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DOE OSTI2020

Radiative heating rate profiles over the southeast Atlantic Ocean during the 2016 and 2017 biomass burning seasons

Marine boundary layer clouds, including the transition from stratocumulus to cumulus, are poorly represented in numerical weather prediction and general circulation models. Further uncertainties in the cloud structure arise in the presence of biomass burning carbonaceous aerosol, as is the case over the southeast Atlantic Ocean, where biomass burning aerosol is transported from the African continent. As the aerosol plume progresses across the southeast Atlantic Ocean, radiative heating within the aerosol layer has the potential to alter the thermodynamic environment and therefore the cloud structure; however, limited work has been done to quantify this along the trajectory of the aerosol plume in the region. The deployment of the first Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF1) in support of the Layered Atlantic Smoke Interactions with Clouds field campaign provided a unique opportunity to collect observations of cloud and aerosol properties during two consecutive biomass burning seasons during July through October of 2016 and 2017 over Ascension Island (7.96° S, 14.35° W). Using observed profiles of temperature, humidity, and clouds from the field campaign alongside aerosol optical properties from Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), as input for the Rapid Radiation Transfer Model (RRTM), profiles of the radiative heating rate due to aerosols and clouds were computed. Radiative heating is also assessed across the southeast Atlantic Ocean using an ensemble of back trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Idealized experiments using the RRTM with and without aerosols and a range of values for the single-scattering albedo (SSA) demonstrate that shortwave (SW) heating within the aerosol layer above Ascension Island can locally range between 2 and 8 K d -1 depending on the aerosol optical properties, though impacts of the aerosol can be felt elsewhere in the atmospheric column. When considered under clear conditions, the aerosol has a cooling effect at the TOA, and based on the observed cloud properties at Ascension Island, the cloud albedo is not large enough to overcome this. Shortwave radiative heating due to biomass burning aerosol is not balanced by additional longwave (LW) cooling, and the net radiative impact results in a stabilization of the lower troposphere. However, these results are extremely sensitive to the single-scattering albedo assumptions in models.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1981

A simple atmospheric model on the sphere with 100% parallelism

A simple shallow water equations model used to test numerical weather prediction schemes is presented. The spherical geometry is transformed into a formally doubly periodic configuration which can be implemented on a massively parallel computer at 100% parallelism. A nonstaggered grid with all variables defined at the grid points (circles) is used. The parallel structure was simulated by performing step 1 in a FORTRAN array, on an Amdahl serial machine, changing the signs of the winds on the dark side.

Kalnay, E.↗

NASA NTRS1984

Orographic Effects in Atmospheric Circulation

The role of orography on the large-scale and regional atmospheric circulation, with special emphasis on lee cyclogenesis was studied. Effects observed in the actual atmosphere as well as numerical weather prediction and general circulation models are included.

Duffy, D. G.↗

NASA NTRS2004

Multi-Spectral Cloud Retrievals from Moderate Image Spectrometer (MODIS)

MODIS observations from the NASA EOS Terra spacecraft (1030 local time equatorial sun-synchronous crossing) launched in December 1999 have provided a unique set of Earth observation data. With the launch of the NASA EOS Aqua spacecraft (1330 local time crossing! in May 2002: two MODIS daytime (sunlit) and nighttime observations are now available in a 24-hour period allowing some measure of diurnal variability. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate modeling, climate change studies, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. An overview of the instrument and cloud algorithms will be presented along with various examples, including an initial analysis of several operational global gridded (Level-3) cloud products from the two platforms. Statistics of cloud optical and microphysical properties as a function of latitude for land and Ocean regions will be shown. Current algorithm research efforts will also be discussed.

Platnick, Steven↗

NASA NTRS2018

Characterizing Differences in the Aerosol Plume and Cloud Structure over Ascension Island During the 2016 and 2017 Biomass Burning Seasons

Marine boundary layer clouds, including the transition from stratocumulus to cumulus, are poorly represented in numerical weather prediction and general circulation models. In many cases, the complex physical relationships between marine boundary cloud morphology and the environmental conditions in which the clouds exist are not well understood. Such uncertainties arise in the presence of biomass burning carbonaceous aerosol, as is the case over the southeast Atlantic Ocean. It is likely that the absorbing and heating properties of these aerosols influence the microphysical composition and macrophysical arrangement of marine stratocumulus and trade cumulus in this region; however, this has yet to be quantified. The deployment of the Atmospheric Radiation Measurement Mobile Facility #1 (AMF1) in support of LASIC (Layered Atlantic Smoke Interactions with Clouds) provided a unique opportunity to collect observations of cloud and aerosol properties during two consecutive biomass burning seasons during July through October of 2016 and 2017 over Ascension Island (7.96 S, 14.35 W). Through the use of AMF1 observations, the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and back trajectories from the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT), it will be demonstrated that differences in the atmospheric circulation during the two years result in varying aerosol conditions over Ascension Island. When the aerosol plume is overhead, the aerosol loading is higher during the 2016 season as a result of a weaker subtropical high-pressure system. Furthermore, the aerosol plume originates from central Africa in 2016, but further south in 2017. Contrasts in the season-to-season and day-to-day aerosol loading are used to categorize boundary layer cloud and sub-cloud turbulence measurements above Ascension Island using the AMF1 Doppler lidar and cloud radar.

Collow, Allison B. Marquardt↗

NASA NTRS2018

Radiative Heating Profiles over Ascension Island during the 2016 and 2017 Biomass Burning Seasons

Marine boundary layer clouds, including the transition from stratocumulus to cumulus, are poorly represented in numerical weather prediction and general circulation models. In many cases, the complex physical relationships between cloud morphology and the environmental conditions in which marine boundary layer clouds exist are not well understood. Such uncertainties arise in the presence of biomass burning carbonaceous aerosol, as is the case over the southeast Atlantic Ocean, where it is likely that the absorbing and heating properties of these aerosols modify the microphysical composition and macrophysical arrangement of marine stratocumulus and trade cumulus. The deployment of the Atmospheric Radiation Measurement Mobile Facility #1 (AMF1) in support of LASIC (Layered Atlantic Smoke Interactions with Clouds) provided a unique opportunity to observe thermodynamic, cloud and aerosol properties during two consecutive biomass burning seasons from July through October of 2016 and 2017 over Ascension Island (7.96 S, 14.35 W). These observations in conjunction with radiation transfer modeling were used to assess the impact of biomass burning carbonaceous aerosol plumes as they passed over the site.Thermodynamic profiles were generated using a combination of radiosonde data and thermodynamic profilers to provide high temporal resolution profiles of quantities that are important for cloud development, such as CAPE and CIN. Coincident Ka-band radar and lidar profiles were used to characterize the cloud and sub-cloud structure. The resulting thermodynamic and cloud profiles are used as input forcing for the Rapid Radiative Transfer Model (RRTM) to compute radiative heating profiles over the observation site. Idealized experiments using RRTM, with and without aerosols present, are used to assess the impacts of the absorbing aerosol on the heating rate profiles.

Cumulus↗

NASA NTRS2019

NASA Disasters Program: A Partner for Coastal Disaster Response, Resiliency, and Risk Reduction

Summary: The NASA Applied Sciences: Disasters Program has kicked off a pilot project as “Mid-Atlantic Resiliency Demonstration Study, Communities at Intensive Risk” in FY17 and FY18; Efforts focus on a holistic, interdisciplinary approach to integrate a full suite of capabilities from numerical weather prediction, tide and surge modeling at high spatial resolution and urban/neighborhood scales, and remote sensing capabilities for water detection and depth estimation; Future efforts - Partner with Federal Agencies, academia professional societies to complement and augment ongoing work using Earth observations unique to NASA - Translate hazards to risk in order to understand local and regional impacts and minimize vulnerability.

Bell, Jordan↗

NASA NTRS2019

Aerosol Radiative Effects over Ascension Island Using LASIC Observations and MERRA-2

Marine boundary layer clouds, including the transition from stratocumulus to cumulus, are poorly represented in numerical weather prediction and general circulation models. In many cases, the complex physical relationships between marine boundary cloud morphology and the environmental conditions in which the clouds exist are not well understood. Such uncertainties arise in the presence of biomass burning carbonaceous aerosol, as is the case over the southeast Atlantic Ocean. It is likely that the absorbing and heating properties of these aerosols influence the microphysical composition and macrophysical arrangement of marine stratocumulus and trade cumulus in this region; however, this has yet to be quantified. The deployment of the Atmospheric Radiation Measurement Mobile Facility #1 (AMF1) in support of LASIC (Layered Atlantic Smoke Interactions with Clouds) provided a unique opportunity to collect observations of cloud and aerosol properties during two consecutive biomass burning seasons during July through October of 2016 and 2017 over Ascension Island (7.96 S, 14.35 W). Thermodynamic profiles will be analyzed through the unique combination of sounding data from radiosonde launches and microwave profiling radiometers, giving observations of additional quantities important for cloud development such as CAPE and CIN at a fine temporal resolution. The thermodynamic profiles will be presented in conjunction with detailed observations of the cloud structure over the site from a K-band cloud radar, micropulse lidar, and laser ceilometer. Finally, the observed thermodynamic and cloud profiles will be used as input forcing, alongside aerosols from the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), for the Rapid Radiative Transfer Model (RRTM) to gain information regarding the radiative heating profiles. Idealized experiments using RRTM with and without aerosols will be used to quantify the impact of biomass burning carbonaceous aerosol plumes as they pass over the site.

Collow, Allie↗

NASA NTRS2019

Thermodynamic, Cloud, and Radiative Heating Profiles over Ascension Island During the 2016 and 2017 Biomass Burning Seasons

Marine boundary layer clouds, including the transition from stratocumulus to cumulus, are poorly represented in numerical weather prediction and general circulation models. In many cases, the complex physical relationships between marine boundary cloud morphology and the environmental conditions in which the clouds exist are not well understood. Such uncertainties arise in the presence of biomass burning carbonaceous aerosol, as is the case over the southeast Atlantic Ocean. It is likely that the absorbing and heating properties of these aerosols influence the microphysical composition and macrophysical arrangement of marine stratocumulus and trade cumulus in this region; however, this has yet to be quantified. The deployment of the Atmospheric Radiation Measurement Mobile Facility #1 (AMF1) in support of LASIC (Layered Atlantic Smoke Interactions with Clouds) provided a unique opportunity to collect observations of cloud and aerosol properties during two consecutive biomass burning seasons during July through October of 2016 and 2017 over Ascension Island (7.96 S, 14.35 W). Thermodynamic profiles will be analyzed through the unique combination of sounding data from radiosonde launches and microwave profiling radiometers, giving observations of additional quantities important for cloud development such as CAPE and CIN at a fine temporal resolution. The thermodynamic profiles will be presented in conjunction with detailed observations of the cloud structure over the site from a K-band cloud radar, micropulse lidar, and laser ceilometer. Finally, the observed thermodynamic and cloud profiles will be used as input forcing, alongside aerosols from the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), for the Rapid Radiative Transfer Model (RRTM) to gain information regarding the radiative heating profiles. Idealized experiments using RRTM with and without aerosols will be used to quantify the impact of biomass burning carbonaceous aerosol plumes as they pass over the site.

Collow, Allison B.↗

NASA NTRS2020

Radiative Heating from Biomass Burning Aerosol and its Impact on Cloud Structure in the Southeast Atlantic

Marine boundary layer clouds, including the transition from stratocumulus to cumulus, are poorly represented in numerical weather prediction and general circulation models. In many cases, the complex physical relationships between marine boundary cloud morphology and the environmental conditions in which the clouds exist are not well understood. Such uncertainties arise in the presence of biomass burning carbonaceous aerosol, as is the case over the southeast Atlantic Ocean. It is likely that the absorbing and heating properties of these aerosols influence the microphysical composition and macrophysical arrangement of marine stratocumulus and trade cumulus in this region; however, this has yet to be quantified. The deployment of the Atmospheric Radiation Measurement Mobile Facility #1 (AMF1) in support of LASIC (Layered Atlantic Smoke Interactions with Clouds) provided a unique opportunity to collect observations of cloud and aerosol properties during two consecutive biomass burning seasons during July through October of 2016 and 2017 over Ascension Island (7.96 S, 14.35 W). Thermodynamic profiles will be analyzed through the unique combination of sounding data from radiosonde launches and microwave profiling radiometers, giving observations of additional quantities important for cloud development such as CAPE and CIN at a fine temporal resolution. The thermodynamic profiles will be presented in conjunction with detailed observations of the cloud structure over the site from a K-band cloud radar, micropulse lidar, and laser ceilometer. The observed thermodynamic and cloud profiles will be used as input forcing, alongside aerosols from the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), for the Rapid Radiative Transfer Model (RRTM) to gain information regarding the radiative heating profiles. Idealized experiments using RRTM with and without aerosols will be used to quantify the impact of biomass burning carbonaceous aerosol plumes as they pass over the site. Due to documented discrepancies in the single scatter albedo (SSA) between models and observations, further sensitivity experiments will demonstrate the importance of the optical properties of biomass burning aerosol in accurately representing heating within the column. Finally, the heating rates will be put into context of the cloud structure over the site from the perspective of the mass flux closure from the University of Washington shallow convective scheme.

Collow, Allison↗

NASA NTRS2020

Radiative Heating Rate Profiles over the Southeast Atlantic Ocean during the 2016 and 2017 Biomass Burning Seasons

Marine boundary layer clouds, including the transition from stratocumulus to cumulus, are poorly represented in numerical weather prediction and general circulation models. Further uncertainties in the cloud structure arise in the presence of biomass burning carbonaceous aerosol, as is the case over the southeast Atlantic Ocean where biomass burning aerosol is transported from the African continent. As the aerosol plume progresses across the southeast Atlantic Ocean, radiative heating within the aerosol layer has the potential to alter the thermodynamic environment and therefore the cloud structure; however, limited work has been done to quantify this along the trajectory of the aerosol plume in the region. The deployment of the First Atmospheric Radiation Measurement Mobile Facility in support of the Layered Atlantic Smoke Interactions with Clouds field campaign provided a unique opportunity to collect observations of cloud and aerosol properties during two consecutive biomass burning seasons during July through October of 2016 and 2017 over Ascension Island (7.96 °S, 14.35 °W). Using observed profiles of temperature, humidity, and clouds from the field campaign, alongside aerosol optical properties from MERRA-2 as input for the Rapid Radiation Transfer Model, profiles of the radiative heating rate due to aerosols and clouds were computed. Radiative heating is also assessed across the southeast Atlantic Ocean using an ensemble of back trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory Model. Idealized experiments using the Rapid Radiation Transfer Model with and without aerosols and a range of values for the single scattering albedo demonstrate that shortwave heating within the aerosol layer above Ascension Island can locally range between 2 and 8 K per day depending on the aerosol optical properties, though impacts of the aerosol can be felt elsewhere in the atmospheric column. When considered under clear conditions, the aerosol has a cooling effect at the TOA and based on the observed cloud properties at Ascension Island, the cloud albedo is not large enough to overcome this. Shortwave radiative heating due to biomass burning aerosol is not balanced by additional longwave cooling, and the net radiative impact results in a stabilization of the lower troposphere. However, these results are extremely sensitive to the single scattering albedo assumptions in models.

Allison B. Marquardt Collow↗

NASA NTRSDate not supplied

Introduction to the JPSS-2 Advanced Technology Microwave Sounder (ATMS) Government Calibration Data Book (GCDB)

The third Advanced Technology Microwave Sounder (ATMS) is an instrument onboard the Joint Polar Satellite System (JPSS), JPSS-2 (renamed NOAA-21 in orbit) mission. This report is to introduce the JPSS-2 Government Calibration Data Book (J2 GCDB) for ATMS, SN 304. This J2 GCDB document contains key information generated during the calibration testing campaign that is driving parameters for radiometric performance. This document also contains supporting data that augments the calibration results. The values in this document are utilized by ATMS’s calibration packet which is, in turn, an integral component in the interpretation of science data. The calibration data in this report was collected from tests such as shelf-level testing, antenna testing, instrument thermal vacuum (TVAC) testing; satellite TVAC testing; and JPSS-2 post-launch tests. JPSS-2 was launched on November 10, 2022. In the subsequent years, the Government will release an ATMS GCDB for each JPSS mission. We expect that all public users can download these ATMS GCDBs from the NOAA operational Integrated Calibration and Validation System (ICVS) website, see more discussions below. The goal of this GCDB is to demonstrate how to characterize ATMS measurements using JPSS-2 ATMS on-orbit operational data and to provide relevant explanations. This document serves as a primary public domain reference for calibrating operational ATMS Raw Data Records (RDR) science data, as used in the current operational Interface Data Processing Segment (IDPS) system. This same RDR science data is distributed through direct broadcast (DB) to DB users for use in their ground processing systems. This J2 GCDB provides the results of the ATMS system radiometric calibration, the antenna flat reflector emissivity [1], the antenna pattern measurements, the antenna pattern corrected brightness temperature [2], the brightness temperature of the lunar disk [3], Lunar Intrusion (LI) correction algorithm [4], receiver spectral parameters, and mechanical alignment on-orbit pointing results, and the striping effect appeared significantly in S-NPP on-orbit radiance data when the data are compared to the Radiative Transfer Model (RTM) simulation in numerical weather prediction (NWP) system [5]. It also provides the parameters required for conversion of telemetry counts to engineering units, for radiometric calibration, and for antenna beam geo-location. Moreover, it provides JPSS-2 ATMS Spectral Response Functions data, some additional information related to ATMS on-orbit performance, on-orbit lunar intrusion correction parameters and Earth contamination bias, and on how to derive ATMS RDR, antenna Temperature Data Records (TDR), and Sensor Data Records (SDR). Furthermore, an introduction of NOAA operational Integrated Calibration and Validation System (ICVS) website and services is added in this J2 GCDB. This ICVS hosts a long-term monitoring system which allows to visualization and comparison of data from JPSS missions, NOAA legacy Polar Operational Environmental Satellites (POES), and Geostationary Operational Environmental Satellites (GOES). From NOAA Comprehensive Large Array-data Stewardship System (CLASS), the public users can download all JPSS ATMS data products for all JPSS missions.

Microwave Sounder↗

NASA NTRS2026

Measure sea level air pressure from space to improve knowledge and forecasting of the atmospheric state

Modern numerical weather prediction (NWP) and analysis models require globally-observed meteorological data including sea-level pressure (SLP) for accurate operations. Up until now, SLP has only been measured by in situ instruments from ships, buoys, and ocean platforms. These measurements are sparse with large gaps, leaving models starved of this critical information to constrain the atmospheric state. Recent advancements in differential absorption radar (DAR) provide a path to close this critical observation gap through spaceborne observations in the coming decade, improving the analysis models relied upon for atmospheric research and the weather forecasts depended upon daily for public safety and commerce.

Matthew L Walker McLinden↗

NASA NTRS2007

Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model: Results for the Mississippi River Basin

NASA's GRACE mission has the potential to be extremely valuable for water resources applications and global water cycle research. What makes GRACE unique among Earth Science satellite systems is that it is able to monitor variations in water stored in all forms, from snow and surface water to soil moisture to groundwater in the deepest aquifers. However, the space and time resolutions of GRACE observations are coarse. GRACE typically resolves water storage changes over regions the size of Nebraska on a monthly basis, while city-scale, daily observations would be more useful for water management, agriculture, and weather prediction. High resolution numerical (computer) hydrology models have been developed, which predict the fates of water and energy after they strike the land surface as precipitation and sunlight. These are similar to weather and climate forecast models, which simulate atmospheric processes. We integrated the GRACE observations into a hydrology model using an advanced technique called data assimilation. The results were new estimates of groundwater, soil moisture, and snow variations, which combined the veracity of GRACE with the high resolution of the model. We tested the technique over the Mississippi River basin, but it will be even more valuable in parts of the world which lack reliable data on water availability.

Zaitchik, Benjamin F.↗

DOE OSTI2014

Massively parallel solvers for elliptic partial differential equations in numerical weather and climate prediction

The demand for substantial increases in the spatial resolution of global weather and climate prediction models makes it essential to use numerically efficient and highly scalable algorithms to solve the equations of large-scale atmospheric fluid dynamics. For stability and efficiency reasons, several of the operational forecasting centres, in particular the Met Office and the European Centre for Medium-Range Weather Forecasts (ECMWF) in the UK, use semi-implicit semi-Lagrangian time-stepping in the dynamical core of the model. The additional burden with this method is that a three-dimensional elliptic partial differential equation (PDE) for the pressure correction has to be solved at every model time step and this often constitutes a significant proportion of the time spent in the dynamical core. In global models, this PDE must be solved in a thin spherical shell. To run within tight operational time-scales, the solver has to be parallelized and there seems to be a (perceived) misconception that elliptic solvers do not scale to large processor counts and hence implicit time-stepping cannot be used in very high-resolution global models. After reviewing several methods for solving the elliptic PDE for the pressure correction and their application in atmospheric models, we demonstrate the performance and very good scalability of Krylov subspace solvers and multigrid algorithms for a representative model equation with more than 1010 unknowns on 65 536 cores on the High-End Computing Terascale Resource (HECToR), the UK's national supercomputer. Here, we tested and optimized solvers from two existing numerical libraries (the Distributed and Unified Numerics Environment (DUNE) and Parallel High Performance Preconditioners (hypre)) and implemented both a conjugate gradient solver and a geometric multigrid algorithm based on a tensor-product approach, which exploits the strong vertical anisotropy of the discretized equation. We study both weak and strong scalability and compare the absolute solution times for all methods; in contrast to one-level methods, the multigrid solver is robust with respect to parameter variations.

58 GEOSCIENCES↗

DOE OSTI2024

Short-Term Probabilistic Solar Forecasting via Reinforcement Learning over ECMWF

In this paper, we present an innovative reinforcement learning approach for short-term solar forecasting, leveraging data from the European Centre for Medium-Range Weather Forecasts (ECMWF). The methodology begins with the application of the System Advisor Model (SAM) to transform various ECMWF numerical weather prediction members into predictive photovoltaic power generation. To enhance the precision of deterministic forecasting, we introduce a dynamic model selection algorithm based on Q-learning. This algorithm dynamically identifies and utilizes the most accurate ensemble member for forecasting purposes. Furthermore, we employ a support vector regression surrogate model with a Gaussian distribution to generate probabilistic forecasts, providing a holistic view of solar energy generation uncertainty. To expedite the training process and make it more practical for real-world applications, we integrate a rolling update workflow. This innovative workflow reduces the training period from months to a mere 19 days, making our method highly efficient. Numerical results of the case study show that in comparison to benchmark models, the proposed method improves the deterministic and probabilistic solar forecasting accuracy by up to 40.84% and 48.42%, respectively.

ensemble forecasting↗

NASA NTRS1994

North African savanna fires and atmospheric carbon dioxide

The effect of north African savanna fires on atmospheric CO2 is investigated using a tracer transport model. The model uses winds from operational numerical weather prediction analyses and provides CO2 concentrations as a function of space and time. After a spin-up period of several years, biomass-burning sources are added, and model experiments are run for an additional year, utilizing various estimates of CO2 sources. The various model experiments show that biomass burning in the north African savannas significantly affects CO2 concentrations in South America. The effect is more pronounced during the period from January through March, when biomass burning in South America is almost nonexistent. During this period, atmospheric CO2 concentrations in parts of South America typically may increase by 0.5 to 0.75 ppm at 970 mbar, the average pressure of the lowest model layer. These figures are above the probable uncertainty level, as model runs with biomass-burning sources estimated from independent studies using distinct data sets and techniques indicate. From May through September, when severe biomass burning occurs in South America, the effect of north African savanna fires over South America has become generally small at 970 mbar, but north of the equator it may be of the same magnitude or larger than the effect of South American fires. The CO2 concentration increase in the extreme northern and southern portions of South America, however, is mostly due to southern African fires, whose effect may be 2-3 times larger than the effect of South American fires at 970 mbar. Even in the central part of the continent, where local biomass-burning emissions are maximum, southern African fires contribute to at least 15% of the CO2 concentration increase at 970 mbar. At higher levels in the atmosphere, less CO2 emitted by north African savanna fires reaches South America, and at 100 mbar no significant amount of CO2 is transported across the Atlantic Ocean. The vertical structure of the CO2 concentration increase due to biomass burning differs substantially, depending on whether sources are local or remote. A prominent maximum of CO2 concentration increase in the lower layers characterizes the effect of local sources, whereas a more homogeneous profile of CO2 concentration increase characterizes the effect of remote sources. The results demonstrate the strong remote effects of African biomoass burning which, owing to the general circulation of the atmosphere, are felt as far away as South America.

Iacobellis, Sam F.↗

NASA NTRS2009

Developing a Model-based Capability to Analyze Requirements for the Climate Observing System

Models are foundational for estimating states of the earth's climate system, both as tools to extrapolate information in time and space, and as observation 'operators' used to relate what is analyzed and predicted to what is observed. Expanding the simulation approach further, observing system simulation experiments (OSSEs) are designed to mimic the complete process of analyzing the climate state by replacing real observations with entirely simulated ones determined from a model-based depiction of nature. OSSEs provide a framework to 'fly' simulated satellite instruments through a synthetic atmosphere and investigate the trade-spaces of measurements for various satellite configurations and sampling strategies, and assess their measurement impact on modeling and forecasting capabilities. Such a tool is a crucial but as yet unfulfilled need for future mission selection and design. The components of a state-of-the-art OSSE system are being assembled at the Global Modeling and Assimilation Office (GMAO, Code 610.1) at NASA/GSFC, leveraging on the GMAO's existing modeling and data assimilation infrastructure for numerical weather prediction (NWP). The OSSE framework is based on the GMAO's Goddard Earth Observing System atmospheric general circulation model, version 5 (GEOS-5) and the Gridpoint Statistical Interpolation (GSI) observational analysis scheme, combined with the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) model developed by the Atmospheric Chemistry and Dynamics Branch (Code 613.3). This system is an evolving, key component of Goddard's planned development of an Integrated Earth System Analysis (IESA) capability, which will bring together into a single, fully interactive system Goddard's modeling and assimilation efforts in atmosphere, ocean and chemistry and aerosols to provide a comprehensive analysis and prediction system for weather and climate In addition to providing a state-of-the-art capability for assimilating current observation types, GEOS-5, and the future IESA, provide the capability to identify the need for, and assess the potential impact of, future observing systems under consideration for improving weather and climate prediction.

Gelaro, Ronald↗