EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Evaluation and Projection of Extreme Precipitation over Northern China in CMIP5 Models

Xi Lu
Xi Lu
  • Sun Yat-sen University, School of Atmospheric Sciences, China (

This study evaluates 32 climate models from CMIP5 compared with a daily gridded
observation dataset of extreme precipitation indices including total extreme precipitation (R95p),
maximum consecutive five days of precipitation (RX5day) and wet days larger than 10 mm of
precipitation (R10mm) over Northern China during the historical period (1986–2005). Results show
the majority models have good performance on spatial distribution but overestimate the amplitude of
precipitation over Northern China. Most models can also capture interannual variation of R95p and
RX5d, but with poor simulations on R10mm. Considering both spatial and temporal factors, the best
multi-model ensemble (Group 1) has been selected and improved by 42%, 34%, and 37% for R95p,
RX5d, and R10mm, respectively. Projection of extreme precipitation indicates that the fastest-rising
region is in Northwest China due to the enhanced rainfall intensity. However, the uncertainty
analysis shows the increase of extreme rainfall over Northwest China has a low confidence level.
The projection of increasing extreme rainfall over Northeast China from Group 1 due to the longer
extreme rainfall days is more credible. The weak subtropical high and southwest winds from Arabian
Sea lead to the low wet biases from Group 1 and the cyclonic anomalies over Northeast China, which
result in more extreme precipitation.

How to cite: Lu, X.: Evaluation and Projection of Extreme Precipitation over Northern China in CMIP5 Models, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1458,, 2019