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At least 1,081 records · Page 60

Building Reliable Forecasts of Solar Activity

Solar ionizing radiation critically depends on the level of the Sun’s magnetic activity. For robust physics-based forecasts, we employ the procedure of data assimilation, which combines theoretical modeling and observational data such that uncertainties in both the model and the observations are taken into account. Currently we are working in two major directions: 1) development of a new long-term forecast procedure on time-scales of the 11-year solar cycle, using a 2-dimensional mean-field dynamo model and synoptic magnetograms; 2) development of 3-dimensional radiative MHD (Magnetohydrodynamic) simulations to investigate the origin and precursors of local manifestations of magnetic activity, such as the formation of magnetic structures and eruptive dynamics.

Kitiashvili, Irina↗

Characterizing uncertainties in ground “truth” of precipitation over complex terrain through high-resolution numerical modeling

Ground observation of precipitation over complex terrain is subject to large uncertainties due to inadequate sampling. This study explores a method that combines limited gauge data and a high-resolution numerical simulation to quantify the precipitation uncertainties in central Himalaya. Specifically, the Coefficient of spatial Variability (CV) of precipitation and the minimum Number of Required Stations (NRS) to obtain areal-mean precipitation ground truth values within a 0.25-degree area are investigated using fine-scale meteorological simulation at 1.5 km grid spacing. Evaluation over a densely-gauged area demonstrates comparable CV and NRS values between station observations and simulations. The simulated CV and NRS values in a larger area show a strong and positive dependence on each other and an expected positive (negative) correlation with topographic complexity (temporal scale). The proposed method sheds lights on evaluating precipitation products and holds promise for informing the layout of rain gauge networks in complex terrain.

Ouyang, Lin↗

Venus cloud models

Remote observations of Venus are reviewed. The strongest inferences of cloud properties can be drawn from polarization data which provide information about cloud particles near 68 km. Particle properties are not as well determined at higher and lower levels. If the clouds are generated photochemically from reduced sulfur species, the supply of O2 may be an important constraint on cloud production. Vapor-pressure data reviewed, and it is shown that deep clouds cannot be H2SO4-H2O aerosols unless the mixing ratios of both H2SO4 and H2O approach 0.001 below 50 km.

Wofsy, S. C.↗

QH observations

A model of the dissociative lifetime of the hydroxyl radical is computed where the H2O and OH velocities are vectorially added. A lifetime of approximately 3 x 100,000 seconds is determined.

Festou, M.↗

Plasma pressure in the environment of Jupiter, inferred from Voyager 1 magnetometer observations

A model combining the internal magnetic field with a self-consistent model of the Jovian magnetodisc was fitted to the Voyager 1 Jovian magnetic field data by means of a generalized inverse technique. The model parameters included the internal field spherical harmonic coefficients as well as with parameters describing the plasma distribution in the magnetosphere. Assuming that the pressure in the middle and outer magnetosphere is related to the unit flux tube volume V through PV exp gamma = const, the model fit yielded a value of 0.88 for gamma. If the hot (30 keV) plasma is transported adiabatically inward under the interchange instability triggered by centrifugal force of the heavy torus ions, losses are not sufficient to account for such a low value of gamma beyond L = 10. Closer to the planet, as the outer edge of the Io plasma torus is approached, PV exp gamma is found to decrease inward, as expected from the particle measurements, which identified an inner boundary of the particle fluxes in that region. With the present stage of the development of magnetodisc models, secular variations of the internal field still remain difficult to estimate.

Caudal, G.↗

A Study of Mesoscale Gravity Waves over the North Atlantic with Satellite Observations and a Mesoscale Model

Satellite microwave data are used to study gravity wave properties and variabilities over the northeastern United States and the North Atlantic in the December-January periods. The gravity waves in this region, found in many winters, can reach the stratopause with growing amplitude. The Advanced Microwave Sounding Unit-A (AMSU-A) observations show that the wave occurrences are correlated well with the intensity and location of the tropospheric baroclinic jet front systems. To further investigate the cause(s) and properties of the North Atlantic gravity waves, we focus on a series of wave events during 19-21 January 2003 and compare AMSU-A observations to simulations from a mesoscale model (MM5). The simulated gravity waves compare qualitatively well with the satellite observations in terms of wave structures, timing, and overall morphology. Excitation mechanisms of these large-amplitude waves in the troposphere are complex and subject to further investigations.

mesoscale gravity waves↗

Local Scale Radiobrightness Modeling During the Intensive Observing Period-4 of the Cold Land Processes Experiment-1

The NASA Cold Land Processes Field Experiment (CLPX-1) was designed to provide microwave remote sensing observations and ground truth for studies of snow and frozen ground remote sensing, particularly issues related to scaling. CLPX-1 was conducted in 2002 and 2003 in Colorado, USA. One of the goals of the experiment was to test the capabilities of microwave emission models at different scales. Initial forward model validation work has concentrated on the Local-Scale Observation Site (LSOS), a 0.8 ha study site consisting of open meadows separated by trees where the most detailed measurements were made of snow depth and temperature, density, and grain size profiles. Results obtained in the case of the 3& Intensive Observing Period (IOP3) period (Feb., 2003, dry snow) suggest that a model based on Dense Medium Radiative Transfer (DMRT) theory is able to model the recorded brightness temperatures using snow parameters derived from field measurements. This paper focuses on the ability of forward DMRT modelling, combined with snowpack measurements, to reproduce the radiobrightness signatures observed by the University of Michigan s Truck-Mounted Radiometer System (TMRS) at 19 and 37 GHz during the 4th IOP (IOP4) in March, 2003. Unlike IOP3, conditions during IOP4 include both wet and dry periods, providing a valuable test of DMRT model performance. In addition, a comparison will be made for the one day of coincident observations by the University of Tokyo's Ground-Based Microwave Radiometer-7 (GBMR-7) and the TMRS. The plot-scale study in this paper establishes a baseline of DMRT performance for later studies at successively larger scales. And these scaling studies will help guide the choice of future snow retrieval algorithms and the design of future Cold Lands observing systems.

Kim, Edward J.↗

The continuous UV flux of Alpha Lyrae - Non-LTE results

Non-LTE calculations for the ultraviolet C I and Si I continuous opacity show that LTE results overestimate the importance of these sources of opacity and underestimate the emergent flux in Alpha Lyr. The largest errors occur between 1100 and 1160 A, where the predicted flux in non-LTE is as much as 50 times larger than in LTE, in reasonable accord with Copernicus observations. The discrepancy between LTE models and observations has been interpreted to result from the existence of a chromosphere. Until a self-consistent non-LTE model atmosphere becomes available, such an interpretation is premature.

Snijders, M. A. J.↗

Estimating Alpine Snow Depth by Combining Multi-Frequency Passive Radiance Observations with Ensemble Snowpack Modeling

This paper presents a physically-based snow depth retrieval algorithm adapted for deep mountainous snowpack and airborne multifrequency (10.7, 18.7, 37.0 and 89.0 GHz) passive microwave (PM) radiance observations from a single flight. The algorithm employs a single forecast-analysis cycle of a traditional sequential assimilation scheme. It uses an ensemble of multi-layer snowpack model runs to resolve snow microstructure and melt-refreeze crusts, andmicrowave radiative transfer models to relate snow properties to microwave measurements.Snow depth was retrieved at a 120 m spatial resolution over three 1 km2 Intensive Study Area (ISA) within the Rabbit Ears Meso-Cell Study Area (MSA) from the NASA Cold Land Processes Experiment (CLPX) in Colorado (United States) for one date in February 2003. When evaluated against in situ observations, root mean square error (RMSE) of the snow depth from the assimilation was 13.3 cm for areas with low (<5 %) forest cover, which was a reduction of 48 % in the RMSE compared with the modeled snow depth when the PM observations were not assimilated; indicating a ~5% relative error of the posterior snow depth with respect to the average snow depth (200 cm) measured at these pixels. For pixels with forest cover ranging from 5-15% and 15-30%, results were improved (R2 increased from 0.65 to 0.71 and from 0 to 0.38, respectively) by introducing a forest radiative transfer model during the assimilation.

Airborne Multifrequency↗

An evaluation of global organic aerosol schemes using airborne observations

Chemical transport models have historically struggled to accurately simulate the magnitude and variability of observed organic aerosol (OA), with previous studies demonstrating that models significantly underestimate observed concentrations in the troposphere. In this study, we explore two different model OA schemes within the standard GEOS-Chem chemical transport model and evaluate the simulations against a suite of 15 globally distributed airborne campaigns from 2008 to 2017, primarily in the spring and summer seasons. These include the ATom, KORUS-AQ, GoAmazon,FRAPPE, SEAC4RS, SENEX, DC3, CalNex, OP3, EUCAARI, ARCTAS and ARCPAC campaigns and provide broad coverage over a diverse set of atmospheric composition regimes – anthropogenic, biogenic, pyrogenic and remote. The schemes include significant differences in their treatment of the primary and secondary components of OA – a “simple scheme” that models primary OA (POA) as non-volatile and takes a fixed-yield approach to secondary OA (SOA) formation and a “complex scheme” that simulates POA as semi-volatile and uses a more sophisticated volatility basis set approach for non-isoprene SOA, with an explicit aqueous uptake mechanism to model isoprene SOA. Despite these substantial differences, both the simple and complex schemes perform comparably across the aggregate dataset in their ability to capture the observed variability (with an R2 of 0.41 and 0.44, respectively). The simple scheme displays greater skill in minimizing the overall model bias (with a normalized mean bias of 0.04 compared to 0.30 for the complex scheme). Across both schemes, the model skill in reproducing observed OA is superior to previous model evaluations and approaches the fidelity of the sulfate simulation within the GEOS-Chem model. However,there are significant differences in model performance across different chemical source regimes, classified here into seven categories.Higher-resolution nested regional simulations indicate that model resolution is an important factor in capturing variability in highly localized campaigns, while also demonstrating the importance of well-constrained emissions inventories and local meteorology, particularly over Asia. Our analysis suggests that a semi-volatile treatment of POA is superior to anon-volatile treatment. It is also likely that the complex scheme parameterization overestimates biogenic SOA at the global scale. While this study identifies factors within the SOA schemes that likely contribute to OA model bias (such as a strong dependency of the bias in the complex scheme on relative humidity and sulfate concentrations), comparisons with the skill of the sulfate aerosol scheme in GEOS-Chem indicate the importance of other drivers of bias, such as emissions, transport and deposition, that are exogenous to the OA chemical scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of GMI All-Sky Radiance Assimilation in the NASA GEOS Forecast System

The assimilation of cloud- and precipitation-affected ("all-sky") radiances has become an important focus of development at most numerical weather prediction centers. Efforts at the Global Modeling and Assimilation Office (GMAO) have focused on all-sky assimilation of GPM Microwave Imager (GMI) radiances, which became operational in the GEOS real-time production system in July 2018. Implementation of the all-sky capability required several upgrades to the GEOS hybrid 4D-EnVar assimilation infrastructure including the addition of control variables for cloud liquid, cloud ice, rain and snow, enhancements to the radiative transfer model, new hybrid background and observational error models, and modified quality control and bias correction procedures. This talk describes the impact of GMI all-sky radiance assimilation on GEOS analyses and forecasts as determined from examination of various metrics including statistics of background departures and analysis increments, forecast skill scores, and forecast sensitivity observation impact (FSOI) calculations. It is shown that in addition to the hydrometeors themselves, the initial wind, temperature and pressure fields all undergo significant dynamic adjustment in response to the analyzed cloud and precipitation features. Assimilation of GMI radiances leads to improved forecasts of lower tropospheric wind, temperature and humidity, especially in the tropics. The largest forecast improvements occur during the first 48 hours, with diminishing impact thereafter. However, combining GMI all-sky assimilation with improvements to the GEOS model physics as in the recent implementation of the real-time production system, extends these forecast improvements well in to the medium range. FSOI results based on a 24-hr moist global energy norm show that GMI radiances provide nearly uniform beneficial impact throughout the tropics, with more mixed impacts in the subtropics. While the overall impact of GMI is smaller than that of other, much more numerous microwave and hyperspectral infrared radiance types, its impact is among the largest of all radiance types on a per-observation basis.

Gelaro, Ron↗

A magnetospheric field model incorporating the OGO 3 and 5 magnetic field observations.

A magnetospheric field model is presented in which the usually assumed toroidal ring current is replaced by a circular disk current of finite thickness that extends from the tail to geocentric distances less than 3 earth radii. The drastic departure of this model from the concept of the conventional ring current lies in that the current is continuous from the tail to the inner magnetosphere. This conceptual change was required to account for the recent results of analysis of the OGO 3 and 5 magnetic field observations. In the present model the cross-tail current flows along circular arcs concentric with the earth and completes circuit via surface currents on the magnetopause. Apart from these return currents in the tail magnetopause, Mead's (1964) model is used for the field from the magnetopause current. The difference scalar field, Delta B, defined as the difference between the scalar field calculated from the present model and the magnitude of the dipole field, is found to be in gross agreement with the observed Delta B.

Sugiura, M.↗

A magnetospheric field model incorporating the OGO 3 and 5 magnetic field observations

A magnetospheric field model is presented in which the usually assumed toroidal ring current is replaced by a circular disk current of finite thickness that extends from the tail to geocentric distances less than 3 earth radii. The drastic departure of this model from the concept of the conventional ring current lies in the fact that the current is continuous from the tail to the inner magnetosphere. This conceptual change was required to account for the recent results of analysis of the OGO 3 and 5 magnetic field observations. In the present model the cross-tail current flows along circular arcs concentric with the earth and completes circuit via surface currents on the magnetopause. Apart from these return currents in the tail magnetopause, Mead's model is used for the field from the magnetopause current. The difference scalar field, delta B, defined as the difference between the scalar field calculated from the present model and the magnitude of the dipole field is found to be in gross agreement with the observed delta B. An updated version of the delta B contours from the OGO 3 and 5 observations, which is used for the comparison, is presented.

Sugiura, M.↗

Pre-clinical investigation of astatine-211-parthanatine for high-risk neuroblastoma

Abstract Astatine-211-parthanatine ([ 211 At]PTT) is an alpha-emitting radiopharmaceutical therapeutic that targets poly(adenosine-diphosphate-ribose) polymerase 1 (PARP1) in cancer cells. High-risk neuroblastomas exhibit among the highest PARP1 expression across solid tumors. In this study, we evaluated the efficacy of [ 211 At]PTT using 11 patient-derived xenograft (PDX) mouse models of high-risk neuroblastoma, and assessed hematological and marrow toxicity in a CB57/BL6 healthy mouse model. We observed broad efficacy in PDX models treated with [ 211 At]PTT at the maximum tolerated dose (MTD 36 MBq/kg/fraction x4) administered as a fractionated regimen. For the MTD, complete tumor response was observed in 81.8% (18 of 22) of tumors and the median event free survival was 72 days with 30% (6/20) of mice showing no measurable tumor >95 days. Reversible hematological and marrow toxicity was observed 72 hours post-treatment at the MTD, however full recovery was evident by 4 weeks post-therapy. These data support clinical development of [ 211 At]PTT for high-risk neuroblastoma.

60 APPLIED LIFE SCIENCES↗

Aspects of modelling the tectonics of large volcanoes on the terrestrial planets

Analytic solutions for the response of planetary lithospheres to volcanic loads have been used to model faulting and infer elastic plate thicknesses. Predictions of the distribution of faulting around volcanic loads, based on the application of Anderson's criteria for faulting to the results of the models, do not agree well with observations. Such models do not give the stress state and stress history within the edifice. The effects of episodic load growth can also be treated. When these effects are included, models give much better agreement with observations.

Mcgovern, Patrick J.↗

The Climatology of Carbon Monoxide and Water Vapor on Mars as Observed by CRISM and Modeled by the GEM-Mars General Circulation Model

Radiative transfer modeling of near-infrared spectra taken by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) instrument onboard Mars Reconnaissance Orbiter (MRO) enables the column-integrated abundance of carbon monoxide (CO) and water vapor (H 2 O) to be retrieved. These results provide a detailed global description of the seasonal and spatial distribution of CO in the Mars atmosphere and new information about the interannual variability of H2O. The CRISM retrievals show the seasonally and globally averaged carbon monoxide mixing ratio to be near 800 parts per million, but with strong seasonal variations, especially at high latitudes. At low latitudes, the carbon monoxide mixing ratio varies in response to the mean seasonal cycle of surface pressure and shows little variation with topography. At high latitudes, carbon monoxide is depleted in the summer hemisphere by a factor of two or more, while in the winter hemisphere there is relatively higher mixing ratio in regions with low-lying topography. Water vapor shows only modest interannual variations, with the largest observed difference being unusually dry conditions in the wake of the Mars Year 28 global dust storm. Modeling results from the GEM (Global Environmental Multiscale) - Mars general circulation model generally reproduce the observed seasonal and spatial trends and provide insight into the underlying physical processes.

Smith, Michael D.↗

Integrating Remote Sensing Observations with NASA's GEOS-5 Modeling Framework in Support of Retrospective Analyses and Seasonal Prediction of Biosphere-Atmosphere CO2 Flux

The absorption of nearly half of all anthropogenic carbon dioxide (CO2) emissions by terrestrial and marine ecosystems has played a critical role in mitigating climate change. However, a persistent lack of understanding of these uptake processes impedes attribution, and thereby introduces large uncertainties into projections of the trajectory of carbon and climate in coming decades. A better understanding and quantification of the seasonal and interannual variability of carbon flux between the atmosphere and ocean and terrestrial biospheres is critically needed to improve predictions from Earth system models. We propose to bring together a diverse suite of remote sensing observations, mechanistic models, and NASA's Goddard Earth Observing System, version 5 (GEOS-5) model to address two objective 1) quantify the processes controlling the temporal variability of biosphere-atmosphere CO2 flux on seasonal and interannual timescales from 1989 to 2018 and 2) evaluating the predictability of the components of carbon flux on seasonal timescales. Because GEOS-5 has been developed to incorporate a variety of Earth system observations and includes a complete and physically consistent depiction of the atmosphere, land, and ocean carbon cycles, it represents a unique and ideal synthesis framework for this effort. By expanding the realism of processes that could be included in GEOS-5 seasonal forecasts, this effort supports NASA's goals toward an integrated Earth system modeling and prediction framework.We propose to integrate a number of observations into the GEOS-5 modeling system to refine retrospective estimates of both terrestrial and marine carbon flux and to test hypotheses regarding the effects of climate drivers on terrestrial carbon flux. This will include assimilating several satellite ocean color products in the NASA Ocean Biogeochemistry Model (NOBM) to improve the representation of ocean biology. We will also utilize remote sensing datasets to increase the temporal resolution of global land-use change estimates and fire emissions to better constrain the temporal variability of the terrestrial carbon cycle. This information will be incorporated into two NASA terrestrial biosphere models Catchment-CN, a dynamic vegetation model that is integrated within GEOS-5 and the Ecosystem Demography (ED) model, a core modeling resource supporting the Global Ecosystem Dynamics Investigation (GEDI) mission to map biomass. Fluxes will be evaluated through 1) comparison to top-down flux estimates inferred from surface CO2 observations and 2) comparison against available aircraft and satellite observations.By combining predictions of net ecosystem exchange and air-sea CO2 flux from land and ocean models with statistical predictions of land use change, fire, and fossil fuel emissions, we propose to create the first dynamical CO2 forecast on seasonal timescales. Because of the experimental nature of this endeavor, an important project objective will be to evaluate the limits to the predictability of different carbon cycle processes over lead times of 1-12 months using different satellite and surface data streams.

Ott, Lesley↗