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NASA NTRSDate not supplied

Using XR for Improving Scientific Discovery With Numerical Weather Models

Our work explores the use of extended reality (XR) to im- prove scientific discovery with numerical weather/climate models that inform Earth science digital twins, specifically the NASA Goddard Earth Observing System (GEOS) global atmospheric model. The overall project is named the Vi- sualization And Lagrangian dynamics Immersive eXtended Reality Toolkit (VALIXR), which has two main areas of focus: (1) enhancing the understanding of and interaction with model output data through advanced visualizations in the XR environment, and (2) the integration of Lagrangian dynamics into the GEOS model, which allows a natural, feature-specific analysis of Earth science phenomena as op- posed to traditional, fixed-point Eulerian dynamics. Here, we report initial work on these focus areas.

Thomas Grubb↗

NASA NTRS2012

NASA Earth Observation Systems and Applications for Public Health and Air Quality Models and Decisions Support

Health and Air Quality providers and researchers need environmental data to study and understand the geographic, environmental, and meteorological differences in disease. Satellite remote sensing of the environment offers a unique vantage point that can fill in the gaps of environmental, spatial, and temporal data for tracking disease. This presentation will demonstrate the need for collaborations between multi-disciplinary research groups to develop the full potential of utilizing Earth Observations in studying health. Satellite earth observations present a unique vantage point of the earth's environment from space, which offers a wealth of health applications for the imaginative investigator. The presentation is directly related to Earth Observing systems and Global Health Surveillance and will present research results of the remote sensing environmental observations of earth and health applications, which can contribute to the public health and air quality research. As part of NASA approach and methodology they have used Earth Observation Systems and Applications for Public Health and Air Quality Models to provide a method for bridging gaps of environmental, spatial, and temporal data for tracking disease. This presentation will provide an overview of projects dealing with infectious diseases, water borne diseases and air quality and how many environmental variables effect human health. This presentation will provide a venue where the results of both research and practice using satellite earth observations to study weather and it's role in public health research.

Estes, Sue↗

NASA NTRS2013

NASA Earth Observation Systems and Applications for Public Health and Air Quality Models and Decisions Support

Estes, Sue↗

NASA NTRSDate not supplied

A11I-2104 Evaluation of the NASA GEOS Chemistry-Climate Model Coupled Atmosphere-Ocean Configuration for its Suitability to Simulations of Atmospheric Composition in a Changing Climate

The NASA Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM) is a full tropospheric-stratospheric chemistry enabled configuration of the NASA GEOS Earth system model. Among the objectives for research performed with GEOSCCM is to understand the impacts of climate change on recovery of the stratospheric ozone layer over the twenty-first century. Simulations performed in the past with GEOSCCM did not have an interactive ocean and were driven with projected sea surface temperature and sea ice boundary conditions provided by external models. This method limits the application of GEOSCCM for climate study because it doesn’t allow the feedback of composition changes to ocean. For a full representation of the chemistry-climate feedbacks in the Earth System, we have developed a configuration of GEOSCCM that makes use of the MOM5 ocean general circulation model coupled to the GEOS atmospheric general circulation model. This configuration leverages development of the GEOS Sub-seasonal-to-Seasonal (S2S) prediction system, and includes interactive, radiatively coupled aerosols and two-moment, aerosol-aware cloud microphysics. W e have assessed the baseline model climate sensitivity with an Monday, 11 December 2023 08:30 - 12:50 Poster Hall A-C - South (Exhibition Level, South, MC) experiment performed under pre-industrial (e.g., year 1850) greenhouse gas conditions and a second experiment under 4xCO2 conditions, similar to the typical CMIP protocol. The GEOS model is demonstrated to have a climate sensitivity of a 2.6 K increase in global mean surface temperature for an equivalent doubling of CO2 from pre-industrial conditions, in line with current CMIP models. This configuration of the GEOS model is suitable for application to multidecadal to century-long simulations of climate system response to changing greenhouse gas levels. We report here our evaluation of the climate diagnostics of this configuration and discuss future directions for work with this model configuration, including an ongoing twenty-first century projection experiment based on the Chemistry-Climate Model Intercomparison project protocol.

models↗

NASA NTRSDate not supplied

Interannual to Decadal Variability in Subarctic Atlantic Ocean Primary Productivity Historical Variability, Dynamics, and Response to Warming

Phytoplankton primary productivity in the Subarctic Atlantic Ocean sustains valuable fisheries and exports anthropogenic atmospheric carbon dioxide, but multiple Earth system models show that this productivity declines substantially in 21st century global warming scenarios. Prior studies have investigated the spatial and temporal dynamics of the seasonal cycle of the phytoplankton, which exhibit a prominent but spatially variable spring bloom that is caused by the closely related seasonal cycles in solar radiation and vertical mixing that modulate both phytoplankton growth and loss rates. However, recent work indicates that multi-decade declines in this spring bloom with global warming in multiple Earth system models are driven by reductions in circulation of nutrients from the subtropical and tropical thermocline, rather than local changes in vertical mixing or shortwave radiation in the Subarctic. It is unclear if current models of how phytoplankton productivity varies seasonally or over a century in global warming can be interpolated to explain the interannual to decadal variability. In this poster, I will quantify the interannual to decadal variability of phytoplankton chlorophyll using historical satellite ocean color observations and model simulations with the Community Earth System Model. I will then use the observations and model simulations to elucidate the mechanisms of interannual to decadal variability and how that variability is restructured in 21st century global warming scenarios.

nterannual↗

NASA NTRS2014

Sensitivity of Tropical Cyclones to Parameterized Convection in the NASA GEOS5 Model

The sensitivity of tropical cyclones (TCs) to changes in parameterized convection is investigated to improve the simulation of TCs in the North Atlantic. Specifically, the impact of reducing the influence of the Relaxed Arakawa-Schubert (RAS) scheme-based parameterized convection is explored using the Goddard Earth Observing System version5 (GEOS5) model at 0.25 horizontal resolution. The years 2005 and 2006 characterized by very active and inactive hurricane seasons, respectively, are selected for simulation. A reduction in parameterized deep convection results in an increase in TC activity (e.g., TC number and longer life cycle) to more realistic levels compared to the baseline control configuration. The vertical and horizontal structure of the strongest simulated hurricane shows the maximum lower-level (850-950hPa) wind speed greater than 60 ms and the minimum sea level pressure reaching 940mb, corresponding to a category 4 hurricane - a category never achieved by the control configuration. The radius of the maximum wind of 50km, the location of the warm core exceeding 10 C, and the horizontal compactness of the hurricane center are all quite realistic without any negatively affecting the atmospheric mean state. This study reveals that an increase in the threshold of minimum entrainment suppresses parameterized deep convection by entraining more dry air into the typical plume. This leads to cooling and drying at the mid- to upper-troposphere, along with the positive latent heat flux and moistening in the lower-troposphere. The resulting increase in conditional instability provides an environment that is more conducive to TC vortex development and upward moisture flux convergence by dynamically resolved moist convection, thereby increasing TC activity.

GEOS5↗

NASA NTRS2015

Impact of Stratospheric Ozone Zonal Asymmetries on the Tropospheric Circulation

The depletion and recovery of Antarctic ozone plays a major role in changes of Southern Hemisphere (SH) tropospheric climate. Recent studies indicate that the lack of polar ozone asymmetries in chemistry climate models (CCM) leads to a weaker and warmer Antarctic vortex, and smaller trends in the tropospheric mid-latitude jet and the surface pressure. However, the tropospheric response to ozone asymmetries is not well understood. In this study we report on a series of integrations of the Goddard Earth Observing System Chemistry Climate Model (GEOS CCM) to further examine the effect of zonal asymmetries on the state of the stratosphere and troposphere. Integrations with the full, interactive stratospheric chemistry are compared against identical simulations using the same CCM except that (1) the monthly mean zonal mean stratospheric ozone from first simulation is prescribed and (2) ozone is relaxed to the monthly mean zonal mean ozone on a three day time scale. To analyze the tropospheric response to ozone asymmetries, we examine trends and quantify the differences in temperatures, zonal wind and surface pressure among the integrations.

Chemistry-Climate Modeling↗

NASA NTRSDate not supplied

CERES BiDirectional Scans (BDS) data in HDF (CER_BDS_Aqua-FM3_Edition1)

Each BiDirectional Scans (BDS) data product contains twenty-four hours of Level-1b data for each CERES scanner instrument mounted on each spacecraft. The BDS includes samples taken in normal and short Earth scan elevation profiles in both fixed and rotating azimuth scan modes (including space, internal calibration, and solar calibration views). The BDS contains Level-0 raw (unconverted) science and instrument data as well as the geolocated converted science and instrument data. The BDS contains additional data not found in the Level-0 input file, including converted satellite position and velocity data, celestial data, converted digital status data, and parameters used in the radiance count conversion equations. The following CERES BDS data sets are currently available: CER_BDS_TRMM-PFM_Edition1 CER_BDS_Terra-FM1_Edition1 CER_BDS_Terra-FM2_Edition1 CER_BDS_Terra-FM1_Edition2 CER_BDS_Terra-FM2_Edition2 CER_BDS_Aqua-FM3_Edition1 CER_BDS_Aqua-FM4_Edition1 CER_BDS_Aqua-FM3_Edition2 CER_BDS_Aqua-FM4_Edition2 CER_BDS_Aqua-FM3_Edition1-CV CER_BDS_Aqua-FM4_Edition1-CV CER_BDS_Terra-FM1_Edition1-CV CER_BDS_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2005-11-02] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

EOSDIS↗

NASA NTRSDate not supplied

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-MODIS_Edition2B)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2006-01-01] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

ICE WATER PATH↗

NASA NTRSDate not supplied

A14H-04 Analysis of Simulated and Observed Trends in Global Surface PM2.5 and Aerosol Optical Properties from 1958 to 2018 Using the NASA GEOSCCM

Modeling of long-term trends of aerosols and their properties is important for constraining aerosol-climate forcing, and for characterizing changes in particulate matter pollution speciation and exposure. Here we study global and regional long-term trends in surface fine particulate matter (PM ) and aerosol optical properties for 60 years from 1958 to 2018, using simulations performed with the NASA Goddard Earth Observing System Chemistry Climate Model (GEOSCCM), and evaluate the model hindcast with observations for the last three decades. Comparing the modeled aerosols with a diverse set of observations helps interpret observed and simulated trends, and serves as a benchmark for future GEOSCCM developments and input datasets improvements. We first characterize modeled global and regional temporal changes in surface PM and its components, aerosol optical depth (AOD) and single scattering albedo (SSA) and we interpret their link with emissions drivers. We then compare modeled surface PM with ground-based observations from monitoring networks and with global reconstructed PM datasets from observations-model data fusion. Total AOD is compared with long-term satellite measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) and measurements from the ground-based Aerosol Robotic Network (AERONET). Additional aerosol optical properties, such as absorption and scattering coefficients, are evaluated with ground-based observations from the Global Atmosphere Watch (GAW) records.

aerosols↗

NASA NTRSDate not supplied

Application of the Global Precipitation Forecast dataset for Global Landslide Forecasting System

Landslides are extremely damaging, pervasive and cause fatalities and economic impacts. Extreme rainfall events, coupled with inopportune surface conditions, are the primary triggers of landslides around the world. Forecasting landslide events represent an area of open research. A global Landslide Hazard Assessment for Situational Awareness (LHASA) model has been created that provides near real-time dynamic landslide characterization using Integrated Multi-Satellite Retrievals for Global Precipitation Mission (IMERG). However, it does not provide information on prediction of landslides into future. This study considers how global precipitation forecast data compares to satellite rainfall at different spatiotemporal scales and outlines the potential for its use in landslide hazard prediction/forecasting system. NASA Goddard Earth Observing System (GEOS)-Forecast model assimilates new observations every 6 hours, at 00, 06, 12, and 18 UTC. The GEOS-Forecast model is initialized at 00 UTC and is evaluated with IMERG Early, using Multi-Radar Multi-Sensor gauge corrected (MRMS-GC) precipitation product as a reference over contiguous United States (CONUS). Categorical and continuous statistics along with probability density functions and cumulative distribution functions are considered to assess the performance of the precipitation products, with a focus on landslide hotspots. Seasonality appears to influence the performance of both the GEOS-Forecast and IMERG Early product. Moreover, the global comparison between the GEOS-Forecast and IMERG Early is carried out in terms of percentile difference, correlation, and bias maps. For extreme rainfall events in regions such as Mekong, Colombia, and Tajikistan, GEOS-Forecast appears to resolve high rainfall relative to IMERG Early more frequently. Validation over landslide points reveal that for 24hr rainfall accumulations > 100mm, GEOS-Forecast and IMERG coincide. GEOS-Forecast and IMERG Early precipitation matches more closely for tropical cyclones than other types of storms. Overall, the performance varies with respect to location, rainfall intensities, and type of precipitation events.

Sana Khan↗

NASA NTRS2007

Initial Verification of GEOS-4 Aerosols Using CALIPSO and MODIS: Scene Classification

A-train sensors such as MODIS and MISR provide column aerosol properties, and in the process a means of estimating aerosol type (e.g. smoke vs. dust). Correct classification of aerosol type is important because retrievals are often dependent upon selection of the right aerosol model. In addition, aerosol scene classification helps place the retrieved products in context for comparisons and analysis with aerosol transport models. The recent addition of CALIPSO to the A-train now provides a means of classifying aerosol distribution with altitude. CALIPSO level 1 products include profiles of attenuated backscatter at 532 and 1064 nm, and depolarization at 532 nm. Backscatter intensity, wavelength ratio, and depolarization provide information on the vertical profile of aerosol concentration, size, and shape. Thus similar estimates of aerosol type using MODIS or MISR are possible with CALIPSO, and the combination of data from all sensors provides a means of 3D aerosol scene classification. The NASA Goddard Earth Observing System general circulation model and data assimilation system (GEOS-4) provides global 3D aerosol mass for sulfate, sea salt, dust, and black and organic carbon. A GEOS-4 aerosol scene classification algorithm has been developed to provide estimates of aerosol mixtures along the flight track for NASA's Geoscience Laser Altimeter System (GLAS) satellite lidar. GLAS launched in 2003 and did not have the benefit of depolarization measurements or other sensors from the A-train. Aerosol typing from GLAS data alone was not possible, and the GEOS-4 aerosol classifier has been used to identify aerosol type and improve the retrieval of GLAS products. Here we compare 3D aerosol scene classification using CALIPSO and MODIS with the GEOS-4 aerosol classifier. Dust, smoke, and pollution examples will be discussed in the context of providing an initial verification of the 3D GEOS-4 aerosol products. Prior model verification has only been attempted with surface mass comparisons and column optical depth from AERONET and MODIS.

Welton, Ellsworth J.↗

NASA NTRS1999

Interannual Variability of the Mosaic Land-Surface Model

Recently, NASA Goddard Earth Observing System (GEOS-1) reanalysis data has been used to provide forcing for the Koster and Suarez Mosaic Land-surface Model (LSM). The LSM was integrated off-line at all global land points for the period of 1983 - 1995 by the Off-line Land- surface GEOS Assimilation system (OLGA). Here, we compare the interannual variability of OLGA, GEOS-1 and surface observing stations temperature and moisture. Particular attention is given to the United States because of the extreme seasons of 1988 and 1993. Furthermore, the comparison of OLGA is extended to include the analysis of data on the'tiles' (different surface types) in the Mosaic LSM. Results indicate that the GEOS-1 near-surface temperature and moisture reasonably represents the interannual variability in more normal years. However, OLGA also simulates the extreme drought and floods years well. The analysis of the tile information shows that the "Bare soil" surface type is most sensitive to the climate extremes. Off-line testing has provided valuable information on the performance of the Mosaic LSM prior to its incorporation into the new version of the GEOS Data Assimilation System and the integration of a new long reanalysis.

Bosilovich, Michael G.↗

NASA NTRS2018

Mt. Pinatubo's Impacts on the GEOS Forecasting System

The eruption of Mount Pinatubo in June 1991 had dramatic effects on the global climate, introducing a sudden and extreme forcing on the radiative budget. In this presentation we analyze the effects of the Mt. Pinatubo eruption on the seasonal forecast performed with Goddard Earth Observing System (GEOS), an Earth System Model that includes a bulk aerosol model coupled to radiation and an interactive ocean.We performed three ten-member ensembles of 12-month simulations (June 1991-May 1992). These simulations were performed with a 0.5 longitude by 0.5 latitude horizontal resolution. Out of the three ensembles, one excludes the eruption, representing the control experiment. The other two ensembles include the eruption of Mt. Pinatubo, varying in the effective radius of the volcanic sulfate: one assumed the effective radius to be equal to 0.35 micron (as for tropospheric aerosol) and the other has the effective radius set to 0.6 micron (closer to natural observation). Through the analysis of the aerosol forcing results derived from the two assumptions, we can show how this forcing acts on the seasonal forecast system. In particular, we will focus on the impacts to the surface and ocean temperatures and precipitation.

Mukherjee, Nikita↗

NASA NTRS2000

The Sensitivity of Model Ozone to Advective and Photochemical Processes in the High Latitude Winter Lower Stratosphere

Three dimensional chemistry and transport models (CTMs) contain a set of coupled continuity equations which describe the evolution of constituents such as ozone and other minor species which affect ozone. Both advection and photochemical processes contribute to constituent evolution, and a CTM provides a means to evaluate these contributions separately. Such evaluation is particularly useful when both terms are important to the modeled tendency. An example is the ozone tendency in the high latitude winter lower stratosphere, where advection tends to increase ozone, and catalytic processes involving chlorine radicals tend to decrease ozone. The Goddard three dimensional chemistry and transport model uses meteorological fields from the Goddard Earth Observing System Data Assimilation System, thus the modeled ozone evolution may reproduce the observed evolution and provide a test of the model representation of photochemical processes if the transport is shown to be modeled appropriately. We have investigated the model advection further using diabatic trajectory calculations. For long lived constituents such as N2O, the model field for a particular time on a potential temperature surface is compared with a field produced by calculating 15 day back trajectories for a fixed latitude longitude grid, and mapping model N2O at the terminus of the back trajectories onto the initial grid. This provides a quantitative means to evaluate two aspects of the CTM transport: one, the model horizontal gradient between middle latitudes and the polar vortex is compared with the gradient produced using the non-diffusive trajectory calculation; two, the model vertical advection, which is produced by the divergence of the horizontal winds, is compared with the vertical transport expected from diabatic cooling.

Douglass, A.↗

NASA NTRS2017

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

We provide an introduction to a new high-resolution (0.25 degree) global composition forecast produced by NASA's Global Modeling and Assimilation office. The NASA Goddard Earth Observing System version 5 (GEOS-5) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (approximately 25 km). Previously, this combination of detailed chemistry and resolution was only provided by regional models. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 11) to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). The resolution of the forecasts is the highest resolution compared to current, publically-available global composition forecasts. Evaluation and validation of modeled trace gases and aerosols compared to surface and satellite observations will be presented for constituents relative to health air quality standards. Comparisons of modeled trace gases and aerosols against satellite observations show that the model produces realistic concentrations of atmospheric constituents in the free troposphere. Model comparisons against surface observations highlight the model's capability to capture the diurnal variability of air pollutants under a variety of meteorological conditions. The GEOS-5 composition forecasting system offers a new tool for scientists and the public health community, and is being developed jointly with several government and non-profit partners. Potential applications include air quality warnings, flight campaign planning and exposure studies using the archived analysis fields.

Knowland, E. Emma↗

NASA NTRS2018

Air Quality Forecasts Using the NASA GEOS Model

We provide an introduction to a new high-resolution (0.25 degree) global composition forecast produced by NASA's Global Modeling and Assimilation office. The NASA Goddard Earth Observing System version 5 (GEOS-5) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (~25 km). Previously, this combination of detailed chemistry and resolution was only provided by regional models. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 11) to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). The resolution of the forecasts is the highest resolution compared to current, publically-available global composition forecasts. Evaluation and validation of modeled trace gases and aerosols compared to surface and satellite observations will be presented for constituents relative to health air quality standards. Comparisons of modeled trace gases and aerosols against satellite observations show that the model produces realistic concentrations of atmospheric constituents in the free troposphere. Model comparisons against surface observations highlight the model's capability to capture the diurnal variability of air pollutants under a variety of meteorological conditions. The GEOS-5 composition forecasting system offers a new tool for scientists and the public health community, and is being developed jointly with several government and non-profit partners. Potential applications include air quality warnings, flight campaign planning and exposure studies using the archived analysis fields.

Keller, Christoph A.↗

NASA NTRS2018

Air Quality Forecasts Using the NASA GEOS Model

Knowland, K. Emma↗