SearcharxivSearch

arXiv · 2111.06720

Importance of the advection scheme for the simulation of water isotopes over Antarctica by atmospheric general circulation models: A case study for present-day and Last Glacial Maximum with LMDZ-iso

Abstract

Atmospheric general circulation models (AGCMs) are known to have a warm and isotopically enriched bias over Antarctica. We test here the hypothesis that these biases are partly consequences of a too diffusive advection. Exploiting the LMDZ-iso model, we show that a less diffusive representation of the advection, especially on the horizontal, is very important to reduce the bias in the isotopic contents of precipitation above this area. The choice of an appropriate representation of the advection is thus essential when using GCMs for paleoclimate applications based on polar water isotopes. Too much diffusive mixing along the poleward transport leads to overestimated isotopic contents in water vapor because dehydration by mixing follows a more enriched path than dehydration by Rayleigh distillation. The near-air surface temperature is also influenced, to a lesser extent, by the diffusive properties of the advection scheme directly via the advection of the air and indirectly via the radiative effects of changes in high cloud fraction and water vapor. A too diffusive horizontal advection increases the temperature and so also contributes to enrich the isotopic contents of water vapor over Antarctica through a reduction of the distillation. The temporal relationship, from Last Glacial Maximum (LGM) to present-day conditions, between the mean annual near-air surface temperature and the water isotopic contents of precipitation for a specific location can also be impacted, with significant consequences on the paleo-temperature reconstruction from observed changes in water isotopes.

Explore related subjects

Keep this discovery

BibTeXRIS

Alexandre Cauquoin, Camille Risi, Étienne Vignon. 2021-11-12. Importance of the advection scheme for the simulation of water isotopes over Antarctica by atmospheric general circulation models: A case study for present-day and Last Glacial Maximum with LMDZ-iso. https://doi.org/10.1016/j.epsl.2019.115731

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Windowed Envelope Statistics for Time-Domain Significant Wave Height Estimation From HF Radar

Significant wave height (SWH) retrieval from high-frequency (HF) radar typically relies on a weak second-order Doppler continuum that is sensitive to noise, interference, and spectral leakage. This letter presents a Windowed Envelope Statistics Estimator (WESE) that operates directly on beam-formed time-domain voltages. A second-order term obtained from a Neumann expansion of the rough-surface field equation motivates quadratic compensation of localized radar features. WESE extracts the mean, standard deviation, or variance from overlapping windows of the in-phase, quadrature, or envelope-magnitude sequence, followed by quadratic compensation, rank ordering, least-squares regression, and causal smoothing. Evaluation used 335 synchronized hourly observations from a 13.385 MHz, 12-element WERA system at Argentia, Newfoundland and Labrador. The optimal configuration used quadrature variance, a 16-sample window, 896 retained chronological samples, and 30-h smoothing, achieving an RMSE of 0.152 m and a Pearson correlation of 0.978. This represents RMSE reductions of 32.1% and 18.7% relative to previously reported linear and second-order compensated ordered-statistics models, respectively. The results demonstrate robust time-domain SWH estimation without explicit Doppler-spectrum construction.

physics.ao-ph

KiloDA: Reconstructing kilometer-scale near-surface wind states from sparse station observations

Accurate kilometer-scale near-surface winds are important for understanding atmospheric processes over complex terrain, yet remain difficult to reconstruct from sparse and unevenly distributed observations. Here we introduce KiloDA, a diffusion framework for hourly kilometer-scale wind reconstruction from surface stations. KiloDA learns the statistical distribution and spatial structure of wind fields from historical 3-km Weather Research and Forecasting (WRF) model forecasts. At each reconstruction time, no contemporaneous WRF field is used. Instead, station observations provide the only constraints on the current atmospheric state and guide posterior sampling from the learned prior. In idealized WRF experiments, KiloDA recovers localized wind structures when only 0.24% of grid cells are observed and shows an overall advantage over conventional interpolation across terrain conditions and wind speed regimes. This capability largely transfers to real observations. In a fully withheld region, KiloDA reduces the median wind speed root mean square error (RMSE) by 19% relative to ERA5 reanalysis, using only observations outside the region, with the largest improvements over high-elevation and high-relief terrain. A random station holdout further confirms that this advantage extends across different complex-terrain locations and holdout configurations. These results show that historical model archives can provide useful structural knowledge for reconstructing kilometer-scale wind fields from sparse observations without requiring an accurate model estimate of the current atmospheric state.

physics.ao-ph