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NASA NTRS2021

Investigating the Utility of Hyperspectral Sounders in the 9.6 μm Band to Improve Ozone Analyses

Hyperspectral sounder brightness temperatures assimilated in the Global Earth Observing System Atmospheric Data Assimilation System (GEOS-ADAS) were previously limited to assimilating temperature and moisture. The ozone-sensitive 9.6 𝜇 m region is sensed by several hyperspectral sounders including AIRS (Atmospheric InfraRed Sounder), IASI (Infrared Atmospheric Sounding Interferometer), and CrIS (Cross-track Infrared Sounder). Direct assimilation of brightness temperatures in the 9.6 𝜇 m region have been operational at ECMWF for several years. With this study, similar improvements using the GEOS-ADAS are presented. Channels were selected from available operational subsets evaluating information content and minimizing inter-channel correlation. Additionally, information such as channel selections made by other studies, and vertical sensitivities of ozone and temperature were considered. The analyses produced show improvements verified against ozonesondes taken from SHADOZ (Southern Hemisphere Additional Ozonesondes) and WOUDC (World Ozone and Ultraviolet Data Center). This work will be added to the GEOS-ADAS and will provide an improved source of ozone data in NASA Global Modeling and Assimilation Office products.

Ozone↗
NASA NTRSDate not supplied

A Somewhat Detailed Overview of Cloud Impact on the Earth's Radiation Budget

Using a recent edition of CERES EBAF data I will provide an overview of how present-day clouds affect the shortwave and longwave radiation budget of the planet as a whole, and separately its surface and atmosphere. The overview will make the point that different classes of clouds have distinct radiative effects which are also seasonally varying to a substantial degree. I will then show results from my recent work where cloud classes have been defined from active observations according to their vertical stratification. The observed contribution of the various classes to cloud radiative effect components will be detailed, followed by a comparison with a global model where a similar cloud decomposition yields mixed results about the verisimilitude of its cloud-radiation coupling. Time permitting, I will show how cloud classes allow us to build a framework to study the various factors that contribute to cloud radiative effect anomalies.

cloud radiative effect↗
NASA NTRS2020

Assessment of NO2 Observations During DISCOVER-AQ and KORUS-AQ Field Campaigns

NASA’s Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ, conducted in 2011–2014) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea–United States Air Quality Study (KORUS-AQ, conducted in 2016) in South Korea were two field study programs that provided comprehensive, integrated data sets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with the goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique datasets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 31.9 %. These show even larger differences with Pandora, reaching up to 53.9 %, potentially due to a combination of strong gradients in NO2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO2 values are about a actor of 2 lower in these highly polluted environments due in part to inaccurate retrieval assumptions (e.g., a priori pro-files) but mostly to OMI’s large footprint (>312 km2).

Nitrogen dioxide↗
NASA NTRS2021

Brief Communication: An Empirical Relation Between Center Frequency and Measured Thickness for Radar Sounding of Temperate Glaciers

Radar sounding of the thickness of temperate glaciers is challenged by substantial volume scattering, surface scattering and high attenuation rates. Lower-frequency radar sounders are often deployed to mitigate these effects, but the lack of a global synthesis of their success limits progress in system and survey design. Here we extend a recent global compilation of glacier thickness measurements (GlaThiDa) with the center frequency for radar-sounding surveys. From a maximum reported thickness of ∼ 1500 m near 1 MHz, the maximum thickness sounded decreases by ∼ 500 m per frequency decade. Between 25–100 MHz, newer airborne radar sounders generally outperform older, ground-based ones. Based on globally modeled glacier thicknesses, we conclude that a multi-element, ≤30 MHz airborne radar sounder could survey most temperate glaciers more efficiently.

Joseph A MacGregor↗
NASA NTRSDate not supplied

What (and How) MERRA-2 Reanalysis Data are Used in Applied Sciences

The Modern Era Retrospective-analysis for Research and Applications, Version 2 (MERRA-2) is the global atmospheric data reanalysis for the satellite era produced by NASA’s Global Modeling and Assimilation Office (GMAO), using the Goddard Earth Observing System Model (GEOS)version 5.12.4. The data are officially distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). MERRA-2 data have been widely used by the Earth sciences and application community. Since MERRA-2 data were released in early 2016, the number of registered data users has grown steadily from 1,252 in 2016 to 6477 in 2020. By the end of October 2021, ~16 petabytes (over 360 million files) of data have been distributed to more than 18,900 users. Searching in Google Scholar (https://scholar.google.com/), we have found over 7,000 articles, published between January 2017 and May 2021, involving the use ofMERRA-2 data. The figure shows the numbers for various application areas in which theMERRA-2 data have been used, covering almost all of the application areas defined in NASA Applied Sciences (http://appliedsciences.nasa.gov). The largest number of articles are found in disaster research, with the subcategories ordered in flood, wildfires, hurricanes and cyclones, and other forms of severe weather. In this presentation, we will discuss the preliminary findings from a review of the selected literature that uses MERRA-2 data in applied sciences. The current analytic and interoperable data services at GES DISC are listed, such as the on-the-fly subset and analysis service, NASA Giovanni; THREDDS Data Server(TDS); and Python Jupyter notebooks. In addition, we will introduce two new services for supporting the open sciences: My Dashboard and Related Publications.

data management↗
NASA NTRS2018

Effect of Cross-Correlation of Orbital Error on Probability of Collision Determination

This paper discusses the effect of global model error on probability of collision (Pc) determination. Modifications to the Pc formulation for cross-correlation of orbital error in prediction are developed and assessed for recent conjunctions. While specific geometries can be identified or constructed to produce significant change in Pc for the modified formulation, it is of operational interest to quantify the relative occurrence of such cases for satellite conjunction risk assessment. Such analysis is feasible per data collections in place over the past year.

Cross-correlation↗
NASA NTRSDate not supplied

Interannual Variability of Aerosols and CO in the Upper Troposphere/Lower Stratosphere (UTLS): Connection to the Climate Variability, Asian Summer Monsoon Strengths, and Emissions

We present our study of decadal variations of UTLS aerosol composition in terms of their sources and convective transport mechanisms associated with the Asian summer monsoon. We use the NASA global model GEOS that incorporates emissions from anthropogenic, biomass burning, volcanic, and other natural sources to simulate the aerosols and related gases, and satellite observations of aerosols and CO in the UTLS from 2010-2020 to investigate (1) the interannual variability of aerosol composition in the UTLS, (2) such variability in relationship to the ENSO and Asian summer monsoon strengths, and (3) the connections of UTLS aerosol with the anthropogenic and natural emissions.

decadal variations↗
NASA NTRSDate not supplied

Effect of Cross-Correlation of Orbital Error on Probability of Collision Determination

This paper discusses the effect of global model error on probability of collision (Pc) determination. Modifications to the Pc formulation for cross-correlation of orbital error in prediction are developed and assessed for recent conjunctions. While specific geometries can be identified or constructed to produce significant change in Pc for the modified formulation, it is of operational interest to quanti- fy the relative occurrence of such cases for satellite conjunction risk assessment. Large-scale analysis is feasible per data collections in place over the past year.

Steve Casali↗
NASA NTRSDate not supplied

TROPOMI Geometry-dependent Lambertian-Equivalent surface Reflectivity (GLER) Product for Improved Trace-Gas Retrieval

Accurate information about the reflectivity of the Earth's surface is required for most satellite retrievals of atmospheric composition, and this information is generally taken from monthly surface reflectivity climatology that neglects angular dependence. Previously we introduced Geometry-dependent Lambertian-equivalent surface reflectivity (GLER) which captures solar and satellite viewing angle dependence as well as daily and seasonal changes. GLER is calculated from simulations of Rayleigh-only top-of-atmosphere (TOA) radiances over non-Lambertian surfaces. We use NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) product over land and the wind-dependent Cox–Munk wave-facet slope distribution including water-leaving radiance over water to accounts for surface BRDF. We have developed global GLER product, previously for the Ozone Monitoring Instrument (OMI) and recently for Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) with several new improvements and updates. We have implemented the near real time daily V006 MODIS MCD43C1 BRDF data and gap-filled with a daily BRDF coefficient climatology created from 2002-2017 V006 MCD43GF data. The NASA’s Global Modelling Initiative hourly 0.25 x 0.25 deg Replay simulations are used for more accurate determination of pixel specific terrain pressure. To improve detection of seasonal snow/ice scenes, we use the 4-km snow cover product from the Interactive Multi-sensor Snow and Ice Mapping System (IMS). Finally, we use an improved version of the vector linearized discrete ordinate radiative transfer (VLIDORT) for update of the top-of-atmosphere (TOA) radiance look-up-tables (LUTs). We demonstrate how the use of GLER is beneficial to TROPOMI’s high spatial resolution (up to 3.5 km x 3.5 km) measurements to monitor atmospheric trace gas pollutants down to the sub-city scale.

TROPOMI↗
NASA NTRSDate not supplied

Decoupling the Effects of Anthropogenic Emission Reductions from the Meteorology and Natural Emissions in TROPOMI NO 2 Retrievals During the 2020 COVID-19 Lockdowns

Satellite measurements during the COVID-19 lockdowns that began in 2020 revealed unprecedented reductions in NO 2 tropospheric vertical column densities (VCD). These reductions have largely been attributed to reduced anthropogenic emissions associated with abrupt decreases in road traffic and other power consuming business activities. Although decreased emissions tended to be the main contributor to the observed NO 2 VCD reduction, meteorological variability also played a role. Whereas the observed VCD changes were predominantly negative in places where public health policies were strictly enforced, meteorology had both positive and negative effects over short time intervals. Here, we present results from a global study of the NO 2 reductions aimed at disentangling the meteorological and natural emission variability from the anthropogenic emissions over the world’s most populated megacities. For this study, NASA’s TROPOMI NO 2 algorithm was used in conjunction with the Global Modeling Initiative (GMI) chemical transport model to separate the contributions due emissions and meteorology. A priori NO 2 profiles were generated from two GMI simulations performed for 2020 at a resolution of 0.25° longitude x 0.25° latitude. The first simulation used updated, COVID-impacted NOX emissions based on Forster et al. (2020), while the second simulation used the 2019 emissions with the 2020 meteorology, referred to here as 2020BAU. The 2020BAU data set allowed for the decoupling of the emission component from the meteorology. When compared to the same period in 2019, NO 2 column amounts during the lockdowns were reduced in 35 out of 36 cities. While reduced emissions contributed most to the observed total change in NO 2 during the lockdowns, the effects of meteorology were significant, ranging between 40% (Chennai) and 15% (Beijing). In China, an increase in NO 2 levels due to meteorology were observed in five out of the seven cities considered in the study. Use of different a-priori NO 2 profiles from the two simulations in our TROPOMI retrievals allowed for a determination of retrieval errors that ranged from -1.7% to -11.0%. We used the quality assurance flag > 0.75 to select the highest quality scenes in the study period. Using the GMI, we estimated the sampling biases to be in the range -11% to 10% of the total change for the cities in our study.

Brad Fisher↗
NASA NTRSDate not supplied

The GMAO Observing System Simulation Experiment (OSSE) Framework

We present the current status of the OSSE system at the Global Modeling and Assimilation Office at the National Aeronautics and Space Administration (NASA/GMAO). Some of the OSSE techniques developed at GMAO including simulation of realistic observations, e.g., adding errors to simulated observations, are now widely used by the community to evaluate the impact of new observations on the weather forecasts. This talk presents some of the recent progresses and challenges in simulating realistic observations, radiative transfer modeling support for the GMAO OSSE activities, assimilation of OSSE observations into data assimilation systems, and evaluating the impact of simulated observations on the forecast skills.

Isaac Moradi↗
NASA NTRSDate not supplied

The Generation of Mixing Across the Stratospheric Polarvortex Edge By Breaking Gravity Waves

Modern high resolution global atmospheric analyses are capable of resolving larger gravity waves, including their generation, propagation, and breaking. Orographically generated gravity waves that break in the middle stratosphere often appear as disturbances in maps of potential vorticity, a key stratospheric dynamical quantity. Using analyses from the NASA Global Modeling and Assimilation Office, we show how gravity waves not only disturb the local flow above them but can generate flow instabilities leading to eddies that propagate around the stratospheric polar vortex, creating significant mixing across the vortex edge and into the polar region. These disturbances and mixing events are especially noticeable during NH winter months with low planetary scale wave activity such as in January 2022. During January 2022, the initially circular flow around the polar vortex was disrupted by breaking gravity waves, leading to unstable flow that created a chain of eddies around the vortex edge. The mixing associated with this process led to increased ozone in the upper stratosphere polar region.

Polar Vortex↗
NASA NTRSDate not supplied

Faster Tropical Upper Stratospheric Upwelling is Driving Changes in Ozone Chemistry

Trends in N2O and the chlorofluorocarbons (CFCs) cause trends in O3 through changes in their reactive product gases, NOx and ClOx, but transport plays an important role because it controls the distribution of the long‐lived source gases that produce ozone‐destroying radicals. In this study we show that increased tropical upwelling 10‐5 hPa from 2013‐2021 has changed upper stratospheric (UpS) composition and shifted the balance of O3 loss processes. We use N2O, HNO3, NOx, temperature and O3 data from the Aura Microwave Limb Sounder (MLS) and the SCI‐Sat Atmospheric Chemistry Experiment Fourier Transport Spectrometer (ACE‐FTS) over a 16‐year period to show how changes in reactive nitrogen species affected gas phase ozone chemistry above 30 hPa between June 2013‐May 2021 compared to the previous 8 years, June 2005‐May 2013. We use 2 simulations of the Global Modeling Initiative (GMI) chemistry transport model (CTM), with and without time varying MERRA2 meteorology, to understand how dynamical changes during this 16‐yr period affected O3 through changes in loss via the NOx and ClOx cycles. We also identify the role that the quasi‐biennial oscillation (QBO) in tropical zonal winds plays in the UpS composition changes. We find large increases in tropical upwelling and poleward transport in the northern branch of the UpS transport circulation since 2013 that dramatically increased the abundance of the N2O and its odd nitrogen product gases, NOx and HNO3. O3 loss by NOx in the Arctic UpS increased due to dynamically driven composition change, explaining the observed weak O3 recovery in that region since 2005. The increased upwelling also drove decreases in tropical NOx, leading to increased tropical O3 from 12‐6 hPa.

middle atmosphere chemistry and composition↗
NASA NTRSDate not supplied

Implementing JEDI into NASA GMAO’s Real Time Production Suite

NASA’s Global Modeling and Assimilation Office (GMAO) has prepared their first production system involving the Joint Effort for Data assimilation Integration (JEDI) framework. In this system the central analysis, that drives the deterministic forecast, will be provided using JEDI. This talk outlines the phased approach to implementing JEDI into production that GMAO has designed, and how this approach will allow for a careful analysis of the system against the existing data assimilation framework (GSI). In the first phase of implementation the existing data assimilation system will perform certain actions that are still under development in JEDI. These include thinning the observations and producing satellite bias correction coefficients. JEDI is hooked up to the existing workflow so a single line switch can activate whether the existing or JEDI-based analysis is cycled. Outside of the monumental effort to construct JEDI that is ongoing at the Joint Center for Satellite Data Assimilation (JCSDA), GMAO have undertaken two areas of considerable effort. The talk will describe these efforts and highlight the main challenges that have been encountered. The first area of work is to implement the background error model from the existing data assimilation system into JEDI. The second is to validate the observing system in JEDI against the one in GSI, which has involved several new features being added to the observation operators in JEDI. While the longer-term plans involve trying to improve on the GSI in these two areas, GMAO is keen to have JEDI start from a trusted baseline. This is also key to implementing JEDI quickly so other priorities, such as increasing the number of model levels, can be easily worked on in parallel. GMAO is actively working on a framework to shepherd in the next generation coupled data assimilation system and model. As JEDI is implemented for the first time the plan is to ambitiously cycle through implementations, frequently bringing JEDI features to production. Details of these plans will be given in the talk and we will highlight key implementation and product milestones that we hope to achieve, as well as touch on the development environment that we will use to support frequent refreshing of the production system.

JEDI↗
NASA NTRSDate not supplied

A Cold Wet Mars: A Testable Hypothesis for Ancient Mars Ocean Freezing Point Depression Via Low Molecular Weight Organics

Mars exhibits widespread evidence of surface water in the distant past, but global modeling has had difficulty producing climatological conditions conducive to a wet surface. The hypothesis discussed here examines a different way of approaching the problem rather than focusing on climate, instead an examination of the nature of the surface liquid itself. Previous work has largely assumed that martian surface water was a brine analogous to terrestrial ocean water, but recent discoveries suggest that significant amounts of light organic compounds may have been present via abiogenic native production of light organics on Mars [1]. Light organics such as methanol and formaldehyde have an approximate order-of-magnitude greater freezing point depression than brine, potentially lowering the freezing point of martian surface fluids sufficiently to remain liquid even if the mean surface temperature is below zero Centigrade. As Mars evolved and the surface transitioned to the strongly oxidized conditions seen today, the light organics would have oxidized to carbon dioxide and may be a constituent of the atmosphere today. Considerable work must be done to constrain the freezing points of Mars-relevant organic/water and organic/salt/water mixtures, but this investigation might explain the presence of surface fluid on a cold early Mars – a cold, wet Mars as opposed to a warm, wet Mars. Additionally, this approach may work in conjunction with climatological modeling to better describe early conditions conducive which adequately explain observations. This hypothesis can be tested by examination of ancient fluid inclusions (either in situ or via Mars Sample Return) such as those commonly found in halite, preserving samples of ancient martian surface fluid.

M D Fries↗
NASA NTRSDate not supplied

Status and Progress of Observation Usages in the GMAO GEOS Atmospheric Data Assimilation System

The Global Modeling and Assimilation Office (GMAO) continuously works to enhance the use of observations in the Goddard Earth Observing System – Forward Processing (GEOS-FP) model and analysis system. Updates to GEOS-FP in March 2022 and February 2023 focused on the analysis component, adding new capabilities to ingest radiances and other new observing systems, such as SPIRE GNSS-RO data. Concurrent activities enhance aspects of the radiance assimilation, such as the use of hyperspectral radiances in the stratosphere and lower troposphere, the introduction of microwave radiances over land, and a revised treatment of GMI observations. Furthermore, GMAO has been contributing to the Joint Effort for Data assimilation Integration (JEDI), including development and testing of various components of the observing system and GEOS-specific background error covariances that will allow migration of GEOS-FP from a GSI- to a JEDI-based analysis system. A number of examples are shown.

Y Zhu↗
NASA NTRSDate not supplied

The Transition of Satellite Observations Assimilated in GEOS to JEDI

In order to incorporate the Joint Effort for Data assimilation Integration (JEDI) in the Goddard Earth Observing System (GEOS), which is used for weather, climate, and air quality forecasts and producing reanalysis datasets, it is necessary to validate the observing system in JEDI. NASA’s Global Modeling and Assimilation Office (GMAO), with the Joint Center for Satellite Data Assimilation (JCSDA), is developing the Unified Forward Operator (UFO) and adding all the necessary features to replicate existing capability. Various satellite and conventional observations are assimilated by the Gridpoint Statistical Interpolation (GSI)–based GEOS atmospheric data assimilations system. GMAO has been adding, validating, and updating procedures including the GEOS all-sky microwave radiance assimilation framework to assimilate those observation in UFO. Robust tests are conducted to ensure correct configurations of observational data bias correction (BC), quality control (QC), and observation error in UFO and good agreements between UFO and GSI results. Our work on satellite observations is reported in this presentation.

Jianjun Jin↗
NASA NTRSDate not supplied

The NASA Merra-2 Reanalysis Products: Data and Tools Used for Aerosol and Air Quality Studies

The NASA Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) is atmospheric reanalysis data spanning 1980 to present. It has been produced by the NASA Global Modeling and Assimilation Office (GMAO) and is distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). MERRA-2 data includes 100 collections of Earth system variables, mainly from the atmospheric model, such as aerosol fields and meteorological fields, radiation fields, and aerosol fields, guided by the assimilation of as many as six million observations every six hours. MERRA-2 has been one of the most popular datasets from NASA and is widely used in interdisciplinary research and applications, with increasing numbers of new users. For example, at least 7000 users accessed MERRA-2 data at GES DISC in the year 2021, ~1000 more users than in the year 2020. In this presentation, we will introduce the MERRA-2 datasets associated with aerosol and air quality studies and use a wildfire case study to demonstrate the data tools developed at GES DISC to analyze and visualize MERRA-2 data, such as Giovanni and the level 3 and level 4 subsetter, and Jupyter Python notebook. We will also update the status of cloud migration of the MERRA-2 data to Amazon Web Services (AWS).

Xiaohua Pan↗