Reconstruction of high resolution time series from slow-response broadband solar and terrestrial irradiance measurements by deconvolution

Abstract

Abstract. Broadband solar and terrestrial irradiance measurements of high temporal resolution are needed to study inhomogeneous clouds or surfaces and to derive vertical profiles of heating/cooling rates at cloud top. An efficient method to enhance the temporal resolution of slow-response measurements of broadband irradiance using pyranometer or pyrgeometer is introduced. It is based on the deconvolution theorem of Fourier transform to restore amplitude and phase shift of high frequent fluctuations. It is shown that the quality of reconstruction depends on the instrument noise, the pyrgeometer response time and the frequency of the oscillations. The method is tested in laboratory measurements for synthetic time series including a boxcar function and periodic oscillations using a CGR-4 pyrgeometer with response time of 3 s. The originally slow-response pyrgeometer data were reconstructed to higher resolution and compared to the predefined synthetic time series. The reconstruction of the time series worked up to oscillations of 0.5 Hz frequency and 2 W m−2 amplitude if the sampling frequency of the data acquisition is 16 kHz or higher. For oscillations faster than 2 Hz the instrument noise exceeded the reduced amplitude of the oscillations in the measurements and the reconstruction failed. The method was applied to airborne measurements of upward terrestrial irradiance from the VERDI (Vertical Distribution of Ice in Arctic Clouds) field campaign. Pyrgeometer data above open leads in sea ice and a broken cloud field were reconstructed and compared to KT19 infrared thermometer data. The reconstruction of amplitude and phase shift of the deconvoluted data improved the agreement with the KT19 data. Cloud top temperatures were improved by up to 1 K above broken clouds while an underestimation of 2.5 W m−2 was found for the upward irradiance over small leads when using the slow-response data. The limitations of the method with respect to instrument noise and digitalization of measurements by the data acquisition are discussed.