Do CMIP models capture long term observed annual precipitation trends?
Vicente Serrano S.M., García Herrera R., Peña Angulo D., Tomas Burguera M., Domínguez Castro F., Noguera I., Calvo N., Murphy C., Nieto R., Gimeno L., Gutierrez J.M., Azorin Molina C., El Kenawy A. (2021). Do CMIP models capture long term observed annual precipitation trends?. Climate Dynamics. https://doi.org/10.1007/s00382-021-06034-x
This study provides a long-term (1891–2014) global assessment of precipitation trends using data from two station-based gridded datasets and climate model outputs evolved through the ffth and sixth phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively). Our analysis employs a variety of modeling groups that incorporate low- and high-top level members, with the aim of assessing the possible efects of including a well-resolved stratosphere on the model’s ability to reproduce long-term observed annual precipitation trends. Results demonstrate that only a few regions show statistically signifcant diferences in precipitation trends between observations and models. Nevertheless, this pattern is mostly caused by the strong interannual variability of precipitation in most of the world regions. Thus, statistically signifcant model-observation diferences on trends (1891–2014) are found at the zonal mean scale. The diferent model groups clearly fail to reproduce the spatial patterns of annual precipitation trends and the regions where stronger increases or decreases are recorded. This study also stresses that there are no signifcant diferences between low- and high-top models in capturing observed precipitation trends, indicating that having a well-resolved stratosphere has a low impact on the accuracy of precipitation projections.
This study provides a long-term (1891–2014) global assessment of precipitation trends using data from two station-based gridded datasets and climate model outputs evolved through the ffth and sixth phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively). Our analysis employs a variety of modeling groups that incorporate low- and high-top level members, with the aim of assessing the possible efects of including a well-resolved stratosphere on the model’s ability to reproduce long-term observed annual precipitation trends. Results demonstrate that only a few regions show statistically signifcant diferences in precipitation trends between observations and models. Nevertheless, this pattern is mostly caused by the strong interannual variability of precipitation in most of the world regions. Thus, statistically signifcant model-observation diferences on trends (1891–2014) are found at the zonal mean scale. The diferent model groups clearly fail to reproduce the spatial patterns of annual precipitation trends and the regions where stronger increases or decreases are recorded. This study also stresses that there are no signifcant diferences between low- and high-top models in capturing observed precipitation trends, indicating that having a well-resolved stratosphere has a low impact on the accuracy of precipitation projections.