Engineering topics

Ulrich Salzmann

Publications and source records attributed to Ulrich Salzmann.

3 records

NASA NTRS2023

Highly Restricted Near‐Surface Permafrost Extent During the Mid-Pliocene Warm Period

To better understand how near‐surface permafrost may respond to future warming, we explore the equilibrium spatial extent of near‐surface permafrost during the mid-Pliocene warm period (mPWP), which shares characteristics of the projected future climate. Our simulations, which are constrained by proxy records, suggest highly restricted near‐surface permafrost extent during the mPWP, akin to future large-scale permafrost degradation projections of our model for the end of this century. Our study indicates dramatically smaller-than-present near‐surface permafrost extent in the geological past under climate conditions analogous to those expected if global warming continues unabated. This absence in permafrost will come with critical implications for the global carbon cycle, human livelihoods and infrastructures, and surface and subsurface hydrology.

near‐surface permafrost↗

NASA NTRS2022

Multi-variate Factorisation of Numerical Simulations

Factorisation is widely used in the analysis of numerical simulations. It allows changes in properties of a system to be attributed to changes in multiple variables associated with that system. There are many possible factorisation methods; here we discuss three previously-proposed factorisations that have been applied in the field of climate modelling: the linear factorisation, the Stein and Alpert (1993) factorisation, and the Lunt et al (2012) factorisation. We show that, when more than two variables are being considered, none of these three methods possess all three properties of "uniqueness", "symmetry", and "completeness". Here, we extend each of these factorisations so that they do possess these properties for any number of variables, resulting in three factorisations – the "linear-sum" factorisation, the "shared-interaction" factorisation, and the "scaled-total" factorisation. We show that the linear-sum factorisation and the shared-interaction factorisation reduce to be identical. We present the results of the factorisations in the context of studies that used the previously-proposed factorisations. This reveals that only the linear-sum/shared-interaction factorisation possesses a fourth property – "boundedness", and as such we recommend the use of this factorisation in applications for which these properties are desirable.

Numerican simulations↗

NASA NTRS2021

Multi-Variate Factorisation of Numerical Simulations

Factorisation (also known as “factor separation”) is widely used in the analysis of numerical simulations. It allows changes in properties of a system to be attributed to changes in multiple variables associated with that system. There are many possible factorisation methods; here we discuss three previously proposed factorisations that have been applied in the field of climate modelling: the linear factorisation, the Stein and Alpert (1993) factorisation, and the Lunt et al. (2012) factorisation. We show that, when more than two variables are being considered, none of these three methods possess all four properties of “uniqueness”, “symmetry”, “completeness”, and “purity”. Here, we extend each of these factorisations so that they do possess these properties for any number of variables, resulting in three factorisations – the “linear-sum” factorisation, the “shared-interaction” factorisation, and the “scaled-residual” factorisation. We show that the linear-sum factorisation and the shared-interaction factorisation reduce to be identical in the case of four or fewer variables, and we conjecture that this holds for any number of variables. We present the results of the factorisations in the context of three past studies that used the previously proposed factorisations.

Numerical simulations↗