Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “CLOUDS”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Reconstructing Subgrid Cloud Variability Guided by CloudSat/CALIPSO Observations

Predicting realistic cloud subgrid variability remains a challenge for Global Climate Models (GCMs) even though it can play an important role for proper representation of processes pertaining to cloud microphysics, precipitation, and radiation, but also for comparisons with satellite observations which are of much higher resolution than model grids. The diagnostic approach of subgrid cloud variability is commonly handled by subcolumn cloud generators. For a specific GCM, one ideally wants the subgrid variability used for comparisons with satellite observations to be created by the same generator and with the same rules as the one used for model integration. With this in mind, we have embarked in an effort to test and improve cloud subcolumn generators appropriate for GCMs. For this purpose, we use cloud (hydrometeor) products from active observations by the CloudSat radar (CPR) and the CALIPSO lidar (CALIOP). Cloud products from active sensors while suffering signi􀂦cant sampling and coverage drawbacks have the advantage of resolving both horizontal and vertical variability. The main question is: given a profile of cloud condensate mean and variance, can we create a subgrid cloud field that is statistically similar to the observed subgrid cloud field? By “statistically”, we suggest that we do not aspire to reproduce “well” each individual subgrid cloud field of a GCM-scale region, but that our generator performs well for a large ensemble of cases. We simulate radar, passive imager, and radiation flux fields from the observed 2D cloud fields and create one-point statistics; we use the profiles of cloud condensate mean and variance as input to the generator to create subgrid cloud fields; we compare the statistics; we adjust the rules of the generator to create the best possible agreement between the radar, imager and radiation field statistics. In this process, the active observations have actually a dual role: they provide the actual subgrid cloud field which can be reduced to a profile of mean and variance used by the subcolumn generator, but they also provide the rules needed by the generator, such as measures (e.g, decorrelation length) of the vertical overlap of cloud fraction and of the condensate horizontal variability. This presentation will show our progress using Cloudsat and CALIPSO products in this dual fashion.

clouds↗
NASA NTRSDate not supplied

Evaluating Combined Lidar and Polarimeter Measurements of Cloud Top Parameters (Extinction, Scattering Cross Sections, and Droplet Number Density, Liquid Water Content)

We present a new method to derive profiles of extinction from a lidar which is then combined with polarimeter measurements to derive cloud droplet number density (CDNC) in the tops of warm clouds. The method employs polarization-sensitive elastic backscatter lidar measurements to estimate attenuation of the lidar signal within the cloud and polarimeter estimates of cloud droplet size distributions. The measurements used for this demonstration are from NASA Langley Research Center’s High Spectral Resolution Lidar – Generation 2 (HSRL-2) and NASA GISS’s Research Scanning Polarimeter (RSP). The measurements were acquired on NASA’s ACTIVATE mission, during which the instruments were deployed in a down-looking mode from a high-altitude aircraft, which flew in coordination with a low-flying aircraft acquiring coincident in situ measurements of cloud droplet size and number. The high vertical (1.25 m) and horizontal (~50 m) sampling resolution of the HSRL-2 data enabled retrievals of single-scattering extinction profiles to within ~2.5 optical depths of cloud top. Another key feature of the method was the well-calibrated measurement of backscatter at cloud top due to using the HSRL technique. The RSP retrievals of cloud droplet effective radius and variance were accomplished using the “cloud-bow” technique. Overall, the technique provides extinction profile estimates for the top 2.5 optical depths of water clouds that can be used to estimate the cloud droplet number density in various types of warm clouds. The mean extinction values at cloud top (0-1 optical depth) are compared against cloud drop size and number concentration acquired from wing-mounted probes (e.g., DMT Cloud Droplet Probe - CDP, SPEC Fast Cloud Droplet Probe FCDP, and SPEC 2D Stereo Probe - 2DS) that were deployed on the low-flying aircraft. Comparisons between the effective radius and variance from the polarimeter, lidar ratio (extinction to backscatter) from the lidar and polarimeter, and LWC are also presented. All measurements were acquired over the Western North Atlantic over 3 years from 2020 to 2022.

lidar↗
NASA NTRS1977

Wind estimates from cloud motions - Results from Phases I, II and III of an in situ aircraft verification experiment

An experiment is in progress to verify geostationary-satellite-derived cloud-motion wind estimates by in-situ aircraft wind-velocity measurements. One or more low-level aircraft equipped with Inertial Navigation Systems (INS) were used to define the vertical extent and horizontal motion of a cloud and to measure the ambient wind field. A high-level aircraft, also equipped with an INS, took photographs to describe the horizontal extent of the cloud field and to measure cloud motion. To date the experiment has been conducted over tropical oceans and in the western Gulf of Mexico. A total of 60 h have been spent tracking some 40 tropical cumulus and five cirrus clouds. Results for tropical cumulus clouds indicate excellent agreement between the cloud motion and the wind at cloud base. The magnitude of the vector difference between the cloud motion and the cloud-base wind is less than 1.3 m/s for 67% of the cases with track lengths of 1 h or longer. Similarly, the vector differences between the cloud motion and the wind at sub-cloud (150 m), mid-cloud, and cloud-top levels are 1.5, 3.6 and 7.0 m/s, respectively. The cirrus cloud motions agreed best with the mean wind in the cloud layer with a vector difference of about 1.6 m/s.

Hasler, A. F.↗
NASA NTRS1993

Cloud fields derived from satellite and surface data during FIRE cirrus phase 2

The interpretation of surface and aircraft measurements of cloud properties taken during field programs must take into account the large-scale cloud and meteorological conditions. Cloud properties are also required at scales beyond the point and line data taken from ground and aircraft platforms. Satellite data can provide a quantitative description of these large-scale cloud properties. When derived from geostationary satellite data, the cloud fields constitute a unique source for evaluating the development and demise of a cloud system. Satellites, however, can only see the tops of clouds, so that cloud layers below the uppermost cloud deck may remain undetected resulting in a incomplete depiction of the cloud system. Some multilayer clouds are amenable to detection from satellites. Many, especially in midlatitude cyclonic systems, can only be observed from the surface. A combination of surface and satellite cloud observations should be the most complete quantification of large-scale cloudiness if there are sufficient surface measurements. During the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment Phase 2 (FIRE-2) Cirrus Intensive Field Observation (IFO) period (November 13 - December 7, 1991) conducted at Coffeyville, Kansas, cirrus observations were taken in a variety of conditions. The IFO area was selected for a variety of reasons including the relatively dense network of surface weather stations and special surface instrumentation sites. Thus, the FIRE-2 IFO presents an excellent opportunity to combine cloud observations from surface and satellite observations. This paper presents an analysis of cloud properties on a mesoscale grid using satellite cloud property retrievals, surface observer data, and rawinsonde temperature and humidity profiles.

Minnis, Patrick↗
NASA NTRS1994

Cloud properties inferred from 8-12 micron data

A trispectral combination of observations at 8-, 11-, and 12-micron bands is suggested for detecting cloud and cloud properties in the infrared. Atmospheric ice and water vapor absorption peak in opposite halves of the window region so that positive 8-minus-11-micron brightness temperature differences indicate cloud, while near-zero or negative differences indicate clear regions. The absorption coefficient for water increases more between 11 and 12 microns than between 8 and 11 microns, while for ice, the reverse is true. Cloud phases is determined by a scatter diagram of 8-minus-11-micron versus 11-minus-12-micron brightness temperature differences; ice cloud shows a slope greater than 1 and water cloud less than 1. The trispectral brightness temperature method was tested upon high-resolution interferometer data resulting in clear-cloud and cloud-phase delineation. Simulations using differing 8-micron bandwidths revealed no significant degradation of cloud property detection. Thus, the 8-micron bandwidth for future satellites can be selected based on the requirements of other applications, such as surface characterization studies. Application of the technique to current polar-orbiting High-Resolution Infrared Sounder (HIRS)-Advanced Very High Resolution Radiometer (AVHRR) datasets is constrained by the nonuniformity of the cloud scenes sensed within the large HIRS field of view. Analysis of MAS (MODIS Airborne Simulator) high-spatial resolution (500 m) data with all three 8-, 11-, and 12-micron bands revealed sharp delineation of differing cloud and background scenes, from which a simple automated threshold technique was developed. Cloud phase, clear-sky, and qualitative differences in cloud emissivity and cloud height were identified on a case study segment from 24 November 1991, consistent with the scene. More rigorous techniques would allow further cloud parameter clarification. The opportunities for global cloud delineation with the Moderate-Resolution Imaging Spectrometer (MODIS) appear excellent. The spectral selection, the spatial resolution, and the global coverage are all well suited for significant advances.

Strabala, Kathleen I.↗
NASA NTRS2001

Characterizing the Influence of the General Circulation on Marine Boundary Layer Clouds

The seasonal and intraseasonal variability of boundary layer cloud in the subtropical eastern oceans are studied using combined data from the International Satellite Cloud Climatology Project (ISCCP) and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis. Spectral analysis reveals that most of the time variability of cloud properties occurs on seasonal to annual time scales. The variance decreases one to two orders of magnitude for each decade of time scale decrease, indicating that daily to monthly time scales have smaller, but non-negligible variability. The length of these dominant time scales suggests that the majority of the variability is influenced by the general circulation and its interaction with boundary layer turbulence, rather than a product of boundary layer turbulence alone. Previous datasets have lacked the necessary resolution in either time or in space to properly characterize variability on synoptic scales; this is remedied by using global satellite-retrieved cloud properties. We characterize the intraseasonal subtropical cloud variability in both hemispheres and in different seasons. In addition to cloud fraction, we examine variability of cloud optical thickness - cloud top pressure frequency distributions. Despite the large concentration of research on the variability of Northern Hemisphere (NH) regions during summer, it is noted that the largest amplitude intraseasonal variability in the NH regions occurs during local winter. The effect of intraseasonal variability on the calculation and interpretation of seasonal results is investigated. Decreases in seasonally averaged cloud cover, optical thickness and cloud top pressure from the May-through-September season to the November-through-March season are most apparent in the NH regions. Further analysis indicates that these changes are due to an increase in frequency, but a decrease in the persistence of synoptic events. In addition, changes in cloud top pressure and optical thickness characteristics from the summer to winter seasons indicate that the NH subtropics undergo a change in dynamic regime with season. This change appears in the cloud fields as a shift from the more commonly seen lower-altitude, thicker optical thickness clouds to higher-altitude, thinner clouds. The latter cloud-type is associated with the lower sea level pressure, upward vertical velocity phase of the synoptic wave. Intraseasonal changes in cloud properties in the Southern Hemisphere and NH summer are much smaller in amplitude. Although they also appear to be linked to changes in the large-scale dynamics, similarly to NH winter variations, the relationships are more ambiguous due to the small amplitudes and longer time scales. We attempt to interpret some of these relationships using the results of the Betts and Ridgway (1989) box model. However, these results cannot consistently explain the patterns when results from all regions are considered, implying that this model may not adequately explain all the processes involved in the variability.

Rozendaal, Margaret A.↗
NASA NTRS2003

Using Cloud Top Pressures Derived from Raman Scattering in the UV for the OMI Total Column Ozone Retrievals

The OMI cloud pressure product is necessary for accounting for cloud effects on the mission- critical total ozone product. One of the OM1 cloud pressure algorithms uses UV measurements to derive cloud pressures from the high frequency structure of top- of-atmosphere reflectance caused by rotational Raman scattering (RRS) in the atmosphere. RRS results in filling-in of Fraunhofer lines in the backscatter UV spectra (also known as the Ring effect). The magnitude of filling-in of the Fraunhofer lines is roughly proportional to the average number of solar photon scatterings in the atmosphere above the clouds. This property of RRS is used to deduce an effective cloud pressure. The cloud pressure algorithm retrieves the cloud pressure and cloud fraction using a concept of the Mixed Lambert Equivalent Reflectivity (MLER) also used for the TOMS-V8 OM1 total column ozone algorithm. Currently, this OMI total column ozone algorithm utilizes information about cloud top pressures from a climatology based on IR measurements. The IR-derived cloud top pressure is known to be lower than UV-derived cloud top pressure because UV radiation penetrates clouds deeper than IR radiation. That is why the UV-derived cloud pressure may be more consistent withthe total ozone algorithm. We estimate total column ozone differences caused by replacing the cloud pressure climatology with cloud pressures retrieved from GOME data same as used for retrieval of ozone.

Joiner, J.↗
NASA NTRS2000

Top-of-Atmosphere Albedo Estimation from Angular Distribution Models using Scene Identification from Satellite Cloud Property Retrievals

The next generation of Earth radiation budget satellite instruments will routinely merge estimates of global top-of-atmosphere radiative fluxes with cloud properties. This information will offer many new opportunities for validating radiative transfer models and cloud parameterizations in climate models. In this study, five months of POLarization and Directionality of the Earth's Reflectances (POLDER) 670 nm radiance measurements are considered in order to examine how satellite cloud property retrievals can be used to define empirical Angular Distribution Models (ADMs) for estimating top-of-atmosphere (TOA) albedo. ADMs are defined for 19 scene types defined by satellite retrievals of cloud fraction and cloud optical depth. Two approaches are used to define the ADM scene types: The first assumes there are no biases in the retrieved cloud properties and defines ADMs for fixed discrete intervals of cloud fraction and cloud optical depth (fixed-tau approach). The second approach involves the same cloud fraction intervals, but uses percentile intervals of cloud optical depth instead (percentile-tau approach). Albedos generated using these methods are compared with albedos inferred directly from the mean observed reflectance field. Albedos based on ADMs that assume cloud properties are unbiased (fixed-tau approach) show a strong systematic dependence on viewing geometry. This dependence becomes more pronounced with increasing solar zenith angle, reaching approximately equals 12% (relative) between near-nadir and oblique viewing zenith angles for solar zenith angles between 60 deg and 70 deg. The cause for this bias is shown to be due to biases in the cloud optical depth retrievals. In contrast, albedos based on ADMs built using percentile intervals of cloud optical depth (percentile-tau approach) show very little viewing zenith angle dependence and are in good agreement with albedos obtained by direct integration of the mean observed reflectance field (less than 1% relative error). When the ADMs are applied separately to populations consisting of only liquid water and ice clouds, significant biases in albedo with viewing geometry are observed (particularly at low sun elevations), highlighting the need to account for cloud phase both in cloud optical depth retrievals and in defining ADM scene types. ADM-derived monthly mean albedos determined for all 5 deg x 5 deg latitude/longitude regions over ocean are in good agreement (regional RMS relative errors less than 2%) with those obtained by direct integration when ADM albedos inferred from specific angular bins are averaged together. Albedos inferred from near-nadir and oblique viewing zenith angles are the least accurate, with regional RMS errors reaching approximately 5-10% (relative). Compared to an earlier study involving ERBE ADMs, regional mean albedos based on the 19 scene types considered here show a factor of 4 reduction in bias error and a factor of 3 reduction in RMS error.

Loeb, N. G.↗
NASA NTRS2007

Stable Low Cloud Phase II: Nocturnal Event Study

This report describes the work done by the Applied Meteorology Unit (AMU) in developing a database of nights that experienced rapid (< 90 minutes) low cloud formation in a stable atmosphere, resulting in ceilings at the Shuttle Landing Facility (TTS) that violated Space Shuttle Flight Rules (FR). This work is the second phase of a similar AMU task that examined the same phenomena during the day. In the first phase of this work, the meteorological conditions favoring the rapid formation of low ceilings include the presence of any inversion below 8000 ft, high relative humidity (RH) beneath the inversion and a clockwise turning of the winds from the surface to the middle troposphere (-15000 ft). The AMU compared and contrasted the atmospheric and thermodynamic conditions between nights with rapid low ceiling formation and nights with low ceilings resulting from other mechanisms. The AMU found that there was little to discern between the rapidly-forming ceiling nights and other low ceiling nights at TTS. When a rapid development occurred, the average RH below the inversions was 87% while non-events had an average RH of 79%. One key parameter appeared to be the vertical wind profile in the Cape Canaveral, FL radiosonde (XMR) sounding. Eighty-three percent of the rapid development events had veering winds with height from the surface to the middle troposphere (-15,000 ft) while 61% of the non-events had veering winds with height. Veering winds indicate a warm-advection regime, which supports large-scale rising motion and ultimately cloud formation in a moist environment. However, only six of the nights (out of 86 events examined) with low cloud ceilings had an occurrence of rapidly developing ceilings. Since only 7% rapid development events were observed in this dataset, it is likely that rapid low cloud development is not a common occurrence during the night, or at least not as common as during the day. In the AMU work on the daytime rapid low cloud development (Case and Wheeler 2005), nearly 30% of the low cloud ceiling cases investigated were identified as rapidly developing events. Forecasters at the Space Meteorology Group (SMG) issue 30 to 90 minute forecasts for low cloud ceilings at TTS to support Space Shuttle landings. Mission verification statistics have shown ceilings to be the number one forecast challenge. More specifically, forecasters at SMG are concerned with any rapidly developing clouds/ceilings below 8000 R in a stable, capped thermodynamic environment. Therefore, the AMU was tasked to examine archived events of rapid stable cloud formation resulting in ceilings below 8000 ft, and document the atmospheric regimes favoring this type of cloud development. The AMU examined the cool season months of November to March during the years of 1994-2005 for nights that had low-level inversions and rapid, stable low cloud formation that resulted in ceilings violating the Space Shuttle FR. The AMU wrote and modified existing code to identify inversions from the evening and morning XMR radiosonde during the cool season and output pertinent sounding information. They parsed all days with cloud ceilings below 8000 ft at TTS, forming a database of possible rapidly-developing low ceiling events. Nights with precipitation or noticeable fog burn-off situations were excluded from the database. Only the nighttime hours were examined for possible ceiling development events since the daytime events were examined in the first phase of this work. The report presents one sample case of rapidly-developing low cloud ceilings. The case depicts the representative meteorological and thermodynamic characteristics of such events. The case also illustrates how quickly the cloud decks can develop, sometimes forming in 30 minutes or less. The report also summarizes the composite meteorological conditions for 6 event nights with rapid low cloud ceiling formation and 80 non-events nights consisting of advection or widespread low cloud ceilings. The teorological conditions were quite similar for both the event and non-event nights, since both types of nights experienced low cloud ceilings. Both types of nights had a relatively moist environment beneath an inversion based below 8000 ft.

Bauman, William H., III↗
NASA NTRS2009

Vertical Cloud Climatology During TC4 Derived from High-Altitude Aircraft Merged Lidar and Radar Profiles

Aircraft lidar works by shooting laser pulses toward the earth and recording the return time and intensity of any of the light returning to the aircraft after scattering off atmospheric particles and/or the Earth s surface. The scattered light signatures can be analyzed to tell the exact location of cloud and aerosol layers and, with the aid of a few optical assumptions, can be analyzed to retrieve estimates of optical properties such as atmospheric transparency. Radar works in a similar fashion except it sends pulses toward earth at a much larger wavelength than lidar. Radar records the return time and intensity of cloud or rain reflection returning to the aircraft. Lidar can measure scatter from optically thin cirrus and aerosol layers whose particles are too small for the radar to detect. Radar can provide reflection profiles through thick cloud layers of larger particles that lidar cannot penetrate. Only after merging the two instrument products can accurate measurements of the locations of all layers in the full atmospheric column be achieved. Accurate knowledge of the vertical distribution of clouds is important information for understanding the Earth/atmosphere radiative balance and for improving weather/climate forecast models. This paper describes one such merged data set developed from the Tropical Composition, Cloud and Climate Coupling (TC4) experiment based in Costa Rica in July-August 2007 using the nadir viewing Cloud Physics Lidar (CPL) and the Cloud Radar System (CRS) on board the NASA ER-2 aircraft. Statistics were developed concerning cloud probability through the atmospheric column and frequency of the number of cloud layers. These statistics were calculated for the full study area, four sub-regions, and over land compared to over ocean across all available flights. The results are valid for the TC4 experiment only, as preferred cloud patterns took priority during mission planning. The TC4 Study Area was a very cloudy region, with cloudy profiles occurring 94 percent of the time during the ER-2 flights. One to three cloud layers were common, with the average calculated at 2.03 layers per profile. The upper troposphere had a cloud frequency generally over 30%, reaching 42 percent near 13 km during the study. There were regional differences. The Caribbean was much clearer than the Pacific regions. Land had a much higher frequency of high clouds than ocean areas. One region just south and west of Panama had a high probability of clouds below 15 km altitude with the frequency never dropping below 25% and reaching a maximum of 60% at 11-13 km altitude. These cloud statistics will help characterize the cloud volume for TC4 scientists as they try to understand the complexities of the tropical atmosphere.

Hlavka, Dennis↗
NASA NTRS2010

Detection of Multi-Layer and Vertically-Extended Clouds Using A-Train Sensors

The detection of mUltiple cloud layers using satellite observations is important for retrieval algorithms as well as climate applications. In this paper, we describe a relatively simple algorithm to detect multiple cloud layers and distinguish them from vertically-extended clouds. The algorithm can be applied to coincident passive sensors that derive both cloud-top pressure from the thermal infrared observations and an estimate of solar photon pathlength from UV, visible, or near-IR measurements. Here, we use data from the A-train afternoon constellation of satellites: cloud-top pressure, cloud optical thickness, the multi-layer flag from the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the optical centroid cloud pressure from the Aura Ozone Monitoring Instrument (OMI). For the first time, we use data from the CloudSat radar to evaluate the results of a multi-layer cloud detection scheme. The cloud classification algorithms applied with different passive sensor configurations compare well with each other as well as with data from CloudSat. We compute monthly mean fractions of pixels containing multi-layer and vertically-extended clouds for January and July 2007 at the OMI spatial resolution (l2kmx24km at nadir) and at the 5kmx5km MODIS resolution used for infrared cloud retrievals. There are seasonal variations in the spatial distribution of the different cloud types. The fraction of cloudy pixels containing distinct multi-layer cloud is a strong function of the pixel size. Globally averaged, these fractions are approximately 20% and 10% for OMI and MODIS, respectively. These fractions may be significantly higher or lower depending upon location. There is a much smaller resolution dependence for fractions of pixels containing vertically-extended clouds (approx.20% for OMI and slightly less for MODIS globally), suggesting larger spatial scales for these clouds. We also find higher fractions of vertically-extended clouds over land as compared with ocean, particularly in the tropics and summer hemisphere.

Joiner, J.↗
NASA NTRS2011

Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)

A model evaluation approach is proposed in which weather and climate prediction models are analyzed along a Pacific Ocean cross section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade winds, to the deep convection regions of the ITCZ the Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/ WGNE) Pacific Cross-Section Intercomparison (GPCI). The main goal of GPCI is to evaluate and help understand and improve the representation of tropical and subtropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross section from the subtropics to the tropics for the season June July August of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the 40-yr ECMWF Re-Analysis (ERA-40) in the deep tropics (in particular) with the corresponding impact in the outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid water path and shortwave radiation; significant differences between the models in terms of vertical cross sections of cloud properties (in particular), vertical velocity, and relative humidity. An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of some models and ERA-40 in the stratocumulus regions [as compared to the first International Satellite Cloud Climatology Project (ISCCP)] is associated not only with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition that occurs too early along the trade wind Lagrangian trajectory. Histograms of cloud cover along the cross section differ significantly between models. Some models exhibit a quasi-bimodal structure with cloud cover being either very large (close to 100%) or very small, while other models show a more continuous transition. The ISCCP observations suggest that reality is in-between these two extreme examples. These different patterns reflect the diverse nature of the cloud, boundary layer, and convection parameterizations in the participating weather and climate prediction models.

Teixeira, J.↗
NASA NTRS2019

Polarimetric Retrievals of Cloud Droplet Number Concentrations

Cloud droplet number concentration (Nd) is an important parameter of liquid clouds and is crucial to understanding aerosol-cloud interactions. It couples boundary layer aerosol composition, size and concentration with cloud reflectivity. It affects cloud evolution, precipitation, radiative forcing, global climate and, through observation, can be used to partially monitor the first indirect effect. With its unique combination of multi-wavelength, multi-angle, total and polarized reflectance measurements, the Research Scanning Polarimeter (RSP) retrieves Nd with relatively few assumptions. The approach involves measuring cloud optical thickness, mean droplet extinction cross-section and cloud physical thickness. Polarimetric observations are capable of measuring the effective variance, or width, of the droplet size distribution. Estimating cloud geometrical thickness is also an important component of the polarimetric Nd retrieval, which is accomplished using polarimetric measurements in a water vapor absorption band to retrieve the amount of in-cloud water vapor and relating this to physical thickness. We highlight the unique abilities and quantify uncertainties of the polarimetric approach. We validate the approach using observational data from the North Atlantic and Marine Ecosystems Study (NAAMES). NAAMES targets specific phases in the seasonal phytoplankton lifecycle and ocean-atmosphere linkages. This study provides an excellent opportunity for the RSP to evaluate its approach of sensing Nd over a range of concentrations and cloud types with in situ measurements from a Cloud Droplet Probe (CDP). The RSP and CDP, along with an array of other instruments, are flown on the NASA C-130 aircraft, which flies in situ and remote sensing legs in sequence. Cloud base heights retrieved by the RSP compare well with those derived in situ (R=0.83) and by a ceilometer aboard the R.V. Atlantis (R=0.79). Comparing geometric mean values from 12 science flights throughout the NAAMES-1 and NAAMES-2 campaigns, we find a strong correlation between Nd retrieved by the RSP and CDP (R=0.96). A linear least squares fit has a slope of 0.92 and an intercept of 0.3 cm−3. Uncertainty in this comparison can be attributed to cloud 3D effects, nonlinear liquid water profiles, multilayered clouds, measurement uncertainty, variation in spatial and temporal sampling, and assumptions used within the method. Radiometric uncertainties of the RSP measurements lead to biases on derived optical thickness and cloud physical thickness, but these biases largely cancel out when deriving Nd for most conditions and geometries. We find that a polarimetric approach to sensing Nd is viable and the RSP is capable of accurately retrieving Nd for a variety of cloud types and meteorological conditions.

Droplet concentration↗
NASA NTRSDate not supplied

ENSO Tropical Cloud and TOA radiative signatures from the CERES observation

The Clouds and the Earth's Radiant Energy System (CERES) project now has over 15 years accurately observed top-of-the-atmosphere (TOA) flux record for climate monitoring and diagnostic studies. The CERES flux-by-cloud-type dataset, which contains cloud properties and radiative fluxes for 42 cloud types sorted by cloud top pressure and cloud optical depth, is used to investigate the clouds and their associated TOA (top-of-the-atmosphere) fluxes changes over the tropical area during ENSO events during the observed period. Unlike past studies, this study shows the impact of ENSO on cloud properties like optical depth, cloud top effective pressure and temperature and TOA LW and SW fluxes for each sub cloud type. The study reveals the detailed contributions from different cloud types for radiative characteristics during different phases of ENSO. This is especially important for very small net TOA radiative balance due to the cancellation of the fluxes from different cloud types. To further demonstrate the usefulness of this dataset, NCAR Community Atmosphere Model (CAM) is used to simulate the cloud and radiative changes during the period. The model cloud properties are converted to MODIS like cloud properties using modified MODIS simulator. The dataset serves as a more stringent validation of the model for cloud properties and radiative fluxes.

Moguo Sun↗
NASA NTRS2015

Remote Sensing of Cloud Top Heights Using the Research Scanning Polarimeter

Clouds cover roughly two thirds of the globe and act as an important regulator of Earth's radiation budget. Of these, multilayered clouds occur about half of the time and are predominantly two-layered. Changes in cloud top height (CTH) have been predicted by models to have a globally averaged positive feedback, however observational changes in CTH have shown uncertain results. Additional CTH observations are necessary to better and quantify the effect. Improved CTH observations will also allow for improved sub-grid parameterizations in large-scale models and accurate CTH information is important when studying variations in freezing point and cloud microphysics. NASA's airborne Research Scanning Polarimeter (RSP) is able to measure cloud top height using a novel multi-angular contrast approach. RSP scans along the aircraft track and obtains measurements at 152 viewing angles at any aircraft location. The approach presented here aggregates measurements from multiple scans to a single location at cloud altitude using a correlation function designed to identify the location-distinct features in each scan. During NASAs SEAC4RS air campaign, the RSP was mounted on the ER-2 aircraft along with the Cloud Physics Lidar (CPL), which made simultaneous measurements of CTH. The RSPs unique method of determining CTH is presented. The capabilities of using single and combinations of channels within the approach are investigated. A detailed comparison of RSP retrieved CTHs with those of CPL reveal the accuracy of the approach. Results indicate a strong ability for the RSP to accurately identify cloud heights. Interestingly, the analysis reveals an ability for the approach to identify multiple cloud layers in a single scene and estimate the CTH of each layer. Capabilities and limitations of identifying single and multiple cloud layers heights are explored. Special focus is given to sources of error in the method including optically thin clouds, physically thick clouds, multi-layered clouds as well as cloud phase. When determining multi-layered CTHs, limits on the upper clouds opacity are assessed.

Cloud height indicators↗
NASA NTRSDate not supplied

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided many statistics on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus was segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution possible for capturing cloud initiation and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool, strategies to identify development stages from cloud tracks, and preliminary results that document cumulus lifecycle properties from satellite. The application of AHI 0.5-km reflectance has both strengths and limitations when attempting to track lifecycles of the smallest resolvable clouds. We show that by aggregating cloud tracks from a few case studies of CAMP2EX, we can discern differences in cloud lifetime and development according to ensembles selected from areas of interest. The results demonstrate an ability to quantify lifetimes and assess rates of change in cloud characteristics that are likely controlled by the surrounding environment and meteorology.

Cloud Tracking↗
NASA NTRS2022

Detailing Cloud Property Feedbacks with a Regime-Based Decomposition

Diagnosing the root causes of cloud feedback in climate models and reasons for inter-model disagreement is a necessary first step in understanding their wide variation in climate sensitivities. Here we bring together two analysis techniques that illuminate complementary aspects of cloud feedback. The first quantifies feedbacks from changes in cloud amount, altitude, and optical depth, while the second separates feedbacks due to cloud property changes within specific cloud regimes from those due to regime occurrence frequency changes. We find that in the global mean, shortwave cloud feedback averaged across ten models comes solely from a positive within-regime cloud amount feedback countered slightly by a negative within-regime optical depth feedback. These within-regime feedbacks are highly uniform: In nearly all regimes, locations, and models, cloud amount decreases and cloud albedo increases with warming. In contrast, global-mean across-regime components vary widely across models but are very small on average. This component, however, is dominant in setting the geographic structure of the shortwave cloud feedback: Thicker, more extensive cloud types increase at the expense of thinner, less extensive cloud types in the extratropics, and vice versa at low latitudes. The prominent negative extratropical optical depth feedback has contributions from both within- and across-regime components, suggesting that thermodynamic processes affecting cloud properties as well as dynamical processes that favor thicker cloud regimes are important. The feedback breakdown presented herein may provide additional targets for observational constraints by isolating cloud property feedbacks within specific regimes without the obfuscating effects of changing dynamics that may differ across timescales.

climate sensitivity↗
NASA NTRS2013

Estimating the Direct Radiative Effect of Absorbing Aerosols Overlying Marine Boundary Layer Clouds in the Southeast Atlantic Using MODIS and CALIOP

Absorbing aerosols such as smoke strongly absorb solar radiation, particularly at ultraviolet and visible/near-infrared (VIS/NIR) wavelengths, and their presence above clouds can have considerable implications. It has been previously shown that they have a positive (i.e., warming) direct aerosol radiative effect (DARE) when overlying bright clouds. Additionally, they can cause biased passive instrument satellite retrievals in techniques that rely on VIS/NIR wavelengths for inferring the cloud optical thickness (COT) and effective radius (re) of underlying clouds, which can in turn yield biased above-cloud DARE estimates. Here we investigate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical property retrieval biases due to overlying absorbing aerosols observed by Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and examine the impact of these biases on above-cloud DARE estimates. The investigation focuses on a region in the southeast Atlantic Ocean during August and September (2006-2011), where smoke from biomass burning in southern Africa overlies persistent marine boundary layer stratocumulus clouds. Adjusting for above-cloud aerosol attenuation yields increases in the regional mean liquid COT (averaged over all ocean-only liquid clouds) by roughly 6%; mean re increases by roughly 2.6%, almost exclusively due to the COT adjustment in the non-orthogonal retrieval space. It is found that these two biases lead to an underestimate of DARE. For liquid cloud Aqua MODIS pixels with CALIOP-observed above-cloud smoke, the regional mean above-cloud radiative forcing efficiency (DARE per unit aerosol optical depth (AOD)) at time of observation (near local noon for Aqua overpass) increases from 50.9Wm(sup-2)AOD(sup-1) to 65.1Wm(sup-2)AOD(sup -1) when using bias-adjusted instead of nonadjusted MODIS cloud retrievals.

aerosols↗