EGU2020-3731
https://doi.org/10.5194/egusphere-egu2020-3731
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Tropical Cyclone Precipitation in the AMIP Experiments of the Primavera Project

Wei Zhang1, Gabriele Villarini1, Enrico Scoccimarro2, and Malcolm Roberts3
Wei Zhang et al.
  • 1IIHR-Hydroscience & Engineering, The University of Iowa (wei-zhang-3@uiowa.edu)
  • 2Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Bologna, Italy
  • 3UK Meteorological Office, Exeter, UK

This study examines the climatology and structure of precipitation associated with tropical cyclones based on the Atmospheric Model Intercomparison Project (AMIP) runs of the Process-based climate simulation: advances in high resolution modelling and European climate risk assessment (Primavera) Project during 1979-2014. We assess the role of spatial resolution in shaping tropical cyclone precipitation along with inter-model variability by evaluating climate models with a variety of dynamic cores and parameterization schemes. AMIP runs that prescribe historical sea surface temperatures and radiative forcings can well reproduce the observed spatial pattern of tropical cyclone precipitation climatology, with high-resolution performing better than low-resolution ones in the first order. Overall, the AMIP runs can also reproduce the fractional contribution of tropical cyclone precipitation to total precipitation in observations. Similar to tropical cyclone precipitation climatology, the factional contrition is better simulated by high-resolution models. All the models in the AMIP runs underestimate the observed composite tropical cyclone rainfall structure over both land and ocean, and we identify differences in this factor between high-resolution and low-resolution models. The underestimation of rainfall composites by the AMIP runs are also supported by the radial profile of tropical cyclone precipitation. This study shows that the high-resolution climate models can reproduce well the spatial pattern of tropical cyclone climatology and underestimate the composite rainfall structure, with increased spatial resolution that overall improves the performance of simulation.

How to cite: Zhang, W., Villarini, G., Scoccimarro, E., and Roberts, M.: Tropical Cyclone Precipitation in the AMIP Experiments of the Primavera Project, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3731, https://doi.org/10.5194/egusphere-egu2020-3731, 2020