A statistical distribution commonly used for describing measured wind speed data is the Weibull distribution. A review of the methods found in the statistical literature for the purpose of estimation of the parameters in Weibull distributions is given, with a special emphasis on the efficiency of the different methods. From this review, the most appropriate method for a given application can be chosen. The general conclusion is that maximum likelihood estimators should be used due to their large sample efficiency. However, they require an iterative minimization. The recommended closed form estimators when there are few observations (say, less than 25) are the least-squares estimators. If wind speed data with a good speed resolution are available, the closed form ten fractile estimators are very good. The simplest are the two fractile estimators. They, however, require around three times as many observations as the maximum likelihood estimators in order to be of the same accuracy. If mean and stan... Abstract A statistical distribution commonly used for describing measured wind speed data is the Weibull distribution. A review of the methods found in the statistical literature for the purpose of estimation of the parameters in Weibull distributions is given, with a special emphasis on the efficiency of the different methods. From this review, the most appropriate method for a given application can be chosen. The general conclusion is that maximum likelihood estimators should be used due to their large sample efficiency. However, they require an iterative minimization. The recommended closed form estimators when there are few observations (say, less than 25) are the least-squares estimators. If wind speed data with a good speed resolution are available, the closed form ten fractile estimators are very good. The simplest are the two fractile estimators. They, however, require around three times as many observations as the maximum likelihood estimators in order to be of the same accuracy. If mean and stan...