The Use of Microwave Radiometry to Determine a Cloud Seeding Opportunity

The Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) and MODIS/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.2 μm (12.9 μm for MASTER). These observations were obtained from the NASA ER‐2 aircraft as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment conducted over Central America and surrounding Pacific and Atlantic Oceans between 17 July and 8 August 2007. Multispectral images in eleven distinct bands were used to derive a confidence in clear sky (or alternatively the probability of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). The cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm to that implemented operationally to process MODIS cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER data in TC4, is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from MODIS on the Terra spacecraft. Finally, this MODIS‐based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness of liquid water clouds from MISR. Results of this analysis are compared and contrasted.

<p>Clouds exert a strong radiative impact on the surface and have complicated effects that are still not well understood, particularly in the Antarctic. The amount of supercooled liquid water in Antarctic clouds, for example, is still poorly constrained, due to the low number of observations on the continent. It is also not clear how the radiative properties of supercooled liquid in those clouds should be represented in climate models. In particular, the complex refractive index (CRI) of liquid water is known to depend on temperature, but this dependence is typically ignored in climate models.</p><p>Here, we present cloud properties retrieved from Antarctic downwelling infrared radiance measurements made by an Atmospheric Emitted Radiance Interferometer (AERI) and by the Polar AERI (PAERI), using the CLoud and Atmospheric Radiation Retrieval Algorithm (CLARRA). Preliminary retrievals were made of cloud height, optical depth, thermodynamic phase, and effective radius for field experiments at Amundsen-Scott South Pole Station (2001) and at McMurdo Station (2016).</p><p>At South Pole, we find that clouds are typically thin and near the surface, in keeping with prior work. For thin clouds, the mode of the effective radii of liquid droplets (~4 μm) and ice particles (~15 μm in summer, ~12 μm in winter) at South Pole are found to be smaller than typical Arctic values (~9 μm for liquid and 17 to 25 μm for ice). Although ice cloud was found to dominate year-round at South Pole, significant supercooled liquid water was present in the summer. Cloud properties retrieved at South Pole will be compared to retrievals from McMurdo.</p><p>We further find that ignoring the temperature dependence of the CRI of supercooled liquid cloud leads to negative biases in part of the atmospheric window region (700 – 1000 cm<sup>-1</sup>), indicating underestimation of the greenhouse effect. These biases are expected to be partially offset by positive biases below 600 cm<sup>-1</sup>. Based on these considerations, we recommend using temperature-dependent CRI for infrared radiance simulations of supercooled liquid water cloud.</p>

Abstract. This study examines the characteristics of the microphysics and macrophysics of water clouds from East Asia to the North Pacific, using data from active CloudSat radar measurements and passive MODerate-resolution Imaging Spectroradiometer (MODIS) retrievals. Our goals are to clarify differences in microphysics and macrophysics between land and oceanic clouds, seasonal differences unique to the midlatitudes, characteristics of the drizzling process, and cloud vertical structure. In pristine oceanic areas, fractional occurrences of cloud optical thickness (COT) and cloud droplet effective radius (CDR) increase systematically with an increase in drizzle intensity, but these characteristics of the COT and CDR transition are less evident in polluted land areas. In addition, regional and seasonal differences are identified in terms of drizzle intensity as a function of the liquid water path (LWP) and cloud droplet number concentration (Nc). The correlations between drizzle intensity and LWP, and between drizzle intensity and Nc, are both more robust over oceanic areas than over land areas. We also demonstrate regional and seasonal characteristics of the cloud vertical structure. Our results suggest that aerosol–cloud interaction mainly occurs around the cloud base in polluted land areas during the winter season. In addition, a difference between polluted and pristine areas in the efficiency of cloud droplet growth is confirmed. These results suggest that water clouds over the midlatitudes exhibit a different drizzle system to those over the tropics.

The lack of high quality measurements of Hg and trace elements in cloud and fog water led to the design of a new collector for clean sequential sampling of cloud and fog water. Cloud water was collected during nine non-precipitating cloud events on Mt. Mansfield, VT in the northeastern USA between August 1 and October 31, 1998. Sequential samples were collected during six of these events. Mercury cloud water concentrations ranged from 7.5 to 71.8 ng l(-1), with a mean of 24.8 ng l(-1). Liquid water content explained about 60% of the variability in Hg cloud concentrations. Highest Hg cloud water concentrations were found to be associated with transport from the Mid-Atlantic and Ohio River Valley, and lowest concentrations with transport from the north of Mt. Mansfield out of Canada. Twenty-nine event precipitation samples were collected during the ten-week cloud sampling period near the base of Mt. Mansfield as part of a long-term deposition study. The Hg concentrations of cloud water were similar to, but higher on average (median of 12.5 ng l(-1)) than Hg precipitation concentrations (median of 10.5 ng l(-1)). Cloud and precipitation samples were analyzed for fifteen trace elements including Mg, Cu, Zn, As, Cd and Pb by ICP-MS. Mean concentrations were higher in cloud water than precipitation for elements with predominately anthropogenic, but not crustal origin in samples from the same source region. One possible explanation is greater in-cloud scavenging of crustal elements in precipitating than non-precipitating clouds, and greater below-cloud scavenging of crustal than anthropogenic aerosols.

Abstract. This empirical study demonstrates the feasibility of using 89-GHz Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) passive microwave brightness temperature data to detect heavily drizzling cells within subtropical marine stratocumulus. For the purpose of this paper, we define heavily drizzling cells as areas ≥ 6 km × 4 km with C-band Z > 0 dBZ; equivalent to > 0.084 mm h−1. A binary heavy drizzle product is described that can be used to determine areal and feature statistics of drizzle cells within the major marine stratocumulus regions. Current satellite liquid water path (LWP) and cloud radar products capable of detecting drizzle are either lacking in resolution (AMSR-E LWP), diurnal coverage (MODIS LWP), or spatial coverage (CloudSat). The AMSR-E 89-GHz data set at 6 km × 4 km spatial resolution is sufficient for resolving individual heavily drizzling cells. Radiant emission at 89 GHz by liquid-water cloud and precipitation particles from drizzling cells in marine stratocumulus regions yields local maxima in brightness temperature against an otherwise cloud-free background brightness temperature. The background brightness temperature is primarily constrained by column-integrated water vapor for moderate sea surface temperatures. Clouds containing ice are screened out. Once heavily drizzling pixels are identified, connected pixels are grouped into discrete drizzle cell features. The identified drizzle cells are used in turn to determine several spatial statistics for each satellite scene, including drizzle cell number and size distribution. The identification of heavily drizzling cells within marine stratocumulus regions with satellite data facilitates analysis of seasonal and regional drizzle cell occurrence and the interrelation between drizzle and changes in cloud fraction.

Synergetic use of POLDER and MODIS for multilayered cloud identification

Direct interception of windblown cloud water by forests has been dubbed “occult deposition” because it represents a hydrological input that is hidden from rain gauges. Eddy correlation studies of this phenomenon have estimated cloud water fluxes to vegetation yet have lacked estimates of error bounds. This paper presents an evaluation of instrumental and methodological errors for cloud liquid water fluxes to put such eddy correlation measurements in context. Procedures for data acquisition, processing (including correction factors), and calibration testing of the particulate volume monitor (PVM) and forward-scattering spectrometer probe (FSSP) are detailed. Nearly 200 h of in-cloud data are analyzed for intercomparison of these instruments. Three methods of coordinate system rotation are investigated; the flux shows little sensitivity to the method used, and the difference between fluxes at different stations is even less sensitive to this choice. Side-by-side intercomparison of two PVMs and one FSSP leads to error bounds of 0.01–0.035 g m−3 on half-hour mean cloud liquid water content (relative to typical values of 0.35 g m−3) and 2–3.5 mg m−2 s−1 on the surface-normal liquid water flux (typical magnitude of 7 mg m−2 s−1 for these data), depending on which instruments are compared.

The method of simultaneously retrieving ice water path and mass median diameter using microwave data at two frequencies is examined and implemented for tropical nonprecipitating clouds. To develop the retrieval algorithm, the authors first derived a bulk mass–size relation for ice particles in tropical clouds based on microphysical data collected during the Central Equatorial Pacific Experiment. This relation effectively allows ice particle density to decrease with particle size. In implementing the retrieval algorithm, 150- and 220-GHz Millimeter-Wave Imaging Radiometer data collected during the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment were used. Ice water path and mass median diameter are determined based on a lookup table generated by a radiative transfer model. The lookup table depends on cloud type, cloud liquid water path, and atmospheric temperature and humidity profiles. Only nonprecipitating clouds are studied in this paper. Error analyses were performed by a Monte Carlo procedure in which atmospheric profiles, ice cloud height, liquid water content, surface temperature, and instrument noise vary randomly within their uncertainty range through a Latin hypercube sampling scheme. The rms error in the retrievals is then assessed and presented in a two-dimensional diagram of ice water path and mass median diameter. It is shown that the simultaneous retrieval method using 150 and 220 GHz may be used for clouds with ice water path larger than 200 g m−2 and mass median diameter larger than 200 μm. To obtain meaningful retrievals for “thinner” clouds, higher microwave frequencies are needed. It is also shown that liquid water clouds that are at the same altitude as ice clouds interfere with the retrievals to a significant degree. To obtain reasonable ice water path and mass median size retrievals, it is necessary first to group clouds into several classes, then to apply separate algorithms to the different classes. The accuracy of the retrievals also depends on cloud type, with the best accuracy for cirrus and the worst for the midtop mixed-phase cloud among the clouds investigated in this study.

<strong class="journal-contentHeaderColor">Abstract.</strong> Single layer nonprecipitating warm clouds are integral to Earth&rsquo;s climate, and accurate estimates of cloud liquid water content for these clouds are critical for constraining cloud models and understanding climate feedbacks. As the only cloud-sensitive radar currently in space, CloudSat provides very important cloud profiling capabilities. However, a significant fraction of clouds are missed by CloudSat, because they are either too thin or too close to the earth&rsquo;s surface. We find that the CloudSat 2B-CWC-RVOD product misses about 73 % of nonprecipitating liquid cloudy pixels, and about 63 % of total nonprecipitating liquid cloud water content, compared to coincident MODIS observations. Those percentages increase to 84 % and 69 %, respectively, if MODIS &ldquo;partly cloudy&rdquo; pixels are included. We develop a method, based on adiabatic parcel theory but modified to account for the fact that observed clouds are often subadiabatic, to estimate profiles of cloud liquid water content based on MODIS observations of cloud top effective radius and cloud optical depth combined with CALIPSO observations of cloud top height. We find that, for cloudy pixels that are detected by CloudSat, the resulting subadiabatic profiles of cloud water are similar to what is retrieved from CloudSat. For cloudy pixels that are not detected by CloudSat, the subadiabatic profiles can be used to supplement the CloudSat profiles, recovering much of the missing cloud water and generating realistic-looking merged profiles of cloud water. Adding this missing cloud water to the CWC-RVOD product increases the mean cloud liquid water path by 228 % for single layer nonprecipitating warm clouds. This method will be included in a subsequent reprocessing of the 2B-CWC-RVOD algorithm.

A new multiparameter retrieval algorithm based on a backpropagation neural network (BPNN) has been developed for deriving integrated water vapor (WV) and cloud liquid water (CLW) contents over oceans from brightness temperatures (BTs) measured by the Multi-frequency Scanning Microwave Radiometer (MSMR) launched onboard Indian Remote Sensing satellite IRS-P4. The MSMR measures brightness temperatures in vertical and horizontal polarizations at 6.0-, 10.65-, 18.0-, and 21.0-GHz frequencies. The data are available at three spatial grid resolutions of 150, 75, and 50 km. In this paper, a BPNN has been trained using brightness temperatures simulated through radiative transfer model and simulated surface and atmospheric parameters. The present algorithm has been compared with the operational MSMR retrieval algorithm based on statistical regression using the same dataset. The validation of WV with in situ data (Vaisala radiosonde) is presented. Moreover, comparison of WV and CLW derived from MSMR using BPNN with the finished products from the Special Sensor Microwave/Imager and the Tropical Rainfall Measuring Mission Microwave Imager has also been carried out. The complexity of the BPNN in retrieval of geophysical products, individually and simultaneously, has also been discussed. Simultaneous retrieval of WV and CLW improves the results.

Two techniques were developed to measure water vapor and cloud liquid water by combined ground-based sensors. One technique retrieves water vapor and cloud liquid profiles from a microwave radiometer, a ceilometer, a Radio Acoustic Sounding System and surface in situ sensors. The other technique extends profiles of water vapor measured by a Raman lidar to altitudes above its last range gate. This technique augments Raman lidar data with those from a microwave radiometer and surface in situ sensors. Both techniques are evaluated using experimental data.

Water vapor and cloud liquid water influence the accuracy of altimeter measurements by delaying the time that altimeter's signals travel from satellite to the ocean surface and back. Atmospheric correction microwave radiometer (ACMR) can be used to measure radiation from atmosphere and earth's surface so as to retrieve the amount of water vapor and cloud liquid water. HY-2 satellite is a Chinese satellite for ocean dynamic environmental monitoring. It launched on Aug.16, 2011. ACMR is one of HY-2 satellite payloads. The other payloads are an altimeter, a scatterometer and a scanning microwave radiometer. ACMR started to work on Sep.1, 2011. Since then, it has been in normal operation. In this paper, instrument description, pre-launch calibration and in-orbit performance assessment of ACMR are briefly presented.

Snowmelt detection on the Antarctic ice sheet and ice Shelves based on AMSR2 89 GHz channels

Los Alamos and Sandia National Laboratories are partners in an effort to survey the super-cooled liquid water in clouds over the state of New Mexico in a project sponsored by the New Mexico Small Business Assistance Program. This report summarizes the scientific work performed at Sandia National Laboratories during the 2009. In this second year of the project a practical methodology for estimating cloud super-cooled liquid water was created. This was accomplished through the analysis of certain MODIS sensor satellite derived cloud products and vetted parameterizations techniques. A software code was developed to analyze multiple cases automatically. The eighty-one storm events identified in the previous year effort from 2006-2007 were again the focus. Six derived MODIS products were obtained first through careful MODIS image evaluation. Both cloud and clear-sky properties from this dataset were determined over New Mexico. Sensitivity studies were performed that identified the parameters which most influenced the estimation of cloud super-cooled liquid water. Limited validation was undertaken to ensure the soundness of the cloud super-cooled estimates. Finally, a path forward was formulized to insure the successful completion of the initial scientific goals which include analyzing different of annual datasets, validation of the developed algorithm, and the creation of a user-friendly and interactive tool for estimating cloud super-cooled liquid water.

Radiative transfer simulations are performed to determine how water vapor and nonprecipitating cloud liquid water and ice particles within typical midlatitude atmospheres affect brightness temperatures TB's of moisture sounding channels used in the Advanced Microwave Sounding Unit (AMSU) and AMSU-like instruments. The purpose is to promote a general understanding of passive top-of-atmosphere TB's for window frequencies at 23.8, 89.0, and 157.0 GHz, and water vapor frequencies at 176.31, 180.3 1, and 182.31 GHz by documenting specific examples. This is accomplished through detailed analyses of TB's for idealized atmospheres, mostly representing temperate conditions over land. Cloud effects are considered in terms of five basic properties: droplet size distribution, phase, liquid or ice water content, altitude, and thickness. Effects on TB of changing surface emissivity also are addressed. The brightness temperature contribution functions are presented as an aid to physically interpreting AMSU TB's. Both liquid and ice clouds impact the TB's in a variety of ways. The TB's at 23.8 and 89 GHZ are more strongly affected by altostratus liquid clouds than by cirrus clouds for equivalent water paths. In contrast, channels near 157 and 183 GHz are more strongly affected by ice clouds. Higher clouds have a water impact on 157- and 183-GHz TB's than do lower clouds. Clouds depress TB's of the higher-frequency channels by suppressing, but not necessarily obscuring, radiance contributions from below. Thus, TB's are less closely associated with cloud-top temperatures than are IR radiometric temperatures. Water vapor alone accounts for up to 89% of the total attenuation by a midtropospheric liquid cloud for channels near 183 GHz. The Rayleigh approximation is found to be adequate for typical droplet size distributions; however, Mie scattering effects from liquid droplets become important for droplet size distribution functions with modal radii greater than 20 µm near 157 and 183 GHz, and greater than 30–40 µm at 89 GHz. This is due mainly to the relatively small concentrations of droplets much larger than the mode radius. Orographic clouds and tropical cumuli have been observed to contain droplet size distributions with mode radii in the 30–40-µm range. Thus, as new instruments bridge the gap between microwave and infrared to frequencies even higher than 183 GHz, radiative transfer modelers are cautioned to explicitly address scattering characteristics of such clouds.