Appendix 1: Salvo Combat Models for Surface Warfare

Abstract

The modelling conducted to examine the balance of power in ASuW is laid out in brief here. This appendix will be of use for readers attempting to replicate the authors’ findings or to test hypotheses with their own input data. The logic of modelling a single salvo exchange is described below. The campaign analysis allowed each party a set number of salvos depending on information advantage – NATO secures the first salvo in an offensive posture, for example. These assumptions depend on the authors’ qualitative analysis and are exogenous to the model, which can be tested with different assumptions. To examine the balance of power on the ocean surface, the authors used two stylised salvo combat models derived from the work of Wayne Hughes. The first model examines the risk to assets at the GIUK Gap posed by long-range strike assets, such as the Backfire bomber and the MIG-31K, as well as SSGN-launched P-800 Oniks missiles. The second examines an engagement closer to the Russian bastion in which a NATO CSG backed by two surface action groups – 13 vessels in all – confronts the surface forces of the Northern Fleet. The latter model is useful for examining whether NATO can support missions such as SEAD against the Kola Peninsula using carrier-enabled power projection. Sorties by NATO airborne strike assets are treated as part of its salvos, with munitions loads multiplied by sortie rates. This is consistent with previous work on battles in the Pacific theatre in which airborne sorties were incorporated into the salvo combat model. For the first model, the authors assume that Russian OTH targeting can provide the location of any given vessel with an uncertainty of 20 km. Based on this, Russian combat aviation and MPAs can conduct sorties to provide more granular data or Russian anti-access capabilities can be ‘fired blind’ to saturate the area of uncertainty. The lethality of Russian forces under conditions of information advantage, such as when they have granular targeting information, can be calculated using two adaptations of Hughes’s original models, an