The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) is a two-wavelength polarization lidar that performs global profiling of aerosols and clouds in the troposphere and lower stratosphere. CALIOP is the primary instrument on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite, which has flown in formation with the NASA A-train constellation of satellites since May 2006. The global, multiyear dataset obtained from CALIOP provides a new view of the earth's atmosphere and will lead to an improved understanding of the role of aerosols and clouds in the climate system. A suite of algorithms has been developed to identify aerosol and cloud layers and to retrieve a variety of optical and microphysical properties. CALIOP represents a significant advance over previous space lidars, and the algorithms that have been developed have many innovative aspects to take advantage of its capabilities. This paper provides a brief overview of the CALIPSO mission, the CALIOP instrument and data products, and an overview of the algorithms used to produce these data products.
The current cloud thermodynamic phase discrimination by Cloud-Aerosol Lidar Pathfinder Satellite Observations (CALIPSO) is based on the depolarization of backscattered light measured by its lidar [Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP)]. It assumes that backscattered light from ice crystals is depolarizing, whereas water clouds, being spherical, result in minimal depolarization. However, because of the relationship between the CALIOP field of view (FOV) and the large distance between the satellite and clouds and because of the frequent presence of oriented ice crystals, there is often a weak correlation between measured depolarization and phase, which thereby creates significant uncertainties in the current CALIOP phase retrieval. For water clouds, the CALIOP-measured depolarization can be large because of multiple scattering, whereas horizontally oriented ice particles depolarize only weakly and behave similarly to water clouds. Because of the nonunique depolarization–cloud phase relationship, more constraints are necessary to uniquely determine cloud phase. Based on theoretical and modeling studies, an improved cloud phase determination algorithm has been developed. Instead of depending primarily on layer-integrated depolarization ratios, this algorithm differentiates cloud phases by using the spatial correlation of layer-integrated attenuated backscatter and layer-integrated particulate depolarization ratio. This approach includes a two-step process: 1) use of a simple two-dimensional threshold method to provide a preliminary identification of ice clouds containing randomly oriented particles, ice clouds with horizontally oriented particles, and possible water clouds and 2) application of a spatial coherence analysis technique to separate water clouds from ice clouds containing horizontally oriented ice particles. Other information, such as temperature, color ratio, and vertical variation of depolarization ratio, is also considered. The algorithm works well for both the 0.3° and 3° off-nadir lidar pointing geometry. When the lidar is pointed at 0.3° off nadir, half of the opaque ice clouds and about one-third of all ice clouds have a significant lidar backscatter contribution from specular reflections from horizontally oriented particles. At 3° off nadir, the lidar backscatter signals for roughly 30% of opaque ice clouds and 20% of all observed ice clouds are contaminated by horizontally oriented crystals.
[1] The CALIOP depolarization measurements, combined with backscatter intensity measurements, are effective in discriminating between water clouds and ice clouds. The same depolarization measurements can also be used for estimating liquid water content information. Using cloud temperature information from the collocated infrared imaging radiometer measurements and cloud water paths from collocated MODIS measurements, this study compiles global statistics of the occurrence frequency, liquid water content, liquid water path, and their temperature dependence. For clouds with temperatures between −40°C and 0°C, the liquid phase fractions and liquid water paths are significantly higher than the ones from previous studies using passive remote sensing measurements. At midlatitudes, the occurrence of liquid phase clouds at temperatures between −40°C and 0°C depends jointly on both cloud height and cloud temperature. At high latitudes, more than 95% of low-level clouds with temperatures between −40°C and 0°C are water clouds. Supercooled water clouds are mostly observed over ocean near the storm-track regions and high-latitude regions. Supercooled water clouds over land are observed in the Northern Hemisphere over Europe, East Asia, and North America, and these are the supercooled water clouds with highest liquid water contents. The liquid water content of all supercooled water clouds is characterized by a Gamma (G) distribution. The mode values of liquid water content are around 0.06 g/m 3 and are independent of cloud temperature. For temperatures warmer than −15°C, mean value of the liquid water content is around 0.14 g/m 3 . As the temperature decreases, the mean cloud liquid water content also decreases. These results will benefit cloud models and cloud parameterizations used in climate models in improving their ice-phase microphysics parameterizations and the aviation hazard forecast.Citation: Hu, Y., S. Rodier, K. Xu, W. Sun, J. Huang, B. Lin, P. Zhai, and D. Josset (2010), Occurrence, liquid water content, and fraction of supercooled water clouds from combined CALIOP/IIR/MODIS measurements,
[1] Summertime Tibetan dust aerosol plumes are detected from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. CALIPSO reveals that dust storms occur more frequently than previously found from Tibetan surface observations because few surface sites were available over remote northwestern Tibet due to high elevation and harsh climate. The Tibetan dust aerosol is characterized by column-averaged volume depolarization and total volume color ratios around 21% and 0.83, respectively. The dust layers appear most frequently around 4 -7 km above mean sea level. The volume depolarization ratio for about 90% of the dust particles is less than 10% at low altitudes (3 -5 km), while only about 50% of the particles have a greater depolarization ratio at higher altitudes (7-10 km). The 4-day back trajectory analyses show that these plumes probably originate from the nearby Taklamakan desert surface and accumulate over the northern slopes of the Tibetan Plateau. These dust outbreaks can affect the radiation balance of the atmosphere of Tibet because they both absorb and reflect solar radiation. Citation:
[1] The semi-direct effects of dust aerosols are analyzed over eastern Asia using 2 years (June 2002 to June 2004 The results show that the water path of dust-contaminated clouds is considerably smaller than that of dust-free clouds. The mean ice water path (IWP) and liquid water path (LWP) of dusty clouds are less than their dust-free counterparts by 23.7% and 49.8%, respectively. The long-term statistical relationship derived from ISCCP also confirms that there is significant negative correlation between dust storm index and ISCCP cloud water path (CWP). These results suggest that dust aerosols warm clouds, increase the evaporation of cloud droplets and further reduce the CWP, the so-called semi-direct effect. The semi-direct effect may play a role in cloud development over arid and semi-arid areas of East Asia and contribute to the reduction of precipitation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.