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A versatile system for processing geostationary satellite data with run-time visualization capability

To better predict global climate change, scientists are developing climate models that require interdisciplinary and collaborative efforts in their building. We are currently involved in several such projects but will briefly discuss activities in support of two such complementary projects: the Atmospheric Radiation Measurement (ARM) program of the Department of Energy and Sequoia 2000, a joint venture of the University of California, the private sector, and government agencies. Our contribution to the ARM program is to investigate the role of clouds on the top of the atmosphere and on surface radiance fields through the data analysis of surface and satellite observations and complex modeling of the interaction of radiation with clouds. One of our first ARM research activities involves the computation of the broadband shortwave surface irradiance from satellite observations. Geostationary satellite images centered over the first ARM observation site are received hourly over the Internet network and processed in real time to compute hourly and daily composite shortwave irradiance fields. The images and the results are transferred via a high-speed network to the Sequoia 2000 storage facility in Berkeley, where they are archived These satellite-derived results are compared with the surface observations to evaluate the accuracy of the satellite estimate and the spatial representation of the surface observations. In developing the software involved in calculating the surface shortwave irradiance, we have produced an environment whereby we can easily modify and monitor the data processing as required. Through the principles of modular programming, we have developed software that is easily modified as new algorithms for computation are developed or input data availability changes. In addition, the software was designed so that it could be run from an interactive, icon-driven, graphical interface, TCL-TK, developed by Sequoia 2000 participants. In this way, the data flow can be interactively assessed and altered as needed. In this environment, the intermediate data processing 'images' can be viewed, enabling the investigator to easily monitor the various data processing steps as they progress. Additionally, this environment allows the rapid testing of new processing modules and allows their effects to be visually compared with previous results.

Landsfeld, M.↗

CALIPSO-Inferred Aerosol Direct Radiative Effects: Bias Estimates Using Ground-Based Raman Lidars

Observational constraints on the change in the radiative energy budget caused by the presence of aerosols, i.e. the aerosol direct radiative effect (DRE), have recently been made using observations from the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO). CALIPSO observations have the potential to provide improved global estimates of aerosol DRE compared to passive sensor-derived estimates due to CALIPSO's ability to perform vertically-resolved aerosol retrievals over all surface types and over cloud. In this study we estimate the uncertainties in CALIPSO-inferred aerosol DRE using multiple years of observations from the Atmospheric Radiation Measurement (ARM) program's Raman lidars (RL) at midlatitude and tropical sites. Examined are assumptions about the ratio of extinction-to-backscatter (i.e. the lidar ratio) made by the CALIPSO retrievals, which are needed to retrieve the aerosol extinction profile. The lidar ratio is shown to introduce minimal error in the mean aerosol DRE at the top-of-atmosphere and surface. It is also shown that CALIPSO is unable to detect all radiatively-significant aerosol, resulting in an underestimate in the magnitude of the aerosol DRE by 30-50%. Therefore, global estimates of the aerosol DRE inferred from CALIPSO observations are likely too weak.

Thorsen, Tyler↗

CALIPSO-Inferred Aerosol Direct Radiative Effects: Bias Estimates Using Ground-Based Raman Lidars

Observational constraints on the change in the radiative energy budget caused by the presence of aerosols, i.e. the aerosol direct radiative effect (DRE), have recently been made using observations from the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO). CALIPSO observations have the potential to provide improved global estimates of aerosol DRE compared to passive sensor-derived estimates due to CALIPSO's ability to perform vertically-resolved aerosol retrievals over all surface types and over cloud. In this study we estimate the uncertainties in CALIPSO-inferred aerosol DRE using multiple years of observations from the Atmospheric Radiation Measurement (ARM) program's Raman lidars (RL) at mid-latitude and tropical sites. Examined are assumptions about the ratio of extinction-to-backscatter (i.e. the lidar ratio) made by the CALIPSO retrievals, which are needed to retrieve the aerosol extinction profile. The lidar ratio is shown to introduce minimal error in the mean aerosol DRE at the top-of-atmosphere and surface. It is also shown that CALIPSO is unable to detect all radiatively-significant aerosol, resulting in an underestimate in the magnitude of the aerosol DRE by 30â€"50%. Therefore, global estimates of the aerosol DRE inferred from CALIPSO observations are likely too weak.

Thorsen, Tyler↗

Evaluation of CloudSat Radiative Kernels Using ARM and CERES Observations and ERA5 Reanalysis

Despite the widespread use of the radiative kernel technique for studying radiative feedbacks and radiative forcings, there has not been any systematic, observation-based validation of the radiative kernel method. Here, we utilize observed and reanalyzed radiative fluxes and atmospheric profiles from the Atmospheric Radiation Measurement (ARM) program and ERA5 reanalysis to assess a set of observation-based radiative kernels from CloudSat for six ARM sites. The CloudSat radiative kernels, convoluted with the ERA5 state variables, can almost perfectly reconstruct the monthly anomalies of shortwave (SW) and longwave (LW) radiative fluxes in ERA5 at the surface (SFC) and top-of atmosphere (TOA) with correlations significantly being greater than 0.95. The biases of kernel-estimated flux anomalies calculated using the ARM-observed state variables can be more than twice as large when compared with the ARM-observed surface flux anomalies and Clouds and Earth’s Radiant Energy System (CERES) observed anomalies at the TOA. Generally, clouds contribute to most (>60%) of the variance of flux anomalies at Southern Great Plain (SGP), Tropical Western Pacific (TWP), and Eastern North Atlantic (ENA), and surface albedo dominates (>69%) the variance of SW flux anomalies at North Slope of Alaska (NSA). The radiative kernels exhibit the lowest correlation (r~[0.55,0.85]) when reconstructing SFC LW flux anomalies at SGP, TWP, and ENA, whose biases are related to the possibility that the kernels may not fully capture the characteristics 47 associated with MJO and ENSO at TWP and the presence of clouds at SGP and ENA.

Radiative kernels↗

The Continuous Intercomparison of Radiation Codes (CIRC): Phase I Cases

CIRC aspires to be the successor to ICRCCM (Intercomparison of Radiation Codes in Climate Models). It is envisioned as an evolving and regularly updated reference source for GCM-type radiative transfer (RT) code evaluation with the principle goal to contribute in the improvement of RT parameterizations. CIRC is jointly endorsed by DOE's Atmospheric Radiation Measurement (ARM) program and the GEWEX Radiation Panel (GRP). CIRC's goal is to provide test cases for which GCM RT algorithms should be performing at their best, i.e, well characterized clear-sky and homogeneous, overcast cloudy cases. What distinguishes CIRC from previous intercomparisons is that its pool of cases is based on observed datasets. The bulk of atmospheric and surface input as well as radiative fluxes come from ARM observations as documented in the Broadband Heating Rate Profile (BBHRP) product. BBHRP also provides reference calculations from AER's RRTM RT algorithms that can be used to select the most optimal set of cases and to provide a first-order estimate of our ability to achieve radiative flux closure given the limitations in our knowledge of the atmospheric state.

Oreopoulos, Lazaros↗

Aerosol analysis techniques and results from micro pulse lidar

The effect of clouds and aerosol on the atmospheric energy balance is a key global change problem. Full knowledge of aerosol distributions is difficult to obtain by passive sensing alone. Aerosol and cloud retrievals in several important areas can be significantly improved with active remote sensing by lidar. Micro Pulse Lidar (MPL) is an aerosol and cloud profilometer that provides a detailed picture of the vertical structure of boundary layer and elevated dust or smoke plume aerosols. MPL is a compact, fully eyesafe, ground-based, zenith pointing instrument capable of full-time, long-term unattended operation at 523 nm. In October of 1993, MPL began taking full-time measurements for the Atmospheric Radiation Measurement (ARM) program at its Southern Great Plains (SGP) site and has since expanded to ARM sites in the Tropical West Pacific (TWP) and the North Slope of Alaska (NSA). Other MPL's are moving out to some of the 60 world-wide Aerosol Robotic Network (AERONET) sites which are already equipped with automatic sun-sky scanning spectral radiometers providing total column optical depth measurements. Twelve additional MPL's have been purchased by NASA to add to the aerosol and cloud database of the EOS ground validation network. The original MPL vertical resolution was 300 meters but the newer versions have a vertical resolution of 30 meters. These expanding data sets offer a significant new resource for atmospheric radiation analysis. Under the direction of Jim Spinhirne, the MPL analysis team at NASA/GSFC has developed instrument correction and backscatter analysis techniques for ARM to detect cloud boundaries and analyze vertical aerosol structures. A summary of MPL applications is found in Hlavka (1997). With the aid of independent total column optical depth instruments such as the Multifilter Rotating Shadowband Radiometer (MFRSR) at the ARM sites or sun photometers at the AERONET sites, the MPL data can be calibrated, and time-resolved vertical profiles of aerosol optical depth as well as aerosol extinction can be calculated. The techniques used to calibrate the lidar, calculate the aerosol extinction-to-backscatter ratio, and produce profiles of aerosol extinction and aerosol optical depths, will be described. Results using these techniques will be presented for case studies at the ARM site in the Tropical West Pacific and later in the Southern Great Plains.

Hlavka, Dennis L.↗

Nighttime Cirrus Detection using Atmospheric Infrared Sounder Window Channels and Total Column Water Vapor

A method of cirrus detection at nighttime is presented that utilizes 3.8 and 10.4 (micro)m infrared (IR) window brightness temperature differences (dBT) and total column precipitable water (PW) measurements. This technique is applied to the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit A (AMSU-A) instrument suite on board EOS-Aqua, where dBT is determined from sets of carefully selected AIRS window channels, while PW is derived from the synergistic AIRS and AMSU-A water vapor retrievals. Simulated and observed dBT for a particular value of PW are not constant; several physical factors impact dBT, including the variability in temperature and relative humidity profiles, surface emissivity, instrument noise, and skin/ near-surface air temperature differences. We simulate clear-sky dBT over a realistic range of PWs using 8350 radiosondes that have varying temperature and relative humidity profiles. Thresholds between cloudy and uncertain sky conditions are derived once the scatter in the clear-sky dBT is determined. Simulations of optically thin cirrus indicate that this technique is most sensitive to cirrus optical depth in the 10 (micro)m window of 0.1-0.15 or greater over the tropical and subtropical oceans, where surface emissivity and skin/near-surface air temperature impacts on the IR radiances are minimal. The method at present is generally valid over oceanic regions only, specifically, the tropics and subtropics. The detection of thin cirrus, and other cloud types, is validated using observations at the Atmospheric Radiation Measurement (ARM) program site located at Manus Island in the tropical western Pacific for 89 coincident EOS-Aqua overpasses. Even though the emphasis of this work is on the detection of thin cirrus at nighttime, this technique is sensitive to a broad cloud morphology. The cloud detection technique agrees with ARM-detected clouds 82-84% of the time, which include thin cirrus, as well as other cloud types. Most of the disagreements are well explained by AIRS footprint-scale heterogeneity compared to ARM point measurements, cirrus overlying lower-layer water clouds, possible mixed phase microphysics in midlevel clouds, and significant IR channel noise for cold BT scenes over deep convective towers.

Atmospheric Radiation Measurement (RAM)↗

Asymmetry in the Diurnal Variation of Surface Albedo

Remote sensing of surface properties and estimation of clear-sky and surface albedo generally assumes that the albedo depends only on the solar zenith angle. The effects of dew, frost, and precipitation as well as evaporation and wind can lead to some systematic diurnal variability resulting in an asymmetric diurnal cycle of albedo. This paper examines the symmetry of both surface-observed albedos and top-of-the-atmosphere (TOA) albedos derived from satellite data. Broadband and visible surface albedos were measured at the Department of Energy Atmospheric Radiation Measurement (ARM) Program Southern Great Plains Central Facility, at some fields near the ARM site, and over a coniferous forest in eastern Virginia. Surface and wind conditions are available for most cases. GOES-8 satellite radiance data are converted to broadband albedo using bidirectional reflectance functions and an empirical narrowband-to-broadband relationship. The initial results indicate that surface moisture has a significant effect and can change the albedo in the afternoon by 20% relative to its morning counterpart. Such effects may need to be incorporated in mesoscale and even large-scale models of atmospheric processes.

Mayor, S.↗

Mechanisms of Diurnal Precipitation over the United States Great Plains: A Cloud-Resolving Model Simulation

The mechanisms of summertime diurnal precipitation in the US Great Plains were examined with the two-dimensional (2D) Goddard Cumulus Ensemble (GCE) cloud-resolving model (CRM). The model was constrained by the observed large-scale background state and surface flux derived from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program s Intensive Observing Period (IOP) data at the Southern Great Plains (SGP). The model, when continuously-forced by realistic surface flux and large-scale advection, simulates reasonably well the temporal evolution of the observed rainfall episodes, particularly for the strongly forced precipitation events. However, the model exhibits a deficiency for the weakly forced events driven by diurnal convection. Additional tests were run with the GCE model in order to discriminate between the mechanisms that determine daytime and nighttime convection. In these tests, the model was constrained with the same repeating diurnal variation in the large-scale advection and/or surface flux. The results indicate that it is primarily the surface heat and moisture flux that is responsible for the development of deep convection in the afternoon, whereas the large-scale upward motion and associated moisture advection play an important role in preconditioning nocturnal convection. In the nighttime, high clouds are continuously built up through their interaction and feedback with long-wave radiation, eventually initiating deep convection from the boundary layer. Without these upper-level destabilization processes, the model tends to produce only daytime convection in response to boundary layer heating. This study suggests that the correct simulation of the diurnal variation in precipitation requires that the free-atmospheric destabilization mechanisms resolved in the CRM simulation must be adequately parameterized in current general circulation models (GCMs) many of which are overly sensitive to the parameterized boundary layer heating.

Lee, M.-I.↗

Remote Sensing Data from CLARET: A Prototype Cart Data Set

A data set containing radiation, meteorological, and cloud sensor observations is documented. It was prepared for use by the Department of Energy's Atmospheric Radiation Measurement (ARM) program and other interested scientists. These data are a precursor of the types of data that ARM Cloud And Radiation Testbed (CART) sites will provide. The data are from the Cloud Lidar And Radar Exploratory Test (CLARET) conducted by the Wave Propagation Laboratory during autumn 1989 in the Denver-Boulder area of Colorado primarily for the purpose of developing new cloud-sensing techniques on cirrus. After becoming aware of this experiment, ARM scientists requested archival of subsets or the data to assist in the developing ARM program. Five CLARET cases were selected: two with cirrus, one with stratus, one with mixed-phase clouds, and one with clear skies. The cases range from 2 to 9.5 h in length. A pyranometer, pyrgeometer, pyrheliometer, and an infrared radiometer constituted the ensemble of instruments that provided surface radiation data. A lidar, radar, and ceilometer observed the cloud geometrical structure, and visual reports and all-sky camera observations were assimilated to provide cloud cover data. Radiosondes, wind profiler, RASS (profiling virtual temperature), microwave radiometers (observing column integrated liquid water and water vapor), and standard surface measurements provided meteorological data. Satellite data from the stratus case and one cirrus case were analyzed for statistics on cloud cover and top height. The main body of the selected data are available on diskette from the Wave Propagation Laboratory or Los Alamos National Laboratory. In addition to documenting the data set, this report describes CLARET and gives a bibliography of publications associated with the project. Some preliminary results of CLARET' research are also summarized. Simultaneous CO 2 lidar and radar backscatter measurements were shown to provide estimates of the effective radius of ice particles. Simultaneous radar and infrared radiometer data appear useful for estimating column-integrated numbers and average sizes of ice cloud particles. Ice water content obtained with this method compared favorably with values from another empirical technique using radar data alone. Depolarization of the CO 2 lidar signal from ice clouds was surprisingly small, suggesting that calculation of backscatter from nonspherical particles for this lidar is a tractable problem. Examples are also cited of CO 2 lidar measurements of the effective radius of water cloud drop size distributions and of inference of the size of pristine ice crystals that assume a particular orientation in the air. These parameters are all important to radiative transfer through clouds.

Clouds (Meteorology)↗

Overview of the 2010 Carbonaceous Aerosols and Radiative Effects Study (CARES)

Substantial uncertainties still exist in the scientific understanding of the possible interactions between urban and natural (biogenic) emissions in the production and transformation of atmospheric aerosol and the resulting impact on climate change. The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Carbonaceous Aerosol and Radiative Effects Study (CARES) carried out in June 2010 in Central Valley, California, was a comprehensive effort designed to improve this understanding. The primary objective of the field study was to investigate the evolution of secondary organic and black carbon aerosols and their climate-related properties in the Sacramento urban plume as it was routinely transported into the forested Sierra Nevada foothills area. Urban aerosols and trace gases experienced significant physical and chemical transformations as they mixed with the reactive biogenic hydrocarbons emitted from the forest. Two heavily-instrumented ground sites - one within the Sacramento urban area and another about 40 km to the northeast in the foothills area - were set up to characterize the evolution of meteorological variables, trace gases, aerosol precursors, aerosol size, composition, and climaterelated properties in freshly polluted and "aged" urban air. On selected days, the DOE G-1 aircraft was deployed to make similar measurements upwind and across the evolving Sacramento plume in the morning and again in the afternoon. The NASA B-200 aircraft, carrying remote sensing instruments, was also deployed to characterize the vertical and horizontal distribution of aerosols and aerosol optical properties within and around the plume. This overview provides: (a) the scientific background and motivation for the study, (b) the operational and logistical information pertinent to the execution of the study, (c) an overview of key observations and initial findings from the aircraft and ground-based sampling platforms, and (d) a roadmap of planned data analyses and focused modeling efforts that will facilitate the integration of new knowledge into improved representations of key aerosol processes and properties in climate models.

aerosols↗

Comparison of measurements by the NASA/GSFC scanning raman lidar and the DOE/ARM CART raman lidar

Latent heat transfer through evaporation and condensation of water vapor is the most important energy transport mechanism in the atmosphere. In addition, water vapor is the most active greenhouse gas. Any global warming scenario must take accurate account of the spatial and temporal variation of water vapor in order to account for both of these effects. Due to the great importance of water vapor in atmospheric radiation studies, specific intensive operations periods (IOPs) have been hosted by the Department of Energy's Atmospheric Radiation Measurements (ARM) program. One of the goals of these IOPs has been to determine the quality of and explain any discrepancies among a wide variety of water vapor measuring instruments. Raman lidar systems developed by NASA/Goddard Space Flight Center and DOE/Sandia National Laboratories have participated in the two Water Vapor IOPs (WVIOPs) held at the Southern Great Plains (SGP) Cloud and Radiation Testbed Site (CART) site during 1996 (WVIOP1) and 1997 (WVIOP2). Detailed comparisons of these two systems is ongoing but this effort has already resulted in numerous improvements in design and data analysis for both lidar systems.

Whiteman, David↗

Comparison of Aerosol Optical Depth from Four Solar Radiometers During the Fall 1997 ARM Intensive Observation Period

In the Fall of 1997 the Atmospheric Radiation Measurement (ARM) program conducted an Intensive Observation Period (IOP) to study aerosols. Five sun-tracking radiometers were present to measure the total column aerosol optical depth. This comparison performed on the Southern Great Plains (SGP) demonstrates the capabilities and limitations of modern tracking sunphotometers at a location typical of where aerosol measurements are required. The key result was agreement in aerosol optical depth measured by 4 of the 5 instruments within 0.015 (rms). The key to this level of agreement was meticulous care in the calibrations of the instruments.

Schmid, B.↗

Comparison of Columnar Water Vapor Measurements During The Fall 1997 ARM Intensive Observation Period: Optical Methods

In the fall of 1997 the Atmospheric Radiation Measurement (ARM program conducted an intensive Observation Period (IOP) to study water vapor at its Southern Great Plains (SGP) site. Among the large number of instruments, four sun-tracking radiometers were present to measure the columnar water vapor (CWV). All four solar radiometers retrieve CWV by measuring solar transmittance in the 0.94-micrometer water vapor absorption band. As one of the steps in the CWV retrievals the aerosol component is subtracted from the total transmittance, in the 0.94-micrometer band. The aerosol optical depth comparisons among the same four radiometers are presented elsewhere. We have used three different methods to retrieve CWV. Without attempting to standardize on the same radiative transfer model and its underlying water vapor spectroscopy we found the CWV to agree within 0.13 cm (rms) for CWV values ranging from 1 to 5 cm. Preliminary results obtained when using the same updated radiative transfer model with updated spectroscopy for all instruments will also be shown. Comparisons to the microwave radiometer results will be included in the comparisons.

Schmid, Beat↗

Comparison of Columnar Water Vapor Measurements During The Fall 1997 ARM Intensive Observation Period: Solar Transmittance Methods

In the fall of 1997, during an Intensive Observation Period (IOP), the Atmospheric Radiation Measurement (ARM) program conducted a study of water vapor abundance measurement at its Southern Great Plains (SGP) site. Among a large number of instruments, four sun-tracking radiometers were present to measure the columnar water vapor (CWV). All four solar radiometers retrieve CWV by measuring total solar transmittance in the 0.94-gm water vapor absorption band and subtracting contributions due to Rayleigh, ozone and aerosol transmittances. The aerosol optical depth comparisons among the same four radiometers has been presented elsewhere (Geophys. Res. Lett., 26, 17, 2725-2728, 1999). We have used three different methods to retrieve CWV. In a first round of comparison no attempt was made to standardize on the same radiative transfer model and its underlying water vapor spectroscopy. In the second round of comparison we used the same line-by-line code (which includes recently corrected H2O spectroscopy) to retrieve CAN from all four suntracking radiometers. This decreased the mean CWV by 8% or 13%. The spread of 8% in the solar radiometer results found when using the same model is an indication of the other-than-model uncertainties involved in determining CWV from solar transmittance measurements with current instrumentation.

Schmid, B.↗

A 3-Year Climatology of Cloud and Radiative Properties Derived from GOES-8 Data Over the Southern Great Plains

While the various instruments maintained at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) Central Facility (CF) provide detailed cloud and radiation measurements for a small area, satellite cloud property retrievals provide a means of examining the large-scale properties of the surrounding region over an extended period of time. Seasonal and inter-annual climatological trends can be analyzed with such a dataset. For this purpose, monthly datasets of cloud and radiative properties from December 1996 through November 1999 over the SGP region have been derived using the layered bispectral threshold method (LBTM). The properties derived include cloud optical depths (ODs), temperatures and albedos, and are produced on two grids of lower (0.5 deg) and higher resolution (0.3 deg) centered on the ARM SGP CF. The extensive time period and high-resolution of the inner grid of this dataset allows for comparison with the suite of instruments located at the ARM CF. In particular, Whole-Sky Imager (WSI) and the Active Remote Sensing of Clouds (ARSCL) cloud products can be compared to the cloud amounts and heights of the LBTM 0.3 deg grid box encompassing the CF site. The WSI provides cloud fraction and the ARSCL computes cloud fraction, base, and top heights using the algorithms by Clothiaux et al. (2001) with a combination of Belfort Laser Ceilometer (BLC), Millimeter Wave Cloud Radar (MMCR), and Micropulse Lidar (MPL) data. This paper summarizes the results of the LBTM analysis for 3 years of GOES-8 data over the SGP and examines the differences between surface and satellite-based estimates of cloud fraction.

Khaiyer, M. M.↗

Polar Cirrus Cloud Properties Through Long-Term Lidar and Radiometer Observations

In comparison to mid latitude cloud cover, knowledge of polar cirrus and other cloud cover is limited. The interpretations of satellite-based cloud imaging and retrievals in polar regions have major problems due to factors such as darkness and extreme low temperatures. Beginning in 2002 a NASA orbiting lidar instrument, GLAS, (Geoscience Laser Altimeter System) will unambiguously define cloud type and fraction with good coverage of polar regions. Active laser sensing gives the spatial and temporal distribution of clouds and diamond dust. In preparation for, and supplementing the GLAS measurements are ground based MP (micro pulse) lidar experiments providing continuous profiling. MP lidar installations have been operating at the South Pole since December 1999 and at the Atmospheric Radiation Measurement (ARM) program arctic site since 1996. Both at the ARM Barrow, Alaska site and at the South Pole station, Fourier-transform interferometers also observe clouds in the wavelength intervals between approximately 5 and 18 microns. Spectral instruments can yield cloud microphysical properties with additional information from lidar about the vertical extent of clouds being modeled. We examine the simultaneous lidar and spectral data from both Barrow and South Pole, to obtain cloud properties (optical depth, particle size) by the use of both instruments. The results have applications to interpretation of current satellite data, and GLAS measurements when available.

Spinhirne, James↗