arXiv subjects

Detlef Stammer

Publications and source records attributed to Detlef Stammer.

2 recordsLinked to original sources

arXiv2024

Local and Remote Forcing Factors of Heatwave in India -A Reanalysis and Adjoint model based study

Continental heatwaves can dramatically impact ecosystems and societies, e.g., by leading to excess mortality, wildfires, and harvest failures. With a warming climate, their impacts potentially intensify globally, but the Indian subcontinent appears to be particularly vulnerable to such extreme events. In this study, we use reanalysis and the adjoint of the atmospheric model, PlaSim, to identify drivers of heatwaves occurring April and May over north-central India. Reanalysis results suggest that the existence of high temperatures in the study region is highly sensitive to the low local soil moisture which is observed weeks before a heatwave commences. Soil moisture variability in northern India is influenced by moisture transport from the west during winter--spring. Preceding dry soil moisture conditions can be associated with a `persistent jet' conditions linked to atmospheric dynamical changes in the North Atlantic region. An associated northward shift in the upper tropospheric zonal wind occurs approximately a month prior to the heatwaves, influencing the area and intensity of western disturbances embedded in the jet stream. This weakens the moisture flow from the north of the Arabian Sea, further reducing soil moisture levels and creating conditions conducive to heatwaves. An adjoint sensitivity analysis and forward model perturbation experiments confirm the causal relationships for the proposed heatwave development mechanism over north-central India, identifying the remote influence of North Atlantic sea surface temperature variability on extreme temperatures in India. Our findings highlight the complex interplay of local and remote factors in heatwave development over India.

physics.ao-ph↗

arXiv2024

Long-window tandem variational data assimilation methods for chaotic climate models tested with the Lorenz 63 system

4D-variational data assimilation is applied to the Lorenz '63 model to introduce a new method for parameter estimation in chaotic climate models. The approach aims to optimise an Earth system model (ESM), for which no adjoint exists, by utilising the adjoint of a different, potentially simpler ESM. This relies on the synchronisation of the model to observed data. Dynamical state and parameter estimation (DSPE) is used to stabilise the tangent linear system by reducing all positive Lyapunov exponents to negative values, thereby improving parameter estimation by enabling long assimilation windows. The method introduces a second layer of synchronisation between the two models, with and without an adjoint, to facilitate linearisation around the trajectory of the model for which no adjoint exists. This is achieved by synchronising two Lorenz '63 systems, one with and the other without an adjoint model. Results are presented for an idealised case of identical, perfect models and for a more realistic case in which they differ from one another. If employed on a high-resolution ESM for which a coarse resolution adjoint exists, the method will save computational resources as only one forward run with the full high-resolution ESM per iteration is needed. It is demonstrated that there is negligible error and uncertainty change compared to the traditional optimisation of a full ESM with an adjoint. Stemming from this approach, it is shown that the synchronisation between two identical models can be used to filter noisy data in a dynamical way which reduces the parametric uncertainty of the optimised model by approximately one third. Such a precision gain could prove valuable for seasonal, annual, and decadal predictions.

physics.ao-ph↗