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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Simulation of African Easterly Waves in a Global Climate Model

Abstract African easterly waves (AEWs) exert significant influence on local and downstream high-impact weather including tropical cyclone (TC) genesis over the Atlantic. Accurate representation of AEWs in climate and weather prediction models therefore is necessary for skillful predictions. In this study, we examine simulated AEWs, including their evolution, vertical structure, and linkage to tropical cyclone genesis, in the NASA Goddard Earth Observing System Model, version 5 (GEOS-5) atmospheric global climate model. Identified by the leading empirical orthogonal function mode of time-filtered precipitation, the observed westward propagating AEWs along the southern track over the Atlantic are largely captured in GEOS-5, but with a slower phase speed and significantly weaker amplitude downstream off the West Africa coast. The weak downstream development of AEWs in GEOS-5 is accompanied by much reduced TC genesis over the main development region. Further analyses suggest that the slow westward propagation and weaker AEW amplitude downstream can be ascribed to a weak African easterly jet, while overestimated negative (positive) meridional potential vorticity (PV) gradients appear to the north (south) of 10°N in GEOS-5. The greatly overestimated positive meridional PV gradient to the south of 10°N is expected to generate strong horizontal stretching in the AEW wave pattern in the model, which hinders organization of convection and its feedback to sustain the AEW development. Persistent and vigorous AEW precipitation in the Guinea Highlands of the West Africa coast could also be responsible for reduced westward propagation of AEWs in the model.

Meteorology & Atmospheric Sciences↗
NASA NTRS2017

An 8-Year, High-Resolution Reanalysis of Atmospheric CO2 Mixing Ratios Based on OCO-2 and GOSAT-ACOS Retrievals

The NASA GMAO (Global Modeling and Assimilation Office) reanalysis blends OCO-2 (Orbiting Carbon Observatory 2) and GOSAT-ACOS (Greenhouse Gases Observing Satellite-Atmospheric Carbon Observations from Space) retrievals (top) with GEOS (Goddard Earth Observing System) model predictions (bottom) to estimate the full 3D (three-dimensional) state of CO2 every 3 hours (middle). This poster describes monthly atmospheric growth rates derived from the reanalysis and an application to aircraft data with the potential to aid bias correction.

GEOS-Carb↗
NASA NTRS2019

Planetary Boundary Layer Height from AIRS and MERRA-2 Products at NASA GES DISC, and Insights from Data Intercomparison

The Atmospheric Infrared Sounder (AIRS) is the hyperspectral infrared sounder onboard NASA's Aqua satellite, launched in 2002. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), in collaboration with NASA Sounder Team at JPL, provides processing, archiving, and distribution services for NASA sounders: the Aqua AIRS mission and the subsequent Suomi-National Polar-orbiting Partnership Cross-track Infrared Sounder (CrIS) mission. The Planetary Boundary Layer (PBL) Height is a new variable added in the AIRS Version 6 support product. It is derived based on gradients of the retrieved atmospheric thermodynamic profile, and gives the pressure at the top of PBL over the ocean. The GES DISC also provides services for the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) product generated by the Goddard Earth Observing System Model, Version 5 (GEOS-5) data assimilation system. The monthly PBL Height variable has been available in the Giovanni system, which is a Web-based application developed by the GES DISC providing a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data. In this work, we will present the monthly PBL Height data from AIRS and MERRA-2 and the services to support data intercomparison, such as access, plotting, subsetting, re-gridding, and generation of a multi-year monthly mean. We will also show intercomparison results, and evaluate whether (over the ocean) AIRS can observe PBL features similar to the reanalysis product at monthly and longer-term scales.

AIRS↗
NASA NTRS2017

Update on the NASA GEOS-5 Aerosol Forecasting and Data Assimilation System

GEOS-5 is the Goddard Earth Observing System model. GEOS-5 is maintained by the NASA Global Modeling and Assimilation Office. Core development is within GMAO,Goddard Atmospheric Chemistry and Dynamics Laboratory, and with external partners. Primary GEOS-5 functions: Earth system model for studying climate variability and change, provide research quality reanalyses for supporting NASA instrument teams and scientific community, provide near-real time forecasts of meteorology,aerosols, and other atmospheric constituents to support NASA airborne campaigns.

GEOS-5↗
DOE OSTI2025

Confronting Earth System Model trends with observations

Anthropogenically forced climate change signals are emerging from the noise of internal variability in observations, and the impacts on society are growing. For decades, Climate or Earth System Models have been predicting how these climate change signals will unfold. While challenges remain, given the growing forced trends and the lengthening observational record, the climate science community is now in a position to confront the signals, as represented by historical trends, in models with observations. This review covers the state of the science on the ability of models to represent historical trends in the climate system. It also outlines robust procedures that should be used when comparing modeled and observed trends and how to move beyond quantification into understanding. Finally, this review discusses cutting-edge methods for identifying sources of discrepancies and the importance of future confrontations.

58 GEOSCIENCES↗
NASA NTRS2008

Performance of Versions 1,2 and 3 of the Goddard Earth Observing System (GEOS) Chemistry-Climate Model (CCM)

Version 1 of the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM) was used in the first CCMVa1 model evaluation and forms the basis for several studies of links between ozone and the circulation. That version of the CCM was based on the GEOS-4 GCM. Versions 2 and 3 of the GEOS CCM are based on the GEOS-5 GCM, which retains the "Lin-Rood" dynamical core but has a totally different set of physical parameterizatiOns to GEOS-4. In Version 2 of the GEOS CCM the Goddard stratospheric chemistry module is retained. Difference between Versions 1 and 2 thus reflect the physics changes of the underlying GCMs. Several comparisons between these two models are made, several of which reveal improvements in Version 2 (including a more realistic representation of the interannual variability of the Antarctic vortex). In Version 3 of the GEOS CCM, the stratospheric chemistry mechanism is replaced by the "GMI COMBO" code that includes tropospheric chemistry and different computational approaches. An advantage of this model version. is the reduction of high ozone biases that prevail at low chlorine loadings in Versions 1 and 2. This poster will compare and contrast various aspects of the three model versions that are relevant for understanding interactions between ozone and climate.

Pawson, Steven↗
NASA NTRS2018

Assimilating GCOM-W AMSR2 Radiance Data in Future GEOS Reanalysis

Surface and atmospheric radiation are being measured by space-borne conical scanning microwave radiometers with high accuracy and spatial resolution since 1980s'. These radiometers include Special Sensor Microwave Imager (SSM/I) onboard various NOAA's polar-orbiting satellites, Special Sensor Microwave Imager Sounder (SSMIS) onboard Defense Meteorological Satellite Program (DMSP) satellites, and Advanced Microwave Scanning Radiometer for EOS (AMSR-E), Advanced Microwave Scanning Radiometer 2 (AMSR2), Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI), and Global Precipitation Measurement (GPM) Microwave Imager (GMI) onboard NASA and JAXA's satellites. Atmospheric temperature, humidity, clouds, and precipitation are retrieved using brightness temperature data at frequencies between 22 GHz – 183 GHz. Some of the brightness temperature and retrieved rain rate data made by these imagers are assimilated in NASA Global Modelling and Assimilation Office (GMAO)'s weather and climate data sets including the Modern-Era Retrospective analysis for Research and Applications (MERRA) and its version 2 (MERRA-2) data sets. However, those radiance data are assimilated with the Goddard Earth Observing System model, version 5 (GEOS-5) only in clear-sky conditions. Recently, we started assimilate GPM/GMI radiance data with GEOS-5's atmospheric data assimilation system GSI under all-sky conditions in order to have better constraints in analyzed hydrological properties. GMAO plans to assimilate more microwave radiometers' brightness temperature data in its analyses. In this talk, we will discuss TMI and AMSR2 data's impact in temperature, humidity, clouds and precipitation under all-sky conditions in future GEOS reanalysis.

Jin, Jianjun↗
NASA NTRS2019

Convective Entrainment Rates Estimated from Aura CO and CloudSat/CALIPSO Observations and Comparison with GEOS-5

Entrainment rate (λ) in convective parameterizations remains a sensitive parameter with much uncertainty in model simulations. This study estimates λ using carbon monoxide (CO) measurements jointly from the Microwave Limb Sounder (MLS) and Tropospheric Emission Spectrometer (TES) onboard the Aura satellite, associated with deep convective cases identified by CloudSat and CALIPSO observations. CO is treated as a conserved quantity over convective transport time scales and a simple entraining-plume model is used to derive entrainment rates. The relationships of the observational estimates of λ as a function of convective height, environmental relative humidity and convective available potential energy (CAPE) derived from Atmospheric Infrared Sounder (AIRS) data are compared with those from Goddard Earth Observing System Model (GEOS-5) simulations. Bulk statistics of λ show that the values of λ are predominately below 20% km(exp-1) for deep convection and the occurrence frequency of any λ decreases with increasing λ. Composite λ values are generally lower in the tropics compared to northern mid-latitudes in both observations and the GEOS-5 model. A decrease of λ with increasing convective height is found in both observations and model simulations. We also find that λ tends to decrease with increasing CAPE in the observation-based λ’s and plume-based GEOS-5 λ’s, although the model given λ’s have a non-monotonic relation with CAPE. The observed λ’s have a weak relation with lower-to-mid tropospheric RH, while both GEOS-5 plume-based and given λ increases with increasing RH.

Ryan E Stanfield↗
NASA NTRSDate not supplied

PolarMERRA: A Polar-Focused Global Reanalysis Project for Scientific and Stakeholder Needs

The adequate modeling of physical processes in the Arctic and Antarctic is vital for developing prediction capabilities and for obtaining an understanding of rapidly evolving polar conditions, including their potential global impacts. These processes are often poorly represented in global models and reanalyses, owing to a legacy modeling focus on midlatitude processes, as well as a scarcity of observations needed for model development in polar regions. The polarMERRA initiative, a joint effort between NASA’s Cryospheric Sciences and Modeling and Prediction programs, seeks to improve the representation of cryospheric and polar atmospheric processes and to develop an open-source framework for a quantitively evaluation of polar-relevant variables against current and future satellite and in-situ observations, models, and reanalyses. Here, we evaluate the impacts of spatial resolution and modifications to sea ice, ice sheet, and atmospheric parameterizations on the representation of high latitude conditions by using a quantitative scorecard approach that leverages NASA’s extensive satellite record. Investigations are conducted using the NASA Goddard Earth Observing System model (GEOS) and its data assimilation system (GEOS DAS). Through a quantitative identification of process deficiencies, bias reductions in key surface variables, including temperature and precipitation over cryospheric surfaces, may be achieved. The polarMERRA project additionally seeks to identify additional data sources for use in the GEOS DAS, and to incorporate data and parameterization improvements into future model and reanalysis products for scientific and stakeholder use.

Lauren C Andrews↗
NASA NTRS2018

Performance and Evaluation of the Global Modeling and Assimilation Office Observing System Simulation Experiment

The National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO) has spent more than a decade developing and implementing a global Observing System Simulation Experiment framework for use in evaluting both new observation types as well as the behavior of data assimilation systems. The NASA/GMAO OSSE has constantly evolved to relect changes in the Gridpoint Statistical Interpolation data assimiation system, the Global Earth Observing System model, version 5 (GEOS-5), and the real world observational network. Software and observational datasets for the GMAO OSSE are publicly available, along with a technical report. Substantial modifications have recently been made to the NASA/GMAO OSSE framework, including the character of synthetic observation errors, new instrument types, and more sophisticated atmospheric wind vectors. These improvements will be described, along with the overall performance of the current OSSE. Lessons learned from investigations into correlated errors and model error will be discussed.

OSS↗
NASA NTRS2008

Examination of Observation Impacts derived from OSEs and Adjoint Models

With the adjoint of a data assimilation system, the impact of any or all assimilated observations on measures of forecast skill can be estimated accurately and efficiently. The approach allows aggregation of results in terms of individual data types, channels or locations, all computed simultaneously. In this study, adjoint-based estimates of observation impact are compared with results from standard observing system experiments (OSEs) in the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) GEOS-5 system. The two approaches are shown to provide unique, but complimentary, information. Used together, they reveal both redundancies and dependencies between observing system impacts as observations are added or removed. Understanding these dependencies poses a major challenge for optimizing the use of the current observational network and defining requirements for future observing systems.

Gelaro, Ronald↗
NASA NTRS2019

Planetary Boundary Layer Height from AIRS, MERRA-2, and GPS Radio Occultation Data Products at NASA GES DISC, and Insights from Their Profiles Intercomparison

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides archive and distribution services for several data products in the Planetary Boundary Layer (PBL) category. As a new variable added to the Atmospheric Infrared Sounder (AIRS) Version 6 support product, the PBL height from AIRS is derived based on the gradients of the retrieved relative humidity profile, and provides the atmospheric pressure at the top of the PBL over the ocean. The GES DISC also hosts the Modern-Era Retrospective analysis for Research and Applications-2 (MERRA-2) product generated by the Goddard Earth Observing System Model Version 5 (GEOS-5) data assimilation system. The PBL height from MERRA-2 is based on the total eddy diffusion coefficient of heat. The monthly PBL height has been made available in the Giovanni system (Giovanni is a Web-based application developed by the GES DISC providing a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data). Recently, the GES DISC began serving the global PBL height climatology product derived from the COSMIC/FORMOSAT-3 and TerraSAR-X Global Positioning System (GPS) radio occultation (RO) measurements from June 2006 to December 2015. In a previous study, we presented the monthly PBL height data from AIRS and MERRA-2 and demonstrated the GES DISC services which support data intercomparison, such as access, plotting, sub-setting, regridding, and generation of a multi-year monthly mean. We also provided intercomparison results, and found that different PBL height definitions contributed to significant differences of PBL height values between AIRS and MERRA-2. In this work, we present the 10-year seasonal climatologies from the AIRS, MERRA-2 and GPS-RO. We also used the cross section and vertical profile services in Giovanni to display and analyze the vertical atmosphere structure over regions where the PBL height derived from the AIRS and MERRA-2 are quite different. The examination of the AIRS and MERRA-2 three-dimensional data found that the relative humidity profiles had larger differences than the temperature profiles. The MERRA-2 gives more details than the AIRS for the vertical distribution of the humidity.

Ding, Feng↗
NASA NTRS2016

Role of Updraft Velocity in Temporal Variability of Global Cloud Hydrometeor Number

Understanding how dynamical and aerosol inputs affect the temporal variability of hydrometeor formation in climate models will help to explain sources of model diversity in cloud forcing, to provide robust comparisons with data, and, ultimately, to reduce the uncertainty in estimates of the aerosol indirect effect. This variability attribution can be done at various spatial and temporal resolutions with metrics derived from online adjoint sensitivities of droplet and crystal number to relevant inputs. Such metrics are defined and calculated from simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1 (CAM5.1). Input updraft velocity fluctuations can explain as much as 48% of temporal variability in output ice crystal number and 61% in droplet number in GEOS-5 and up to 89% of temporal variability in output ice crystal number in CAM5.1. In both models, this vertical velocity attribution depends strongly on altitude. Despite its importance for hydrometeor formation, simulated vertical velocity distributions are rarely evaluated against observations due to the sparsity of relevant data. Coordinated effort by the atmospheric community to develop more consistent, observationally based updraft treatments will help to close this knowledge gap.

cloud condensation nuclei↗
NASA NTRS2011

Performance Tests of Snow-Related Variables Over the Tibetan Plateau and Himalayas Using a New Version of NASA GEOS-5 Land Surface Model that Includes the Snow Darkening Effect

The snow darkening effect, i.e. the reduction of snow albedo, is caused by absorption of solar radiation by absorbing aerosols (dust, black carbon, and organic carbon) deposited on the snow surface. This process is probably important over Himalayan and Tibetan glaciers due to the transport of highly polluted Atmospheric Brown Cloud (ABC) from the Indo-Gangetic Plain (IGP). This effect has been incorporated into the NASA Goddard Earth Observing System model, version 5 (GEOS-5) atmospheric transport model. The Catchment land surface model (LSM) used in GEOS-5 considers 3 snow layers. Code was developed to track the mass concentration of aerosols in the three layers, taking into account such processes as the flushing of the compounds as liquid water percolates through the snowpack. In GEOS-5, aerosol emissions, transports, and depositions are well simulated in the Goddard Chemistry Aerosol Radiation and Transport (GO CART) module; we recently made the connection between GOCART and the GEOS-5 system fitted with the revised LSM. Preliminary simulations were performed with this new system in "replay" mode (i.e., with atmospheric dynamics guided by reanalysis) at 2x2.5 degree horizontal resolution, covering the period 1 November 2005 - 31 December 2009; we consider the final three years of simulation here. The three simulations used the following variants of the LSM: (1) the original Catchment LSM with a fixed fresh snowfall density of 150 kg m-3 ; (2) the LSM fitted with the new snow albedo code, used here without aerosol deposition but with changes in density formulation and melting water effect on snow specific surface area, (3) the LSM fitted with the new snow albedo code as same as (2) but with fixed aerosol deposition rates (computed from GOCART values averaged over the Tibetan Plateau domain [Ion.: 60-120E; lat.: 20-50N] during March-May 2008) applied to all grid points at every time step. For (2) and (3), the same setting on the fresh snowfall density as in (1) was used.

Yasunari, Tppei J.↗
NASA NTRS2013

The Influence of Observation Errors on Analysis Error and Forecast Skill Investigated with an Observing System Simulation Experiment

The Global Modeling and Assimilation Office (GMAO) observing system simulation experiment (OSSE) framework is used to explore the response of analysis error and forecast skill to observation quality. In an OSSE, synthetic observations may be created that have much smaller error than real observations, and precisely quantified error may be applied to these synthetic observations. Three experiments are performed in which synthetic observations with magnitudes of applied observation error that vary from zero to twice the estimated realistic error are ingested into the Goddard Earth Observing System Model (GEOS-5) with Gridpoint Statistical Interpolation (GSI) data assimilation for a one-month period representing July. The analysis increment and observation innovation are strongly impacted by observation error, with much larger variances for increased observation error. The analysis quality is degraded by increased observation error, but the change in root-mean-square error of the analysis state is small relative to the total analysis error. Surprisingly, in the 120 hour forecast increased observation error only yields a slight decline in forecast skill in the extratropics, and no discernable degradation of forecast skill in the tropics.

Observation Error↗
NASA NTRS2018

Multidecadal Changes in Lower Stratospheric Ozone: Variability Vs. Trends

As upper stratospheric ozone appears to be recovering as a result of decreasing chlorine loading following the implementation of the Montreal Protocol and its amendments and in agreement with model projections, several recent studies report an apparent decline of ozone concentrations in the lower stratosphere in the last two decades, particularly in the extratropics. Our previous work as well as at least two other studies provide evidence that this decline results from transport changes rather than an intensification of chemical depletion. It remains unclear whether these changes represent long-term internal variability or are a consequence of a climate forcing. Here we perform free-running ensembles of the recent past (1980-2016) using the Goddard Earth Observing System Model (GEOS) at the cubed sphere C180 (approximately half degree) resolution. Two suites of 10-member ensembles are performed, one in which observed sea surface temperature (SSTs) are fully prescribed, and the other in which the linear SST trend over the recent past is removed so as to only retain internal variability. We evaluate the trends in both ozone as well as two idealized tracers with prescribed uniform loss that are used to isolate the role of transport from chemistry and emissions. Probability-distribution-functions of the trends in both ozone and idealized tracers are compared among ensemble members and with observed trends in order to evaluate the likelihood of recent observed declines in lower stratospheric ozone, relative to large internal variability. Moreover, comparisons among simulations with and without imposed SST trends indicate the extent to which dynamically-driven ozone trends reflect forced trends or internal variability in lower stratospheric dynamics.

Wargan, Krzysztof↗
NASA NTRS2019

Joint Assimilation of the Aura Microwave Limb Sounder and Ozone Mapping and Profiler Suite Limb Profiler Data: Towards a Reanalysis of Stratospheric Ozone for Trend Studies

The future trajectory of the stratospheric ozone recovery will be sensitive to greenhouse gas concentrations through thermal control of chemical loss and via stratospheric circulation changes. The latter in particular is subject to considerable uncertainty meriting continuing monitoring of the evolution of ozone throughout the depth of the stratosphere. Atmospheric reanalyses utilize the data assimilation methodology to obtain comprehensive representations of the state of the atmosphere, including its composition, on multidecadal scales by combining diverse measurements from satellite-borne and conventional data sources. Systematic biases among these various data types pose a challenge for assimilation by introducing spurious discontinuities that affect the utility of reanalyses for studies of long-term variability and trends.In this presentation we will outline an approach, developed at NASA's Global Modeling and Assimilation Office (GMAO), that allows joint assimilation of stratospheric ozone profiles from the Microwave Limb Sounder (MLS) on EOS Aura and the Ozone Mapping and Profiler Suite Limb Profiler (OMPS-LP) currently flying on the Suomi-NPP satellite with future missions projected into the 2030s. We will demonstrate that a simple offline correction significantly reduces biases between MLS and OMPS-LP ozone data providing a strategy for generating a long-term vertically resolved homogenized representation of stratospheric ozone in future reanalyses. One novel element of our approach compared to previous GMAO reanalysis is the use of a version of the Goddard Earth Observing System model with full stratospheric chemistry. We will show selected comparisons of MLS and OMPS-LP assimilation experiments with independent ozonesonde and satellite data as well as two examples of process-based evaluation focused on the 2016 QBO disruption and Arctic winter ozone loss focusing on the relative performance of the MLS and OMPS-LP analyses.

Wargan, K.↗
NASA NTRS2018

Application of Aura OMI L2G Products Compared with NASA MERRA-2 Assimilation

The Ozone Monitoring Instrument (OMI) is one of the instruments aboard NASA's Aura satellite. It measures ozone total column and vertical profile, aerosols, clouds, and trace gases including NO2, SO2, HCHO, BrO, and OClO using absorption in the ultraviolet electromagnetic spectrum (280 - 400 nm). OMI Level-2G (L2G) products are based on the pixel-level OMI granule satellite measurements stored within global 0.25 deg. X 0.25 deg. grids, therefore they conserve all the Level 2 (L2) spatial and temporal details for 24 hours of scientific data in one file. 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. MERRA-2 includes aerosol data reanalysis and improved representations of stratospheric ozone, compared with its predecessor MERRA, in both instantaneous and time-averaged collections. It is found that simply comparing satellite Level-3 products might cause biases, due to lack of detailed temporal and original retrieval information. It is therefore preferable to inter-compare or implement satellite derived physical quantities directly with/to model assimilation with as high temporal and spatial resolutions as possible. This study will demonstrate utilization of OMI L2G daily aerosol and ozone products by comparing them with MERRA-2 hourly aerosol/ozone simulations, matched in both space and time aspects. Both OMI and MERRA-2 products are accessible online through NASA Goddard Earth Sciences Data Information Services Center (GES DISC, https://disc.gsfc.nasa.gov/).

OMI L2G products↗