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NASA NTRS2019

Cloud Remote Sensing with EPIC/DSCOVR Observations: A Sensitivity Study with Radiative Transfer Simulations

The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) views nearly the whole sunlit face of the Earth with 10 spectral bands ranging from the UV to the near-infrared, including two oxygen absorbing bands centered at 764 nm (A-band) and 687.75 nm (B-band). Clouds are among the primary remote sensing targets using EPIC images because of their important impacts on the Earth’s radiation budget. In order to facilitate the EPIC cloud data product development, we have built a radiative transfer simulator featuring flexible cloud microphysical parameters, gas absorptions, and the instrument line shape functions for each EPIC band. The radiative transfer simulator is used to explore the sensitivity of EPIC observations on liquid-phase cloud microphysical parameters, including optical depth, geometric thickness, and cloud top height. We found that the ratios of the reflectances in the oxygen A and B bands to their respective continuum measurements can be used to increase the confidence level of cloud masking over scenes with sun-glint. In addition, the 388 nm band can be used to differentiate low and high clouds with the uncertainty of roughly 2–3 km. Combining this information with the oxygen absorption bands, the cloud geometric thickness can be obtained with the rough uncertainty of 3–4 km.

atmospheric and ocean optics↗

NASA NTRS2019

Application of High-Dimensional Fuzzy K-Means Cluster Analysis to CALIOP/CALIPSO Version 4.1 Cloud-Aerosol Discrimination

This study applies fuzzy k-means (FKM) cluster analyses to a subset of the parameters reported in the CALIPSO lidar level 2 data products in order to classify the layers detected as either clouds or aerosols. The results obtained are used to assess the reliability of the cloud–aerosol discrimination (CAD) scores reported in the version 4.1 release of the CALIPSO data products. FKM is an unsupervised learning algorithm, whereas the CALIPSO operational CAD algorithm (COCA) takes a highly supervised approach. Despite these substantial computational and architectural differences, our statistical analyses show that the FKM classifications agree with the COCA classifications for more than 94 % of the cases in the troposphere. This high degree of similarity is achieved because the lidar-measured signatures of the majority of the clouds and the aerosols are naturally distinct, and hence objective methods can independently and effectively separate the two classes in most cases. Classification differences most often occur in complex scenes (e.g., evaporating water cloud filaments embedded in dense aerosol) or when observing diffuse features that occur only intermittently (e.g., volcanic ash in the tropical tropopause layer). The two methods examined in this study establish overall classification correctness boundaries due to their differing algorithm uncertainties. In addition to comparing the outputs from the two algorithms, analysis of sampling, data training, performance measurements, fuzzy linear discriminants, defuzzification, error propagation, and key parameters in feature type discrimination with the FKM method are further discussed in order to better understand the utility and limits of the application of clustering algorithms to space lidar measurements. In general, we find that both FKM and COCA classification uncertainties are only minimally affected by noise in the CALIPSO measurements, though both algorithms can be challenged by especially complex scenes containing mixtures of discrete layer types. Our analysis results show that attenuated backscatter and color ratio are the driving factors that separate water clouds from aerosols; backscatter intensity, depolarization, and mid-layer altitude are most useful in discriminating between aerosols and ice clouds; and the joint distribution of backscatter intensity and depolarization ratio is critically important for distinguishing ice clouds from water clouds.

Zeng, Shan↗

NASA NTRS2015

Formation of Cirrus Clouds near the Tropical Tropopause and Their Implications for Stratospheric Humidity, Radiation Budgets, and Climate

Optically-thin cirrus clouds are a nearly ubiquitous feature of the transition layer between the tropical troposphere and stratosphere (known as the Tropical Tropopause Layer). Given their high occurrence frequency, these clouds have significant impacts on the Earth's radiation budget, with a particularly strong influence on the outgoing longwave radiation. Further, ice crystal growth and sedimentation in these clouds dehydrates air in the cold TTL to very low water vapor mixing ratios. Since transport from the troposphere into the stratosphere occurs primarily through the tropical tropopause and the Brewer-Dobson circulation transports air from the TTL throughout the stratosphere, cloud processes in the TTL cold trap essentially regulate the humidity of the entire stratosphere. It has been shown that even small changes in stratospheric humidity can have significant impacts on the Earth's radiation budget and climate, with magnitudes comparable to anthropogenic changes in greenhouse gases. The humidity of air crossing the TTL cold trap depends to first order on tropical tropopause temperatures, but also on deep convection reaching the TTL, large-scale transport (in balance with TTL radiative heating), atmospheric waves, and cloud microphysical processes. Gaps in our understanding of TTL transport and cloud processes motivated the NASA Airborne Tropical TRopopause EXperiment (ATTREX). ATTREX used the long-range (16,000 km), high-altitude (20 km) Global Hawk unmanned aircraft system equipped with twelve instruments measuring clouds, water vapor, meteorological conditions, chemical tracers, chemical radicals, and radiation. I will discuss the physics of TTL cirrus formation and the impact of these clouds on water vapor and radiation budgets, including new results emerging from the ATTREX measurements.

Jensen, Eric↗

NASA NTRSDate not supplied

Cloud Uniformity Measurement from NASA's 2nd Fundamental Ice Crystal Icing Test - Part 2 (Temperature and Humidity)

This paper provides a characterization of the temperature and humidity variations within icing cloud flows generated during the second Fundamental Ice Crystal Icing Physics test conducted in NASA’s Propulsion Systems Laboratory, in June of 2018. The tests were conducted at airflow velocities of 85, 135, and 185 m/s, a static pressure of 44.8 kPa, and a total temperature of 7.2 ⁰C. A custom rearward facing probe and commercial total air temperature probe were used to obtain temperature and humidity profiles of the icing cloud flow leaving the exit duct plane. Additional background humidity measurements were also obtained from a commercial total water content probe. The probes captured the changes in temperature and humidity that took place at the test section after the cloud was activated. As the main altitude airflow interacts with the icing cloud, their thermodynamic properties undergo substantial changes. Due to the particle nature of the icing cloud, the droplets and ice crystals tend to redistribute within the cloud as it propagates with the main flow. Data will be presented that shows how these factors affect the thermodynamic property distribution within the icing cloud. A discussion is given of the thermal balances in the icing cloud, between the evaporating spray droplets and the airflow, as a basis for interpreting the measured results.

Crystal Icing↗

NASA NTRSDate not supplied

IceCube: Demonstration of an 883 GHz Radiometer for Ice Cloud Remote Sensing

IceCube was a technology demonstration of an 883 GHz heterodyne radiometer on a 3U CubeSat for ice cloud characterization. The project was a collaboration between Goddard Space Flight Center, Virginia Diodes Inc., and Wallops Flight Facility. IceCube was launched to the International Space Station (ISS) in April 2017, and was deployed to the orbit in May 2017. The radiometer measured ice cloud emissions from an ISS orbit for over 15 months. IceCube generated the first 883 GHz cloud map over a large operation temperature range of (5 ºC—37 ºC). Cloud ice plays a major role in the cloud precipitation process and Earth’s energy budget. Ice clouds are used in global circulation models as tuning parameters to achieve model agreement with observation at the top of the atmosphere in the radiation budget and at the bottom for precipitation, however, due to a lack of accurate ice cloud measurements large uncertainties exist in these models. Submillimeter wave remote sensing is capable of addressing this issue by measuring cloud ice mass and microphysical properties in the middle-to-upper troposphere. This fills the sensitivity gap not covered by the visible/infrared and microwave sensors [1]. The goal of IceCube was to increase the TRL of a heterodyne 883 GHz radiometer (using commercial parts) from 5 to 7 by validating the performance in a relevant spaceflight environment. The design of the radiometer was driven by frequency of operation, bandwidth, calibration, available power, and thermal environment requirements. The design included a 15 mm aperture off-axis parabolic reflector with a Potter feed horn, an 883 GHz 2nd-harmonic mixer that is fed by a local oscillator chain with a 24.3 GHz dielectric resonator (MLA), followed by a 6 GHz bandwidth centered at 9 GHz intermediate frequency assembly (IFA), receiver interface card, and power distribution unit. The IFA included an internal noise diode calibration to separate the MLA performance from the rest of the system. For this the radiometer had four operational states: antenna, antenna + noise, reference, and reference + noise; each state’s duration was 10 ms. The total power dissipation of the instrument was 5.6 W. The spacecraft had spinning capabilities to provide a cold sky view for calibration. We present the instrument design, ground test results, challenges, and highlight some of the flight measurements.

N Ehsan↗

NASA NTRS2007

Toward the characterization of upper tropospheric clouds using Atmospheric Infrared Sounder and Microwave Limb Sounder observations

We estimate the accuracy of cloud top altitude (Z) retrievals from the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) observing suite (ZA) on board the Earth Observing System Aqua platform. We compare ZA with coincident measurements of Z derived from the micropulse lidar and millimeter wave cloud radar at the Atmospheric Radiation Measurement (ARM) program sites of Nauru and Manus islands (ZARM) and the inferred Z from vertically resolved Microwave Limb Sounder (MLS) ice water content (IWC) retrievals. The mean difference in ZA minus ZARM plus or minus one standard deviation ranges from −2.2 to 1.6 km ± 1.0 to 4.2 km for all cases of AIRS effective cloud fraction (f A) > 0.15 at Manus Island using the cloud radar only. The range of mean values results from using different approaches to determine ZARM, day/night differences, and the magnitude of f A; the variation about the mean decreases for increasing values of f A. Analysis of ZARM from the micropulse lidar at Nauru Island for cases restricted to 0.05 ≤ f A ≤ 0.15 indicates a statistically significant improvement in ZA − ZARM over the cloud radar-derived values at Manus Island. In these cases the ZA − ZARM difference is −1.1 to 2.1 km ± 3.0 to 4.5 km. These results imply that the operational ZA is quantitatively useful for constraining cirrus altitude despite the nominal 45 km horizontal resolution. Mean differences of cloud top pressure (PCLD) inferred from coincident AIRS and MLS ice water content (IWC) retrievals depend upon the method of defining AIRS PCLD (as with the ARM comparisons) over the MLS spatial scale, the peak altitude and maximum value of MLS IWC, and f A. AIRS and MLS yield similar vertical frequency distributions when comparisons are limited to f A > 0.1 and IWC > 1.0 mg m−3. Therefore the agreement depends upon the opacity of the cloud, with decreased agreement for optically tenuous clouds. Further, the mean difference and standard deviation of AIRS and MLS PCLD are highly dependent on the MLS tangent altitude. For MLS tangent altitudes greater than 146 hPa, the strength of the limb technique, the disagreement becomes statistically significant. This implies that AIRS and MLS “agree” in a statistical sense at lower tangent altitudes and “disagree” at higher tangent altitudes. These results provide important insights on upper tropospheric cloudiness as observed by nadir-viewing AIRS and limb-viewing MLS.

Wu, Dong L.↗

NASA NTRS2020

Sensitivities in Satellite Lidar‐Derived Estimates of Daytime Top‐of‐the‐Atmosphere Optically Thin Cirrus Cloud Radiative Forcing: A Case Study

An optically thin cirrus cloud was profiled concurrently with nadir‐pointing 1,064 nm lidars on 11 August 2017 over eastern Texas, including NASA's airborne Cloud Physics Lidar (CPL) and space‐borne Clouds and Aerosol Transport System (CATS) instruments. Despite resolving fewer (37% vs. 94%) and denser (i.e., more emissive) clouds (average cloud optical depth of 0.10 vs. 0.03, respectively), CATS data render a near‐equal estimate of the top‐of‐atmosphere (TOA) net cloud radiative forcing (CRF) versus CPL. The sample‐relative TOA net CRF solved from CPL is 1.39 W/m2, which becomes 1.32 W/m2 after normalizing by occurrence frequency. Since CATS overestimates extinction for this case, the sample‐relative TOA net forcing is ~3.0 W/m2 larger than CPL, with the absolute value reduced to within 0.3 W/m2 of CPL due its underestimation of cloud occurrence. We discuss the ramifications of thin cirrus cloud detectability from satellite and its impact on attempts at TOA CRF closure.

Erica K. Dolinar↗

NASA NTRS2021

Arctic Cloud Response to a Perturbation in Sea Ice Concentration: The North Water Polynya

Surface and atmosphere energy exchanges play an important role in the Arctic climate system by influencing the lower atmospheric stability and humidity, sea ice melt and growth, and surface temperature. Sea ice significantly alters the character of these energy exchanges relative to ice-free ocean. The observed decline in Arctic sea ice since 1979 motivates questions related to the evolving role of surface-atmosphere coupling and potential feedbacks on the Arctic system. Due to the strong wintertime cloud warming effect, a critical question concerns the potential response of low clouds to Arctic sea ice decline. Previous approaches relied on interannual variability to investigate the cloud response to sea ice decline. However, the covariation between atmospheric conditions and sea ice makes it difficult to define an observational control when using interannual variability. To circumvent this difficulty, we exploit the recurring North Water polynya, an episodic opening in the northern Baffin Bay sea ice, as a natural laboratory to isolate the cloud response to a rapid, near-step perturbation in sea ice. Our results show that during the event, (a) low-cloud cover is 10%–33% larger over the polynya than nearby sea ice, (b) cloud liquid water content is up to 400% larger over the polynya than nearby sea ice, and (c) the surface cloud radiative effect is 18 W/sq. m larger over the polynya than nearby sea ice. Our results provide evidence that the low-cloud response during a polynya is a positive feedback lengthening the event.

Emily E. Monroe↗

NASA NTRSDate not supplied

Observing Ice Phase Clouds and Precipitation with Millimeter- and Submillimeter-wave Radiometry during the IMPACTS field campaign: Algorithm Development for the Emerging Class of Microwave Radiometers

Millimeter- and submillimeter-wave (mmWave, submm) radiometers provide significant information content on atmospheric water in liquid, ice, and vapor phases. Recent sensors, such as the Global Precipitation Measurement (GPM) or the Temporal Experiment for Storms and Tropical Systems Technology – Demonstration (TEMPEST-D), use mmWave bands to improve estimation of ice-phase precipitation, and future missions, such as the Atmosphere Observing System (AOS), will extend to submm to provide additional information on thinner ice clouds, linking clouds and precipitation and therefore elucidating the links between weather, climate, and the water cycle. To support the expanded use of mmWave/submm radiometry and exploit the available information content on condensed water mass, we demonstrate ice and liquid water path retrievals for NASA Goddard Space Flight Center's airborne radiometers the Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) and the Configurable Scanning Submillimeter-wave Instrument/Radiometer (CoSSIR, formerly the Compact Scanning Submillimeter Imaging Radiometer). The analysis is based on data collected during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Storms (IMPACTS) field campaign. A simulation study compares and contrasts retrievals for CoSMIR and CoSSIR, with CoSSIR demonstrating higher skill in ice retrievals, particularly for thin clouds, and the CoSMIR frequencies performing better for liquid. Additionally, we look at dual-polarized radiances observed by CoSMIR during the first two IMPACTS deployments to understand the polarization signatures induced by oriented hydrometeors. Results will be presented in the context of upcoming missions and sensors including AOS and the Ice Cloud Imager (ICI). We will describe the objectives for the expected first flight of the newly upgraded CoSSIR during the final IMPACTS deployment, and we will share novel science investigations we plan to undertake with CoSSIR's new capabilities. Popular Summary: Ice in clouds and falling snow is an important component of weather, climate, and water resources. To better use a new class of sensors that provide information on atmospheric ice, we developed an approach to measure ice clouds and falling snow using airborne data taken during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Storms (IMPACTS), a field campaign to study winter storms. We look at the results for two similar instruments to understand how those differences affect these measurements of clouds and snow, and we further investigate the information the sensors can provide on properties of the clouds and snow.

Ian S Adams↗

NASA NTRSDate not supplied

Implementing Atmospheric Infrared Sounder (AIRS) and Cross-Track Infrared Sounder (CrIS) Cloud-Clearing Algorithm into the NASA GEOS: Focus on the 2017 Atlantic Tropical Cyclone Season

Numerical Weather Prediction (NWP) centers assimilate cloud-free infrared (IR) radiances because the assimilation of all-sky IR radiances is not yet operationally achievable. The cloud-clearing procedure offers a simpler, but effective strategy that produces cloud-affected radiances suitable for assimilation in partially cloudy regions. Several studies conducted by this team have demonstrated that IR Cloud-Cleared Radiances (CCRs), if thinned more aggressively than clear-sky radiances, can improve analysis and forecasts, particularly in meteorologically active areas. However, CCRs are not used by operational centers due partly to the thought that the process of cloud-clearing may affect latency and introduce difficult-to-control external dependencies. This study presents the results of implementing an Atmospheric Infrared Sounder (AIRS) and Cross-Track Infrared Sounder (CrIS) cloud-clearing procedure into the NASA Goddard Earth Observing System (GEOS) to demonstrate the portability of the procedure. The AIRS and CrIS cloud-clearing algorithms have been deprived of external dependencies, made customizable to any specific model, and the computational efficiency has been improved via parallelization. The revised AIRS and CrIS cloud-clearing algorithms allow a customized choice of channel selection, the use of a user-specified model's fields as first guess, and can perform in real time. Data assimilation experiments with the hybrid 4DEnVar GEOS system were successfully performed for the 2017 tropical cyclones (TC) season with a focus on three major hurricanes (Harvey, Irma, and Maria). This study shows that assimilation of locally-generated CCRs have a positive impact on both global skill and TC representation, compared to the assimilation of AIRS and CrIS clear-sky radiances, and a comparable or slightly improved impact compared to assimilation of CCRs produced by external sources, such as NASA's Distributed Active Archive Centers and NOAA’s Comprehensive Large Array-data Stewardship System. The customization and computational efficiency of the revised procedure would enable its usability in a real-time forecast context.

Niama Boukachaba↗

NASA NTRSDate not supplied

Observing Ice Phase Clouds and Precipitation with Millimeter- and Submillimeter-wave Radiometry during the IMPACTS field campaign: Algorithm Development for the Emerging Class of Microwave Radiometers

Ian S Adams↗

NASA NTRS2024

Substantial Cooling Effect From Aerosol-Induced Increase in Tropical Marine Cloud Cover

With global warming currently standing at approximately +1.2 °C since preindustrial times, climate change is a pressing global issue. Marine cloud brightening is one proposed method to tackle warming through injecting aerosols into marine clouds to enhance their reflectivity and thereby planetary albedo. However, because it is unclear how aerosols influence clouds, especially cloud cover, both climate projections and the effectiveness of marine cloud brightening remain uncertain. Here, we use satellite observations of volcanic eruptions in Hawaii to quantify the aerosol fingerprint on tropical marine clouds. We observe a large enhancement in reflected sunlight, mainly due to an aerosol-induced increase in cloud cover. This observed strong negative aerosol forcing suggests that the current level of global warming is driven by a weaker net radiative forcing than previously thought, arising from the competing effects of greenhouse gases and aerosols. This implies a greater sensitivity of Earth’s climate to radiative forcing and therefore a larger warming response to both rising greenhouse gas concentrations and reductions in atmospheric aerosols due to air quality measures. However, our findings also indicate that mitigation of global warming via marine cloud brightening is plausible and is most effective in humid and stable conditions in the tropics where solar radiation is strong.

Atmospheric science↗

NASA NTRSDate not supplied

Parameterization of Vertical Cloud Distribution from C3M and MERRA Data Using ML Method

Clouds play a key role in regulating the hydrological cycle and the Earth's radiative energy budget. However, global climate models (GCMs) with a horizontal grid spacing on the order of 100 km have limitations in representing sub-grid cloud dynamics with spatial scales on the order of 1 km, leading to potential uncertainties in cloud radiative feedback on the global scale. In our research, we will leverage the capabilities of Deep Machine Learning (DML) methods to construct parameterizations of sub-grid volumetric cloud fraction (VCF), which is the frequency of occurrence on a grid volume accumulated in the horizontal and vertical directions. Our investigation delves into the intricate relationship between VCF obtained from the NASA CALIPSO-CloudSat-CERES-MODIS (CCCM) satellite observation data and 3-D MERRA-2 reanalysis meteorological profiling data (e.g., wind, relative humidity, temperature). Through a comprehensive one-year data training utilizing the Sequence to Sequence DML method, we have successfully disentangled the complicated cloud formation dynamics across diverse meteorological conditions through a day-to-day analysis framework. Preliminary findings reveal promising statistical agreements in geographical and vertical distributions and seasonal variations of volumetric cloud fraction between ML prediction and satellite measurements. These results underscore the aptitude of our DML model to discern underlying cloud physical processes and accurately represent sub-grid cloud formation dynamics. Additionally, we have also employed trained neural network to analyze uncertainties arising from errors in meteorological data, further enhancing the robustness of our VCF parameterization.

Shan Zeng↗

NASA NTRSDate not supplied

Ice-Over-Water Cloud Properties in an Artificial Neural Network Approach

Clouds are a crucial component of the atmospheric energy system, particularly the radiative balance within, above, and below the troposphere. The vertical distribution of cloud mass and phase determines layer heating rates, the loss of radiation to space, and the amount of radiative heating at the surface. Thus, it is important to know how clouds are distributed both vertically and horizontally at all times of day. Satellite remote sensing is the only approach available to monitor clouds day and night around the globe. In this paper several artificial neural network (ANN) algorithms, employing several Aqua MODIS infrared channels, profiles of relative humidity and temperature from GMAO numerical weather analyses, and the retrieved total cloud visible optical depth, are trained to detect multilayer ice-over-water cloud systems and to retrieve some of their properties as identified by a year of 2008 Aqua MODIS data matched with CloudSat and CALIPSO (CC) cloud profiles. The CC lidar and radar profiles provide the vertical structure that serves as output truth for the multilayer algorithm. The neural networks were trained using one year (2008) of cloud top height data from the CC dataset, with correlation around 0.94 (0.95) and MAE as low as 0.82 (0.81) km for nonpolar regions during the day (night). Applying the trained ANN to independent year 2009 MODIS data resulted in a combined ML and single layer hit rate of 86.4% (85.1%) for nonpolar regions during the day (night). Since the ANN is trained using near-nadir MODIS pixels, infrared radiance corrections were developed as a function of view zenith angle from MODIS and applied to off-nadir pixels when processing MODIS swath data. The multilayer amount derived with the ANN is relatively invariant with increasing view zenith angle compared to the multilayer amount without the corrections.

MODIS↗

NASA NTRS2024

Iridescence Reveals the Formation and Growth of Ice Aerosols in Martian Noctilucent Clouds

Water and carbon dioxide each form mesospheric clouds on Mars. At such altitudes (40–100 km), clouds may remain sunlit for part of the night. We describe a previously unreported, visually spectacular season of iridescent, noctilucent clouds visible in early southern autumn from the Curiosity rover's site in Gale crater. Ice nucleation begins near sunset with a narrow range of particle sizes, and the ice aerosols grow and precipitate. The iridescence, visible through three-color imaging, arises from locally uniform particle sizes resulting from similar growth histories. Colorful fall streaks show the clouds evolving, and a scattering corona shows size uniformity over large areas. The terminator was observed on the clouds, allowing the determination of cloud altitudes and a likely CO2 composition. This is the first observation of particle size variations within individual Martian clouds, allowing a new probe of Martian cloud physics.

M T Lemmon↗

DOE OSTI2022

Analysis of aerosol cloud interactions with a consistent signal of meteorology and other influencing parameters

Quantifying the impact of aerosols on cloud micro/macro physical properties and estimating the signature of Aerosol Cloud Interactions (ACI) is one of the challenging tasks in atmospheric sciences. The Moderate Resolution Imaging Spectroradiometer and the European Centre for Medium-Range Weather Forecasts ERA-5 reanalysis data are employed to systematically study the ACI over the monsoon region in Pakistan. Based on the monsoon occurrence and rainfall intensity, the whole region is divided into three sub-regions labeled as highly intensive (R1), moderately intensive (R2) and weak (R3) monsoon region. The results indicate that the monthly mean Aerosol Optical Depth (AOD) peaks in the summer monsoon months (Jun, Jul, Aug, Sep). Here, the well-known Twomey effect whereby the Cloud Droplet Radius (CDR) decreases with increasing AOD holds only over R3; the opposite effects (Anti-Twomey effect) are found over R1 and R2, all passing the test of statistical significance (p<0.05). The multi-year AOD is found to be positively correlated with Cloud Liquid Water Path (CLWP) and Cloud Optical Depth (COD) over R1 and R2, suggesting that thicker clouds containing more water droplets are formed in polluted atmosphere. Over R3, decreases in CLWP and COD are found with increasing AOD only when AOD is less than~0.325. The analysis of ACI over R1 and R2 during the winter months shows similar but stronger responses of CDR, CLWP and COD to the variation in AOD. The weaker responses during the summer monsoon season may attributed to the occurrence of high level cloud and unstable atmospheric condition. Further investigation of the influences of Relative Humidity and pressure vertical velocity on the CDR-AOD relationships shows that although the magnitude of the CDR-AOD correlations change with meteorological conditions, the sign of correlations remain unchanged with meteorological conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Climatology of Melting Layer Heights Estimated From Cloud Radar Observations at Various Locations

A melting layer (ML) detection algorithm for cloud radar with polarimetric capability was developed and applied to the cloud radar data collected from five different sites around the world for several years. The retrieved melting layer top height (MLH) showed a very good correspondence with the ECMWF Reanalysis 5 zero degree level data for all five sites. The ML characteristics were distinctively different for different sites, revealing climatological characteristics of ML forming clouds in different regions. Generally, ML tended to occur more frequently in summer than in winter except for a maritime site, where low stratiform clouds formed frequently in summer, the top of which might be lower than the freezing level. In contrast, at two Arctic sites, ML occurred almost exclusively in summer because it was too cold to have an ML in the other seasons. The MLH also varied significantly from site to site but generally was higher during warmer seasons. Based on MLH, two new indices, bulk temperature lapse rate (BLR) and relative depth (RD) of liquid cloud below MLH (RD) were developed, which were useful to explain the environmental characteristics of the five sites. BLR generally increased with the surface temperature at all sites except at the marine site that showed an opposite trend, where a unique synoptic pattern in winter generated high BLR in this cold season. Finally, these findings confirm that studies on thermodynamic structures using cloud radars can be broadened, taking advantage of BLR and RD information, as these indices can represent environmental thermodynamic characteristics of the clouds that have ML.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Scaling of Turbulence and Microphysics in a Convection–Cloud Chamber of Varying Height

Abstract The convection–cloud chamber enables measurement of aerosol and cloud microphysics, as well as their interactions, within a turbulent environment under steady‐state conditions. Increasing the size of a convection–cloud chamber, while holding the imposed temperature difference constant, leads to increased Rayleigh, Reynolds and Nusselt numbers. Large–eddy simulation coupled with a bin microphysics model allows the influence of increased velocity, time, and spatial scales on cloud microphysical properties to be explored. Simulations of a convection–cloud chamber, with fixed aspect ratio and increasing heights of H = 1, 2, 4, and (for dry conditions only) 8 m are performed. The key findings are: Velocity fluctuations scale as H 1/3 , consistent with the Deardorff expression for convective velocity, and implying that the turbulence correlation time scales as H 2/3 . Temperature and other scalar fluctuations scale as H −3/7 . Droplet size distributions from chambers of different sizes can be matched by adjusting the total aerosol injection rate as the horizontal cross‐sectional area (i.e., as H 2 for constant aspect ratio). Injection of aerosols at a point versus distributed throughout the volume makes no difference for polluted conditions, but can lead to cloud droplet size distribution broadening in clean conditions. Cloud droplet growth by collision and coalescence leads to a broader right tail of the distribution compared to condensation growth alone, and this tail increases in magnitude and extent monotonically as the increase of chamber height. These results also have implications for scaling within turbulent, cloudy mixed‐layers in the atmosphere, such as fog layers.

54 ENVIRONMENTAL SCIENCES↗