Climate Science for Service Partnership China
The Climate Science for Service Partnership China (CSSP China) is a scientific research project that is building the basis for services to support climate and weather resilient economic development and social welfare through strong, strategic partnerships harnessing UK scientific expertise.
Through CSSP China (supported by the Newton Fund and the Department for Business, Energy & Industrial Strategy (BEIS) ) we are developing a strongly bilateral partnership between the Met Office, the (CMA), the (IAP) at the Chinese Academy of Sciences, and other key institutes within China and the UK.
The overarching aims of CSSP China are to:
- develop and use improved underpinning data sets for understanding past climate, recent extremes, and possible future changes in China;
- enhance understanding of global dynamics of climate variability and change to improve regional climate predictions of extreme events;
- enhance understanding of East Asian climate variability and extremes, their causes and predictability;
- develop underpinning models and climate projection systems for improved simulation of climate and understanding of future changes; and
- develop applied science and prototype services to support climate-resilient development and social welfare.
CSSP China focuses on five main research areas:
- Work package 1: Monitoring, Attribution and Reanalysis
- Work package 2: Global dynamics of climate variability and change
- Work package 3: East Asian climate variability and extremes
- Work package 4: Development of models and climate projection systems
- Work package 5: Climate Services
CSSP China research grants awarded – September 2019
Following the publication of calls in May 2019, we are pleased to announce the following awards for new project work under CSSP China commencing in October 2019:
- University of Reading/National Centre for Atmospheric Science (NCAS) - Providing methodologies and communications materials for sharing the outputs and knowledge from CSSP China.
- Read a blog post on this here
CSSP China launched in 2014
- CSSP China Infographic
- Yangtze river flood infographic
- UNSEEN infographic
- Case study - Addressing air quality issues in China
- Case study - Climate change and extreme events
- Case study - Improving the prediction of tropical cyclones
- Case study - Developing a global network of science partnerships
- Case study - Science summary - energy
- Case study - Science summary - extreme weather
- Case study - Science summary - urban
- Case study - seasonal forecasting of rainfall in the Yangtze River basin
- Case study - unprecedented events
Measuring climate risk in China “climate change is increasing the likelihood of drought over the summer monsoon season as well as the chance of flash flooding during individual monsoon rainstorms.” (2017)
Extremes “Human influence on the climate has resulted in an 11-fold increase in the likelihood of extremely hot spring mean temperatures in northern China.” (2015)
Seasonal forecasts for the Yangtze River Basin. A prototype climate service has been trialled “producing a real-time seasonal forecast for the Yangtze river basin throughout the spring and summer of 2016” providing advice for decision makers at hydroelectric dams. (2017) – See WP5.
Unprecedented events. An innovative technique for assessing current risk of unprecedented climate extreme events UNSEEN (UNprecedented Simulation of Extremes with ENsembles). (2017) – See also WP3 & 5. Li et al 2016 and Thompson et al 2018
Aerosol forcing of extreme summer drought over North China– (Lixia Zhang et al., 2017) à finding that the cooling effect of aerosols have contributed to increased drought in Northern China.
ENSO Transition from La Nina to El Nino drives prolonged Spring-Summer Drought over North China – (Lixia Zhang, 2018) à improving our knowledge of persistent drought precursors which results in “agricultural damage and long-term regional water crises”.
Contribution from CSSP China to development of the latest generation of global coupled physical model HadGEM3-GC3.1 for CMIP6. GC3.1 shows improved performance across a wide-range of present day metrics of climate processes & variability. HadGEM3-GC3.1 is the basis of the PPE and the earth system model, UKESM1, developed jointly with NERC.
Williams, K. D., Copsey, D., Blockley, E. W., Bodas-Salcedo, A., Calvert, D., Comer, R., Davis, P., Graham, T., Hewitt, H. T., Hill, R., Hyder, P., Ineson, S., Johns, T. C., Keen, A. B., Lee, R. W., Megann, A., Milton, S. F., Rae, J. G. L., Roberts, M. J., Scaife, A. A., Schiemann, R., Storkey, D., Thorpe, L., Watterson, I. G., Walters, D. N., West, A., Wood, R. A., Woollings, T. and Xavier, P. K. (2017), The Met Office Global Coupled Model 3.0 and 3.1 (GC3.0 & GC3.1) Configurations. J. Adv. Model. Earth Syst. doi:10.1002/2017MS001115
Contributions to delivery of the framework for PPE and to the final 15-member coupled PPE climate projections to 2100 being used for UKCP18 project and for studying climate change responses over East Asia within CSSP China project.
Nudging the global model back to re-analyses over specific regions has been used to determine the role of remotely forced model systematic errors on performance in the East Asian region – removing model errors over the tropics improves aspects of the East Asian/Pacific circulation (e.g. west Pacific sub-tropical high), important both for moisture transport into the East Asian Monsoon and for steering of tropical cyclones in the west Pacific.
Rodríguez, J. M., Milton, S. F., & Marzin, C. (2017). The East Asian atmospheric water cycle and monsoon circulation in the Met Office Unified Model. Journal of Geophysical Research: Atmospheres, 122, 10,246–10,265. https://doi.org/10.1002/2016JD025460
Prediction of extreme precipitation in Chinese Flooding events of 2016. Collaborative research between WP3 and WP4 and CMA to study the predictability and physical processes behind the 2016 flooding events (May 2016 and July 2016 - Wuhan floods). Explores relevance of short-range NWP predictions to predicting embedded "extreme weather" in seasonal and climate change predictions and the processes required to accurately represent these extremes.
Li, J., H. Chen, X. Rong, J. Su, Y. Xin, K. Furtado, S. Milton, and N. Li, 2018: How Well Can a Climate Model Simulate an Extreme Precipitation Event: A Case Study Using the Transpose-AMIP Experiment. J. Climate, 31, 6543–6556, https://doi.org/10.1175/JCLI-D-17-0801.1
Understanding risk of yield shocks. A new technique for assessing current climate risk to extreme events UNSEEN (UNprecendented Simulation of Extremes with Ensembles) (see WP2) has been used to understand and communicate current and future risk to food security; for example examining the likelihood of maize yield shocks due to unprecedented severe water stress in the future.