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NASA NTRS2003

The Reanalysis for Stratospheric Trace Gas Studies

The "Reanalysis for Stratospheric Trace Gas Studies" (ReSTS) project intends to provide a state-of-the-art meteorological dataset for use in chemistry-transport models (CTMs). The initial focus is on the period from May 1991 until April 1995, which encompasses the initial few years of observations from NASA's Upper Atmosphere Research Satellite (UARS) as well as the abrupt increase and slow decay of volcanic aerosol loading from Mount Pinatubo. The reanalysis is being performed using NASA's operational "GEOS-4" data assimilation system. The results presented in this paper will begin with an overview of the meteorology of the ReSTS period, validating the ReSTS data against independent analyses, followed by an evaluation of the system statistics (the "Observation minus Forecast" for different input data types). Some sensitivities to the assumptions made in the assimilation process will be presented, including aspects of the forecast model and the statistical model used in the observation-forecast merging. Aspects of trace-gas transport will be discussed, focussing on the on-line water vapor distribution (which is a quasi-inert trace gas in the stratosphere), off-line transport studies of ozone and selected long-lived species, as well as assimilated ozone. The results will be discussed in the context of transport studies and our ability to use reanalyzed datasets to examine long-term variations in the meteorology and composition of the middle atmosphere.

Pawson, Steven↗

NASA NTRS2022

An Evaluation of Biomass Burning Aerosol Mass, Extinction, and Size Distribution in Geos Using Observations From Camp2EX

Biomass burning aerosol impacts aspects of the atmosphere and Earth system through radiative forcing, serving as cloud condensation nuclei, and air quality. Despite its importance, the representation of biomass burning aerosol is not always accurate in numerical weather prediction and climate models or reanalysis products. Using observations collected as part of the Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) in August through October of 2019, aerosol concentration and optical properties are evaluated within the Goddard Earth Observing System (GEOS) and its underlying aerosol module, GOCART. In the operational configuration, GEOS assimilates aerosol optical depth observations at 550 nm to constrain aerosol fields. Particularly for biomass burning aerosol, without the assimilation of aerosol optical depth, aerosol extinction is underestimated compared to observations collected in the Philippines region during the CAMP2Ex campaign. The assimilation process adds excessive amounts of carbon to account for the underestimated extinction, resulting in positive biases in the mass of black and organic carbon, especially within the boundary layer, relative to in situ observations from the Langley Aerosol Research Group Experiment. Counteracting this, GEOS is deficient in sulphate and nitrate aerosol just above the boundary layer. Aside from aerosol mass, extinction within GEOS is a function of ambient relative humidity and an assumed particle size distribution. The relationship between dry and ambient extinction in GEOS reveals that hygroscopic growth is too aggressive within the model for biomass burning aerosol. An additional concern lies in the assumed particle size distribution for GEOS, which has a mode radius that is too small for organic carbon. Variability in the observed particle size distribution for biomass burning aerosol within a single flight also illuminates the fact that a single assumed particle size distribution is not sufficient and that for a proper representation, a more advanced aerosol module with GEOS may be necessary.

Aerosol Mass↗

NASA NTRSDate not supplied

Evaluation of GEOS Aerosols Using CAMP2Ex Observations

Biomass burning aerosol impacts aspects of the atmosphere and Earth system through direct and semi-direct effects, as well as influencing air quality. Despite its importance, the representation of biomass burning aerosol is not always accurate in numerical weather prediction and climate models or reanalysis products. Using observations collected as part of the Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) in August through October of 2019, aerosol concentration and optical properties are evaluated within the Goddard Earth Observing System (GEOS) and its underlying aerosol module, GOCART. In the operational configuration, GEOS assimilates aerosol optical depth observations at 550 nm from AERONET and MODIS to constrain aerosol fields. Particularly for biomass burning aerosol, without the assimilation of aerosol optical depth, aerosol extinction is underestimated compared to observations collected in the Philippines region during the CAMP2Ex campaign. The assimilation process adds excessive amounts of carbon to account for the underestimated extinction, resulting in positive biases in the mass of black and organic carbon, especially within the boundary layer, relative to in situ observations from the Langley Aerosol Research Group Experiment. Counteracting this, GEOS is deficient in sulfate and nitrate aerosol just above the boundary layer. Aerosol extinction within GEOS is a function of the mass of different aerosol species, the ambient relative humidity, the assumed spectral optical properties, and particle size distribution per species. The relationship between dry and ambient extinction in GEOS reveals that hygroscopic growth is too high within the model for biomass burning aerosol. An additional concern lies in the assumed particle size distribution for GEOS, which has a single mode radius that is too small for organic carbon. Variability in the observed particle size distribution for biomass burning aerosol within a single flight also illuminates the fact that a single assumed particle size distribution is not sufficient and that for a proper representation, a more advanced aerosol module within GEOS may be necessary.

Allison Collow↗

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 NTRS2017

Optimal A-Train Data Utilization: A Use Case of Aura OMI L2G and MERRA-2 Aerosol Products

Ozone Monitoring Instrument (OMI) aboard NASA's Aura mission measures ozone column and profile, aerosols, clouds, surface UV irradiance, and the trace gases including NO2, SO2, HCHO, BrO, and OClO using UltraViolet electromagnetic spectrum (280 - 400 nm) with a daily global coverage and a pixel spatial resolution of 13 km × 24 km at nadir, and it's been one of the key instruments to study the Earth's atmospheric composition and chemistry. The second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) is NASA's atmospheric reanalysis using an upgraded version of Goddard Earth Observing System Model, version 5 (GEOS-5) data assimilation system. Compared to its predecessor MERRA, MERRA-2 is enhanced with more aspects of the Earth system among which is aerosol assimilation. When comparing between satellite pixel measurements and modeled grid data, how to properly handle counterpart pairing is critical considering their spatial and temporal variations. The comparison between satellite and model data by simply using Level 3 (L3) products may result biases due to lack of detailed temporal information. It has been preferred to inter-compare or implement satellite derived physical quantity (i.e., Level 2 (L2) Swath type) directly with/to model measurements with higher temporal and spatial resolution as possible. However, this has posed a challenge in the community to handle. Rather than directly handling the L2 or L3 data, there is a Level 2G (L2G) product conserving L2 pixel scientific data quality but in Grid type with the global coverage. In this presentation, we would like to demonstrate the optimal utilization of OMI L2G daily aerosol products by comparing with MERRA-2 hourly aerosol simulations matched well in both space and time.

MERRA-2 reanalysis↗

NASA NTRSDate not supplied

Applied Uses of MERRA Reanalyses: Current and Future Prospects

During the initial planning of the Modern Era Retrospective-analysis for Research and Applications (MERRA), the project was envisioned to become a tool for applied sciences and decision makers, as well as weather and climate research. MERRA was the first reanalysis to provide data at 1 hourly frequencies. After discussions with wind energy users, 50m above the surface winds were included in the data collection to begin to represent the environment at the turbine height. MERRA-2 was the first reanalysis to include interactive and assimilated aerosols. From these, PM 1, 2.5 and 10 records have been computed and contribute to the climate and health sector. The US Center for Disease Control is accessing MERRA-2 data for comparison along with their health data. MERRA-2 Extreme Indices have been computed from the high frequency data (e.g. precipitation maxima, heat waves and fire weather). These have been used to characterize the changing extremes in the United States and around the globe as well as the weather associated with the extremes. The next-generation, MERRA-21C, includes increased resolution (25km) and continues to provide innovative Earth system data. For example, a boundary layer collection will provide constant height level data starting at 100m, continuing up to 4000m. This will provide detailed information about the boundary layer processes that greatly affect the biosphere. Chemical tracers for constituents are included in the system. The ensemble data assimilation is run with 32 members, and the variance for critical variables are stored. We will explore the use of this variance as one measure of uncertainty relevant for applied uses, which has not been included in any MERRA reanalysis. We will discuss use case scenarios developed to engage with the energy and financial sectors, to better understand their needs for climate data. Prospects for further downscaling of reanalyses will also be explored.

Michael Bosilovich↗

NASA NTRSDate not supplied

Distribution and Sources of Tropospheric Aerosols Over the Western North Atlantic During ACTIVATE (February-March 2020)

The Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) is a five-year (2019-2023) NASA Earth-Venture Suborbital-3 (EVS-3) mission to robustly characterize aerosol-cloud-meteorology interactions during February-June, with a focus on marine boundary layer clouds. This characterization requires understanding of aerosol composition, distribution, transport pathways, and sources. Here we use the GEOS-Chem chemical transport model driven by the MERRA-2 reanalysis to simulate tropospheric carbon monoxide (CO) and aerosols over the western North Atlantic Ocean (WNAO) during the first field deployment of ACTIVATE (February-March 2020). CO is used as a tracer to diagnose transport pathways for continental pollution outflow to the WNAO. The aerosol simulation represents all major aerosols including sulfate-nitrate-ammonium (SNA), mineral dust, sea salt, black and organic carbon aerosols. Model-simulated mixing ratios of SNA and organic carbon are compared with aircraft observations. We show that intensive aerosol mass measurements in the lower troposphere over the North American outflow region during ACTIVATE provide strong constraints on model aerosol wet scavenging. Comparisons of model aerosol extinctions with the airborne High Spectral Resolution Lidar-2 (HSRL-2) measurements indicate that the model generally captures continental outflow of aerosols and enhanced extinctions associated with sea salt. Simulated aerosol optical depths (AODs) and extinction vertical profiles are also compared with satellite retrievals from MODIS/Aqua and CALIOP/CALIPSO, respectively. CALIOP sometimes observes enhanced aerosol extinction at altitudes between ~1.5km and ~2.0km south of 32°N. The model reproduces this enhancement and attributes it to coarse-mode sea salt associated with high relative humidity. The relative contributions of continental and oceanic sources to the aerosol loading, AOD, and their distributions over the study domain will also be discussed.

aerosols↗

DOE OSTI2025

Regime-based aerosol–cloud interactions from CALIPSO-MODIS and the Energy Exascale Earth System Model version 2 (E3SMv2) over the Eastern North Atlantic

This study investigates aerosol-cloud interactions in marine boundary layer (MBL) clouds using an advanced deep-learning-driven synoptic-regime-based framework, combining satellite data (CALIPSO vertically resolved aerosol extinction and MODIS cloud properties) with 1° nudged Energy Exascale Earth System Model version 2 (E3SMv2) simulation over the Eastern North Atlantic (ENA; ∼10°×10°, 2006–2014). The E3SMv2 captures observed seasonal variations in cloud droplet number concentrations (N d ) and liquid water path (LWP), though it systematically underestimates N d . We then partition ENA meteorology into four synoptic regimes (Pre-Trough, Post-Trough, Ridge, Trough) via a deep-learning clustering of ERA5 reanalysis fields, enabling regime-dependent aerosol-cloud interactions analyses. Both satellite and E3SMv2 exhibit an inverted-V LWP-N d relationship. In Post-Trough and Ridge regimes, the satellite shows stronger negative LWP-N d sensitivities than in Pre-Trough regime. The Trough regime displays a muted satellite LWP response. In comparison, the model predicts more exaggerated LWP responses across regimes, with LWP increasing too quickly at low N d and decreasing more sharply at high N d , especially in Pre-Trough and Trough regimes. These exaggerated model LWP sensitivities may stem from uncertainties in representing drizzle processes, entrainment, and turbulent mixing. As for N d susceptibility to aerosols, N d increases with MBL aerosol extinction in both datasets, but the simulated aerosol-cloud interactions appear oversensitive to meteorological conditions. Overall, E3SMv2 better captures aerosol effects under regimes that favor stratiform clouds (Post-Trough, Ridge), but performance deteriorates for regimes with deeper, dynamically complex clouds (Trough), highlighting the need for improved representations of those cloud processes in climate models.

Environmental sciences↗

NASA NTRSDate not supplied

Simulation of the Aerosol Size Distribution Using a Neural Network Surrogate for the Modal Aerosol Module (MAM7)

One objective of atmospheric simulations is to quantify the distribution of aerosols and their properties. Accurate parameterizations of the processes governing aerosol mass, particle number, and particle size distribution are important for predicting the Earth’s net radiative balance and aerosol-cloud interactions. The Modal Aerosol Module (MAM7) is a two-moment aerosol model that simulates mass, number, and size distribution of seven modes comprised of internally mixed aerosol species. The two-moment scheme adds significant computational expense but allows for the prediction of varying particle size distribution relative to the bulk method which predicts only total mass. In this work, we developed a neural network surrogate model for MAM7 (MAMnet) to predict the aerosol number concentration in NASA’s Global Earth Observing System (GEOS) without adding prohibitive computational expense. MAMnet, can be driven by output from a single moment, mass-based, aerosol scheme (Goddard Chemistry Aerosol and Radiation model (GOCART)) or from reanalysis products (Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2)). MAMnet was trained using number concentrations from a 5-year GEOS/MAM7 simulation at 1-degree horizontal resolution and using the total mass calculated across modes as inputs, as well as temperature and air density. The model architecture for MAMnet was based on AlexNet, the 2012 winner of the ImageNet Large Scale Visual Recognition Challenge. While some modifications were necessary to accommodate our problem, important aspects of the network were preserved. MAMnet was able to reproduce zonal dynamics and spatial distributions of the aerosol number concentration however predictability in the upper troposphere was poor.

Katherine H Breen↗

NASA NTRS2007

Version 2.0 AERONET Dust Aerosol properties, Constraints and Application to Asian Dust Observations

In November 2006, AERONET released Version 2 of the Dubovik and King sky radiance and optical depth inversion. Reanalysis of the entire AERONET database revealed marked differences in aerosol properties in arid and semi arid regions with dust dominated aerosols. The change will be illustrated through sensitivity analysis and examples from the UAE2 (United Arab Emirates Unified Aerosol Experiment) field campaign. Properties of dust dominated aerosols will be presented from regional AERONET sites in China showing variations in dust aerosol properties. The constraints and limitations of the AERONET inversion will be presented that will facilitate analysis by the user community of these data.

Holben, Brent↗

NASA NTRS2021

Precipitable water vapor over oceans from the Maritime Aerosol Network: Evaluation of global models and satellite products under clear sky conditions

We present results from an evaluation of precipitable water vapor (W) over remote oceanic areas as derived from global reanalysis models and from satellites against observations from the Maritime Aerosol Network (MAN) for cloudless skies during the period of 2004–2017. They cover polar, mid latitude and tropical oceanic regions and represent a first effort to use MAN observations for such evaluation. The global reanalysis model products evaluated in this study are from the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2), the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA I), and the Climate Forecast System Reanalysis (CFSR) model. The satellite products evaluated are from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Polarization and Directionality of the Earth's Reflectances (POLDER), the Global Ozone Monitoring Experiment (GOME-2), the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and the Atmospheric Infra-red Sounder (AIRS). Satellite retrievals of W are based on the attenuation of solar reflected light by water vapor absorption bands, except those from AIRS that rely on brightness temperature measurements. A very good agreement is observed between the model estimates and MAN, with mean differences of ~5% and standard deviations of ~15%. These results are within the uncertainties associated with the models and the measurements, indicating the skill of the reanalysis models to estimate W over oceans under clear sky conditions. Mean differences of W between the satellite and MAN products are ~11, 6.7, 12, −7, and 3% for MODIS, POLDER, GOME-2, SCIAMACHY and AIRS respectively, while their standard deviations are 31, 29, 28, 20 and 17%. These differences reveal the need to address inconsistencies among different satellite sensors and ground-based measurements to reduce the uncertainties associated with the retrievals.

Daniel Pérez-Ramírez↗

NASA NTRSDate not supplied

Uncertainty in Observational Estimates of the Aerosol Direct Radiative Effect and Forcing

Aerosols continue to be responsible for the largest uncertainty in determining the anthropogenic radiative forcing of the climate. To both reconcile the large range in satellite-based estimates of the aerosol direct radiative effect (DRE, the direct interaction with solar radiation by all aerosols) and to optimize the design of future observing systems, we build a framework for assessing uncertainty in aerosol DRE and the aerosol direct radiative forcing (DRF, the radiative effect of just anthropogenic aerosols, RF_ari). Shortwave aerosol radiative kernels (Jacobians) were derived using the MERRA-2 reanalysis data. These radiative kernels are used to compute a lower-bound on the systematic uncertainty in observational estimates of the aerosol DRE/DRF by making the optimistic assumption that global aerosol observations can be made with the accuracy found in the Aerosol Robotic Network (AERONET) sun photometer retrievals. The total uncertainty is shown to be dominated by contributions from the aerosol single scattering albedo uncertainty. These uncertainty estimates were compared to a literature survey of mostly satellite-based aerosol DRE/DRF values. Comparisons to previous studies reveal that most have significantly underestimated the aerosol DRE uncertainty. Past estimates of the aerosol DRF uncertainty are smaller (on average) than our optimistic observational estimates, including the aerosol DRF uncertainty given in the Intergovernmental Panel on Climate Change (IPCC) fifth assessment report (AR5).

Tyler James Thorsen↗

NASA NTRSDate not supplied

Uncertainty in Observational Estimates of the Aerosol Direct Radiative Effect and Forcing

Tyler James Thorsen↗

NASA NTRS2021

Effect of volcanic emissions on clouds during the 2008 and 2018 Kilauea degassing events

Volcanic eruptions in otherwise clean environments are “natural experiments” wherein the effects of aerosol emissions on clouds and climate can be partitioned from meteorological variability and anthropogenic activities. In this work, we combined satellite retrievals, reanalysis products, and atmospheric modeling to analyze the mechanisms of aerosol–cloud interactions during two degassing events at the Kilauea volcano in 2008 and 2018. The eruptive nature of the 2008 and 2018 degassing events was distinct from long-term volcanic activity for Kilauea. Although previous studies assessed the modulation of cloud properties from the 2008 event, this is the first time such an analysis has been reported for the 2018 event and that multiple degassing events have been analyzed and compared at this location. Both events resulted in significant changes in cloud effective radius and cloud droplet number concentration that were decoupled from local meteorology and in line with an enhanced cloud albedo. However, it is likely that the effects of volcanic emissions on liquid water path and cloud fraction were largely offset by meteorological variability. Comparison of cloud anomalies between the two events suggested a threshold response of aerosol–cloud interactions to overcome meteorological effects, largely controlled by aerosol loading. In both events, the ingestion of aerosols within convective parcels enhanced the detrainment of condensate in the upper troposphere, resulting in deeper clouds than observed under pristine conditions. Accounting for ice nucleation on ash particles led to enhanced ice crystal concentrations at cirrus levels and a slight decrease in ice water content, improving the correlation of the model results with the satellite retrievals. Overall, aerosol loading, plume characteristics, and meteorology contributed to changes in cloud properties during the Kilauea degassing events.

Katherine H. Breen↗

DOE OSTI2025

Variability of Eastern North Atlantic Summertime Marine Boundary Layer Clouds and Aerosols Across Different Synoptic Regimes Identified With Multiple Conditions

Abstract This study estimates the meteorological covariations of aerosol and marine boundary layer (MBL) cloud properties in the eastern North Atlantic (ENA) region, characterized by diverse synoptic conditions. Using a deep‐learning‐based clustering model with mid‐level and surface daily meteorological data, we identify seven distinct synoptic regimes during the summer from 2016 to 2021. Our analysis, incorporating reanalysis data and satellite retrievals, shows that surface aerosols and MBL clouds exhibit clear regime‐dependent characteristics, whereas lower tropospheric aerosols do not. This discrepancy likely arises from synoptic regimes determined by daily large‐scale conditions, which may overlook air mass histories that predominantly dictate lower tropospheric aerosol conditions. Focusing on three regimes dominated by northerly winds, we analyze the Atmospheric Radiation Measurement Program (ARM) ENA observations on Graciosa Island in the Azores. In the subtropical anticyclone regime, fewer cumulus clouds and more single‐layer stratocumulus clouds with light drizzle are observed, along with the highest cloud droplet number concentration (Nd), surface cloud condensation nuclei (CCN) and surface aerosol levels. The post‐trough regime features more broken or multi‐layer stratocumulus clouds with slightly higher surface rain rate, and lower Nd and surface CCN levels. The weak trough regime is characterized by the deepest MBL clouds, primarily cumulus and broken stratocumulus clouds, with the strongest surface rain rate and the lowest Nd, surface CCN and surface aerosol levels, indicating strong wet scavenging. These findings highlight the importance of considering the covariation of cloud and aerosol properties driven by large‐scale regimes when assessing aerosol indirect effects using observations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2010

The Sensitivity of Simulated Ocean Biogeochemistry to Forcing Fields Derived from NCEP and MERRA Reanalysis Products

Ocean biogeochemistry models are typically forced by atmospheric and oceanic data derived from reanalysis products. For the NASA Ocean Biogeochemistry Model (NOBM) such reanalysis forcing fields include: surface wind stress, sea surface temperature, ice distributions, shortwave radiation, surface wind speeds and surface atmospheric pressure. Additionally, proper computation of ocean irradiance requires reanalysis products of relative humidity and precipitable water (in addition to aerosol and cloud information which is derived from satellite data). The question posed here is, does the choice of reanalysis products make a difference in the representation of ocean biology and biogeochemistry? NOBM was forced by NCEP and MERRA reanalysis products for the period 2002-2009. We find that in 2009 global distributions and abundances of biological variables (total chlorophyll and nutrients) and carbon (dissolved inorganic and organic carbon and surface pCO2) were similar between the two different forcing fields. Global statistical comparisons with satellite and in situ data also showed negligible differences.

Gregg, Watson↗

DOE OSTI2025

Intensifying heat extremes in China attributed to rising greenhouse gases and declining aerosols since the 2010s

Rising temperatures have increased the frequency, duration, and intensity of extreme temperature events over China in recent decades. The upward trends in heat extremes in China in the warm season (May–September) and their relationships with changes in aerosols and greenhouse gases are investigated using observations, reanalysis data and model results. Significant increasing trends in China are observed in daily maximum temperatures (TXx), heatwave frequency, and heatwave mean duration during 2011–2023, with increasing rates of 0.70 °C/decade, 3.77 d/decade and 0.31 d/event/decade, respectively. This study shows that 43 ± 3% of the TXx increases in China are attributed to the rising CO2 concentrations. Aerosol optical depth in China decreased at a rate of 0.054 per decade from 2011 to 2023 due to significant air quality improvements. The weakened aerosol cooling effect due to declining aerosols contributes 27 ± 3% to the observed TXx trend. In eastern China, where aerosol reductions were most significant, aerosol reduction even accounts for 79 ± 10% of the TXx increasing trend. The intensifying heat waves attributed to GHGs and aerosols are in accordance with the increasing extreme high temperatures. The results highlight the significant impacts of rising GHGs and decreasing aerosols on heat extreme events over China in recent years, emphasizing the need of considering both GHGs and aerosols to address the issue of intensification of heat extremes in a warming future.

Zou, Aili↗

NASA NTRS2017

Aerosol EnKF at GMAO

In the GEOS near real-time system, as well as in MERRA-2 which is the latest reanalysis produced at NASAs Global Modeling and Assimilation Office(GMAO), the assimilation of aerosol observations is performed by means of a so-called analysis splitting method. In line with the transition of the GEOS meteorological data assimilation system to a hybrid Ensemble-Variational formulation, we are updating the aerosol component of our assimilation system to an ensemble square root filter(EnSRF; Whitaker and Hamill (2002)) type of scheme.We present a summary of our preliminary results of the assimilation of column integrated aerosol observations (Aerosol Optical Depth; AOD) using an Ensemble Square Root Filters (EnSRF) scheme and the ensemble members produced routinely by the meteorological assimilation.

MERRA-2 EnSRF↗