newton fund. FOREX aims to analyse changes of local and regional extreme events (TC’s, EASM) under changed future climate conditions using a huge amount of different climate projection datasets (CMIP3, CMIP5, Perturbed-physic ensembles) with a strong focus on climate change signals on longer time-scales.
MUDEX consists of three work-packages (WP):
WP1: Assess decadal to multi-decadal variability in long-term reanalysis data (ERA-20C) as well as historical CMIP5 simulations. This WP focuses especially in how far observed mechanisms influence the EASM on these time-scales are present in current (CMIP5) historical simulations.
WP2: This WP aims to asess changes of the EASM on decadal- to multi-decadal time-scales under changed greenhouse gas concentrations. Different emission scenarios (RCP4.5, RCP8.5) are used for a range of CMIP5 models.
WP3: Climate change signals are usually derived by deriving changes at the end of the 21st century compared to a reference period at the end of the 20th century. Typically climate change signals are averaged over 30-40 year periods. However, the choice of this period might be crucial for meteorological systems showing a large decadal to multi-decadal variability, as the current phase of the system might dominate the climate change signal. This WP aims to assess the effect of different decadal- to multi-decadal phases of the EASM on the derived climate change signal. Results obtained here are crucial for mitigation and adaptation strategies (and thus decision makers) over the East Asian reigon.
Training and Skills
CENTA students will attend 45 days training throughout their PhD including a 10 day placement. In the first year, students will be trained as a single cohort on environmental science, research methods and core skills. Throughout the PhD, training will progress from core skills sets to master classes specific to the student's projects and themes.
Specific for this project, the PhD student will gain skills to analyse state-of-the-art forecast data. This training will be in direct modelling as well as in a response surface approach and, specifically, is in:
extreme value and multi-variate analytical statistics
the basics of CAT models and their specific features to model hazards, vulnerabilities and exposure
fieldwork, integrated modelling
GIS, and relevant programming giving the student skills identified as ‘most wanted’ for environmental jobs; ‘modelling’, ‘multi-disciplinarity’, ‘risk and uncertainty’.
This is excellent employment market preparation as scientific research skills, technical analysis and industry related model skills will be practiced and gained.
Year 1: In the first year work will start with in-depth literature research on the topic. Additionally, the student will make herself/himself familiar with the computational system at the UoB (including the HPC cluster Bluebear). Learning the usage of important tools in handling large datasets (e.g. cdo – climate data operators) and to start first scientific analysis of the data sets under investigation is intended in the first year.
Year 2: In this year the student will concentrate on the work in WP1. Using ERA-20C and historical simulations from CMIP5 models will be used to assess decadal- to multi-decadal variability of the ISM in reanalysis and model data.
Year 3: In year three, the student will work on WP2 and WP3 using information from WP1. Changes of the EASM on multi-decadal time-scales will be analysed and related to the effect of the multi-decadal phase of the EASM on the climate change signals for a huge range of CMIP5 models.
Partners and collaboration (including CASE)
Partners in this CENTA-PhD studentship will be University of Birmingham and regional partners in China (e.g. the Nanjing University of Information Science & Technology) with which the PI has scientific collaboration in the framework of the CSSP-China project. Further on, collaborations exist with different groups at the Uk Met Office, who is leading institution in this Newton Fund funded project.
Dr Gregor C. Leckebusch
Senior Lecturer for Meteorology and Climatology
EHS Postgraduate Research Tutor
School of Geography, Earth and Environmental Sciences
University of Birmingham
Tel: +44 (0)121 41 45518