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NASA NTRS2018

Data Assimilation of Terrestrial Water Storage to Adjust Precipitation Fluxes

The Gravity Recovery and Climate Experiment (GRACE) mission has provided unprecedented observations of terrestrial water storage (TWS) dynamics at basin to continental scales. TWS is defined as the sum of groundwater, soil moisture, snow, surface water, ice and biomass water. Data assimilation of GRACE TWS observations has been shown to improve simulation of groundwater, streamflow, and snow water equivalent, and has also proven useful for drought monitoring and identifying human impacts on the water cycle. From a modeling perspective, the TWS components are defined as "prognostic hydrological states". Existing GRACE data assimilation schemes update these prognostic states directly. In this work, we propose an alternate approach in which precipitation fluxes are adjusted in order to achieve the desired change in the hydrological prognostic states. Limitations of such an approach include the assumption that all errors in TWS originate from errors in precipitation. Nonetheless, benefits comprise (1) the water balance is maintained, as opposed to having to add increments to the water budget components, (2) the model automatically determines how to distribute the updates among the TWS prognostic states, and (3) it is not necessary to know the exact time of the observation TWS, because the TWS change timing is determined by the precipitation forcing.

Girotto, Manuela↗

NASA NTRSDate not supplied

CERES Clouds and Radiative Swath (CRS) data in HDF (CER_CRS_TRMM-PFM-VIRS_Edition2C)

The Clouds and Radiative Swath (CRS) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The CRS contains all of the CERES SSF product data. For each CERES footprint on the SSF the CRS also contains vertical flux profiles evaluated at four levels in the atmosphere: the surface, 500-, 70-, and 1-hPa. The CRS fluxes and cloud parameters are adjusted for consistency with a radiative transfer model and adjusted fluxes are evaluated at the four atmospheric levels for both clear-sky and total-sky. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

ICE PARTICLE DIAMETER↗

NASA NTRSDate not supplied

CERES Clouds and Radiative Swath (CRS) data in HDF. (CER_CRS_Terra-FM1-MODIS_Edition2A)

The Clouds and Radiative Swath (CRS) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The CRS contains all of the CERES SSF product data. For each CERES footprint on the SSF the CRS also contains vertical flux profiles evaluated at four levels in the atmosphere: the surface, 500-, 70-, and 1-hPa. The CRS fluxes and cloud parameters are adjusted for consistency with a radiative transfer model and adjusted fluxes are evaluated at the four atmospheric levels for both clear-sky and total-sky. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2001-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

SHORTWAVE FILTERED RADIANCE↗

NASA NTRSDate not supplied

CERES Clouds and Radiative Swath (CRS) data in HDF. (CER_CRS_Terra-FM2-MODIS_Edition2A

The Clouds and Radiative Swath (CRS) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The CRS contains all of the CERES SSF product data. For each CERES footprint on the SSF the CRS also contains vertical flux profiles evaluated at four levels in the atmosphere: the surface, 500-, 70-, and 1-hPa. The CRS fluxes and cloud parameters are adjusted for consistency with a radiative transfer model and adjusted fluxes are evaluated at the four atmospheric levels for both clear-sky and total-sky. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2001-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CLOUD LAYER AREA↗

NASA NTRSDate not supplied

CERES Clouds and Radiative Swath (CRS) data in HDF. (CER_CRS_Terra-FM1-MODIS_Edition2B)

The Clouds and Radiative Swath (CRS) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The CRS contains all of the CERES SSF product data. For each CERES footprint on the SSF the CRS also contains vertical flux profiles evaluated at four levels in the atmosphere: the surface, 500-, 70-, and 1-hPa. The CRS fluxes and cloud parameters are adjusted for consistency with a radiative transfer model and adjusted fluxes are evaluated at the four atmospheric levels for both clear-sky and total-sky. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

SHORTWAVE FLUX↗

NASA NTRSDate not supplied

CERES Clouds and Radiative Swath (CRS) data in HDF. (CER_CRS_Terra-FM2-MODIS_Edition2B)

The Clouds and Radiative Swath (CRS) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The CRS contains all of the CERES SSF product data. For each CERES footprint on the SSF the CRS also contains vertical flux profiles evaluated at four levels in the atmosphere: the surface, 500-, 70-, and 1-hPa. The CRS fluxes and cloud parameters are adjusted for consistency with a radiative transfer model and adjusted fluxes are evaluated at the four atmospheric levels for both clear-sky and total-sky. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2001-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

SHORTWAVE UNFILTERED RADIANCE↗

NASA NTRSDate not supplied

CERES Monthly Gridded Single Satellite Fluxes and Clouds (FSW) in HDF (CER_FSW_TRMM-PFM-VIRS_Beta1)

The Monthly Gridded Radiative Fluxes and Clouds (FSW) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The FSW is also produced for combinations of scanner instruments. All instantaneous fluxes from the CERES CRS product for a month are sorted by 1-degree spatial regions and by the Universal Time (UT) hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the FSW along with other flux statistics and scene information. The mean adjusted fluxes at the four atmospheric levels defined by CRS are also included for both clear-sky and total-sky scenes. In addition, four cloud height categories are defined by dividing the atmosphere into four intervals with boundaries at the surface, 700-, 500-, 300-hPa, and the Top-of-the-Atmosphere (TOA). The cloud layers from CRS are put into one of the cloud height categories and averaged over the region. The cloud properties are also column averaged and included on the FSW. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CLOUD OVERLAP↗

NASA NTRSDate not supplied

CERES Monthly Gridded Single Satellite Fluxes and Clouds (FSW) in HDF (CER_FSW_Terra-FM1-MODIS_Edition2C)

The Monthly Gridded Radiative Fluxes and Clouds (FSW) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The FSW is also produced for combinations of scanner instruments. All instantaneous fluxes from the CERES CRS product for a month are sorted by 1-degree spatial regions and by the Universal Time (UT) hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the FSW along with other flux statistics and scene information. The mean adjusted fluxes at the four atmospheric levels defined by CRS are also included for both clear-sky and total-sky scenes. In addition, four cloud height categories are defined by dividing the atmosphere into four intervals with boundaries at the surface, 700-, 500-, 300-hPa, and the Top-of-the-Atmosphere (TOA). The cloud layers from CRS are put into one of the cloud height categories and averaged over the region. The cloud properties are also column averaged and included on the FSW. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

NET FLUX↗

NASA NTRSDate not supplied

CERES) Monthly Gridded Single Satellite Fluxes and Clouds (FSW) in HDF (CER_FSW_Terra-FM2-MODIS_Edition2C)

The Monthly Gridded Radiative Fluxes and Clouds (FSW) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The FSW is also produced for combinations of scanner instruments. All instantaneous fluxes from the CERES CRS product for a month are sorted by 1-degree spatial regions and by the Universal Time (UT) hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the FSW along with other flux statistics and scene information. The mean adjusted fluxes at the four atmospheric levels defined by CRS are also included for both clear-sky and total-sky scenes. In addition, four cloud height categories are defined by dividing the atmosphere into four intervals with boundaries at the surface, 700-, 500-, 300-hPa, and the Top-of-the-Atmosphere (TOA). The cloud layers from CRS are put into one of the cloud height categories and averaged over the region. The cloud properties are also column averaged and included on the FSW. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2001-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CLOUD OVERLAP↗

NASA NTRS2011

Small Rayed Crater Ejecta Retention Age Calculated from Current Crater Production Rates on Mars

Ejecta from impact craters, while extant, records erosive and depositional processes on their surfaces. Estimating ejecta retention age (Eret), the time span when ejecta remains recognizable around a crater, can be applied to estimate the timescale that surface processes operate on, thereby obtaining a history of geologic activity. However, the abundance of sub-kilometer diameter (D) craters identifiable in high resolution Mars imagery has led to questions of accuracy in absolute crater dating and hence ejecta retention ages (Eret). This research calculates the maximum Eret for small rayed impact craters (SRC) on Mars using estimates of the Martian impactor flux adjusted for meteorite ablation losses in the atmosphere. In addition, we utilize the diameter-distance relationship of secondary cratering to adjust crater counts in the vicinity of the large primary crater Zunil.

Rayed Craters↗

NASA NTRS2015

Development of an Infrared Lamp Array for the Smap Spacecraft Thermal Balance Test

NASA launched the SMAP observatory in January 2015 aboard a Delta II into a sun-synchronous orbit around Earth. The science payload of a radar and a radiometer utilizes a shared rotating six-meter antenna to provide a global map of the Earth's soil moisture content and its freeze/thaw state on a global, high-resolution scale in this three-year mission. An observatory-level thermal balance test conducted in May/June 2014 validated the thermal design and demonstrated launch readiness as part of the planned environmental test campaign. An infrared lamp array was designed and used in the thermal balance test to replicate solar heating on the solar array and sunlit side of the spacecraft that would normally be seen in orbit. The design, implementation, and operation of an infrared lamp array used for this nineteen-day system thermal test are described in this paper. Instrumental to the smooth operation of this lamp array was a characterization test performed in the same chamber two months prior to the observatory test to provide insight into its array operation and flux uniformity. This knowledge was used to identify the lamp array power settings that would provide the worst case predicted on-orbit fluxes during eclipse, cold, and hot cases. It also showed the lamp array variation when adjustments in flux were needed. Calorimeters calibrated prior to testing determined a relationship between calorimeter temperature and lamp array flux. This allowed the team to adjust the lamp output for the desired absorbed flux on the solar array. Flux levels were within 10% of the desired value at the center of the solar array with an ability to maintain these levels within 5% during steady state cases. All tests demonstrated the infrared lamp array functionality and furthered lamp array understanding for modeling purposes. This method contributed to a high-fidelity environmental simulation, which was required to replicate the extreme on-orbit thermal environments.

Miller, Jennifer R.↗

NASA NTRS2011

Video Meteor Fluxes

The flux of meteoroids, or number of meteoroids per unit area per unit time, is critical for calibrating models of meteoroid stream formation and for estimating the hazard to spacecraft from shower and sporadic meteors. Although observations of meteors in the millimetre to centimetre size range are common, flux measurements (particularly for sporadic meteors, which make up the majority of meteoroid flux) are less so. It is necessary to know the collecting area and collection time for a given set of observations, and to correct for observing biases and the sensitivity of the system. Previous measurements of sporadic fluxes are summarized in Figure 1; the values are given as a total number of meteoroids striking the earth in one year to a given limiting mass. The Gr n et al. (1985) flux model is included in the figure for reference. Fluxes for sporadic meteoroids impacting the Earth have been calculated for objects in the centimeter size range using Super-Schmidt observations (Hawkins & Upton, 1958); this study used about 300 meteors, and used only the physical area of overlap of the cameras at 90 km to calculate the flux, corrected for angular speed of meteors, since a large angular speed reduces the maximum brightness of the meteor on the film, and radiant elevation, which takes into account the geometric reduction in flux when the meteors are not perpendicular to the horizontal. They bring up corrections for both partial trails (which tends to increase the collecting area) and incomplete overlap at heights other than 90 km (which tends to decrease it) as effects that will affect the flux, but estimated that the two effects cancelled one another. Halliday et al. (1984) calculated the flux of meteorite-dropping fireballs with fragment masses greater than 50 g, over the physical area of sky accessible to the MORP fireball cameras, counting only observations in clear weather. In the micron size range, LDEF measurements of small craters on spacecraft have been used to estimate the flux (Love & Brownlee, 1993); here the physical area of the detector is well known, but the masses depend strongly on the unknown velocity distribution. In the same size range, Thomas & Netherway (1989) used the narrow-beam radar at Jindalee to calculate the flux of sporadics. In between these very large and very small sizes, a number of video and photographic observations were reduced by Ceplecha (2001). These fluxes were calculated (details are given in Ceplecha, 1988) taking the Halliday et al. (1984) MORP fireball fluxes, slightly corrected in mass, as a calibration, and adjusting the flux of small cameras to overlap with the number/mass relation from that work.

Campbell-Brown, M. D.↗

NASA NTRS2008

Climate Model Evaluation using New Datasets from the Clouds and the Earth's Radiant Energy System (CERES)

There are some in the science community who believe that the response of the climate system to anthropogenic radiative forcing is unpredictable and we should therefore call off the quest . The key limitation in climate predictability is associated with cloud feedback. Narrowing the uncertainty in cloud feedback (and therefore climate sensitivity) requires optimal use of the best available observations to evaluate and improve climate model processes and constrain climate model simulations over longer time scales. The Clouds and the Earth s Radiant Energy System (CERES) is a satellite-based program that provides global cloud, aerosol and radiative flux observations for improving our understanding of cloud-aerosol-radiation feedbacks in the Earth s climate system. CERES is the successor to the Earth Radiation Budget Experiment (ERBE), which has widely been used to evaluate climate models both at short time scales (e.g., process studies) and at decadal time scales. A CERES instrument flew on the TRMM satellite and captured the dramatic 1998 El Nino, and four other CERES instruments are currently flying aboard the Terra and Aqua platforms. Plans are underway to fly the remaining copy of CERES on the upcoming NPP spacecraft (mid-2010 launch date). Every aspect of CERES represents a significant improvement over ERBE. While both CERES and ERBE measure broadband radiation, CERES calibration is a factor of 2 better than ERBE. In order to improve the characterization of clouds and aerosols within a CERES footprint, we use coincident higher-resolution imager observations (VIRS, MODIS or VIIRS) to provide a consistent cloud-aerosol-radiation dataset at climate accuracy. Improved radiative fluxes are obtained by using new CERES-derived Angular Distribution Models (ADMs) for converting measured radiances to fluxes. CERES radiative fluxes are a factor of 2 more accurate than ERBE overall, but the improvement by cloud type and at high latitudes can be as high as a factor of 5. Diurnal cycles are explicitly resolved by merging geostationary satellite observations with CERES and MODIS. Atmospheric state data are provided from a frozen version of the Global Modeling and Assimilation Office- Data Assimilation System at the NASA Goddard Space Flight Center. In addition to improving the accuracy of top-of-atmosphere (TOA) radiative fluxes, CERES also produces radiative fluxes at the surface and at several levels in the atmosphere using radiative transfer modeling, constrained at the TOA by CERES (ERBE was limited to the TOA). In all, CERES uses 11 instruments on 7 spacecraft all integrated to obtain climate accuracy in TOA to surface fluxes. This presentation will provide an overview of several new CERES datasets of interest to the climate community (including a new adjusted TOA flux dataset constrained by estimates of heat storage in the Earth system), show direct comparisons between CERES ad ERBE, and provide a detailed error analysis of CERES fluxes at various time and space scales. We discuss how observations can be used to reduce uncertainties in cloud feedback and climate sensitivity and strongly argue why we should NOT "call off the quest".

Loeb, Norman G.↗

NASA NTRSDate not supplied

Understanding The Top-Of-Atmosphere Fluxes Difference Between Aerocom Phase III Models And The CERES Product: Clear-Sky Perspective

The Clouds and the Earth’s Radiant Energy System (CERES) project produces a long-term global climate data record (CDR) that can be used to detect decadal changes in the Earth’s radiation budget (ERB) from the surface to the top-of-atmosphere (TOA). The CERES Energy Balanced and Filled (EBAF) product includes monthly mean shortwave (SW), longwave (LW), and net TOA all-sky and clear-sky radiative fluxes over 1-degree latitude by 1-degree longitude regions. The EBAF SW and LW fluxes are adjusted within their uncertainties to be consistent with the heat storage in the Earth-atmosphere system (Johnson et al. 2016). EBAF also provides a gap-free monthly mean clear-sky flux map by inferring clear-sky fluxes from both CERES and MODIS measurements (Loeb et al. 2018). In this study, we compare the TOA clear-sky fluxes from Aerocom phase III output with those from the CERES EBAF products. Flux differences over the ocean are generally smaller than over the land, and the magnitude of the differences shows seasonal and regional dependency. To understand the flux differences, aerosol optical depths (AOD) from the Aerocom models are compared with the satellite retrievals from MODIS and MISR. Over the ocean, the AOD differences and the flux differences show consistent regional features, indicating that the differences between models and observations are robust as the CERES EBAF clear-sky SW fluxes and MODIS/MISR AODs are determined independently. However, very little resemblance is found between the AOD and flux differences over the land. To further understand the cause of the flux differences over the land, we compare the land surface albedo from MODIS with the albedo from the models and find consistency in regional albedo differences and flux differences. Monthly regional radiative kernels of AOD and surface albedo derived using the MERRA-2 reanalysis data (Thorsen et al. 2020) are applied to AOD and surface albedo differences between models and observations. For most of the models, the AOD and surface albedo differences can explain most of the flux differences between models and CERES EBAF. The EOS era satellites have provided 20 years of carefully calibrated and validated observations that are suitable for trend analysis. Both the MODIS AOD and CERES EBAF clear-sky SW flux show decreasing trends over the coastal regions of eastern China and the eastern United States due to the emission control policies enforced in both countries, and an increasing trend off the coast of India. The AOD and clear-sky SW flux trends are less consistent over land, as the surface albedo changes complicate the clear-sky SW flux trend. The AOD and clear-sky SW flux trends from the Oslo model HIST run are also examined. However, none of the aforementioned regional trends are found in the model results.

Wenying Su↗

NASA NTRS1962

Time-Dependent Structure of the Upper Atmosphere

The physical properties of the upper atmosphere are determined mainly by heat conduction, the heat sources and the barometric law. An analysis of the integro-differential equation which describes these physical processes has been carried out. It is found that heating of the thermosphere due to absorption of the solar extreme ultraviolet (EUV) radiation alone cannot explain the observed diurnal variation of density and temperature, since it would yield a maximum of these properties at about 17h local time, instead of 14h where it is observed. Secondly, if the EUV flux is adjusted to give the observed average temperature, then the diurnal variation in density would be much too large compared with the observed amplitude. Thirdly, it would require an extremely high efficiency for the conversion of EUV radiation into heat, if we compare the required flux with Hinteregger's measurements of the EUV flux. Thus, it is necessary to have another heat source in addition to the heating due to absorption of EUV radiation. If an additional beat source is used, which has a maximum at about 9h local time and a flux of 1 erg cm−1 sec−1, a time-dependent model of the upper atmosphere is obtained that is in good agreement with the observed densities. There is evidence that this additional heat source derives its energy ultimately from the solar corpuscular radiation. In this paper we present the results of calculations for a model in the equatorial and temperature zones of the earth, for those times when the average solar activity corresponds to a solar radiation flux of 200×110−22 Wm−2 (cps)−1 at 10.7-cm wavelength. The physical properties (temperature, density, pressure, scale height, mean molecular weight and the number densities of N2, O2, O, He and H) are given as a function of local time and for the altitudes between 120 km and 2050 km.

ATMOSPHERE↗

NASA NTRS1977

The spectral energy distribution of Zeta Puppis and HD 50896

The ultraviolet spectral energy distribution of the O5f star Zeta Pup and the WN5 star HD 50896 are derived from OAO-2 observations with the calibration of Bless, Code, and Fairchild (1976). An estimate of the interstellar reddening (0.12 magnitude) of the Wolf-Rayet star is determined from the size of the characteristic interstellar extinction bump at 4.6 inverse microns. After correction for extinction, both stars show a flat energy distribution in the ultraviolet. The distribution of HD 50896 from 1100 A to 2 microns is in good agreement with results of extended model atmospheres, but some uncertainty remains because of the interstellar-extinction correction. The absolute energy distribution of Zeta Pup is fitted by a 42,000-K plane-parallel model if the model's flux is adjusted for the effects of electron scattering in the stellar wind and for UV line blanketing that was determined empirically from high-resolution Copernicus satellite observations. To achieve this fit, it is necessary to push both the spectroscopically determined temperature and the ultraviolet calibration to the limits of their probable errors.

Holm, A. V.↗

NASA NTRS1992

Adjustment of footprint correction for airborne flux mapping over the FIFE site

A meaningful interpretation of airborne flux estimates over nonuniform terrain must consider local advection from nonhomogeneous source distributions (footprint correction). An empirical procedure for footprint correction of airborne flux data obtained in the First ISLSCP Field Experiment (FIFE) 1989 is presented, based on simple analytical solutions of the diffusion equation which have been adjusted to approximate more realistic solutions. Optimized estimates of surface flux 'maps' derived from airborne observations are then constructed for maximum correlation between flux estimates and independently observed surface characteristics. This paper also includes an analysis of resolution for the given procedure, in terms of amplitude recovery of hypothetical square-wave distributions of surface flux density, and discusses its implications for the interpretation of the optimized estimates of FIFE surface flux maps. Results show that corrected spatial sink distributions are obtained by the current empirical procedure at the cost of considerable reduction in amplitude recovery of small-scale variations in surface flux density. The high spatial correlation observed between corrected flux maps and surface characteristics such as greenness or surface temperature excess is ascribed to the approximately correct positioning of the main flux gradients across the site, which can be expected to have been reproduced with amplitude recovery equal to or greater than 60 percent.

Schuepp, P. H.↗

NASA NTRS2003

Validation of the Archived CERES Surface and Atmosphere Radiation Budget (SARB) at SGP

The CERES Surface and Atmosphere Radiation Budget (SARB) product (Charlock et al, 2002) includes the vertical profile of broadband SW, broadband LW, and 8-12 micron window (WN) fluxes; upwelling and downwelling at TOA, 70 hPa, 200 hPa, 500 hPa, and the surface; and for all-sky and clear-sky conditions. We test the archived CERES TRMM record of SARB for January-August 1998 and focus on discrepancies with ground-based measurements at SGP. The CERES SARB is generated by a highly modified Fu-Liou radiative transfer code (Fu and Liou, 1993). The most critical inputs for this application are cloud optical properties (fractional area, optical depth, particle size and phase, height of top, and estimate of geometrical thickness Minnis et al., 2002) from the narrowband VIRS imager. Numerous VIRS pixels (approx. 2km resolution at nadir) are matched to each of the large (approx. 20km) CERES broadband footprints (Wielicki et al, 1996). Other inputs include temperature and humidity from ECMWF (Rabier et al, 1998) , NCEP ozone profiles from SBUV and TOVS (Yang et al, 2001), aerosol optical thickness (AOT) from the Model for Atmospheric Transport and Chemistry (MATCH) aerosol assimilation (Collins et al., 2001) or alternately from the VIRS imager (Ignatov and Stowe, 2000). VIRS AOT is available for clear and partly cloudy ocean footprints during daylight; and only when viewing geometry renders a contribution from sunglint as unlikely. For other footprints, AOT is taken from MATCH. AOT is apportioned into fractions of dust (Tegan and Lacis, 1996), sea salt, sulfate, dust, soluble organic, insoluble organic, and soot (Hess et al., 1996) using the 6-hourly MATCH output. Tuned fluxes are retrieved by adjusting inputs to nudge computed TOA fluxes toward CERES observations (Rose et al, 1997). In clear conditions, the fields of humidity, surface skin temperature, surface albedo and AOT are adjusted to produce a closer match of computed and observed fluxes at TOA. When CERES footprints have clouds, the cloud optical thickness, fractional area within the footprint, and temperature of cloud top are adjusted by the tuning algorithm. Both tuned and untuned fluxes are archived, as are the respective adjustments to any parameters at the surface or within the atmosphere.

Charlock, Thomas P.↗