This paper describes Jacobian adaptation (JA) of acoustic models to environmental noise and its experimental evaluation. JA is based on a "noise adaptation" idea, which is acoustic model adaptation from initial noise A to target noise B , and uses Jacobian matrices to relate changes in environmental noise with changes in the "speech+noise" acoustic model. It is experimentally shown that JA performs well compared with existing techniques such as HMM composition, particularly when only a short sample (shorter than 1 sec) of the target noise is given, and that JA is very advantageous in terms of computational cost. Moreover, this paper describes JA used in combination with noise spectral subtraction and shows that improving SNR by spectral subtraction leads to higher efficiency.