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NASA NTRSDate not supplied

Characterizing Wildfires in Western US.: A Cloud-based Case Study for Interdisciplinary Research using NASA Resources

This presentation will demonstrate a case study of interdisciplinary research done in the Amazon Web Services (AWS) cloud platform, in addition to in the local machine. We conduct data analysis next to data by leveraging various cloud-based data in NASA Earthdata Cloud, which are distributed by different missions/NASA Distributed Active Archive Centers (DAACs), and cloud computing resources at NASA. For instance, we directly access multiple datasets stored in the AWS Simple Storage Service (S3) buckets using a Python Jupyter notebook through a JupyterHub interface hosted in AWS (without having to download data), and conduct data analysis next to data in the cloud. We will also show how to share the research results following Open Source policy. This case study characterizes the change in wildfire events in the western United States during the past 20 years. In particular, we focus on the wildfires in California in 2021, one of the most severe wildfire years occurring in the most recent 20 years in California. We will analyze the possible causes of wildfires, such as drought conditions and climate variability, and examine the impacts of wildfires on air quality and atmospheric composition, and on land cover. We will examine the data distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), including aerosols and meteorological data from the NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), precipitation from the Global Precipitation Measurement (GPM) and Global Precipitation Climate Project (GPCP), and aerosol index from Ozone Monitoring Instrument (OMI). We also utilize the data distributed by the Physical Oceanography (PO) DAAC, such as Sea Surface Temperature (SST) data from the Group for High Resolution Sea Surface Temperature (GHRSST), and the data distributed by Land Processes (LP) DAAC, such as Normalized Difference Vegetation Index (NDVI).

Xiaohua Pan↗
NASA NTRSDate not supplied

Online Rapid Analysis of Laser Heterodyne Radiometer (LHR) Data Using the Planetary Spectrum Generator (PSG)

One of the biggest challenges in developing scientific instruments is not just the build and testing of an instrument, but the method for processing the data and producing a consistent, well characterized data product that can be confidently used by the public and scientific community. Raw data products are frequently an array of numbers that are a read-out of voltages. The challenge is to convert these arrays into meaningful information as well as remove noise and interferences. Because this can be a tedious and time-consuming, the goal is to automate the process so that data ca be processed rapidly and be available in real-time for event monitoring. Here we present a rapid analysis method for Laser Heterodyne Radiometer (LHR) data that can be used to analyze data taken from a range of LHR observation modes (column, limb, etc.). This online tool uses the versatile Planetary Spectrum Generator (PSG) and allows LHR users to quickly analyze their own data using a NASA Goddard Space Flight Center (GSFC) monitored capability to ensure quality and reproducibility in the data products. Background: Development of a miniaturized LHR (mini-LHR) as a ground instrument for measuring carbon dioxide (CO 2 ) and methane (CH 4 ) in the atmospheric column started in 2009 with the commercial availability of distributive feedback lasers (DFB) in wavelengths that could measure absorption of gases in the near-IR. As new DFB lasers, detectors and hardware emerged at different wavelengths, additional gases were added to the capability. The mini-LHR was adapted into an occultation-viewing CubeSat with Lawrence Livermore National Laboratory (LLNL) for observing CO 2 , CH 4 , and H 2 O in the limb and was launched in 2019. Other versions of the LHR technology have been designed for observation of water vapor in the lunar exosphere as well as observations of trace gases in planetary atmospheres and plumes from icy moons. The PSG is an online tool developed at GSFC that can be used for synthesizing Earth and planetary spectra (atmospheres and surfaces) over a broad range of wavelengths (0.1 μm to 100 mm) for any observatory, orbiter or lander. Spectra are simulated by combining several state-of-the-art radiative transfer models, spectroscopic databases, planetary databases, as well as modern-era retrospective analysis for research and applications, version 2 (MERRA-2) data set which provides meteorological inputs such as modeled surface pressure for calculating dry-air columns.

Emily Wilson↗
NASA NTRSDate not supplied

Generating Global CH4 NASA GEOS Product by Assimilating TROPOMI

Radiative properties of methane (CH4) significantly contribute to climate change and the recent acceleration of global CH4 growth requires thorough investigation into its causes. Examination of temporal and spatial CH4 variability is crucial for better understanding the shifts that are currently taking place. Integrating different CH4 observations to create a reliable, easily to use global atmospheric CH4 product could contribute to assessment of emissions processes, but remains challenging due to the lack of long satellite data records. Here we present the NASA Goddard Earth Observing System (GEOS) based global CH4 product constrained by atmospheric transport from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and assimilated CH4 from the TROPOspheric Monitoring Instrument (TROPOMI). This product uses the Constituent Data Assimilation System (CoDAS) component of the GEOS capability, which has been expanded and generalized to assimilate any satellite, ground-based, or in situ observation of atmospheric composition that can be expressed as a vertical sounding or point sample. The product is similar to the one generated by assimilating carbon dioxide (CO2) data into GEOS from Orbiting Carbon Observatory 2 (OCO-2): OCO-2 GEOS Level 3 daily and monthly, 0.5x0.625 assimilated CO2 V10r. The preliminary product is investigated using a variety of quality check approaches with the help of in situ observations to examine bias correction, error inflation, and performance of the assimilation system. Potential applications of this approach include support for interpretation of high-resolution point source detection approaches, climate and greenhouse gas reanalyses, and boundary conditions for regional modeling approaches.

Nikolay Balashov↗
NASA NTRSDate not supplied

High Latitude Atmospheric Rivers: Teleconnections and Impacts

Atmospheric rivers (ARs) are long, narrow synoptic scale features that act as moisture transport vehicles by moving water vapor poleward. They are typically found in storm tracks and often have profound implications for regional hydroclimate. For high latitude locales such as Antarctica and the Arctic, ARs are fewer in number but often have an outsized impact by either producing significant snow accumulation events, or, depending on their thermal characteristics, initiating melt events on ice sheets, ice shelves, and sea ice. In this study, we apply both reanalysis and climate model data to evaluate high latitude ARs for both the Arctic and Antarctic in the context of teleconnections and modes of variability. Specifically, we fold in both MERRA-2 and ERA5 reanalysis as well as historical and climate change simulations from the CESM2 (Community Earth System Model, Version 2) and E3SMv2 (Energy Exascale Earth System Model, v2) with multiple ensemble members to better understand natural variability versus climate change signals. An overview of AR climatology and impacts will be presented, including a baseline uncertainty quantification analysis using data from ARTMIP (the Atmospheric River Tracking Method Intercomparison Project). AR impacts during specific modes of variability will be characterized by diagnosing precipitation and boundary layer temperature associated with Ars influencing the cryosphere. Modes of variability investigated include the SAM (Southern Annular Mode), PDO (Pacific Decadal Oscillation), PSA2 (Pacific South American Mode 2), the IOD (Indian Ocean Dipole), and the AO (Arctic Oscillation).

Atmospheric Rivers↗
NASA NTRSDate not supplied

Revisiting the Causes of the US Midwest Great Flood of 1993

The floods that occurred in the Midwest during the summer of 1993 remain one of the greatest flooding events in US history. While a considerable amount of work has already been done addressing its causes there still remain uncertainties as to the relative roles of forcing from the tropics and the extra-tropics as well as the extended nature of the excessive rainfall that lasted throughout much of the late spring and summer of that year. Here we use a novel “replay” technique in which the GEOS AGCM is constrained to remain close to the MERRA-2 reanalysis over specified regions of the globe to isolate the causes of the excessive rain. We show the main rainfall event in the upper Midwest in July (extending into August) was the result of the development of a large amplitude Rossby wave (and associated pronounced moisture influx from the Gulf of Mexico) apparently forced by anomalous transient eddies in the western North Pacific. Rainfall that fell in the Midwest during the two months prior to that, while not as intense, acted to precondition the soil, with forcing from the tropics contributing to the May precipitation, while the excessive Midwest rain that fell during June was part of a record hemispheric-wide precipitation signal that appears to be linked to an unusually cold north polar stratosphere. The nature of the stratospheric impact and the possible delayed influence of the Pinatubo eruption is currently being assessed.

Midwest↗
NASA NTRSDate not supplied

Use of Aerosol Observations From Aircraft in Satellite Remote Sensing and Modelling Comparisons

Aerosol extensive and intensive properties vary throughout the world and remain one of the largest uncertainties in determining future climate both because of difficulties in their measurement and their modelled behaviors. Here we highlight the contributions of airborne sampling by the sunphotometer 4STAR (Spectrometers for Sky-Scanning Sun Tracking Atmospheric Research) from two different parts of the world; Korean peninsula and region during the KORUS-AQ experiment (KORean-US Air Quality in May-June 2016) and over the South East Atlantic during ORACLES (ObseRvations of CLouds above Aerosols and their intEractionS in August-September-October 2016, 2017, and 2018) field campaign. The high temporal and spatial resolution, afforded by airborne sampling during KORUS-AQ, are used to determine the variability of aerosol intensive and extensive properties, which is a metric than can be compared in between multiple different observations and models, even over varying surfaces and spanning multiple different aerosol emission sources. We show the consistency over spatial scales of the AOD (Aerosol Optical Depth), and the aerosol intensive properties (Angstrom exponent - AE, fine mode fraction - FMF) observed by 4STAR, GOCI (Geostationary Ocean Color Imager Yonsei aerosol retrieval v2), MERRA-2 reanalysis (Modern-Era Retrospective Analysis for Research and Applications, v2), and from airborne in situ aerosol optical measurements by LARGE (NASA Langley Aerosol Research Group Experiment). The majority of AODs due to fine mode aerosol is observed at altitudes lower than 2 km and is dependent on the prevailing meteorological conditions. AE and FMF are found to be more spatially variable than AOD during all of KORUS-AQ, even when accounting for potential sampling biases. This may indicate that microphysical processes like aerosol particle formation, growth, and coagulation impact the dominant aerosol size at shorter scales than their combined effect on the aerosol optical depth by the aerosol emission, transport, and removal. Averaging between measurements and model, the distance at which the correlation to itself is reduced by 15% is 65 km for AOD, and 22.7 km for AE. Vertically resolved measurement from an aircraft enable the direct measurements of aerosols overlying clouds. When aerosol overlie bright clouds, their radiative impact on the incident light can be either positive or negative. This difference in radiative impact promotes difficulties in remote sensing aerosol properties, which have shown biases in AOD retrievals when clouds are underneath. The AOD above clouds measured by 4STAR during ORACLES are used to build and improve upon the current Near-Real-Time MODACAERO algorithm for above cloud AOD from MODIS, into a continuity product for NASA EOS/SNPP/JPSS.

Aerosol↗
NASA NTRS2022

Global Premature Mortality By Dust and Pollution PM 2.5 Estimated From Aerosol Reanalysis of the Modern-Era Retrospective Analysis for Research and Applications, Version 2

This study quantifies global premature deaths attributable to long-term exposure of ambient PM 2.5 , or PM 2.5 -attributable mortality, by dust and pollution sources. We used NASA’s Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) aerosol reanalysis product for PM 2.5 and the cause-specific relative risk (RR) from the integrated exposure-response (IER) model to estimate global PM2.5-attributable mortality for five causes of deaths, namely ischaemic heart disease (IHD), cerebrovascular disease (CEV) or stroke, lung cancer (LC), chronic obstructive pulmonary disease (COPD), and acute lower respiratory infection (ALRI). The estimated yearly global PM 2.5 -attributable mortality in 2019 amounts to 2.89 (1.38–4.48) millions, which is composed of 1.19 (0.73–1.84) million from IHD, 1.01 (0.35–1.55) million from CEV, 0.29 (0.11–0.48) million from COPD, 0.23 (0.14–0.33) million from ALRI, and 0.17 (0.04–0.28) million from LC (the numbers in parentheses represent the estimated mortality range due corresponding to RR spread at the 95% confidence interval). The mortality counts vary with geopolitical regions substantially, with the highest number of deaths occurring in Asia. China and India account for 40% and 23% of the global PM 2.5 -attributable deaths, respectively. In terms of sources of PM 2.5 , about 22% of the global all-cause PM 2.5 -attributable deaths are caused by desert dust. The largest dust attribution is 37% for ALRI. The relative contributions of dust and pollution sources vary with the causes of deaths and geographical regions. Enforcing air pollution regulations to transfer areas from PM 2.5 nonattainment to PM2.5 attainment can have great health benefits. Being attainable with the United States air quality standard (AQS) of 15 μg/m 3 globally would have avoided nearly 40% or 1.2 million premature deaths. The most recent update of PM 2.5 guideline from 10 to 5 μg/m 3 by the World Health Organization (WHO) would potentially save additional one million lives. Our study highlights the importance of distinguishing aerodynamic size from geometric size in accurately assessing the global health burden of PM 2.5 and particularly for dust. A use of geometric size in diagnosing dust PM 2.5 from the model simulation, a common approach in current health burden assessment, could overestimate the PM 2.5 level in the dust belt by 40–170%, leading to an overestimate of global all-cause mortality by 1 million or 32%.

PM2.5↗
NASA NTRS2022

Canadian and Alaskan Wildfire Smoke Particle Properties, Their Evolution and Controlling Factors, From Satellite Observations

The optical and chemical properties of biomass burning (BB) smoke particles greatly affect the impact that wildfires have on climate and air quality. Previous work has demonstrated some links between smoke properties and factors such as fuel type and meteorology. However, the factors controlling BB particle speciation at emission are not adequately understood nor are the factors driving particle aging during atmospheric transport. As such, modeling wildfire smoke impacts on climate and air quality remains challenging. The potential to provide robust, statistical characterizations of BB particles based on ecosystem type and ambient environmental conditions with remote sensing data is investigated here. Space-based Multi-angle Imaging SpectroRadiometer (MISR) observations, combined with the MISR Research Aerosol (RA) algorithm and the MISR Interactive Explorer (MINX) tool, are used to retrieve smoke plume aerosol optical depth (AOD) and to provide constraints on plume vertical extent; smoke age; and particle size, shape, light-absorption properties, and absorption spectral dependence. These tools are applied to numerous wildfire plumes in Canada and Alaska, across a range of conditions, to create a regional inventory of BB particle-type temporal and spatial distribution. We then statistically compare these results with satellite measurements of fire radiative power (FRP) and land cover characteristics, as well as short-term climate, meteorological, and drought information from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis and the North American Drought Monitor. We find statistically significant differences in the retrieved smoke properties based on land cover type, with fires in forests producing the thickest plumes containing the largest, brightest particles and fires in savannas and grasslands exhibiting the opposite. Additionally, the inferred dominant aging mechanisms and the timescales over which they occur vary systematically between land types. This work demonstrates the potential of remote sensing to constrain BB particle properties and the mechanisms governing their evolution over entire ecosystems. It also begins to realize this potential, as a means of improving regional and global climate and air quality modeling in a rapidly changing world.

Katherine T. Junghenn Noyes↗
NASA NTRSDate not supplied

Regional Energy Budget Over Ocean Derived From Satellite Observations

The uncertainty in regional surface energy flux derived by summing all energy flux components is known to be large. In addition, quantifying the regional energy flux uncertainty considering all flux component uncertainties is very difficult. However, this approach is needed to understand regional energy flux components and how these components change with time. The CERES surface radiation budget data product, Edition 4.1 EBAF combined with reanalysis products was used to assess regional surface energy budget over ocean in earlier studies. The CERES team revised the data product and released Edition 4.2 EBAF product in February 2023. Prominent differences from the earlier edition are: 1) no geostationary satellite derived cloud properties are used for surface irradiance computations and 2) MERRA-2 provides temperature and humidity profiles. Combined with surface turbulent fluxes from various products, this study uses the revised EBAF surface irradiances and addresses regional energy budget over ocean. In addition, the uncertainty in regional surface radiation and energy budgets is discussed.

Seiji Kato↗
NASA NTRSDate not supplied

Forecasting Tonga water vapor effects on the stratosphere during April through August 2022

The ability of an ensemble based Subseasonal-to-Seasonal (S2S) forecast system to capture the circulation anomalies created by the Tonga water vapor injection is investigated using the NASA GEOS-S2S (version 2) system. A 40-member ensemble was initialized in April 2022 based on MERRA-2 meteorology with assimilated Tonga water vapor taken from the M2-SCREAM MLS assimilation. The 40-member forecasts were run through June 2022 with 10 selected members continuing through August 2022. Duplicate ensembles were initialized without the Tonga water vapor as a control experiment. Results show that the forecasted patterns of cooling at 20 hPa, water vapor advection at 20 hPa, and zonal mean winds at 1 hPa agree well the assimilation products out to 4 months, indicating the usefulness of S2S system diagnostics in understanding the impact of the large water perturbation.

Lawrence Coy↗
NASA NTRS2023

An Evaluation of A Physics-Based Firn Model and A Semi-Empirical Firn Model Across the Greenland Ice Sheet (1980–2020)

The Greenland Ice Sheet's (GrIS) firn layer buffers the ice sheet's contribution to sea level rise by storing meltwater in its pore space. However, available pore space and meltwater retention capability is lost due to ablation of the firn layer and refreezing of meltwater as near-surface ice slabs in the firn. Understanding how firn properties respond to climate is important for constraining the GrIS's future contribution to sea level rise in a warming climate. Observations of firn density provide detailed information about firn properties, but they are spatially and temporally limited. Here we use two firn models, the physics-based SNOWPACK model and the Community Firn Model configured with a semi-empirical densification equation (CFM-GSFC), to quantify firn properties across the GrIS from 1980 through 2020. We use an identical forcing (Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) atmospheric reanalysis) for SNOWPACK and the CFM-GSFC in order to isolate firn model differences. To evaluate the models, we compare simulated firn properties, including firn air content (FAC), to measurements from the Surface Mass Balance and Snow on Sea Ice Working Group (SUMup) dataset of snow and firn density. Both models perform well (mean absolute percentage errors of 14 % in SNOWPACK and 16 % in the CFM-GSFC), though their performance is hindered by the spatial resolution of the atmospheric forcing. In the ice-sheet-wide simulations, the 1980–1995 average spatially integrated FAC (i.e., air volume in the firn) for the upper 100 m is 34 645 km 3 from SNOWPACK and 28 581 km 3 from the CFM-GSFC. The discrepancy in the magnitude of the modeled FAC stems from differences in densification with depth and variations in the sensitivity of the models to atmospheric forcing. In more recent years (2005–2020), both models simulate substantial depletion of pore space. During this period, the spatially integrated FAC across the entire GrIS decreases by 3.2 % (−66.6 km 3 yr −1 ) in SNOWPACK and 1.5 % (−17.4 km 3 yr −1 ) in the CFM-GSFC. These differing magnitudes demonstrate how model differences propagate throughout the FAC record. Over the full modeled record (1980–2020), SNOWPACK simulates a loss of pore space equivalent to 3 mm of sea level rise buffering, while the CFM-GSFC simulates a loss of 1 mm. The greatest depletion in FAC is along the margins and especially along the western margin where observations and models show the formation of near-surface, low-permeability ice slabs that may inhibit meltwater storage.

Megan Thompson-Munson↗
NASA NTRSDate not supplied

Earth Radiation Budget Climate Record Composed of Multiple Satellite Observations

Effects of cloud diurnal cycle on top-of-atmosphere (TOA) and surface regional monthly mean irradiances, climatological mean, and anomalies are analyzed using CERES derived TOA irradiances and surface irradiances computed with MODIS derived cloud properties. Cloud properties derived from Terra and Aqua MODIS are sufficient to capture cloud diurnal cycle to compute regional monthly mean surface irradiances. While missing cloud diurnal cycle leads to a biased TOA and surface regional irradiances for regions with a strong cloud diurnal cycle, monthly regional TOA and surface anomalies derived from one sun-synchronous orbit agrees well with those derived from two sun-synchronous orbits. Based on these results, the algorithm to produce Edition 4.2 CERES EBAF product is developed. Regional TOA and surface climatological means derived from one sun-synchronous orbit are adjusted to match corresponding climatological means derived from Terra+Aqua observations. This climatological adjustment approach is used to merge the Terra only period to the Terra+Aqua period and to extend the Terra and Aqua record by merging NOAA20 observations. Two additional differences of Edition 4.2 EBAF algorithm to compute surface irradiances compared to the earlier version are: 1) no geostationary satellite derived cloud properties are used and 2) temperature and humidity from MERRA-2 instead of GEOIS-5.4.1 are used. Once surface monthly regional mean irradiances are compared with surface observations, the agreement is equivalent to the agreement with the earlier version. However, because surface irradiances are not affected by geostationary satellite artifacts, regional surface irradiance anomaly time series is significantly improved, especially for longwave irradiances.

Seiji Kato↗
NASA NTRSDate not supplied

Springtime SEA Air Is Consistently Both Smoky and Humid, but This Relationship (and Its Radiative Effects) Varies Spatially and Seasonally

The atmosphere over the southeast Atlantic Ocean (SEA) sees a consistent springtime biomass burning (BB) smoke from widespread agricultural fires on the African continent. This smoke layer is initially lofted high in a continental mixed layer (~5-6km) and is then transported westward in the free troposphere, where it overlies and ultimately mixes into the SEA stratocumulus-topped oceanic boundary layer. Coincident with this smoke is an elevated humidity signal which is present from the time a given airmass is over the continental source region. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) was a NASA Earth Venture Suborbital mission with the goal of measuring aerosol, cloud, and atmospheric properties over this region during three deployments in September 2016, August 2017, and October 2018. A previous study discussed the spatial characteristics of the water vapor-BB plume observations in the September 2016 flight data and their degree of agreement with several atmospheric reanalyses and models. In the present work, we first discuss atmospheric chemistry, structure, and aerosol results from all three ORACLES deployments to place these results in a broader seasonal context. Despite the differing locations and season of each deployment, we show that there continues to be good agreement between the airborne ORACLES dataset and large-scale reanalyses, specifically the ECMWF ERA5 and CAMS reanalyses. Other reanalyses (specifically NASA's MERRA-2) preserved the observed correlation between meteorology and biomass burning conditions, but, as was seen for 2016, was frequently displaced spatially relative to the observations. The CAMS reanalysis performs better with water vapor than with CO. Results comparing CAMS column AOD to the field measurements show slight overestimates, consistent with previous analysis, but the good relationship observed between AOD and inlet-based aerosol extinction demonstrates this metric's utility to broader studies. The good ERA5/CAMS/ORACLES agreement allows us to next examine the multi-year seasonal patterns and trends beyond the three ORACLES deployment periods. Looking at seven years of reanalysis data for the BB season, we find distinct variations between each month/deployment in terms of vertical smoke distribution and correlation to atmospheric specific humidity, due to changing conditions through the BB season. Using k-means clustering of these climatological reanalysis, we identify six canonical atmospheric profile types of varying total atmospheric humidity and vertical structure and describe their changing incidence spatially and throughout the season, and six analogous profile types for carbon monoxide, allowing us to characterize the atmospheric structure of both vapor and BB over time throughout the SEA region. This classification will allow for a more complete analysis of the broader radiative and dynamical effects of humid aerosols overlying stratocumulus clouds.

Kristina Marie Myers Pistone↗
NASA NTRS2022

Recent Trends in Transport of Surface Carbonaceous Aerosols to the Upper-Troposphere-Lower-Stratosphere Linked to Expansion of the Asian Summer Monsoon Anticyclone

Using MERRA-2 re-analyses, we have examined recent trends (2000-2019) in transport of surface carbonaceous aerosols (CA), i.e., organic carbon (OC) and black carbon (BC), to the upper troposphere (UT) and lower stratosphere (LS) during the Asian summer monsoon (ASM). We find a significant increased concentration of UTLS CA, linked to a linear trend in an expansion of the Asian Summer Monsoon Anticyclone (ASMA). Over core monsoon latitudes (25°-35°N), the trends in UTLS CA are enabled by increased upward transport from surface sources via an intensified monsoon meridional circulation, with increased latent heating over the southern Tibetan Plateau and foothill regions, enhanced by feedback processes associated with radiative heating by UTLS CA. In the extra-tropics, increased UTLS CA stems primarily from an extended source of increased wildfire emissions over eastern Siberia and northern Asia, coincident with a large-scale anomalous anticyclone with enhanced surface warming and drying near (80°-120°E, 55°-70°N). Here, carbonaceous aerosols are transported upward from the surface to the LS, likely by increased pyro-convection associated with enhanced wildfires, and enter the tropical UTLS via increased equator ward transport on the eastern flanks of anomalous upper-level anticyclones, coupled to the expanded ASMA. Overall, the increasing UTLS CA trends associated with expansion of the ASMA are consistent with a hydrostatic expansion of a warming troposphere, reflected in a rise in the tropical tropopause and consequential dynamical adjustments of the [ASM subtropical jetstream, modulating the climate of the greater ASM region.

interdecadal trends↗
NASA NTRS2023

Public Health Data Applications Using the CDC Tracking Network: Augmenting Environmental Hazard Information with Lower-latency NASA Data

Exposure to environmental hazards is an important determinant of health, and the frequency and severity of exposures is expected to be impacted by climate change. Through a partnership with the U.S. National Aeronautics and Space Administration, the U.S. Centers for Disease Control and Prevention’s National Environmental Public Health Tracking Network is integrating timely observations and model data of priority environmental hazards into its publicly accessible Data Explorer (https://ephtracking.cdc.gov/DataExplorer/). Newly integrated datasets over the contiguous U.S. (CONUS) include: daily 5-day forecasts of air quality based on the Goddard Earth Observing System Composition Forecast (GEOS-CF), daily historical (1980-present) concentrations of speciated PM2.5 based on the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), and Moderate Resolution Imaging Spectroradiometer (MODIS) daily near real-time maps of flooding (MCDWD). Data integrated into the CDC Tracking Network are broadly intended to improve community health through action by informing both research and early warning activities, including (1) describing temporal and spatial trends in disease and potential environmental exposures, (2) identifying populations most affected, (3) generating hypotheses about associations between health and environmental exposures, and (4) developing, guiding, and assessing environmental public health policies and interventions aimed at reducing or eliminating health outcomes associated with environmental factors.

air quality↗
NASA NTRS2023

Decadal Changes in the Antarctic Sea Ice Response to the Changing ENSO in the Last Four Decades

Sea ice fraction (SIF) over the Ross/Amundsen/Bellingshausen Sea (RAB) are investigated using the Modern-Era Retrospective Analysis for Research and Application, Version 2 (MERRA-2), focusing on the differences in time-lagged response to ENSO between the late 20th (1980–2000, L20) and the early 21st century (2001–2021, E21). The findings suggest that the typical Antarctic response to ENSO is influenced by changes in ENSO type/intensity, highlighting the need for caution when investigating the Antarctic teleconnection. Time-lagged regressions onto the mature phase of El Niño reveal that the SIF decrease and SST increase over the RAB is relatively weaker in E21 and most pronounced at 0–4 months lag. Conversely, the SIF in L20 continues to decline and reaches its peak at two-season lag (5–7 months). Tropospheric wind, pressure, and wave activity in response to El Niño in L20 show a zonally oriented high/low-pressure areas with two-season lag, enhancing the poleward flow that plays a key role in sea ice melt in the RAB, while this pattern in E21 is insignificant at the same lag. This study suggests that stronger (weaker) and more eastern (central) Pacific ENSOs on average in L20 (E21) are associated with this decadal change in the SIF response to ENSO.

Antarctic sea ice↗
NASA NTRSDate not supplied

Boundary Layer Data Assimilation and Interaction with Parameterizations in the NASA GEOS Model

The NASA Global Modeling and Assimilation Office develops the Goddard Earth Observing System (GEOS), which assimilates a wide range of observations to support medium range and seasonal forecasts and production of reanalyses like MERRA-2. In this talk we report on recent efforts to assimilate boundary layer (PBL) height observations derived from radiosondes, GNSS radio occultation, space-based lidar (CALIPSO, CATS, IceSat-2) and ground-based lidar (MPLNET). A novel component of this project includes examining the influence of model parameterizations on PBL profile estimates. We will discuss physics-based parameterizations of the PBL and how they may benefit or distort representation of PBL profiles in data assimilation. In particular, we consider the tendency of PBL parameterizations to compensate for analysis updates of state variables, effectively reducing the information retained from observations. We will present efforts to reduce this compensation in GEOS by using the PBL height analysis to adjust length scales used in the model PBL parameterizations.

Nathan P. Arnold↗
NASA NTRSDate not supplied

Regional Impacts of Ice Sheet Surface Representation Improvements in an Earth System Model

Ice sheet surface conditions and their subsequent impact on surface mass balance play an important role in ice sheet dynamics and ice sheet interaction with the overlying atmosphere and surrounding ocean. The NASA Global Modeling and Assimilation Office’s (GMAO) Goddard Earth Observing System (GEOS) ecosystem of models and reanalyses model ice sheet and glacier surface mass balance with a moderately complex snow and ice module, including prognostic surface albedo evolution, fractional snow cover, and snowpack hydrology and meltwater retention. With this configuration, Greenland near surface air temperatures and ice sheet melt are well represented in MERRA-2, GMAO’s current atmospheric reanalysis; however, the similarity to observations in some regions is due, in part, to compensating biases in surface energy budget. Recent improvements to GEOS’ cloud microphysics and longwave radiation parameterizations reduced biases in surface net longwave radiation and exacerbated surface net shortwave radiation biases, effectively increasing near surface temperatures and melting, particularly during the summer months. Here, we demonstrate the Earth system response to an improved representation of the ice sheet surface focused on minimizing the surface energy biases and increasing spatial and temporal representativeness. New changes to the surface albedo parameterization, including the introduction of a prognostic aerosol darkening scheme, help mitigate shortwave biases, while modifications to surface roughness characteristics improve near surface sensible heat fluxes. Focusing on the Arctic and Greenland, we examine the combined impact on these changes on regional weather conditions and ice sheet surface mass balance using a high resolution atmospheric only experiment, and we use a coupled model configuration to assess the impact on oceanic conditions and subseasonal-to-seasonal prediction. Overall, these improvements increase modeled ice sheet surface realism and provide a strong basis for more accurate ice sheet mass balance in GMAO’s future reanalyses and forecasting systems.

Lauren C. Andrews↗