TY - JOUR
T1 - Automated classification of simulated wind field patterns from multiphysics ensemble forecasts
AU - Durán, Pablo
AU - Basu, Sukanta
AU - Meißner, Cathérine
AU - Adaramola, Muyiwa S.
PY - 2020
Y1 - 2020
N2 - In this study, we have proposed an automated classification approach to identify meaningful patterns in wind field data. Utilizing an extensive simulated wind database, we have demonstrated that the proposed approach can identify low-level jets, near-uniform profiles, and other patterns in a reliable manner. We have studied the dependence of these wind profile patterns on locations (eg, offshore vs onshore), seasons, and diurnal cycles. Furthermore, we have found that the probability distributions of some of the patterns depend on the underlying planetary boundary layer schemes in a significant way. The future potential of the proposed approach in wind resource assessment and, more generally, in mesoscale model parameterization improvement is touched upon in this paper.
AB - In this study, we have proposed an automated classification approach to identify meaningful patterns in wind field data. Utilizing an extensive simulated wind database, we have demonstrated that the proposed approach can identify low-level jets, near-uniform profiles, and other patterns in a reliable manner. We have studied the dependence of these wind profile patterns on locations (eg, offshore vs onshore), seasons, and diurnal cycles. Furthermore, we have found that the probability distributions of some of the patterns depend on the underlying planetary boundary layer schemes in a significant way. The future potential of the proposed approach in wind resource assessment and, more generally, in mesoscale model parameterization improvement is touched upon in this paper.
KW - low-level jets
KW - mesoscale modeling
KW - neural networks
KW - planetary boundary layer
KW - self-organizing maps
KW - vertical wind profile
UR - http://www.scopus.com/inward/record.url?scp=85078626174&partnerID=8YFLogxK
U2 - 10.1002/we.2462
DO - 10.1002/we.2462
M3 - Article
AN - SCOPUS:85078626174
SN - 1095-4244
VL - 23
SP - 898
EP - 914
JO - Wind Energy
JF - Wind Energy
IS - 4
ER -