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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Hourly PM 2.5 Estimates across California from 2018 to 2023

This study presents a new data set of hourly PM 2.5 concentrations across California from 2018 to 2023 at a three-kilometer resolution. This data set was developed by assimilating observations from PurpleAir and the U.S. EPA Air Quality System monitors into wildfire smoke forecasts from the High-Resolution Rapid Refresh Smoke (HRRR-Smoke) model using the Gridpoint Statistical Interpolation (GSI) three-dimensional variational data assimilation framework. Archived forecasts of modeled wildfire smoke PM 2.5 from HRRR-Smoke create the background field for assimilation, which is then corrected using surface observations of total PM 2.5 . The resulting reanalysis from GSI provides an estimate of total PM 2.5 that minimizes error from both the observational and the model data. Validation results indicate strong performance, with monthly R 2 values ranging from 0.73 to 0.91 across the six-year data set, comparable to other PM 2.5 data sets. Case studies are presented for three major fire events, the 2018 Camp Fire, 2019 Kincade Fire, and 2020 Lightning Complex Fires to demonstrate the data set’s fidelity in resolving plume dynamics and local exposure patterns. Root-mean-squared error averaged over each month scales with average PM 2.5 concentrations, resulting in a low error under typical conditions but higher absolute errors during extreme smoke events. This is the first long-term, hourly PM 2.5 data set of its kind for California and enables the generation of subdaily exposure metrics, such as peak hourly concentrations, exceedance durations, and time-of-day exposure peaks. The novelty and strong validation of this data set make it a compelling resource for future studies on the impact and significance of subdaily PM 2.5 exposure.

PM2.5↗
NASA NTRS1976

Reanalysis of the Apollo cosmic gamma-ray spectrum in the 0.3 to 10 MeV energy region

Additional data obtained from the Apollo-16 and -17 missions, together with collateral calculations on background radiation effects, have enabled an improved subtraction of unwanted backgrounds from the diffuse cosmic gamma-ray data previously reported from Apollo-15. As a result, the 1- to 10-MeV spectrum is lowered significantly and connects smoothly with recent data at other energies. The inflection reported previously is much less pronounced and has no more than a 1.5-sigma significance. Sky occultation by the Apollo-16 spacecraft shows the bulk of the 0.3- to 1-MeV radiation to be diffuse. The analysis of spurious backgrounds points to important improvements for future experiments designed for this spectral region.

Trombka, J. I.↗
NASA NTRS1977

Reanalysis of the Apollo cosmic gamma-ray spectrum in the 0.3 to 10 MeV energy region

Additional data obtained from the Apollo 16 and Apollo 17 missions, together with collateral calculations on background radiation effects, have made possible an improved subtraction of unwanted backgrounds from the diffuse cosmic gamma-ray data previously reported from Apollo 15. As a result, the 1- to 10-MeV spectrum is lowered significantly and connects smoothly with recent data at other energies. The inflection reported previously is much less pronounced and has no more than a 1.5-sigma significance. Sky occultation by the Apollo 16 spacecraft shows the bulk of the 0.3- to 1-MeV radiation to be diffuse. The analysis of spurious backgrounds points to important improvements for future experiments designed for this spectral region.

Trombka, J. I.↗
NASA NTRS1977

Reanalysis of the Apollo cosmic gamma-ray spectrum in the 0.3 to 10 MeV energy region

Additional data obtained from the Apollo 16 and 17 missions, together with collateral calculations on background radiation effects, have made possible an improved subtraction of unwanted backgrounds from the diffuse cosmic gamma ray data previously reported from Apollo 15. As a result, the 1 to 10 MeV spectrum is lowered significantly and connects smoothly with recent data at other energies. The inflection reported previously is much less pronounced and has no more than 1.5 sigma significance. Sky occultation by the Apollo 16 spacecraft shows the bulk of the 0.3 to 1 MeV radiation to be diffuse. The analysis of spurious backgrounds points to important improvements for future experiments designed for this spectral region. A light-weight satellite design can give a fourfold improvement in the signal to noise for such a measurement. Use of an anisotropic central crystal, which spins quickly compared with possible time variations in detector background, would enable sensitive limits to be set on galactic plane and point source contributions.

Dyer, C. S.↗
NASA NTRS2000

Sensitivity of Spacebased Microwave Radiometer Observations to Ocean Surface Evaporation

Ocean surface evaporation and the latent heat it carries are the major components of the hydrologic and thermal forcing on the global oceans. However, there is practically no direct in situ measurements. Evaporation estimated from bulk parameterization methods depends on the quality and distribution of volunteer-ship reports which are far less than satisfactory. The only way to monitor evaporation with sufficient temporal and spatial resolutions to study global environment changes is by spaceborne sensors. The estimation of seasonal-to-interannual variation of ocean evaporation, using spacebased measurements of wind speed, sea surface temperature (SST), and integrated water vapor, through bulk parameterization method,s was achieved with reasonable success over most of the global ocean, in the past decade. Because all the three geophysical parameters can be retrieved from the radiance at the frequencies measured by the Scanning Multichannel Microwave Radiometer (SMMR) on Nimbus-7, the feasibility of retrieving evaporation directly from the measured radiance was suggested and demonstrated using coincident brightness temperatures observed by SMMR and latent heat flux computed from ship data, in the monthly time scale. However, the operational microwave radiometers that followed SMMR, the Special Sensor Microwave/Imager (SSM/I), lack the low frequency channels which are sensitive to SST. This low frequency channels are again included in the microwave imager (TMI) of the recently launched Tropical Rain Measuring Mission (TRMM). The radiance at the frequencies observed by both TMI and SSM/I were simulated through an atmospheric radiative transfer model using ocean surface parameters and atmospheric temperature and humidity profiles produced by the reanalysis of the European Center for Medium Range Weather Forecast (ECMWF). From the same ECMWF data set, coincident evaporation is computed using a surface layer turbulent transfer model. The sensitivity of the radiance to evaporation over various seasons and geographic locations are examined. The microwave frequencies with radiance that are significant correlated with evaporation are identify and capability of estimating evaporation directly from TMI will be discussed.

Liu, Timothy W.↗
NASA NTRS2020

NASA’s High-Resolution GEOS Forecasting and Reanalysis Products: Impact of Stratospheric Intrusions on Surface Ozone Air Quality

A new approach to the study of stratospheric intrusions (SIs)? the introduction of ozone-rich lower stratospheric air into the troposphere ? uses NASA's Goddard Earth Observing System Model (GEOS) model and assimilation products with an objective feature tracking algorithm to investigate the atmospheric dynamics in the UTLS region that generate SIs and the different mechanisms through which SIs may influence tropospheric chemistry and surface air quality. In particular, SIs have been linked with surface ozone air quality exceedances, especially at the high elevations in the western USA in springtime. However, the impact of SIs in the remaining seasons and over the rest of the USA is less clear. Improved understanding of the connections between large-scale climate variability and local-scale dynamically-driven air quality events may support improved seasonal prediction of SI events. While the spring over the western USA does exhibit the largest number of SIs affecting the lower troposphere, we demonstrate that the number of intrusions in the remaining seasons and over the eastern USA is sizable. Using a multitude of observational datasets, including lidar data, ozonesondes and air quality monitoring surface sites, in combination with GEOS forecast and reanalysis products, the transport of ozone from the stratosphere toward the surface is assessed. By focusing on recent reports of high ozone at monitoring station sites likely associated with SIs, we aim to provide the public with tools which are available in near-real time to enhance their capability to identify the impact of stratospheric air on surface ozone concentrations separate from anthropogenic sources.

Knowland, K. Emma↗
DOE OSTI2024

An ML-based terrestrial data fusion and augmentation framework to enable advanced understanding of the terrestrial carbon and water interactions

Soil moisture is essential to the terrestrial carbon and water cycles and land–atmosphere interactions. There are various types of soil moisture data, and each type has the distinct spatiotemporal strengths and limitations, depending on the diverse applications and retrieval methodologies of different data types (Li et al., in review; The PNNL-82151 FY23 Report). However, the limitations of different soil moisture data in terms of accuracy and spatiotemporal coverage hinder our ability to further understand the soil moisture dynamics across scales. To have a gap free soil moisture data product with a fine spatiotemporal coverage and vertical profiles, we train extreme gradient boosting (XGBoost) models by using (1) in-situ soil moisture measurements from the International Soil Moisture Network (ISMN), (2) soil moisture from the ECMWF reanalysis (ERA) at the 9 km and sub-daily spatiotemporal resolution, (3) the Daymet meteorological fields, and (4) data products that characterize surface conditions, including soil texture, organic content, topography, vegetation type, and rooting depth. We use the trained XGBoost models that have consistent performance across seven soil layers, i.e., 0–5 cm, 5–10 cm, 10–20 cm, 20–40 cm, 40–60 cm, 60–100 cm, and 100–200 cm, and the gridded model predictors to generate a soil moisture data at the 1 km and daily spatiotemporal resolution for the Continental United States (CONUS) from 2001–2020. This dataset can be broadly used for Earth system model benchmark, monitoring extreme weathers, making informed decisions regarding agriculture, water resource management, climate change mitigation, and ecosystem preservation.

58 GEOSCIENCES↗
DOE OSTI2023

Carbon Outgassing in the Antarctic Circumpolar Current Is Supported by Ekman Transport From the Sea Ice Zone in an Observation‐Based Seasonal Mixed‐Layer Budget

Despite its importance for the global cycling of carbon, there are still large gaps in our understanding of the processes driving annual and seasonal carbon fluxes in the high-latitude Southern Ocean. This is due in part to a historical paucity of observations in this remote, turbulent, and seasonally ice-covered region. Here, we use autonomous biogeochemical float data spanning 6 full seasonal cycles and with circumpolar coverage of the Southern Ocean, complemented by atmospheric reanalysis, to construct a monthly climatology of the mixed layer budget of dissolved inorganic carbon (DIC). We investigate the processes that determine the annual mean and seasonal cycle of DIC fluxes in two different zones of the Southern Ocean—the Sea Ice Zone (SIZ) and Antarctic Southern Zone (ASZ). We find that, annually, mixing with carbon-rich waters at the base of the mixed layer supplies DIC which is, in the ASZ, either used for net biological production or outgassed to the atmosphere. In contrast, in the SIZ, where carbon outgassing and the biological pump are weaker, the surplus of DIC is instead advected northward to the ASZ. In other words, carbon outgassing in the southern Antarctic Circumpolar Current (ACC), which has been attributed to remineralized carbon from deep water upwelled in the ACC, is also due to the wind-driven transport of DIC from the SIZ. These results stem from the first observation-based carbon budget of the circumpolar Southern Ocean and thus provide a useful benchmark to evaluate climate models, which have significant biases in this region.

Sauvé, Jade↗
DOE OSTI2025

A Climatology and Life‐Cycle Characteristics of Atmospheric Fronts and Their Associated Precipitation

Abstract Atmospheric fronts are one of the main sources of mid‐latitude variability. We employ a novel method for identifying and tracking fronts and frontal precipitation. Thermal and dynamical variables are used to identify fronts as areal objects in space, which are tracked in time using the open‐source TempestExtremes software package. Precipitation objects are co‐located to identify frontal precipitation. The method is subjected to validation and sensitivity tests using manually curated data from the National Weather Service. Climatologies of fronts and frontal precipitation are computed from reanalysis and observations; fronts are present upwards of 14% of the time in the storm tracks, and represent the majority (up to 90%) of total and extreme precipitation. Novel aspects of the method are showcased through the lifetime characteristics of fronts across North America. Three sets of warm and cold fronts were discovered, and their duration, distance‐traveled, and translation velocity are examined. Plain Language Summary Mid‐latitude low‐pressure systems and weather fronts are important for our day‐to‐day experience of weather events, particularly in the mid‐latitudes. This work makes use of standardized atmospheric data and creates a method of automatically tracking these important atmospheric features and their precipitation to quantify their relative role in global precipitation. Weather fronts are persistent in the mid‐latitudes and are associated with the majority of precipitation–particularly the most intense precipitation. Trajectories of fronts over North America are categorized to create a set of archetypal fronts that occur in that region. The differences between these types of fronts are characterized. Key Points An automated, efficient, and skillful frontal detection algorithm is developed and validated Fronts contribute a larger fraction of extreme precipitation than all precipitation in mid‐latitude storm tracks Fronts across North America have substantial variation in characteristics depending on their origin location

extratropical cyclone↗
DOE OSTI2022

The Relation of Environmental Conditions With Charge Structure in Central Argentina Thunderstorms

In this study we explored the environmental conditions hypothesized to induce a dominant charge structure in thunderstorms in the province of Cordoba, Argentina, during the RELAMPAGO-CACTI (Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations-Clouds, Aerosols, Complex Terrain Interactions) field campaigns. Hypothesized environmental conditions are thought to be related to small warm cloud residence time and warm rain growth suppression, which lead to high cloud liquid water contents in the mixed-phase zone, contributing to positive charging of graupel and anomalous charge structure storms. Data from radiosondes, a cloud condensation nuclei (CCN) ground-based instrument and reanalysis were used to characterize the proximity inflow air of storms with anomalous and normal charge structures. Consistent with the initial hypothesis, anomalous storms had small warm cloud depth caused by dry low-level humidity and low 0°C height. Anomalous storms were associated with lower CCN concentrations than normal storms, an opposite result to the initial expectation. High CAPE is not an important condition for the development of anomalous storms in Argentina, as no clear pattern could be found among the different parameters calculated for updraft proxy that would be consistent with the initial hypothesis.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Use and Limitations of a Climate-Quality Data Record to Study Temperature Trends on the Greenland Ice Sheet

Enhanced melting of the Greenland Ice Sheet has been documented in recent literature along with surface-temperature increases measured using infrared satellite data since 1981. Using a recently-developed climate-quality data record, 11- and 12-year trends in the clear-sky ice-surface temperature (IST) of the Greenland Ice Sheet have been studied using the Moderate-Resolution Imaging Spectroradiometer (MODIS) IST product. Daily and monthly MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 are now available at 6.25-km spatial resolution on a polar stereographic grid as described in Hall et al. (submitted). This record will be elevated in status to a climate-data record (CDR) when more years of data become available either from the MODIS on the Terra or Aqua satellites, or from the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched in October 2011. Maps showing the maximum extent of melt for the entire ice sheet and for the six major drainage basins have been developed from the MODIS IST dataset. Twelve-year trends of the duration of the melt season on the ice sheet vary in different drainage basins with some basins melting progressively earlier over the course of the study period. Some (but not all) of the basins also show a progressively-longer duration of melt. IST 12-year trends are compared with in-situ data, and climate data from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) Reanalysis.

Hall, Dorothy K.↗
NASA NTRS2011

Observational Diagnoses of Extratropical Ozone STE from 2005-2010

The transport of ozone from the stratosphere to the extratropical troposphere is an important boundary condition to tropospheric chemistry. However, previous direct estimates from models and indirect estimates from observations have poorly constrained the magnitude of ozone stratosphere-troposphere exchange (STE). In this study we provide a direct diagnosis of the extratropical ozone STE using data from the Microwave Limb Sounder on Aura and output of the MERRA reanalysis over the time period from 2005 to the present. We find that the mean annual STE is about 275 Tg yr-1 and 205 Tg yr-1 in the NH and SH, respectively. The interannual variability of the magnitude is about twice as great in the NH than the SH. This variability is dominated by the seasonal variability during the late winter and spring. A comparison of the ozone flux to the mass flux reveals that there is not a simple relationship between the two quantities. This presentation will also examine the magnitude and distribution of ozone in the lower stratosphere relative to the years of maximum and minimum ozone STE

Olsen, Mark A.↗
NASA NTRS2012

Derivation of a New Smoke Emissions Inventory using Remote Sensing, and Its Implications for Near Real-Time Air Quality Applications

A new emissions inventory of particulate matter (PM) is being derived mainly from remote sensing data using fire radiative power (FRP) and aerosol optical depth (AOD) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, as well as wind data from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis dataset, which spans the satellite era. This product is generated using a coefficient of emission, C(sub e), that has been produced on a 1x1 degree global grid such that, when it is multiplied with satellite measurements of FRP or its time-integrated equivalent fire radiative energy (FRE) retrieved over a given area and time period, the corresponding PM emissions are estimated. This methodology of using C(sub e) to derive PM emissions is relatively new and advantageous for near real-time air quality applications compared to current methods based on post-fire burned area that may not provide emissions in a timely manner. Furthermore, by using FRP to characterize a fire s output, it will represent better accuracy than the use of raw fire pixel counts, since fires in individual pixels can differ in size and strength by orders of magnitude, resulting in similar differences in emission rates. Here we will show examples of this effect and how this new emission inventory can properly account for the differing emission rates from fires of varying strengths. We also describe the characteristics of the new emissions inventory, and propose the process chain of incorporating it into models for air quality applications.

Ellison, Luke↗
NASA NTRS2023

A Surface Radiation Balance Data Set from Siple Dome in West Antarctica for Atmospheric and Climate Model Evaluation

A field campaign at Siple Dome in West Antarctica during the austral summer 2019-2020 offers an opportunity to evaluate climate model performance, particularly cloud microphysical simulation. Over Antarctic ice sheets and ice shelves, clouds are a major regulator of the surface energy balance, and in the warm season their presence occasionally induces surface melt that can gradually weaken an ice shelf structure. This dataset from Siple Dome, obtained using transportable and solar-poweredequipment, includes surface energy balance measurements, meteorology and cloud remote sensing. To demonstrate how these data can be used to evaluate model performance, comparisons are made with meteorological reanalysis known to give generally good performance over Antarctica (ERA5). Surface albedo measurements show expected variability with observed cloud amount, and can be used to evaluate a model's snowpack parameterization. One case study discussed involves a squall with northerly winds, during which ERA5 fails to produce cloud cover throughout one of the days. A second case study illustrates how shortwave spectroradiometer measurements that encompass the 1.6-micron atmospheric window reveal cloud phase transitions associated with cloud lifecycle. Here, continuously precipitating mixed-phase clouds become mainly liquid water clouds from local morning through the afternoon, not reproduced by ERA5. We challenge researchers to run their various regional or global models in a manner that has the large-scale meteorology follow the conditions of this field campaign, compare cloud and radiation simulations with this Siple Dome dataset, and potentially investigate why cloud microphysical simulations or other model components might produce discrepancies with these observations.

cloud remote sensing↗
NASA NTRS2000

Interannual Variability of the Tropical Energy Balance: Reconciling Observations and Models

Since the beginning of the World Climate Research Program's Global Precipitation Climatology Project (GPCP) satellite remote sensing of precipitation has made dramatic improvements, particularly for tropical regions. Data from microwave and infrared sensors now form the most critical input to precipitation data sets and can be calibrated with surface gauges to so that the strengths of each data source can be maximized in some statistically optimal sense. Recent availability of the TRMM (Tropical Rainfall Measuring Mission) has further aided in narrowing uncertainties in rainfall over the tropics and subtropics. Although climate modeling efforts have long relied on space-based precipitation estimates for validation, we now are in a position to make more quantitative assessments of model performance, particularly in tropical regions. An integration of the CCM3 using observed SSTs as a lower boundary condition is used to examine how well this model responds to ENSO forcing in terms of anomalous precipitation. An integration of the NCEP spectral model used for the Reanalysis-11 effort is also examined. This integration is run with specified SSTs, but no data assimilation. Our analysis focuses on two aspects. First are the spatial anomalies that are indicative of dislocations in Hadley and Walker circulations. Second, we consider the ability of models to replicate observed increases in oceanic precipitation that are noted in satellite observations for large ENSO events. Finally, we consider a slab ocean version of the CCM3 model with prescribed ocean heat transports that mimic upwelling anomalies, but which still allows the surface energy balance to be predicted. This less restrictive experiment is used to understand why model experiments with specified SSTs seem to have noticeably less interannual variability than do the satellite precipitation observations.

Robertson, Franklin R.↗
NASA NTRS2017

Status and Plans for Reanalysis at NASA/GMAO

Reanalysis plays a critical role in GMAOs goal to enhance NASA's program of Earth observations, providing vital data sets for climate research and the development of future missions. As the breadth of NASAs observations expands to include multiple components of the Earth system, so does the need to assimilate observations from currently uncoupled components of the system in a more physically consistent manner. GMAOs most recent reanalysis of the satellite era, MERRA-2, has completed the period 1980-present, and is now running as a continuing global climate analysis with two- to three-week latency. MERRA-2 assimilates meteorological and aerosol observations as a weakly coupled assimilation system as a first step toward GMAOs longer term goal of developing an integrated Earth system analysis (IESA) capability that will couple assimilation systems for the atmosphere, ocean, land and chemistry. The GMAO strategy is to progress incrementally toward an IESA through an evolving combination of coupled systems and offline component reanalyses driven by, for example, MERRA-2 atmospheric forcing. Most recently, the GMAO has implemented a weakly coupled assimilation scheme for analyzing ocean skin temperature within the existing atmospheric analysis. The scheme uses background fields from a near-surface ocean diurnal layer model to assimilate surface-sensitive radiances plus in-situ observations along with all other observations in the atmospheric assimilation system. In addition, MERRA-2-driven simulations of the ocean (plus sea ice) and atmospheric chemistry (for the EOS period) are currently underway, as is the development of a coupled atmosphere-ocean assimilation system. This talk will describe the status of these ongoing efforts and the planned steps toward an IESA capability for climate research.

MERRA-2↗
NASA NTRS2016

MERRA-2 Input Observations: Summary and Assessment

The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) is an atmospheric reanalysis, spanning 1980 through near-realtime, that uses state-of-the-art processing of observations from the continually evolving global observing system. The effectiveness of any reanalysis is a function not only of the input observations themselves, but also of how the observations are handled in the assimilation procedure. Relevant issues to consider include, but are not limited to, data selection, data preprocessing, quality control, bias correction procedures, and blacklisting. As the assimilation algorithm and earth system models are fundamentally fixed in a reanalysis, it is often a change in the character of the observations, and their feedbacks on the system, that cause changes in the character of the reanalysis. It is therefore important to provide documentation of the observing system so that its discontinuities and transitions can be readily linked to discontinuities seen in the gridded atmospheric fields of the reanalysis. With this in mind, this document provides an exhaustive list of the input observations, the context under which they are assimilated, and an initial assessment of selected core observations fundamental to the reanalysis.

Satellite Observations↗
DOE OSTI2026

Gridded Sub-daily Climate Forcings for North America Based on Daymet and ERA5 (Daymet-ERA5)

To support high spatial and temporal resolution land surface modeling, this dataset provides hourly time step historic weather forcing at 1-km spatial resolution for the entire North America. The latest Daymet V4 data provides gridded historic daily weather observations at 1-km spatial resolution from 1980 to 2024. Using sub-daily temporal information from the ECMWF ERA5 reanalysis, Daymet was further temporally downscaled to hourly time steps and provided in the format required for land surface model simulations. The process of temporal downscaling preserves the relative magnitude in each hourly time step from ERA5 while maintaining the total and average values from Daymet for each day. This results in a blended 1980-2024 Daymet-ERA5 dataset. Available variables include surface air temperature, precipitation, specific humidity, shortwave and longwave radiation, wind speed, and pressure. These data can be used as a high-resolution meteorological forcing dataset to support high-resolution land surface modeling where accurate meteorological forcing datasets built from historic observations and/or reanalysis datasets are desirable.

54 ENVIRONMENTAL SCIENCES↗