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NASA NTRSDate not supplied

Disruption of the 2022-2023 stratospheric circulation by the Hunga Tonga-Hunga Ha'apai volcano

In January 2022 the Hunga Tonga-Hunga Ha'apai (HTHH) volcano erupted, injecting an unprecedented amount of water vapor into the stratosphere that increased the total stratospheric water burden by ~10%. As the initial plume of water vapor spread throughout the stratosphere, radiative heating and cooling anomalies affected the stratospheric circulation altering the climatological mean residual circulation. Here we compare the 1980-2021 MERRA-2 (Modern Era Reanalysis for Research and Applications, Version 2) mean residual circulation climatology to the years 2022-2023 to identify stratospheric circulation changes associated with the anomalous water vapor. The HTHH water vapor is explicitly tracked using the M2-SCREAM (MERRA-2 Stratospheric Composition Reanalysis of Aura Microwave Limb Sounder) water vapor analysis. Anomalies in temperature, jet location, polar vortex strength and ozone advection in response to the HTHH water vapor anomaly are also documented. These results reveal details of the evolution of the HTHH induced stratospheric circulation anomalies with special emphasis on how these circulation anomalies affected the 2023 ozone hole.

Lawrence Coy↗
NASA NTRSDate not supplied

Disruption of the 2022-2023 Stratospheric Circulation By the Hunga Tonga-Hunga Ha'apai Volcano

In January 2022 the Hunga Tonga-Hunga Ha'apai (HTHH) volcano erupted, injecting an unprecedented amount of water vapor into the stratosphere that increased the total stratospheric water burden by ~10%. As the initial plume of water vapor spread throughout the stratosphere, radiative heating and cooling anomalies affected the stratospheric circulation altering the climatological mean residual circulation. Here we compare the 1980-2021 MERRA-2 (Modern Era Reanalysis for Research and Applications, Version 2) mean residual circulation climatology to the years 2022-2023 to identify stratospheric circulation changes associated with the anomalous water vapor. The HTHH water vapor is explicitly tracked using the M2-SCREAM (MERRA-2 Stratospheric Composition Reanalysis of Aura Microwave Limb Sounder) water vapor analysis. Anomalies in temperature, jet location, polar vortex strength and ozone advection in response to the HTHH water vapor anomaly are also documented. These results reveal details of the evolution of the HTHH induced stratospheric circulation anomalies with special emphasis on how these circulation anomalies affected the 2023 ozone hole.

Lawrence Coy↗
NASA NTRSDate not supplied

Improving Ocean Reanalyses and ENSO Forecasts By Assimilation of Rain-Corrected Satellite Sea Surface Salinity Using the GMOA S2s Forecast System

The ENSO phenomenon has a significant global socio-economic impact and has been the key focus for improving coupled ocean-atmosphere forecasts. Assimilation of satellite altimetry and subsurface temperature and salinity from (mostly) Argo help improve the initialization of the thermocline, while satellite SST aids in constraining surface heat-fluxes, leading to improved coupled system sub-seasonal to seasonal forecasts. However, few studies have focused on improving the near-surface density and mixing through satellite sea surface salinity (SSS) assimilation. The few ocean models that assimilate satellite SSS, bias correct to normalize towards the near-surface Argo data for expediency. This assumption is likely inadequate in rainy regions, where buoyant water forms a fresh surface lens. In previous work, we showed that adjusting SSS to bulk salinity (Sb) using the Rain Impact Model (RIM) of Santos-Garcia et al., 2014 improves the near-surface density and mixed layer depth, leading to deeper thermocline and improved NINO3.4 SST forecasts. We now utilize the Soil Moisture and Ocean Salinity rain-corrected (SMOS_RC) SSS, available in SMOS-CATDS products, to represent Sb more accurately at the first model layer (e.g., 5 m). Rather than a diffusivity model as RIM, SMOS_RC uses a statistical correction dependent on Integrated Multi-satellitE Retrievals for GPM (IMERG) rain rates, established on observed SMOS SSS decreases related to Sb in the presence of rain (Supply et al., 2020). For all experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF scheme (Penny et al., 2013). One reanalysis additionally assimilates SMOS SSS data as is, and a separate reanalysis assimilates SMOS_RC. We assess the impact on near-surface and subsurface dynamics by validating against observations and explore how SSS assimilation (SMOS vs SMOS_RC) impacts ENSO forecasts using the NASA GMAO Sub-seasonal to Seasonal coupled forecast system (S2S-v3, Molod et al. 2020). We show that improved estimates of density and near-surface mixing led to more accurate coupled air/sea interaction and better ENSO forecasts. The increased SSS, resulting from the removal of the instantaneous rain effect, modifies the ocean state by enhancing mixing and deepening the thermocline.

Veronica Ruiz Xomchuk↗
NASA NTRSDate not supplied

Relationships Between Variability in the Stratospheric Polar Vortex, Upper Tropospheric Jets, Tropopauses, and UTLS Ozone

The impacts of stratospheric polar vortex variations on upper troposphere / lower stratosphere (UTLS) circulation and composition are not well understood. We use stratospheric polar vortex geometry / strength diagnostics combined with characterisation of tropopauses and UTLS jets to show links between stratospheric polar vortex variability and regional variations in UTLS jet and tropopause characteristics. Polar vortex diagnostics are from Characterization and Analysis of Vortex Evolution using Algorithms for Region Tracking (CAVE-ART), while UTLS diagnostics are from JEt and Tropopause Products for Analysis and Characterization (JETPAC). We will present results showing UTLS jet and tropopause characteristics for strong and weak stratospheric vortex states (defined using vortex-focused metrics that are less dependent on geometry and position than commonly used diagnostics), as well as regional variations in correlations between CAVE-ART and JETPAC diagnostics. Furthermore, we will focus on preliminary results extending the stratospheric vortex, UTLS jet, and tropopause relationships to assess their impacts on regional ozone variations diagnosed from the M2-SCREAM (MERRA-2 Stratospheric Composition Reanalysis of Aura Microwave Limb Sounder) composition reanalysis.

Gloria Manney↗
NASA NTRSDate not supplied

Satellite Data Assimilation in the GEOS Atmospheric Data Assimilation System

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

Jianjun Jin↗
NASA NTRSDate not supplied

Evaluation of Regional Water and Energy Balance in Contemporary Reanalyses

Regional to continental water and energy balance in reanalyses provide crucial information on the climate and climate variations in that region and can contrast other regions. Reanalyses are a valuable tool in piecing together the complete balance owing to the incorporation of the budgets in the background model and the assimilation of observation. On the other hand, the background model has its own biases and observational assimilation can lead to non-negligible tendencies within the budgets, and these can vary over space and time. Here, we will compare the balance within several reanalyses and how they have evolved over recent decades. Several observational data products will provide reference points in the comparison. In addition, a recent project has integrated observations of the water and energy budgets in an optimization that aims to reduce the imbalance of regional budgets in using observational terms from disparate sources. In evaluating the regional balances, we will incorporate, when available, the water and energy convergence terms as well as their analysis increments (which may be diagnosed as residuals). The reanalyses considered here include: Japanese Reanalyses for Three Quarters Century (JRA3Q), ECMWF Reanalysis version 5 (ERA5), Modern Era Retrospective-analysis for Research and Applications version 2 (MERRA-2) and the NCEP Reanalysis II (NCEPR2). NCEPR2 is representative of the late 90s technology, while the others represent the contemporary climate reanalyses presently available. We will discuss the regional balances over key river basins (e.g. Mississippi and Amazon), and a range of continents including those well observed (North America and Europe) and those with fewer consistent observations (e.g. Africa). These contrasting regions show the degree of advancement in reanalyses and expose areas in need of improvement. The results also demonstrate the usefulness of producing complete atmospheric water and energy budgets as part of the diagnostic output.

Michael G Bosilovich↗
NASA NTRS2023

Impact of Design Factors for ESA CCI Satellite Soil Moisture Data Assimilation over Europe

In this study, soil moisture retrievals of the combined active–passive ESA Climate Change Initiative (CCI) soil moisture product are assimilated into the Noah-MP land surface model over Europe using a one-dimensional ensemble Kalman filter and an 18-yr study period. The performance of the data assimilation (DA) system is evaluated by comparing it with a model-only experiment (at in situ sites) and by assessing statistics of innovations and increments as DA diagnostics (over the entire domain). For both assessments, we explore the impact of three design choices, resulting in the following insights. 1) The magnitude of the assumed observation errors strongly affects the skill improvements evaluated against in situ stations and internal diagnostics. 2) Choosing between climatological or monthly cumulative distribution function matching as the observation bias correction method only has a marginal effect on the in situ skill of the DA system. However, the internal diagnostics suggest a more robust system parameterization if the observations are rescaled monthly. 3) The choice of atmospheric reanalysis dataset to force the land surface model affects the model-only skill and the DA skill improvements. The model-only skill is higher with input from the MERRA-2 than with input from the ERA5 reanalysis, resulting in larger DA skill improvements for the latter. Additionally, we show that the added value of the DA strongly depends on the quality of the satellite retrievals and land cover, with the most substantial soil moisture skill improvements occurring over croplands and skill degradation occurring over densely forested areas.

Soil moisture↗
NASA NTRSDate not supplied

A Long-Term GOES Satellite Overshooting Cloud Top and Anvil Cloud Climatology Over South America

The modern-era GOES satellite series began in 1994 with the GOES-8 satellite, and was augmented in 2018 with higher spatial resolution and more frequent imaging when GOES-16 became operational. GOES imagery has provided forecasters and researchers new perspectives into cloud top patterns associated with severe convection, and the ability to better forecast convection in regions without adequate ground-based weather radar coverage. While much attention has been given to convection over North America, convection over South America can be equally, if not more, intense and frequent. Recent studies have demonstrated that overshooting cloud tops (OT) and surrounding anvil clouds can be detected within infrared satellite imagery. Relative storm updraft intensity metrics such as the tropopause-relative infrared brightness temperature, the prominence of an OT relative to its surrounding anvil, and cloud top height can also be derived using automated methods combined with reanalysis data. These automated OT detection and intensity estimation methods have recently been applied to all GOES images collected over South America, in combination with the MERRA-2 reanalysis, from 1995 to 2022 at NASA Langley within a project supported by the NASA Applied Sciences Disasters program. Innovative aggregation methods have merged these products into daily, monthly, annual, and multi-annual composites, with hourly time bins, at ~4 km pixel spacing to enable researchers a new opportunity to study South American convective processes throughout the diurnal cycle. These products have recently become publicly available from NASA. This presentation will overview this new dataset, and novel insights into South American convection depicted by the data.

Kristopher Bedka↗
NASA NTRSDate not supplied

The Representation of Aerosols in GMAO’s Newest Reanalyses

Over the past few years, NASA’s Global Modelling and Assimilation Office has been working on the configuration and production of three new reanalysis products, GEOS-IT, GiOcean, and MERRA-21C. GEOS-IT, or the Goddard Earth Observing System for Instrument Teams, is a 3D variational data assimilation system that runs in a near real time framework however retrospectively provides data back through 1998 to deliver a consistent view of the Earth-atmosphere system for the production of observational NASA products. Retrospective production for GEOS-IT is complete and the meteorology has since been used to produce the one way weakly coupled GiOcean reanalysis. Due to differences in the atmospheric model, particularly related to scavenging, aerosols are not identical in GEOS-IT and GiOcean. MERRA-21C, or the Modern Era Restrospective analysis for Research and Applications in the 21st century, is a hybrid 4D ensemble variational system at a finer horizontal resolution of 0.25 degrees. Although different in their intended use, and therefore configuration, these systems prominently feature coupling between meteorology and aerosols. The differences and similarities in the aerosol configuration between the three systems will be discussed, covering biomass burning and anthropogenic emissions as well as observations used for the assimilation of aerosol optical depth. A large emphasis will be placed on the version of the underlying aerosol module, GOCART, which underwent a complete refactoring and the addition of radiatively active brown carbon between GEOS-IT and MERRA-21C. Independent observations will be used to evaluate the performance of aerosols in both reanalyses, focusing on aerosol optical depth, surface particulate matter, and vertical profiles of aerosol backscatter.

Allison Collow↗
NASA NTRSDate not supplied

Evaluation of Regional Water and Energy Balance in Contemporary Reanalyses

Regional to continental water and energy balance in reanalyses provide crucial information on the climate and climate variations in that region and can contrast other regions. Reanalyses are a valuable tool in piecing together the complete balance owing to the incorporation of the budgets in the background model and the assimilation of observation. On the other hand, the background model has its own biases and observational assimilation can lead to non-negligible tendencies within the budgets, and these can vary over space and time. Here, we will compare the balance within several reanalyses and how they have evolved over recent decades. Several observational data products will provide reference points in the comparison. In addition, a recent project has integrated observations of the water and energy budgets in an optimization that aims to reduce the imbalance of regional budgets in using observational terms from disparate sources. In evaluating the regional balances, we will incorporate, when available, the water and energy convergence terms as well as their analysis increments (which may be diagnosed as residuals). The reanalyses considered here include: Japanese Reanalyses for Three Quarters Century (JRA3Q), ECMWF Reanalysis version 5 (ERA5), Modern Era Retrospective-analysis for Research and Applications version 2 (MERRA-2) and the NCEP Reanalysis II (NCEPR2). NCEPR2 is representative of the late 90s technology, while the others represent the contemporary climate reanalyses presently available. We will discuss the regional balances over key river basins (e.g. Mississippi and Amazon), and a range of continents including those well observed (North America and Europe) and those with fewer consistent observations (e.g. Africa). These contrasting regions show the degree of advancement in reanalyses and expose areas in need of improvement. The results also demonstrate the usefulness of producing complete atmospheric water and energy budgets as part of the diagnostic output.

Michael Bosilovich↗
NASA NTRSDate not supplied

Global Ocean Mass Change Derived From Atmospheric Reanalyses

Barystatic sea level change is a significant climate variable and a gauge for water exchanges between land, atmosphere, and ocean, with consequential relevance to stakeholders. The monitoring and attribution of globally averaged sea level variations represents substantial challenges to the climate community. Atmospheric reanalyses provide a level of monitoring for elements of the climate system that are in communication with the ocean, including the atmosphere, terrestrial land, and the surfaces of glaciated land. Global atmospheric reanalyses comprise model output that is statistically adjusted to available observations. Potentially, reanalyses offer a climatic context to observed changes in water mass distribution. Improvement in the representation of the water cycle and in water mass conservation have been stated goals of reanalysis projects. Here, we assess the capability of atmospheric reanalyses to represent variations in the global water budget from the perspective of ocean mass balance. The purpose of this work is to provide a detailed evaluation of current atmospheric reanalyses and their ability to reproduce spatial and temporal variations in atmospheric and terrestrial water storage. A second goal is to identify and characterize recent apparent trends in the water balance. We examine the ERA5, MERRA-2, and JRA-3Q reanalyses with a focus on the radio-occultation observing period from 2007 to the present. For terrestrial water storage we also compare with ERA5-Land, a surface reanalysis. The primary validation is from the NASA/DLR Gravity Recovery and Climate Experiment (GRACE) and its follow-on, GRACE-FO. The Atmospheric Infrared Sounder (AIRS) onboard NASA's Aqua satellite is also used for evaluation of the atmospheric moisture budget. Comparisons reveal strengths and weaknesses in the reanalyses of each component of the climate system. Reanalyses agree closely on atmospheric moisture storage trends, although mean values differ. Reanalyses show significant differences in land water storage. They also apply large corrections to the land water budget. Finally, reanalyses have differing abilities in representing the surface mass balance over glaciated land. Using the observed gravimetry record, changes in the underlying glaciated land ice are examined as a residual.

Richard Cullather↗
NASA NTRS2012

The GEOS-iODAS: Description and Evaluation

This report documents the GMAO's Goddard Earth Observing System sea ice and ocean data assimilation systems (GEOS iODAS) and their evolution from the first reanalysis test, through the implementation that was used to initialize the GMAO decadal forecasts, and to the current system that is used to initialize the GMAO seasonal forecasts. The iODAS assimilates a wide range of observations into the ocean and sea ice components: in-situ temperature and salinity profiles, sea level anomalies from satellite altimetry, analyzed SST, and sea-ice concentration. The climatological sea surface salinity is used to constrain the surface salinity prior to the Argo years. Climatological temperature and salinity gridded data sets from the 2009 version of the World Ocean Atlas (WOA09) are used to help constrain the analysis in data sparse areas. The latest analysis, GEOS ODAS5.2, is diagnosed through detailed studies of the statistics of the innovations and analysis departures, comparisons with independent data, and integrated values such as volume transport. Finally, the climatologies of temperature and salinity fields from the Argo era, 2002-2011, are presented and compared with the WOA09.

Climate↗
NASA NTRS2014

Evaluating Observation Influence on Regional Water Budgets in Reanalyses

The assimilation of observations in reanalyses incurs the potential for the physical terms of budgets to be balanced by a term relating the fit of the observations relative to a forecast first guess analysis. This may indicate a limitation in the physical processes of the background model, or perhaps inconsistencies in the observing system and its assimilation. In the MERRA reanalysis, an area of long term moisture flux divergence over land has been identified over the Central United States. Here, we evaluate the water vapor budget in this region, taking advantage of two unique features of the MERRA diagnostic output; 1) a closed water budget that includes the analysis increment and 2) a gridded diagnostic output data set of the assimilated observations and their innovations (e.g. forecast departures). In the Central United States, an anomaly occurs where the analysis adds water to the region, while precipitation decreases and moisture flux divergence increases. This is related more to a change in the observing system than to a deficiency in the model physical processes. MERRAs Gridded Innovations and Observations (GIO) data narrow the observations that influence this feature to the ATOVS and Aqua satellites during the 06Z and 18Z analysis cycles. Observing system experiments further narrow the instruments that affect the anomalous feature to AMSUA (mainly window channels) and AIRS. This effort also shows the complexities of the observing system, and the reactions of the regional water budgets in reanalyses to the assimilated observations.

Atmospheric Reanalysis↗
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 NTRS2018

Recent Decline in Extratropical Lower Stratospheric Ozone Attributed to Circulation Changes

The 1998-2016 ozone trends in the lower stratosphere are examined using the Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) and related National Aeronautics and Space Administration products. After removing biases resulting from step changes in the MERRA-2 ozone observations, a discernible negative trend of 1.67 +/- 0.54 Dobson units per decade (DU/decade) is found in the 10-km layer above the tropopause between 20 deg N and 60 deg N. A weaker but statistically significant trend of 1.17 +/- 0.33 DU/decade exists between 50 deg S and 20 deg S. In the Tropics, a positive trend is seen in a 5-km layer above the tropopause. Analysis of an idealized tracer in a model simulation constrained by MERRA-2 meteorological fields provides strong evidence that these trends are driven by enhanced isentropic transport between the tropical (20 deg S-20 deg N) and extratropical lower stratosphere in the past two decades. This is the first time that a reanalysis data set has been used to detect and attribute trends in lower stratospheric ozone.

trend↗
NASA NTRSDate not supplied

Updates of MERRA-2 Data and Services at NASA GES DISC

Over40 years of NASA climate reanalysis datasets from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) are available at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). In addition to being used in traditional weather and climate research, MERRA-2 is also widely used in application studies of, e.g., wind and solar energy, air quality and health, food and drought, and heat waves. Two new MERRA-2 datasets were recently added at the GES DISC: (1) climate statistics derived fromMERRA-2 daily data to assist in the analysis of extreme temperature and precipitation events and of large-scale meteorological patterns from 1980 to the present and (2) gridded satellite and conventional observations processed in the MERRA-2 system, along with key statistics derived from the data assimilation, to help better understand how the quality of observations directly affect there analysis data. The GES DISC focuses its efforts on continually improving existing data services and to develop new data tools to satisfy various user communities. The newly added features include the following: Time series service: This is a new service for MERRA-2 data, which enables the easy and fast access of long-term hourly or daily time series at a location for popular parameters. The data is saved in a single le in Ascii format with a user- friendly structure. New analytic functions in the subsetter interface: Options for downloading daily minimum and maximum values have been added into the subsetter interface, in addition to the existing daily mean option, for all MERRA-2 and MERRA sub-daily products. Data format conversion to GeoTIFF has been implemented. New variables in Giovanni: Most monthly variables have been integrated into Giovanni, GESDISC’s online visualization and analysis tool. Due to the large data volume, hourly variables were selected based on user requests. More online information: New MERRA-2 documentation has been added: Data How-To, Data in Action, and FAQ. This presentation overviews two new MERRA-2 datasets and illustrates the new features of data services through a number of case studies. MERRA-2 data and services can be found at: https://disc.gsfc.gov/datasets?

Data management↗
NASA NTRS2021

Variation of Ice Microphysical Properties With Temperature and Humidity at Tops of Convective Clouds

A better understanding of the many interacting processes governing the evaluation of ice in natural clouds is required to improve the representation of ice clouds in global circulation models. Recent studies suggest a dominant role of vapor growth processes in determining the temperature dependence of cloud top ice sizes and shapes. Using airborne cloud remote sensing along with reanalysis data, here we show that observed cloud top ice effective radii and estimated normalized growth rates at cloud top highly correlate with an approximately linear relationship, which is consistent with a conceptual model also presented. Furthermore, significant differences in crystal shape characteristics and scattering asymmetry parameters are found between sub- and super-saturated cloud tops over ocean, although not over land. These results provide valuable observational targets for studying ice formation and evolution processes using models, while also helping interpretation of satellite observations of ice microphysical properties at cloud tops.

ice↗