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Fred G. Rose

Publications and source records attributed to Fred G. Rose.

12 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

A Synopsis of AIRS Global-Mean Clear-Sky Radiance Trends From 2003 to 2020

Atmospheric Infrared Sounder (AIRS) aboard the National Aeronautics and Space Administration (NASA) Aqua satellite has been operating since September 2002. Its information content, superb instrument performance, and dense sampling pattern make the AIRS radiances an invaluable data set for climate studies. The trends of global-mean, nadir-view, clear-sky AIRS radiances from 2003 to 2020 are studied here, together with the counterparts of synthetic radiances based on two reanalyzes, European Centre for Medium-Range Weather Forecasts Reanalysis V5 (ECMWF ERA5) and NASA Goddard Earth Observing System V5.4.1 (GEOS-5.4.1; a reanalysis product without assimilation of hyperspectral radiances such as AIRS). The AIRS observation shows statistically significant negative trends in most of its CO2 channels, positive but non-significant trends in the channels over the window regions, and statistically significant positive trends in some of its H2O channels. The best agreements between observed and simulated radiance trends are seen over the CO2 tropospheric channels, while the observed and simulated trends over the CO2 stratospheric channels are opposite. ERA5 results largely agree with the AIRS observation over the H2O channels. The comparison in the H2O channels helps reveal a data continuity issue in the GEOS-5.4.1. Contributions from individual variables to the radiance trends are also assessed by performing separate simulations. This study provides the first synopsis of the global-mean trend of AIRS radiances over all its thermal-IR channels.

CO2↗
NASA NTRS2019

Decomposing Shortwave Top-of-Atmosphere and Surface Radiative Flux Variations in Terms of Surface and Atmospheric Contributions

Adiagnostic tool for determining surface and atmospheric contributions to interannual variations in top-of-atmosphere (TOA) reflected shortwave (SW) and net downward SW surface radiative fluxes is introduced. The method requires only upward and downward radiative fluxes at the TOA and surface as input and therefore can readily be applied to both satellite-derived and model-generated adiative fluxes. Observations from the Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Edition 4.0 product show that 81% of the monthly variability in global mean reflected SW TOA flux anomalies is associated with atmospheric variations (mainly clouds),6%is from surface variations, and 13% is from atmosphere–surface covariability. Over the Arctic Ocean, most of the variability in both reflected SW TOA flux and net downward SW surface flux anomalies is explained by variations in sea ice and cloud fraction alone (r2 5 0.94). Compared to CERES, variability in two reanalyses—the ECMWF interim reanalysis (ERA-Interim) and NASA’s Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2)—show large differences in the regional distribution of variance for both the atmospheric and surface contributions to anomalies in net downward SW surface flux. For MERRA-2 the atmospheric contribution is 17% too large compared to CERES while ERA-Interim underestimates the variance by 15%. The difference is mainly due to how cloud variations are represented in the reanalyses. The overall surface contribution in both ERA-Interim and MERRA-2 is smaller than CERES EBAF by 15% for ERA-Interim and 58% for MERRA-2, highlighting limitations of the reanalyses in representing surface albedo variations and their influence on SW radiative fluxes.

Norman G. Loeb↗
NASA NTRSDate not supplied

TPSAS-NF1676L-10726-DND

The principal component radiative transfer model PCRTM (Xu 2006) simulates spectral longwave radiance at a 0.5cm-1 resolution over the wavelengths (50-2760cm-1) using 280 principal components. The CERES product SSF containing CERES field-of-view (FOV) cloud properties based on MODIS pixel information are used as inputs. NASA GMAO(Global Modeling and Assimilation Office)Geos-4 temperature and humidity profiles, as well as SMOBA (Stratosphere Monitoring Ozone Blended Analysis) ozone profiles allow computations for five years (Jan 2001- Dec 2006) of FOV nadir spectral radiance. The approximately twice daily FOV PCRTM simulations along with CERES broadband measurements are time-space averaged to 10deg zonal monthly data. Analysis of monthly seasonal and deseasonalized interannual variability in terms of brightness temperature are presented. Comparison of interannual variability in the portions of the spectrum seen by the AIRS instrument are shown. Comparisons of spectral integrated PCRTM simulations to CERES broadband longwave radiance measurements are made. In order to study the sensitivity of the spatially and temporally averaged TOA spectrum to various atmospheric properties, we perturbed atmospheric and surface temperatures, humidity, cloud height, cloud fraction, and particle size. The sensitivity of the spectrum to these properties depends on region and seasons. Month to month variability of the longwave spectra to these perturbations is 10 to 20% of the global monthly mean perturbation response. In addition, it depends on time period and size of the area used for averaging spectra. In this poster, the magnitude of sensitivity variability and how the sensitivity changes depending on temporal and spatial scale of averaging will be discussed.

Fred G. Rose↗
NASA NTRSDate not supplied

Towards a more realistic representation of NASA CERES-derived surface radiative fluxes during polar night: a comparison with the MOSAiC field campaign

The Arctic is one of the most sensitive regions of Earth to climate change, and yet remains one of the more difficult regions to both observe and simulate. The high latitude of the Arctic gives it some unusual features compared with much of Earth, such as large and variable sea ice cover, extensive mixed phase cloud cover, and the polar day/night cycle. These features significantly influence the radiative environment of the Arctic as well as the ability to observe it. The remoteness of the Arctic from most of civilization makes large volumes of in situ observations difficult to collect, and so satellite observations are a critical tool for observing the region, such as those from Clouds and the Earth’s Radiant Energy System (CERES). But validating the satellite radiative flux estimates is difficult because of the lack of in situ measurements. A useful remedy is utilizing measurements from field campaigns, such as the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition during 2019-2020. The extensive high-quality surface radiative flux and meteorological measurements collected from MOSAiC provide a useful check on flux retrievals from CERES instruments. Previous work compared MOSAiC and CERES surface radiative fluxes during the 2020 melt season (April-September). Errors in CERES fluxes were related to errors in estimated atmospheric optical depth and surface albedo. We conduct a similar assessment of CERES surface flux retrievals using MOSAiC data, but for the months of October through March instead. As this time period is mostly during polar night and twilight, the focus of the study is on longwave surface fluxes. To better understand the reasons for errors in CERES fluxes, we use the large set of meteorological measurements also collected by MOSAiC, including surface temperature, thermodynamic vertical profiles, surface turbulent fluxes, and cloud properties. For example, one notable possible source of error in the CERES estimate of surface downwelling longwave flux is the estimate of cloud base height when compared with MOSAiC W-band radar measurements – an overestimate of cloud base height yields an underestimate of the downwelling flux on the order of tens of W m2.

J. Brant Dodson↗
NASA NTRSDate not supplied

Direct Aerosol Radiative Effect Derived From CERES Data Products

The CERES team uses MODIS and VIIRS derived aerosol optical thickness to compute surface and in atmosphere irradiances. In producing the data products, aerosol optical thicknesses derived by Dark Target and Deep Blue algorithms are assimilated in an aerosol transport model. In addition, the aerosol transport model provides aerosol optical thicknesses under cloudy conditions and aerosol optical thicknesses over polar regions. These aerosol optical thicknesses are used for hourly irradiance computations in 11 grids. Global mean top-of-atmosphere direct aerosol radiative effects are -5.2 Wm-2 and -2.2 Wm-2 for, respectively, clear-sky and all-sky conditions. Spatial pattern of the trend of the computed clear-sky direct aerosol radiative effect agrees with that derived from CERES observations. In this presentation, the importance of seamless transition of aerosol optical thicknesses derived from MODIS to those derived from VIIRS is emphasized. Currently, the CERES team is working with MODIS dark target and deep blue teams to achieve the seamless transition in producing CERES Edition 4 data products.

Seiji Kato↗