cloud property retrieval using synergistic AATSR and MERIS observations

A newly developed daytime cloud property retrieval algorithm FAME-C (Freie Universität Berlin AATSR MERIS Cloud) is presented. Synergistic observations from AATSR and MERIS, both mounted on the polar orbiting satellite ENVISAT, are used for cloud screening. For cloudy pixels two main steps are carried out in a sequential form. First, a micro-physical cloud property retrieval is performed using an AATSR near-infrared and visible channel. Cloud phase, cloud optical thickness, and effective radius are retrieved, and subsequently cloud water path is computed. Second, two independent cloud top height products are retrieved. For cloud top temperature AATSR brightness temperatures are used, while for cloud top pressure the MERIS oxygen-A absorption channel is used. Results from the micro-physical retrieval serve as input for the two cloud top height retrievals. Introduced are the AATSR and MERIS forward models and auxiliary data needed in FAME-C. Also, the optimal estimation method with uncertainty estimates, which also provides for uncertainty estimated of the retrieved property on a pixel-basis, is presented. Within the frame of the ESA Climate Change Initiative project first global cloud property retrievals have been conducted for the years 2007–2009. For this time period verification efforts are presented comparing FAME-C cloud micro-physical properties to MODIS-TERRA derived cloud micro-physical properties for four selected regions on the globe. The results show reasonable accuracies between the cloud micro- physical retrievals. Biases are generally smallest for marine stratocumulus clouds; −0.28, 0.41μm and −0.18 g m−2 for cloud optical thickness, effective radius and cloud water path, respectively. This is also true for the root mean square error. Also, both cloud top height products are compared to cloud top heights derived from ground-based cloud radars located at several ARM sites. FAME-C mostly shows an underestimation of cloud top heights when compared to radar observations, which is partly attributed to the difficulty of accurate cloud property retrievals for optically thin clouds and multi-layer clouds. The bias is smallest, −0.9 km, for AATSR derived cloud top heights for single- layer clouds

FAME-C: cloud property retrieval using synergistic AATSR and MERIS observations

A newly developed daytime cloud property retrieval algorithm, FAME-C (Freie Universität Berlin AATSR MERIS Cloud), is presented. Synergistic observations from the Advanced Along-Track Scanning Radiometer (AATSR) and the Medium Resolution Imaging Spectrometer (MERIS), both mounted on the polar-orbiting Environmental Satellite (Envisat), are used for cloud screening. For cloudy pixels two main steps are carried out in a sequential form. First, a cloud optical and microphysical property retrieval is performed using an AATSR near-infrared and visible channel. Cloud phase, cloud optical thickness, and effective radius are retrieved, and subsequently cloud water path is computed. Second, two cloud top height products are retrieved based on independent techniques. For cloud top temperature, measurements in the AATSR infrared channels are used, while for cloud top pressure, measurements in the MERIS oxygen-A absorption channel are used. Results from the cloud optical and microphysical property retrieval serve as input for the two cloud top height retrievals. Introduced here are the AATSR and MERIS forward models and auxiliary data needed in FAME-C. Also, the optimal estimation method, which provides uncertainty estimates of the retrieved property on a pixel basis, is presented. Within the frame of the European Space Agency (ESA) Climate Change Initiative (CCI) project, the first global cloud property retrievals have been conducted for the years 2007–2009. For this time period, verification efforts are presented, comparing, for four selected regions around the globe, FAME-C cloud optical and microphysical properties to cloud optical and microphysical properties derived from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite. The results show a reasonable agreement between the cloud optical and microphysical property retrievals. Biases are generally smallest for marine stratocumulus clouds: −0.28, 0.41 μm and −0.18 g m−2 for cloud optical thickness, effective radius and cloud water path, respectively. This is also true for the root-mean-square deviation. Furthermore, both cloud top height products are compared to cloud top heights derived from ground-based cloud radars located at several Atmospheric Radiation Measurement (ARM) sites. FAME-C mostly shows an underestimation of cloud top heights when compared to radar observations. The lowest bias of −0.3 km is found for AATSR cloud top heights for single-layer clouds, while the highest bias of −3.0 km is found for AATSR cloud top heights for multilayer clouds. Variability is low for MERIS cloud top heights for low-level clouds, and high for MERIS cloud top heights for mid-level and high-level single-layer clouds, as well as for both AATSR and MERIS cloud top heights for multilayer clouds

Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud_cci project

New cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS are presented. Two retrieval systems were developed that include components for cloud detection and cloud typing followed by cloud property retrievals based on the optimal estimation (OE) technique. The OE-based retrievals are applied to simultaneously retrieve cloud-top pressure, cloud particle effective radius and cloud optical thickness using measurements at visible, near-infrared and thermal infrared wavelengths, which ensures spectral consistency. The retrieved cloud properties are further processed to derive cloud-top height, cloud-top temperature, cloud liquid water path, cloud ice water path and spectral cloud albedo. The Cloud_cci products are pixel-based retrievals, daily composites of those on a global equal-angle latitude–longitude grid, and monthly cloud properties such as averages, standard deviations and histograms, also on a global grid. All products include rigorous propagation of the retrieval and sampling uncertainties. Grouping the orbital properties of the sensor families, six datasets have been defined, which are named AVHRR-AM, AVHRR-PM, MODIS-Terra, MODIS-Aqua, ATSR2-AATSR and MERIS+AATSR, each comprising a specific subset of all available sensors. The individual characteristics of the datasets are presented together with a summary of the retrieval systems and measurement records on which the dataset generation were based. Example validation results are given, based on comparisons to well-established reference observations, which demonstrate the good quality of the data. In particular the ensured spectral consistency and the rigorous uncertainty propagation through all processing levels can be considered as new features of the Cloud_cci datasets compared to existing datasets. In addition, the consistency among the individual datasets allows for a potential combination of them as well as facilitates studies on the impact of temporal sampling and spatial resolution on cloud climatologies.</p><p class="p">For each dataset a digital object identifier has been issued:</p><p class="p">Cloud_cci AVHRR-AM: <a href="https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-AM/V002" target="_blank">https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-AM/V002</a></p><p class="p">Cloud_cci AVHRR-PM: <a href="https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V002" target="_blank">https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V002</a></p><p class="p">Cloud_cci MODIS-Terra: <a href="https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Terra/V002" target="_blank">https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Terra/V002</a></p><p class="p">Cloud_cci MODIS-Aqua: <a href="https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Aqua/V002" target="_blank">https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Aqua/V002</a></p><p class="p">Cloud_cci ATSR2-AATSR: <a href="https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V002" target="_blank">https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V002</a></p><p class="p">Cloud_cci MERIS+AATSR: <a href="https://doi.org/10.5676/DWD/ESA_Cloud_cci/MERIS+AATSR/V002" target="_blank">https://doi.org/10.5676/DWD/ESA_Cloud_cci/MERIS+AATSR/V002</a