Comparing ERA-Interim clouds with satellite observations using a simplified satellite simulator

Abstract

Abstract. An evaluation of the ERA-Interim clouds using satellite observations is presented. To facilitate such an evaluation in a proper way, a simplified satellite simulator has been developed and applied to 6-hourly ERA-Interim reanalysis data covering the period of 1982 to 2014. The simulator converts modelled cloud fields, for example those of the ERA-Interim reanalysis, to simulated cloud fields by accounting for specific characteristics of passive imaging satellite sensors such as the Advanced Very High Resolution Radiometer (AVHRR), which form the basis of many long-term observational datasets of cloud properties. It is attempted to keep the simulated cloud fields close to the original modelled cloud fields to allow a quality assessment of the latter based on comparisons of the simulated clouds fields with the observations. Applying the simulator to ERA-Interim data, this study firstly focuses on the spatial distribution and frequency of clouds (total cloud fraction) and on their vertical position, using cloud-top pressure to express the cloud fraction of high-level, mid-level and low-level clouds. Furthermore, the cloud-top thermodynamic phase is investigated. All comparisons incorporate knowledge of systematic uncertainties in the satellite observations and are further stratified by accounting for the limited sensitivity of the observations to clouds with very low cloud optical thickness (COT). The comparisons show that ERA-Interim cloud fraction is generally too low nearly everywhere on the globe except in the polar regions. This underestimation is caused by a lack of mid-level and/or low-level clouds, for which the comparisons only show a minor sensitivity to the cloud optical thickness thresholds applied. The amount of ERA-Interim high-level clouds, being higher than in the observations, agrees with the observations within their estimated uncertainties. Removing the optically very thin clouds (COT <0.15) from the model fields improves the agreement with the observations for high-level cloud fraction locally (e.g. in the tropics), while for the mid-latitude regions, the best agreement for high-level cloud fraction is found when removing all clouds with COT <1.0. Comparisons of the cloud thermodynamic phase at the cloud top reveal a too high relative ice cloud frequency in ERA-Interim, being most pronounced in the higher latitudes. Indications are found that this is due to the suppression of liquid cloud occurrence for temperatures below −23 ∘C in ERA-Interim. The application of this simulator facilitates a more effective use of passive satellite observations of clouds in the evaluation of modelled cloudiness, for example in reanalyses.

An evaluation of cloud vertical structure in three reanalyses against CloudSat/cloud‐aerosol lidar and infrared pathfinder satellite observations

“…The situation is not getting much better for numerical weather models in spite of finer resolution and advanced assimilation system. For example, Stengel et al, () points out that the total cloud cover in ERA‐Interim is generally too low nearly everywhere on the globe except in polar‐regions. Naud et al , () found cloud fraction is slightly underestimated over the southern oceans for ERA‐Interim, but severely underestimated for MERRA.…”

Cloud_cci Advanced Very High Resolution Radiometer post meridiem (AVHRR-PM) dataset version 3: 35-year climatology of global cloud and radiation properties

“…As described in this paper, version 3 of the Cloud_cci AVHRR-PM dataset has been generated (and linked to a DOI; Stengel et al, 2019). In addition to cloud properties, this new version extends the product portfolio by BOA and TOA broadband radiative fluxes and covers the time period 1982 to 2016.…”

“…For the presented dataset (Cloud_cci AVHRR-PMv3), a DOI has been issued: https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V003 (Stengel et al, 2019). The landing page points to additional documentation and data download sites.…”

The Cloud_cci simulator v1.0 for the Cloud_cci climate data record and its application to a global and a regional climate model

“…However, the simulated Cloud_cci differs from MODIS since, for consistency with the Cloud_cci CDR, the simulator uses the same cloud particle models as used in Cloud_cci retrievals (McGarragh et al, 2018), and they differ from those used in the MODIS retrievals. Liquid water path (LWP) and ice water path are calculated from the simulated τ c and r e in the same manner as for the Cloud_cci CDR which follows Stephens (1978). The cloud albedo is derived from look-up tables as a function of simulated r e and τ c , and the solar zenith angle.…”