Abstract. Several sets of reference regions have been used in the literature for the regional synthesis of observed and modelled climate and climate change information. A popular example is the series of reference regions used in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Adaptation (SREX). The SREX regions were slightly modified for the Fifth Assessment Report of the IPCC and used for reporting subcontinental observed and projected changes over a reduced number (33) of climatologically consistent regions encompassing a representative number of grid boxes. These regions are intended to allow analysis of atmospheric data over broad land or ocean regions and have been used as the basis for several popular spatially aggregated datasets, such as the Seasonal Mean Temperature and Precipitation in IPCC Regions for CMIP5 dataset. We present an updated version of the reference regions for the analysis of new observed and simulated datasets (including CMIP6) which offer an opportunity for refinement due to the higher atmospheric model resolution. As a result, the number of land and ocean regions is increased to 46 and 15, respectively, better representing consistent regional climate features. The paper describes the rationale for the definition of the new regions and analyses their homogeneity. The regions are defined as polygons and are provided as coordinates and a shapefile together with companion R and Python notebooks to illustrate their use in practical problems (e.g. calculating regional averages). We also describe the generation of a new dataset with monthly temperature and precipitation, spatially aggregated in the new regions, currently for CMIP5 and CMIP6, to be extended to other datasets in the future (including observations). The use of these reference regions, dataset and code is illustrated through a worked example using scatter plots to offer guidance on the likely range of future climate change at the scale of the reference regions. The regions, datasets and code (R and Python notebooks) are freely available at the ATLAS GitHub repository: https://github.com/SantanderMetGroup/ATLAS (last access: 24 August 2020), https://doi.org/10.5281/zenodo.3998463 (Iturbide et al., 2020).

[1] The Sr/Ca ratio of coral aragonite is used to reconstruct past sea surface temperature (SST). Twentyone laboratories took part in an interlaboratory study of coral Sr/Ca measurements. Results show interlaboratory bias can be significant, and in the extreme case could result in a range in SST estimates of 7 C. However, most of the data fall within a narrower range and the Porites coral reference material JCp-1 is now characterized well enough to have a certified Sr/Ca value of 8.838 mmol/mol with an expanded uncertainty of 0.089 mmol/mol following International Association of Geoanalysts (IAG) guidelines. This uncertainty, at the 95% confidence level, equates to 1.5 C for SST estimates using Porites, so is approaching fitness for purpose. The comparable median within laboratory error is <0.5 C. This difference in uncertainties illustrates the interlaboratory bias component that should be reduced through the use of reference materials like the JCp-1. There are many potential sources contributing to biases in comparative methods but traces of Sr in Ca standards and uncertainties in reference solution composition can account for half of the combined uncertainty. Consensus values that fulfil the requirements to be certified values were also obtained for Mg/Ca in JCp-1 and for Sr/Ca and Mg/Ca ratios in the JCt-1 giant clam reference material. Reference values with variable fitness for purpose have also been obtained for Li/Ca, B/Ca, Ba/Ca, and U/Ca in both reference materials. In future, studies reporting coral element/Ca data should also report the average value obtained for a reference material such as the JCp-1.

Accurate projections of future temperature and precipitation patterns in many regions of the world depend on quantifying anthropogenic signatures in tropical Pacific climate against its rich background of natural variability. However, the detection of anthropogenic signatures in the region is hampered by the lack of continuous, century-long instrumental climate records. This study presents coral-based sea surface temperature (SST) and salinity proxy records from Palmyra Island in the central tropical Pacific over the twentieth century, based on coral strontium/calcium and the oxygen isotopic composition of seawater (d