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At least 91 records · Page 5

Sunspot models with Alfven wave emission

Sunspot models have been computed on the assumption that the missing flux is transported by undissipated Alfven waves. In order to estimate the flux of these waves, we propose an extension of Opik's cellular model of convection to include the effects of a vertical magnetic field on horizontal gas flow. Horizontal motions, not vertical motions, are impeded more or less severely depending on the electrical conductivity, and this reduces the convective flux. These motions, however, shake the field lines; this is assumed to be a source of Alfven waves, compensating for the reduction in the convective flux. The free parameter D/H (ratio of cell diameter to cell depth) is adjusted such that the total sum of radiative, convective, and Alfven wave fluxes remains constant at all depths and equals the undisturbed solar flux entering the spot from below. Our treatment is speculative to some extent, but it leads to a unique spot model for a given field strength.

Mullan, D. J.↗

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↗

Assessment of Retrieved GMI Emissivity Over Land, Snow and Sea Ice in the GEOS System

Measurements from microwave sounders and imagers provide a valuable source of information including atmospheric temperature and water vapor in Numerical Weather Prediction (NWP) systems that assimilate these observations directly over water surfaces (oceans and other large water bodies). In a recent decadal survey, targeted observables in the Planetary Boundary Layer (PBL) were cited as a key need for future observations (NASEM, 2018). Microwave observations which sense in the PBL are currently available, however, utilizing surface-sensitive microwave observations for atmospheric data assimilation remains a challenge over land, snow and sea ice. This is in part due to the inability of surface emissivity models used by NWP data assimilation systems to simulate observations with sufficient accuracy. The GEOS-ADAS (Todling and el Akkraoui, 2018) which utilizes the Community Radiative Transfer Model (CRTM) (Han, 2006; Chen 2009) is no exception. The ECMWF system has retrieved instantaneous surface emissivity from surface-sensitive channels for SSMI/S and MHS radiance observations, and apply these estimates to the closest channels higher in frequency (Baordo and Geer 2016) in the calculation of simulated radiances. This approach currently is also being tested in the GEOS-ADAS for AMSU-A and ATMS radiances (Zhu et al. 2021). No or minimal emissivity spectral variability has been assumed in the above-mentioned studies. Recently, work by Munchak et al., 2020 (hereby referred to as M2020) provided a new database for emissivity over land, snow and sea ice retrieved from the NASA Global Precipitation Mission (GPM). Compared with Tool to Estimate Land Surface Emissivities at Microwave (TELSEM2; Wang et al., 2017), M2020 provides emissivities for more frequencies(i.e., 10.7 GHz V/H). Moreover, this database is unique in that it utilizes both active and passive data to retrieve surface emissivity and normalized radar cross section. While the emissivity values may be useful for other sensors, they are most applicable to the GPM Microwave Imager (GMI). In this work the GEOS-ADAS is modified to utilize emissivity values from Munchak et al, 2020 in place of values used by CRTM. Presently, only GMI radiances over ocean are used in the operational GEOS-ADAS. This study will focus on the GMI radiances over land, snow, and ice, as a first attempt to evaluate GMI radiances over these non-water surface types. Two cases are then presented, one with one week of observation minus background departures using the modified GEOS-ADAS, and one utilizing the original GEOS-ADAS. It should be noted that the surface emissivity models in CRTM are not state of the art and are scheduled to be replaced by the Community Surface Emissivity Module (CSEM; Chen and Weng, 2016). Simulations using default CRTM emissivity values are used merely as reference comparing against M2020, and is not a thorough comparison against other more state of the art modules such as CSEM.

GMI↗

Impact of Surface Roughness and Soil Texture on Mineral Dust Emission Fluxes Modeling

Dust production models (DPM) used to estimate vertical fluxes of mineral dust aerosols over arid regions need accurate data on soil and surface properties. The Laboratoire Inter-Universitaire des Systemes Atmospheriques (LISA) data set was developed for Northern Africa, the Middle East, and East Asia. This regional data set was built through dedicated field campaigns and include, among others, the aerodynamic roughness length, the smooth roughness length of the erodible fraction of the surface, and the dry (undisturbed) soil size distribution. Recently, satellite-derived roughness length and high-resolution soil texture data sets at the global scale have emerged and provide the opportunity for the use of advanced schemes in global models. This paper analyzes the behavior of the ERS satellite-derived global roughness length and the State Soil Geographic data base-Food and Agriculture Organization of the United Nations (STATSGO-FAO) soil texture data set (based on wet techniques) using an advanced DPM in comparison to the LISA data set over Northern Africa and the Middle East. We explore the sensitivity of the drag partition scheme (a critical component of the DPM) and of the dust vertical fluxes (intensity and spatial patterns) to the roughness length and soil texture data sets. We also compare the use of the drag partition scheme to a widely used preferential source approach in global models. Idealized experiments with prescribed wind speeds show that the ERS and STATSGO-FAO data sets provide realistic spatial patterns of dust emission and friction velocity thresholds in the region. Finally, we evaluate a dust transport model for the period of March to July 2011 with observed aerosol optical depths from Aerosol Robotic Network sites. Results show that ERS and STATSGO-FAO provide realistic simulations in the region.

textures↗

Microwave Signatures of Snow on Sea Ice: Modeling

Accurate knowledge of snow-depth distribution over sea ice is critical for polar climate studies. Current snow-depth-over-sea-ice retrieval algorithms do not sufficiently account for variations in snow and ice physical properties that can affect the accuracy of retrievals. For this reason, airborne microwave observations were coordinated with ground-based measurements of snow depth and snow properties in the vicinity of Barrow, AK, in March 2003. In this paper, the effects of snowpack properties and ice conditions on microwave signatures are examined using detailed surface-based measurements and airborne observations in conjunction with a thermal microwave-emission model. A comparison of the Microwave Emission Model of Layered Snowpacks (MEMLS) simulations with detailed snowpack and ice data from stakes along the Elson Lagoon and the Beaufort Sea and ra- 'diometer data taken from low-level flights using a Polarimetric Scanning Radiometer (PSR-A) shows that MEMLS can be used to simulate snow on sea ice and is a useful tool for understanding the limitations of the snow-depth algorithm. Analysis of radiance data taken over the Elson Lagoon and the Beaufort Sea using MEMLS suggests that the radiometric differences between the two locations are due to the differences in sea-ice emissivity. Furthermore, measured brightness temperatures suggest that the current snow-depth retrieval algorithm is sufficient for areas of smooth first-year sea ice, whereas new algorithm coefficients are needed for rough first-year sea ice. Snowpack grain size and density remain an unresolved issue for snow-depth retrievals using passive-microwave radiances.

Powell, D. C.↗

Trajectory modeling of emissions from lower stratospheric aircraft

A series of isentropic trajectory calculations has been performed for emissions by stratospheric aircraft moving across the northern midlatitude oceanic flight corridors. Emission of exhaust is simulated by the daily initialization of air parcels along a flight path on the 500 K isentropic surface. Parcels are tracked during the first three weeks of each January from 1980 to 1994 in order to determine the interannual variability in the spatial distribution of the exhaust and the likelihood of exposure to cold temperatures. Few parcels emitted along these flight paths at this time of year had experienced nitric acid trihydrate (NAT) formation temperatures, except for the particularly cold Januarys 1986, 1987, and 1992. Large zonal fluctuations in the distribution of the emissions are typical for this time year and are strongly dependent on flight path. An extended 6-month (January-June) run in which parcels were released daily along the New York-London route shows that emissions in the flight corridor increase at a time-averaged rate which is nearly twice the rate at which the zonal average increases. In addition, local fluctuations of pollutant density can be several times higher than the zonal average and can persist for several weeks. A rapid buildup of emissions occurred during the summer months. These elevated emission levels must be considered in the interpretation of environmental impact assessments based on two-dimensional transport models.

Sparling, Lynn C.↗

The ISM From the Soft X-ray Background Perspective

In the past few years progress in understanding the local and Galactic ISM in terms of the diffuse X-ray background has been as much about what hasn't been seen as it has been about detections. High resolution spectra of the local SXRB have been observed, but are inconsistent with current thermal emission models. An excess over the extrapolation of the high-energy (most clearly visible at E greater than 1.5 keV) extragalactic power law down to 3/4 keV has been observed but only at the level consistent with cosmological models, implying the absence of at least a bright hot Galactic halo. A very recent FUSE result indicates that O VI emission from the Local Hot Bubble is insignificant, if it exists at all, a result which is also inconsistent with current thermal emission models. A short review of the current status of our (well, at least my) understanding of the Galactic SXRB and ISM is presented here.

Snowden, S. L.↗

The profile algorithm for microwave delay estimation from water vapor radiometer data

A new algorithm has been developed for the estimation of tropospheric microwave path delays from water vapor radiometer (WVR) data, which does not require site and weather dependent empirical parameters to produce accuracy better than 0.3 cm of delay. Instead of taking the conventional linear approach, the new algorithm first uses the observables with an emission model to determine an approximate form of the vertical water vapor distribution, which is then explicitly integrated to estimate wet path delays in a second step. The intrinsic accuracy of this algorithm, excluding uncertainties caused by the radiometers and the emission model, has been examined for two channel WVR data using path delays and corresponding simulated observables computed from archived radiosonde data. It is found that annual rms errors for a wide range of sites average 0.18 cm in the absence of clouds, 0.22 cm in cloudy weather, and 0.19 cm overall. In clear weather, the new algorithm's accuracy is comparable to the best that can be obtained from conventional linear algorithms, while in cloudy weather it offers a 35 percent improvement.

Robinson, Steven E.↗

Models for infrared emission from IRAS galaxies

Models for the infrared emission from Infrared Astronomy Satellite (IRAS) galaxies by Rowan-Robinson and Crawford, by deJong and Brink, and by Helou, are reviewed. Rowan-Robinson and Crawford model the 12 to 100 micron radiation from IRAS galaxies in terms of 3 components: a normal disk component, due to interstellar cirrus; a starburst component, modeled as hot stars in an optically thick dust cloud; and a Seyfert component, modeled as a power-law continuum immersed in an n(r) variation r sup -1 dust cloud associated with the narrow-line region of the Seyfert nucleus. The correlations between the luminosities in the different components, the blue luminosity, and the X-ray luminosity of the galaxies are consistent with the model. Spectra from 0.1 to 1000 microns are predicted and compared with available observations. The de Jong and Brink, and Helou, model IRAS non-Seyfert galaxies in terms of a cool (cirrus) component and a warm (starburst) component. The de Jong and Brink estimate the face-on internal extinction in the galaxies and find that it is higher in galaxies with more luminous starbursts. In Helou's model the spectrum of the warm component varies strongly with the luminosity in that component. The three models are briefly compared.

Rowan-Robinson, M.↗

Summary of Quantitative Interpretation of Image Far Ultraviolet Auroral Data

Direct imaging of the magnetosphere by instruments on the IMAGE spacecraft is supplemented by simultaneous observations of the global aurora in three far ultraviolet (FUV) wavelength bands. The purpose of the multi-wavelength imaging is to study the global auroral particle and energy input from thc magnetosphere into the atmosphere. This paper describes provides the method for quantitative interpretation of FUV measurements. The Wide-Band Imaging Camera (WIC) provides broad band ultraviolet images of the aurora with maximum spatial and temporal resolution by imaging the nitrogen lines and bands between 140 and 180 nm wavelength. The Spectrographic Imager (SI), a dual wavelength monochromatic instrument, images both Doppler-shifted Lyman alpha emissions produced by precipitating protons, in the SI-12 channel and OI 135.6 nm emissions in the SI-13 channel. From the SI-12 Doppler shifted Lyman alpha images it is possible to obtain the precipitating proton flux provided assumptions are made regarding the mean energy of the protons. Knowledge of the proton (flux and energy) component allows the calculation of the contribution produced by protons in the WIC and SI-13 instruments. Comparison of the corrected WIC and SI-13 signals provides a measure of the electron mean energy, which can then be used to determine the electron energy fluxun-. To accomplish this reliable modeling emission modeling and instrument calibrations are required. In-flight calibration using early-type stars was used to validate the pre-flight laboratory calibrations and determine long-term trends in sensitivity. In general, very reasonable agreement is found between in-situ measurements and remote quantitative determinations.

Frey, H. U.↗

Historical (1700–2012) Global Multi-Model Estimates of the Fire Emissions from the Fire Modeling Intercomparison Project (FireMIP)

Fire emissions are critical for carbon and nutrient cycles, climate, and air quality. Dynamic Global Vegetation Models (DGVMs) with interactive fire modeling provide important estimates for long-term and large-scale changes of fire emissions. Here we present the first multi-model estimates of global gridded historical fire emissions for 1700-2012, including carbon and 33 species of trace gases and aerosols. The dataset is based on simulations of nine DGVMs with different state-of-the-art global fire models that participated in the Fire Modeling Intercomparison Project (FireMIP), using the same and standardized protocols and forcing data, and the most up-to-date fire emission factor table from field and laboratory studies over various land cover types. We evaluate the simulations of present-day fire emissions by comparing them with satellite-based products. Evaluation results show that most DGVMs simulate present-day global fire emission totals within the range of satellite-based products, and can capture the high emissions over the tropical savannas, low emissions over the arid and sparsely vegetated regions, and the main features of seasonality. However, most of the models fail to simulate the interannual variability, partly due to a lack of modeling peat fires and tropical deforestation fires. Historically, all models show only a weak trend in global fire emissions before ~1850s, consistent with multi-source merged historical reconstructions. The long-term trends among DGVMs are quite different for the 20th century, with some models showing an increase and others a decrease in fire emissions, mainly as a result of the discrepancy in their simulated responses to human population density change and land-use and land-cover change (LULCC). Our study provides a basic dataset for developing regional and global multi-source merged historical reconstructions and merging methods, and analyzing historical changes of fire emissions and their uncertainties as well as their role in the Earth system. It also highlights the importance of accurately modeling the responses of fire emissions to LULCC and population density change in reducing uncertainties in historical reconstructions of fire emissions and providing more reliable future projections.

Li, Fang↗

The diffuse galactic gamma ray emission

The EGRET (Energetic Gamma-Ray Experiment Telescope) detector will provide a much more detailed view of the diffuse galactic gamma ray intensity in terms of higher resolution, greater statistical significance, and broader energy range than earlier missions. These observations will furnish insight into a number of very important questions related to the dynamics and structure of the Galaxy. A diffuse emission model is being developed that incorporates the latest information on matter distribution and source functions. In addition, it is tailored to the EGRET instrument response functions. The analysis code of the model maintains flexibility to accommodate the quality of the data that is anticipated. The discussion here focuses on the issues of the distributions of matter, cosmic rays, and radiation fields, and on the important source functions that enter into the model calculation of diffuse emission.

Bertsch, David L.↗

Modeling aerosol emissions from the combustion of composite materials

The use of advanced composite materials (ACM) in the B-2 bomber, composite armored vehicle, and F-22 advanced tactical fighter has rekindled interest concerning the health risk of burned or burning ACM. The objective of this work was to determine smoke production from burning ACM and its toxicity. A commercial version of the UPITT II combustion toxicity method developed at the University of Pittsburgh, and subsequently refined through a US Army-funded basic research project, was used to established controlled combustion conditions which were selected to evaluate real-world exposure scenarios. Production and yield of toxic species varied with the combustion conditions. Previous work with this method showed that the combustion conditions directly influenced the toxicity of the decomposition products from a variety of materials.

Roop, J. A.↗

Assimilation of Multi-Frequency, Multi-Polarization Passive Microwave Brightness Temperature Observations in North America over Snow-Covered Regions Using Support Vector Machines

Accurately estimating the mass of water within a snowpack (a.k.a. snow water equivalent, or SWE) across regional or continental scales is a challenge. In order to overcome some of the limitations in traditional SWE retrieval algorithms or radiative transfer-based snow emission models, this study explores the use of a support vector machine (SVM) to merge an advanced land surface model within a radiance emission (i.e., brightness temperature) assimilation framework. The goal of direct radiance assimilation is preferable as it avoids inconsistencies in the use of ancillary data between the assimilation system and the independently-generated geophysical retrieval. The impact of assimilating multiple observations simultaneously at different frequency and polarization combinations is then evaluated via comparisons to state-of-the-art SWE and snow depth products as well as available ground-based measurements across North America for the years 2002 through 2011. It is found that assimilation-derived estimates (relative to estimates without assimilation) tend to better agree with state-of-the-art snow products. In addition, an overall improvement in goodness-of-fit statistics for snow estimates is achieved via assimilation when compared against ground-based snow measurements. In addition, these improvements in snow are shown to translate into improvements in streamflow predictions. Specifically, 11 out of the 13 major snow-dominated basins investigated have improved cumulative runoff estimates versus ground-based discharge measurements compared to the no-assimilation scenario. It is proven that a SVM can serve as an efficient and effective observation operator for a snow mass analysis within a radiance assimilation system.

Xue, Yuan↗