Search

This paper presents the operational cloud retrieval algorithms for the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Space Agency Sentinel-5 Precursor (S5P) mission scheduled for launch in 2017. Two algorithms working in tandem are used for retrieving cloud properties: OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks). OCRA retrieves the cloud fraction using TROPOMI measurements in the ultraviolet (UV) and visible (VIS) spectral regions, and ROCINN retrieves the cloud top height (pressure) and optical thickness (albedo) using TROPOMI measurements in and around the oxygen A-band in the near infrared (NIR). Cloud parameters from TROPOMI/S5P will be used not only for enhancing the accuracy of trace gas retrievals but also for extending the satellite data record of cloud information derived from oxygen A-band measurements, a record initiated with the Global Ozone Monitoring Experiment (GOME) on board the second European Remote-Sensing Satellite (ERS-2) over 20 years ago. The OCRA and ROCINN algorithms are integrated in the S5P operational processor UPAS (Universal Processor for UV/VIS/NIR Atmospheric Spectrometers), and we present here UPAS cloud results using the Ozone Monitoring Instrument (OMI) and GOME-2 measurements. In addition, we examine anticipated challenges for the TROPOMI/S5P cloud retrieval algorithms, and we discuss the future validation needs for OCRA and ROCINN. [ABSTRACT FROM AUTHOR]

We use observations of surface and top-of-the-atmosphere (TOA) broadband radiation fluxes determined from the Atmospheric Radiation Measurement programme mobile facility, the Geostationary Earth Radiation Budget (GERB) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) instruments and a range of meteorological variables at a site in the Sahel to test the ability of the ECMWF Integrated Forecasting System cycle 43r1 to describe energy budget variability. The model has daily average biases of -12 and 18W m-2 for outgoing longwave and reflected shortwave TOA radiation fluxes, respectively. At the surface, the daily average bias is 12(13)W m-2 for the longwave downwelling (upwelling) radiation flux and -21(-13)W m-2 for the shortwave downwelling (upwelling) radiation flux. Using multivariate linear models of observation-model differences, we attribute radiation flux discrepancies to physical processes, and link surface and TOA fluxes. We find that model biases in surface radiation fluxes are mainly due to a low bias in ice water path (IWP), poor description of surface albedo and model-observation differences in surface temperature. We also attribute observed discrepancies in the radiation fluxes, particularly during the dry season, to the misrepresentation of aerosol fields in the model from use of a climatology instead of a dynamic approach. At the TOA, the low IWP impacts the amount of reflected shortwave radiation while biases in outgoing longwave radiation are additionally coupled to discrepancies in the surface upwelling longwave flux and atmospheric humidity. [ABSTRACT FROM AUTHOR]

A strong diurnal variation of aerosol has been observed in many heavily polluted regions in China. This variation could affect the direct aerosol radiative forcing (DARF) evaluation if the daily averaged value is used as normal rather than the time-resolved values. To quantify the effect of using the daily averaged DARF, 196 days of high temporal resolution ground-based data collected in SKYNET Hefei site during the period from 2007 to 2013 is used to perform an assessment. We demonstrate that strong diurnal changes of heavy aerosol loading have an impact on the 24-haveraged DARF when daily averaged optical properties are used to retrieve this quantity. The DARF errors varying from - 7.6 to 15.6 W m-2 absolutely and from 0.1 to 28.5 % relatively were found between the calculations using daily aver-age aerosol properties, and those using time-resolved aerosol observations. These errors increase with increasing daily aerosol optical depth (AOD) and decreasing daily single-scattering albedo (SSA), indicating that the high temporal resolution DARF data set should be used in the model instead of the normal daily-averaged one, especially under heavy aerosol loading conditions for regional campaign studies. We also found that statistical errors (0.3 W m-2 absolutely and 11.8 % relatively) will be less, which means that the effect of using the daily averaged DARF can be weakened by using a long-term observational data set. [ABSTRACT FROM AUTHOR]

The article presents a study which examines the vertical profile of the snow's specific surface area (SSA) and density at Dome C and Dumont D'Urville in Antarctica. The study assesses the infrared (IR) reflectance of snow at 1310 nanometers using the dual-frequency integrating sphere for snow (DUFISS) system. It is found out that the vertical profile of SSA and density can be used in calculating the spectral albedo of the snow for several illumination conditions.