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Mikhail D. Alexandrov
,
Andrew A. Lacis
,
Barbara E. Carlson
, and
Brian Cairns

Abstract

Measurements from ground-based sun photometer networks can be used both to provide ground-truth validation of satellite aerosol retrievals and to produce a land-based aerosol climatology that is complementary to satellite retrievals that are currently performed mostly over ocean. The multifilter rotating shadowband radiometer (MFRSR) has become a popular network instrument in recent years. Several networks operate about a hundred instruments providing good geographical coverage of the United States. In addition, international use of the MFRSR has continued to increase, allowing MFRSR measurements to significantly contribute to aerosol climatologies.

This study investigates the feasibility of creating a ground-based aerosol climatology using MFRSR measurements. Additionally, this analysis allows for testing of the performance of the retrieval algorithm under a variety of conditions. The retrieval algorithm is used for processing MFRSR data from clear and partially cloudy days to simultaneously retrieve daily time series of column mean aerosol particle size, aerosol optical depth, NO2, and ozone column amounts together with the instrument's calibration constants directly from the MFRSR measurements for a variety of sites covering a range of atmospheric and surface conditions. This analysis provides a description of seasonal changes in aerosol parameters and in column amounts of ozone and NO2 as a function of geographical location. In addition, the relationship between NO2 column amount and aerosol optical depth as a potential indicator of tropospheric pollution is investigated. Application of this analysis method to the measurements from growing numbers of MFRSRs will allow for expansion on this developing climatology.

Full access
Mikhail D. Alexandrov
,
Alexander Marshak
,
Brian Cairns
,
Andrew A. Lacis
, and
Barbara E. Carlson

Abstract

Statistical scale-by-scale analysis, for the first time, has been applied to the aerosol optical thickness (AOT) retrieved from the Multi-Filter Rotating Shadowband Radiometer (MFRSR) network. The MFRSR data were collected in September 2000 from the dense local network operated by the U.S. Department of Energy Atmospheric Radiation Measurement program, located in Oklahoma and Kansas. These data have 20-s temporal resolution. The instrument sites form an irregular grid with the mean distance between neighboring sites about 80 km. It is found that temporal variability of AOT can be separated into two well-established scale-invariant regimes: 1) microscale (0.5–15 km), where fluctuations are governed by 3D turbulence, and 2) intermediate scale (15–100 km), characterized by a transition toward large-scale 2D turbulence. The spatial scaling of AOT was determined by the comparison of retrievals between different instrument sites (distance range 30–400 km). The authors investigate how simultaneous determination of AOT scaling in space and time can provide means to examine the validity of Taylor's frozen turbulence hypothesis. The temporal evolution of AOT scaling exponents during the month appeared to be well correlated with changes in aerosol vertical distribution, while their spatial variability reflects the concavity/convexity of the site topography. Explanations based on dynamical processes in atmospheric convective boundary layer are suggested.

Full access
Mikhail D. Alexandrov
,
Igor V. Geogdzhayev
,
Kostas Tsigaridis
,
Alexander Marshak
,
Robert Levy
, and
Brian Cairns

Abstract

A novel model for the variability in aerosol optical thickness (AOT) is presented. This model is based on the consideration of AOT fields as realizations of a stochastic process that is the exponent of an underlying Gaussian process with a specific autocorrelation function. In this approach, AOT fields have lognormal PDFs and structure functions with the correct asymptotic behavior at large scales. The latter is an advantage compared with fractal (scale invariant) approaches. The simple analytical form of the structure function in the proposed model facilitates its use for the parameterization of AOT statistics derived from remote sensing data. The new approach is illustrated using a 1-yr-long global MODIS AOT dataset (over ocean) with 10-km resolution. It was used to compute AOT statistics for sample cells forming a grid with 5° spacing. The observed shapes of the structure functions indicated that, in a large number of cases, the AOT variability is split into two regimes that exhibit different patterns of behavior: small-scale stationary processes and trends reflecting variations at larger scales. The small-scale patterns are suggested to be generated by local aerosols within the marine boundary layer, while the large-scale trends are indicative of elevated aerosols transported from remote continental sources. This assumption is evaluated by comparison of the geographical distributions of these patterns derived from MODIS data with those obtained from the GISS GCM. This study shows considerable potential to enhance comparisons between remote sensing datasets and climate models beyond regional mean AOTs.

Full access
Joseph S. Schlosser
,
Ryan Bennett
,
Brian Cairns
,
Gao Chen
,
Brian L. Collister
,
Johnathan W. Hair
,
Michael Jones
,
Michael A. Shook
,
Armin Sorooshian
,
Kenneth L. Thornhill
,
Luke D. Ziemba
, and
Snorre Stamnes

Abstract

Suborbital (e.g., airborne) campaigns that carry advanced remote sensing and in situ payloads provide detailed observations of atmospheric processes, but can be challenging to use when it is necessary to geographically collocate data from multiple platforms that make repeated observations of a given geographic location at different altitudes. This study reports on a data collocation algorithm that maximizes the volume of collocated data from two coordinated suborbital platforms and demonstrates its value using data from the NASA Aerosol Cloud Meteorology Interactions Over the western Atlantic Experiment (ACTIVATE) suborbital mission. A robust data collocation algorithm is critical for the success of the ACTIVATE mission goal to develop new and improved remote sensing algorithms, and quantify their performance. We demonstrate the value of these collocated data to quantify the performance of a recently developed vertically resolved lidar + polarimeter–derived aerosol particle number concentration (Na ) product, resulting in a range-normalized mean absolute deviation (NMAD) of 9% compared to in situ measurements. We also show that this collocation algorithm increases the volume of collocated ACTIVATE data by 21% compared to using only nearest-neighbor finding algorithms alone. Additional to the benefits demonstrated within this study, the data files and routines produced by this algorithm have solved both the critical collocation and the collocation application steps for researchers who require collocated data for their own studies. This freely available and open-source collocation algorithm can be applied to future suborbital campaigns that, like ACTIVATE, use multiple platforms to conduct coordinated observations, e.g., a remote sensing aircraft together with in situ data collected from suborbital platforms.

Significance Statement

This study describes a data collocation (i.e., selection) process that aims to maximize the volume of data identified to be simultaneously collected in time and space from two coordinated measurement platforms. The functional utility of the resultant dataset is also demonstrated by extending the validation of aerosol particle number concentration derived from standard lidar and polarimeter data products from a suborbital mission that used two aircraft platforms.

Open access
Florian Tornow
,
Andrew S. Ackerman
,
Ann M. Fridlind
,
George Tselioudis
,
Brian Cairns
,
David Painemal
, and
Gregory Elsaesser

Abstract

Marine cold-air outbreaks (CAOs) occur in the postfrontal sector of midlatitude storms, usually accompanied by dry intrusions (DIs) shaping the free-tropospheric (FT) air aloft. Substantial rain initiates overcast to broken regime transitions in marine boundary layer (MBL) cloud decks that form where cold air first meets relatively high sea surface temperatures. An exemplary CAO in the northwest Atlantic shows earlier transitions (corresponding to reduced extents of overcast clouds) closer to the low pressure center. We hypothesize that gradients in the meteorological pattern imposed by the prevailing DI induced a variability in substantial rain onset and thereby transition. We compile satellite observations, reanalysis fields, and Lagrangian large-eddy simulations (LES) translating along MBL trajectories to show that postfrontal trajectories closer to the low pressure center are more favorable to rain formation (and thereby cloud transitions) because of 1) weaker FT subsidence rates, 2) greater FT humidity, 3) stronger MBL winds, and 4) a colder MBL with reduced lower-tropospheric stability. LES confirms the observed variability in transitions, with substantial rain appearing earlier where there is swifter reduction of cloud condensation nucleus (CCN) concentration and increase of liquid water path (LWP). Prior to substantial rain, CCN budgets indicate dominant loss terms from FT entrainment and hydrometeor collisions. LWP-enhancing cloud thickness increases more rapidly for weaker large-scale subsidence that enables faster MBL deepening. Mere MBL warming and moistening cannot explain cloud thickness increases. The generality of such a DI-imposed cloud transition pattern merits further investigation with more cases that may additionally be convoluted by onshore aerosol gradients.

Significance Statement

Cold-air outbreaks (CAOs) lead to marine boundary layer (MBL) clouds that commonly undergo rain-initiated overcast to broken cloud regime transitions that can drastically impact reflected solar radiation. We aim to better understand what mechanisms control these transitions. For a CAO event in the northwest Atlantic that shows earlier transitions closer to the low pressure center, we find the transition timing to be largely governed by the coinciding dry intrusion that imposes an inhomogeneous large-scale meteorological pattern onto the overlying free troposphere and thereby affects MBL rain formation. Our findings update conceptual understanding of extratropical cyclones and motivate analyzing observations and conducting simulations for more postfrontal cases through a Lagrangian perspective as done here for one case, to assess the generality of our findings.

Restricted access
Michael I. Mishchenko
,
Brian Cairns
,
Greg Kopp
,
Carl F. Schueler
,
Bryan A. Fafaul
,
James E. Hansen
,
Ronald J. Hooker
,
Tom Itchkawich
,
Hal B. Maring
, and
Larry D. Travis

The NASA Glory mission is intended to facilitate and improve upon long-term monitoring of two key forcings influencing global climate. One of the mission's principal objectives is to determine the global distribution of detailed aerosol and cloud properties with unprecedented accuracy, thereby facilitating the quantification of the aerosol direct and indirect radiative forcings. The other is to continue the 28-yr record of satellite-based measurements of total solar irradiance from which the effect of solar variability on the Earth's climate is quantified. These objectives will be met by flying two state-of-the-art science instruments on an Earth-orbiting platform. Based on a proven technique demonstrated with an aircraft-based prototype, the Aerosol Polarimetry Sensor (APS) will collect accurate multiangle photopolarimetric measurements of the Earth along the satellite ground track within a wide spectral range extending from the visible to the shortwave infrared. The Total Irradiance Monitor (TIM) is an improved version of an instrument currently flying on the Solar Radiation and Climate Experiment (SORCE) and will provide accurate and precise measurements of spectrally integrated sunlight illuminating the Earth. Because Glory is expected to fly as part of the A-Train constellation of Earth-orbiting spacecraft, the APS data will also be used to improve retrievals of aerosol climate forcing parameters and global aerosol assessments with other A-Train instruments. In this paper, we detail the scientific rationale and objectives of the Glory mission, explain how these scientific objectives dictate the specific measurement strategy, describe how the measurement strategy will be implemented by the APS and TIM, and briefly outline the overall structure of the mission. It is expected that the Glory results will be used extensively by members of the climate, solar, atmospheric, oceanic, and environmental research communities as well as in education and outreach activities.

Full access
P. Jeremy Werdell
,
Michael J. Behrenfeld
,
Paula S. Bontempi
,
Emmanuel Boss
,
Brian Cairns
,
Gary T. Davis
,
Bryan A. Franz
,
Ulrik B. Gliese
,
Eric T. Gorman
,
Otto Hasekamp
,
Kirk D. Knobelspiesse
,
Antonio Mannino
,
J. Vanderlei Martins
,
Charles R. McClain
,
Gerhard Meister
, and
Lorraine A. Remer

Abstract

The Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE) mission represents the National Aeronautics and Space Administration’s (NASA) next investment in satellite ocean color and the study of Earth’s ocean–atmosphere system, enabling new insights into oceanographic and atmospheric responses to Earth’s changing climate. PACE objectives include extending systematic cloud, aerosol, and ocean biological and biogeochemical data records, making essential ocean color measurements to further understand marine carbon cycles, food-web processes, and ecosystem responses to a changing climate, and improving knowledge of how aerosols influence ocean ecosystems and, conversely, how ocean ecosystems and photochemical processes affect the atmosphere. PACE objectives also encompass management of fisheries, large freshwater bodies, and air and water quality and reducing uncertainties in climate and radiative forcing models of the Earth system. PACE observations will provide information on radiative properties of land surfaces and characterization of the vegetation and soils that dominate their reflectance. The primary PACE instrument is a spectrometer that spans the ultraviolet to shortwave-infrared wavelengths, with a ground sample distance of 1 km at nadir. This payload is complemented by two multiangle polarimeters with spectral ranges that span the visible to near-infrared region. Scheduled for launch in late 2022 to early 2023, the PACE observatory will enable significant advances in the study of Earth’s biogeochemistry, carbon cycle, clouds, hydrosols, and aerosols in the ocean–atmosphere–land system. Here, we present an overview of the PACE mission, including its developmental history, science objectives, instrument payload, observatory characteristics, and data products.

Open access
Gavin A. Schmidt
,
Reto Ruedy
,
James E. Hansen
,
Igor Aleinov
,
Nadine Bell
,
Mike Bauer
,
Susanne Bauer
,
Brian Cairns
,
Vittorio Canuto
,
Ye Cheng
,
Anthony Del Genio
,
Greg Faluvegi
,
Andrew D. Friend
,
Tim M. Hall
,
Yongyun Hu
,
Max Kelley
,
Nancy Y. Kiang
,
Dorothy Koch
,
Andy A. Lacis
,
Jean Lerner
,
Ken K. Lo
,
Ron L. Miller
,
Larissa Nazarenko
,
Valdar Oinas
,
Jan Perlwitz
,
Judith Perlwitz
,
David Rind
,
Anastasia Romanou
,
Gary L. Russell
,
Makiko Sato
,
Drew T. Shindell
,
Peter H. Stone
,
Shan Sun
,
Nick Tausnev
,
Duane Thresher
, and
Mao-Sung Yao

Abstract

A full description of the ModelE version of the Goddard Institute for Space Studies (GISS) atmospheric general circulation model (GCM) and results are presented for present-day climate simulations (ca. 1979). This version is a complete rewrite of previous models incorporating numerous improvements in basic physics, the stratospheric circulation, and forcing fields. Notable changes include the following: the model top is now above the stratopause, the number of vertical layers has increased, a new cloud microphysical scheme is used, vegetation biophysics now incorporates a sensitivity to humidity, atmospheric turbulence is calculated over the whole column, and new land snow and lake schemes are introduced. The performance of the model using three configurations with different horizontal and vertical resolutions is compared to quality-controlled in situ data, remotely sensed and reanalysis products. Overall, significant improvements over previous models are seen, particularly in upper-atmosphere temperatures and winds, cloud heights, precipitation, and sea level pressure. Data–model comparisons continue, however, to highlight persistent problems in the marine stratocumulus regions.

Full access
Armin Sorooshian
,
Bruce Anderson
,
Susanne E. Bauer
,
Rachel A. Braun
,
Brian Cairns
,
Ewan Crosbie
,
Hossein Dadashazar
,
Glenn Diskin
,
Richard Ferrare
,
Richard C. Flagan
,
Johnathan Hair
,
Chris Hostetler
,
Haflidi H. Jonsson
,
Mary M. Kleb
,
Hongyu Liu
,
Alexander B. MacDonald
,
Allison McComiskey
,
Richard Moore
,
David Painemal
,
Lynn M. Russell
,
John H. Seinfeld
,
Michael Shook
,
William L. Smith Jr
,
Kenneth Thornhill
,
George Tselioudis
,
Hailong Wang
,
Xubin Zeng
,
Bo Zhang
,
Luke Ziemba
, and
Paquita Zuidema

Abstract

We report on a multiyear set of airborne field campaigns (2005–16) off the California coast to examine aerosols, clouds, and meteorology, and how lessons learned tie into the upcoming NASA Earth Venture Suborbital (EVS-3) campaign: Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE; 2019–23). The largest uncertainty in estimating global anthropogenic radiative forcing is associated with the interactions of aerosol particles with clouds, which stems from the variability of cloud systems and the multiple feedbacks that affect and hamper efforts to ascribe changes in cloud properties to aerosol perturbations. While past campaigns have been limited in flight hours and the ability to fly in and around clouds, efforts sponsored by the Office of Naval Research have resulted in 113 single aircraft flights (>500 flight hours) in a fixed region with warm marine boundary layer clouds. All flights used nearly the same payload of instruments on a Twin Otter to fly below, in, and above clouds, producing an unprecedented dataset. We provide here i) an overview of statistics of aerosol, cloud, and meteorological conditions encountered in those campaigns and ii) quantification of model-relevant metrics associated with aerosol–cloud interactions leveraging the high data volume and statistics. Based on lessons learned from those flights, we describe the pragmatic innovation in sampling strategy (dual-aircraft approach with combined in situ and remote sensing) that will be used in ACTIVATE to generate a dataset that can advance scientific understanding and improve physical parameterizations for Earth system and weather forecasting models, and for assessing next-generation remote sensing retrieval algorithms.

Full access
Xiang-Yu Li
,
Hailong Wang
,
Jingyi Chen
,
Satoshi Endo
,
Simon Kirschler
,
Christiane Voigt
,
Ewan Crosbie
,
Luke D. Ziemba
,
David Painemal
,
Brian Cairns
,
Johnathan W. Hair
,
Andrea F. Corral
,
Claire Robinson
,
Hossein Dadashazar
,
Armin Sorooshian
,
Gao Chen
,
Richard Anthony Ferrare
,
Mary M. Kleb
,
Hongyu Liu
,
Richard Moore
,
Amy Jo Scarino
,
Michael A. Shook
,
Taylor J. Shingler
,
Kenneth Lee Thornhill
,
Florian Tornow
,
Heng Xiao
, and
Xubin Zeng

Abstract

Aerosol effects on micro/macrophysical properties of marine stratocumulus clouds over the western North Atlantic Ocean (WNAO) are investigated using in situ measurements and large-eddy simulations (LES) for two cold-air outbreak (CAO) cases (28 February and 1 March 2020) during the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). The LES is able to reproduce the vertical profiles of liquid water content (LWC), effective radius r eff and cloud droplet number concentration Nc from fast cloud droplet probe (FCDP) in situ measurements for both cases. Furthermore, we show that aerosols affect cloud properties (Nc , r eff, and LWC) via the prescribed bulk hygroscopicity of aerosols ( κ ¯ ) and aerosol size distribution characteristics. Nc , r eff, and liquid water path (LWP) are positively correlated to κ ¯ and aerosol number concentration (Na ) while cloud fractional cover (CFC) is insensitive to κ ¯ and aerosol size distributions for the two cases. The realistic changes to aerosol size distribution (number concentration, width, and the geometrical diameter) with the same meteorology state allow us to investigate aerosol effects on cloud properties without meteorological feedback. We also use the LES results to evaluate cloud properties from two reanalysis products, ERA5 and MERRA-2. Compared to LES, the ERA5 is able to capture the time evolution of LWP and total cloud coverage within the study domain during both CAO cases while MERRA-2 underestimates them.

Open access