Reducing the Uncertainties in Direct Aerosol Radiative Forcing

Airborne particles, which include desert and soil dust, wildfire smoke, sea salt, volcanic ash, black carbon, natural and anthropogenic sulfate, nitrate, and organic aerosol, affect Earth's climate, in part by reflecting and absorbing sunlight. This paper reviews current status, and evaluates future prospects for reducing the uncertainty aerosols contribute to the energy budget of Earth, which at present represents a leading factor limiting the quality of climate predictions. Information from satellites is critical for this work, because they provide frequent, global coverage of the diverse and variable atmospheric aerosol load. Both aerosol amount and type must be determined. Satellites are very close to measuring aerosol amount at the level-of-accuracy needed, but aerosol type, especially how bright the airborne particles are, cannot be constrained adequately by current techniques. However, satellite instruments can map out aerosol air mass type, which is a qualitative classification rather than a quantitative measurement, and targeted suborbital measurements can provide the required particle property detail. So combining satellite and suborbital measurements, and then using this combination to constrain climate models, will produce a major advance in climate prediction

EARLINET evaluation of the CATS Level 2 aerosol backscatter coefficient product

We present the evaluation activity of the European Aerosol Research Lidar Network (EARLINET) for the quantitative assessment of the Level 2 aerosol backscatter coefficient product derived by the Cloud-Aerosol Transport System (CATS) aboard the International Space Station (ISS; Rodier et al., 2015). The study employs correlative CATS and EARLINET backscatter measurements within a 50¿km distance between the ground station and the ISS overpass and as close in time as possible, typically with the starting time or stopping time of the EARLINET performed measurement time window within 90¿min of the ISS overpass, for the period from February 2015 to September 2016. The results demonstrate the good agreement of the CATS Level 2 backscatter coefficient and EARLINET. Three ISS overpasses close to the EARLINET stations of Leipzig, Germany; Évora, Portugal; and Dushanbe, Tajikistan, are analyzed here to demonstrate the performance of the CATS lidar system under different conditions. The results show that under cloud-free, relative homogeneous aerosol conditions, CATS is in good agreement with EARLINET, independent of daytime and nighttime conditions. CATS low negative biases are observed, partially attributed to the deficiency of lidar systems to detect tenuous aerosol layers of backscatter signal below the minimum detection thresholds; these are biases which may lead to systematic deviations and slight underestimations of the total aerosol optical depth (AOD) in climate studies. In addition, CATS misclassification of aerosol layers as clouds, and vice versa, in cases of coexistent and/or adjacent aerosol and cloud features, occasionally leads to non-representative, unrealistic, and cloud-contaminated aerosol profiles. Regarding solar illumination conditions, low negative biases in CATS backscatter coefficient profiles, of the order of 6.1¿%, indicate the good nighttime performance of CATS. During daytime, a reduced signal-to-noise ratio by solar background illumination prevents retrievals of weakly scattering atmospheric layers that would otherwise be detectable during nighttime, leading to higher negative biases, of the order of 22.3¿%.Peer ReviewedPostprint (published version

Synergy of Multiple Satellite Observations in the Study of Cloud Thermodynamics of Tropical Deep Convection.

Tropical convection lies at the heart of atmospheric research, especially for global weather and climate predictions; satellite measurements with large spatial coverage provide valuable information to deepen and broaden our scientific understandings of this subject. This thesis is motivated to utilize satellite measurements with assistance of modeling tools in a synergistic way to study tropical deep convection. First a generic parallax correction method is proposed to remove the biases resulting from the mismatch of satellite footprints due to different sensor viewing angles targeting the same object. Second a non-blackbody correction is proposed to better estimate cloud top temperature utilizing the vertical structure within the cloud top layer probed by CloudSat and CALIPSO. The distance between the physical cloud top and the effective emission level is shown to have a linear dependence on cloud top fuzziness (CTF; difference between cloud top and 10dBz radar echo) when CTF is less than ~2km. Beyond this threshold, the effective emission level remains 0.74km below the cloud top due to the saturation of IR absorption and emission. This relationship clearly improves simulated MODIS radiances comparing with the observed counterparts. The distribution of cloud top buoyancy for tropical deep convections derived using cloud top and ambient condition indicates that convective development is sensitive to both land-ocean contrast and diurnal cycle. Under certain assumptions, vertical velocity inside the convective core is derived and the result is consistent with typical vertical velocity profiles observed by air-bone Doppler radars for tropical deep convections, such as the altitude for the maximum vertical velocity and the existence of a weak detrainment layer in the mid-troposphere. GCM simulations indicate that overshooting deep convection could be responsible for the vertical transport of black carbon into the stratosphere especially over the India subcontinent during South Asia summer monsoon, and that black carbon in the stratosphere is transported upward at as large as twice the speed of water vapor transport. To explore a possible observational strategy for such injection of black carbon into the stratosphere, a limb-view infrared detection method is proposed based on forward modeling of radiative transfer and the simulated profiles.PhDAtmospheric, Oceanic and Space SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/109016/1/cpwang_1.pd

Developing and testing a coupled regional modeling system for establishing an integrated modeling and observational framework for dust aerosol

To this date, estimates of the climate response to mineral dust remain largely uncertain because of our limited capability to quantify dust distribution in the atmosphere. Focusing on the Central and East Asian dust source regions, this thesis aims to develop a coupled regional dust modeling system to provide an improved modeling capability of atmospheric dust as well as to aid the integration of ground-based and satellite observations. The objectives of this study are as follows: 1) evaluate the capabilities of the available data to detect and quantify mineral dust in the atmosphere; 2) develop and test a coupled regional dust modeling system able to simulate size resolved dust concentrations accounting for the regional specifics of Central and East Asia; and 3) outline a methodology for data and modeling integration. The capabilities of ground-based and satellite data to characterize dust in the atmosphere are examined in great details. Based on analysis of MODIS data reflectance and radiances, we found evidence for regional signature of dust in near-IR and proposed a new probabilistic dust-cloud mask that explicitly takes into account the spatial variability characteristics of dust aerosols. We developed a coupled regional dust modeling system (WRF-DuMo) by incorporating a dust emission module (DuMo) into the NCAR WRF model. The WRF-DuMo unique capabilities include explicit treatment of land surface properties in Central and East Asia, a suite of dust emission schemes with different levels of complexity, multiple options for dust injection in the atmosphere and flexible parameters of the initial size distribution of emitted dust. Two representative dust events that originated in East Asia in the springs of 2001 and 2007 have been modeled with WRF-DuMo. Simulations with different initial size distribution of dust, injection and emission parameterizations have been performed to investigate their relative role on the modeled dust fields. We performed an integrated analysis of modeled dust fields and satellite observations by introducing an ensemble model dust index, which used in conjunction with satellite dust retrievals improves the capability to characterize dust fields. Finally, we provide recommendations for the development of an integrated observational and modeling dust framework.Ph.D.Committee Chair: Sokolik, Irina; Committee Member: Curry, Judith; Committee Member: Kalashnikova, Olga; Committee Member: Nenes, Athanasios; Committee Member: Stieglitz, Mar

Aerosol typing over Europe and its benefits for the CALIPSO and EarthCARE missions: Statistical analysis based on multiwavelength aerosol lidar measurements from ground-based EARLINET stations and comparison to spaceborne CALIPSO data

Aerosols show type-specific characteristics, which depend on intensive aerosol optical and microphysical properties that influence the radiation processes in the atmosphere in several ways. There are still large uncertainties in the calculation of the aerosol direct radiative effect. The classification of aerosols and the characterization of the vertical aerosol distribution is needed in order to provide more accurate information for radiative-transfer simulations. In the framework of the present thesis, the vertical and spatial distribution as well as optical properties of atmospheric aerosols over the European continent were investigated based on lidar measurements. Possibilities for an aerosol classification or so-called aerosol typing were presented and major aerosol types were specified. Former studies about the classification of aerosols were summarized and representative values for aerosol-type-dependent parameters were given. Case studies were used to demonstrate how observations of the European lidar network EARLINET from 2008 until 2010 were analyzed for aerosol layers and how model simulations and auxiliary data including the assessment of meteorological conditions were applied to determine the origin of each single aerosol layer. Thus, aerosol-type dependent parameters were evaluated and a novel method for the typing of aerosols was developed, which can be used, e.g., within algorithms of satellite data retrievals. Additionally, conversion factors were determined, which are needed for the harmonization of satellite data of present and upcoming missions. Furthermore, findings of the aerosol typing based on EARLINET data were compared to results of the aerosol classification scheme for satellite-borne lidar measurements onboard CALIPSO. It could be shown that deficient classifications of the aerosol type emerged systematically within the automated CALIPSO algorithm. Those wrong classification leads to an underestimation of the single-scattering albedo and hence to an overestimation of the warming effect of the respective aerosol layer. This overestimated warming effect has to be kept in mind for simulations of the global aerosol radiative effect based on CALIPSO data.Die Bestimmung des direkten Strahlungsantriebs von Aerosolen ist mit großen Unsicherheiten behaftet. Inwiefern Aerosole die Strahlungsprozesse in der Atmosphäre beeinflussen ist abhängig von ihren optischen und mikrophysikalischen Eigenschaften. Zur Optimierung von Strahlungstransfersimulationen werden daher ergänzende Informationen über typspezifische Aerosoleigenschaften sowie die vertikale Aerosolverteilung benötigt. Im Rahmen der vorliegenden Arbeit wurden anhand von Lidarmessungen die vertikale und räumliche Verteilung atmosphärischer Aerosole über Europa analysiert sowie deren optische Eigenschaften ermittelt. Einleitend werden Möglichkeiten der Aerosolklassifizierung erläutert und Aerosoltypen spezifiziert, die über Europa beobachtet werden können. Vorherige Studien zur Aerosolklassifizierung sind in einer Literaturübersicht zusammengefasst. Anhand von Fallstudien wurde zunächst die Analyse von Beobachtungen des europäischen Lidarnetzwerkes EARLINET von 2008 bis 2010 auf das Vorhandensein von Aerosolschichten verdeutlicht. Die Herkunft jeder einzelnen Aerosolschicht wurde anschließend unter Verwendung von Modellrechnungen sowie weiteren Informationen bestimmt und aerosoltypspezifische Kenngrößen berechnet. Mit Hilfe dieser Kenngrößen ist es möglich, den Typ des Aerosols abzuleiten. Daraus wurde eine neuartige Methode zur Typisierung von Aerosolen entwickelt, die z.B. in Algorithmen zur Verarbeitung von Satellitendaten verwendet werden kann. Zusätzlich wurden Umrechnungsfaktoren bestimmt, die zur Zusammenführung und zum Vergleich von Daten aktueller und zukünftiger Satellitenmissionen benötigt werden. Die Ergebnisse der Aerosoltypisierung auf Basis von EARLINET-Daten wurden anschließend mit Ergebnissen der automatischen Typisierung weltraumbasierter Lidarmessungen des CALIPSO-Satelliten verglichen. Es konnte gezeigt werden, dass innerhalb des CALIPSO-Algorithmus systematisch fehlerhafte Klassifizierungen des Aerosoltyps auftreten. Diese falsche Klassifizierung führt zu einer Unterschätzung der Einfachstreualbedo und zu einer Überschätzung der erwärmenden Wirkung der betreffenden Aerosolschicht. Die überschätzte Wärmewirkung hat wiederum fehlerhafte Ergebnisse bei Strahlungstransferrechnungen, die auf CALIPSO-Daten basieren, zur Folge

Aerosol typing over Europe and its benefits for the CALIPSO and EarthCARE missions: Statistical analysis based on multiwavelength aerosol lidar measurements from ground-based EARLINET stations and comparison to spaceborne CALIPSO data

Aerosols show type-specific characteristics, which depend on intensive aerosol optical and microphysical properties that influence the radiation processes in the atmosphere in several ways. There are still large uncertainties in the calculation of the aerosol direct radiative effect. The classification of aerosols and the characterization of the vertical aerosol distribution is needed in order to provide more accurate information for radiative-transfer simulations. In the framework of the present thesis, the vertical and spatial distribution as well as optical properties of atmospheric aerosols over the European continent were investigated based on lidar measurements. Possibilities for an aerosol classification or so-called aerosol typing were presented and major aerosol types were specified. Former studies about the classification of aerosols were summarized and representative values for aerosol-type-dependent parameters were given. Case studies were used to demonstrate how observations of the European lidar network EARLINET from 2008 until 2010 were analyzed for aerosol layers and how model simulations and auxiliary data including the assessment of meteorological conditions were applied to determine the origin of each single aerosol layer. Thus, aerosol-type dependent parameters were evaluated and a novel method for the typing of aerosols was developed, which can be used, e.g., within algorithms of satellite data retrievals. Additionally, conversion factors were determined, which are needed for the harmonization of satellite data of present and upcoming missions. Furthermore, findings of the aerosol typing based on EARLINET data were compared to results of the aerosol classification scheme for satellite-borne lidar measurements onboard CALIPSO. It could be shown that deficient classifications of the aerosol type emerged systematically within the automated CALIPSO algorithm. Those wrong classification leads to an underestimation of the single-scattering albedo and hence to an overestimation of the warming effect of the respective aerosol layer. This overestimated warming effect has to be kept in mind for simulations of the global aerosol radiative effect based on CALIPSO data.Die Bestimmung des direkten Strahlungsantriebs von Aerosolen ist mit großen Unsicherheiten behaftet. Inwiefern Aerosole die Strahlungsprozesse in der Atmosphäre beeinflussen ist abhängig von ihren optischen und mikrophysikalischen Eigenschaften. Zur Optimierung von Strahlungstransfersimulationen werden daher ergänzende Informationen über typspezifische Aerosoleigenschaften sowie die vertikale Aerosolverteilung benötigt. Im Rahmen der vorliegenden Arbeit wurden anhand von Lidarmessungen die vertikale und räumliche Verteilung atmosphärischer Aerosole über Europa analysiert sowie deren optische Eigenschaften ermittelt. Einleitend werden Möglichkeiten der Aerosolklassifizierung erläutert und Aerosoltypen spezifiziert, die über Europa beobachtet werden können. Vorherige Studien zur Aerosolklassifizierung sind in einer Literaturübersicht zusammengefasst. Anhand von Fallstudien wurde zunächst die Analyse von Beobachtungen des europäischen Lidarnetzwerkes EARLINET von 2008 bis 2010 auf das Vorhandensein von Aerosolschichten verdeutlicht. Die Herkunft jeder einzelnen Aerosolschicht wurde anschließend unter Verwendung von Modellrechnungen sowie weiteren Informationen bestimmt und aerosoltypspezifische Kenngrößen berechnet. Mit Hilfe dieser Kenngrößen ist es möglich, den Typ des Aerosols abzuleiten. Daraus wurde eine neuartige Methode zur Typisierung von Aerosolen entwickelt, die z.B. in Algorithmen zur Verarbeitung von Satellitendaten verwendet werden kann. Zusätzlich wurden Umrechnungsfaktoren bestimmt, die zur Zusammenführung und zum Vergleich von Daten aktueller und zukünftiger Satellitenmissionen benötigt werden. Die Ergebnisse der Aerosoltypisierung auf Basis von EARLINET-Daten wurden anschließend mit Ergebnissen der automatischen Typisierung weltraumbasierter Lidarmessungen des CALIPSO-Satelliten verglichen. Es konnte gezeigt werden, dass innerhalb des CALIPSO-Algorithmus systematisch fehlerhafte Klassifizierungen des Aerosoltyps auftreten. Diese falsche Klassifizierung führt zu einer Unterschätzung der Einfachstreualbedo und zu einer Überschätzung der erwärmenden Wirkung der betreffenden Aerosolschicht. Die überschätzte Wärmewirkung hat wiederum fehlerhafte Ergebnisse bei Strahlungstransferrechnungen, die auf CALIPSO-Daten basieren, zur Folge

The Atmospheric Infrared Sounder Version 6 Cloud Products

The version 6 cloud products of the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) instrument suite are described. The cloud top temperature, pressure, and height and effective cloud fraction are now reported at the AIRS field-of-view (FOV) resolution. Significant improvements in cloud height assignment over version 5 are shown with FOV-scale comparisons to cloud vertical structure observed by the CloudSat 94 GHz radar and the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP). Cloud thermodynamic phase (ice, liquid, and unknown phase), ice cloud effective diameter D(sub e), and ice cloud optical thickness () are derived using an optimal estimation methodology for AIRS FOVs, and global distributions for 2007 are presented. The largest values of tau are found in the storm tracks and near convection in the tropics, while D(sub e) is largest on the equatorial side of the midlatitude storm tracks in both hemispheres, and lowest in tropical thin cirrus and the winter polar atmosphere. Over the Maritime Continent the diurnal variability of tau is significantly larger than for the total cloud fraction, ice cloud frequency, and D(sub e), and is anchored to the island archipelago morphology. Important differences are described between northern and southern hemispheric midlatitude cyclones using storm center composites. The infrared-based cloud retrievals of AIRS provide unique, decadal-scale and global observations of clouds over portions of the diurnal and annual cycles, and capture variability within the mesoscale and synoptic scales at all latitudes

Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud_cci project

New cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS are presented. Two retrieval systems were developed that include components for cloud detection and cloud typing followed by cloud property retrievals based on the optimal estimation (OE) technique. The OE-based retrievals are applied to simultaneously retrieve cloud-top pressure, cloud particle effective radius and cloud optical thickness using measurements at visible, near-infrared and thermal infrared wavelengths, which ensures spectral consistency. The retrieved cloud properties are further processed to derive cloud-top height, cloud-top temperature, cloud liquid water path, cloud ice water path and spectral cloud albedo. The Cloud_cci products are pixel-based retrievals, daily composites of those on a global equal-angle latitude–longitude grid, and monthly cloud properties such as averages, standard deviations and histograms, also on a global grid. All products include rigorous propagation of the retrieval and sampling uncertainties. Grouping the orbital properties of the sensor families, six datasets have been defined, which are named AVHRR-AM, AVHRR-PM, MODIS-Terra, MODIS-Aqua, ATSR2-AATSR and MERIS+AATSR, each comprising a specific subset of all available sensors. The individual characteristics of the datasets are presented together with a summary of the retrieval systems and measurement records on which the dataset generation were based. Example validation results are given, based on comparisons to well- established reference observations, which demonstrate the good quality of the data. In particular the ensured spectral consistency and the rigorous uncertainty propagation through all processing levels can be considered as new features of the Cloud_cci datasets compared to existing datasets. In addition, the consistency among the individual datasets allows for a potential combination of them as well as facilitates studies on the impact of temporal sampling and spatial resolution on cloud climatologies

SPARE-ICE: synergistic Ice Water Path from passive operational sensors

This article presents SPARE-ICE, the Synergistic Passive Atmospheric Retrieval Experiment-ICE. SPARE-ICE is the first Ice Water Path (IWP) product combining infrared and microwave radiances. By using only passive operational sensors, the SPARE-ICE retrieval can be used to process data from at least the NOAA 15 to 19 and MetOp satellites, obtaining time series from 1998 onward. The retrieval is developed using collocations between passive operational sensors (solar, terrestrial infrared, microwave), the CloudSat radar, and the CALIPSO lidar. The collocations form a retrieval database matching measurements from passive sensors against the existing active combined radar-lidar product 2C-ICE. With this retrieval database, we train a pair of artificial neural networks to detect clouds and retrieve IWP. When considering solar, terrestrial infrared, and microwave-based measurements, we show that any combination of two techniques performs better than either single-technique retrieval. We choose not to include solar reflectances in SPARE-ICE, because the improvement is small, and so that SPARE-ICE can be retrieved both daytime and nighttime. The median fractional error between SPARE-ICE and 2C-ICE is around a factor 2, a figure similar to the random error between 2C-ICE ice water content (IWC) and in situ measurements. A comparison of SPARE-ICE with Moderate Resolution Imaging Spectroradiometer (MODIS), Pathfinder Atmospheric Extended (PATMOS-X), and Microwave Surface and Precipitation Products System (MSPPS) indicates that SPARE-ICE appears to perform well even in difficult conditions. SPARE-ICE is available for public use

Earth System Science Research Using Datra and Products from Terra, Aqua, and ACRIM Satellites

The report describes the research conducted at CSR to extend MODIS data and products to the applications required by users in the State of Texas. This research presented in this report was completed during the timeframe of August 2004 - December 31, 2007. However, since annual reports were filed in December 2005 and 2006, results obtained during calendar year 2007 are emphasized in the report. The stated goals of the project were to complete the fundamental research needed to create two types of new, Level 3 products for the air quality community in Texas from data collected by NASA s EOS Terra and Aqua missions