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At least 109 records · Page 6

Near real-time air quality forecasts using the NASA GEOS model

NASA's Global Modeling and Assimilation Office (GMAO) produces high-resolution global forecasts for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) 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. The assimilation system is being expanded to include chemically reactive trace gases. We discuss current capabilities of the GEOS Constituent Data Assimilation System (CoDAS) to improve atmospheric composition modeling and possible future directions, notably incorporating new observations (TROPOMI, geostationary satellites) and machine learning techniques. We show how machine learning techniques can be used to correct for sub-grid-scale variability, which further improves model estimates at a given observation site.

Air Quality Forecast↗

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

As temperatures increase, the onset and severity of droughts is likely to become more intense. Improved tools for understanding, monitoring and predicting droughts will be a key component of 21st century climate adaption. The best drought monitoring systems will bring together accurate precipitation estimates with skillful climate and weather forecasts. Such systems combine the predictive power inherent in the current land surface state with the predictive power inherent in low frequency ocean-atmosphere dynamics. To this end, researchers at the Climate Hazards Group (CHG), in collaboration with partners at the USGS and NASA, have developed i) a long (1981-present) quasi-global (50degS-50degN, 180degW-180degE) high resolution (0.05deg) homogenous precipitation data set designed specifically for drought monitoring, ii) tools for understanding and predicting East African boreal spring droughts, and iii) an integrated land surface modeling (LSM) system that combines rainfall observations and predictions to provide effective drought early warning. This talk briefly describes these three components. Component 1: CHIRPS The Climate Hazards group InfraRed Precipitation with Stations (CHIRPS), blends station data with geostationary satellite observations to provide global near real time daily, pentadal and monthly precipitation estimates. We describe the CHIRPS algorithm and compare CHIRPS and other estimates to validation data. The CHIRPS is shown to have high correlation, low systematic errors (bias) and low mean absolute errors. Component 2: Hybrid statistical-dynamic forecast strategies East African droughts have increased in frequency, but become more predictable as Indo- Pacific SST gradients and Walker circulation disruptions intensify. We describe hybrid statistical-dynamic forecast strategies that are far superior to the raw output of coupled forecast models. These forecasts can be translated into probabilities that can be used to generate bootstrapped ensembles describing future climate conditions. Component 3: Assimilation using LSMs CHIRPS rainfall observations (component 1) and bootstrapped forecast ensembles (component 2) can be combined using LSMs to predict soil moisture deficits. We evaluate the skill such a system in East Africa, and demonstrate results for 2013.

Funk, Chris↗

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

As temperatures increase, the onset and severity of droughts is likely to become more intense. Improved tools for understanding, monitoring and predicting droughts will be a key component of 21st century climate adaption. The best drought monitoring systems will bring together accurate precipitation estimates with skillful climate and weather forecasts. Such systems combine the predictive power inherent in the current land surface state with the predictive power inherent in low frequency ocean-atmosphere dynamics. To this end, researchers at the Climate Hazards Group (CHG), in collaboration with partners at the USGS and NASA, have developed i) a long (1981-present) quasi-global (50degS-50degN, 180degW-180degE) high resolution (0.05deg) homogenous precipitation data set designed specifically for drought monitoring, ii) tools for understanding and predicting East African boreal spring droughts, and iii) an integrated land surface modeling (LSM) system that combines rainfall observations and predictions to provide effective drought early warning. This talk briefly describes these three components. Component 1: CHIRPS The Climate Hazards group InfraRed Precipitation with Stations (CHIRPS), blends station data with geostationary satellite observations to provide global near real time daily, pentadal and monthly precipitation estimates. We describe the CHIRPS algorithm and compare CHIRPS and other estimates to validation data. The CHIRPS is shown to have high correlation, low systematic errors (bias) and low mean absolute errors. Component 2: Hybrid statistical-dynamic forecast strategies East African droughts have increased in frequency, but become more predictable as Indo- Pacific SST gradients and Walker circulation disruptions intensify. We describe hybrid statistical-dynamic forecast strategies that are far superior to the raw output of coupled forecast models. These forecasts can be translated into probabilities that can be used to generate bootstrapped ensembles describing future climate conditions. Component 3: Assimilation using LSMs CHIRPS rainfall observations (component 1) and bootstrapped forecast ensembles (component 2) can be combined using LSMs to predict soil moisture deficits. We evaluate the skill such a system in East Africa, and demonstrate results for 2013.

Funk, Chris↗

Characterization of geostationary particle signatures based on the 'injection boundary' model

A simplified analytical procedure is used to characterize the details of geostationary particle signatures, in order to lend support to the 'injection boundary' concept. The signatures are generated by the time-of-flight effects evolving from an initial sharply defined, double spiraled boundary configuration. Complex and highly variable dispersion patterns often observed by geostationary satellites are successfully reproduced through the exclusive use of the most fundamental convection configuration characteristics. Many of the details of the patterns have not been previously presented. It is concluded that most of the dynamical dispersion features can be mapped to the double spiral boundary without further ad hoc assumptions, and that predicted and observed dispersion patterns exhibit symmetries distinct from those associated with the quasi-stationary particle convection patterns.

Mauk, B. H.↗

Formaldehyde Column Density as an Indicator for Elevated Surface Ozone

Efforts to observe near-surface ozone directly from space are hindered by the limited sensitivity of ozone satellite retrievals to the lower troposphere. Formaldehyde (HCHO) column observations from the NASA DISCOVER-AQ campaign showed a strong relationship with surface ozone, particularly when biogenic volatile organic compounds (VOCs) were the dominant ozone precursor due to their strong temperature-driven variability. Both tropospheric ozone and HCHO are secondarily produced through the oxidation of VOCs and in regions where the main fate of RO2 is reaction with NO, thus formaldehyde and ozone are generally co-produced. This work explores the relationship between column formaldehyde and surface ozone using data from two air quality research campaigns, the Long Island Sound Tropospheric Ozone Study (LISTOS) in 2018 and the Korea U.S. - Air Quality (KORUS-AQ) campaign in 2016. These campaigns included HCHO column information from airborne in-situ profiling and remote sensing and ground-based Pandora spectrometers in combination with surface ozone monitors in each region. These data are used to further explore the HCHO-ozone relationship and its potential for identifying areas of elevated ozone using remote sensing or satellite observations of column HCHO alone. These two regions offer a valuable comparison given their different VOC mixtures and the higher NOx levels in Seoul that result in ozone titration effects. This work will also address the potential for this application with future geostationary satellite observations.

Laura Margaret Judd↗

U.S. Plans for Geostationary Hyperspectral Infrared Sounders

NOAA’s Geostationary Extended Observations (GeoXO) satellite system will provide advanced hyperspectral resolution infrared observations. The first GeoXO Sounder (GXS) will fly in the mid-2030s and provide an unprecedented level of information. The plans are for the GXS to be located at a longitude over the center of the U.S. The GXS will be as much of an improvement over the legacy Geostationary Operational Environmental Satellite (GOES)broad-spectral resolution sounder as the Advanced Baseline Imager (ABI) was to the legacy imager. The GXS will be the U.S. contribution to the global ring of geostationary advanced infrared sounders. The GXS sensor will provide unique information about the vertical structure of moisture, winds, and temperature to support both Numerical Weather Prediction (NWP)and nowcasting applications.

Timothy J Schmit↗

Precipitation from Space: Advancing Earth System Science

Of the three primary sources of spatially contiguous precipitation observations (surface networks, ground-based radar, and satellite-based radar/radiometers), only the last is a viable source over ocean and much of the Earth's land. As recently as 15 years ago, users needing quantitative detail of precipitation on anything under a monthly time scale relied upon products derived from geostationary satellite thermal infrared (IR) indices. The Special Sensor Microwave Imager (SSMI) passive microwave (PMW) imagers originated in 1987 and continue today with the SSMI sounder (SSMIS) sensor. The fortunate longevity of the joint National Aeronautics and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA) Tropical Rainfall Measuring Mission (TRMM) is providing the environmental science community a nearly unbroken data record (as of April 2012, over 14 years) of tropical and sub-tropical precipitation processes. TRMM was originally conceived in the mid-1980s as a climate mission with relatively modest goals, including monthly averaged precipitation. TRMM data were quickly exploited for model data assimilation and, beginning in 1999 with the availability of near real time data, for tropical cyclone warnings. To overcome the intermittently spaced revisit from these and other low Earth-orbiting satellites, many methods to merge PMW-based precipitation data and geostationary satellite observations have been developed, such as the TRMM Multisatellite Precipitation Product and the Climate Prediction Center (CPC) morphing method (CMORPH. The purpose of this article is not to provide a survey or assessment of these and other satellite-based precipitation datasets, which are well summarized in several recent articles. Rather, the intent is to demonstrate how the availability and continuity of satellite-based precipitation data records is transforming the ways that scientific and societal issues related to precipitation are addressed, in ways that would not be otherwise possible. These developments have taken place in parallel with the growth of an increasingly interconnected scientific environment. Scientists from different disciplines can easily interact with each other via information and materials they encounter online, and collaborate remotely without ever meeting each other in person. Likewise, these precipitation datasets are quickly and easily available via various data portals and are widely used. Within the framework of the NASA/JAXA Global Precipitation Measurement (GPM mission, these applications will become increasingly interconnected. We emphasize that precipitation observations by themselves provide an incomplete picture of the state of the atmosphere. For example, it is unlikely that a richer understanding of the global water cycle will be possible by standalone missions and algorithms, but must also involve some component of data, where model analyses of the physical state are constrained alongside multiple observations (e.g., precipitation, evaporation, radiation). The next section provides examples extracted from the many applications that use various high-resolution precipitation products. The final section summarizes the future system for global precipitation processing.

Kucera, Paul A.↗

Breaking Barriers: Integrating Geo-Leo Aerosol Data with an Open-Source Approach

The scientific community is still examining the novel data from geostationary satellite observations and evaluating methods for effectively fusing the polar observations with various spatial and temporal resolutions. However, the merged data will present a significant ""Big Data"" challenge, including processing, storage, data discoverability, accessibility, and migration within cloud computing environments. We have developed an open-source package to fuse aerosol optical depths (AOD) products from six satellite sensors in the past four years (2019~2023), and this presentation will update our recent progress. Using this Python-based package, we produced a level 3 global (AOD) product in a quarter-degree spatial resolution every half-hour, fusing the Level 2 AOD data with the Dark Target aerosol retrieval algorithm from six satellites: three geostationary (GOES-16/17 and Himawari-8) with high temporal resolution, and three polar orbiting (TERRA/MODIS, AQUA/MODIS, and SNPP-VIIRS) with global coverage. By integrating these observations, the diurnal cycle of global AOD in this fused product can be characterized at local, regional, and global scales. Furthermore, we are committed to openness and transparency by providing our package and its associated functionalities as open-source. Our dedication to adhering to the FAIR, CARE, and TRUST principles ensures that our users can rely on the integrity and ethical standards of our work. For instance of Interoperability, this package fuses remote sensing products on demand into desired temporal and spatial domains. It can be run in a central processing unit (CPU) or a Graphics processing unit (GPU) mode. This package will empower researchers and practitioners to use satellite and sensor data efficiently in various applications and research.

Xiaohua Pan↗

Leveraging Thousands of Contrail Observations from GLOBE Citizen Scientists

The GLOBE (Global Learning and Observations to Benefit the Environment) Program is NASA's largest and longest-operating citizen science program contributing Earth observations. Over 800,000 cloud observations have been reported worldwide since YEAR that include reports of short-lived, persistent, and persistent-spreading contrails. While contrails can be challenging to observe with space-borne platforms, humans are adept at spotting contrails from the ground. The NASA GLOBE Clouds team at NASA Langley Research Center in Hampton, Virginia matches cloud observations to multiple satellite platforms for comparison, including: NASA's CERES (Clouds and Earth's Radiant Energy System) instrument onboard Terra and Aqua, CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation), and geostationary satellites. A pilot project was started with select students in the United States to track airplanes above 25,000 ft and report airplane type, altitude, and report if a contrail was being or was not being produced. The objective of the pilot project was to establish if this is a scalable approach for building an international observational dataset documenting what types of airplanes are creating what types of contrails (short-lived, persistent, spreading) under what atmospheric conditions. Preliminary results of this pilot project will be presented.

Colón Robles, Marilé↗

Climate Model Evaluation using New Datasets from the Clouds and the Earth's Radiant Energy System (CERES)

There are some in the science community who believe that the response of the climate system to anthropogenic radiative forcing is unpredictable and we should therefore call off the quest . The key limitation in climate predictability is associated with cloud feedback. Narrowing the uncertainty in cloud feedback (and therefore climate sensitivity) requires optimal use of the best available observations to evaluate and improve climate model processes and constrain climate model simulations over longer time scales. The Clouds and the Earth s Radiant Energy System (CERES) is a satellite-based program that provides global cloud, aerosol and radiative flux observations for improving our understanding of cloud-aerosol-radiation feedbacks in the Earth s climate system. CERES is the successor to the Earth Radiation Budget Experiment (ERBE), which has widely been used to evaluate climate models both at short time scales (e.g., process studies) and at decadal time scales. A CERES instrument flew on the TRMM satellite and captured the dramatic 1998 El Nino, and four other CERES instruments are currently flying aboard the Terra and Aqua platforms. Plans are underway to fly the remaining copy of CERES on the upcoming NPP spacecraft (mid-2010 launch date). Every aspect of CERES represents a significant improvement over ERBE. While both CERES and ERBE measure broadband radiation, CERES calibration is a factor of 2 better than ERBE. In order to improve the characterization of clouds and aerosols within a CERES footprint, we use coincident higher-resolution imager observations (VIRS, MODIS or VIIRS) to provide a consistent cloud-aerosol-radiation dataset at climate accuracy. Improved radiative fluxes are obtained by using new CERES-derived Angular Distribution Models (ADMs) for converting measured radiances to fluxes. CERES radiative fluxes are a factor of 2 more accurate than ERBE overall, but the improvement by cloud type and at high latitudes can be as high as a factor of 5. Diurnal cycles are explicitly resolved by merging geostationary satellite observations with CERES and MODIS. Atmospheric state data are provided from a frozen version of the Global Modeling and Assimilation Office- Data Assimilation System at the NASA Goddard Space Flight Center. In addition to improving the accuracy of top-of-atmosphere (TOA) radiative fluxes, CERES also produces radiative fluxes at the surface and at several levels in the atmosphere using radiative transfer modeling, constrained at the TOA by CERES (ERBE was limited to the TOA). In all, CERES uses 11 instruments on 7 spacecraft all integrated to obtain climate accuracy in TOA to surface fluxes. This presentation will provide an overview of several new CERES datasets of interest to the climate community (including a new adjusted TOA flux dataset constrained by estimates of heat storage in the Earth system), show direct comparisons between CERES ad ERBE, and provide a detailed error analysis of CERES fluxes at various time and space scales. We discuss how observations can be used to reduce uncertainties in cloud feedback and climate sensitivity and strongly argue why we should NOT "call off the quest".

Loeb, Norman G.↗

Satellite Data Assimilation in the GEOS Atmospheric Data Assimilation System

The Goddard Earth Observing System (GEOS) is used for weather, climate, and air quality forecasts and producing reanalysis datasets. Its atmospheric data assimilation system (ADAS) is a hybrid–4DEnVar system. Various satellite radiance, atmospheric motion vector (winds), aircraft, and convectional data are assimilated by this system to produce global atmospheric states. The GEOS ADAS is enhanced by considering correlated observational errors among infrared radiance observations and assimilating new microwave radiance data in all-sky conditions. Historical microwave radiance data are tested within the all-sky microwave radiance assimilation framework and show beneficial effect in the preparation of the next GEOS reanalysis product. In this seminar, I will present the procedures of to assimilate microwave radiance data in all-sky conditions in the GEOS-ADAS. I will also discuss our efforts to update GEOS ADAS by assimilating more satellite data such as geostationary infrared observations and new observations made by the Advanced Technology Microwave Sounder (ATMS) aboard NOAA 21 polar orbit satellite.

Jianjun Jin↗

Glyoxal Yield from Isoprene Oxidation and Relation to Formaldehyde: Chemical Mechanism, Constraints from SENEX Aircraft Observations, and Interpretation of OMI Satellite Data

Glyoxal (CHOCHO) is produced in the atmosphere by the oxidation of volatile organic compounds(VOCs). Like formaldehyde (HCHO), another VOC oxidation product, it is measurable from space by solar backscatter. Isoprene emitted by vegetation is the dominant source of CHOCHO and HCHO in most of the world. We use aircraft observations of CHOCHO and HCHO from the Southeast Nexus (SENEX) campaign over the southeast US in summer 2013 to better understand the CHOCHO time-dependent yield from isoprene oxidation, its dependence on nitrogen oxides (NO (sub x) triple bonded to NO plus NO2), the behavior of the CHOCHO-HCHO relationship, the quality of Ozone Monitoring Instrument (OMI) CHOCHO satellite observations, and the implications for using CHOCHO observations from space as constraints on isoprene emissions. We simulate the SENEX and OMI observations with the Goddard Earth Observing System chemical transport model (GEOSChem) featuring a new chemical mechanism for CHOCHO formation from isoprene. The mechanism includes prompt CHOCHO formation under low-NO (sub x) conditions following the isomerization of the isoprene peroxy radical (ISOPO2).The SENEX observations provide support for this prompt CHOCHO formation pathway, and are generally consistent with the GEOS-Chem mechanism. Boundary layer CHOCHO and HCHO are strongly correlated in the observations and the model, with some departure under low-NO (sub x) conditions due to prompt CHOCHO formation. SENEX vertical profiles indicate a free-tropospheric CHOCHO background that is absent from the model. The OMI CHOCHO data provide some support for this free-tropospheric background and show southeast US enhancements consistent with the isoprene source but a factor of 2 too low. Part of this OMI bias is due to excessive surface reflectivities assumed in the retrieval. The OMI CHOCHO and HCHO seasonal data over the southeast US are tightly correlated and provide redundant proxies of isoprene emissions. Higher temporal resolution in future geostationary satellite observations may enable detection of the prompt CHOCHO production under low-NO (sub x) conditions apparent in the SENEX data.

OMI↗

Diverse Responses of Multiple Satellite-Derived Vegetation Greenup Onsets to Dry Periods in the Amazon

Satellite-derived vegetation greenness and seasonal dynamics in the Amazon have generated considerable academic debate over the past two decades. Despite this, the phenological timing of Amazon forests and, in particular their responses to dry periods, remain poorly understood. Here we explicitly identify the diverse timing of vegetation canopy greenup onsets from 10-min geostationary satellite observations, and compute the timing of both the start and end of dry periods from daily precipitation data. We, for the first time, reveal that the Amazon vegetation canopy regularly experiences two cycles of greenup onsets during a year. The occurrence of greenup onset varies diversely from the start to end of the dry periods, but demonstrates regular shifts in local areas, although irregular shifts across the region. The multiple greenup onsets show complex spatial shifts, which closely follow the spatial movement of dry periods. The results provide a new insight into our understanding of the complexity of Amazonian vegetation canopy dynamics during dry periods, which could significantly improve the simulation of carbon and water cycles.

Satellite-Derived Vegetation↗

Multi-sensor Observations of a High-velocity Fireball over the South Atlantic on 2026 April 1

A high-velocity fireball was detected over the South Atlantic (41.9°S, 54.7°W) on 2026 April 1 at 02:13:14 UTC by U.S. Government (USG) sensors, with peak brightness at 90.5 km altitude. The event was well-observed from geostationary orbit by two civilian lightning imagers with near-orthogonal geometry, the Geostationary Operational Environmental Satellite-East Geostationary Lightning Mapper (GLM) and the Exploitation of Meteorological Satellites Meteosat Third Generation Imager 1 Lightning Imager, and it produced low-frequency acoustic signatures. The GLM measured a total radiated energy of 2.4 × 10 10 J, corresponding to a calculated impact energy of 0.086 kt TNT equivalent. Stereoscopic triangulation of the imager tracks yields an independent pre-atmospheric velocity of ~57 km s −1 , some 18% below the USG-reported value. Because orbital provenance is acutely sensitive to the entry velocity, whose reported uncertainty could be substantial, this discrepancy is notable. We document the multi-sensor record and identify the analysis required to assess provenance, which a subsequent study will present.

Silber, Elizabeth Allaryce [Sandia National Lab. (↗

The coupling between the ionosphere and the protonosphere and its implications on the long term variations of ionospheric electron content

The long-term variations in the daytime exchange flux are estimated with the use of model hydrogen concentrations based on the inverse relationship between the abundance of neutral hydrogen and the neutral temperature in the thermosphere. The results are found to be compatible with the observed long-term behavior of the ionospheric electron content at a midlatitude location, as revealed by Faraday observations using geostationary satellites. The basic processes occurring in the ionosphere are reviewed, with emphasis on the concepts of limiting velocity and limiting flux. An approach to the problem of numerical simulation of the ionosphere is also presented and discussed.

Waldman, H.↗

Local time variations of particle flux produced by an electrostatic field in the magnetosphere

The local time variations of particle distributions, which can be produced by the sudden enhancement of a cross-tail electric field, are examined by using adiabatic theory. The strong coupling between acceleration, inward motion, and east-west drift is emphasized. The model is used to interpret recent measurements of delay times of newly accelerated electrons at different local times at geostationary orbit. Observations of the asymmetric storm time 'ring current' are interpreted in terms of the model without invoking particle loss.

Kivelson, M. G.↗

DSN research and technology support

Continuing testing and refinement of the remote controlled, unattended automated pulsar observing station is noted, along with routine pulsar observations of 22 pulsars. Radar observations of geostationary satellite are discussed. Current status of the 400-kW X-band radar is reported along with routine automatic testing of the stability-reliability of the DSS 13 maser-receiver noise adding radiometer combination. A failure in the Faraday rotation receiving system is noted along with discussion in some detail of the activities of the high power transmitter maintenance facility. Continuation of receiver phase stability testing, specifically the effects of temperature on coaxial cables, is discussed and results reported. A demonstration at full power of the microwave power transmission facility is noted and routine support of the planetary radio astronomy experiment is discussed. Transmission of master clock synchronization signals to overseas DSN stations is also reported.

Jackson, E. B.↗