Modelling water isotopes using a global non-hydrostatic model with explicit convection scheme

Abstract

<p>The stable water isotopes (SWIs) (δ<sup>18</sup>O and δD) are used as an indicator of the intensity of the atmospheric hydrological cycle due to their large variability in time and space. SWIs are used for investigating the model’s bias and uncertainty. In this study, we developed a new global storm-resolving model equipped with SWIs (NICAM-WISO). We applied the new model to conduct three current climate simulations using a single-moment cloud microphysics scheme, without any convection parameterization scheme: CTRL, LRES, and HRES. These simulations used the same physical process but at a different horizontal resolution (LRES, 224 km; CTRL, 56 km; HRES, 14 km). We conducted the simulations on the supercomputer Fugaku. CTRL reproduced the seasonal means of the atmospheric hydrological cycle, as well as precipitation isotopic ratios. However, all simulation results have three types of biases. First, in tropical ocean regions, the model had a negative bias in precipitation isotopic ratios; this was caused by a negative bias in vapor isotopic ratios for the middle troposphere, which resulted from excess condensation biases during upward transportation and high-frequency deep convection. Second, all simulations overestimated precipitation isotopic ratios in the East Asia summer monsoon region due to low precipitation in the region caused by a shift in the moisture convergence zone from eastern China to the western Pacific Ocean. Third, in cold continental regions such as Siberia, Greenland, and Antarctica, the model had a positive bias in precipitation isotopic ratios due to a moisture bias and a low temperature effect; these regions also had a large positive bias in terms of precipitation deuterium excess. A particularly large bias was observed in ice clouds with low ice water content, indicating uncertainties in the vapor deposition process. Together, these results suggest that stable water isotopes are helpful for identifying biases associated with cloud microphysics and the atmospheric hydrological cycle. The unique constraints of stable water isotopes revealed cloud microphysics uncertainty and biases in the hydrological simulations.</p>