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NASA NTRSDate not supplied

Assimilation of Spaceborne Microwave and Radar Observations

Radiative transfer models are extensively used for the assimilation of satellite observations into NWP models as well as retrieving geophysical products from satellite measurements. The Community Radiative Transfer Model (CRTM) is a community model developed by NOAA JCSDA and widely used for different purposes requiring RT calculations. CRTM requires bulk optical properties of hydrometeors in the form of lookup tables in order to perform all-sky RT calculations. However, the current cloud scattering lookup tables in CRTM assume spherical shapes for all frozen hydrometeors, whereas actual clouds contain frozen particles with diverse shapes. The first part of this talk presents the implementation and validation of a comprehensive Discrete Dipole Approximation (DDA) cloud scattering database into CRTM, specifically targeting microwave frequencies. The DDA technique proves effective in simulating the optical properties of non-spherical hydrometeors in the microwave region. The original DDA database assumes total random orientation in calculating single scattering properties. To generate the required mass scattering parameters for CRTM, the single scattering properties and water content dependent particle size distributions are used. The evaluation of results involved a collocated dataset comprising short-term forecasts from the Integrated Forecast System of the European Center for Medium-Range Weather Forecasts and satellite microwave data. The findings demonstrate that the DDA lookup tables significantly reduce discrepancies between simulated and observed values when compared to the Mie tables. Passive instruments lack the ability to provide vertically resolved measurements of clouds and precipitation, which can be obtained by active radar instruments. However, incorporating these active measurements into data assimilation systems presents challenges due to the absence of fast forward radiative transfer models and difficulties in error modeling. The second part of the talk focuses on the development, evaluation, and sensitivity analysis of a forward radar model integrated into CRTM. The forward radar model utilizes scattering properties obtained from hydrometeor lookup tables generated using the discrete dipole approximation. By utilizing CRTM instrument-specific coefficients, the model can calculate both reflectivity and attenuated reflectivity for any given radar instrument and zenith angles. Evaluation using CloudSat measurements demonstrates a strong agreement between simulations and observations when the input profiles of hydrometeors align with the measured reflectivity profiles.

Isaac Moradi↗
DOE OSTI2018

Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) Winter Intensive Operational Period: Aerodynamic Particle Sizer Field Campaign Report

An aerodynamic particle sizer spectrometer (APS, model 3321 by TSI Inc., Shoreview, Minnesota) was deployed at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility Eastern North Atlantic (ENA) observatory during the second (winter) intensive operational period (IOP) of the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. Data were collected from January 9 through February 26, 2018, covering the second deployment of the ARM Aerial Facility (AAF) aircraft within ACE-ENA. The standard ENA instrument suite does not provide measurements of aerosol particle size distribution for diameters greater than one micron. Properties of coarse-mode (super-micron) aerosols are rarely measured, although super-micron particles can play an important role in the aerosol life cycle, affecting aerosol optical properties and cloud nuclei activity (e.g., Clarke et al. 2003). The APS was deployed to fill this gap in particle size measurements: it is capable of measuring size-resolved concentration of the aerosols in the 0.5-20 μm range (aerodynamic diameter). The APS was installed in the aerosol trailer to sample through the main stack. Special attention was given to selection of the instrument location (just below the main stack) to minimize particle losses in the connecting lines. Most atmospheric aerosols are hygroscopic, so the measurement of the aerosol size distributions should either be performed in a controlled humidity environment or accompanied by concurrent measurement of the temperature and humidity of the sample air. The latter strategy was used during this deployment: a high-precision humidity/temperature transmitter (model EE08 by E+E Elektonik GMBH, Engerwitzdorf, Germany) was mounted in the APS sampling line immediately upstream of the APS inlet. A dedicated laptop computer was used for data collection and communications. The APS was controlled with vendor-supplied software (Aerosol Instrument Manager, ver. 10.1, TSI); aerosol size distribution data were collected over a period of 55 seconds and converted to one-minute averages. Temperature and humidity analog signals were acquired via analog-to-digital converter (ADC) module (model WTAIN-M by Weeder Technologies, Fort Walton Beach, Florida) using vendor-supplied software (ModCom) with 1- sec resolution. In post-processing, the APS data were exported from TSI proprietary format into “comma-separated value” American Standard Code for Information Interchange (ASCII) files and matched with appropriately averaged temperature and humidity data. Two significant periods of missing data were caused by local power outages. Vendor-supplied software was not designed for unattended operation: it needs to be manually restarted including sensor configuration setup.

ACE-ENA, Azores, ultra-high-sensitivity aerosol sp↗
NASA NTRS2012

Taking the Pulse of PyroCumulus Clouds

Forest fires can burn large areas, but can also inject smoke into the upper troposphere/lower stratosphere (UT/LS), where stakes are even higher for climate, because emissions tend to have a longer lifetime, and can produce significant regional and even global climate effects, as is the case with some volcanoes. Large forest fires are now believed to be more common in summer, especially in the boreal regions, where pyrocumulus (pyroCu), and occasionally pyrocumuionimbus (pyroCb) clouds are formed, which can transport emissions into the UT/LS. A major difficulty in developing realistic fire plume models is the lack of observational data within fire plumes that resolves structure at a few 100 m scales, which can be used to validate these models. Here, we report detailed airborne radiation measurements within strong pyroCu taken over boreal forest fires in Saskatchewan, Canada during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) summer field campaign in 2008. We find that the angular distribution of radiance within the pyroCu is closely related to the diffusion domain in water clouds and can be described by very similar simple cosine functions. We demonstrate with Monte Carlo simulations that radiation transport in pyroCu is inherently a 3D phenomenon and must account for particle absorption. However, the simple cosine function promises to offer an easy solution for climate models. The presence of a prominent smoke core, defined by strong extinction in the UV, VIS and NIR, suggests that the core might be an important pathway for emission transport to the upper troposphere and lower stratosphere. We speculate that this plume injection core is generated and sustained by complex processes not yet well understood, but not necessarily related directly to the intense fires that originally initiated the plume rise.

Gatebe, C. K.↗
NASA NTRS2000

Influence of the Biosphere on Precipitation: July 1995 Studies with the ARM-CART Data

Ensemble sets of simulation experiments were conducted with a single column model (SCM) using the Goddard GEOS II GCM physics containing a recent version of the Cumulus Scheme (McRAS) and a biosphere based land-fluxes scheme (SSiB). The study used the 18 July to 5 August 1995 ARM-CART (Atmospheric Radiation Measurement-Cloud Atmospheric Radiation Test-bed) data, which was collected at the ARM-CART site in the mid-western United States and analyzed for single column modeling (SCM) studies. The new findings affirm the earlier findings that the vegetation, which increases the solar energy absorption at the surface together with soil and soil-moisture dependent processes, which modulate the surface, fluxes (particularly evapotranspiration) together help to increase the local rainfall. In addition, the results also show that for the particular study period roughly 50% of the increased evaporation over the ARM-CART site would be converted into rainfall with the Column, while the remainder would be advected out to the large-scale. Notwithstanding the limitations of only one-way interaction (i.e., the large-scale influencing the regional physics and not vice versa), the current SCM simulations show a very robust relationship. The evaporation-precipitation relationship turns out to be independent of the soil types, and soil moisture; however, it is weakly dependent on the vegetation cover because of its surface-albedo effect. Clearly, these inferences are prone to weaknesses of the SCM physics, the assumptions of the large-scale being unaffected by gridscale (SCM-scale) changes in moist processes, and other limitations of the evaluation procedures.

Sud, Y. C.↗
NASA NTRS1994

CS multitransitional study of density distribution in star-forming regions. 2: The S140 region

The S140 molecular cloud was observed in five transitions of CS with resolutions of 11 to 45 arcsec. The data were analyzed with both the LVG and microturbulent models of radiative transfer to derive the density structure. It was found that the CS emission comes from three components of gas: a spherical component centered on the infrared cluster, an arc component along the ionization front between the S140 H II region and the dense molecular cloud core, and a high-velocity component from the dense part of a molecular outflow. The spherical component contributes most to the CS emission and was analyzed in more detail than the other components. Using a temperature distribution derived from an analysis of the dust emission from S140, we fit a power-law density distribution of n(r) = n(sub i)(r/r(sub i))(exp -alpha) to the spherical component. The best fit was for n(sub i) = 1.4 x 10(exp 6) (density at r(sub i) = 0.026 pc) and alpha = 0.8. The density (n(sub i)) was found to be greater than or equal to the density required to account for the dust emission, depending on the dust opacity laws adopted. The presence of optical emission (Dinerstein, Lester, & Rank 1979) suggests a clumpy structure for the dense gas. Considerations of the virial mass and the lowest amount of column density required to produce dust emission put the volume filling factor (f(sub nu)) of the dense gas at approximately 0.14-0.5. We compared S140 with other regions of star formation where the density structure has been derived from excitation analysis. Source-source variations in density gradients and clumpiness clearly exist, ranging from alpha = 2 and f(sub nu) approximately 1 in B335 to alpha approximately 0, f(sub nu) approximately 0.1 in M17. There is a tendency for more massive star-forming regions to have a flatter density distribution, a more clumpy structure, and a large number of young stars. The implications of this tendency are discussed.

Zhou, Shudong↗
NASA NTRS2000

A New Neural Network Approach Including First-Guess for Retrieval of Atmospheric Water Vapor, Cloud Liquid Water Path, Surface Temperature and Emissivities Over Land From Satellite Microwave Observations

The analysis of microwave observations over land to determine atmospheric and surface parameters is still limited due to the complexity of the inverse problem. Neural network techniques have already proved successful as the basis of efficient retrieval methods for non-linear cases, however, first-guess estimates, which are used in variational methods to avoid problems of solution non-uniqueness or other forms of solution irregularity, have up to now not been used with neural network methods. In this study, a neural network approach is developed that uses a first-guess. Conceptual bridges are established between the neural network and variational methods. The new neural method retrieves the surface skin temperature, the integrated water vapor content, the cloud liquid water path and the microwave surface emissivities between 19 and 85 GHz over land from SSM/I observations. The retrieval, in parallel, of all these quantities improves the results for consistency reasons. A data base to train the neural network is calculated with a radiative transfer model and a a global collection of coincident surface and atmospheric parameters extracted from the National Center for Environmental Prediction reanalysis, from the International Satellite Cloud Climatology Project data and from microwave emissivity atlases previously calculated. The results of the neural network inversion are very encouraging. The r.m.s. error of the surface temperature retrieval over the globe is 1.3 K in clear sky conditions and 1.6 K in cloudy scenes. Water vapor is retrieved with a r.m.s. error of 3.8 kg/sq m in clear conditions and 4.9 kg/sq m in cloudy situations. The r.m.s. error in cloud liquid water path is 0.08 kg/sq m . The surface emissivities are retrieved with an accuracy of better than 0.008 in clear conditions and 0.010 in cloudy conditions. Microwave land surface temperature retrieval presents a very attractive complement to the infrared estimates in cloudy areas: time record of land surface temperature will be produced.

Aires, F.↗
NASA NTRS1999

A Superposition Technique for Deriving Photon Scattering Statistics in Plane-Parallel Cloudy Atmospheres

Photon transport in a multiple scattering medium is critically dependent on scattering statistics, in particular the average number of scatterings. A superposition technique is derived to accurately determine the average number of scatterings encountered by reflected and transmitted photons within arbitrary layers in plane-parallel, vertically inhomogeneous clouds. As expected, the resulting scattering number profiles are highly dependent on cloud particle absorption and solar/viewing geometry. The technique uses efficient adding and doubling radiative transfer procedures, avoiding traditional time-intensive Monte Carlo methods. Derived superposition formulae are applied to a variety of geometries and cloud models, and selected results are compared with Monte Carlo calculations. Cloud remote sensing techniques that use solar reflectance or transmittance measurements generally assume a homogeneous plane-parallel cloud structure. The scales over which this assumption is relevant, in both the vertical and horizontal, can be obtained from the superposition calculations. Though the emphasis is on photon transport in clouds, the derived technique is applicable to any scattering plane-parallel radiative transfer problem, including arbitrary combinations of cloud, aerosol, and gas layers in the atmosphere.

Platnick, S.↗
NASA NTRS1972

A plausible energy source and structure for quasi-stellar objects.

If a collision of two large, massive, fast gas clouds occurs, their kinetic energy is converted to radiation in a pair of shock fronts at their interface. Basic constraints imposed on such a model by observations of QSOs are considered. It is shown that a very large shock area is required if such a collision process is to provide the energy for a QSO. Details regarding the anticipated spectrum are discussed together with the opacity of the neutral clouds.

Daltabuit, E.↗
NASA NTRS2021

Solving Global Cirrus Cloud Top-of-the-Atmosphere Radiative Forcing from Satellite Lidar

We estimate top-of-the-atmosphere (TOA) cirrus cloud radiative forcing from satellite lidar observations. We describe the technical innovations necessary to conduct this experiment. Specifically, we highlight advances in broadband radiative transfer modeling, and the optical and physical parameterizations necessary to run them. We present two years of results, across two decades (2008 vs. 2018), highlighting seasonal and annual differences. The goal of this endeavor is to standardize mechanics for transitioning this work to operational Level 2 ground and satellite lidar products moving forward. However, the unique TOA forcing characteristics of cirrus clouds are also discussed, including specifically daytime characteristics than can oscillate between warming and cooling regionally.

James R Campbell↗
DOE OSTI2025

Simulating Pyrocumulonimbus Clouds Using a Multiscale Wildfire Simulation Framework

Pyrocumulonimbus (pyroCb) clouds, driven by extreme fires under favorable meteorological conditions, can inject smoke into the stratosphere at magnitudes comparable to those of moderate volcanic eruptions, potentially altering the global radiative balance and atmospheric composition. However, simulating pyroCb is particularly challenging in Earth system models. Using the Energy Exascale Earth System Model (E3SM), we developed a novel global multiscale framework to model pyroCb events in California, which includes a high‐resolution fire radiative power time series, a one‐dimensional plume‐rise parameterization, a fire‐induced vertical water vapor transport scheme, and a surface wildfire sensible heat flux representation. Our simulation successfully reproduces many pyroCb features, including cloud height, spatiotemporal evolution, and convective intensity in comparison with satellite and ground‐based observations. Sensitivity experiments show that realistic pyroCb simulation depends on vertical water vapor transport. These advances provide a basis for future exploration of pyroCb impacts at regional and global scales within climate models.

E3SM↗
DOE OSTI2020

Seasonal Dependent Impact of Ice Cloud Longwave Scattering on the Polar Climate

Most climate models neglect cloud longwave (LW) scattering because scattering is considered negligible compared to strong LW absorption by clouds and greenhouse gases. While this rationale is valid for simulating extrapolar regions, it is questionable for the polar regions, where the atmosphere is dry and hence has weak absorption, and ice clouds that have strong scattering capability frequently occur. Using the slab-ocean Community Earth System Model, we show that ice cloud LW scattering can warm winter surface air temperature by 0.8–1.8 K in the Arctic and 1.3–1.9 K in the Antarctic, while this warming becomes much weaker in polar summer. Such scattering effect cannot be correctly assessed when sea surface temperature and sea ice are prescribed as this effect is manifested through a surface-atmosphere coupling. Furthermore, cloud LW scattering is a necessity for the correct simulation of polar climate and surface radiation budget, especially in the winter.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1997

Regional Application of an Ecosystem Production Model for Studies of Biogeochemistry in the...

The degree to which primary production, soil carbon, and trace gas fluxes in tropical forests of the Amazon are limited by moisture availability and other environmental factors was examined using an ecosystem modeling application for the country of Brazil. A regional geographic information system (GIS) serves as the data source of climate drivers, satellite images, land cover, and soil properties for input to the NASA Ames-CASA (Carnegie-Ames-Stanford Approach) model over a 8-km grid resolution. Simulation results supports the hypothesis that net primary production (NPP) is limited by cloud interception of solar radiation over the humid northwestern portion of the region. Peak annual rates for NPP of nearly 1.4 kg C m-2yr -1are localized in the seasonally dry eastern Amazon in areas that we assume are primarily deep-rooted evergreen forest cover. Regional effects of forest conversion on NPP and soil carbon content are indicated in the model results, especially in seasonally dry areas. Comparison of model flux predictions along selected eco-climatic transects reveal moisture, soil, and land use controls on gradients of ecosystem production and soil trace gas emissions (CO2, N2O, and NO). These results are used to formulate a series of research hypotheses for testing in the next phase of regional modeling, which includes recalibration of the light-use efficiency term in CASA using field measurements of NPP, and refinements of vegetation index and soil property (texture and potential rooting depth) maps for the region.

Potter, C. S.↗
DOE OSTI2021

Developing and Testing a Novel Stochastic Ice Microphysics Parameterization for Cloud and Climate Models Using ARM Field Campaign Data (Final Progress Report)

The major goals of this project were: 1) to use field campaign measurements from DOE’s Atmospheric Radiation Measurement (ARM) program to characterize variability of important parameters describing properties of ice particles in the atmosphere; 2) based on this observational analysis, to develop a parameterization scheme for weather and climate models that stochastically varies these parameters, and implement the new scheme into a weather model called the Weather Research and Forecasting model (WRF); 3) to use WRF coupled with the new stochastic scheme to simulate ARM field campaign thunderstorm cases and analyze how accounting for this parameter variability affects the model simulations. This work was performed jointly between the National Center for Atmospheric Research, University of Oklahoma, and University of Utah. To accomplish these goals, we extended an approach previously developed to characterize the variability in the size distribution of ice particles to parameters that are explicitly represented in models (i.e., relationships between ice particle mass and size, and between particle fall velocity and size). Our project was, to our knowledge, the first to apply observationally-constrained estimates of this parameter variability describing mass-size and fall velocity-size in a modeling framework. Our results showed efficacy of the approach, evaluated using ARM observations. Similarly, to our knowledge, work in this project was the first to propose and evaluate in detail a stochastic approach for unresolved turbulent mixing in high-resolution model simulations against detailed, benchmark large eddy simulations and ARM observations. Results showed some promising behavior, particularly with increased mixing and dilution of air in thunderstorm cores with surrounding environmental air, bringing the stochastic simulations closer to the benchmark large eddy simulations; however, results were somewhat degraded using stochastic mixing compared to observations from the AMIE/DYNAMO field campaign. This project also further refined and applied a modeling methodology called “piggybacking” that can robustly separate dynamical and thermodynamic impacts of model changes, and comparison studies of different models based on cases developed from ARM observations. Finally, this project directly supported three graduate students who completed their PhDs as well as a postdoctoral research fellow.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Radiative Transfer and Satellite Remote Sensing of Cirrus Clouds Using FIRE-2-IFO Data

Under the support of the NASA grant, we have developed a new geometric-optics model (GOM2) for the calculation of the single-scattering and polarization properties for arbitrarily oriented hexagonal ice crystals. From comparisons with the results computed by the finite difference time domain (FDTD) method, we show that the novel geometric-optics can be applied to the computation of the extinction cross section and single-scattering albedo for ice crystals with size parameters along the minimum dimension as small as approximately 6. We demonstrate that the present model converges to the conventional ray tracing method for large size parameters and produces single-scattering results close to those computed by the FDTD method for size parameters along the minimum dimension smaller than approximately 20. We demonstrate that neither the conventional geometric optics method nor the Lorenz-Mie theory can be used to approximate the scattering, absorption, and polarization features for hexagonal ice crystals with size parameters from approximately 5 to 20. On the satellite remote sensing algorithm development and validation, we have developed a numerical scheme to identify multilayer cirrus cloud systems using AVHRR data. We have applied this scheme to the satellite data collected over the FIRE-2-IFO area during nine overpasses within seven observation dates. Determination of the threshold values used in the detection scheme are based on statistical analyses of these satellite data.

Source record↗
NASA NTRS2024

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↗
DOE OSTI2017

Recent advances in understanding secondary organic aerosol: Implications for global climate forcing: Advances in Secondary Organic Aerosol

Anthropogenic emissions and land use changes have modified atmospheric aerosol concentrations and size distributions over time. Understanding preindustrial conditions and changes in organic aerosol due to anthropogenic activities is important because these features (1) influence estimates of aerosol radiative forcing and (2) can confound estimates of the historical response of climate to increases in greenhouse gases. Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, represents a major fraction of global submicron-sized atmospheric organic aerosol. Over the past decade, significant advances in understanding SOA properties and formation mechanisms have occurred through measurements, yet current climate models typically do not comprehensively include all important processes. Our review summarizes some of the important developments during the past decade in understanding SOA formation. We also highlight the importance of some processes that influence the growth of SOA particles to sizes relevant for clouds and radiative forcing, including formation of extremely low volatility organics in the gas phase, acid-catalyzed multiphase chemistry of isoprene epoxydiols, particle-phase oligomerization, and physical properties such as volatility and viscosity. Several SOA processes highlighted in this review are complex and interdependent and have nonlinear effects on the properties, formation, and evolution of SOA. Current global models neglect this complexity and nonlinearity and thus are less likely to accurately predict the climate forcing of SOA and project future climate sensitivity to greenhouse gases. Efforts are also needed to rank the most influential processes and nonlinear process-related interactions, so that these processes can be accurately represented in atmospheric chemistry-climate models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2008

Application of the CloudSat and NEXRAD Radars Toward Improvements in High Resolution Operational Forecasts

As computational power increases, operational forecast models are performing simulations with higher spatial resolution allowing for the transition from sub-grid scale cloud parameterizations to an explicit forecast of cloud characteristics and precipitation through the use of single- or multi-moment bulk water microphysics schemes. investments in space-borne and terrestrial remote sensing have developed the NASA CloudSat Cloud Profiling Radar and the NOAA National Weather Service NEXRAD system, each providing observations related to the bulk properties of clouds and precipitation through measurements of reflectivity. CloudSat and NEXRAD system radars observed light to moderate snowfall in association with a cold-season, midlatitude cyclone traversing the Central United States in February 2007. These systems are responsible for widespread cloud cover and various types of precipitation, are of economic consequence, and pose a challenge to operational forecasters. This event is simulated with the Weather Research and Forecast (WRF) Model, utilizing the NASA Goddard Cumulus Ensemble microphysics scheme. Comparisons are made between WRF-simulated and observed reflectivity available from the CloudSat and NEXRAD systems. The application of CloudSat reflectivity is made possible through the QuickBeam radiative transfer model, with cautious application applied in light of single scattering characteristics and spherical target assumptions. Significant differences are noted within modeled and observed cloud profiles, based upon simulated reflectivity, and modifications to the single-moment scheme are tested through a supplemental WRF forecast that incorporates a temperature dependent snow crystal size distribution.

Molthan, A. L.↗
DOE OSTI2020

Assessing Global and Local Radiative Feedbacks Based on AGCM Simulations for 1980–2014/2017

In order to avoid contamination of unobservable and uncertain effective radiative forcing (ERF) on the diagnosis of radiative feedbacks based on short-term climate variability, we verify the Kernel-Gregory feedback calculation method using atmospheric model experiments with prescribed ERF. We show that both clear-sky radiative fluxes and all-sky radiative feedbacks have a closure between model simulations and kernel derivations. A near-zero global mean net cloud feedback is found in the simulation with prescribed ERF, which results in a more negative global net climate feedback, -2 W m -2 K -1 . Consistent with AMIP6 ensemble mean results, the lapse rate feedback is the largest contributor among all feedbacks to temperature amplification over the three poles (Arctic, Antarctic and Tibetan Plateau), followed by surface albedo feedback and Planck feedback deviation from its global mean. Except for the higher surface albedo feedback in the Antarctic, other feedbacks are almost same between the Arctic and Antarctic.

54 ENVIRONMENTAL SCIENCES↗