Uncertainties in MODIS‐Based Cloud Liquid Water Path Retrievals at High Latitudes Due to Mixed‐Phase Clouds and Cloud Top Height Inhomogeneity

Abstract

Combined A-train remote sensing measurements from Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), CloudSat, and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) are used to study MODIS liquid water path (LWP) uncertainties at high latitudes. The focus is on quantifying uncertainties due to mixed-phase clouds and solar zenith angle-dependent bias, both of which disproportionately affect the MODIS data set in the polar regions. Multisensor LWP retrievals in stratiform mixed-phase clouds show that treating mixed-phase clouds as liquid clouds result in LWP bias that is related to the ice water path (IWP) on average and reaches close to 15% at IWP of 150 g/m 2 and can reach 40% or higher when IWP is greater than 400 g/m 2 . Moreover, A-train measurements and radiative transfer modeling are used to further understand the well-known yet unresolved solar zenith angle-dependent high bias in MODIS LWP. It is shown that the cloud top height variation is one of the main factors that contribute to this bias due to three-dimensional radiative interactions with cloud top inhomogeneity. Excluding only 0.5% of data points that show significant three-dimensional errors reduces the bias by 25 g/m 2 at solar zenith angle of 80°and improves agreement with the AMSR-E LWP trends. Three-dimensional radiative transfer simulations confirm that cloud top inhomogeneity is primarily responsible for the solar zenith angle-dependent LWP bias as observed by the MODIS measurements. This study provides a framework to guide future improvements of MODIS LWP data set, which is a key data source to constrain climate models.

Characteristics of Sea‐Effect Clouds and Precipitation Over the Sea of Japan Region as Observed by A‐Train Satellites

“…Uncertainty exists among the three retrieved water path products. Khanal and Wang (2018) found a 15-40% MODIS LWP bias for mixed-phase clouds.…”

“…Uncertainty exists among the three retrieved water path products. Khanal and Wang () found a 15–40% MODIS LWP bias for mixed‐phase clouds. AMSR‐E can be biased high compared to MODIS but is considered advantageous due to microwave emissions from liquid water being available throughout the column (Lebsock & Su, ).…”

Improvement of inorganic aerosol component in PM<sub>2.5</sub> by constraining aqueous-phase formation of sulfate in cloud with satellite retrievals: WRF-Chem simulations

“…the aqueous oxidation of S(IV) by HCHO and hydroxyl hydroperoxide (ISOPOOH) to form hydroxy-methane sulfonate (HMS) and sulfate (Moch et al, 2018;Dovrou et al, 2019), can also explain the sulfate underestimation even though the cloud water has already been corrected. In addition, cloud constraints are based on the MODIS LWP, which has been reported with an uncertainty range of ±30 % (Dong et al, 2008;Min et al, 2012;Khanal et al, 2018).…”

Arctic clouds in ECHAM6 and their sensitivity to cloud microphysics and surface fluxes

“…As most precipitation in higher latitudes is formed by the aforementioned process, a higher ice content should lead to the dissipation of clouds, as can be seen in the rather rapid transition from the cloudy to the clear state that is often observed in the Arctic (Morrison et al, 2011). Previously, Klaus et al (2012) explored the sensitivity of cloud microphysical properties in a single column setup of the regional Arctic climate model HIRHAM5, which also uses the physical parametrizations of ECHAM. They modified several commonly used microphysical tuning parameters and only a stronger WBF process and a more effective collection of cloud droplets by snow were able to reduce the liquid water content.…”

“…Due to this strong variation in γ thr for different horizontal resolutions and due to the fact that it is one of the few parameters that is able to reduce the liquid water content of clouds in the Arctic (Klaus et al, 2012), we will now explore how the sensitivity of cloud cover and cloud phase reacts to changes in γ thr . Lower values of γ thr increase the effectiveness of the WBF process, leading to less cloud water but more cloud ice to be present.…”