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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

3D Shortwave Radiative Kernels of Marine Boundary-layer Clouds Using Scanning Radar/Lidar and Array Spectroradiometer

This project set out to use synergetic measurements from the ARM program to observe 3D cloud field observations, and to investigate how inadequate treatment of the observed 3D characteristics of clouds in models may impact estimates of low-cloud feedback magnitude. The project comprises three components, including 1) retrieving cloud and precipitation properties, 2) developing fast radiative transfer code incorporating 3D cloud effects, and 3) estimating 3D effects/impacts on a global scale. This report documents our main research outcomes. Specifically, a novel cloud retrieval method is developed, allowing us to better characterize cloud population and sizes, drizzle properties and precipitation formation, and to better understand their interactions with aerosols. These observed 3D cloud fields were used in a fast radiative transfer code, helping discover non-negligible 3D radiative effects in the longwave spectral region. The retrieved cloud properties were also used to investigate several hypothesized cloud feedback processes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Evaluation of NCAR CAM5 simulated marine boundary layer cloud properties using a combination of satellite and surface observations

Marine boundary layer (MBL) clouds are a strong modulator of Earth’s radiative energy budget. The feedback of MBL clouds in a changing climate remains one of the largest uncertainties in our understanding of climate sensitivity, and recent studies have also suggested that radiative feedbacks related to MBL clouds may play an important role in low-frequency climate variabilities such as the Atlantic multidecadal oscillation. Despite their importance in the climate system, simulating MBL clouds in Earth system models (ESMs) has proved to be extremely challenging. The overarching objective of this proposal is to evaluate the MBL cloud simulation skills of the CAM5 with different cloud parameterization schemes through systematic comparison with both ground- and satellite based cloud observations. In particular, we seek to understand the advantages and limitations of the newly developed subgrid cloud parameterization scheme CLUBB (Cloud Layers Unified By Binormals) for simulation MBL clouds through comparisons of CAM5-CLUBB simulations with ARM (CAP-MBL campaign data) and satellite observations, as well as the “conventional” CAM5 and a CAM5 with the so-called super-parameterization (i.e., CAM5-MMF). In the rest of this report, we will briefly highlight our major research achievements.

58 GEOSCIENCES↗
DOE OSTI2020

Improving GCM Predictability of Mixed-Phase Clouds and Aerosol Interactions at High Latitudes with ARM Observations

The overachieving goal of this project is to improve the predictability of mixed-phase clouds and aerosol interactions in the Community Atmosphere Model version 6 (CAM6) through comparison with the ARM observations. There are three main objectives of the proposed study: (1) Improve the representation of ice microphysical processes in mixed-phase clouds; (2) Test the performance of ice microphysics in CESM-CAM6 with the ARM observations in northern and southern high latitudes; and (3) Examine mixed-phase cloud microphysics-aerosol-turbulence-radiation interactions in CESM-CAM6. In this project, we have (1) Improved the representation of ice microphysical processes in mixed-phase clouds in CESM-CAM6 by implementing the marine organic aerosol (MOA) and treating the ice nucleating particles (INPs) from MOA and its impacts on mixed-phase clouds. We improved the treatment of ice depositional growth through the Wegener–Bergeron–Findeisen (WBF) process by considering the subgrid heterogeneous distributions between liquid droplets and ice crystals in mixed-phase clouds; (2) Tested the performance of ice microphysics in CESM-CAM6 with the ARM observations at high latitudes. We compared the simulated INP concentrations with the ARM observations, e.g., from M-PACE, ISDAC, INPOP, and other data (Mace Head, Zeppelin, CAPRICORN). We examined the impact of improved WBF treatment on model simulated Arctic mixed-phase clouds observed in the M-PACE field campaign. Seasonal variations of modeled mixed-phase cloud properties (LWO, IWP) are compared with the ground-based remote sensing retrievals at the ARM’s NSA $Utqia\dot{g}vik$ site; and (3) Examined mixed-phase cloud microphysics-aerosol-dynamics-radiation interactions in CESM-CAM6 that include the impacts of MOA INPs, and impacts of different model parameterizations (CLUBB versus UW turbulence & shallow convection schemes, MG2 versus MG1) on high-latitude mixed-phase cloud properties. Aerosol indirect effects of MOA through the liquid phase (droplet activation) and ice phase processes (e.g., the glaciation indirect effect) were investigated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Beirut Explosion Yield and Mushroom Cloud Height - Effects of the Source Environment

I use crater dimensions to estimate the yield of the August 4th, 2020 Beirut explosion to be equivalent to approximately 1.4 kilotons of TNT with a lower bound of about 0.7 kilotons. Based on the amount of ammonium nitrate reported to have been stored at the Beirut harbor, I assume an upper bound for the yield of 2.75 kilotons. However, it is highly likely that the yield was less than 2.75 kilotons, since reported values for TNT equivalence of ammonium nitrate are typically much less than one hundred percent. The crater-size based yield estimates are based on crater radius estimates from satellite imagery and empirical curves and data for scaled crater radius from past chemical and nuclear explosions. I present evidence that suggests that the relatively large crater radius is due to a high degree of coupling of shock wave energy to the surrounding medium and a reduction of the effective stress because of a high level of saturation of the geologic media beneath the explosion. I provide yield estimates based on seismic body-wave magnitude and crater depth as corroborating evidence. I compare preliminary estimates for the maximum debris cloud height, based on cell phone videos/images, with predicted maximum heights for this yield range from empirical formulas and numerical cloud-rise models. Based on a preliminary analysis of cell phone footage, the observed maximum cloud height appears to be approximately 1600 m. This is much lower than that predicted using standard empirical formulas and buoyant cloud rise models. I present results from a modified buoyant cloud rise model that more accurately predicts the maximum cloud height by allowing for the inclusion of a fixed amount of air and/or water into the fireball at the start of cloud rise. The amount of mass that needs to be added at the start, to reproduce the observed maximum cloud height, is relatively small compared to the total mass entrained during cloud rise. A much greater amount of dry air or debris is required, relative to water, for an equivalent reduction in maximum cloud height. The ammonium nitrate is one possible source for water in the fireball since it was being stored in a very humid environment and ammonium nitrate is known to be hygroscopic. The ground beneath the explosion, especially if it were saturated, and the nearby harbor could also have been sources for water or debris in the fireball.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Three-Channel Sunphotometer Cloud Mode Value-Added Product Report

A primary source of uncertainty in Earth system model (ESM) predictions is the representation of cloud processes and associated cloud feedback. Several fundamental cloud properties critical to the understanding of aerosol-cloud interactions are poorly constrained by observations, with key deficiencies in our observations of cloud and precipitation droplet sizes and cloud optical depth. Observations of these cloud properties are often challenging to estimate from remote-sensing platforms and costly to obtain from in situ aircraft. Nevertheless, observations of boundary-layer clouds, and improved knowledge of stratocumulus cloud (Sc) processes, are especially important to ESM advancement. This is because these clouds have extensive coverage and exert controls on boundary-layer dynamics and the global radiative energy balance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Final report: Insights from ARM observations into aerosol processing and transport by extratropical cyclones and aerosol effects on cyclone clouds

This project advanced understanding of aerosol–cloud interactions in extratropical cyclones using observations from the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) observatory and ACE-ENA field campaigns, along with satellite datasets and numerical modeling. We have quantified the susceptibility of frontal clouds to aerosols, showing that this susceptibility is similar to that in non-frontal clouds despite substantial (factor 2) differences in droplet concentrations between these cloud types, and also significant differences in cloud albedo. A key finding was that Aitken-mode (here, 60-100nm diameter) aerosols play a disproportionately important role in droplet activation in frontal clouds, and concentrations of these particles are frequently strongly biased in climate models. Activation of aerosols depends strongly on updraft speeds, and via collaboration with Argonne National Laboratory we contributed to quantifying these better with the ARM radar wind profiler at the ENA site. Our studies in the North Atlantic have analogs in the Southern Ocean, and to draw these out we examined data from the MARCUS and SOCRATES field campaigns. We identified new particle formation within extratropical cyclones as a potentially important source of cloud condensation nuclei in these pristine marine environments. By combining ARM observations with perturbed parameter ensemble simulations, we demonstrated that surface observations can effectively constrain aerosol–cloud adjustments and reduce uncertainty in simulated cloud liquid water path responses by approximately 15%, yielding stronger constraints on historical aerosol cooling effects. The work further established precipitation processes as a dominant control on aerosol–cloud interactions and Earth system predictability.

Gordon, Hamish [Department of Chemical Engineering↗
DOE OSTI2016

A long-term study of aerosol–cloud interactions and their radiative effect at the Southern Great Plains using ground-based measurements

Empirical estimates of the microphysical response of cloud droplet size distribution to aerosol perturbations are commonly used to constrain aerosol–cloud interactions in climate models. Instead of empirical microphysical estimates, here macroscopic variables are analyzed to address the influence of aerosol particles and meteorological descriptors on instantaneous cloud albedo and the radiative effect of shallow liquid water clouds. Long-term ground-based measurements from the Atmospheric Radiation Measurement (ARM) program over the Southern Great Plains are used. A broad statistical analysis was performed on 14 years of coincident measurements of low clouds, aerosol, and meteorological properties. Here two cases representing conflicting results regarding the relationship between the aerosol and the cloud radiative effect were selected and studied in greater detail. Microphysical estimates are shown to be very uncertain and to depend strongly on the methodology, retrieval technique and averaging scale. For this continental site, the results indicate that the influence of the aerosol on the shallow cloud radiative effect and albedo is weak and that macroscopic cloud properties and dynamics play a much larger role in determining the instantaneous cloud radiative effect compared to microphysical effects. On a daily basis, aerosol shows no correlation with cloud radiative properties (correlation = -0.01 ± 0.03), whereas the liquid water path shows a clear signal (correlation = 0.56 ± 0.02).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Impacts of solar-absorbing aerosol layers on the transition of stratocumulus to trade cumulus clouds

Abstract. The effects of an initially overlying layer of solar-absorbing aerosol on the transition of stratocumulus to trade cumulus clouds are examined using large-eddy simulations. For lightly drizzling cloud the transition is generally hastened, resulting mainly from increased cloud droplet number concentration (Nc) induced by entrained aerosol. The increased Nc slows sedimentation of cloud droplets and shortens their relaxation time for diffusional growth, both of which accelerate entrainment of overlying air and thereby stratocumulus breakup. However, the decrease in albedo from cloud breakup is more than offset by redistributing cloud water over a greater number of droplets, such that the diurnal-average shortwave forcing at the top of the atmosphere is negative. The negative radiative forcing is enhanced by sizable longwave contributions, which result from the greater cloud breakup and a reduced boundary layer height associated with aerosol heating. A perturbation of moisture instead of aerosol aloft leads to a greater liquid water path and a more gradual transition. Adding absorbing aerosol to that atmosphere results in substantial reductions in liquid water path (LWP) and cloud cover that lead to positive shortwave and negative longwave forcings on average canceling each other. Only for heavily drizzling clouds is the breakup delayed, as inhibition of precipitation overcomes cloud water loss from enhanced entrainment. Considering these simulations as an imperfect proxy for biomass burning plumes influencing Namibian stratocumulus, we expect regional indirect plus semi-direct forcings to be substantially negative to negligible at the top of the atmosphere, with its magnitude sensitive to background and perturbation properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Subgrid variations of the cloud water and droplet number concentration over the tropical ocean: satellite observations and implications for warm rain simulations in climate models

Abstract. One of the challenges in representing warm rain processes in global climate models (GCMs) is related to the representation of the subgrid variability of cloud properties, such as cloud water and cloud droplet number concentration (CDNC), and the effect thereof on individual precipitation processes such as autoconversion. This effect is conventionally treated by multiplying the resolved-scale warm rain process rates by an enhancement factor ( E q ) which is derived from integrating over an assumed subgrid cloud water distribution. The assumed subgrid cloud distribution remains highly uncertain. In this study, we derive the subgrid variations of liquid-phase cloud properties over the tropical ocean using the satellite remote sensing products from Moderate Resolution Imaging Spectroradiometer (MODIS) and investigate the corresponding enhancement factors for the GCM parameterization of autoconversion rate. We find that the conventional approach of using only subgrid variability of cloud water is insufficient and that the subgrid variability of CDNC, as well as the correlation between the two, is also important for correctly simulating the autoconversion process in GCMs. Using the MODIS data which have near-global data coverage, we find that E q shows a strong dependence on cloud regimes due to the fact that the subgrid variability of cloud water and CDNC is regime dependent. Our analysis shows a significant increase of E q from the stratocumulus (Sc) to cumulus (Cu) regions. Furthermore, the enhancement factor E N due to the subgrid variation of CDNC is derived from satellite observation for the first time, and results reveal several regions downwind of biomass burning aerosols (e.g., Gulf of Guinea, east coast of South Africa), air pollution (i.e., East China Sea), and active volcanos (e.g., Kilauea, Hawaii, and Ambae, Vanuatu), where the E N is comparable to or even larger than E q , suggesting an important role of aerosol in influencing the E N . MODIS observations suggest that the subgrid variations of cloud liquid water path (LWP) and CDNC are generally positively correlated. As a result, the combined enhancement factor, including the effect of LWP and CDNC correlation, is significantly smaller than the simple product of E q ∙ E N . Given the importance of warm rain processes in understanding the Earth's system dynamics and water cycle, we conclude that more observational studies are needed to provide a better constraint on the warm rain processes in GCMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The prevalence of precipitation from polar supercooled clouds

Abstract. Supercooled clouds substantially impact polar surface energy budgets, but large-scale models often underestimate their occurrence, which motivates accurately establishing metrics of basic processes. An analysis of long-term measurements at Utqiaġvik, Alaska, and McMurdo Station, Antarctica, combines lidar-validated use of soundings to identify supercooled cloud layers and colocated ground-based profiling radar measurements to quantify cloud base precipitation. We find that more than 85 % (75 %) of sampled supercooled layers are precipitating over the Arctic (Antarctic) site, with more than 75 % (50 %) precipitating continuously to the surface. Such high frequencies can be reconciled with substantially lesser spaceborne estimates by considering differences in radar hydrometeor detection sensitivity. While ice precipitation into supercooled clouds from aloft is common, we also find that the great majority of supercooled cloud layers without ice falling into them are themselves continuously generating precipitation. Such sustained primary ice formation is consistent with continuous activation of immersion-mode ice-nucleating particles (INPs), suggesting that supercooled cloud formation is a principal gateway to ice formation at temperatures greater than ∼-38 ∘C over polar regions. The prevalence of weak precipitation fluxes is also consistent with supercooled cloud longevity and with well-observed and widely simulated case studies. An analysis of colocated microwave radiometer retrievals suggests that weak precipitation fluxes can be nonetheless consequential to moisture budgets for supercooled clouds owing to small liquid water paths. The results here also demonstrate that the observed abundance of mixed-phase clouds can vary substantially with instrument sensitivity and methodology. Finally, we suggest that these ground-based precipitation rate statistics offer valuable guidance for improving the representation of polar cloud processes in large-scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The diurnal susceptibility of subtropical clouds to aerosols

The diurnal susceptibility of clouds and their radiative properties to aerosols is examined during their Lagrangian transition from subtropical stratocumulus to shallow cumulus regimes. Using large-eddy simulations, we analyze the six-day evolution of an air mass along a 3800 km observed trajectory from the coast of Peru toward the equator. Pristine and polluted scenarios are simulated with forcing imposed from weather reanalysis. The polluted scenario exhibits stronger diurnal variations in cloud water, cloud fraction, and albedo, with enhanced nighttime entrainment and suppressed precipitation. The overall response of cloud properties and outgoing shortwave radiation to droplet number concentration follows a distinct diurnal pattern: strong positive cloud adjustments dominate at night and in the morning, while weak negative adjustments prevail in the afternoon. This cycle is driven by the competition between precipitation suppression, which enhances cloud water and coverage, and entrainment drying, which depletes them. In polluted conditions, enhanced entrainment leads to a deeper and more decoupled boundary layer that cannot be sustained by surface fluxes in the afternoon, resulting in negative cloud adjustments. The enhanced entrainment rate under polluted conditions is caused by the reduced sedimentation of cloud and precipitation water from the entrainment zone. While the Twomey effect dominates the diurnal average albedo response, the diurnal variation in the competing cloud adjustments lead to a near-neutral net susceptibility in the afternoon, highlighting the critical role of diurnally varying processes in aerosol-cloud interactions.

Geosciences↗
DOE OSTI2025

Marine and continental stratocumulus cloud microphysical properties obtained from routine ARM Cimel sunphotometer observations

This study investigates marine and continental stratocumulus (Sc) cloud properties obtained from an automated implementation of a multispectral photometer retrieval. Photometer methods simultaneously retrieve cloud optical depth (τ) and cloud droplet effective radius (r e ), with estimates for liquid water path (LWP) calculated on the availability of those quantities. These applied methods evaluate retrieved cloud properties for Sc identified during a recent 6 year period over the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program sites in Oklahoma, USA (SGP) and in the Azores, Portugal (ENA). Modest agreement in key quantity retrievals is found between the routine photometer products and multisensor collocated profiling references. Cumulative breakdowns contingent on cloud thickness indicate increases in all retrieved quantities in thicker clouds, with larger discrepancies in the relative performance between the retrievals collected in the presence of drizzle. Under continental cloud conditions, the clouds of a similar thickness and r e to those sampled under marine conditions report a factor of 1.5 larger τ and LWP. An r 2 ≅0.65 is found between photometer τ retrievals and shadowband radiometer measurements, with photometer retrievals reporting a high (relative) bias. The τ intercomparisons indicate that variability between retrievals is a factor of three larger than errors reported from individual retrieval input perturbation tests. Photometer r e retrievals suggest a low r 2 (< 0.1) having a standard deviation ≅ 3 µm when compared to ARM baseline multi-sensor radar/radiometer references (accounting for offsets in the cloud droplet number concentration assumptions of the latter). However, photometer LWP calculations remain relatively unbiased in non-drizzling conditions, with errors O (50 g m −2 ) and r 2 ≅0.5 to collocated radiometer and interferometer references. Additional sensitivity tests for island influences on marine Sc properties suggest that while island-influenced winds may promote larger cloud LWP or thickness, the influence could be within retrieval method uncertainty and/or collocated instrument variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains

Abstract. Based on long-term observations at the Southern Great Plains site by the Atmospheric Radiation Measurement (ARM) program for training and validation, a deep-learning model is developed to simulate the daytime evolution of boundary layer clouds (BLCs) from the perspective of land–atmosphere coupling. The model takes ARM measurements (including early-morning soundings and diurnally varying surface meteorological conditions and heat fluxes) as inputs and predicts hourly estimates (including cloud occurrence, the positions of cloud boundaries, and the vertical profile of the cloud fraction) as outputs. The deep-learning model offers good agreement with the observed cloud fields, especially in the accuracy with which cloud occurrence and base height are reproduced. When the inputs are substituted by reanalysis data from ERA5 and MERRA-2, the outputs of the deep-learning model provide a better agreement with observation than the cloud fields extracted from ERA5 and MERRA-2 themselves. Thus, the deep-learning model shows great potential to serve as a diagnostic tool for the performance of physics-based models in simulating stratiform and cumulus clouds. By quantifying biases in clouds and attributing them to the simulated atmospheric state variables versus the model-parameterized cloud processes, this observation-based deep-learning model may offer insights into the directions needed to improve the simulation of BLCs in physics-based models for weather forecasting and climate prediction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Arctic Mixed-Phase Cloud Base Ice Precipitation Properties During the M-PACE Field Campaign

Cloud-climate feedbacks are still the greatest source of uncertainty in current climate projections. Arctic clouds, which are predominantly stratiform and supercooled, often long-lived, and nearly-continuously precipitate ice particles, contribute roughly 10% of the uncertainty attributed to the global cloud feedback. This Arctic cloud uncertainty is driven by incomplete observational and theoretical knowledge required to estimate and explain the state and active processes occurring in those clouds. A focus on ice precipitation properties at Arctic cloud base rather than the surface deconfounds the product of cloud condensate sink processes from the influence of the atmospheric thermodynamic state below cloud base, rendering cloud-base properties a more appealing target for inference and evaluation of model simulations. This dataset provides a set of 25 samples from the M-PACE field campaign, all of which were retrieved using the synthesis of ARM radar and lidar measurements. The retrieved ice precipitation variables in this dataset include, among others, the ice number concentration, water content, PSD parameters, precipitation rate, mass-weighted fall velocity, vertical air motion, and effective radius, all of which are highly valuable for model evaluation and a general understanding of polar cloud sink processes. Each variable sample includes its mean value and associated uncertainty. Additional variables based on ARM measurements (liquid layer statistics, etc.) are included in this dataset as well. The retrieval algorithm and analysis of this dataset are described in Silber (JGR, 2023, https://doi.org/10.1029/2022JD038202).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1974

Wind estimates from cloud motions: Phase 1 of an in situ aircraft verification experiment

An initial experiment was conducted to verify geostationary satellite derived cloud motion wind estimates with in situ aircraft wind velocity measurements. Case histories of one-half hour to two hours were obtained for 3-10km diameter cumulus cloud systems on 6 days. Also, one cirrus cloud case was obtained. In most cases the clouds were discrete enough that both the cloud motion and the ambient wind could be measured with the same aircraft Inertial Navigation System (INS). Since the INS drift error is the same for both the cloud motion and wind measurements, the drift error subtracts out of the relative motion determinations. The magnitude of the vector difference between the cloud motion and the ambient wind at the cloud base averaged 1.2 m/sec. The wind vector at higher levels in the cloud layer differed by about 3 m/sec to 5 m/sec from the cloud motion vector.

Hasler, A. F.↗
NASA NTRS1975

Cloud structure and heating rates in the atmosphere of Venus

Ground-based observations and Venera 8 entry-probe measurements are used to infer the vertical distribution of cloud particles in the atmosphere of Venus. In the cloud-top region, from a few millibars to a few hundred millibars pressure, the mixing ratio of cloud particles to gas increases with depth. The visible clouds are diffuse with a scale height about one-half of the gaseous atmosphere. Although the presence of significant vertical structure could escape detection by available observations, the diffuse haze appears to extend over at least 20 km in altitude. The Venera 8 measurements suggest considerable vertical structure in the deep atmosphere. A unique solution for the cloud structure is not possible, but if it is assumed that the cloud optical properties are independent of height, then some characteristics of the relative cloud structure can be deduced. Under this assumption, the results show a maximum cloud density near 40 km, a nearly homogeneous particle mixing in the region from about 40 to 50 km, and a fairly sharp cloud bottom near 30 km. Relative maxima in the cloud density are also implied near 55 and 10 km, but with much greater uncertainty.

Lacis, A. A.↗
NASA NTRS1976

A single field of view method for retrieving tropospheric temperature profiles from cloud-contaminated radiance data

An iterative method is presented to retrieve single field of view (FOV) tropospheric temperature profiles directly from cloud-contaminated radiance data. A well-defined temperature profile may be calculated from the radiative transfer equation (RTE) for a partly cloudy atmosphere when the average fractional cloud amount and cloud-top height for the FOV are known. A cloud model is formulated to calculate the fractional cloud amount from an estimated cloud-top height. The method is then examined through use of simulated radiance data calculated through vertical integration of the RTE for a partly cloudy atmosphere using known values of cloud-top height(s) and fractional cloud amount(s). Temperature profiles are retrieved from the simulated data assuming various errors in the cloud parameters. Temperature profiles are retrieved from NOAA-4 satellite-measured radiance data obtained over an area dominated by an active cold front and with considerable cloud cover and compared with radiosonde data. The effects of using various guessed profiles and the number of iterations are considered.

Hodges, D. B.↗
NASA NTRS1976

Wind estimates from cloud motions - Phase 1 of an in situ aircraft verification experiment

An initial experiment has been conducted to verify geostationary-satellite-derived cloud motion wind estimates with in situ aircraft wind velocity measurements. Case histories of 1/2 to 2 h were obtained for 3-10 km diameter cumulus cloud systems on 6 days. Also, one cirrus cloud case was obtained. In most cases the clouds were discrete enough that both the cloud motion and the ambient wind could be measured with the same aircraft Inertial Navigation System (INS). Since the INS drift error is the same for both the cloud motion and wind measurements, the drift error drops out of the relative motion determinations. The magnitude of the vector difference between the cloud motion and the ambient wind at the cloud base averaged 1.2 m/sec. The wind vector at higher levels in the cloud layer differed by about 3 to 5 m/sec from the cloud motion vector.

Hasler, A. F.↗