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NASA NTRS2021

Retrieving the global distribution of the threshold of wind erosion from satellite data and implementing it into the Geophysical Fluid Dynamics Laboratory land–atmosphere model (GFDL AM4.0/LM4.0)

Dust emission is initiated when surface wind velocities exceed the threshold of wind erosion. Many dust models used constant threshold values globally. Here we use satellite products to characterize the frequency of dust events and land surface properties. By matching this frequency derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue aerosol products with surface winds, we are able to retrieve a climatological monthly global distribution of the wind erosion threshold (V(threshold)) over dry and sparsely vegetated surfaces. This monthly two-dimensional threshold velocity is then implemented into the Geophysical Fluid Dynamics Laboratory coupled land–atmosphere model (AM4.0/LM4.0). It is found that the climatology of dust optical depth (DOD) and total aerosol optical depth, surface PM10 dust concentrations, and the seasonal cycle of DOD are better captured over the “dust belt” (i.e., northern Africa and the Middle East) by simulations with the new wind erosion threshold than those using the default globally constant threshold. The most significant improvement is the frequency distribution of dust events, which is generally ignored in model evaluation. By using monthly rather than annual mean V(threshold), all comparisons with observations are further improved. The monthly global threshold of wind erosion can be retrieved under different spatial resolutions to match the resolution of dust models and thus can help improve the simulations of dust climatology and seasonal cycles as well as dust forecasting.

Bing Pu↗
NASA NTRS2012

Precipitation Response to Regional Radiative Forcing

Precipitation shifts can have large impacts on human society and ecosystems. Many aspects of how inhomogeneous radiative forcings influence precipitation remain unclear, however. Here we investigate regional precipitation responses to various forcings imposed in different latitude bands in a climate model. We find that several regions show strong, significant responses to most forcings, but that the magnitude and even the sign depends upon the forcing location and type. Aerosol and ozone forcings typically induce larger responses than equivalent carbon dioxide (CO2) forcing, and the influence of remote forcings often outweighs that of local forcings. Consistent with this, ozone and especially aerosols contribute greatly to precipitation changes over the Sahel and South and East Asia in historical simulations, and inclusion of aerosols greatly increases the agreement with observed trends in these areas, which cannot be attributed to either greenhouse gases or natural forcings. Estimates of precipitation responses derived from multiplying our Regional Precipitation Potentials (RPP; the response per unit forcing relationships) by historical forcings typically capture the actual response in full transient climate simulations fairly well, suggesting that these relationships may provide useful metrics. The strong sensitivity to aerosol and ozone forcing suggests that although some air quality improvements may unmask greenhouse gas-induced warming, they have large benefits for reducing regional disruption of the hydrologic cycle.

Shindell, D. T.↗
NASA NTRS2015

Interannual Variability of Tropospheric Trace Gases and Aerosols: The Role of Biomass Burning Emissions

Fires are responsible for a range of gaseous and aerosol emissions. However, their influence on the interannual variability of atmospheric trace gases and aerosols has not been systematically investigated from a global perspective. We examine biomass burning emissions as a driver of interannual variability of large-scale abundances of short-lived constituents such as carbon monoxide (CO), hydroxyl radicals (OH), ozone and aerosols using the GISS ModelE composition-climate model and a range of observations, with an emphasis on satellite information. Our model captures the observed variability of the constituents examined in most cases, but with substantial underestimates in boreal regions. The strongest interannual variability on a global scale is found for carbon monoxide (10 for its global annual burden), while the lowest is found for tropospheric ozone (10 for its global annual burden). Regionally, aerosol optical depth shows variability that exceeds 50. Areas of strong variability include the tropical land regions and northern high latitudes, while even regions in the northern midlatitudes experience substantial inteannual variability of aerosols. Ozone variability peaks over Equatorial Asia in boreal autumn, partly due to varying biomass burning emissions, and over the western and central Pacific in the rest of the year, mainly due to meteorological fluctuations. We find that biomass burning emissions are almost entirely responsible for global CO interannual variability, and similarly important for OH variability. The same is true for global and regional aerosol variability, especially when not taking into account dust and sea-salt particles. We show that important implications48 can arise from such interannual influences for regional climate and air quality.

aerosols↗
NASA NTRS2005

Assimilation of MLS and OMI Ozone Data

Ozone data from Aura Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) were assimilated into the ozone model at NASA's Global Modeling and Assimilation Office (GMAO). This assimilation produces ozone fields that are superior to those from the operational GMAO assimilation of Solar Backscatter Ultraviolet (SBUV/2) instrument data. Assimilation of Aura data improves the representation of the "ozone hole" and the agreement with independent Stratospheric Aerosol and Gas Experiment (SAGE) III and ozone sonde data. Ozone in the lower stratosphere is captured better: mean state, vertical gradients, spatial and temporal variability are all improved. Inclusion of OMI and MLS data together, or separately, in the assimilation system provides a way of checking how consistent OMI and MLS data are with each other, and with the ozone model. We found that differences between OMI total ozone column data and model forecasts decrease after MLS data are assimilated. This indicates that MLS stratospheric ozone profiles are consistent with OMI total ozone columns. The evaluation of error characteristics of OMI and MLS ozone will continue as data from newer versions of retrievals becomes available. We report on the initial step in obtaining global assimilated ozone fields that combine measurements from different Aura instruments, the ozone model at the GMAO, and their respective error characteristics. We plan to use assimilated ozone fields in estimation of tropospheric ozone. We also plan to investigate impacts of assimilated ozone fields on numerical weather prediction through their use in radiative models and in the assimilation of infrared nadir radiance data from NASA's Advanced Infrared Sounder (AIRS).

Stajner, I.↗
NASA NTRS2019

Global and Regional Trends of Atmospheric Sulfur

The profound changes in global SO[subscript 2] emissions over the last decades have affected atmospheric composition on a regional and global scale with large impact on air quality, atmospheric deposition and the radiative forcing of sulfate aerosols. Reproduction of historical atmospheric pollution levels based on global aerosol models and emission changes is crucial to prove that such models are able to predict future scenarios. Here, we analyze consistency of trends in observations of sulfur components in air and precipitation from major regional networks and estimates from six different global aerosol models from 1990 until 2015. There are large interregional differences in the sulfur trends consistently captured by the models and observations, especially for North America and europe. europe had the largest reductions in sulfur emissions in the first part of the period while the highest reduction came later in North America and east Asia. the uncertainties in both the emissions and the representativity of the observations are larger in Asia. However, emissions from East Asia clearly increased from 2000 to 2005 followed by a decrease, while in India a steady increase over the whole period has been observed and modelled. the agreement between a bottom-up approach, which uses emissions and process-based chemical transport models, with independent observations gives an improved confidence in the understanding of the atmospheric sulfur budget.

Aas, Wenche↗
NASA NTRS2012

Effect of Spectrally Varying Albedo of Vegetation Surfaces on Shortwave Radiation Fluxes and Aerosol Direct Radiative Forcing

This study develops an algorithm for representing detailed spectral features of vegetation albedo based on Moderate Resolution Imaging Spectrometer (MODIS) observations at 7 discrete channels, referred to as the MODIS Enhanced Vegetation Albedo (MEVA) algorithm. The MEVA algorithm empirically fills spectral gaps around the vegetation red edge near 0.7 micrometers and vegetation water absorption features at 1.48 and 1.92 micrometers which cannot be adequately captured by the MODIS 7 channels. We then assess the effects of applying MEVA in comparison to four other traditional approaches to calculate solar fluxes and aerosol direct radiative forcing (DRF) at the top of atmosphere (TOA) based on the MODIS discrete reflectance bands. By comparing the DRF results obtained through the MEVA method with the results obtained through the other four traditional approaches, we show that filling the spectral gap of the MODIS measurements around 0.7 micrometers based on the general spectral behavior of healthy green vegetation leads to significant improvement in the instantaneous aerosol DRF at TOA (up to 3.02Wm(exp -2) difference or 48% fraction of the aerosol DRF, .6.28Wm(exp -2), calculated for high spectral resolution surface reflectance from 0.3 to 2.5 micrometers for deciduous vegetation surface). The corrections of the spectral gaps in the vegetation spectrum in the near infrared, again missed by the MODIS reflectances, also contributes to improving TOA DRF calculations but to a much lower extent (less than 0.27Wm(exp -2), or about 4% of the instantaneous DRF). Compared to traditional approaches, MEVA also improves the accuracy of the outgoing solar flux between 0.3 to 2.5 micrometers at TOA by over 60Wm(exp -2) (for aspen 3 surface) and aerosol DRF by over 10Wm(exp -2) (for dry grass). Specifically, for Amazon vegetation types, MEVA can improve the accuracy of daily averaged aerosol radiative forcing in the spectral range of 0.3 to 2.5 micrometers at equator at the equinox by 3.7Wm(exp -2). These improvements indicate that MEVA can contribute to regional climate studies over vegetated areas and can help to improve remote sensing-based studies of climate processes and climate change.

Zhu, L.↗
NASA NTRS1985

Accurate Airborne Particle Sampler

Air inducted isokinetically into centrifugal collector. Cloud drop collector accurately and efficiently samples droplets and rejects aerosol particles. Number of these collectors connected in series, each designed that largest size fraction of droplets captured in first one and successively smaller size fractions captured in others. By analyzing each size fraction, chemical composition of cloud droplets related to drop size.

Miller, I. M.↗
NASA NTRS2023

Reducing Aerosol Forcing Uncertainty by Combining Models With Satellite and Within-The-Atmosphere Observations: A Three-Way Street

Aerosol forcing uncertainty represents the largest climate forcing uncertainty overall. Its magnitude has remained virtually undiminished over the past 20 years despite considerable advances in understanding most of the key contributing elements. Recent work has produced modest increases only in the confidence of the uncertainty estimate itself. This review summarizes the contributions toward reducing the uncertainty in the aerosol forcing of climate made by satellite observations, measurements taken within the atmosphere, as well as modeling and data assimilation. We adopt a more measurement-oriented perspective than most reviews of the subject in assessing the strengths and limitations of each; gaps and possible ways to fill them are considered. Currently planned programs supporting advanced, global-scale satellite and surface-based aerosol, cloud, and precursor gas observations, climate modeling, and intensive field campaigns aimed at characterizing the underlying physical and chemical processes involved, are all essential. But in addition, new efforts are needed: (a) to obtain systematic aircraft in situ measurements capturing the multi-variate probability distribution functions of particle optical, microphysical, and chemical properties (and associated uncertainty estimates), as well as co-variability with meteorology, for the major aerosol airmass types; (b) to conceive, develop, and implement a suborbital (aircraft plus surface-based) program aimed at systematically quantifying the cloud-scale microphysics, cloud optical properties, and cloud-related vertical velocities associated with aerosol-cloud interactions; and (c) to focus much more research on integrating the unique contributions of satellite observations, suborbital measurements, and modeling, to reduce the persistent uncertainty in aerosol climate forcing.

aerosol climate forcing↗
NASA NTRS2015

Testing the Two-Layer Model for Correcting Clear Sky Reflectance near Clouds

A two-layer model (2LM) was developed in our earlier studies to estimate the clear sky reflectance enhancement due to cloud-molecular radiative interaction at MODIS at 0.47 micrometers. Recently, we extended the model to include cloud-surface and cloud-aerosol radiative interactions. We use the LES/SHDOM simulated 3D true radiation fields to test the 2LM for reflectance enhancement at 0.47 micrometers. We find: The simple model captures the viewing angle dependence of the reflectance enhancement near cloud, suggesting the physics of this model is correct; the cloud-molecular interaction alone accounts for 70 percent of the enhancement; the cloud-surface interaction accounts for 16 percent of the enhancement; the cloud-aerosol interaction accounts for an additional 13 percent of the enhancement. We conclude that the 2LM is simple to apply and unbiased.

MODIS↗
NASA NTRS2019

Evaluating Models' Response of Tropical Low Clouds to SST Forcings Using CALIPSO Observations

Recent studies have shown that, in response to a surface warming, the marine tropical low-cloud cover (LCC) as observed by passive-sensor satellites substantially decreases, therefore generating a smaller negative value of the top-of-the-atmosphere (TOA) cloud radiative effect (CRE). Here we study the LCC and CRE interannual changes in response to sea surface temperature (SST) forcings in the GISS model E2 climate model, a developmental version of the GISS model E3 climate model, and in 12 other climate models, as a function of their ability to represent the vertical structure of the cloud response to SST change against 10 years of CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) observations. The more realistic models (those that satisfy the observational constraint) capture the observed interannual LCC change quite well ([delta]LCC]/[delta]SST= -3.49±1.01%K [negative 1 superscript] vs. [delta]LCC/[delta]SST[subscript obs]= -3.59±0.28%K[negative 1 superscript]) while the others largely underestimate it ([delta]LCC/[delta]SST= -1.32±1.28%K[negative 1 superscript]). Consequently, the more realistic models simulate more positive shortwave (SW) feedback ([delta]CRE/[delta]SST=2.60±1.13Wm[negative 2 superscript] K[negative 1 superscript]) than the less realistic models (CRE/SST=0.87±2.63Wm2K1), in better agreement with the observations ([delta]CRE/[delta]SST[subscript obs]=3±0.26Wm[negative 2 superscript] K[negative 1 superscript] ), although slightly underestimated. The ability of the models to represent moist processes within the planetary boundary layer (PBL) and produce persistent stratocumulus (Sc) decks appears crucial to replicating the observed relationship between clouds, radiation and surface temperature. This relationship is different depending on the type of low clouds in the observations. Over stratocumulus regions, cloud-top height increases slightly with SST, accompanied by a large decrease in cloud fraction, whereas over trade cumulus (Cu) regions, cloud fraction decreases everywhere, to a smaller extent.

low clouds↗
NASA NTRS2020

Local to Global Air Quality Simulations using the NASA GEOS Composition Forecast Model, GEOS-CF

We give an overview of the NASA Global Earth Observing System Composition Forecast model (GEOS-CF), a high-resolution (roughly 25-km) global composition model developed by the NASA Global Modeling and Assimilation Office (GMAO). This system combines the GEOS weather and aerosol model with the GEOS-Chem chemistry module to provide a holistic view of atmospheric composition that captures a wide range of air pollutants such as ozone,nitrogen oxides, volatile organic compounds, and fine particulate matter.Given the global extent of the model, GEOS-CF captures large-scale processes such as long-range transport of air pollutants, across ocean basins and continents.

Knowland, Emma K.↗
NASA NTRS2024

The Thermal Structure and Composition of Jupiter's Great Red Spot From JWST/MIRI

Jupiter's Great Red Spot (GRS) was mapped by the James Webb Space Telescope (JWST)/Mid-Infrared Instrument (4.9–27.9 μm) in July and August 2022. These observations took place alongside a suite of visual and infrared observations from; Hubble, JWST/NIRCam, Very Large Telescope/VISIR and amateur observers which provided both spatial and temporal context across the jovian disc. The stratospheric temperature structure retrieved using the NEMESIS software revealed a series of hot-spots above the GRS. These could be the consequence of GRS-induced wave activity. In the troposphere, the temperature structure was used to derive the thermal wind structure of the GRS vortex. These winds were only consistent with the independently determined wind field by JWST/NIRCam at 240 mbar if the altitude of the Hubble-derived winds were located around 1,200 mbar, considerably deeper than previously assumed. No enhancement in ammonia was found within the GRS but a link between elevated aerosol and phosphine abundances was observed within this region. North-south asymmetries were observed in the retrieved temperature, ammonia, phosphine and aerosol structure, consistent with the GRS tilting in the north-south direction. Finally, a small storm was captured north-west of the GRS that displayed a considerable excess in retrieved phosphine abundance, suggestive of vigorous convection. Despite this, no ammonia ice was detected in this region. The novelty of JWST required us to develop custom-made software to resolve challenges in calibration of the data. This involved the derivation of the “FLT-5” wavelength calibration solution that has subsequently been integrated into the standard calibration pipeline.

Jake Harkett↗
NASA NTRSDate not supplied

Spaceborne Lidar Retrievals of PM2.5 for Air Quality Studies and Applications

Fine particulate matter (PM2.5) substantially contributes to air pollution and negatively affects human health. While many studies have investigated the use of passive column-integrated aerosol optical depth to infer surface PM2.5, the use of lidar observations for air quality characterization is not nearly as extensive. Lidar measurements are critical, however, due to the vertical aerosol information they provide, including near the surface. In this presentation, we first provide an overview of various lidar-based approaches for estimating PM2.5 concentrations and then discuss how lidar measurements can assist other air quality applications. For example, estimates of PM2.5 have been obtained in a physics-based approach through CALIOP near-surface aerosol extinction retrievals, assumptions on the mass extinction efficiency, and incorporating other parameters (an aerosol hygroscopic growth factor and PM2.5/PM10 ratio). Application of this algorithm over the contiguous United States (CONUS) from 2006 to 2018 yielded larger PM2.5 values over the eastern and western CONUS (~10-15 μg/m³) and lower PM2.5 levels in the central CONUS (~5 μg/m³). These spatial patterns were similar to those from gridded PM2.5 concentrations obtained through in situ measurements at ground stations operated by the US Environmental Protection Agency. In another approach, the Cloud Aerosol Transport System (CATS) lidar was used with the Goddard Earth Observing System (GEOS) model in a 1D ensemble-based variational technique to obtain PM2.5 over the US and Europe, and the spatial patterns of the CATS/GEOS based PM2.5 concentrations generally captured those from surface stations (with corresponding hourly EPA PM2.5 vs CATS PM2.5 statistics of R=0.4 and bias=1.5 μg/m³). In our recent work, as part of the Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group, we have applied both the CALIOP and CATS/GEOS based approaches over the highly polluted country of India during the post-monsoon season (September-October 2016). We derived elevated levels of two-month mean PM2.5 (~100 μg/m³) in northern India, especially near New Delhi. These high PM2.5 concentrations in the Indo-Gangetic plain are driven in large part from the seasonal burning of crop residue and meteorological conditions typical at this time of the year, such as low wind speeds and a shallow boundary layer. While the satellite-derived PM2.5 moderately replicates (R = ~0.7-0.9) the spatial variability in the two-month mean of surface in situ PM2.5 from monitoring sites operated by the Central and State Pollution Control Boards, we show results from specific scenes for which there are large deviations between the satellite-derived PM2.5 and in situ measurements. Other current work on this topic focuses on developing PM2.5 estimates using airborne high spectral resolution lidar measurements through machine learning regression algorithms and involves several parameters (e.g., aerosol extinction, color ratio, lidar ratio). Application of this method over major metropolitan areas in the US and Asia have resulted in high correlations (R = 0.93) with surface measurements. This airborne lidar approach can be adapted to spaceborne lidar measurements, and all three of these approaches can be applied to ESA’s EarthCARE Atmospheric Lidar instrument, setting the stage for the future Cloud Aerosol Lidar for Global Scale Observations of the Ocean-Land Atmosphere System (CALIGOLA) mission. Ultimately, beyond estimates of PM2.5, the aerosol vertical distribution from lidars can benefit studies involving passive sensor approaches for PM2.5 proxies (including from geostationary satellites), wildfire smoke plume injection heights, volcanic emissions (e.g., ash height retrievals), and aerosol/air quality model assimilation, evaluation, and forecasts.

Travis D Toth↗
NASA NTRS2016

Improving Our Fundamental Understanding of the Role of Aerosol Cloud Interactions in the Climate System

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

general circulation models↗
NASA NTRS2018

Analysis of the Planetary Boundary Layer Height During DISCOVER-AQ Baltimore–Washington, D.C., with Lidar and High-Resolution WRF Modeling

The daytime planetary boundary layer (PBL) was examined for the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Baltimore (Maryland)–Washington, D.C., campaign of July 2011 using PBL height (PBLH) retrievals from aerosol backscatter measurements from ground-based micropulse lidar (MPL), the NASA Langley Research Center airborne High Spectral Resolution Lidar-1 (HSRL-1), and the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. High-resolution Weather Research and Forecasting (WRF) Model simulations with horizontal grid spacing of 1 km and different combinations of PBL schemes, urban parameterization, and sea surface temperature inputs were evaluated against PBLHs derived from lidars, ozonesondes, and radiosondes. MPL and WRF PBLHs depicted a growing PBL in the morning that reached a peak height by midafternoon. WRF PBLHs calculated from gridded output profiles generally showed more rapid growth and higher peak heights than did the MPLs, and all WRF–lidar differences were dependent on model configuration, PBLH calculation method, and synoptic conditions. At inland locations, WRF simulated an earlier descent of the PBL top in the afternoon relative to the MPL retrievals and radiosonde PBLHs. At Edgewood, Maryland, the influence of the Chesapeake Bay breeze on the PBLH was captured by both the ozonesonde and WRF data but generally not by the MPL PBLH retrievals because of generally weaker gradients in the aerosol backscatter profile and limited normalized relative backscatter data near the top height of the marine layer.

Hegarty, Jennifer D.↗
NASA NTRS1986

Dynamics and composition of particles from an aeolian input event to the Sargasso Sea

The present paper is concerned with studies related to the capture of aeolian mineral particles in the Sargasso Sea region in late June 1980. Attention is given to measurement techniques, aerosol sampling, particle trap sampling, investigations utilizing scanning electron microscopy, and the obtained results. Conceivable sources for nonbiogenic particles measured in the water column are related to fallout from the Mount St. Helens eruption and soil materials transported by winds from the North American or African continents. It is found that present aerosol transport models are not adequaely addressing the transport of giant particles from the Sahara to the Sargasso Sea. Data regarding the variation of Sargasso Sea aerosol mass concentrations with time are presented in a table.

Carder, K. L.↗
NASA NTRS2020

High Resolution Global Coupled Chemistry-Meteorology Simulations Using the NASA GEOS Composition Forecast System, GEOS-CF

We will give an overview of the NASA Global Earth Observing System Composition Forecast system (GEOS-CF), a high-resolution (0.25 degree) global composition model developed by the NASA Global Modeling and Assimilation Office (GMAO). This system combines the GEOS weather and aerosol model with the GEOS-Chem chemistry module (version 12) to provide a holistic view of atmospheric composition that captures a wide range of air pollutants such as ozone, nitrogen oxides, volatile organic compounds, and fine particulate matter. The spatial resolution of 0.25 degrees (approx. 25 km) is fine enough to resolve local features such as nighttime ozone titration previously resolved only by urban or regional models. Furthermore, since there are no boundary conditions for a global model, the GEOS-CF captures large-scale processes such as long-range transport of air pollutants from forest fires. Comparisons against surface observations highlight the model’s overall capability to reproduce the diurnal variability of air pollutants under a variety of meteorological conditions. In addition, we show how machine learning techniques can be used to correct for sub-grid variability, which further improves model estimates at a given surface observation site. The GEOS-CF system offers a new tool for scientists and the public health community alike and is being developed jointly with several government and non-profit partners. As an example, we will show the use of GEOS-CF during the Satellite Coastal and Oceanic Atmospheric Pollution Experiment (SCOAPE). The campaign, conducted in collaboration between NASA and the Bureau of Ocean Energy Management (BOEM), aims to investigate the response of onshore air quality to Outer Continental Shelf (OCS) oil and gas exploration, development and production. Detailed gas-phase chemistry, as provided by GEOS-CF, is critical to understand the formation of air pollution related to hydrocarbon emissions from offshore oil and gas activities. The accuracy of GEOS-CF can be further improved by incorporating detailed offshore emissions compiled by BOEM.

Knowland, K. Emma↗
NASA NTRS2015

Total Dust Deposition Flux During Precipitation in Toyama, Japan, in the Spring of 2009: A Sensitivity Analysis with the NASA GEOS-5 Model

We compared the observed total dust deposition fluxes during precipitation (TDP) mainly at Toyama in Japan during the period January - April 2009 with results available from four NASA GEOS-5 global model experiments. The modeled results were obtained from three previous experiments and carried out in one experiment, which were all driven by assimilated meteorology and simulating aerosol distributions for the time period. We focus mainly on the observations of two distinct TDP events, which were reported in Osada et al. (2011), at Toyama, Japan, in February (Event B) and March 2009 (Event C). Although all of our GEOS-5 simulations captured aspects of the observed TDP, we found that our low horizontal spatial resolution control experiment performed generally the worst. The other three experiments were run at a higher spatial resolution, with the first differing only in that respect from the control, the second adding imposed a prescribed corrected precipitation product, and the final experiment adding as well assimilation of aerosol optical depth based on MODIS observations. During Event C, the increased horizontal resolution could increase TDP with precipitation increase. There was no significant improvement, however, due to the imposition of the corrected precipitation product. The simulation that incorporated aerosol data assimilation performed was by far the best for this event, but even so could only reproduce less than half of the observed TDP despite the significantly increased atmospheric dust mass concentrations. All three of the high spatial resolution experiments had higher simulated precipitation at Toyama than was observed and that in the lower resolution control run. During Event B, the aerosol data assimilation run did not perform appreciably better than the other higher resolution simulations, suggesting that upstream conditions (i.e., upstream cloudiness), or vertical or horizontal misplacement of the dust plume did not allow for significant improvement in the simulated aerosol distributions. Furthermore, a detailed comparison of observed hourly precipitation and surface particulate mass concentration data suggests that the observed TDP during Event B was highly dependent on short periods of weak precipitation correlated with elevated dust surface concentrations, important details possibly not captured well in a current global model.

Dust; Wet deposition; Numerical modeling; Japan; P↗