Forecasting surface layer atmospheric parameters at the LBT site

Abstract

In this paper we quantify the performances of an automated weather forecast system implemented on the Large Binocular Telescope (LBT) site at Mt. Graham (Arizona) in forecasting the main atmospheric parameters close to the ground. The system employs a mesoscale non-hydrostatic numerical model (Meso-Nh). To validate the model we compare the forecasts of wind speed, wind direction, temperature and relative humidity close to the ground with the respective values measured by instrumentation installed on the telescope dome. The study is performed over a large sample of nights uniformly distributed over two years. The quantitative analysis is done using classical statistical operators (bias, RMSE and $\sigma$) and contingency tables, which allows to extract complementary key information, such as the percentage of correct detection (PC) and the probability to obtain a correct detection within a defined interval of values (POD). Results of our study indicate that the model performances in forecasting the atmospheric parameters we have just cited are very good, in some cases excellent: RMSE for temperature is below 1° C, for relative humidity is 14%, for the wind speed is around 2.5m/s. The relative error of the RMSE for wind direction varies from 9% to 17% depending on the wind speed conditions. This work is performed in the context of ALTA (Advanced LBT Turbulence and Atmosphere) Center project, which final goal is to provide forecasts of all the atmospheric parameters and the optical turbulence to support LBT observations, adaptive optics facilities and interferometric facilities.

http://academic.oup.com/mnras/article/466/2/1925/2917962/Forecasting-surface-layer-atmospheric-parameters 22 pages, 16 figures, 21 tables

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• FAST: A software suite for automatic weather and optical turbulence forecast on ground-based telescope sites