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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Historic Global Biomass Burning Emissions for CMIP6 (BB4CMIP) Based on Merging Satellite Observations with Proxies and Fire Models (1750-2015)

Fires have influenced atmospheric composition and climate since the rise of vascular plants, and satellite data has shown the overall global extent of fires. Our knowledge of historic fire emissions has progressively improved over the past decades due mostly to the development of new proxies and the improvement of fire models. Currently there is a suite of proxies including sedimentary charcoal records, measurements of fire-emitted trace gases and black carbon stored in ice and firn, and visibility observations. These proxies provide opportunities to extrapolate emissions estimates based on satellite data starting in 1997, but each proxy has strengths and weaknesses regarding, for example, the spatial and temporal extents over which they are representative. We developed a new historic biomass burning emissions dataset starting in 1750 that merges the satellite record with several existing proxies, and uses the average of six models from the Fire Model Intercomparison Project (FireMIP) protocol to estimate emissions when the available proxies had limited coverage. According to our approach, global biomass burning emissions were relatively constant with 10-year averages varying between 1.8 and 2.3 petagrams of carbon per year. Carbon emissions increased only slightly over the full time period and peaked during the 1990's after which they decreased gradually. There is substantial uncertainty in these estimates and patterns varied depending on choices regarding data representation, especially on regional scales. The observed pattern in fire carbon emissions is for a large part driven by African fires, which accounted for 58 percent of global fire carbon emissions. African fire emissions declined since about 1950 due to conversion of savanna to cropland, and this decrease is partially compensated for by increasing emissions in deforestation zones of South America and Asia. These global fire emissions estimates are mostly suited for global analyses and will be used in the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations.

Biomass burning; Satellite observations; computer ↗
NASA NTRS2021

A multi-model CMIP6-PMIP4 study of Arctic sea ice at 127 ka: sea ice data compilation and model differences

The Last Interglacial period (LIG) is a period with increased summer insolation at high northern latitudes, which results in strong changes in the terrestrial and marine cryosphere. Understanding the mechanisms for this response via climate modelling and comparing the models' representation of climate reconstructions is one of the objectives set up by the Paleoclimate Modelling Intercomparison Project for its contribution to the sixth phase of the Coupled Model Intercomparison Project. Here we analyse the results from 16 climate models in terms of Arctic sea ice. The multi-model mean reduction in minimum sea ice area from the pre industrial period (PI) to the LIG reaches 50 % (multi-model mean LIG area is 3.20×10^6 sq.km, compared to 6.46×10^6 sq.km for the PI). On the other hand, there is little change for the maximum sea ice area (which is 15–16×10^6 sq.km for both the PI and the LIG. To evaluate the model results we synthesise LIG sea ice data from marine cores collected in the Arctic Ocean, Nordic Seas and northern North Atlantic. The reconstructions for the northern North Atlantic show year-round ice-free conditions, and most models yield results in agreement with these reconstructions. Model–data disagreement appear for the sites in the Nordic Seas close to Greenland and at the edge of the Arctic Ocean. The northernmost site with good chronology, for which a sea ice concentration larger than 75 % is reconstructed even in summer, discriminates those models which simulate too little sea ice. However, the remaining models appear to simulate too much sea ice over the two sites south of the northernmost one, for which the reconstructed sea ice cover is seasonal. Hence models either underestimate or overestimate sea ice cover for the LIG, and their bias does not appear to be related to their bias for the pre-industrial period. Drivers for the inter-model differences are different phasing of the up and down short-wave anomalies over the Arctic Ocean, which are associated with differences in model albedo; possible cloud property differences, in terms of optical depth; and LIG ocean circulation changes which occur for some, but not all, LIG simulations. Finally, we note that inter-comparisons between the LIG simulations and simulations for future climate with moderate (1 %/yr) CO2 increase show a relationship between LIG sea ice and sea ice simulated under CO2 increase around the years of doubling CO2. The LIG may therefore yield insight into likely 21st century Arctic sea ice changes using these LIG simulations.

Arctic sea ice↗
NASA NTRSDate not supplied

NASA Earth Exchange – Current overview of climate and wildfire-oriented works

NASA Earth Exchange (NEX) combines state-of-the-art supercomputing, Earth system modeling, and NASA remote sensing data feeds to deliver a work environment for exploring and analyzing petabyte-scale datasets covering large regions, continents, or the globe. As an accessible platform, NEX can accelerate fundamental research, develop new applications, and reduce overall project costs by providing the research community with data, software, and high-end computing power. Two research thrusts for the NEX community are developing and distributing the NEX-GDDP-CMIP6 downscaled climate dataset and the community-driven wildfire research. NEX-GDDP-CMIP6 dataset is comprised of global downscaled climate scenarios derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across two of the four “Tier 1” greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). The wildfire research thrust leverages geostationary and low earth orbit remote sensing platforms and advanced modeling (WRF). We present a high-level overview of the NEX community, discuss relevant datasets and show several visualization techniques of data used in the wildfire research activity.

NEX↗
NASA NTRS2021

Large-scale features of Last Interglacial climate: results from evaluating the lig127k simulations for the Coupled Model Intercomparison Project (CMIP6)–Paleoclimate Modeling Intercomparison Project (PMIP4)

The modeling of paleoclimate, using physically based tools, is increasingly seen as a strong out-of-sample test of the models that are used for the projection of future climate changes. New to the Coupled Model Intercomparison Project (CMIP6) is the Tier 1 Last Interglacial experiment for 127 000 years ago (lig127k), designed to address the climate responses to stronger orbital forcing than the midHolocene experiment, using the same state-of-the-art models as for the future and following a common experimental protocol. Here we present a first analysis of a multi-model ensemble of 17 climate models, all of which have completed the CMIP6 DECK (Diagnostic, Evaluation and Characterization of Klima) experiments. The equilibrium climate sensitivity (ECS) of these models varies from 1.8 to 5.6°C. The seasonal character of the insolation anomalies results in strong summer warming over the Northern Hemisphere continents in the lig127k ensemble as compared to the CMIP6 piControl and much-reduced minimum sea ice in the Arctic. The multi-model results indicate enhanced summer monsoonal precipitation in the Northern Hemisphere and reductions in the Southern Hemisphere. These responses are greater in the lig127k than the CMIP6 midHolocene simulations as expected from the larger insolation anomalies at 127 than 6 ka. New synthesis for surface temperature and precipitation, targeted for 127 ka, have been developed for comparison to the multi-model ensemble. The lig127k model ensemble and data reconstructions are in good agreement for summer temperature anomalies over Canada, Scandinavia, and the North Atlantic and for precipitation over the Northern Hemisphere continents. The model–data comparisons and mismatches point to further study of the sensitivity of the simulations to uncertainties in the boundary conditions and of the uncertainties and sparse coverage in current proxy reconstructions. The CMIP6–Paleoclimate Modeling Intercomparison Project (PMIP4) lig127k simulations, in combination with the proxy record, improve our confidence in future projections of monsoons, surface temperature, and Arctic sea ice, thus providing a key target for model evaluation and optimization.

Last Interglacial climate↗
NASA NTRS1978

Extreme ultraviolet composite spectra of representative solar features

The spectral identifications and absolute intensities of lines in the EUV spectrum for various solar features, such as the quiet sun, active regions, coronal holes, and the off-limb corona, are presented and discussed. Composite spectra have been assembled and processed from the ATM ultraviolet spectrometer data with a spectral resolution of 1.6 A over the range 280-1350 A. These spectra represent a self-consistent set of observations with good photometric calibration, in which intercomparison of intensities from different regions is used to assist in line identifications and to draw general conclusions on average physical conditions in the solar atmosphere. The quiet-sun line intensities obtained near solar minimum are compared with OSO 6 results near solar maximum to provide an estimate for the changes over the solar cycle.

Vernazza, J. E.↗
NASA NTRS1986

Investigation of scene identification algorithms for radiation budget measurements

The computation of Earth radiation budget from satellite measurements requires the identification of the scene in order to select spectral factors and bidirectional models. A scene identification procedure is developed for AVHRR SW and LW data by using two radiative transfer models. These AVHRR GAC pixels are then attached to corresponding ERBE pixels and the results are sorted into scene identification probability matrices. These scene intercomparisons show that there generally is a higher tendency for underestimation of cloudiness over ocean at high cloud amounts, e.g., mostly cloudy instead of overcast, partly cloudy instead of mostly cloudy, for the ERBE relative to the AVHRR results. Reasons for this are explained. Preliminary estimates of the errors of exitances due to scene misidentification demonstrates the high dependency on the probability matrices. While the longwave error can generally be neglected the shortwave deviations have reached maximum values of more than 12% of the respective exitances.

Diekmann, F. J.↗
NASA NTRS1989

Investigation of scene identification algorithms for radiation budget measurements

The computation of earth radiation budget from satellite measurements requires the identification of the scene in order to select spectral factors and bidirectional models. A scene identification procedure is developed for AVHRR SW and LW data by using two radiative transfer models. These AVHRR GAC pixels are then attached to corresponding ERBE pixels and the results are sorted into scene identification probability matrices. These scene intercomparisons show that there generally is a higher tendency for underestimation of cloudiness over ocean at high cloud amounts, e.g., mostly cloudy instead of overcast, partly cloudy instead of mostly cloudy, for the ERBE relative to the AVHRR results. Reasons for this are explained. Preliminary estimates of the errors of exitances due to scene misidentification demonstrates the high dependency on the probability matrices. While the longwave error can generally be neglected the shortwave deviations have reached maximum values of more than 12 percent of the respective exitances.

Diekmann, F. J.↗
NASA NTRS1989

An intercomparison of longwave measurements by ERBE radiometers on the NOAA-9 and ERBS satellites

Two instrument modules of each satellite on which the Earth Radiation Budget Experiment (ERBE) is orbiting observe components of the earth radiation budget with three different scales of earth view. An intercomparison of longwave measurements by these instruments provides relative information concerning radiometric performance at satellite altitude, techniques of estimating upwelling exitances, and an end-to-end evaluation of the data processing system. Results indicate that the ERBE radiometers are mildly sensitive to varying thermal loads from the spacecraft and/or the earth-space environment. Radiometric variations at the satellite and methods of data interpretation contribute about equally to the uncertainty of radiant exitances from the earth.

House, Frederick B.↗
NASA NTRS2005

Validation of AIRS/AMSU Cloud Retrievals Using MODIS Cloud Analyses

The AIRS/AMSU (flying on the EOS-AQUA satellite) sounding retrieval methodology allows for the retrieval of key atmospheric/surface parameters under partially cloudy conditions (Susskind et al.). In addition, cloud parameters are also derived from the AIRS/AMSU observations. Within each AIRS footprint, cloud parameters at up to 2 cloud layers are determined with differing cloud top pressures and effective (product of infrared emissivity at 11 microns and physical cloud fraction) cloud fractions. However, so far the AIRS cloud product has not been rigorously evaluated/validated. Fortunately, collocated/coincident radiances measured by MODIS/AQUA (at a much lower spectral resolution but roughly an order of-magnitude higher spatial resolution than that of AIRS) are used to determine analogous cloud products from MODIS. This allows us for a rather rare and interesting possibility: the intercomparisons and mutual validation of imager vs. sounder-based cloud products obtained from the same satellite positions. First, we present results of small-scale (granules) instantaneous intercomparisons. Next, we will evaluate differences of temporally averaged (monthly) means as well as the representation of inter-annual variability of cloud parameters as presented by the two cloud data sets. In particular, we present statistical differences in the retrieved parameters of cloud fraction and cloud top pressure. We will investigate what type of cloud systems are retrieved most consistently (if any) with both retrieval schemes, and attempt to assess reasons behind statistically significant differences.

Molnar, Gyula I.↗
NASA NTRS2020

An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation

To better understand and characterize current uncertainties in the important observational constraint of climate models of aerosol optical depth (AOD), we evaluate and intercompare 14 satellite products, representing nine different retrieval algorithm families using observations from five different sensors on six different platforms. The satellite products (super-observations consisting of 1°×1° daily aggregated retrievals drawn from the years 2006, 2008 and 2010) are evaluated with AErosol RObotic NETwork (AERONET) and Maritime Aerosol Network (MAN) data. Results show that different products exhibit different regionally varying biases (both under- and overestimates) that may reach ±50 %, although a typical bias would be 15 %–25 % (depending on the product). In addition to these biases, the products exhibit random errors that can be 1.6 to 3 times as large. Most products show similar performance, although there are a few exceptions with either larger biases or larger random errors. The intercomparison of satellite products extends this analysis and provides spatial context to it. In particular, we show that aggregated satellite AOD agrees much better than the spatial coverage (often driven by cloud masks) within the 1°×1° grid cells. Up to ∼50 % of the difference between satellite AOD is attributed to cloud contamination. The diversity in AOD products shows clear spatial patterns and varies from 10 % (parts of the ocean) to 100 % (central Asia and Australia). More importantly, we show that the diversity may be used as an indication of AOD uncertainty, at least for the better performing products. This provides modellers with a global map of expected AOD uncertainty in satellite products, allows assessment of products away from AERONET sites, can provide guidance for future AERONET locations and offers suggestions for product improvements. We account for statistical and sampling noise in our analyses. Sampling noise, variations due to the evaluation of different subsets of the data, causes important changes in error metrics. The consequences of this noise term for product evaluation are discussed.

Aerosol↗
NASA NTRS1994

Global reference frame: Intercomparison of results (SLR, VLBI and GPS)

The terrestrial reference frame (TRF) is realized by a set of positions and velocities derived from a combination of the three space geodetic techniques, SLR, VLBI and GPS. The standard International TRF is constructed by the International Earth Rotation Service in such a way that it is stable with time and the addition of new data. An adopted model for overall plate motion, NUVEL-1 NNR, defines the conceptual reference frame in which all the plates are moving. In addition to the measurements made between reference points within the space geodetic instruments, it is essential to have accurate, documented eccentricity measurements from the instrument reference points to ground monuments. Proper local surveys between the set of ground monuments at a site are also critical for the use of the space geodetic results. Eccentricities and local surveys are, in fact, the most common and vexing sources of error in the use of the TRF for such activities as collocation and intercomparison.

Ma, Chopo↗
NASA NTRS2002

MPL-Net Measurements of Aerosol and Cloud Vertical Distributions at Co-Located AERONET Sites

In the early 1990s, the first small, eye-safe, and autonomous lidar system was developed, the Micropulse Lidar (MPL). The MPL acquires signal profiles of backscattered laser light from aerosols and clouds. The signals are analyzed to yield multiple layer heights, optical depths of each layer, average extinction-to-backscatter ratios for each layer, and profiles of extinction in each layer. In 2000, several MPL sites were organized into a coordinated network, called MPL-Net, by the Cloud and Aerosol Lidar Group at NASA Goddard Space Flight Center (GSFC) using funding provided by the NASA Earth Observing System. tn addition to the funding provided by NASA EOS, the NASA CERES Ground Validation Group supplied four MPL systems to the project, and the NASA TOMS group contributed their MPL for work at GSFC. The Atmospheric Radiation Measurement Program (ARM) also agreed to make their data available to the MPL-Net project for processing. In addition to the initial NASA and ARM operated sites, several other independent research groups have also expressed interest in joining the network using their own instruments. Finally, a limited amount of EOS funding was set aside to participate in various field experiments each year. The NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project also provides funds to deploy their MPL during ocean research cruises. All together, the MPL-Net project has participated in four major field experiments since 2000. Most MPL-Net sites and field experiment locations are also co-located with sunphotometers in the NASA Aerosol Robotic Network. (AERONET). Therefore, at these locations data is collected on both aerosol and cloud vertical structure as well as column optical depth and sky radiance. Real-time data products are now available from most MPL-Net sites. Our real-time products are generated at times of AERONET aerosol optical depth (AOD) measurements. The AERONET AOD is used as input to our processing routines, which calculate the aerosol layer top height and extinction profile, and our MPL calibration value. A variety of other data products are available or under development. We present an overview of the MPL-Net project and discuss data products useful to the AERONET community. Results from several sites and field experiments will be presented.

Welton, Ellsworth J.↗
NASA NTRS1985

Intercomparison of global SST fields derived from satellite sensors and ship observations

Near global comparisons were made between binned forms of SST obtained from different instruments, ship meteorological observations, and the output of a meteorological model. Binning hereinafter means gridding by simple summation of data values in a bin, which in this study was a 2 deg. x 2 deg. box or a 10 deg. x 10 box surrounding a grid node. In the binned comparisons, the question is asked: are the binned data from two instruments drawn from the same population? The first two measures of statistical moments of the populations are used to test the hypothesis that they are. Comparisons were also attempted between raw forms of the various SST retrievals, using a structure function analysis. The results of this analysis were relatively uninteresting and are therefore omitted.

Pazan, S. E.↗
NASA NTRS1990

Operational overview of NASA GTE/CITE 2 airborne instrument intercomparisons - Nitrogen dioxide, nitric acid, and peroxyacetyl nitrate

This paper provides the rationale, objectives, approach, and a brief description of the instrumentation included in the second airborne Chemical Instrumentation Test and Evaluation (CITE 2) mission conducted on NASA's Electra aircraft. CITE 2 intercompared data from instruments measuring NO2, HNO3, and PAN in the troposphere. This study, conducted in August 1986, encountered marine and continental air with free tropospheric mixing ratios of NO2, HNO3, and PAN typically less than 120, 150, and 200 parts per trillion by volume, respectively.

Hoell, James M., Jr.↗
NASA NTRS1997

Technical Report Series on Global Modeling and Data Assimilation: Interannual Variability and Potential Predictability in Reanalysis Products - Volume 13

The Data Assimilation Office (DAO) at Goddard Space Flight Center and the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) have produced multi-year global assimilations of historical data employing fixed analysis systems. These "reanalysis" products are ideally suited for studying short-term climatic variations. The availability of multiple reanalysis products also provides the opportunity to examine the uncertainty in the reanalysis data. The purpose of this document is to provide an updated estimate of seasonal and interannual variability based on the DAO and NCEP/NCAR reanalyses for the 15-year period 1980-1995. Intercomparisons of the seasonal means and their interannual variations are presented for a variety of prognostic and diagnostic fields. In addition, atmospheric potential predictability is re-examined employing selected DAO reanalysis variables.

Min, Wei↗
NASA NTRS2014

The Parallel System for Integrating Impact Models and Sectors (pSIMS)

We present a framework for massively parallel climate impact simulations: the parallel System for Integrating Impact Models and Sectors (pSIMS). This framework comprises a) tools for ingesting and converting large amounts of data to a versatile datatype based on a common geospatial grid; b) tools for translating this datatype into custom formats for site-based models; c) a scalable parallel framework for performing large ensemble simulations, using any one of a number of different impacts models, on clusters, supercomputers, distributed grids, or clouds; d) tools and data standards for reformatting outputs to common datatypes for analysis and visualization; and e) methodologies for aggregating these datatypes to arbitrary spatial scales such as administrative and environmental demarcations. By automating many time-consuming and error-prone aspects of large-scale climate impacts studies, pSIMS accelerates computational research, encourages model intercomparison, and enhances reproducibility of simulation results. We present the pSIMS design and use example assessments to demonstrate its multi-model, multi-scale, and multi-sector versatility.

crop modeling↗
NASA NTRS1998

Tropospheric- Stratospheric Measurement Studies Summary

The two high altitude aircraft, ER-2 NASA #706 and 709 and the DC-8 NASA #717 are in active use in several programs of upper atmospheric research to study polar ozone changes, stratospheric-tropospheric exchange processes and atmospheric effects of aviation aircraft. The ER-2 has participated in seven major missions which mainly concentrated on vortex dynamics and the large losses of Ozone in the Polar regions (Ozone hole) observed in the spring. One mission verified the complex dynamical chemical and physical processes that occur during sunrise and sunset. Stratospheric Tracers of Atmospheric Transport (STRAT) obtained background measurements using the full ER-2 suite of instruments. Photochemistry of Ozone Loss in the Arctic Region in Summer (POLARIS) in 1997 assisted in understanding the mid-latitude and Arctic Ozone losses during the Northern Summer. The DC-8 with the Meteorological Measurement System (MMS) has participated in the Subsonic Aircraft: Cloud and Contrail Effects Special Study (SUCCESS), in 1996 and the Subsonic assessment Ozone and Nitrogen oxide experiment (SONEX) in 1997 missions. The MMS with its sophisticated software accurately measures ground speed and attitude, in-situ static and dynamic pressure total temperature, which are used to calculate the three dimensional wind fields, static pressure, temperature and turbulence values to meteorological accuracy. The meteorological data is not only of interest for its own sake in atmospheric dynamical processes such as mountain waves and flux measurements; but is also required by other ER-2 experiments that simultaneously measure water vapor, O3, aerosols, NO, HCl, CH4, N2O, ClO, BrO, CO2, NOy, HOx and temperature gradients. MMS products are extensively used to assist in the interpretation of their results in understanding the importance of convective effects relative to in-situ chemical changes, as may be noted by examining the list of references attached. The MMS consists of three subsystems: (a) aircraft instrumentation, inertial navigation system (INS), static and dynamic pressure taps, (b) additional dedicated instrumentation measuring angle of attack, yaw, total temperature, and a GPS which on the DC-8 measures position, velocity and attitude (c) an on board data, storage and computing acquisition system. This instrumentation and the associated software requires both an on-going laboratory ground calibration procedure for the total air temperature, static and total pressure inputs, verification of the INS dynamic response and also extensive air measurements and intercomparisons which ultimately verify and calibrate the complete system and its software. More than the usual accuracy is required because of the near cancellation occurring in the difference between the ground speed and true airspeed vectors used to give the wind vector. In the past year we have redesigned, recalibrated and used the MMS system on the NASA DC-8 that was previously used in the SUCCESS mission for the SONEX mission. Two papers were co-authored based on SUCCESS flights. Several reports and handouts were written for SONEX. Calibrations of the DC-8 pressure transducer temperature measuring thermistors was completed and an extensive analysis spanning several years of data files of the DC-8 Rosemount pressure transducer calibrations was done.

Browen, Stuart W.↗
NASA NTRS1979

Intercomparison of GEOS 3 tracking systems

Measurements and time biases of the GEOS 3 tracking systems in the Atlantic calibration area were determined in relation to the Goddard lasers. In collocation tests the lasers agreed with each other to about 10 cm. Early RAMLAS laser data contained an apparent time bias of 647 microsec. Later, in a laser collocation test, RAMLAS differed from MOBLAS 2 by +11.3 cm and -28 microsec. An overlooked correction reduced the -28 microsec to -8 microsec. The geoceivers initially had range rate biases of 3-6 m/s and constant time biases of several milliseconds. During the first month of GEOS 3 operations the range rate biases decreases monotonically by 2.5 + or - 1.0 m/s. The C band radar biases relative to the lasers were usually within several meters and several tenths of milliseconds. The unified S band system relative biases were usually within + or - 4 mm/s and + or - 0.1 ms. The average and scatter of the altimeter biases recovered on 18 laser reference arcs was - 5.3 + or - 0.6 m.

Berbert, J. H.↗