Christophe Sturm

Process-evaluation of tropospheric humidity simulated by general circulation models using water vapor isotopologues: 1. Comparison between models and observations

The goal of this study is to determine how H2O and HDO measurements in water vapor can be used to detect and diagnose biases in the representation of processes controlling tropospheric humidity in atmospheric general circulation models (GCMs). We analyze a large number of isotopic data sets (four satellite, sixteen ground-based remote-sensing, five surface in situ and three aircraft data sets) that are sensitive to different altitudes throughout the free troposphere. Despite significant differences between data sets, we identify some observed HDO/H2O characteristics that are robust across data sets and that can be used to evaluate models. We evaluate the isotopic GCM LMDZ, accounting for the effects of spatiotemporal sampling and instrument sensitivity. We find that LMDZ reproduces the spatial patterns in the lower and mid troposphere remarkably well. However, it underestimates the amplitude of seasonal variations in isotopic composition at all levels in the subtropics and in midlatitudes, and this bias is consistent across all data sets. LMDZ also underestimates the observed meridional isotopic gradient and the contrast between dry and convective tropical regions compared to satellite data sets. Comparison with six other isotope-enabled GCMs from the SWING2 project shows that biases exhibited by LMDZ are common to all models. The SWING2 GCMs show a very large spread in isotopic behavior that is not obviously related to that of humidity, suggesting water vapor isotopic measurements could be used to expose model shortcomings. In a companion paper, the isotopic differences between models are interpreted in terms of biases in the representation of processes controlling humidity. Copyright

Comprehensive Dynamical Models of Global and Regional Water Isotope Distributions

Water isotope tracers can be included in comprehensive atmospheric models and can provide deeper insight to isotope distributions than simple physically-based isotope models or statistical methods because of their ability to resolve the underlying processes of interest. Within such models, isotope tracers follow normal “prognostic” water, and differ only in that fractionation is applied during surface evaporation and transpiration, cloud condensation processes, exchange between falling raindrops and environmental air, and when there are any extra water sources. The details of the mass balance that underlies modeling isotopes and the key processes can be represented in models are examined to illuminate how it is the compilation of many simple aspects which give rise to a comprehensive model. One particular advantage of dynamical isotope models is their ability to account for mixing of air masses by resolved larger-scale transport and by smaller scale parameterized turbulence. While the output from comprehensive dynamical isotope models is useful for subsequent applications, adequate accounting for model error is needed. In the past, few observations have been available to validate isotopic models, especially for vapor which is the model state variable of importance, and validating models remains a limitation. Nonetheless, comprehensive models are valuable in mapping water isotope distributions in vapor and precipitation. They are also well suited to diagnostic studies in which model sensitivity tests expose the physical basis for the final isotopic signal. This type of analysis is invaluable in guiding the interpretation of isotopic observations.