Arnout J. Feijt

Validation of Cloud Liquid Water Path Retrievals from SEVIRI Using One Year of CloudNET Observations

Abstract The accuracy and precision are determined of cloud liquid water path (LWP) retrievals from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat-8 using 1 yr of LWP retrievals from microwave radiometer (MWR) measurements of two CloudNET stations in northern Europe. The MWR retrievals of LWP have a precision that is superior to current satellite remote sensing techniques, which justifies their use as validation data. The Cloud Physical Properties (CPP) algorithm of the Satellite Application Facility on Climate Monitoring (CM-SAF) is used to retrieve LWP from SEVIRI reflectances at 0.6 and 1.6 μm. The results show large differences in the accuracy and precision of LWP retrievals from SEVIRI between summer and winter. During summer, the instantaneous LWP retrievals from SEVIRI agree well with those from the MWRs. The accuracy is better than 5 g m−2 and the precision is better than 30 g m−2, which is similar to the precision of LWP retrievals from MWR. The added value of the 15...

Accuracy of Cloud Optical Depth Retrievals from Ground-Based Pyranometers

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 th...

Validation of a Physical Retrieval Scheme of Solar Surface Irradiances from Narrowband Satellite Radiances

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 o...

Ground-Based and Satellite Observations of Cloud Fields in the Netherlands

Abstract A study is performed on the combination of ground-based and satellite observations for the derivation of cloud properties. Ground-based measurements from a lidar ceilometer and an infrared radiometer were combined with measurements of the NOAA Advanced Very High Resolution Radiometer and Meteosat satellite instruments. Two case studies are presented: a case with streets of fair weather cumuli and a case with a weak cold front involving cumulus, stratus, and cirrus clouds. From the combination of ground-based and satellite observations, a much better description of the cloud field geometry, cloud base, and cloud top can be obtained than with satellite or ground-based observations alone. The combination of satellite retrievals and lidar-ceilometer measurements is promising. This concept is widely applicable because lidar ceilometers are available on airports all over the world and the used infrared sensors are relatively cheap and can easily be installed. This opens the way for a much improved auto...

Validation of liquid cloud property retrievals from SEVIRI using ground?based observations

Partly due to aerosol effects stratocumulus clouds vary considerably in liquid water path (LWP), geometrical thickness (h) and droplet number concentration (Nc). Cloud models have been developed to simulate h and Nc using satellite retrieved cloud optical thickness (?) and effective radius (re) values. In this paper we examine the consistency between LWP and h values inferred from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard METEOSAT-8. The use of METEOSAT-8 data means that time series of LWP and h can be validated at a 15-minute resolution, and used for examining the first indirect aerosol effect. For single-layered stratocumulus clouds the LWP and h retrievals from SEVIRI are compared to corresponding ground-based observations at two Cloudnet sites. A study on the sensitivity of the cloud model to the uncertainties in SEVIRI retrievals of ? and re reveals that h and Nc simulations are only accurate for clouds with effective radii larger than 5 ?m. The SEVIRI and ground-based retrievals of LWP and h show very good agreement, with accuracies of about 15 g m?2 and 20 m, respectively. This agreement could only be achieved by assuming sub-adiabatic profiles of droplet concentration and liquid water path in the cloud model. The degree of adiabaticity for single-layered stratocumulus clouds could be quantified by simultaneous analysis of SEVIRI and ground-based LWP and h values, which suggests that stratocumulus clouds over North Western Europe deviate, on average, from adiabatic clouds.

Validation of cloud parameter retrieval methods with objective ground based measurements

Abstract To understand and model the radiative transport in a cloudy atmosphere information on the cloud height and optical thickness is indispensable. Therefore retrieval techniques for cloud parameters are developed for the AVHRR, ATSR and the future MSG. Mainly synoptic observations are used for validation despite their subjective nature and varying quality. To validate advanced cloud parameter retrieval methods objective physical measurements are necessary. At KNMI retrieval methods of cloud fraction, cloud top temperature, optical thickness and LWP from AVHRR observations are developed. Much effort is put in building an infrastructure for validation. The retrieval methods are validated with a two-year data set from the KNMI Cloud Detection System (CDS). Detailed analysis is performed with observations from the CLARA-campaigns, when a number of advanced remote sensing and in-situ instruments were added to the CDS. The collocated lidar, radar, microwave radiometer and aircraft measurements from the CLARA data set allow for the evaluation of the assumptions in cloud parameter retrieval methods. Furthermore, the study presented here shows that combining measurements from lidar, radar and AVHRR provide information on cloud properties that cannot be retrieved from any of these instruments alone.

Cloud optical thickness retrieval from AVHRR data

The relation between the reflectivity of the atmosphere-surface system and the optical thickness of a homogeneous cloud layer in the atmosphere is investigated at 0.63 micrometer, which is the central wavelength of NOAA-AVHRR (advanced very high resolution radiometer) channel 1. A detailed radiative transfer model is employed, in which the multiple scattering and absorption resulting from cloud particles, molecules, aerosols, ozone and surface are fully taken into account. To estimate the sensitivity of the relation between atmospheric reflectivity and cloud optical thickness, the influence of variation of solar zenith angle, surface albedo, cloud particle effective radius and viewing geometry are examined. The relation between reflectivity and cloud optical thickness is mainly sensitive to solar zenith angle, surface albedo and viewing geometry. Therefore, these parameters have to be known for a retrieval of cloud optical thickness from reflectivity measurements. For actual retrievals, a database is prepared with atmospheric reflectivities for many solar zenith angles, viewing zenith angles, azimuth angles, surface albedos and cloud optical thicknesses. The retrieval method is applied to an AVHRR image of Sept 11, 1994. First results show a promising correlation with cloud optical thickness estimations from ground based measurements of direct solar irradiance.

Evaluation of the diurnal cycle of model predicted cloud properties using MSG‐SEVIRI observations

The evaluation of the diurnal cycle of cloud properties as predicted by climate models receives relatively little attention, mostly due to the lack of observational data. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the geostationary METEOSAT‐8 satellite is the first instrument able to provide accurate information on diurnal cycles during daylight hours of cloud properties over land and ocean surfaces. This paper evaluates the diurnal cycle of Cloud Amount (CA), Cloud Phase (CPH) and Condensed Water Path (CWP) as predicted by the Regional Atmospheric Climate Model (RACMO), using corresponding SEVIRI retrievals. The study is done for Europe using hourly cloud properties retrievals from SEVIRI during the summer of 2004.

On the Sensitivity of Satellite‐Derived Cloud Properties To Sensor Resolution and Broken Clouds

The sensitivity of cloud properties derived from meteorological imagers to sensor resolution is investigated by a comparison of results obtained from 1×1 km2 versus down‐sampled 3×3 km2 resolution MODIS reflectances. Focus is put on deviations caused by the plane‐parallel albedo bias for completely overcast, single‐phase pixels (67% of cloudy pixels), and by broken clouds (20% of cloudy pixels). For pixels corresponding to overcast water clouds, a low bias of −5.6% in cloud optical thickness and −3.8% in liqud water path is observed. A method to significantly reduce these biases is described, if information on unresolved variability in reflectance is available. For broken clouds, retrieval results are found to be rather unreliable. Again, a significant improvement in accuracy is achieved, if information on the sub‐pixel cloud fraction is used in the retrieval.

Assessment report on NRP subtheme “Atmospheric processes & UV-B radiation”

Abstract The atmosphere is a very complex, open, dynamic and multi-causal relation system in which non-linear processes and feedback mechanisms play an important role. Research within this subtheme in NRP-1 focused on uncertainties in our understanding of three issues i.o. o − the role of clouds and aerosols on the radiation budget − the role of atmospheric ozone in global change and the effect of atmospheric change on UV-B climatology − trophospheric budgets of non CO2 greenhouse gases These issues are being dealt with in 12 projects. On average good progress has been made in many of the projects and through there are some weaknesses, the overall quality of science and technological developments is good and in some cases even excellent in comparison to international standards. Links with international programmes such as IGBP, CEC, EUREKA/EUROTRAC are well established.