A Comparative Study of Cloud Properties Between Northern and Southern High Latitudes Based on ARM Observations and EAMv2 Simulations
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54 ENVIRONMENTAL SCIENCES↗
Engineering topics
Liu, X.
Publications and source records attributed to Liu, X..
CIRCLEZ : Reliable photometric redshifts for active galactic nuclei computed solely using photometry from Legacy Survey Imaging for DESI
Photometric redshifts for galaxies hosting an accreting supermassive black hole in their center, known as active galactic nuclei (AGNs), are notoriously challenging. At present, they are most optimally computed via spectral energy distribution (SED) fittings, assuming that deep photometry for many wavelengths is available. However, for AGNs detected from all-sky surveys, the photometry is limited and provided by a range of instruments and studies. This makes the task of homogenizing the data challenging, presenting a dramatic drawback for the millions of AGNs that wide surveys such as SRG/eROSITA are poised to detect. This work aims to compute reliable photometric redshifts for X-ray-detected AGNs using only one dataset that covers a large area: the tenth data release of the Imaging Legacy Survey (LS10) for DESI. LS10 provides deep grizW1-W4 forced photometry within various apertures over the footprint of the eROSITA-DE survey, which avoids issues related to the cross-calibration of surveys. We present the results from CIRCLEZ, a machine-learning algorithm based on a fully connected neural network. CIRCLEZ is built on a training sample of 14 000 X-ray-detected AGNs and utilizes multi-aperture photometry, mapping the light distribution of the sources. The accuracy (σNMAD) and the fraction of outliers (η) reached in a test sample of 2913 AGNs are equal to 0.067 and 11.6%, respectively. The results are comparable to (or even better than) what was previously obtained for the same field, but with much less effort in this instance. We further tested the stability of the results by computing the photometric redshifts for the sources detected in CSC2 and Chandra-COSMOS Legacy, reaching a comparable accuracy as in eFEDS when limiting the magnitude of the counterparts to the depth of LS10. The method can be applied to fainter samples of AGNs using deeper optical data from future surveys (for example, LSST, Euclid), granting LS10-like information on the light distribution beyond the morphological type. Along with this paper, we have released an updated version of the photometric redshifts (including errors and probability distribution functions) for eROSITA/eFEDS.
79 ASTRONOMY AND ASTROPHYSICS↗
Multi-messenger Astrophysics with Pulsar Timing Arrays: Astro2020 Science White Paper
Pulsar timing arrays (PTAs) are on the verge of detecting low-frequency gravitational waves (GWs)from supermassive black hole binaries (SMBHBs). With continued observations of a large sampleof millisecond pulsars, PTAs will reach this major milestone within the next decade. Already,SMBHB candidates are being identied by electromagnetic surveys in ever-increasing numbers;upcoming surveys will enhance our ability to detect and verify candidates, and will be instrumentalin identifying the host galaxies of GW sources. Multi-messenger (GW and electromagnetic) obser-vations of SMBHBs will revolutionize our understanding of the co-evolution of SMBHs with theirhost galaxies, the dynamical interactions between binaries and their galactic environments, and thefundamental physics of accretion. Multi-messenger observations can also make SMBHBs `standardsirens' for cosmological distance measurements out to z ~ 0.5 LIGO has already ushered in break-through insights in our knowledge of black holes. The multi-messenger detection of SMBHBs withPTAs will be a breakthrough in the years 2020-2030 and beyond, and prepare us for LISA to helpcomplete our views of black hole demographics and evolution at higher redshifts.
Kelley, L. Z.↗
The Pathfinder Mission for Climate Absolute Radiance and Refractivity Observatory
Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, and sea level has risen.
Baize, R. R.↗
Agricultural Fires in the Southeastern U.S. During SEAC4RS: Emissions of Trace Gases and Particles and Evolution of Ozone, Reactive Nitrogen, and Organic Aerosol
Emissions from 15 agricultural fires in the southeastern U.S. were measured from the NASA DC-8 research aircraft during the summer 2013 Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign. This study reports a detailed set of emission factors (EFs) for 25 trace gases and 6 fine particle species. The chemical evolution of the primary emissions in seven plumes was examined in detail for ~1.2 h. A Lagrangian plume cross-section model was used to simulate the evolution of ozone (O3), reactive nitrogen species, and organic aerosol (OA). Observed EFs are generally consistent with previous measurements of crop residue burning, but the fires studied here emitted high amounts of SO2 and fine particles, especially primary OA and chloride. Filter-based measurements of aerosol light absorption implied that brown carbon (BrC) was ubiquitous in the plumes. In aged plumes, rapid production of O3, peroxyacetyl nitrate (PAN), and nitrate was observed with (Delta)O3/(Delta)CO, (Delta)PAN/(Delta)NOy, and (Delta)nitrate/(Delta)NOy reaching approx. 0.1, approx. 0.3, and approx.0.3. For five selected cases, the model reasonably simulated O3 formation but underestimated PAN formation. No significant evolution of OA mass or BrC absorption was observed. However, a consistent increase in oxygen-to-carbon (O/C) ratios of OA indicated that OA oxidation in the agricultural fire plumes was much faster than in urban and forest fire plumes. Finally, total annual SO2, NOx, and CO emissions from agricultural fires in Arkansas, Louisiana, Mississippi, and Missouri were estimated (within a factor of approx. 2) to be equivalent to approx. 2% SO2 from coal combustion and approx. 1% NOx and approx. 9% CO from mobile sources.
OA mass or BrC absorption↗
MUlti-SpEctral, MUlti-SpEcies, MUlti-SatEllite (MUSES) Retrieval Algorithm: Towards Extending Multi-Decadal NASA EOS Atmospheric Composition Data Records
Multi-Spectra, Multi-Species, Multi-Sensors (MUSES): Builds off of heritage from the Tropospheric Emission Spectrometer (TES) optimal estimation (OE) algorithm to combine a priori and satellite data, including rigorous error analysis diagnostics and observation operators needed for trend analysis, climate model evaluation, and data assimilation; has generic design to incorporate forward model radiances from hyperspectral measurements from multiple sensors into the joint retrieval algorithm.
Fu, Dejian↗
An Optimal-Estimation-Based Aerosol Retrieval Algorithm Using OMI Near-UV Observations
An optimal-estimation(OE)-based aerosol retrieval algorithm using the OMI (Ozone Monitoring Instrument) near-ultraviolet observation was developed in this study. The OE-based algorithm has the merit of providing useful estimates of errors simultaneously with the inversion products. Furthermore, instead of using the traditional lookup tables for inversion, it performs online radiative transfer calculations with the VLIDORT (linearized pseudo-spherical vector discrete ordinate radiative transfer code) to eliminate interpolation errors and improve stability. The measurements and inversion products of the Distributed Regional Aerosol Gridded Observation Network campaign in northeast Asia (DRAGON NE-Asia 2012) were used to validate the retrieved aerosol optical thickness (AOT) and single scattering albedo (SSA). The retrieved AOT and SSA at 388 nm have a correlation with the Aerosol Robotic Network (AERONET) products that is comparable to or better than the correlation with the operational product during the campaign. The OEbased estimated error represented the variance of actual biases of AOT at 388 nm between the retrieval and AERONET measurements better than the operational error estimates. The forward model parameter errors were analyzed separately for both AOT and SSA retrievals. The surface reflectance at 388 nm, the imaginary part of the refractive index at 354 nm, and the number fine-mode fraction (FMF) were found to be the most important parameters affecting the retrieval accuracy of AOT, while FMF was the most important parameter for the SSA retrieval. The additional information provided with the retrievals, including the estimated error and degrees of freedom, is expected to be valuable for relevant studies. Detailed advantages of using the OE method were described and discussed in this paper.
Air Pollution↗
Improved O3 and CO Profile Retrievals Using Multispectral Measurements from NASA ''A Train'', Suomi NPP, and S5P Satellites
No abstract available
carbon monozide↗
Quantifying Sources and Sinks of Reactive Gases in the Lower Atmosphere Using Airborne Flux Observations
Atmospheric composition is governed by the interplay of emissions, chemistry, deposition, and transport. Substantial questions surround each of these processes, especially in forested environments with strong biogenic emissions. Utilizing aircraft observations acquired over a forest in the southeast U.S., we calculate eddy covariance fluxes for a suite of reactive gases and apply the synergistic information derived from this analysis to quantify emission and deposition fluxes, oxidant concentrations, aerosol uptake coefficients, and other key parameters. Evaluation of results against state-of-the-science models and parameterizations provides insight into our current understanding of this system and frames future observational priorities. As a near-direct measurement of fundamental process rates, airborne fluxes offer a new tool to improve biogenic and anthropogenic emissions inventories, photochemical mechanisms, and deposition parameterizations.
emission↗
IR Instrument Accuracy Required for Atmospheric Temperature and Water Vapor Trend Detection
This presentation describes how to define IR instrument requirement based on atmospheric temperature and water variability.
Liu, X.↗
Science Accomplishments from a Decade of Aura OMI/MLS Tropospheric Ozone Measurements
Measurements of tropospheric ozone from combined Aura OMI and MLS instruments have yielded a large number of new and important science discoveries over the last decade. These discoveries have generated a much greater understanding of biomass burning, lightning NO, and stratosphere-troposphere exchange sources of tropospheric ozone, ENSO dynamics and photochemistry, intra-seasonal variability-Madden-Julian Oscillation including convective transport, radiative forcing, measuring ozone pollution from space, improvements to ozone retrieval algorithms, and evaluation of chemical-transport and chemistry-climate models. The OMI-MLS measurements have been instrumental in giving us better understanding of the dynamics and chemistry involving tropospheric ozone and the many drivers affecting the troposphere in general. This discussion will provide an overview focusing on our main science results.
ENSO↗
Intercomparison and Evaluation of Global Aerosol Microphysical Properties Among Aerocom Models of a Range of Complexity
Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multimodel- mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation an growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.
Cloud physics↗
An AeroCom Assessment of Black Carbon in Arctic Snow and Sea Ice
Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. Here, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Models (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We accomplish this by driving the offline land and sea ice components of the Community Earth System Model with different deposition fields and meteorological conditions from 2004 to 2009, during which an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measurements, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are −4.4 (−13.2 to +10.7) ng/g for an earlier phase of AeroCom models (phase I), and +4.1 (−13.0 to +21.4) ng/g for a more recent phase of AeroCom models (phase II), compared to the observational mean of 19.2 ng/g. Factors determining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, precipitation, deposition efficiency of aerosols within the Arctic, and meltwater removal of particles in snow. Sensitivity studies show that the model-measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60-90degN) atmospheric residence time for BC in phase II models ranges from 3.7 to 23.2 days, implying large inter-model variation in local BC deposition efficiency. Combined with the fact that most Arctic BC deposition originates from extra-Arctic emissions, these results suggest that aerosol removal processes are a leading source of variation in model performance. The multi-model mean (full range) of Arctic radiative effect from BC in snow is 0.15 (0.07-0.25) W/sq m and 0.18 (0.06-0.28) W/sq m in phase I and phase II models, respectively. After correcting for model biases relative to observed BC concentrations in different regions of the Arctic, we obtain a multi-model mean Arctic radiative effect of 0.17 W/sq m for the combined AeroCom ensembles. Finally, there is a high correlation between modeled BC concentrations sampled over the observational sites and the Arctic as a whole, indicating that the field campaign provided a reasonable sample of the Arctic.
carbon↗
Application of OMI, SCIAMACHY and GOME-2 Satellite SO2 Retrievals for Detection of Large Emission Sources
Retrievals of sulfur dioxide (SO2) from space-based spectrometers are in a relatively early stage of development. Factors such as interference between ozone and SO2 in the retrieval algorithms often lead to errors in the retrieved values. Measurements from the Ozone Monitoring Instrument (OMI), Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and Global Ozone Monitoring Experiment-2 (GOME-2) satellite sensors, averaged over a period of several years, were used to identify locations with elevated SO2 values and estimate their emission levels. About 30 such locations, detectable by all three sensors and linked to volcanic and anthropogenic sources, were found after applying low and high spatial frequency filtration designed to reduce noise and bias and to enhance weak signals to SO2 data from each instrument. Quantitatively, the mean amount of SO2 in the vicinity of the sources, estimated from the three instruments, is in general agreement. However, its better spatial resolution makes it possible for OMI to detect smaller sources and with additional detail as compared to the other two instruments. Over some regions of China, SCIAMACHY and GOME-2 data show mean SO2 values that are almost 1.5 times higher than those from OMI, but the suggested spatial filtration technique largely reconciles these differences.
SO2 retrievals↗
Achieving Climate Change Absolute Accuracy in Orbit
The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREO's inherently high absolute accuracy will be verified and traceable on orbit to Système Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earth's thermal infrared spectrum (5-50 micron), the spectrum of solar radiation reflected by the Earth and its atmosphere (320-2300 nm), and radio occultation refractivity from which accurate temperature profiles are derived. The mission has the ability to provide new spectral fingerprints of climate change, as well as to provide the first orbiting radiometer with accuracy sufficient to serve as the reference transfer standard for other space sensors, in essence serving as a "NIST [National Institute of Standards and Technology] in orbit." CLARREO will greatly improve the accuracy and relevance of a wide range of space-borne instruments for decadal climate change. Finally, CLARREO has developed new metrics and methods for determining the accuracy requirements of climate observations for a wide range of climate variables and uncertainty sources. These methods should be useful for improving our understanding of observing requirements for most climate change observations.
Wielicki, Bruce A.↗
Assessment and Applications of NASA Ozone Data Products Derived from Aura OMI-MLS Satellite Measurements in Context of the GMI Chemical Transport Model
Measurements from the Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS), both onboard the Aura spacecraft, have been used to produce daily global maps of column and profile ozone since August 2004. Here we compare and evaluate three strategies to obtain daily maps of tropospheric and stratospheric ozone from OMI and MLS measurements: trajectory mapping, direct profile retrieval, and data assimilation. Evaluation is based upon an assessment that includes validation using ozonesondes and comparisons with the Global Modeling Initiative (GMI) chemical transport model (CTM). We investigate applications of the three ozone data products from near-decadal and inter-annual timescales to day-to-day case studies. Zonally averaged inter-annual changes in tropospheric ozone from all of the products in any latitude range are of the order 1-2 Dobson Units while changes (increases) over the 8-year Aura record investigated http://eospso.gsfc.nasa.gov/atbd-category/49 vary approximately 2-4 Dobson Units. It is demonstrated that all of the ozone products can measure and monitor exceptional tropospheric ozone events including major forest fire and pollution transport events. Stratospheric ozone during the Aura record has several anomalous inter-annual events including stratospheric warming split events in the Northern Hemisphere extra-tropics that are well captured using the data assimilation ozone profile product. Data assimilation with continuous daily global coverage and vertical ozone profile information is the best of the three strategies at generating a global tropospheric and stratospheric ozone product for science applications.
GMI↗
A Single-column Model Ensemble Approach Applied to the TWP-ICE Experiment
Single-column models (SCM) are useful test beds for investigating the parameterization schemes of numerical weather prediction and climate models. The usefulness of SCM simulations are limited, however, by the accuracy of the best estimate large-scale observations prescribed. Errors estimating the observations will result in uncertainty in modeled simulations. One method to address the modeled uncertainty is to simulate an ensemble where the ensemble members span observational uncertainty. This study first derives an ensemble of large-scale data for the Tropical Warm Pool International Cloud Experiment (TWP-ICE) based on an estimate of a possible source of error in the best estimate product. These data are then used to carry out simulations with 11 SCM and two cloud-resolving models (CRM). Best estimate simulations are also performed. All models show that moisture-related variables are close to observations and there are limited differences between the best estimate and ensemble mean values. The models, however, show different sensitivities to changes in the forcing particularly when weakly forced. The ensemble simulations highlight important differences in the surface evaporation term of the moisture budget between the SCM and CRM. Differences are also apparent between the models in the ensemble mean vertical structure of cloud variables, while for each model, cloud properties are relatively insensitive to forcing. The ensemble is further used to investigate cloud variables and precipitation and identifies differences between CRM and SCM particularly for relationships involving ice. This study highlights the additional analysis that can be performed using ensemble simulations and hence enables a more complete model investigation compared to using the more traditional single best estimate simulation only.
numerical weather forecasting↗