%0 Journal Article %1 sexton2021perturbed %A Sexton, David M. H. %A McSweeney, Carol F. %A Rostron, John W. %A Yamazaki, Kuniko %A Booth, Ben B. B. %A Murphy, James M. %A Regayre, Leighton %A Johnson, Jill S. %A Karmalkar, Ambarish V. %D 2021 %J Climate Dynamics %K climate climatechange colleagues model ukcp %R 10.1007/s00382-021-05709-9 %T A perturbed parameter ensemble of HadGEM3-GC3.05 coupled model projections: part 1: selecting the parameter combinations %U https://doi.org/10.1007/s00382-021-05709-9 %X This is the first of two papers that describe the generation of a 25-member perturbed parameter ensemble (PPE) of high-resolution, global coupled simulations for the period 1900--2100, using CMIP5 historical and RCP8.5 emissions. Fifteen of these 25 coupled simulations now form a subset of the global projections provided for the UK Climate Projections 2018 (UKCP18). This first paper describes the selection of 25 variants (combinations of 47 parameters) using a set of cheap, coarser-resolution atmosphere-only simulations from a large sample of nearly 3000 variants. Retrospective 5-day weather forecasts run at climate resolution, and simulations of 2004--2009 with prescribed SST and sea ice are evaluated to filter out poor performance. We opted for a single design choice and sensitivity tests were done after the PPE was generated to demonstrate the effect of design choices on the filtering. Given our choice, only 38 of the parameter combinations were found to have acceptable performance at this stage. Idealised atmosphere-only simulations were then used to select the subset of 25 members that were as diverse as possible in terms of their CO2 and aerosol forcing, and their response to warmer SSTs. Using our parallel set of atmosphere-only and coupled PPEs (the latter from paper 2), we show that local biases in the atmosphere-only experiments are generally informative about the biases in the coupled PPE. Biases in radiative fluxes and cloud amounts are strongly informative for most regions, whereas this is only true for a smaller fraction of the globe for precipitation and dynamical variables. Therefore, the cheap experiments are an affordable way to search for promising parameter combinations but have limitations.

@article{sexton2021perturbed, abstract = {This is the first of two papers that describe the generation of a 25-member perturbed parameter ensemble (PPE) of high-resolution, global coupled simulations for the period 1900--2100, using CMIP5 historical and RCP8.5 emissions. Fifteen of these 25 coupled simulations now form a subset of the global projections provided for the UK Climate Projections 2018 (UKCP18). This first paper describes the selection of 25 variants (combinations of 47 parameters) using a set of cheap, coarser-resolution atmosphere-only simulations from a large sample of nearly 3000 variants. Retrospective 5-day weather forecasts run at climate resolution, and simulations of 2004--2009 with prescribed SST and sea ice are evaluated to filter out poor performance. We opted for a single design choice and sensitivity tests were done after the PPE was generated to demonstrate the effect of design choices on the filtering. Given our choice, only 38 of the parameter combinations were found to have acceptable performance at this stage. Idealised atmosphere-only simulations were then used to select the subset of 25 members that were as diverse as possible in terms of their CO2 and aerosol forcing, and their response to warmer SSTs. Using our parallel set of atmosphere-only and coupled PPEs (the latter from paper 2), we show that local biases in the atmosphere-only experiments are generally informative about the biases in the coupled PPE. Biases in radiative fluxes and cloud amounts are strongly informative for most regions, whereas this is only true for a smaller fraction of the globe for precipitation and dynamical variables. Therefore, the cheap experiments are an affordable way to search for promising parameter combinations but have limitations.}, added-at = {2021-05-11T10:31:38.000+0200}, author = {Sexton, David M. H. and McSweeney, Carol F. and Rostron, John W. and Yamazaki, Kuniko and Booth, Ben B. B. and Murphy, James M. and Regayre, Leighton and Johnson, Jill S. and Karmalkar, Ambarish V.}, biburl = {https://www.bibsonomy.org/bibtex/24bcb5ea6fc32c786e73c2c5dfe319fe0/pbett}, day = 06, description = {A perturbed parameter ensemble of HadGEM3-GC3.05 coupled model projections: part 1: selecting the parameter combinations | SpringerLink}, doi = {10.1007/s00382-021-05709-9}, interhash = {b07c12f638b97fe0dda9fb49d6db3bcd}, intrahash = {4bcb5ea6fc32c786e73c2c5dfe319fe0}, issn = {1432-0894}, journal = {Climate Dynamics}, keywords = {climate climatechange colleagues model ukcp}, month = may, timestamp = {2021-05-11T10:32:51.000+0200}, title = {A perturbed parameter ensemble of HadGEM3-GC3.05 coupled model projections: part 1: selecting the parameter combinations}, url = {https://doi.org/10.1007/s00382-021-05709-9}, year = 2021 }