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At least 487 records · Page 27

Significance of agricultural row structure on the microwave emissivity of soils

A series of field experiments was carried out to extend the data base available for verifying agricultural row effect models of emissivity. The row effects model was used to simulate a data base from which an algorithm could be developed to account for row effects when the scene dielectric constant and small-scale roughness are unknown. One objective of the study was to quantify the significance of row structure and to develop a practical procedure for removing the effects of periodic row structure on the microwave emissivity of a soil in order to use the emissivity values to estimate the soil moisture. A second objective was to expand the data set available for model verification through field observations using a truck-mounted 1.4-GHz microwave radiometer.

Promes, P. M.↗

CO2 Condensation Models for Mars

During the polar night in both hemispheres of Mars, regions of low thermal emission, frequently referred to as "cold spots", have been observed by Mariner 9, Viking and Mars Global Surveyor (MGS) spacecraft. These cold spots vary in time and appear to be associated with topographic features suggesting that they are the result of a spectral-emission effect due to surface accumulation of fine-grained frost or snow. Presented here are simulations of the Martian polar night using the NASA Ames General Circulation Cloud Model. This cloud model incorporates all the microphysical processes of carbon dioxide cloud formation, including nucleation, condensation and sedimentation and is coupled to a surface frost scheme that includes both direct surface condensation and precipitation. Using this cloud model we simulate the Mars polar nights and compare model results to observations from the Thermal Emission Spectrometer (TES) and the Mars Orbiter Laser Altimeter (MOLA). Model predictions of "cold spots" compare well with TES observations of low emissivity regions, both spatially and as a function of season. The model predicted frequency of CO2 cloud formation also agrees well with MOLA observations of polar night cloud echoes. Together the simulations and observations in the North indicate a distinct shift in atmospheric state centered about Ls 270 which we believe may be associated with the strength of the polar vortex.

Colaprete, A.↗

Spectral Confusion for Cosmological Surveys of Redshifted C II Emission

Far-infrared cooling lines are ubiquitous features in the spectra of star-forming galaxies. Surveys of redshifted fine-structure lines provide a promising new tool to study structure formation and galactic evolution at redshifts including the epoch of reionization as well as the peak of star formation. Unlike neutral hydrogen surveys, where the 21 cm line is the only bright line, surveys of redshifted fine-structure lines suffer from confusion generated by line broadening, spectral overlap of different lines, and the crowding of sources with redshift. We use simulations to investigate the resulting spectral confusion and derive observing parameters to minimize these effects in pencilbeam surveys of redshifted far-IR line emission. We generate simulated spectra of the 17 brightest far-IR lines in galaxies, covering the 150-1300 μm wavelength region corresponding to redshifts 0 < z < 7, and develop a simple iterative algorithm that successfully identifies the 158 μm [C II] line and other lines. Although the [C II] line is a principal coolant for the interstellar medium, the assumption that the brightest observed lines in a given line of sight are always [C II] lines is a poor approximation to the simulated spectra once other lines are included. Blind line identification requires detection of fainter companion lines from the same host galaxies, driving survey sensitivity requirements. The observations require moderate spectral resolution 700 < R < 4000 with angular resolution between 20″ and 10′, sufficiently narrow to minimize confusion yet sufficiently large to include a statistically meaningful number of sources.

galactic evolution at redshifts↗

On the uncertainty in single molecule fluorescent lifetime and energy emission measurements

Time-correlated single photon counting has recently been combined with mode-locked picosecond pulsed excitation to measure the fluorescent lifetimes and energy emissions of single molecules in a flow stream. Maximum likelihood (ML) and least square methods agree and are optimal when the number of detected photons is large however, in single molecule fluorescence experiments the number of detected photons can be less than 20, 67% of those can be noise and the detection time is restricted to 10 nanoseconds. Under the assumption that the photon signal and background noise are two independent inhomogeneous poisson processes, we derive the exact joint arrival time probably density of the photons collected in a single counting experiment performed in the presence of background noise. The model obviates the need to bin experimental data for analysis, and makes it possible to analyze formally the effect of background noise on the photon detection experiment using both ML or Bayesian methods. For both methods we derive the joint and marginal probability densities of the fluorescent lifetime and fluorescent emission. the ML and Bayesian methods are compared in an analysis of simulated single molecule fluorescence experiments of Rhodamine 110 using different combinations of expected background nose and expected fluorescence emission. While both the ML or Bayesian procedures perform well for analyzing fluorescence emissions, the Bayesian methods provide more realistic measures of uncertainty in the fluorescent lifetimes. The Bayesian methods would be especially useful for measuring uncertainty in fluorescent lifetime estimates in current single molecule flow stream experiments where the expected fluorescence emission is low. Both the ML and Bayesian algorithms can be automated for applications in molecular biology.

Brown, Emery N.↗

On the Uncertainty in Single Molecule Fluorescent Lifetime and Energy Emission Measurements

Time-correlated single photon counting has recently been combined with mode-locked picosecond pulsed excitation to measure the fluorescent lifetimes and energy emissions of single molecules in a flow stream. Maximum likelihood (ML) and least squares methods agree and are optimal when the number of detected photons is large, however, in single molecule fluorescence experiments the number of detected photons can be less than 20, 67 percent of those can be noise, and the detection time is restricted to 10 nanoseconds. Under the assumption that the photon signal and background noise are two independent inhomogeneous Poisson processes, we derive the exact joint arrival time probability density of the photons collected in a single counting experiment performed in the presence of background noise. The model obviates the need to bin experimental data for analysis, and makes it possible to analyze formally the effect of background noise on the photon detection experiment using both ML or Bayesian methods. For both methods we derive the joint and marginal probability densities of the fluorescent lifetime and fluorescent emission. The ML and Bayesian methods are compared in an analysis of simulated single molecule fluorescence experiments of Rhodamine 110 using different combinations of expected background noise and expected fluorescence emission. While both the ML or Bayesian procedures perform well for analyzing fluorescence emissions, the Bayesian methods provide more realistic measures of uncertainty in the fluorescent lifetimes. The Bayesian methods would be especially useful for measuring uncertainty in fluorescent lifetime estimates in current single molecule flow stream experiments where the expected fluorescence emission is low. Both the ML and Bayesian algorithms can be automated for applications in molecular biology.

Brown, Emery N.↗

Quantifying Uncertainty in Projections of Stratospheric Ozone Over the 21st Century

Future stratospheric ozone concentrations will be determined both by changes in the concentration of ozone depleting substances (ODSs) and by changes in stratospheric and tropospheric climate, including those caused by changes in anthropogenic greenhouse gases (GHGs). Since future economic development pathways and resultant emissions of GHGs are uncertain, anthropogenic climate change could be a significant source of uncertainty for future projections of stratospheric ozone. In this pilot study, using an ensemble of opportunity of chemistry-climate model (CCM) simulations, the contribution of scenario uncertainty from different plausible emissions pathways for 10 ODSs and GHGs to future ozone projections is quantified relative to the contribution from model uncertainty and internal variability of the chemistry-climate system. For both the global, annual mean ozone concentration and for ozone in specific geographical regions, differences between CCMs are the dominant source of uncertainty for the first two-thirds of the 21 st century, up-to and after the time when ozone concentrations 15 return to 1980 values. In the last third of the 21st century, dependent upon the set of greenhouse gas scenarios used, scenario uncertainty can be the dominant contributor. This result suggests that investment in chemistry-climate modelling is likely to continue to refine projections of stratospheric ozone and estimates of the return of stratospheric ozone concentrations to pre-1980 levels.

Charlton-Perez, A. J.↗

Decoupled predictions of radiative heating in air using a particle simulation method

A particle simulation technique with decoupled radiation is used to estimate the radiative emission along the stagnation streamline and the radiative heating at the stagnation point of a blunt-nosed vehicle entering the earth's atmosphere at hypersonic speed. The direct simulation Monte Carlo (DSMC) method is used to compute the fluid mechanics of the weakly ionized flow. The radiative emission is computed using the NEQAIR computer code with the radiation decoupled from the flowfield solution. It is concluded that the new models make it possible to decrease the predicted total radiative heating at the stagnation point of the vehicle by a factor of 15. A comparison of the DSMC approach with a continuum flow model shows that the total predicted radiative heating estimates agree within a factor of 2.

Boyd, Iain D.↗

Development of a low NO/x/ lean premixed annular combustor

The results of an experimental atmospheric rig test program developed to define a low NO(x) annular combustor of 0.66 m diameter for high-altitude aircraft applications are presented. The test program strategy adopted evaluates the emission characteristics of a baseline configuration and subsequently examines the sensitivity of the emission signatures to variations in the key design features. The lean premixed combustor in axisymmetric annular form demonstrates the capability of operating at reduced-pressure, simulated high-altitude, supersonic cruise conditions with NO(x) emissions below 1.0 g NO2/kg fuel. The testing shows that for the full range of low emissions operation from idle to cruise, a variable dilution port system is necessary, but that fuel-switching can be avoided and a single fuel injection system used.

Roberts, P. B.↗

Sensitivity of Mesoscale Modeling of Smoke Direct Radiative Effect to the Emission Inventory: a Case Study in Northern Sub-Saharan African Region

An ensemble approach is used to examine the sensitivity of smoke loading and smoke direct radiative effect in the atmosphere to uncertainties in smoke emission estimates. Seven different fire emission inventories are applied independently to WRF-Chem model (v3.5) with the same model configuration (excluding dust and other emission sources) over the northern sub-Saharan African (NSSA) biomass-burning region. Results for November and February 2010 are analyzed, respectively representing the start and end of the biomass burning season in the study region. For February 2010, estimates of total smoke emission vary by a factor of 12, but only differences by factors of 7 or less are found in the simulated regional (15degW-42degE, 13degS-17degN) and monthly averages of column PM(sub 2.5) loading, surface PM(sub 2.5) concentration, aerosol optical depth (AOD), smoke radiative forcing at the top-of-atmosphere and at the surface, and air temperature at 2 m and at 700 hPa. The smaller differences in these simulated variables may reflect the atmospheric diffusion and deposition effects to dampen the large difference in smoke emissions that are highly concentrated in areas much smaller than the regional domain of the study. Indeed, at the local scale, large differences (up to a factor of 33) persist in simulated smoke-related variables and radiative effects including semi-direct effect. Similar results are also found for November 2010, despite differences in meteorology and fire activity. Hence, biomass burning emission uncertainties have a large influence on the reliability of model simulations of atmospheric aerosol loading, transport, and radiative impacts, and this influence is largest at local and hourly-to-daily scales. Accurate quantification of smoke effects on regional climate and air quality requires further reduction of emission uncertainties, particularly for regions of high fire concentrations such as NSSA.

Sahel and sub-Saharan African region↗

Global Transport of Aerosol and CO: Initial 3-D Simulations of MAPS, TOMS, and AVHRR

Carbon monoxide concentrations and aerosol properties provide the tracers of global tropospheric perturbation by humankind that are most easily observed from satellite platforms. Aircraft field observations are additionally needed for us to simulate and understand the patterns observed. We report on our accumulating experience in making detailed, situation-specific, 3-D simulations of these tropospheric constituents as observed from the MAPS CO sensor, the Advanced Very High Resolution Radiometer (AVHRR) aerosol scattering data, and the Total Ozone Mapping Spectrometer (TOMS) absorbing-aerosol information. We have found a strong complimentarity of satellite and aircraft data in this effort, and recommend modelers use: (1) satellite data to pose initial questions; (2) aircraft data for modelers' first detailed simulations; and (3) a return to satellite data for global generalization. This work provides one example. Our main tools are the MM5 numerical model for meteorological assimilation and GRACES, our NASA Ames tracer-chemistry model, which incorporates emissions estimates. We report on several six-week simulations of global biomass burning effects as observed in the MAPS October 1994 dataset, and show the usefulness of two aircraft datasets, the TRACE-A (1992) and PEM-Tropics missions of NASA's Global Tropospheric Experiment. Additional information is contained in the original extended abstract.

Chatfield, Robert B.↗

Chemical Source Inversion using Assimilated Constituent Observations in an Idealized Two-dimensional System

We present a source inversion technique for chemical constituents that uses assimilated constituent observations rather than directly using the observations. The method is tested with a simple model problem, which is a two-dimensional Fourier-Galerkin transport model combined with a Kalman filter for data assimilation. Inversion is carried out using a Green's function method and observations are simulated from a true state with added Gaussian noise. The forecast state uses the same spectral spectral model, but differs by an unbiased Gaussian model error, and emissions models with constant errors. The numerical experiments employ both simulated in situ and satellite observation networks. Source inversion was carried out by either direct use of synthetically generated observations with added noise, or by first assimilating the observations and using the analyses to extract observations. We have conducted 20 identical twin experiments for each set of source and observation configurations, and find that in the limiting cases of a very few localized observations, or an extremely large observation network there is little advantage to carrying out assimilation first. However, in intermediate observation densities, there decreases in source inversion error standard deviation using the Kalman filter algorithm followed by Green's function inversion by 50% to 95%.

Tangborn, Andrew↗

Three-D Simulation of the Origin of the Pollutant Ozone Maxima in the Great African Plume: New Meteorology, New Chemistry for TRACE-A

Burning in South Central Africa is primarily responsible for the vast buildup of ozone in the mid-Atlantic noticeable in the Belem, Brazil, ozonesondes, and also visible in analyses using the Total Ozone Mapping Spectrometer (TOMS). We report on full-scale chemistry simulations for the SAFARI/TRACE-A field period of September-October, 1992. These observational programs provided a wealth of comparison data, including spectacular depictions of the vertical structure of ozone and particulate pollution over Africa, South America, and the Equatorial Atlantic [Browell JGR, 1996, submitted] above and below the NASA DC-8 airplane path. These depictions provide strict tests on the ability of a 3-d simulation and its controlling input parameters, most notably the biomass burning emissions strength. We use meteorology from MM5 used as a synoptic assimilation model and our own GRACES Global Regional Air Chemistry Event Simulator. This report will focus on the unique meteorology of the Equatorial Atmosphere around the Gulf of Guinea during the TRACE-A period, which we describe as "the opening of the gate," "the Great African Plume," and the "African Recirculatory System." We expect to assess whether the ozone observed is primarily "transported African smog," the standard view, or whether "re-$NO_[x)$-ification" of the Central Atlantic troposphere (reduction of nitric acid to active nitrogen oxides in clouds or aerosol) may be required for "extended intercontinental ozone production." A status report on a second nitrogen problem, "lower-tropospheric missing NO(y)," in which we find a serious imbalance in the $NO_ {x }$ and $NO_{y}$ budgets when compared with similar atmospheric tracers, will be given. An elaboration of the concepts set off by quotation marks in this abstract will be given in the talk.

Chatfeild, Robert↗

Improved Simulations of Biomass Burning Aerosol Optical Properties and Lifetimes in the NASA GEOS Model during the ORACLES-I Campaign

In order to improve aerosol representation in the NASA Goddard Earth Observing System (GEOS) model, we evaluated simulations of the aerosol properties and transport over the southern African biomass burning source and outflow region using observations made during the first deployment of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) field campaign in September 2016. An example case study of September 24 was analyzed in detail, during which aircraft-based in-situ and remote sensing observations showed the presence of a multi-layered smoke plume structure with significant vertical variation in single scattering albedo (SSA). Our baseline GEOS simulations were not able to represent the observed SSA variation, nor the observed organic aerosol-to-black carbon ratio (OA : BC). Analyzing the simulated smoke age suggests that the higher altitude, less absorbing smoke plume was younger (~4 days), while the lower altitude and more absorbing smoke plume was older (~7 days). We hypothesize a chemical or microphysical loss process exists to explain the change in aerosol absorption as the smoke plume ages, and we apply a simple 6-day e-folding loss rate to the model hydrophilic biomass burning OA to mimic this process. Adding this loss process required some adjustment to the model assumed scaling factors of aerosol emissions to conserve the regional aerosol loading and further improve the simulated OA : BC ratio. Accordingly, we have increased our biomass burning emissions of OA by 60 % and biomass burning BC by 15 %. We also utilized the ORACLES airborne observations to better constrain the simulation of aerosol optical properties, adjusting the assumed particle size, hygroscopic growth, and absorption. Our final GEOS model simulation with additional OA loss and updated optics showed a better performance in simulating AOD and SSA compared to independent ground and space-based retrievals for the entire month of September 2016, including the OMI Aerosol Index. In terms of radiative implications of our model adjustments, the final GEOS simulation suggested a decreased atmospheric warming of about 10 % (~2 W m -2 ) over the south-east Atlantic region and above the stratocumulus cloud decks compared to the model baseline simulations. These results improve the representation of the smoke age, transport, and optical properties in Earth system models.

aerosols↗

Evaluation of the Impacts of Biomass Burning Aerosols on the NASA GEOS Sub-Seasonal Climate Forecasts

Emission sources of trace gases and aerosol particles in the South American (SA)and African (Af) continents have a strong seasonal and space variability associated with the extensive vegetation fires activities. In both continents, during the austral winter, the fires affect mainly tropical forest and savannah-type biomes and are mostly associated with deforestation and agricultural/pasture land management. Smoke aerosol particles, on average, contribute to at least 90% of the total aerosol optical depth (AOD) in the visible spectrum in the case of the South America regional smoke. Smoke aerosols also act as cloud condensation nuclei affecting cloud microphysics properties and therefore, changing the radiation budget, hydrological cycle and global circulation patterns over disturbed areas (Kaufman, 1995; Rosenfeld, 1999; Andreae,et al., 2004; Koren et al., 2004, Zhang, 2008; Ott et al., 2010; Randles et al., 2013). This study aims to evaluate and quantify the impact of including a comprehensive emission field of biomass burning aerosol on the performance of a seasonal climate forecast system, not only regarding the AOD itself but mainly on the meteorological state variable (e.g., precipitation and temperature). To address the questions put above, we designed two numerical experiments: 1- named"AERO_CTL" which applies the Quick Fire Emissions Dataset (QFED) emissions estimated with intra-diurnal variation (hereafter, BBE), and 2- named "AERO_CLM" where the sourcee mission is based on a climatology of the QFED emissions, with only monthly variation(hereafter, BBCLIM). Hindcast simulations were produced using the Goddard Earth ObservingSystem global circulation model, version 5, sub-seasonal to seasonal (GEOS5-S2S) system with a nominal spatial resolution of 56km (Rienecker et al., 2008). In both experiments, the aerosol feedbacks from cloud developments and radiation interactions were accounted. The two experiments consisted of 4 members each and ran from June to November spanning over the years 2000 to 2015. Model performance was evaluated by calculating statistical metrics on the mean area of SA and Af. Our results demonstrated that the skill model in predicting AOD is significantly improve when BBE source emission is applied over SA, but not over the Afcontinent. Over SA, the correlation between the AERO_CTL model configuration and MERRA-2 is 0.93 (R2= 0.86, RMS=0.02, BIAS=0.01), while the AERO_CLM model presents a value of0.81 (R2= 0.65, RMS=0.04, BIAS=0.06). However, the AERO_CTL experiment better represents the inter-annual variability of the AOS in both regions. The gain of the skill in predicting the AOD by the AERO_CTL experiment is also seen in some meteorological variables. We observed an increase in the model skill in predicting the 2-meter temperature and precipitation of up to 0.3 for the AERO_CTL experiment in comparison to the AERO_CLM. AERO_CLM. According to the analyzed hindcast, we inferred that representing the BBE more realistically implies in a significant gain of skills in the seasonal climate forecasting over SA and Af continents.

Aerosol↗

Coalescence of two current loops with a kink instability simulated by a three-dimensional electromagnetic particle code

We have studied the dynamics of a coalescence of current loops using three-dimensional electromagnetic (EM) particle simulation code. Our focus is the investigation of such kinetic processes as energy trasnfer, heating particles, and electromagnetic emissions associated with a current loop coalescence which cannot be studied by MHD simulations. First, the two loops undergo a pinching oscillation due to a pressure imbalance between the inside and outside of the current loop. During the pinching oscillation, a kinetic kink instability is excited and electrons in the loops are heated perpendicularly to an ambient magnetic field. Next, the two current loops collide and coalesce, while at the same time a helical structure grows further. Subsequently, the perturbed current, which is due to these helically bunched electrons, can drive a whistler instability. It should be noted in this case that the whistler wave is excited by the kinetic kink instability and not a beam instability. After the coalescence of two helical loops, tilting motions can be observed in the direction of left-hand rotation, and the helical structure will relax resulting in strong plasma heating mostly in the direction perpendicular to the ambient magnetic field. It is also shown that high-frequency electromagnetic waves can be emitted from the region where the two loops coalesce and propagate strongly in the direction of the electron drift velocity. These processes may be important in understanding heating mechansims for coronal loops as well as radio wave emission mechanisms from active regions of solar plasmas.

Nishikawa, K.-I.↗

Evaluation of Matthews-WLR-CH4: A New Wetland, Lake, and Reservoir Methane Emissions Data Set

Methane (CH4) is emitted from a variety of sources, both natural and anthropogenic, and is the second most important greenhouse gas contributing to climate change. Natural wetlands are the largest single contributor to annual global CH4 emissions and other inland water sources, such as lakes and reservoirs, produce CH4 but have received less attention. These emission sources are among the most uncertain components of the global CH4 cycle. These uncertainties stem from numerous issues, including the vast variability in these ecosystems and the sensitivity of CH4 emissions to interannual climate variations. Existing CH4 emission models display large differences in wetland spatial extent and include simplified, or lack all together, wetland-type classifications. Furthermore, CH4 emissions from lakes and reservoirs are typically combined with wetlands, or ignored, on a regional and global scale. Our NASA Interdisciplinary Research in Earth Science (IDS) study is focused on developing a suite of data sets on wetlands, lakes, and reservoirs (WLR) including global distributions of types, CH4-centric classifications, and daily CH4 emission rates (hereafter Matthews-WLR-CH4). This project is unique in that it comprises source-independent emission data for WLR, the first spatially-explicit data set of lake and reservoir CH4 emissions, and wetland emissions comprising numerous different wetland-type classifications.The focus of this study is to perform the initial evaluation of the wetland and lake CH4 emissions data from Matthews-WLR-CH4. This evaluation will focus on the domain of North America and include: 1) estimates of the contribution of wetland and lake sources to total CH4 emissions and atmospheric mixing ratios, 2) comparisons of wetland fraction and CH4 emissions to a suite of existing models (e.g., Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP), Global Carbon Project (GCP)), and 3) an accuracy assessment with in situ airborne and tower-based atmospheric CH4 observations when the Matthews-WLR-CH4 emissions are implemented in forward and inverse CarbonTracker-Lagrange (CT-L) CH4 model simulations. Here we will present the new Matthews-WLR-CH4 wetland and lake CH4 emissions data, the initial evaluation of these products, and the path forward for our project.

Reservoir↗

Land Surface Temperature Measurements form EOS MODIS Data

We have developed a physics-based land-surface temperature (LST) algorithm for simultaneously retrieving surface band-averaged emissivities and temperatures from day/night pairs of MODIS (Moderate Resolution Imaging Spectroradiometer) data in seven thermal infrared bands. The set of 14 nonlinear equations in the algorithm is solved with the statistical regression method and the least-squares fit method. This new LST algorithm was tested with simulated MODIS data for 80 sets of band-averaged emissivities calculated from published spectral data of terrestrial materials in wide ranges of atmospheric and surface temperature conditions. Comprehensive sensitivity and error analysis has been made to evaluate the performance of the new LST algorithm and its dependence on variations in surface emissivity and temperature, upon atmospheric conditions, as well as the noise-equivalent temperature difference (NE(Delta)T) and calibration accuracy specifications of the MODIS instrument. In cases with a systematic calibration error of 0.5%, the standard deviations of errors in retrieved surface daytime and nighttime temperatures fall between 0.4-0.5 K over a wide range of surface temperatures for mid-latitude summer conditions. The standard deviations of errors in retrieved emissivities in bands 31 and 32 (in the 10-12.5 micrometer IR spectral window region) are 0.009, and the maximum error in retrieved LST values falls between 2-3 K. Several issues related to the day/night LST algorithm (uncertainties in the day/night registration and in surface emissivity changes caused by dew occurrence, and the cloud cover) have been investigated. The LST algorithms have been validated with MODIS Airborne Simulator (MAS) dada and ground-based measurement data in two field campaigns conducted in Railroad Valley playa, NV in 1995 and 1996. The MODIS LST version 1 software has been delivered.

Wan, Zhengming↗

Global Dust Cycle and Direct Radiative Effect in E3SM Version 1: Impact of Increasing Model Resolution

Quantification of dust aerosols in Earth System Models (ESMs) has important implications for water cycle and biogeochemistry studies. This study examines the global life cycle and direct radiative effects (DREs) of dust in the U.S. Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1), and the impact of increasing model resolution both horizontally and vertically. The default 1° E3SMv1 captures the spatial and temporal variability in the observed dust aerosol optical depth (DAOD) reasonably well, but overpredicts dust absorption in the shortwave (SW). Simulations underestimate the dust vertical and long-range transport, compared with the satellite dust extinction profiles. After updating dust refractive indices and correcting for a bias in partitioning size-segregated emissions, both SW cooling and longwave (LW) warming of dust simulated by E3SMv1 are increased and agree better with other recent studies. The estimated net dust DRE of −0.42 Wm−2 represents a stronger cooling effect than the observationally based estimate −0.2 Wm−2 (−0.48 to +0.2), due to a smaller LW warming. Constrained by a global mean DAOD, model sensitivity studies of increasing horizontal and vertical resolution show strong influences on the simulated global dust burden and lifetime primarily through the change of dust dry deposition rate; there are also remarkable differences in simulated spatial distributions of DAOD, DRE, and deposition fluxes. Thus, constraining the global DAOD is insufficient for accurate representation of dust climate effects, especially in transitioning to higher- or variable-resolution ESMs. Better observational constraints of dust vertical profiles, dry deposition, size, and LW properties are needed.

dust aerosol↗