Gerald G. Mace

THE CLOUDSAT MISSION AND THE A-TRAIN A New Dimension of Space-Based Observations of Clouds and Precipitation

CloudSat is a satellite experiment designed to measure the vertical structure of clouds from space. The expected launch of CloudSat is planned for 2004, and once launched, CloudSat will orbit in formation as part of a constellation of satellites (the A-Train) that includes NASAs Aqua and Aura satellites, a NASA–CNES lidar satellite (CALIPSO), and a CNES satellite carrying a polarimeter (PARASOL). A unique feature that CloudSat brings to this constellation is the ability to fly a precise orbit enabling the fields of view of the CloudSat radar to be overlapped with the CALIPSO lidar footprint and the other measurements of the constellation. The precision and near simultaneity of this overlap creates a unique multisatellite observing system for studying the atmospheric processes essential to the hydrological cycle. The vertical profiles of cloud properties provided by CloudSat on the global scale fill a critical gap in the investigation of feedback mechanisms linking clouds to climate. Measuring these profi...

Objective Determination of Cloud Heights and Radar Reflectivities Using a Combination of Active Remote Sensors at the ARM CART Sites

Abstract The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Program is deploying sensitive, millimeter-wave cloud radars at its Cloud and Radiation Test Bed (CART) sites in Oklahoma, Alaska, and the tropical western Pacific Ocean. The radars complement optical devices, including a Belfort or Vaisala laser ceilometer and a micropulse lidar, in providing a comprehensive source of information on the vertical distribution of hydrometeors overhead at the sites. An algorithm is described that combines data from these active remote sensors to produce an objective determination of hydrometeor height distributions and estimates of their radar reflectivities, vertical velocities, and Doppler spectral widths, which are optimized for accuracy. These data provide fundamental information for retrieving cloud microphysical properties and assessing the radiative effects of clouds on climate. The algorithm is applied to nine months of data from the CART site in Oklahoma for initial evaluation. Much of...

Hydrometeor detection using Cloudsat - An earth-orbiting 94-GHz cloud radar

In late April 2006, NASA launched Cloudsat, an earth-observing satellite that uses a near-nadir-pointing millimeter-wavelength radar to probe the vertical structure of clouds and precipitation. The first step in using Cloudsat measurements is to distinguish clouds and other hydrometeors from radar noise. In this article the operational Cloudsat hydrometeor detection algorithm is described, difficulties due to surface clutter are discussed, and several examples from the early mission are shown. A preliminary comparison of the Cloudsat hydrometeor detection algorithm with lidar-based results from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is also provided.

Uncertainties in modeled and measured clear-sky surface shortwave irradiances

A comparison of five independent measurements of the clear-sky downward shortwave irradiance at the surface shows that they scatter within a 5% range depending on their calibration constants. When the measurements are corrected using data from two cavity radiometers, three of the five independent measurements agree within 3 W m−2 over three clear-sky days, which is well within the estimated error limit of ±1.5%. A comparison of these three sets of irradiance measurements with the computed irradiance by a δ2-stream model reveals that the model overestimates the irradiance by 5%. Detailed investigation of the approximations and uncertainties associated with the computations (including the measurement error in the water vapor and ozone amounts, neglecting the state of polarization and trace gas absorption, the 2-stream approximation, the neglect of the spectral dependence of the surface albedo, and the uncertainties associated with aerosols) demonstrates that the discrepancy is not due to these approximations. Further analysis of the modeled and measured irradiance shows that the discrepancy is almost entirely due to the difference between modeled and measured diffuse field irradiances. An analysis of narrow-band diffuse to total irradiance ratios shows that this discrepancy is the largest near 400 nm and decreases with wavelength. These results rely on the absolute calibrations of two cavity radiometers, two shaded pyranometers, and one unshaded pyranometer, as well as ratios of irradiances measured by a multifilter rotating shadow-band radiometer. Therefore, in order for instrumental error to account for the diffuse field discrepancy, three independent measurements of the diffuse field irradiance must be biased low by at least 40%. For an aerosol to account for this discrepancy, it must be highly absorbing with a single-scattering albedo as low as 0.3. The unlikelihood of instrumental errors of 40% and aerosol single-scattering albedos of 0.3 suggests a third possibility: the neglect of some gaseous absorption process at visible wavelengths.

A new retrieval for cloud liquid water path using a ground‐based microwave radiometer and measurements of cloud temperature

A new method to retrieve cloud liquid water path using 23.8 and 31.4 GHz microwave radiometer brightness temperature measurements is developed. This method does not depend on climatological estimates of either the mean radiating temperature of the atmosphere Tmr or the mean cloud liquid water temperature Tcloud. Rather, Tmr is estimated from surface temperature and relative humidity measurements, while Tcloud is estimated using millimeter-wave cloud radar data, together with atmospheric temperature profiles obtained from either radiosonde or rapid update cycle (RUC) model output. Simulations demonstrate that the new retrieval method significantly reduces the biases in the liquid water path estimates that are apparent in a site-specific retrieval based on monthly stratified, local climatology. An analysis of the liquid water path estimates produced by the two retrievals over four case study days illustrates trends and retrieval performances consistent with the model simulations.

Global hydrometeor occurrence as observed by CloudSat: Initial observations from summer 2006

Measurements of global hydrometeor coverage and occurrence frequencies as observed by the cloud radar on CloudSat are summarized using data collected during Summer 2006. CloudSat was launched on 28 April 2006 and began collecting data routinely on 7 June 2006. In this article we document the distribution of cloudiness from the ITCZ to the Polar regions as observed by CloudSat during the first summer of operations. The overall global hydrometeor coverage as observed by CloudSat is found to be 0.506. The vertical distribution of zonally averaged hydrometeor occurrence shows the relationship of clouds with components of the atmospheric general circulation such as the Hadley Cell, the ubiquitous storms over the Southern Ocean, and the subtropical stratocumulus regimes.

The Tropical Warm Pool International Cloud Experiment

A comprehensive dataset describing tropical cloud systems and their environmental setting and impacts has been collected during the Tropical Warm Pool International Cloud Experiment (TWPICE) and Aerosol and Chemical Transport in Tropical Convection (ACTIVE) campaign in the area around Darwin, Northern Australia, in January and February 2006. The aim of the experiment was to observe the evolution of tropical cloud systems and their interaction with the environment within an observational framework optimized for a range of modeling activities with the goal of improving the representation of cloud and aerosol process in a range of models. The experiment design utilized permanent observational facilities in Darwin, including a polarimetric weather radar and a suite of cloud remote-sensing instruments. This was augmented by a dense network of soundings, together with radiation, flux, lightning, and remote-sensing measurements, as well as oceanographic observations. A fleet of five research aircraft, including ...

Cirrus layer microphysical properties derived from surface-based millimeter radar and infrared interferometer data

Observational data regarding the properties of cirrus clouds are needed to aid in the development of accurate, physically based parameterizations in climate models. The Atmospheric Radiation Measurement (ARM) program, sponsored by the U.S. Department of Energy, is providing continuous observations of cirrus clouds with a suite of instrumentation at several locales. In this paper, we describe an algorithm to derive the microphysical properties of optically thin cirrus clouds. This algorithm uses radar reflectivity and infrared emission spectra from an interferometer and is tailored for the specific instruments at the ARM sites. We present in situ validation of the technique and examine a cirrus case study to illustrate the sensitivity of the algorithm. In the case study, solar fluxes calculated from the retrieved microphysical parameters are compared to observed fluxes to build confidence in the algorithm results. Comparison of the retrieved quantities to microphysical parameters retrieved from satellite data is also presented.

Toward Understanding of Differences in Current Cloud Retrievals of ARM Ground-Based Measurements

Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models and better estimate of the Earth radiative budget. However, large differences are found in current cloud products retrieved from ground-based remote sensing measurements using various retrieval algorithms. Understanding the differences is an important step to address uncertainties in the cloud retrievals. In this study, an in-depth analysis of nine existing ground-based cloud retrievals using ARM remote sensing measurements is carried out. We place emphasis on boundary layer overcast clouds and high level ice clouds, which are the focus of many current retrieval development efforts due to their radiative importance and relatively simple structure. Large systematic discrepancies in cloud microphysical properties are found in these two types of clouds among the nine cloud retrieval products, particularly for the cloud liquid and ice particle effective radius. Note that the differences among some retrieval products are even larger than the prescribed uncertainties reported by the retrieval algorithm developers. It is shown that most of these large differences have their roots in the retrieval theoretical bases, assumptions, as well as input and constraint parameters. This study suggests the need to further validate current retrieval theories and assumptions and even the development of new retrieval algorithms with more observations under different cloud regimes.

Comparison of Stratus Cloud Properties Deduced from Surface, GOES, and Aircraft Data during the March 2000 ARM Cloud IOP

Low-level stratus cloud microphysical properties derived from surface and Geostationary Operational Environmental Satellite (GOES) data during the March 2000 cloud intensive observational period (IOP) at the Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) site are compared with aircraft in situ measurements. For the surface retrievals, the cloud droplet effective radius and optical depth are retrieved from a d2-stream radiative transfer model with the input of ground-based measurements, and the cloud liquid water path (LWP) is retrieved from ground-based microwave-radiometer-measured brightness temperature. The satellite results, retrieved from GOES visible, solar-infrared, and infrared radiances, are averaged in a 0.5 8 3 0.58 box centered on the ARM SGP site. The forward scattering spectrometer probe (FSSP) on the University of North Dakota Citation aircraft provided in situ measurements of the cloud microphysical properties. During the IOP, four low-level stratus cases were intensively observed by the ground- and satellite-based remote sensors and aircraft in situ instruments resulting in a total of 10 h of simultaneous data from the three platforms. In spite of the large differences in temporal and spatial resolution between surface, GOES, and aircraft, the surface retrievals have excellent agreement with the aircraft data overall for the entire 10-h period, and the GOES results agree reasonably well with the surface and aircraft data and have similar trends and magnitudes except for the GOES-derived effective radii, which are typically larger than the surface- and aircraft-derived values. The means and standard deviations of the differences between the surface and aircraft effective radius, LWP, and optical depth are 24% 6 20.1%, 21% 6 31.2%, and 8% 6 29.3%, respectively; while their correlation coefficients are 0.78, 0.92, and 0.89, respectively, during the 10-h period. The differences and correlations between the GOES-8 and aircraft results are of a similar magnitude, except for the droplet sizes. The averaged GOES-derived effective radius is 23% or 1.8 mm greater than the corresponding aircraft values, resulting in a much smaller correlation coefficient of 0.18. Additional surface‐satellite datasets were analyzed for time periods when the aircraft was unavailable. When these additional results are combined with the retrievals from the four in situ cases, the means and standard deviations of the differences between the satellite-derived cloud droplet effective radius, LWP, and optical depth and their surface-based counterparts are 16% 6 31.2%, 4% 6 31.6%, and 26% 6 39.9%, respectively. The corresponding correlation coefficients are 0.24, 0.88, and 0.73. The frequency distributions of the two datasets are very similar indicating that the satellite retrieval method should be able to produce reliable statistics of boundary layer cloud properties for use in climate and cloud process models.