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- Author or Editor: A. van Lammeren x
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Abstract
Errors in cloud optical depth retrieved from pyranometer irradiances are estimated using a fractal model of cloud inhomogeneity. The cloud field is constructed from a two-dimensional array of pixels. For each of the pixels, which are 200 × 200 m2 in size, the radiative transfer is calculated using the independent pixel approximation. If cloud cover is 100%, the retrieval bias can be positive or negative for individual 10-min averaged transmittances, depending on the position of cloud inhomogeneities with respect to the pyranometer. The mean bias is always negative. Increasing the averaging time to 40 min reduces the scatter in the bias, although the mean bias remains −1.0, a value that depends on the choice of fractal model. If cloud cover is less than 100%, but there is no independent means to omit partly cloudy periods from the irradiance records, the negative retrieval bias will increase with reduced cloud cover and optical depth. Below optical depths of 5, the retrieval errors are so large that no meaningful results are obtained despite the fact that retrievals may appear to be reasonable. The simulations herein cannot take account of three-dimensional photon transport. The results of this study demonstrate that it is essential to measure cloud fraction and the variability of the cloud structure if optical depth is to be retrieved from pyranometer observations. Extra instruments recommended for ground-based remote sensing of cloud optical depth are a cloud lidar, powerful enough to probe the entire troposphere, and a microwave radiometer to measure the total column liquid water.
Abstract
Errors in cloud optical depth retrieved from pyranometer irradiances are estimated using a fractal model of cloud inhomogeneity. The cloud field is constructed from a two-dimensional array of pixels. For each of the pixels, which are 200 × 200 m2 in size, the radiative transfer is calculated using the independent pixel approximation. If cloud cover is 100%, the retrieval bias can be positive or negative for individual 10-min averaged transmittances, depending on the position of cloud inhomogeneities with respect to the pyranometer. The mean bias is always negative. Increasing the averaging time to 40 min reduces the scatter in the bias, although the mean bias remains −1.0, a value that depends on the choice of fractal model. If cloud cover is less than 100%, but there is no independent means to omit partly cloudy periods from the irradiance records, the negative retrieval bias will increase with reduced cloud cover and optical depth. Below optical depths of 5, the retrieval errors are so large that no meaningful results are obtained despite the fact that retrievals may appear to be reasonable. The simulations herein cannot take account of three-dimensional photon transport. The results of this study demonstrate that it is essential to measure cloud fraction and the variability of the cloud structure if optical depth is to be retrieved from pyranometer observations. Extra instruments recommended for ground-based remote sensing of cloud optical depth are a cloud lidar, powerful enough to probe the entire troposphere, and a microwave radiometer to measure the total column liquid water.
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.
Clouds cause uncertainties in the determination of climate sensitivity to either natural or anthropogenic changes. Furthermore, clouds dominate our perception of the weather, and the relatively poor forecast of cloud and precipitation parameters in numerical weather prediction (NWP) models is striking. In order to improve modeling and forecasting of clouds in climate and NWP models the BALTEX BRIDGE Campaign (BBC) was conducted in the Netherlands in August/September 2001 as a contribution to the main field experiment of the Baltic Sea Experiment (BALTEX) from April 1999 to March 2001 (BRIDGE). The complex cloud processes, which involve spatial scales from less than 1 mm (condensation nuclei) to 1000 km (frontal systems) require an integrated measurement approach. Advanced remote sensing instruments were operated at the central facility in Cabauw, Netherlands, to derive the vertical cloud structure. A regional network of stations was operated within a 100 km × 100 km domain to observe solar radiation, cloud liquid water path, cloud-base temperature, and height. Aircraft and tethered balloon measurements were used to measure cloud microphysical parameters and solar radiation below, in, and above the cloud. Satellite measurements complemented the cloud observations by providing the spatial structure from above. In order to better understand the effect of cloud inhomogeneities on the radiation field, three-dimensional radiative transfer modeling was closely linked to the measurement activities. To evaluate the performance of dynamic atmospheric models for the cloudy atmosphere four operational climate and NWP models were compared to the observations. As a first outcome of BBC we demonstrate that increased vertical resolution can improve the representation of clouds in these models.
Clouds cause uncertainties in the determination of climate sensitivity to either natural or anthropogenic changes. Furthermore, clouds dominate our perception of the weather, and the relatively poor forecast of cloud and precipitation parameters in numerical weather prediction (NWP) models is striking. In order to improve modeling and forecasting of clouds in climate and NWP models the BALTEX BRIDGE Campaign (BBC) was conducted in the Netherlands in August/September 2001 as a contribution to the main field experiment of the Baltic Sea Experiment (BALTEX) from April 1999 to March 2001 (BRIDGE). The complex cloud processes, which involve spatial scales from less than 1 mm (condensation nuclei) to 1000 km (frontal systems) require an integrated measurement approach. Advanced remote sensing instruments were operated at the central facility in Cabauw, Netherlands, to derive the vertical cloud structure. A regional network of stations was operated within a 100 km × 100 km domain to observe solar radiation, cloud liquid water path, cloud-base temperature, and height. Aircraft and tethered balloon measurements were used to measure cloud microphysical parameters and solar radiation below, in, and above the cloud. Satellite measurements complemented the cloud observations by providing the spatial structure from above. In order to better understand the effect of cloud inhomogeneities on the radiation field, three-dimensional radiative transfer modeling was closely linked to the measurement activities. To evaluate the performance of dynamic atmospheric models for the cloudy atmosphere four operational climate and NWP models were compared to the observations. As a first outcome of BBC we demonstrate that increased vertical resolution can improve the representation of clouds in these models.
The Baltic Sea Experiment (BALTEX) is one of the five continental-scale experiments of the Global Energy and Water Cycle Experiment (GEWEX). More than 50 research groups from 14 European countries are participating in this project to measure and model the energy and water cycle over the large drainage basin of the Baltic Sea in northern Europe. BALTEX aims to provide a better understanding of the processes of the climate system and to improve and to validate the water cycle in regional numerical models for weather forecasting and climate studies. A major effort is undertaken to couple interactively the atmosphere with the vegetated continental surfaces and the Baltic Sea including its sea ice. The intensive observational and modeling phase BRIDGE, which is a contribution to the Coordinated Enhanced Observing Period of GEWEX, will provide enhanced datasets for the period October 1999–February 2002 to validate numerical models and satellite products. Major achievements have been obtained in an improved understanding of related exchange processes. For the first time an interactive atmosphere–ocean–land surface model for the Baltic Sea was tested. This paper reports on major activities and some results.
The Baltic Sea Experiment (BALTEX) is one of the five continental-scale experiments of the Global Energy and Water Cycle Experiment (GEWEX). More than 50 research groups from 14 European countries are participating in this project to measure and model the energy and water cycle over the large drainage basin of the Baltic Sea in northern Europe. BALTEX aims to provide a better understanding of the processes of the climate system and to improve and to validate the water cycle in regional numerical models for weather forecasting and climate studies. A major effort is undertaken to couple interactively the atmosphere with the vegetated continental surfaces and the Baltic Sea including its sea ice. The intensive observational and modeling phase BRIDGE, which is a contribution to the Coordinated Enhanced Observing Period of GEWEX, will provide enhanced datasets for the period October 1999–February 2002 to validate numerical models and satellite products. Major achievements have been obtained in an improved understanding of related exchange processes. For the first time an interactive atmosphere–ocean–land surface model for the Baltic Sea was tested. This paper reports on major activities and some results.
