1041 / 2024-09-20 09:36:40
Comparing and Evaluating Nudging for Simulating Precipitation and Oxygen Isotopes in iCAM6 Model
iCAM6,Nudging,Monsoon
Session 53 - Geological analogues for future warm ocean and climate
Abstract Accepted
The classic explanation of monsoon region precipitation isotopes is Dansgaard's (1964) "amount effect", which describes a negative relationship between oxygen isotopes in tropical precipitation and local rainfall. Speleothem oxygen isotopes from monsoon regions have long been interpreted using this theory. However, recent studies suggest that the "amount effect" alone cannot fully account for variations in precipitation isotopes, other studies have shown other processes to be important: circulation changes, upstream rainout, sources composition, source location and so on. Thus, clarifying the distribution of precipitation isotopes in monsoon regions is essential.
Numerical modeling is a powerful tool for interpreting climate signals across various timescales and provides robust evidence for the mechanisms driving these signals. Nudging, a continuous data assimilation method, adjusts the model state toward observations by adding new terms proportional to the difference between the model and observations into the prognostic equations. In this study, we will conduct several nudging experiments using the iCAM6 model and compare the results with modern precipitation isotope observations to reduce biases in simulated precipitation and oxygen isotope.
The objective is to improve the reliability of model interpretations of rainfall and precipitation isotopes, providing a direct basis for paleoclimate proxy interpretation. Ultimately, this will establish a foundation for future research on decoding precipitation isotope signals in the East Asian monsoon region and understanding the climate implications of these variations.
Numerical modeling is a powerful tool for interpreting climate signals across various timescales and provides robust evidence for the mechanisms driving these signals. Nudging, a continuous data assimilation method, adjusts the model state toward observations by adding new terms proportional to the difference between the model and observations into the prognostic equations. In this study, we will conduct several nudging experiments using the iCAM6 model and compare the results with modern precipitation isotope observations to reduce biases in simulated precipitation and oxygen isotope.
The objective is to improve the reliability of model interpretations of rainfall and precipitation isotopes, providing a direct basis for paleoclimate proxy interpretation. Ultimately, this will establish a foundation for future research on decoding precipitation isotope signals in the East Asian monsoon region and understanding the climate implications of these variations.