Search Results
Abstract
An algorithm is presented to derive the downwelling solar surface irradiance from satellite measurements of the 0.63-μm reflectance, which explicitly accounts for variations in cloud optical depth and integrated water vapor. For validation, a long-term dataset of 40 356 pyranometer measurements and 1450 NOAA-14 Advanced Very High Resolution Radiometer (AVHRR) satellite scenes of the Netherlands is used. A mean overestimate of the satellite-retrieved irradiance by 7% is found, which is consistent with numerous other studies reporting positive biases of atmospheric transmissivities that are calculated by radiative transfer schemes in comparison with measurements. The bias can be explained by the calibration and measurement uncertainties of both the AVHRR and pyranometer. A strong solar zenith angle dependence of the bias is found when water clouds are assumed in the retrieval. Such a dependence is not observed for ice clouds. Currently, there is not enough information for a conclusive explanation of this behavior. Comparing individual pyranometer measurements at 30 stations within a region of about 150 km2 averaged over 40 min, a large rmse of 86 W m−2 is found. If the average of all of the stations for a satellite overpass is considered instead, a much better accuracy is achieved (rmse of 33 W m−2). For monthly averages of all of the stations, the rmse is further reduced to 12 W m−2. Evidence is presented that suggests that a significant fraction of the rmse in the comparison originates from the variability of the irradiance field, which limits the representativeness of the reference ground-based pyranometer measurements for the satellite-retrieved values.
Abstract
An algorithm is presented to derive the downwelling solar surface irradiance from satellite measurements of the 0.63-μm reflectance, which explicitly accounts for variations in cloud optical depth and integrated water vapor. For validation, a long-term dataset of 40 356 pyranometer measurements and 1450 NOAA-14 Advanced Very High Resolution Radiometer (AVHRR) satellite scenes of the Netherlands is used. A mean overestimate of the satellite-retrieved irradiance by 7% is found, which is consistent with numerous other studies reporting positive biases of atmospheric transmissivities that are calculated by radiative transfer schemes in comparison with measurements. The bias can be explained by the calibration and measurement uncertainties of both the AVHRR and pyranometer. A strong solar zenith angle dependence of the bias is found when water clouds are assumed in the retrieval. Such a dependence is not observed for ice clouds. Currently, there is not enough information for a conclusive explanation of this behavior. Comparing individual pyranometer measurements at 30 stations within a region of about 150 km2 averaged over 40 min, a large rmse of 86 W m−2 is found. If the average of all of the stations for a satellite overpass is considered instead, a much better accuracy is achieved (rmse of 33 W m−2). For monthly averages of all of the stations, the rmse is further reduced to 12 W m−2. Evidence is presented that suggests that a significant fraction of the rmse in the comparison originates from the variability of the irradiance field, which limits the representativeness of the reference ground-based pyranometer measurements for the satellite-retrieved values.
Abstract
A method is presented to obtain droplet concentration for water clouds from ground-based remote sensing observations. It relies on observations of cloud thickness, liquid water path, and optical extinction near the cloud base. The method was tested for two case studies (19 April 1996 and 4 September 1996) during the Clouds And Radiation experiment (CLARA). The CLARA experiment was designed to observe clouds using a variety of remote sensing instruments near the city of Delft in the western part of the Netherlands. The measurement of cloud thickness is dependent on the detection of cloud base by lidar and cloud top by radar. It is shown that during CLARA it was possible to detect cloud base with an uncertainty of less than 30 m using current lidar techniques. The agreement between in situ and remote sensing observations of droplet concentration was reasonable. An error analysis indicates that this method is most sensitive to uncertainties in liquid water path and the unknown effects of multiple scattering on lidar signal returns. When the liquid water path is very small the relative error of the liquid water path increases to unacceptable levels, so that the retrieval of droplet concentration becomes very difficult. The estimated uncertainty in the strength of multiple scattering can explain differences between observations and retrievals of droplet concentration on one day, but not the other.
Abstract
A method is presented to obtain droplet concentration for water clouds from ground-based remote sensing observations. It relies on observations of cloud thickness, liquid water path, and optical extinction near the cloud base. The method was tested for two case studies (19 April 1996 and 4 September 1996) during the Clouds And Radiation experiment (CLARA). The CLARA experiment was designed to observe clouds using a variety of remote sensing instruments near the city of Delft in the western part of the Netherlands. The measurement of cloud thickness is dependent on the detection of cloud base by lidar and cloud top by radar. It is shown that during CLARA it was possible to detect cloud base with an uncertainty of less than 30 m using current lidar techniques. The agreement between in situ and remote sensing observations of droplet concentration was reasonable. An error analysis indicates that this method is most sensitive to uncertainties in liquid water path and the unknown effects of multiple scattering on lidar signal returns. When the liquid water path is very small the relative error of the liquid water path increases to unacceptable levels, so that the retrieval of droplet concentration becomes very difficult. The estimated uncertainty in the strength of multiple scattering can explain differences between observations and retrievals of droplet concentration on one day, but not the other.
