Search NASA⌕ Search

SEARCH · Search NASA

Results for “model reanalysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Reanalysis Surface Mass Balance of the Greenland Ice Sheet along K-transect (2000-2014)

Accurate estimates of surface mass balance over the Greenland ice sheet (GrIS) would contribute to understanding the cause of recent changes and would help to better estimate the future contribution of the GrIS to sea-level rise. Given the limitations of in-situ measurement, modeling, and remote sensing, it is critical to explore the opportunity to merge the available data to better characterize the spatial and temporal variation of the GrIS surface mass balance (SMB). This work utilizes a particle batch smoother data assimilation technique that yields SMB estimates that benefit from the snow model Crocus and a 16-day albedo product derived from satellite remote sensing data. Comparison of the results against in-situ SMB measurements shows that the assimilation of the albedo product reduces the root mean square error (RMSE) of the posterior estimates of SMB by 51% and reduces bias by 95%.

Greenland Ice Sheet↗
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 NTRS2018

GEOS S2S-2_1 File Specification: GMAO Seasonal and Sub-Seasonal Forecast Output

The NASA GMAO seasonal (9 months) and subseasonal (45 days) forecasts are produced with the Goddard Earth Observing System (GEOS) Atmosphere-Ocean General Circulation Model and Data Assimilation System Version S2S-2_1. The new system replaces version S2S-1.0 described in Borovikov et al (2017), and includes upgrades to many components of the system. The atmospheric model includes an upgrade from a pre-MERRA-2 version running on a latitude-longitude grid at approx. 1 degree resolution to a current version running on a cubed sphere grid at approximately 1/2 degree resolution. The important developments are related to the dynamical core (Putman et al., 2011), the moist physics (''two-moment microphysics'' of Barahona et al., 2014) and the cryosphere (Cullather et al., 2014). As in the previous GMAO S2S system, the land model is that of Koster et al (2000). GMAO S2S-2_1 now includes the Goddard Chemistry Aerosol Radiation and Transport (GOCART, Colarco et al., 2010) single moment interactive aerosol model that includes predictive aerosols including dust, sea salt and several species of carbon and sulfate. The previous version of GMAO S2S specified aerosol amounts from climatology, which were used to inform the atmospheric radiation only. The ocean model includes an upgrade from MOM4 to MOM5 (Griffies 2012), and continues to be run on the tripolar grid at approximately 1/2 degree resolution in the tropics with 40 vertical levels. As in S2S-1.0, the sea ice model is from the Los Alamos Sea Ice model (CICE4, Hunke and Lipscomb 2010). The Ocean Data Assimilation System (ODAS) has been upgraded from the one described in Borovikov et al., 2017 to one that uses a modified version of the Penny, 2014 Local Ensemble Transform Kalman Filter (LETKF), and now assimilates along-track altimetry. The ODAS also does a nudging to MERRA-2 SST and sea ice boundary conditions. The atmospheric data assimilation fields used to constrain the atmosphere in the ODAS have been upgraded from MERRA to a MERRA-2 like system. The system is initialized using a MERRA-2-like atmospheric reanalysis (Gelaro et al. 2017) and the GMAO S2S-2_1 ocean analysis. Additional ensemble members for forecasts are produced with initial states at 5-day intervals, with additional members based on perturbations of the atmospheric and ocean states. Both subseasonal and seasonal forecasts are submitted to the National MultiModel Ensemble (NMME) project, and are part of the US/Canada multimodel seasonal forecasts (http://www.cpc.ncep.noaa.gov/products/NMME/). A large suite of retrospective forecasts (''hindcasts'') have been completed, and contribute to the calculation of the model's baseline climatology and drift, anomalies from which are the basis of the seasonal forecasts.

Seasonal Forecast↗
NASA NTRS2003

Long-Term Climatic Variations in the Almati Oblast in Central Asian Kazakhstan: Correlations between National Centers for Environmental Prediction (NCEP) Reanalysis II Results and Oblast Meteorological Station Data from 1949 to the Present

As part of a larger analysis of country systems described elsewhere, named a Crop Country Inventory, CCI, large variations in annual crop yield for selected climate sensitive agricultural regions or sub-regions within a country have been studied over extended periods in decades. These climate sensitive regions, principally responsible for large annual variations in an entire country s crop production, generally are characterized by distinctive patterns of atmospheric circulation and synoptic processes that result in large seasonal fluctuations in temperature, precipitation and soil moisture as well as other climate properties. The immediate region of interest is drought prone Kazakhstan in Central Asia, part of the Former Soviet Union, FSU. As a partial validation test in a dry southern region of Kazakhstan, the Almati Oblast was chosen. The Almati Oblast, a sub-region of Kazakhstan located in its southeast corner, is one of 14 oblasts within the Republic of Kazahstan. The climate data set used to characterize this region was taken from the results of the current maturely developed Global Climate Model, GCM. In this paper, the GCM results have been compared to the meteorological station data at the station locations, over various periods. If the empirical correlation of the data sets from both the GCM and station data is sufficiently significant, this would validate the use of the superior GCM profile mapping and integration for the climatic characterization of a sub-region. Precipitation values interpolated from NCEP Reanalysis II data, a global climate database spanning over 5 decades since 1949, have been statistically correlated with monthly-averaged station data from 1949 through 1993, and with daily station data from April through August, 1990 for the Almati Oblast in Kazakhstan. The resultant correlation is significant, which implies that the methodology may be extended to different regions globally for Crop Country Inventory studies.

Welker, Jean E.↗
NASA NTRS1994

Clouds, hazes, and the stratospheric methane abundance in Neptune

Analysis of high-spatial-resolution (approximately 0.8 arcsec) methane band and continuum imagery of Neptune's relatively homogeneous Equatorial Region yields significant constraints on (1) the stratospheric gaseous methane mixing ratio (f(sub CH4, S)), (2) the column abundances and optical properties of stratospheric and tropospheric hydrocarbon hazes, and (3) the wavelength-dependent single-scattering albedo of the 3-bar opaque cloud. From the center-to-limb behavior of the 7270-A and 8900-A CH4 bands, the stratospheric methane mixing ratios is limited to f(sub CH4, S) less than 1.7 x 10(exp -3), with a nominal value of f(sub CH4, S) = 3.5 x 10(exp -4), one to two orders of magnitude less than pre-Voyager estimates, but in agreement with a number of recent ultraviolet and thermal infrared measurements, and largely in agreement with the tropopause mixing ratio implied by Voyager temperature measurements. Upper limits to the stratospheric haze mass column abundance and 6190-A and 8900-A haze opacities are 0.61 micrograms/sq cm and 0.075 and 0.042, respectively, with nominal values of 0.20 micrograms/sq cm and 0.025 and 0.014 for the 0.2 micrometers radius particles preferred by the recent Voyager PPS analysis of Pryor et al. (1992). The tropospheric CH4 haze opacities are comparable to that found in the stratosphere, i.e., upper limits of 0.104 and 0.065 at 6190 A and 8900 A, respectively, with nominal values of 0.085 and 0.058. This indicates a column abundance less than 11.0 micrograms/sq cm, corresponding to the methane gas content within a well-mixed 3% methane tropospheric layer only 0.1 cm thick near the 1.5-bar CH4 condensation level. Conservative scattering is ruled out for the opaque cloud near 3 bars marking the bottom of the visible atmosphere. Specifically, we find cloud single-scattering albedos of 0.915 +/- 0.006 at 6340 A, 0.775 +/- 0.012 at 7490 A, and 0.803 +/- 0.010 at 8260 A. Global models utilizing a complete global spectrum confirm the red-absorbing character of the 3-bar cloud. The global-mean model has approximately 7.7 times greater stratospheric aerosol content than the Equatorial Region. An analysis of stratospheric haze precipitation rates indicates a steady-state haze production rate of 0.185-1.5 x 10(exp -14) g/sq cm/s, in agreement with recent theoretical photochemical estimates. Finally, reanalysis of the Voyager PPS 7500-A phase angle data utilizing the f(sub CH4, S) value derived here confirms the Pryor et al. result of a tropospheric CH4 haze opacity of a few tenths in the 22-30 degs S latitude region, several times that of the Equatorial Region or of the globe. The factor-of-10 reduction in f(sub CH4, S) below that assumed by Pryor et al. implies decreased gas absorption and consequently a decrease in the forward-scattering component of tropospheric aerosols.

Baines, Kevin H.↗
NASA NTRS2011

Observational Diagnoses of Extratropical Ozone STE from 2005-2010

The transport of ozone from the stratosphere to the extratropical troposphere is an important boundary condition to tropospheric chemistry. However, previous direct estimates from models and indirect estimates from observations have poorly constrained the magnitude of ozone stratosphere-troposphere exchange (STE). In this study we provide a direct diagnosis of the extratropical ozone STE using data from the Microwave Limb Sounder on Aura and output of the MERRA reanalysis over the time period from 2005 to the present. We find that the mean annual STE is about 275 Tg yr-1 and 205 Tg yr-1 in the NH and SH, respectively. The interannual variability of the magnitude is about twice as great in the NH than the SH. This variability is dominated by the seasonal variability during the late winter and spring. A comparison of the ozone flux to the mass flux reveals that there is not a simple relationship between the two quantities. This presentation will also examine the magnitude and distribution of ozone in the lower stratosphere relative to the years of maximum and minimum ozone STE

Olsen, Mark A.↗
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

Parameterization of Vertical Cloud Distribution from C3M and MERRA Data Using ML Method

Clouds play a key role in regulating the hydrological cycle and the Earth's radiative energy budget. However, global climate models (GCMs) with a horizontal grid spacing on the order of 100 km have limitations in representing sub-grid cloud dynamics with spatial scales on the order of 1 km, leading to potential uncertainties in cloud radiative feedback on the global scale. In our research, we will leverage the capabilities of Deep Machine Learning (DML) methods to construct parameterizations of sub-grid volumetric cloud fraction (VCF), which is the frequency of occurrence on a grid volume accumulated in the horizontal and vertical directions. Our investigation delves into the intricate relationship between VCF obtained from the NASA CALIPSO-CloudSat-CERES-MODIS (CCCM) satellite observation data and 3-D MERRA-2 reanalysis meteorological profiling data (e.g., wind, relative humidity, temperature). Through a comprehensive one-year data training utilizing the Sequence to Sequence DML method, we have successfully disentangled the complicated cloud formation dynamics across diverse meteorological conditions through a day-to-day analysis framework. Preliminary findings reveal promising statistical agreements in geographical and vertical distributions and seasonal variations of volumetric cloud fraction between ML prediction and satellite measurements. These results underscore the aptitude of our DML model to discern underlying cloud physical processes and accurately represent sub-grid cloud formation dynamics. Additionally, we have also employed trained neural network to analyze uncertainties arising from errors in meteorological data, further enhancing the robustness of our VCF parameterization.

Shan Zeng↗
NASA NTRS1986

Cometary atmospheres: Modeling the spatial distribution of observed neutral radicals

Progress during the second year of a program of research on the modeling of the spatial distributions of cometary radicals is discussed herein in several major areas. New scale length laws for cometary C2 and CN were determined which explain that the previously-held apparent drop of the C2/CN ratio for large heliocentric distances does not exist and that there is no systematic variation. Monte Carlo particle trajectory model (MCPTM) analysis of sunward and anti-sunward brightness profiles of cometary C2 was completed. This analysis implies a lifetime of 31,000 seconds for the C2 parent and an ejection speed for C2 of approximately 0.5 km/sec upon dissociation from the parent. A systematic reanalysis of published C3 and OH data was begun. Preliminary results find a heliocentric distance dependence for C3 scale lengths with a much larger variation than for C2 and CN. Scale lengths for OH are generally somewhat larger than currently accepted values. The MCPTM was updated to include the coma temperature. Finally, the collaborative effort with the University of Arizona programs has yielded some preliminary CCD images of Comet P/Halley.

Combi, Michael R.↗
NASA NTRS2004

A Subsonic Aircraft Design Optimization With Neural Network and Regression Approximators

The Flight-Optimization-System (FLOPS) code encountered difficulty in analyzing a subsonic aircraft. The limitation made the design optimization problematic. The deficiencies have been alleviated through use of neural network and regression approximations. The insight gained from using the approximators is discussed in this paper. The FLOPS code is reviewed. Analysis models are developed and validated for each approximator. The regression method appears to hug the data points, while the neural network approximation follows a mean path. For an analysis cycle, the approximate model required milliseconds of central processing unit (CPU) time versus seconds by the FLOPS code. Performance of the approximators was satisfactory for aircraft analysis. A design optimization capability has been created by coupling the derived analyzers to the optimization test bed CometBoards. The approximators were efficient reanalysis tools in the aircraft design optimization. Instability encountered in the FLOPS analyzer was eliminated. The convergence characteristics were improved for the design optimization. The CPU time required to calculate the optimum solution, measured in hours with the FLOPS code was reduced to minutes with the neural network approximation and to seconds with the regression method. Generation of the approximators required the manipulation of a very large quantity of data. Design sensitivity with respect to the bounds of aircraft constraints is easily generated.

Patnaik, Surya N.↗
NASA NTRS2012

Atmospheric Reanalyses-Recent Progress and Prospects for the Future. A Report from a Technical Workshop, April 2010

In April 2010, developers representing each of the major reanalysis centers met at Goddard Space Flight Center to discuss technical issues - system advances and lessons learned - associated with recent and ongoing atmospheric reanalyses and plans for the future. The meeting included overviews of each center s development efforts, a discussion of the issues in observations, models and data assimilation, and, finally, identification of priorities for future directions and potential areas of collaboration. This report summarizes the deliberations and recommendations from the meeting as well as some advances since the workshop.

Rienecker, Michele M.↗
NASA NTRS2015

Using Satellite Observations to Evaluate the AeroCOM Volcanic Emissions Inventory and the Dispersal of Volcanic SO2 Clouds in MERRA

Simulation of volcanic emissions in climate models requires information that describes the eruption of the emissions into the atmosphere. While the total amount of gases and aerosols released from a volcanic eruption can be readily estimated from satellite observations, information about the source parameters, like injection altitude, eruption time and duration, is often not directly known. The AeroCOM volcanic emissions inventory provides estimates of eruption source parameters and has been used to initialize volcanic emissions in reanalysis projects, like MERRA. The AeroCOM volcanic emission inventory provides an eruptions daily SO2 flux and plume top altitude, yet an eruption can be very short lived, lasting only a few hours, and emit clouds at multiple altitudes. Case studies comparing the satellite observed dispersal of volcanic SO2 clouds to simulations in MERRA have shown mixed results. Some cases show good agreement with observations Okmok (2008), while for other eruptions the observed initial SO2 mass is half of that in the simulations, Sierra Negra (2005). In other cases, the initial SO2 amount agrees with the observations but shows very different dispersal rates, Soufriere Hills (2006). In the aviation hazards community, deriving accurate source terms is crucial for monitoring and short-term forecasting (24-h) of volcanic clouds. Back trajectory methods have been developed which use satellite observations and transport models to estimate the injection altitude, eruption time, and eruption duration of observed volcanic clouds. These methods can provide eruption timing estimates on a 2-hour temporal resolution and estimate the altitude and depth of a volcanic cloud. To better understand the differences between MERRA simulations and volcanic SO2 observations, back trajectory methods are used to estimate the source term parameters for a few volcanic eruptions and compared to their corresponding entry in the AeroCOM volcanic emission inventory. The nature of these mixed results is discussed with respect to the source term estimates.

OMI SO2↗
NASA NTRS1993

Spectroscopic observations of the detached binary PG 1413 + 015

We present improved estimates of the stellar parameters of the eclipsing, precataclysmic binary system PG 1413 + 015 (GH Vir), which has an orbital period of only 8h16m. Model atmosphere fits a Balmer line profiles yield T(eff) = 48,800 +/- 1200 K and log g = 7.70 +/- 0.11 for the DAO white dwarf primary star, from which a mass of 0.51 +/- 0.04 solar mass is inferred using evolutionary models. An ultraviolet spectrum obtained with the IUE Observatory has a slope consistent with this temperature and the assumption of no interstellar extinction. A red CCD spectrum of the secondary star during the 12-minute total eclipse indicates a spectral type of M3 V-M5 V. Reanalysis of the eclipse light curve leads to an inferred radius of 0.15 solar radius and a mass of 0.10 solar mass for the secondary, the latter being marginally consistent with the spectral type. Reprocessing on the facing side of the secondary produces phase-dependent Balmer line emission and detectable variations in the continuum from 6500-9000 A. The observed levels of reprocessing are consistent with expectations based on the above stellar parameters.

Fulbright, Michael S.↗
NASA NTRS2023

Towards an Indian Land Data Assimilation System (ILDAS): A Coupled Hydrologic-Hydraulic System for Water Balance Assessments

Effective management of water resources requires reliable estimates of land surface states and fluxes, including water balance components. But most land surface models run in uncoupled mode and do not produce river discharge at catchment scales to be useful for water resources management applications. Such integrated systems are also rare over India where hydrometeorological extremes have wreaked havoc on the economy and people. So, an Indian Land Data Assimilation System (ILDAS) with a coupled land surface and a hydrodynamic model has been developed and driven by multiple meteorological forcings (0.1°, daily) to estimate land surface states, channel discharge, and floodplain inundation. ILDAS benefits from an integrated framework as well as the largest suite of observation records collected over India and has been used to produce a reanalysis product for 1981–2021 using four forcing datasets, namely, Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), ECMWF’s ERA-5, and Indian Meteorological Department (IMD) gridded precipitation. We assessed the uncertainty and bias in these precipitation datasets and validated all major components of the terrestrial water balance, i.e., surface runoff, soil moisture, terrestrial water storage anomalies, evapotranspiration, and streamflow, against a combination of satellite and in situ observation datasets. Our assessment shows that ILDAS can represent the hydrological processes reasonably well over the Indian landmass with IMD precipitation showing the best relative performance. Evaluation against ESA-CCI soil moisture shows that MERRA-2 based estimates outperform the others, whereas ERA-5 performs best in simulating evapotranspiration when evaluated against MODIS ET. Evaluations against observed records show that CHIRPS-based estimates have the highest performance in reconstructing surface runoff and streamflow. Once operational, this system will be useful for supporting transboundary water management decision making in the region.

Indian Land Data Assimilation System (ILDAS)↗
NASA NTRSDate not supplied

Evaluation of Planetary Boundary Layer Structure from NASA Global Modeling and Assimilation Office’s Next Retrospective Analysis Product MERRA-21C

The Planetary Boundary Layer (PBL) is a complex interface between Earth’s surface and the atmosphere with high spatiotemporal variability in its characteristics, and accurate simulation and observation of the PBL has proven to be a challenge. In this study, we evaluate PBL structures from NASA Global Modeling and Assimilation Office (GMAO)’s next retrospective analysis product: the Goddard Earth Observing System Retrospective Analysis of the early 21st Century (GEOS-R21C), with 25-km horizontal resolution. The GEOS-R21C incorporates a wide range of observing systems and various improvements over previous GMAO reanalysis. We compare the PBL thermodynamic structure as well as PBL Height (PBLH) from GEOS-R21C with various PBL observations. For PBLH, definitions are different depending on each observing system. PBLHs derived from radiosonde observations and Global Navigation Satellite System Radio Occultation (GNSS RO) are based on bulk Richardson number and refractivity gradient, respectively. The results of the evaluation of PBL structure from GMAO’s next retrospective analysis product will be presented. In addition, comparison between near-real-time (NRT) commercial and NASA commercial GNSS RO PBLH will also be discussed.

Eun-Gyeong Yang↗
NASA NTRS1983

Variability of carbon monoxide in the Mars atmosphere

Recent measurements and reanalyses of past measurements are used to derive estimates of the variability of CO concentrations in the Martian atmosphere. The J = 1 - 2 rotational transition of CO in the microwave spectrum of Mars was observed in January, 1982, and abundances were calculated through surface and atmospheric temperature modeling. A column density of 4.6 + or - 2.0 x 10 to the 20th/sq cm is obtained, which is contrasted with values of 3.0 + or - 1.0 x 10 to the 20th/sq cm in 1980 and 1.7 x + or - 0.9 x 10 to the 20th/sq cm in 1975 obtained by reanalysis of the J = 0 - 1 transition observed by Good and Schloerb (1981) and Kakar et al. (1977), respectively. It is noted that due to the uncertainties in global atmospheric average temperatures, results are consistent with a CO variability of from 0 to 100 percent over a time scale of several years. It is suggested that simultaneous measurements of the J = 0 - 1 and J = 1 - 2 transitions may provide stronger constraints on the CO abundance and atmospheric temperature of Mars.

Clancy, R. T.↗
NASA NTRS1995

Technical report series on global modeling and data assimilation. Volume 4: Documentation of the Goddard Earth Observing System (GEOS) data assimilation system, version 1

This report describes the analysis component of the Goddard Earth Observing System, Data Assimilation System, Version 1 (GEOS-1 DAS). The general features of the data assimilation system are outlined, followed by a thorough description of the statistical interpolation algorithm, including specification of error covariances and quality control of observations. We conclude with a discussion of the current status of development of the GEOS data assimilation system. The main components of GEOS-1 DAS are an atmospheric general circulation model and an Optimal Interpolation algorithm. The system is cycled using the Incremental Analysis Update (IAU) technique in which analysis increments are introduced as time independent forcing terms in a forecast model integration. The system is capable of producing dynamically balanced states without the explicit use of initialization, as well as a time-continuous representation of non- observables such as precipitation and radiational fluxes. This version of the data assimilation system was used in the five-year reanalysis project completed in April 1994 by Goddard's Data Assimilation Office (DAO) Data from this reanalysis are available from the Goddard Distributed Active Center (DAAC), which is part of NASA's Earth Observing System Data and Information System (EOSDIS). For information on how to obtain these data sets, contact the Goddard DAAC at (301) 286-3209, EMAIL daac@gsfc.nasa.gov.

Suarez, Max J.↗
NASA NTRS2017

The Role of DYNAMO in Situ Observations in Improving NASA Ceres-like Daily Surface and Atmospheric Radiative Flux Estimates

The daily surface and atmospheric radiative fluxes from NASA Clouds and the Earths RadiantEnergy System (CERES) Synoptic 1 degree (SYN1deg) Ed3A are among the most widely used data to studycloud-radiative feedback. The CERES SYN1deg data are based on Fu-Liou radiative transfer computations thatuse specific humidity (Q) and air temperature (T) from NASA Global Modeling and Assimilation Office (GMAO)reanalyses as inputs and are therefore subject to the quality of those fields. This study uses in situ Q and Tobservations collected during the Dynamics of the Madden-Julian Oscillation (DYNAMO) field campaign toaugment the input stream used in the NASA GMAO reanalysis and assess the impact on the CERES dailysurface and atmospheric longwave estimates. The results show that the assimilation of DYNAMOobservations considerably improves the vertical profiles of analyzed Q and T over and near DYNAMO stationsby moistening and warming the lower troposphere and upper troposphere and drying and cooling themid-upper troposphere. As a result of these changes in Q and T, the computed CERES daily surface downwardlongwave flux increases by about 5 W m(exp -2), due mainly to the warming and moistening in the lowertroposphere; the computed daily top-of-atmosphere (TOA) outgoing longwave radiation increases by2-3 W m(exp -2) during dry periods only. Correspondingly, the estimated local atmospheric longwave radiativecooling enhances by about 5 W m(exp -2) (7-8 W m(exp -2)) during wet (dry) periods. These changes reduce the bias inthe CERES SYN1deg-like daily longwave estimates at both the TOA and surface and represent animprovement over the DYNAMO region.

DYNAMO↗