基本信息
浏览量:133
职业迁徙
个人简介
My research interests are very broad ranging from methods to reconstruct past climate from proxy records, such as tree rings, and instrumental data, through to modelling future climate. At the heart of my research is the quantitative analysis of models and observations of climate change in order to constrain the future. I’m also interested in extreme climate events and their causes.
My current research has been about extreme events largely in China where with CSSP funding I have been investigating the ability of climate models to simulate extreme events that are relevent to society. This has largely focused on extreme temperatures both “dry bulb” and “wet bulb” in China. I have also led a series of workshop with Chinese and Brizillian scientists where we carried out event attribution studies to see how how much human influences had affected observed observed extreme events. As expected we found large increases in the probability of extreme temperature events. Surprisingly we found significant changes in the probability of hydrological extremes.
I also am interested in the use of optimsation methods applied to climate models to constrain future climate change and currently have a student working on Machine Learning for convective parmaeterisation.
My current research has been about extreme events largely in China where with CSSP funding I have been investigating the ability of climate models to simulate extreme events that are relevent to society. This has largely focused on extreme temperatures both “dry bulb” and “wet bulb” in China. I have also led a series of workshop with Chinese and Brizillian scientists where we carried out event attribution studies to see how how much human influences had affected observed observed extreme events. As expected we found large increases in the probability of extreme temperature events. Surprisingly we found significant changes in the probability of hydrological extremes.
I also am interested in the use of optimsation methods applied to climate models to constrain future climate change and currently have a student working on Machine Learning for convective parmaeterisation.
研究兴趣
论文共 205 篇作者统计合作学者相似作者
按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETYno. 3 (2023): E673-E679
引用0浏览0引用
0
0
crossref(2023)
Nature communicationsno. 1 (2023): 93-11
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETYno. 10 (2023): E1807-E1816
SCIENCE ADVANCESno. 48 (2023): eadi2714-eadi2714
Zenodo (CERN European Organization for Nuclear Research) (2022)
引用0浏览0引用
0
0
user-61447a76e55422cecdaf7d19(2022)
引用0浏览0引用
0
0
user-61447a76e55422cecdaf7d19(2022)
引用0浏览0引用
0
0
加载更多
作者统计
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn