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At least 163 records · Page 9

Spatial and Temporal Distribution of Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched aboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. A comprehensive set of remote sensing algorithms for the retrieval of cloud physical and optical properties have enabled over twelve years of continuous observations of cloud properties from Terra and over nine years from Aqua. The archived products from these algorithms include 1 km pixel-level (Level-2) and global gridded Level-3 products. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. Results include the latitudinal distribution of cloud optical and radiative properties for both liquid water and ice clouds, as well as latitudinal distributions of cloud top pressure and cloud top temperature. MODIS finds the cloud fraction, as derived by the cloud mask, is nearly identical during the day and night, with only modest diurnal variation. Globally, the cloud fraction derived by the MODIS cloud mask is approx.67%, with somewhat more clouds over land during the afternoon and less clouds over ocean in the afternoon, with very little difference in global cloud cover between Terra and Aqua. Overall, cloud fraction over land is approx.55%, with a distinctive seasonal cycle, whereas the ocean cloudiness is much higher, around 72%, with much reduced seasonal variation. Cloud top pressure and temperature have distinct spatial and temporal patterns, and clearly reflect our understanding of the global cloud distribution. High clouds are especially prevalent over the northern hemisphere continents between 30 and 50 . Aqua and Terra have comparable zonal cloud top pressures, with Aqua having somewhat higher clouds (cloud top pressures lower by 100 hPa) over land due to afternoon deep convection. The coldest cloud tops (colder than 230 K) generally occur over Antarctica and the high clouds in the tropics (ITCZ and the deep convective clouds over the western tropical Pacific and Indian sub-continent).

King, Michael D.↗

Evaluation of Aerosol-cloud Interaction in the GISS Model E Using ARM Observations

Observations from the US Department of Energy's Atmospheric Radiation Measurement (ARM) program are used to evaluate the ability of the NASA GISS ModelE global climate model in reproducing observed interactions between aerosols and clouds. Included in the evaluation are comparisons of basic meteorology and aerosol properties, droplet activation, effective radius parameterizations, and surface-based evaluations of aerosol-cloud interactions (ACI). Differences between the simulated and observed ACI are generally large, but these differences may result partially from vertical distribution of aerosol in the model, rather than the representation of physical processes governing the interactions between aerosols and clouds. Compared to the current observations, the ModelE often features elevated droplet concentrations for a given aerosol concentration, indicating that the activation parameterizations used may be too aggressive. Additionally, parameterizations for effective radius commonly used in models were tested using ARM observations, and there was no clear superior parameterization for the cases reviewed here. This lack of consensus is demonstrated to result in potentially large, statistically significant differences to surface radiative budgets, should one parameterization be chosen over another.

Clouds↗

Enhanced Convective Microphysics Scheme and Its Impacts on Mean Climate in E3SM

Abstract To improve the representation of microphysical processes in convective clouds and their interaction with aerosol and stratiform clouds, a two‐moment convective microphysics parameterization (CMP) scheme developed by Song and Zhang (2011, https://doi.org/10.1029/2010jd014833 ) is upgraded and implemented in E3SM. The new developments include: (a) implementing a parameterization for graupel to enhance the representation of ice‐phase microphysical processes; (b) representing the impact of spatial inhomogeneity of cloud droplets in cumulus ensembles on autoconversion and accretion processes to improve the representation of warm‐rain microphysical processes; (c) implementing a comprehensive Bergeron process parameterization to better represent mixed‐phase microphysical processes; and (d) representing the interactions between ice‐phase microphysics and cloud thermodynamics. Simulations show that the cloud microphysical properties simulated by the CMP are generally in good agreement with observations. It reasonably simulates the changes in droplets effective radius related to precipitation formation in convective clouds, as identified from satellite observations. It also successfully simulates the contrast in these processes between maritime and continental clouds, demonstrating its capability to simulate the impact of aerosols on convection. Analyses of the impact of CMP on climate mean state simulation demonstrate that the CMP slightly improves the simulations of precipitation, cloud macrophysical properties, longwave cloud radiative forcing, zonal wind, and temperature. However, a degradation in shortwave cloud radiative forcing occurs.

GCM↗

ARM Data as A Resource for Validation of NASA PACE Cloud Retrievals

NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will launch in January 2024 and continue and improve upon satellite data records in its eponymous domains. PACE will carry a broad-swath hyperspectral imager, OCI, which will provide MODIS/VIIRS-type cloud data products (i.e. a cloud mask, top height, visible optical thickness, droplet effective radius, phase, and derived water path). It will also carry two multi-angle polarimeters (HARP2 and SPEXone) which will not only provide the above but also enable retrievals of additional cloud properties (e.g. droplet effective variance, ice crystal asymmetry parameter). Validating satellite-based cloud retrievals is challenging. We plan to use several ARM data streams to evaluate PACE cloud data products and are prototyping our analyses using retrievals from MODIS on the Aqua satellite and OLCI on the Sentinel-3A satellite. This poster shows how we plan to use ARM data to evaluate liquid water path (via MWRRET) and cloud top height retrievals (via KARZASRCL), with example results from these proxy sensors and ARM data from the SGP, ENA, and NSA sites. We seek comments from and collaborations with the ARM community to get the most out of our respective data streams.

ARM↗

MODIS Cloud Optical Property Retrieval Uncertainties Derived from Pixel-Level VNIR/SWIR Radiometric Uncertainties

Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of optical thickness and effective particle radius for liquid water and ice phase clouds employ a well-known VNIR/ SWIR solar reflectance technique. For this type of algorithm, we evaluate the quantitative uncertainty in simultaneous retrievals of these two cloud parameters to pixel-level radiometric calibration estimates and other fundamental (and tractable) error sources.

Platnick, S.↗

Spatial and Temporal Distribution of Clouds as Observed by MODIS Onboard the Terra and Aqua Satellites

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24,2000 for Terra and June 24,2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, and fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. Over the last year, extensive improvements and enhancements in the global cloud products have been implemented, and reprocessing of all MODIS data on Terra has commenced since first light in February 2000. In the cloud mask algorithm, the most extensive improvements were in distinguishing clouds at nighttime, including the challenging polar darkness regions of the world. Additional improvements have been made to properly distinguish sunglint from clouds in the tropical ocean regions, and to improve the identification of clouds from snow during daytime in Polar Regions. We will show global monthly mean cloud fraction for both Terra and Aqua, and show how similar the global daytime cloud fraction is from these morning and afternoon orbits, respectively. We will also show the zonal distribution of cloud fraction over land and ocean regions for both Terra and Aqua, and show the time series of global cloud fraction from July 2002 through June 2006.

King, Michael D.↗

Comparison of CERES-MODIS Stratus Cloud Properties with Ground-Based Measurements at the DOE ARM Southern Great Plains Site

Overcast stratus cloud properties derived for the Clouds and the Earth's Radiant Energy system (CERES) Project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site from March 2000 through December 2004. Retrievals from ARM surface-based data were averaged over a 1-hour interval centered at the time of each satellite overpass, and the CERES-MODIS cloud properties were averaged within a 30-km x 30 km box centered on the ARM SGP site. Two datasets were analyzed: all of the data (ALL) which include multilayered, single-layered, and slightly broken stratus decks and a subset, single-layered unbroken decks (SL). The CERES-MODIS effective cloud heights were determined from effective cloud temperature using a lapse rate method with the surface temperature specified as the 24-h mean surface air temperature. For SL stratus, they are, on average, within the ARM radar-lidar estimated cloud boundaries and are 0.534 +/- 0.542 km and 0.108 +/- 0.480 km lower than the cloud physical tops and centers, respectively, and are comparable for day and night observations. The mean differences and standard deviations are slightly larger for ALL data, but not statistically different to those of SL data. The MODIS-derived effective cloud temperatures are 2.7 +/- 2.4 K less than the surface-observed SL cloud center temperatures with very high correlations (0.86-0.97). Variations in the height differences are mainly caused by uncertainties in the surface air temperatures, lapse rates, and cloud-top height variability. The biases are mainly the result of the differences between effective and physical cloud top, which are governed by cloud liquid water content and viewing zenith angle, and the selected lapse rate, -7.1 K km(exp -1). Based on a total of 43 samples, the means and standard deviations of the differences between the daytime Terra and surface retrievals of effective radius r(sub e), optical depth, and liquid water path for SL stratu are 0.1 +/- 1.9 micrometers (1.2 +/- 23.5%), -1.3 +/- 9.5 (-3.6 +/-26.2%), and 0.6 +/- 49.9 gm (exp -2) (0.3 +/- 27%), respectively, while the corresponding correlation coefficients are 0.44, 0.87, and 0.89. For Aqua, they are 0.2 +/- 1.9 micrometers (2.5 +/- 23.4%), 2.5 +/- 7.8 (7.8 +/- 24.3%), and 28.1 +/- 52.7 gm (exp -2) (17.2 +/- 32.2%), as well as 0.35, 0.96, and 0.93 from a total of 21 cases. The results for ALL cases are comparable. Although a bias in R(sub e) was expected because the satellite retrieval of effective radius only represents the top of the cloud, the surface-based radar retrievals revealed that the vertical profile of r(sub e) is highly variable with smaller droplets occurring at cloud top in some cases. The larger bias in optical depth and liquid water path for Aqua is due, at least partially, to differences in the Terra and Aqua MODIS visible channel calibrations. methods for improving the cloud-top height and microphysical property retrievals are suggested.

Dong, Xiquan↗

Mesofluidic Oil-Water Separation

Separating flowing multiphase solutions in process at industrial scale is challenging. A rapid continuous approach is desired. These mesofluidic oil-water separation tests were motivated by reports by Dijkshoorn et al [1] who reported separating droplets and particles using displacement with regularly spaced channels using a cross-flow microsieve.. Droplets, including deformable particles, larger than the channel migrate in one direction and thereby deplete in the other direction. Test flowrates were motivated by Burns et al. [4] who showed that separation could occur under laminar conditions, and Pease et al [8, 9] who extended the range to turbulent flow. Testing was conducted using two two-component oil-water mixtures at room temperature. Analysis showed separation of both mineral oils from their oil water mixtures at flowrates from 1-2 L/min and concentrations from 2-10 wt% oil in water.

cloud height, effective cleaning radius, effective↗

Estimating Scaled Cloud Height in Pulse Jet Mixed Vessels

To suspend and mix radioactive slurries without pumps or impellers, the performance of pulsed jet mixed vessels has been investigated. The slurry in the pulse tubes is expelled impinging upon the vessel floor and lifting solids to a “cloud height” in a cyclic process. Experiments measuring cloud height for a variety of waste simulants have been conducted for vessel configurations that varied vessel diameter, fill height and pulse tube number, volume, and nozzle diameter. The elevation to which suspended particles rise is termed the cloud height and derives from a balance between the fluid forces of the jet and the gravitational forces acting on the particle ensemble. Here we use scaling to estimate the cloud height based on conservation of mass and momentum and jet similarity. We find that the cloud height varies with the nozzle exit velocity to the 2/3 power in agreement with observations.

cloud height, effective cleaning radius, effective↗

Early Results from the MODIS Atmosphere Cloud Algorithms

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of five instruments aboard the Terra Earth Observing System platform launched in December 1999. With 36 spectral bands from the visible through the infrared, and spatial resolution from 250m to 1km, the instrument provides an unprecedented opportunity for global cloud studies. A comprehensive set of remote sensing algorithms for cloud masking and retrieval of cloud physical and optical properties have been developed by members of the MODIS atmosphere team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud top physical parameters (temperature, pressure, emissivity), cloud phase, cloud optical parameters (optical depth, effective particle radius, water path), visible cirrus reflectance, a contrail flag, and other derived parameters. All products are archived into two categories: pixel-level retrievals at a 1 km or 5 km spatial resolution at nadir (referred to as Level-2 products) and 1 degree global gridded statistics (Level-3 products). An overview of the MODIS atmosphere algorithms and products, their status, validation activities, and early level-2 and -3 results will be presented.

Platnick, S.↗

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar orbiting, sun-synchronous, platform at an altitude of 705 kilometers, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resolutions of 250 meters (2 bands), 500 meters (5 bands) and 1000 meters (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation we review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of (i) developing a cloud mask for distinguishing clear sky from clouds, (ii) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (iii) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (iv) determining atmospheric profiles of moisture and temperature, and (v) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 degree (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented.

King, Michael D.↗

Remote Sensing of Cloud, Aerosol, and Land Properties from MODIS: Applications to the East Asia Region

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (two bands), 500 m (five bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation we review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of (i) developing a cloud mask for distinguishing clear sky from clouds, (ii) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (iii) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (iv) determining atmospheric profiles of moisture and temperature, and (v) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations to the east Asian region in Spring 2001. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 degree (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented.

King, Michael D.↗

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands from 0.415 to 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation I will review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of: (1) developing a cloud mask for distinguishing clear sky from clouds, (2) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (3) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (4) determining atmospheric profiles of moisture and temperature, and (5) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 deg (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented. Finally, I will present some highlights from the land and ocean algorithms developed for processing global MODIS observations, including: (1) surface reflectance, (2) vegetation indices, leaf area index, and FPAR, (3) albedo and nadir BRDF-adjusted reflectance, (4) normalized water-leaving radiance, (5) chlorophyll-a concentration, and (6) sea surface temperature.

King, Michael D.↗

Biomass-burning Aerosols in South East-Asia: Smoke Impact Assessment (BASE-ASIA)

Biomass burning has been a regular practice for land clearing and land conversion in many countries, especially those in Africa, South America, and Southeast Asia. However, the unique climatology of Southeast Asia is very different than that of Africa and South America, such that large-scale biomass burning causes smoke to interact extensively with clouds during the peak-burning season of March to April. Significant global sources of greenhouse gases (e.g., CO2, CH4), chemically active gases (e.g., NO, CO, HC, CH3Br), and atmospheric aerosols are produced by biomass burning processes. These gases influence the Earth-atmosphere system, impacting both global climate and tropospheric chemistry. Some aerosols can serve as cloud condensation nuclei, which play an important role in determining cloud lifetime and precipitation, hence, altering the earth's radiation and water budget. Biomass burning also affects the biogeochemical cycling of nitrogen and carbon compounds from the soil to the atmosphere; the hydrological cycle (i.e., run off and evaporation); land surface reflectivity and emissivity; as well as ecosystem biodiversity and stability. Analyses from satellite measurements reveal that smoke is frequently present solar (emitted thermal) radiation from clouds due to smoke aerosols can be reduced (enhanced) by as much as 100 (20) W/sq m over the month of March 2000. In addition, the reduction in cloud spectral reflectance at 670 run is large enough to lead to significant errors in retrieving cloud properties (e.g., optical thickness and effective radius) from satellite measurements. The fresh water distribution in this region is highly dependent on monsoon rainfall; in fact, the predictability of the tropical climate system is much reduced during the boreal spring. Estimating the burning fuel (e.g., bark, branches, and wood), an important part of studying regional carbon cycle, may rely on utilizing a wide range of distinctive spectral features in the shortwave and longwave regions. Therefore, to accurately assess the impact of smoke aerosols in this region requires continuous observations from satellites, aircraft, networks of ground-based instruments and dedicated field experiments. A new initiative will be proposed and discussed.

Tsay, Si-Chee↗

Biomass-Burning Aerosols in South East-Asia: Smoke Impact Assessment (BASE-ASIA)

Biomass burning has been a regular practice for land clearing and land conversion in many countries, especially those in Africa, South America, and Southeast Asia. However, the unique climatology of Southeast Asia is very different than that of Africa and South America, such that large-scale biomass burning causes smoke to interact extensively with clouds during the peak-burning season of March to April. Significant global sources of greenhouse gases (e.g., CO2, CH4), chemically active gases (e.g., NO, CO, HC, CH3Br), and atmospheric aerosols are produced by biomass burning processes. These gases influence the Earth- atmosphere system, impacting both global climate and tropospheric chemistry. Some aerosols can serve as cloud condensation nuclei, which play an important role in determining cloud lifetime and precipitation, hence, altering the earth s radiation and water budget. Analyses from satellite measurements reveal the reflected solar (emitted thermal) radiation from clouds due to smoke aerosols can be reduced (enhanced) by 100 (20) Watts per square meter over the month of March 2000. In addition, the reduction in cloud spectral reflectance is large enough to lead to significant errors in satellite retrievals of cloud properties (e.g., optical thickness and effective radius). The fresh water distribution in this region is highly dependent on monsoon rainfall; in fact, the predictability of the tropical climate system is much reduced during the boreal spring. Therefore, to accurately assess the impact of smoke aerosols in this region requires continuous observations from satellites, aircraft, ground-based networks and dedicated field experiments. BASE-ASIA initiative has been proposed and will be discussed.

Tsay, S.-C.↗

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)↗