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At least 757 records · Page 42

Near-Real-Time Detection and Monitoring of Dust Events by Satellite (SeaWIFS, MODIS, and TOMS)

Over the last few years satellites have given us increasingly detailed information on the size, location, and duration of dust events around the world. These data not only provide valuable feedback to the modelling community as to the fidelity of their aerosol models but are also finding increasing use in near real-time applications. In particular, the ability to locate and track the development of aerosol dust clouds on a near real-time basis is being used by scientists and government to provide warning of air pollution episodes over major urban area. This ability has also become a crucial component of recent coordinated campaigns to study the characteristics of tropospheric aerosols such as dust and their effect on climate. One such recent campaign was ACE-Asia, which was designed to obtain the comprehensive set of ground, aircraft, and satellite data necessary to provide a detailed understanding of atmospheric aerosol particles over the Asian-Pacific region. As part of ACE-Asia, we developed a near real-time data processing and access system to provide satellite data from the polar-orbiting instruments Earth Probe TOMS (in the form of absorbing aerosol index) and SeaWiFS (in the form of aerosol optical thickness, AOT, and Angstrom exponent). The results were available via web access. The location and movement information provided by these data were used both in support of the day-to-day flight planning of ACE-Asia and as input into aerosol transport models. While near real-time SeaWiFS data processing can be performed using either the normal global data product or data obtained via direct broadcast to receiving stations close to the area of interest, near real-time MODIS processing of data to provide aerosol retrievals is currently only available using its direct broadcast capability. In this paper, we will briefly discuss the algorithms used to generate these data. The retrieved aerosol optical thickness and Angstrom exponent from SeaWiFS will be compared with those obtained from various AERONET sites over the Asian-Pacific region. The TOMS aerosol index will also be compared with AERONET aerosol optical thickness over different aerosol conditions, and comparisons between the MODIS and SeaWiFS data will also be presented. Finally, we will discuss the climate implication of our studies using the combined satellite and AERONET observations.

Hsu, N. Christina↗

Studies of dust grain properties in infrared reflection nebulae

A model has been developed for reflection nebulae around luminous IR sources embedded in dense dust clouds. The shape of the IR spectrum is shown to be the result of a combination of the scattering properties of the dust, the spectrum of the illuminating source, and foreground extinction, while geometry plays a minor role. Comparison of the model results with IR observations of the reflection nebula surrounding OMC-2/IRS 1 shows that either a grain size distribution like that found in the diffuse ISM, or consisting of larger grains, can explain the observed shape of the spectrum. However, the absolute intensity level of the scattered light, as well as the observed polarization, requires large grains. By adding water-ice mantles to the silicate and graphite cores, the 3.08 micron ice-band feature observed in the spectra of several IR reflection nebulae has been modeled. It is shown that this ice band arises naturally in optically thick reflection nebulae containing ice-coated grains.

Pendleton, Y. J.↗

Autoencoders for Denoising Atmospheric Profiles from ICESat-2

Abstract: The 2nd generation Ice, Cloud, and land Elevation Satellite (ICESat-2) is an altimetry mission designed primarily for measuring ice sheet elevation and sea ice thickness, provides atmospheric profiles of clouds and aerosols at 532 nm using a photo counting detection approach. While highly sensitive for the detection of tenuous aerosol and cloud features, during the day signal-to-noise-ratio (SNR) photon counting detectors are adversely impacted by solar contributions to the total signal. Averaging the data to coarser horizontal resolutions has been the standard way to increase SNR and thus allow clouds and aerosols to be more easily detectable. Recent work has demonstrated success in boosting SNR without decreasing resolution using advanced filtering techniques [Yorks et al., 2021], however, rapid advancements in Deep Learning based image denoising algorithms can further improve the SNR. Here, we present results using a state-of-the-art Deep Learning autoencoder applied to noisy ICESat-2 data to improve daytime SNR and discuss implications for atmospheric feature detection, classification, and optical property retrievals.

denoising↗

Aperture synthesis observations of the molecular ring in the galactic center

Reported are 88 GHz aperture synthesis observations of HCN J=1 yields 0 emission and absorption in the central 5 pc of the Galaxy. The data, taken by the Hat Creek mm-interferometer at 5" to 10" spatial and 4 km/s spectral resolution, show a complete, clumpy ring of molecular gas surrounding the ionized central 2 pc of the Galaxy. The ring is the inner edge of a larger disk extending to about 5 pc. Comparison with sub-mm line data suggests that the HCN 1-0 line is slightly optically thick and originates in subthermally populated gas. The clumpy line emission distribution reflects a combination of hydrogen volume and column density variations. The new data clearly show a close physical relation between the molecular and the ionized gas in the central cavity. The western arc appears to be the ionized inner surface of the molecular ring, and the northern arm and bar may be streamers of ionized gas falling from the ring toward the center. The dominant large scale velocity pattern of the majority of the molecular gas in the inner 5 pc is rotation. No overall radial motion of the ring greater than about 20 km/s is apparent. The rotation is perturbed in several ways; (1) there is a very large local velocity dispersion, (2) the ring shows changes in position angle and inclination (warps), (3) there is a bright, redshifted cloud which appears to be located in the western part of the ring but does not participate in the rotation. These characteristics and the high degree of clumpiness indicate a non-equilibrium configuration of short (less than or approx. 10 to the 4th power to 10 to the 5th power y) dynamical lifetime. The warping and tilting of the structure and the short dynamical lifetime make an accurate determination of equilibrium rotation velocity uncertain.

Guesten, R.↗

New photoionization models of intergalactic clouds

New photoionization models of optically thin low-density intergalactic gas at constant pressure, photoionized by QSOs, are presented. All ion stages of H, He, C, N, O, Si, and Fe, plus H2 are modeled, and the column density ratios of clouds at specified values of the ionization parameter of n sub gamma/n sub H and cloud metallicity are predicted. If Ly-alpha clouds are much cooler than the previously assumed value, 30,000 K, the ionization parameter must be very low, even with the cooling contribution of a trace component of molecules. If the clouds cool below 6000 K, their final equilibrium must be below 3000 K, owing to the lack of a stable phase between 6000 and 3000 K. If it is assumed that the clouds are being irradiated by an EUV power-law continuum typical of WSOs, with J0 = 10 exp -21 ergs/s sq cm Hz, typical cloud thicknesses along the line of sight that are much smaller than would be expected from shocks, thermal instabilities, or gravitational collapse are derived.

Donahue, Megan↗

Cloud Mask Intercomparison eXercise (CMIX): An evaluation of cloud masking algorithms for Landsat 8 and Sentinel-2

Cloud cover is a major limiting factor in exploiting time-series data acquired by optical spaceborne remote sensing sensors. Multiple methods have been developed to address the problem of cloud detection in satellite imagery and a number of cloud masking algorithms have been developed for optical sensors but very few studies have carried out quantitative intercomparison of state-of-the-art methods in this domain. This paper summarizes results of the first Cloud Masking Intercomparison eXercise (CMIX) conducted within the Committee Earth Observation Satellites (CEOS) Working Group on Calibration & Validation (WGCV). CEOS is the forum for space agency coordination and cooperation on Earth observations, with activities organized under working groups. CMIX, as one such activity, is an international collaborative effort aimed at intercomparing cloud detection algorithms for moderate-spatial resolution (10–30 m) spaceborne optical sensors. The focus of CMIX is on open and free imagery acquired by the Landsat 8 (NASA/USGS) and Sentinel-2 (ESA) missions. Ten algorithms developed by nine teams from fourteen different organizations representing universities, research centers and industry, as well as space agencies (CNES, ESA, DLR, and NASA), are evaluated within the CMIX. Those algorithms vary in their approach and concepts utilized which were based on various spectral properties, spatial and temporal features, as well as machine learning methods. Algorithm outputs are evaluated against existing reference cloud mask datasets. Those datasets vary in sampling methods, geographical distribution, sample unit (points, polygons, full image labels), and generation approaches (experts, machine learning, sky images). Overall, the performance of algorithms varied depending on the reference dataset, which can be attributed to differences in how the reference datasets were produced. The algorithms were in good agreement for thick cloud detection, which were opaque and had lower uncertainties in their identification, in contrast to thin/semi-transparent clouds detection. Not only did CMIX allow identification of strengths and weaknesses of existing algorithms and potential areas of improvements, but also the problems associated with the existing reference datasets. The paper concludes with recommendations on generating new reference datasets, metrics, and an analysis framework to be further exploited and additional input datasets to be considered by future CMIX activities.

Sergii Skakun↗

Automatic Jet Contrail Detection and Segmentation

Jet contrails are an important subset of cirrus clouds in the atmosphere, and thin cirrus are thought to enhance the greenhouse effect due to their semi-transparent nature. They are nearly transparent to the solar energy reaching the surface, but they reduce the planetary emission to space due to their cold ambient temperatures. Having 'seeded' the environment, contrails often elongate and widen into cirrus-like features. However, there is great uncertainty regarding the impact of contrails on surface temperature and precipitation. With increasing numbers of subsonic aircraft operating in the upper troposphere, there is the possibility of increasing cloudiness which could lead to changes in the radiation balance. Automatic detection and seg- mentation of jet contrails in satellite imagery is important because (1) it is impractical to compile a contrail climatology by hand, and (2) with the segmented images it will be possible to retrieve contrail physical properties such as optical thickness, effective ice crystal diameter and emissivity.

Weiss, J.↗

Comparisons Between Ground Measurements of Broadband UV Irradiance (300-380 nm) and TOMS UV Estimates at Moscow for 1979-2000

We show the comparisons between ground-based measurements of spectrally integrated (300 nm to 380 nm) ultraviolet (UV) irradiance with satellite estimates from the Total Ozone Mapping Spectrometer (TOMS) total ozone and reflectivity data for the whole period of TOMS measurements (1979-2000) over the Meteorological Observatory of Moscow State University (MO MSU), Moscow, Russia. Several aspects of the comparisons are analyzed, including effects of cloudiness, aerosol, and snow cover. Special emphasis is given to the effect of different spatial and temporal averaging of ground-based data when comparing with low-resolution satellite measurements (TOMS footprint area 50-200 sq km). The comparisons in cloudless scenes with different aerosol loading have revealed TOMS irradiance overestimates from +5% to +20%. A-posteriori correction of the TOMS data accounting for boundary layer aerosol absorption (single scattering albedo of 0.92) eliminates the bias for cloud-free conditions. The single scattering albedo was independently verified using CIMEL sun and sky-radiance measurements at MO MSU in September 2001. The mean relative difference between TOMS UV estimates and ground UV measurements mainly lies within 1 10% for both snow-free and snow period with a tendency to TOMS overestimation in snow-free period especially at overcast conditions when the positive bias reaches 15-17%. The analysis of interannual UV variations shows quite similar behavior for both TOMS and ground measurements (correlation coefficient r=0.8). No long-term trend in the annual mean bias was found for both clear-sky and all-sky conditions with snow and without snow. Both TOMS and ground data show positive trend in UV irradiance between 1979 and 2000. The UV trend is attributed to decreases in both cloudiness and aerosol optical thickness during the late 1990's over Moscow region. However, if the analyzed period is extended to include pre-TOMS era (1968-2000 period), no trend in ground UV irradiance is detected.

Yurova, Alla Y.↗

Raman lidar and sun photometer measurements of aerosols and water vapor during the ARM RCS experiment

The first Atmospheric Radiation Measurement (ARM) Remote Cloud Study (RCS) Intensive Operations Period (IOP) was held during April 1994 at the Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site near Lamont, Oklahoma. This experiment was conducted to evaluate and calibrate state-of-the-art, ground based remote sensing instruments and to use the data acquired by these instruments to validate retrieval algorithms developed under the ARM program. These activities are part of an overall plan to assess general circulation model (GCM) parameterization research. Since radiation processes are one of the key areas included in this parameterization research, measurements of water vapor and aerosols are required because of the important roles these atmospheric constituents play in radiative transfer. Two instruments were deployed during this IOP to measure water vapor and aerosols and study their relationship. The NASA/Goddard Space Flight Center (GSFC) Scanning Raman Lidar (SRL) acquired water vapor and aerosol profile data during 15 nights of operations. The lidar acquired vertical profiles as well as nearly horizontal profiles directed near an instrumented 60 meter tower. Aerosol optical thickness, phase function, size distribution, and integrated water vapor were derived from measurements with a multiband automatic sun and sky scanning radiometer deployed at this site.

Ferrare, R. A.↗

Simultaneous Retrieval of Multiple Aerosol Parameters Using a Multi-Angular Approach

Atmospheric aerosol particles, both natural and anthropogenic, are important to the earth's radiative balance through their direct and indirect effects. They scatter the incoming solar radiation (direct effect) and modify the shortwave reflective properties of clouds by acting as cloud condensation nuclei (indirect effect). Although it has been suggested that aerosols exert a net cooling influence on climate, this effect has received less attention than the radiative forcing due to clouds and greenhouse gases. In order to understand the role that aerosols play in a changing climate, detailed and accurate observations are a prerequisite. The retrieval of aerosol optical properties by satellite remote sensing has proven to be a difficult task. The difficulty results mainly from the tenuous nature and variable composition of aerosols. To date, with single-angle satellite observations, we can only retrieve reliably against dark backgrounds, such as over oceans and dense vegetation. Even then, assumptions must be made concerning the chemical composition of aerosols. The best hope we have for aerosol retrievals over bright backgrounds are observations from multiple angles, such as those provided by the MISR and POLDER instruments. In this investigation we examine the feasibility of simultaneous retrieval of multiple aerosol optical parameters using reflectances from a typical set of twelve angles observed by the French POLDER instrument. The retrieved aerosol optical parameters consist of asymmetry factor, single scattering albedo, surface albedo, and optical thickness.

Kuo, K. S.↗

MODIS Collection 6 Clear Sky Restoral (CSR): Filtering Cloud Mast 'Not Clear' Pixels

Correctly identifying cloudy pixels appropriate for the MOD06 cloud optical and microphysical property retrievals is accomplished in large part using results from the MOD35 1km cloud mask tests (note there are also two 250m subpixel cloud mask tests that can convert the 1km cloudy designations to clear sky). However, because MOD35 is by design clear sky conservative (i.e., it identifies "not clear" pixels), certain situations exist in which pixels identified by MOD35 as "cloudy" are nevertheless likely to be poor retrieval candidates. For instance, near the edge of clouds or within broken cloud fields, a given 1km MODIS field of view (FOV) may in fact only be partially cloudy. This can be problematic for the MOD06 retrievals because in these cases the assumptions of a completely overcast homogenous cloudy FOV and 1-dimensional plane-parallel radiative transfer no longer hold, and subsequent retrievals will be of low confidence. Furthermore, some pixels may be identified by MOD35 as "cloudy" for reasons other than the presence of clouds, such as scenes with thick smoke or lofted dust, and should therefore not be retrieved as clouds. With such situations in mind, a Clear Sky Restoral (CSR) algorithm was introduced in C5 that attempts to identify pixels expected to be poor retrieval candidates. Table 1 provides SDS locations for CSR and partly cloudy (PCL) pixels.

cloud mask↗

The MODIS Aerosol Algorithm, Products, Validation and Applications

The MODerate resolution Imaging Spectroradiometer (MODIS) currently aboard both the Terra and Aqua satellites produces a suite of products designed to characterize global aerosol distribution, optical thickness and particle size. Never before has a space-borne instrument been able to provide such detailed information, complementing field and modeling efforts to produce a comprehensive picture of aerosol characteristics. The three years of Terra-MODIS data have been validated by comparing with co-located AERONET observations of aerosol optical thickness and derivations of aerosol size parameters. Some 8000 comparison points located at 133 AERONET sites around the globe show that the MODIS aerosol optical thickness retrievals are accurate to within the pre-launch expectations. MODIS-derived size parameters are also compared with AERONET retrievals and found to agree well for fine-mode dominated aerosol regimes. Aerosol regimes dominated by dust aerosol are less accurate, attributed to what is thought to be nonsphericity. Errors due to nonsphericity will be reduced by introducing a new set of empirical phase functions, derived without any assumptions of particle shape. The major innovation that MODIS bring to the field of remote sensing of aerosol is the measure of particle size and the separation of finemode and coarsemode dominated aerosol regimes. Particle size can separate finemode man-made aerosols created during combustion, from larger natural aerosols originating from salt spray or wind erosion. This separation allows for the calculation of aerosol radiative effect and the estimation of the man-made aerosol radiative forcing. MODIS can also be used in regional studies of aerosol-cloud interaction that affect the global radiative and hydrological cycles.

Remer, L. A.↗

Satellite Mapping of PM2.5 Episodes in the Wintertime San Joaquin Valley: A "Static" Model Using Column Water Vapor

The use of satellite Aerosol Optical Thickness (AOT) from imaging spectrometers has been successful in quantifying and mapping high PM2.5 (particulate matter mass <2.5µm diameter) episodes for pollution abatement and health studies. However, some regions have high PM2.5 but poor estimation success. The challenges in using Aerosol Optical Thickness (AOT) from imaging spectrometers to characterize PM2.5 worldwide was especially evident in the wintertime San Joaquin Valley (SJV). The SJV's attendant difficulties of high-albedo surfaces and very shallow, variable vertical mixing also occur in other significantly polluted regions around the world. We report on more accurate PM2.5 maps for the whole-winter period in the SJV, Nov 14, 2012?Dec 11, 2013. Intensive measurements by including NASA aircraft were made for several weeks in that winter, the DISCOVER-AQ California mission.We found success with a relatively simple method based on calibration and checking with surface monitors and a characterization of vertical mixing, and incorporating specific understandings of the region's climatology. We estimate PM2.5 to within ~7µgm?3 RMSE and with R values of ~0.9, based on remotely sensed MAIAC (Multi-Angle Implementation of Atmospheric Correction) observations, and that certain further work will improve that accuracy. Mapping is at 1km resolution. This allows a time sequence of mapped aerosols at 1km for cloud-free days. We describe our technique as a "static estimation". Estimation procedures like this one, not dependent on well-mapped source strengths or on transport error, should help full source-driven simulations by deconstructing processes. They also provide a rapid method to create a long-term climatology.Essential features of the technique are (a) daily calibration of the AOT to PM2.5 using available surface monitors, and (b) characterization of mixed-layer dilution using column water vapor (CWV, otherwise "precipitable water"). We noted that on multi-day timescales both water vapor and particles share near-surface sources and both fall to very low values with altitude; indeed, both are largely removed by precipitation. The existence of layers of H2O or aerosol not within the mixed layer adds complexity, but mixed-effects statistical regression captures essential proportionality of PM2.5 and the ratio variable (AOT/CWV). Accuracy is much higher than previous statistical models, and can be extended to the whole Aqua-satellite data record. The maps and time-series we show suggest a repeated pattern for large valleys like the SJV ? progressive stabilization of the mixing height after frontal passages: PM2.5 is somewhat more determined by day-by-day changes in mixing than it is by the progressive accumulation of pollutants (revealed as increasing AOT).

Chatfield, Robert B.↗

CO and OH absorption toward the low-latitude radio source 2023+336

We report interferometric observations of (12)CO (0 to 1) 115 GHz and OH 1667 MHz absorption toward the extragalactic radio continuum source 2023+336. Our data show two partially blended absorption features near +2 km/s LSR which probably originate in local molecular clouds in the Cygnus rift, approximately 0.7 kpc away. The CO lines are optically thin, with tau(sub CO) = 0.5 +/- 0.1, while tau(sub OH) = 0.030 +/- 0.004. The detected absorption features have a combined velocity width of 3.0 km/s FWHM, greater than the width of the corresponding (12)CO emission features, Full Width of Half Maximum (FWHM) = 2.3 km/s, indicating that the absorbing gas in a approximately 1 AU diameter column shows a greater velocity range than the gas in the 0.2 pc diameter emission beam. CO excitation temperatures T(sub ex), range from 2.7 to 7.0 K across the line profile, implying that the gas along this line of sight is rotationally quite cold. By measuring the (12)CO excitation temperature and optical depth, we derive an abundance ratio, (CO)/(H2), of 6 x 10(exp -6), which is more than an order of magnitude lower than is seen elsewhere. Our low observed CO optical depth is inconsistent with the ratio of (12)CO to (13)CO emission line integrals, 16:1, which implies that the (12)CO is optically thick. As a solution to these anomalies, we propose that the CO absorption and emission arise from preferentially different parts of the molecular medium. Other solutions would require an anomalous (12)CO/(13)CO abundance ratio and an anomalous CO/H2 abundance ratio, or much lower excitation temperatures. Since we find no absorption at negative velocities with tau greater than 0.23 (2.5 sigma), there is no compelling evidence for the existence of an extensive population of cold molecular gas in the outer Galaxy along this line of sight.

Kobulnicky, Henry A.↗

The Time Series Technique for Aerosol Retrievals over Land from MODIS: Algorithm MAIAC

Atmospheric aerosols interact with sun light by scattering and absorbing radiation. By changing irradiance of the Earth surface, modifying cloud fractional cover and microphysical properties and a number of other mechanisms, they affect the energy balance, hydrological cycle, and planetary climate [IPCC, 2007]. In many world regions there is a growing impact of aerosols on air quality and human health. The Earth Observing System [NASA, 1999] initiated high quality global Earth observations and operational aerosol retrievals over land. With the wide swath (2300 km) of MODIS instrument, the MODIS Dark Target algorithm [Kaufman et al., 1997; Remer et al., 2005; Levy et al., 2007] currently complemented with the Deep Blue method [Hsu et al., 2004] provides daily global view of planetary atmospheric aerosol. The MISR algorithm [Martonchik et al., 1998; Diner et al., 2005] makes high quality aerosol retrievals in 300 km swaths covering the globe in 8 days. With MODIS aerosol program being very successful, there are still several unresolved issues in the retrieval algorithms. The current processing is pixel-based and relies on a single-orbit data. Such an approach produces a single measurement for every pixel characterized by two main unknowns, aerosol optical thickness (AOT) and surface reflectance (SR). This lack of information constitutes a fundamental problem of the remote sensing which cannot be resolved without a priori information. For example, MODIS Dark Target algorithm makes spectral assumptions about surface reflectance, whereas the Deep Blue method uses ancillary global database of surface reflectance composed from minimal monthly measurements with Rayleigh correction. Both algorithms use Lambertian surface model. The surface-related assumptions in the aerosol retrievals may affect subsequent atmospheric correction in unintended way. For example, the Dark Target algorithm uses an empirical relationship to predict SR in the Blue (B3) and Red (B1) bands from the 2.1 m channel (B7) for the purpose of aerosol retrieval. Obviously, the subsequent atmospheric correction will produce the same SR in the red and blue bands as predicted, i.e. an empirical function of 2.1. In other words, the spectral, spatial and temporal variability of surface reflectance in the Blue and Red bands appears borrowed from band B7. This may have certain implications for the vegetation and global carbon analysis because the chlorophyll-sensing bands B1, B3 are effectively substituted in terms of variability by band B7, which is sensitive to the plant liquid water. This chapter describes a new recently developed generic aerosol-surface retrieval algorithm for MODIS. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm simultaneously retrieves AOT and surface bi-directional reflection factor (BRF) using the time series of MODIS measurements.

Lyapustin, Alexei↗

Calibration of of Sun Photometers and Sky Radiance Sensors

The main source of error in retrieving aerosol optical thicknesses using sun photometry comes from the determination of the TOA voltages. The degradation of interference filters is the most important source of the long-term changes in the cross-calibrations. Although major improvements have been made in the design of the filters (interference filters fabricated using ion-assisted deposition), the filters remain the principal factor limiting performance of the sun photometers. Degradation of filters necessitates frequent calibration of sun photometers and frequent measurements of the filter transmission or the relative system response. The degradation of the filters mounted on the CIMEL sun photometers have been monitored since 1993 by the Aerosol Robotic Network (AERONET) project. The decay reported by Holben et al. for the first two years of a CIMEL#s operation is between 1 and 5%. Nevertheless, the filters mounted on CIMEL instruments are regularly replaced after two years of use. The cross-calibration technique consists of taking measurements concurrently with the uncalibrated and the reference sun photometers. While analyzing measurements, the quality of the calibration has to be checked, using the following considerations: (1) any cirrus clouds suspected to be masking the sun, during the calibration period, need to be reported and the corresponding data set removed; and (2) the stability of the day needs to be checked. This chapter will describe calibration techniques, facilities, and protocols used for calibrating sun photometers and sky radiometers.

Pietras, Christophe↗

Earth-system-model evaluation of cloud and precipitation occurrence for supercooled and warm clouds over the Southern Ocean's Macquarie Island

Abstract. Over the remote Southern Ocean (SO), cloud feedbacks contribute substantially to Earth system model (ESM) radiative biases. The evolution of low Southern Ocean clouds (cloud-top heights < ∼ 3 km) is strongly modulated by precipitation and/or evaporation, which act as the primary sink of cloud condensate. Constraining precipitation processes in ESMs requires robust observations suitable for process-level evaluations. A year-long subset (April 2016–March 2017) of ground-based profiling instrumentation deployed during the Macquarie Island Cloud and Radiation Experiment (MICRE) field campaign (54.5∘ S, 158.9∘ E) combines a 95 GHz (W-band) Doppler cloud radar, two lidar ceilometers, and balloon-borne soundings to quantify the occurrence frequency of precipitation from the liquid-phase cloud base. Liquid-based clouds at Macquarie Island precipitate ∼ 70 % of the time, with deeper and colder clouds precipitating more frequently and at a higher intensity compared to thinner and warmer clouds. Supercooled cloud layers precipitate more readily than layers with cloud-top temperatures > 0 ∘C, regardless of the geometric thickness of the layer, and also evaporate more frequently. We further demonstrate an approach to employ these observational constraints for evaluation of a 9-year GISS-ModelE3 ESM simulation. Model output is processed through the Earth Model Column Collaboratory (EMC2) radar and lidar instrument simulator with the same instrument specifications as those deployed during MICRE, therefore accounting for instrument sensitivities and ensuring a coherent comparison. Relative to MICRE observations, the ESM produces a smaller cloud occurrence frequency, smaller precipitation occurrence frequency, and greater sub-cloud evaporation. The lower precipitation occurrence frequency by the ESM relative to MICRE contrasts with numerous studies that suggest a ubiquitous bias by ESMs to precipitate too frequently over the SO when compared with satellite-based observations, likely owing to sensitivity limitations of spaceborne instrumentation and different sampling methodologies for ground- versus space-based observations. Despite these deficiencies, the ESM reproduces the observed tendency for deeper and colder clouds to precipitate more frequently and at a higher intensity. The ESM also reproduces specific cloud regimes, including near-surface clouds that account for ∼ 25 % of liquid-based clouds during MICRE and optically thin, non-precipitating clouds that account for ∼ 27 % of clouds with bases higher than 250 m. We suggest that the demonstrated framework, which merges observations with appropriately constrained model output, is a valuable approach to evaluate processes responsible for cloud radiative feedbacks in ESMs.

54 ENVIRONMENTAL SCIENCES↗

Effect of Clouds on Shuttle Imaging

This report describes the results of the AMU's task for determining the effect of clouds on optical imaging of the Space Shuttle launch vehicle during its ascent phase from lift-off to Solid Rocket Booster (SRB) Separation. This effort was motivated by Recommendation R3.4-1 from the Columbia Accident Investigation Board Report. The AMU developed a 3-dimensional (3D) model to forecast the probability that at any time from lift-off to SRB separation, at least three of the ascent imaging cameras would have a view of the Shuttle unobstructed by cloud. Because current observational and modeling capabilities do not permit accurate forecasts of cloud morphology and location, the AMU simulated obscuration of the lines-of-sight (LOS) from a network of cameras to the Shuttle by idealized cloud-fields placed randomly within the 3D domain. For each random realization of numerous cloud-field scenarios the number of simultaneous views of the Shuttle was computed from the LOS data between lift-off and SRB separation. The percent of time with 3 simultaneous views was averaged from 100 random realizations of each scenario. Analyses of the percent of time viewable were made to determine its sensitivity to cloud amount, cloud base height, cloud thickness, cloud horizontal dimensions, and an upgrade of the camera network.

Short, David A.↗