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NASA NTRSDate not supplied

The Tables of Aerosol Optics (TAO) Project

The Table of Aerosol Optics (TAO) project is a community repository of optics computations (extinction, absorption, single-scatter albedo, lidar ratio, etc) that are useful for global models and remote sensing applications. TAO expands upon historical efforts (e.g., Hess et al., 1998) by building an open database that uses recent measurements and new computational techniques for non-spherical particles. The ‘open’ aspect of TAO is important, since the size distributions, hygroscopicities, refractive indices, and morphological recommendations of today will undoubtedly yield to different values in the future; the open framework of TAO allows scientists to keep adding new computations to the database as the science evolves. TAO is meant to be a community repository where specialists can put their computations for other scientists to use. So for instance, some groups are advancing new techniques that can accommodate complex fractal aggregates of black carbon, other groups are working on realistic irregular shapes for mineral dust, and different groups are updating the hygroscopicity of various aerosol types using new techniques. The TAO database gives these scientists a place to distribute their products. As TAO grows, modelers and remote sensing specialists will look to TAO as a place to find a wide variety of choices for testing. Meanwhile, global modelers can also use TAO to lobby for new tables that accommodate their needs. Eventually, TAO will provide mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at popular remote sensing and global modeling wavelengths (0.25-40 µm) for all pertinent species (sulfate, sea salt, BC, OC, BrC, dust, etc.). TAO will also accept computations for aerosol ‘type’ (e.g., biomass burning, urban, background, etc.) that may include regional and seasonal variability. Multiple tables may be created for each species or type to account for the multiple valid size distributions, hygroscopicities, complex refractive indices, and shapes that can be found in the literature.

Elisabeth Andrews↗

NASA NTRSDate not supplied

The Tables of Aerosol Optics (TAO) Project

Greg Schuster↗

NASA NTRS2016

The South Residual CO2 Cap on Mars: Investigations with a Mars Global Climate Model

The CO2 cycle is one of the three controlling climate cycles on Mars. One aspect of the CO2 cycle that is not yet fully understood is the existence of a residual CO2 ice cap that is offset from the south pole. Previous investigations suggest that the atmosphere could control the placement of the south residual cap (e.g., Colaprete et al., 2005). These investigations show that topographically forced stationary eddies in the south during southern hemisphere winter produce colder atmospheric temperatures and increased CO2 snowfall over the hemisphere where the residual cap resides. Since precipitated CO2 ice produces higher surface albedos than directly deposited CO2 ice, it is plausible that CO2 snowfall resulting from the zonally asymmetric atmospheric circulation produces surface ice albedos high enough to maintain a residual cap only in one hemisphere. Our current work builds on these initial investigations with a version of the NASA Ames Mars Global Climate Model (GCM) that includes a sophisticated CO2 cloud microphysical scheme. Processes of cloud nucleation, growth, sedimentation, and radiative effects are accounted for. Simulated results thus far agree well with the Colaprete et al. study—the zonally asymmetric nature of the atmospheric circulation produces enhanced snowfall over the residual cap hemisphere throughout much of the winter season. However, the predicted snowfall patterns vary significantly with season throughout the cap growth and recession phases. We will present a detailed analysis of the seasonal evolution of the predicted atmospheric circulation and snowfall patterns to more fully evaluate the hypothesis that the atmosphere controls the placement of the south residual cap.

climate cycles on Mars↗

NASA NTRS2019

Examining Seasonal Trends of the Martian Polar Warming with the NASA Ames Mars Global Climate Model

The presented work focuses on polar warming as a diagnostic of the mean circulation to increase our understanding of processes that control the mean meridional circulation and transport in the Mars’ middle atmosphere. The NASA Ames Mars Global Climate Model is utilized to isolate physical processes to determine their impact on polar warming and its seasonal trends.

Brecht, Amanda S.↗

NASA NTRS2012

A New Global Empirical Model of the Electron Temperature with the Inclusion of the Solar Activity Variations for IRI

A data-base of electron temperature (T(sub e)) comprising of most of the available LEO satellite measurements in the altitude range from 350 to 2000 km has been used for the development of a new global empirical model of T(sub e) for the International Reference Ionosphere (IRI). For the first time this will include variations with solar activity. Variations at five fixed altitude ranges centered at 350, 550, 850, 1400, and 2000 km and three seasons (summer, winter, and equinox) were represented by a system of associated Legendre polynomials (up to the 8th order) in terms of magnetic local time and the earlier introduced in vdip latitude. The solar activity variations of T(sub e) are represented by a correction term of the T(sub e) global pattern and it has been derived from the empirical latitudinal profiles of T(sub e) for day and night (Truhlik et al., 2009a). Comparisons of the new T(sub e) model with data and with the IRI 2007 Te model show that the new model agrees well with the data generally within standard deviation limits and that the model performs better than the current IRI T(sub e) model.

Truhlik, V.↗

NASA NTRS2014

The Effects of Chlorophyll Assimilation on Carbon Fluxes in a Global Biogeochemical Model

In this paper, we investigated whether the assimilation of remotely-sensed chlorophyll data can improve the estimates of air-sea carbon dioxide fluxes (FCO2). Using a global, established biogeochemical model (NASA Ocean Biogeochemical Model, NOBM) for the period 2003-2010, we found that the global FCO2 values produced in the free-run and after assimilation were within -0.6 mol C m(sup -2) y(sup -1) of the observations. The effect of satellite chlorophyll assimilation was assessed in 12 major oceanographic regions. The region with the highest bias was the North Atlantic. Here the model underestimated the fluxes by 1.4 mol C m(sup -2) y(sup -1) whereas all the other regions were within 1 mol C m(sup -2) y(sup -1) of the data. The FCO2 values were not strongly impacted by the assimilation, and the uncertainty in FCO2 was not decreased, despite the decrease in the uncertainty in chlorophyll concentration. Chlorophyll concentrations were within approximately 25% of the database in 7 out of the 12 regions, and the assimilation improved the chlorophyll concentration in the regions with the highest bias by 10-20%. These results suggest that the assimilation of chlorophyll data does not considerably improve FCO2 estimates and that other components of the carbon cycle play a role that could further improve our FCO2 estimates.

Biogeochemical Model↗

NASA NTRS1992

Development of a global backscatter model for NASA's laser atmospheric wind sounder

During the Contract Period April 1, 1989, to September 30, 1992, the Earth Systems Science Laboratory (ESSL) in the Research Institute at the University of Alabama in Huntsville (UAH) conducted a program of basic research on atmospheric backscatter characteristics, leading to the development of a global backscatter model. The ESSL research effort was carried out in conjunction with the Earth System Observing Branch (ES43) at the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center, as part of NASA Contract NAS8-37585 under the Atmospheric Dynamics Program at NASA Headquarters. This research provided important inputs to NASA's GLObal Backscatter Experiment (GLOBE) program, especially in the understanding of global aerosol life cycles, and to NASA's Doppler Lidar research program, especially the development program for their prospective space-based Laser Atmospheric Wind Sounder (LAWS).

Bowdle, David↗

NASA NTRS2013

How Well Do Global Climate Models Simulate the Variability of Atlantic Tropical Cyclones Associated with ENSO?

The variability of Atlantic tropical cyclones (TCs) associated with El Nino-Southern Oscillation (ENSO) in model simulations is assessed and compared with observations. The model experiments are 28-yr simulations forced with the observed sea surface temperature from 1982 to 2009. The simulations were coordinated by the U.S. CLIVAR Hurricane Working Group and conducted with five global climate models (GCMs) with a total of 16 ensemble members. The model performance is evaluated based on both individual model ensemble means and multi-model ensemble mean. The latter has the highest anomaly correlation (0.86) for the interannual variability of TCs. Previous observational studies show a strong association between ENSO and Atlantic TC activity, as well as distinctions in the TC activities during eastern Pacific (EP) and central Pacific (CP) El Nino events. The analysis of track density and TC origin indicates that each model has different mean biases. Overall, the GCMs simulate the variability of Atlantic TCs well with weaker activity during EP El Nino and stronger activity during La Nina. For CP El Nino, there is a slight increase in the number of TCs as compared with EP El Nino. However, the spatial distribution of track density and TC origin is less consistent among the models. Particularly, there is no indication of increasing TC activity over the U.S. southeast coastal region as in observations. The difference between the models and observations is likely due to the bias of vertical wind shear in response to the shift of tropical heating associated with CP El Nino, as well as the model bias in the mean circulation.

Tropical Cyclones↗

NASA NTRS2019

Air Pollution Forecasts Using the NASA GEOS Model: A Unified Tool from Local to Global Scales

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) system combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗

NASA NTRS1995

The simulation of complete 11 and 12 year modulation cycles for cosmic rays in the heliosphere using a drift model with global merged interaction regions

Two-dimensional, time-dependent drift models have done exceptionally well in explaining major modulation features, especially during the A less than 0 magnetic polarity cycle of the heliospheric magnetic field when positively charge particles are drifting in along the heliospheric neutral sheet (HNS). These models were found to do well when the heliospheric 'tilt angles' alpha less than approximately 30 deg (le Roux & Potgeiter). However, they seem to do less well when alpha greater than approximately 30 deg during A less than 0 cycles seem to fail when this happens in A greater than 0 cycles. Progress was made in understanding these phases of the modulation cycle when merged interaction regions (MIRs) were incorporated in time-dependent drift models (Potgieter et al.). It was also explicitly shown that in obtaining large step decreases in cosmic rays, the MIRs had to be global, i.e., having a latitudinal extent of more than approximately 60 deg. Other classes of MIRs, such as local MIRs and co-rotating MIRs were found to be of secondary importance for establishing long-term modulation. In a previous paper we studied the effects of two consecutive, identical global MIRs, together with a changing wavy HNS, on long-term modulation (Potegieter & le Roux). This approach gave a very natural and convincing explanation for the observed step decreases in cosmic-ray modulation. Emphasis was placed in the declining and recovery phases of the 11 yr modulation cycle. In this paper, four consecutive, nonidentical global MIRs, in combination with a varying wavy HNS, were included in our time-dependent drift model in order to do simulations closer to what was observed between 1977 and 1987. By doing this we could model, for the first time, complete 11 and 22 yr cycles in the heliospheric modulation of galactic cosmic-rays, including the solar magnetic polarity reversals.

Le Roux, J. A.↗

NASA NTRS2015

The AgMIP GRIDded Crop Modeling Initiative (AgGRID) and the Global Gridded Crop Model Intercomparison (GGCMI)

Climate change is a significant risk for agricultural production. Even under optimistic scenarios for climate mitigation action, present-day agricultural areas are likely to face significant increases in temperatures in the coming decades, in addition to changes in precipitation, cloud cover, and the frequency and duration of extreme heat, drought, and flood events (IPCC, 2013). These factors will affect the agricultural system at the global scale by impacting cultivation regimes, prices, trade, and food security (Nelson et al., 2014a). Global-scale evaluation of crop productivity is a major challenge for climate impact and adaptation assessment. Rigorous global assessments that are able to inform planning and policy will benefit from consistent use of models, input data, and assumptions across regions and time that use mutually agreed protocols designed by the modeling community. To ensure this consistency, large-scale assessments are typically performed on uniform spatial grids, with spatial resolution of typically 10 to 50 km, over specified time-periods. Many distinct crop models and model types have been applied on the global scale to assess productivity and climate impacts, often with very different results (Rosenzweig et al., 2014). These models are based to a large extent on field-scale crop process or ecosystems models and they typically require resolved data on weather, environmental, and farm management conditions that are lacking in many regions (Bondeau et al., 2007; Drewniak et al., 2013; Elliott et al., 2014b; Gueneau et al., 2012; Jones et al., 2003; Liu et al., 2007; M¨uller and Robertson, 2014; Van den Hoof et al., 2011;Waha et al., 2012; Xiong et al., 2014). Due to data limitations, the requirements of consistency, and the computational and practical limitations of running models on a large scale, a variety of simplifying assumptions must generally be made regarding prevailing management strategies on the grid scale in both the baseline and future periods. Implementation differences in these and other modeling choices contribute to significant variation among global-scale crop model assessments in addition to differences in crop model implementations that also cause large differences in site-specific crop modeling (Asseng et al., 2013; Bassu et al., 2014).

climate↗

NASA NTRS1992

An independent refinement and integration procedure in multiregion finite element analysis

An independent refinement and integration procedure is developed to couple together independently modeled (global and local) regions in a single analysis. The models can have different levels of refinement and along the interface between them the finite element nodes need not coincide with one another. In the local model all the nodes except the nodes at the interface are statically condensed and the reduced stiffness matrix is obtained. For this static condensation a modified frontal solution technique is employed. A spline interpolation function that satisfies the linear isotropic plate bending differential equation is used to relate the local model interface nodal displacements to the global model interface displacements. The proposed independent refinement and integration procedure is evaluated by applying it to two- and three-dimensional cases involving inplane and out-of-plane deformation. The procedure yielded very accurate results for all the examples studied.

Krishnamurthy, T.↗

NASA NTRS2014

Near-Surface Meteorology During the Arctic Summer Cloud Ocean Study (ASCOS): Evaluation of Reanalyses and Global Climate Models.

Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)- Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget.

surface energy↗

NASA NTRS2020

An Integrated Model of Models for Global Flood Alerting

A dramatic increase in frequency of minor to major flooding since 2000 has caused significant damage to infrastructure and economic losses across the world. To mitigate and recover from these losses, actions have been taken to build resilient communities and infrastructures. Situational awareness in near real-time is essential to ensure community resilience and enhance response and recovery efforts. Several hydrologic and hydraulic flood models are available at various spatial and temporal resolutions at regional to global scale. Given the global coverage of two operational flood models - GloFAS (Global Flood Awareness System) and GFMS (Global Flood Monitoring System), the first component of this project first focuses on integrating the outputs from these two models to classify flood severity and send alerts based on potential for impacts similar to the USGS PAGER (used for severity alerting and impact analysis for earthquakes). The second component of the project focuses on using flood outputs derived from earth observation data to validate, update and add additional exposure and impact products to flood alerts. The flood impacts and severity information will be disseminated as alerts and maps through the DisasterAWARE platform, operated by the Pacific Disaster Center (PDC), that provides global multi-hazard alerting and Situational Awareness information to the emergency management community and public. In this presentation, the following objectives will be covered: (i) the effective integration of the flood models, (ii) accuracy of the flood model outputs (flood extent and depth) for specific flood events both in the United States and globally in comparison with each other and earth observation data.

Glasscoe, Margaret↗

NASA NTRSDate not supplied

Can We Model Forest Demography Globally? Benchmarking of State-of-the-Art Demographic DGVMs

Forests in Dynamic Global Vegetation Models (DGVMs) have historically been simulated as area-averaged plant functional types in each gridcell instead of representing communities of trees of different sizes and ages (demography). Just as the behaviour of a tree differs according to its ontogeny, so the behaviour of forests is known to differ depending on their demography. Accurately simulating demography is therefore key in order to address questions on afforestation and management strategies, as well as assessments of resilience of forests to disturbances such as drought and fire or diversity changes after a disturbance. Ultimately, demography determines the overall forest biomass in natural forests and is a key arbiter of growth and mortality rates. DGVMs are now able to simulate size and age structure of the trees in forests. However, these models have so far not been benchmarked alongside each other. We evaluate 6 DGVMs (BiomeE, CABLE-POP, FATES, LPJ-GUESS, JULES-RED, ORCHIDEE) against observations on regrowth dynamics as well as natural forests at boreal, temperate and tropical sites. We examine whether the models capture observed regrowth dynamics after disturbance, well-known stand size structure and well-established processes such as self-thinning. We outline the planned route forward towards a standardised international benchmarking framework for demographic DGVMs.

Dynamic Global Vegetation Models↗

NASA NTRS2001

Using Climate Models to Evaluate Mechanisms of Glacial Inception

The initiation and subsequent growth of an ice sheet or large glacier is based on two primary factors: 1. Most fundamentally, a region must exist with a positive net snow accumulation, that is, cold season snowfall exceeds warm season snowmelt. Because snow can melt very rapidly, in a practical sense this probably means that little or no snow melt should occur in the warm season (mountain glaciers being one possible exception). 2. When sufficient ice builds in a region with a positive net snow accumulation, the ice will flow into adjoining regions with a negative mass balance. Feedbacks can also then arise between the emerging ice sheet and the overall climate, which, among other effects, may cause the mass balance in that region to turn positive. A key question is the relative importance of these two factors. In particular, is it possible for a large lowland region to experience a positive mass balance, such that the ice sheet can arise largely 'in-situ'? Or instead are uplands necessary, such that essentially mountain glaciers form first, and then, under the right conditions, grow and coalesce, eventually spreading out into the lowlands? This is probably the single most fundamental question to be addressed in the modeling of glacial inception. Other key questions then focus on how the (upland or low-land) positive mass balance is obtained at some times, but not others (the ice sheets are not continuously present). For Northern Hemisphere ice sheets in particular, what climatic conditions can lead to abundant winter snowfall in the Canadian Arctic and northern Labrador in conjunction with cool summertime conditions? Are both required, or will cool summer conditions alone suffice? Conversely, are a few years of abnormally heavy snowfall all that is required to trigger glacial inception? A major need at present is for carefully constructed climate model studies aimed at addressing these questions. A successful strategy will almost certainly require more than just a global model; while the global climate model might be necessary to properly simulate large-scale forcing, such models have insufficient spatial resolution to adequately address the roles of topography and the nature of the land surface. Necessary also is the use of a high-resolution regional climate model (in conjunction with a global model). Possible forcing mechanisms of Pleistocene ice ages are well known (e.g., orbital forcing; CO2 fluctuations) but we must understand and be able to successfully model the actual processes involved in glacial inception before we can fully understand the true roles played by these forcing mechanisms.

Oglesby, Robert J.↗

NASA NTRS2018

Cirrus Susceptibility to Changes in Ice Nuclei: Physical Processes, Model Uncertainties, and Measurement Needs

One of the proposed concepts for mitigating the warming effect of increasing greenhouse gases is seeding cirrus cloud with ice nuclei (IN) in order to reduce the lifetime and coverage of cold cirrus that have a net warming impact on the earth's surface. Global model simulations of the net impact of changing upper tropospheric IN have given widely disparate results, partly as a result of poor understanding of ice nucleation processes in the current atmosphere, and partly as a result of poor representation of these processes in global models. Here, we present detailed process-model simulations of tropical tropopause layer (TTL) transport and cirrus formation with ice nuclei properties based on recent laboratory nucleation experiments and field measurements of aerosol composition. The model is used to assess the sensitivity of TTL cirrus occurrence frequency and microphysical properties to the abundance and efficacy of ice nuclei. The simulated cloud properties compared with recent high-altitude aircraft measurements of TTL cirrus and ice supersaturation. We find that abundant effective IN (either from glassy organic aerosols or crystalline ammonium sulfate with concentrations greater than about 100/L) prevent the occurrences of large ice concentration and large ice supersaturations, both of which are clearly indicated by the in situ observations. We find that concentrations of effective ice nuclei larger than about 50/L can drive significant changes in cirrus microphysical properties and occurrence frequency. However, the cloud occurrence frequency can either increase or decrease, depending on the efficacy and abundance of IN added to the TTL. We suggest that our lack of information about ice nuclei properties in the current atmosphere, as well as uncertainties in ice nucleation processes and their representations in global models, preclude meaningful estimates of climate impacts associated with addition of ice nuclei in the upper troposphere. We will briefly discuss the key field measurements needed to constrain ice nucleation processes.

Jensen, Eric↗

NASA NTRS2012

Genesis of Twin Tropical Cyclones as Revealed by a Global Mesoscale Model: The Role of Mixed Rossby Gravity Waves

In this study, it is proposed that twin tropical cyclones (TCs), Kesiny and 01A, in May 2002 formed in association with the scale interactions of three gyres that appeared as a convectively-coupled mixed Rossby gravity (ccMRG) wave during an active phase of the Madden-Julian Oscillation (MJO). This is shown by analyzing observational data and performing simulations using a global mesoscale model. A 10-day control run is initialized at 0000 UTC 1 May 2002 with grid-scale condensation but no cumulus parameterizations. The ccMRG wave was identified as encompassing two developing and one non-developing gyres, the first two of which intensified and evolved into the twin TCs. The control run is able to reproduce the evolution of the ccMRG wave and the formation of the twin TCs about two and five days in advance as well as their subsequent intensity evolution and movement within an 8-10 day period. Five additional 10-day sensitivity experiments with different model configurations are conducted to help understand the interaction of the three gyres. These experiments suggest the improved lead time in the control run may be attributed to the realistic simulation of the ccMRG wave with the following processes: (I) wave deepening associated with wave shortening and/or the intensification of individual gyres, (2) poleward movement of gyres that may be associated with bOlll1dary layer processes, (3) realistic simulation of moist processes at regional scales in association with each of the gyres, and (4) the vertical phasing of low- and mid-level cyclonic circulations associated with a specific gyre.

Shen, Bo-Wen↗