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NASA NTRS2023

Observed Changes in Hydroclimate Attributed to Human Forcing

Observational and modeling studies indicate significant changes in the global hydroclimate in the twentieth and early twenty-first centuries due to anthropogenic climate change. In this review, we analyze the recent literature on the observed changes in hydroclimate attributable to anthropogenic forcing, the physical and biological mechanisms underlying those changes, and the advantages and limitations of current detection and attribution methods. Changes in the magnitude and spatial patterns of precipitation minus evaporation ( P–E ) are consistent with increased water vapor content driven by higher temperatures. While thermodynamics explains most of the observed changes, the contribution of dynamics is not yet well constrained, especially at regional and local scales, due to limitations in observations and climate models. Anthropogenic climate change has also increased the severity and likelihood of contemporaneous droughts in southwestern North America, southwestern South America, the Mediterranean, and the Caribbean. An increased frequency of extreme precipitation events and shifts in phenology has also been attributed to anthropogenic climate change. While considerable uncertainties persist on the role of plant physiology in modulating hydroclimate and vice versa, emerging evidence indicates that increased canopy water demand and longer growing seasons negate the water-saving effects from increased water-use efficiency.

Drought↗
NASA NTRSDate not supplied

Exploring Anomalous PM 2.5 from Wildfires and Dust Storms using Data and Services at NASA GES DISC

The presence of fine particles in the atmosphere with a diameter of less than 2.5 µm, called particulate matter 2.5 (PM 2.5 ), poses a significant threat to human health as a criteria air pollutant. Fortunately, NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC) provides easy access to several PM 2.5 concentration products. These datasets include the reanalysis of global hourly and monthly aerosol components including PM 2.5 data from the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), as well as 3-hourly real-time ensemble forecasts of PM 2.5 from the Hazardous Air Quality Ensemble System (HAQES). The HAQES products are developed by the George Mason University Air Quality Laboratory as part of NASA's Health Air Quality Applied Science Team (HAQAST). The GES DISC is actively collaborating with scientists in the HAQAST program to further expand air quality data collections. Two new datasets are currently being archived: one is the machine learning-based global hourly PM 2.5 derived from MERRA-2; the other is the localized data (NO 2 , O 3 , and PM 2.5 ) time series derived from NASA's GEOS Composition Forecasting (GEOS-CF) system. In this presentation, we will explore the spatial patterns and long-distance transport characteristics of elevated PM 2.5 during extreme pollution events, such as the June 2023 Canadian wildfires, which are still active at the time of writing; and severe spring dust storms in 2023 over Asia. To gain comprehensive insights, we will utilize various PM 2.5 data in conjunction with satellite-observed aerosol data from TROPOspheric Monitoring Instrument (TROPOMI) on Sentinel-5P. The primary focus of this presentation will be to demonstrate effective use of data tools and services to visualize and explore extreme air pollution phenomena. Additionally, we will provide guidance on how users can download specific data of interest, facilitating further analysis and research in this critical area.

air quality↗
NASA NTRS2024

Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS)

The Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, which controls the sources sinks and chemistry within the Goddard Earth Observing System, recently underwent a major refactoring and update to the representation of physical processes. This paper serves to document code changes that were included in GOCART 2nd Generation (GOCART-2G) and establishes a benchmark simulation that is to be used for future development of the system. The code refactoring increases flexibility such multiple instances of an aerosol species can be run and interact with radiation and cloud microphysics, in addition to the output of multiple wavelength aerosol optical properties in support of data assimilation. From a science perspective, a new radiatively active tracer, brown carbon, was added to distinguish smoke from other sources of organic aerosol thereby improving optical properties entering the radiative calculations. A four-year benchmark simulation was evaluated using in situ and space borne measurements to develop a baseline and prioritize future development. A comparison of simulated aerosol optical depth between GOCART-2G and MODIS retrievals indicates the model captures the overall spatial pattern and seasonal cycle of aerosol optical depth but overestimates aerosol extinction over dusty regions and underestimates aerosol extinction over northern hemisphere boreal forests, requiring further tuning of emissions. This MODIS-based analysis is corroborated by comparisons to MISR and selected AERONET stations. Despite the underestimate of aerosol optical depth in biomass burning regions in GEOS, there is an overestimate in the surface mass of organic carbon in the United States, especially during the summer months.

Allison B Collow↗
NASA NTRSDate not supplied

Applications of MERRA-2 data for avian migration, biomass burning, and dusty atmospheric rivers

Three different applications of MERRA-2 data are presented. 1) Using radar data, we introduced a new concept for spatial patterns of bird migration across the contiguous U.S. This approach allowed us to use MERRA-2 data and learn that remote forcing in the tropical Pacific—through a chain of processes including atmospheric Rossby wave trains— controls the climatic conditions, associated with bird migration in North America. 2) We showed that emissions from biomass burning in the Congo Basin are partly controlled by the low-level winds, which are in turn associated with the intensity of the subtropical high in the Indian Ocean. Using back-trajectory analysis, we found that these emissions combined with their transport mechanism explain the interannual variability of black carbon in West Africa. 3) Our analysis showed that atmospheric rivers in the Middle East contribute to both heavy flood and dust transport within their corridor. We also found that warm advection and rain-on-snow effect of dusty atmospheric rivers further enhance the chance of flood through rapid snowmelt processes.

Amin Dezfuli↗
NASA NTRS2024

Long-Term Trends in Aerosols, Low Clouds, and Large-scale Meteorology over the Western North Atlantic from 2003 to 2020

A continuous decrease of aerosol over the western North Atlantic Ocean (WNAO) on decadal timescales provides a long-term experiment to evaluate how other natural and anthropogenic processes affect the manifestation of aerosol-cloud interactions in this region. Furthermore, the WNAO is a natural laboratory with diverse aerosol sources, marine boundary layer clouds that are more variable than marine stratocumulus deck regions, and unique flow regimes set up by the Gulf Stream and semi-permanent Bermuda High. We investigate how satellite-retrieved macrophysical and microphysical properties of low clouds and the surface shortwave irradiance changed from 2003 to 2020, in tandem with this aerosol decrease. The decadal changes in large-scale meteorology relating to the North Atlantic Oscillation (NAO) are also examined. We find no significant changes in low-cloud fraction but a widespread reduction in low-cloud optical depth attributed to fewer and larger cloud droplets with almost no change in cloud liquid water path. Despite robust signals in low-cloud optical properties together with aerosol decrease, a corresponding increase in the surface shortwave irradiance trends, also called surface brightening, is lacking. This absence of brightening is potentially due to concomitant changes found in large-scale meteorology associated with NAO— a Bermuda High strengthening, sea surface warming, and atmospheric moistening— as well as an increase in high cloud fraction that can counteract the surface brightening. Ultimately, our findings suggest that spatial patterns in the decadal meteorological variability, likely set up by NAO, contribute more to the surface cloud radiative effect over the WNAO than aerosol-cloud interactions.

J Minnie Park↗
NASA NTRS2024

Asheville Urban Development II: Mapping Urban Heat to Support Cooling Initiatives and Climate Resilience Planning in the Greater Asheville Area

Asheville, North Carolina experiences the urban heat island effect, where temperatures in the city are higher than in surrounding rural areas. This effect intensifies with increased urbanization and less vegetative cover. Asheville’s urban heat island was exacerbated by population increases and tree cover decline, escalating the need for heat mitigation. We partnered with the City of Asheville’s Sustainability Department and Asheville GreenWorks whose actions prioritize sustainable city planning and equitable climate resilience. Using NASA Earth observations and ancillary datasets we spatially mapped urban heat, heat vulnerability, and cooling and adaptive capacity from 2019-2023. To map urban heat, we used Landsat 8 and 9 Operational Land Imager and Thermal Infrared Sensor for land surface temperature and albedo data and the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station for evapotranspiration data. We assessed heat vulnerability using the urban heat data andthe Centers for Disease Control and Prevention’s Social Vulnerability Index. To evaluate cooling and adaptive capacity we used the InVEST Urban Cooling Model, integrating our heat vulnerability analysis with land use and cover data from Sentinel-1 Synthetic Aperture Rada rand Sentinel-2 Multispectral Instrument. Our results revealed distinct spatial patterns of urban heat, heat vulnerability, and cooling and adaptive capacity in Asheville with downtown as the focal hotspot and an outward decreasing radial pattern. These findings highlight targeted need for interventions to reduce heat impacts, address environmental injustices, and enhance climate resilience. Our project provided research to local organizations that can be used for heat mitigation in the greater Asheville area.

Authors not in NED but are confirmed contractors. ↗
NASA NTRSDate not supplied

Applications of MERRA-2 Data for Avian Migration, Biomass Burning, and Dusty Atmospheric Rivers

Three different applications of MERRA-2 data are presented. 1) Using radar data, we introduced a new concept for spatial patterns of bird migration across the contiguous U.S. This approach allowed us to use MERRA-2 data and learn that remote forcing in the tropical Pacific—through a chain of processes including atmospheric Rossby wave trains— controls the climatic conditions, associated with bird migration in North America. 2) We showed that emissions from biomass burning in the Congo Basin are partly controlled by the low-level winds, which are in turn associated with the intensity of the subtropical high in the Indian Ocean. Using back-trajectory analysis, we found that these emissions combined with their transport mechanism explain the interannual variability of black carbon in West Africa. 3) Our analysis showed that atmospheric rivers in the Middle East contribute to both heavy flood and dust transport within their corridor. We also found that warm advection and rain-on-snow effect of dusty atmospheric rivers further enhance the chance of flood through rapid snowmelt processes.

Amin Dezfuli↗
NASA NTRS2024

PRODEM: An Annual Series of Summer DEMs (2019 through 2022) of the Marginal Areas of the Greenland Ice Sheet

Surface topography across the marginal zone of the Greenland Ice Sheet is constantly evolving in response to changing weather, season, climate, and ice dynamics. However, current digital elevation models (DEMs) for the ice sheet are usually based on data from a multi-year period, thus obscuring these changes over time. Here we present four 500 m resolution summer DEMs (PRODEMs) of the Greenland Ice Sheet marginal zone for 2019 through 2022. The PRODEMs cover the marginal zone from the ice edge to 50 km inland, hence capturing all Greenland outlet glaciers. Each PRODEM is based on data fusion of CryoSat-2 radar altimetry and ICESat-2 laser altimetry using regionally varying kriging of elevation anomalies relative to ArcticDEM. The PRODEMs are validated using leave-one-out cross-validation, and PRODEM19 is further validated against an external data set, showcasing their ability to correctly represent surface elevations within the associated spatially varying prediction uncertainties. We observe a general lowering of surface elevations during the 4-year PRODEM period, but the spatial pattern of change is highly complex and with annual changes superimposed. The PRODEMs enable detailed studies of the marginal ice sheet elevation changes. With their high spatio-temporal resolution, the PRODEMs will be of value to a wide range of researchers and users studying ice sheet dynamics and monitoring how the ice sheet responds to changing environmental conditions. PRODEMs from summer 2019 through 2022 are available at https://doi.org/10.22008/FK2/52WWHG (Winstrup, 2024), and we plan to annually update the product henceforth.

Digital Elevation Models↗
NASA NTRSDate not supplied

Developing Satellite-Assisted Particulate Matter (SAPM) Estimates over India for the MIRA Working Group

The Models, In Situ, and Remote Sensing of Aerosols (MIRA) Working Group is an international collective that encourages collaboration among researchers from these three atmospheric aerosol communities. MIRA currently comprises five interdisciplinary and independently funded Topic Groups, each with specific goals, and involves requests for additional scientific datasets. The Satellite-Assisted Particulate Matter (SAPM) Topic Group, as part of MIRA, focuses on studying particulate matter smaller than 2.5 microns in diameter (PM2.5) due to its significant contribution to air pollution and its harmful effects on human health. While the annual mean PM2.5 levels are typically low (~5-15 μg/m³) across most of the contiguous United States (CONUS), other countries experience much higher concentrations (e.g., India). SAPM aims to compare different methods and techniques for obtaining surface PM2.5 proxies using spaceborne passive and active remote sensors, aerosol models, and in situ measurements. Ultimately, SAPM aims to provide more extensive coverage of PM2.5 concentrations than what is currently available from in situ ground stations, which are limited in some parts of the CONUS and large regions worldwide. Current SAPM members are exploring PM2.5 estimation techniques using active sensors. This presentation offers an overview of these techniques and highlights the strengths and limitations of each approach. These techniques include 1) spaceborne lidar (CALIOP: Cloud-Aerosol Lidar with Orthogonal Polarization) alone, and 2) a combination of spaceborne lidar (CATS: Cloud Aerosol Transport System) and a global aerosol transport model (GEOS: Goddard Earth Observing System). Additionally, we present a case study featuring our SAPM research in India, a country with high levels of PM2.5 concentrations (i.e., state-level annual means of ~100-200 μg/m³). Consistent spatial patterns in PM2.5 over India are found from the in situ data, CALIOP-based, and CATS/model-based methods, with the highest concentrations found in northern India near New Delhi. The gridded PM2.5 analysis yields high R values between in situ and CATS/model (~0.7) and between in situ and CALIOP nighttime (~0.9), as well as good agreement between CATS/model and CALIOP nighttime PM2.5 estimates (R = ~0.8 and slope = ~0.9). For current and future efforts, the SAPM Topic Group is actively seeking new collaborators, especially those working with in situ aerosol measurements, and is interested in acquiring additional aerosol datasets to improve and validate the PM2.5 proxies.

Travis D Toth↗
NASA NTRS1977

Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models

A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.

Miller, L. D.↗
NASA NTRS1985

Spatial and temporal patterns in pigment biomass in Gulf Stream warm-core ring 82B and its environs

A chronology of the horizontal and vertical distribution of phytoplankton pigment biomass provides a biological life history of Gulf Stream warm-core ring 82B. Development of ring 82B is followed through three distinct periods: a winter/early spring period of deep convective overturn with uniform and relatively high pigment concentrations to depths of 400 m, a late spring stratification period with subsurface (20-30 m) pigment maxima and relatively high ring center values compared to surrounding waters, and a Gulf Stream interaction period when ring characteristics are dominated by intrusions of low pigment concentration waters. While the ring maintains a unique identity throughout these periods of its life, prolonged deep vertical mixing as well as episodic interactions with its surrounding have a significant influence on pigment distributions within the ring. These interactions generally enhance pigment biomass compared to the water mass from which it is derived. A consistent feature of pigment distribution is the remarkable coherence between this measure of phytoplankton biomass and the corresponding physical hydrodynamic structure of the upper water column.

Smith, R. C.↗
NASA NTRS1995

Spatial and temporal patterns of biotic exchange of CO2

Our research is focused on a better quantification of the variations in C02(sub) exchanges between the atmosphere and biosphere and the factors responsible for these exchanges. The principal approach is to infer the variations in the exchanges from variations in the atmospheric C02(sub) distribution.

Fung, Inez↗
NASA NTRSDate not supplied

Characterization of Dendritic Spatially Extended 3D Patterns in Directional Solidification: Microgravity Experiments in DECLIC-DSI onboard ISS and 3D Phase-field Simulations

To clarify and characterize the fundamental physical mechanisms active in the dynamical formation of three-dimensional (3D) arrays of dendrites under diffusive growth conditions, in situ monitoring of series of experiments on transparent model alloy succinonitrile – 0.46 wt% camphor was carried out under low gravity in the DECLIC Directional Solidification Insert onboard the International Space Station. These experiments offer the very unique opportunity to observe in situ and characterize the dynamics of the microstructure formation and evolution in extended 3D patterns under microgravity environment. The analyses of the dendritic patterns for a broad range of growth velocities displaying different levels of sidebranching will be presented. Especially, the time evolution of primary spacing, in case of solidifications at constant pulling rate as well as for experiments with pulling rate jump, will be compared to 3D phase-field simulations, and the results will be discussed in terms of stable spacing range.

Kaihua Ji↗
NASA NTRSDate not supplied

Characterization of Dendritic Spatially Extended 3D Patterns in Directional Solidification: Microgravity Experiments in DECLIC-DSI Onboard ISS and 3D Phase-field Simulations

To clarify and characterize the fundamental physical mechanisms active in the dynamical formation of three-dimensional (3D) arrays of dendrites under diffusive growth conditions, in situ monitoring of series of experiments on transparent model alloy succinonitrile – 0.46 wt% camphor was carried out under low gravity in the DECLIC Directional Solidification Insert onboard the International Space Station. These experiments offer the very unique opportunity to observe in situ and characterize the dynamics of the microstructure formation and evolution in extended 3D patterns under microgravity environment. The analyses of the dendritic patterns for a broad range of growth velocities displaying different levels of sidebranching will be presented. Especially, the time evolution of primary spacing, in case of solidifications at constant pulling rate as well as for experiments with pulling rate jump, will be compared to 3D phase-field simulations, and the results will be discussed in terms of stable spacing range.

Kaihua Ji↗
NASA NTRS2022

Spatial and Seasonal Patterns of the Mosquito Community in Central Oklahoma

Mosquitoes (Culicidae) are ubiquitous flying insects that function as vectors for several viruses that cause disease in humans. Mosquito abundance and diversity are influenced by landscape features and environmental factors such as temperature and precipitation and vary across seasons and years. The range and phenology of many mosquito species that vector viruses relevant to human health are changing. We sampled mosquito communities in central Oklahoma for four years at thirteen sites, collecting over 25,000 mosquitoes; among these, we identified 27 different species, including several that transmit human pathogens and were collected in suburban backyards. Community composition differed across the landscape and changed from early season to late season and year to year. This effort to describe mosquito communities in Oklahoma is a first step toward assessing and predicting arbovirus risk, an ongoing and dynamic public health challenge.

David Hoekman↗
NASA NTRS2014

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

aerosol optical depth↗