The CLARREO mission addresses the need to provide accurate, broadly acknowledged climate records that can be used
to validate long-term climate projections that become the foundation for informed decisions on mitigation and adaptation
policies. The CLARREO mission accomplishes this critical objective through rigorous SI traceable decadal change
observations that will reduce the key uncertainties in current climate model projections. These same uncertainties also
lead to uncertainty in attribution of climate change to anthropogenic forcing. CLARREO will make highly accurate and
SI-traceable global, decadal change observations sensitive to the most critical, but least understood climate forcing,
responses, and feedbacks. The CLARREO breakthrough is to achieve the required levels of accuracy and traceability to
SI standards for a set of observations sensitive to a wide range of key decadal change variables. The required accuracy
levels are determined so that climate trend signals can be detected against a background of naturally occurring
variability. The accuracy for decadal change traceability to SI standards includes uncertainties associated with
instrument calibration, satellite orbit sampling, and analysis methods. Unlike most space missions, the CLARREO
requirements are driven not by the instantaneous accuracy of the measurements, but by accuracy in the large time/space
scale averages that are necessary to understand global, decadal climate changes.
The micro- and macrophysical properties of clouds play a crucial role in Earth’s radiation budget. The NASA Clouds and Earth’s Radiant Energy System (CERES) is providing simultaneous measurements of the radiation and cloud fields on a global basis to improve the understanding and modeling of the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. Cloud properties derived for CERES from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites are compared to ensure consistency between the products to ensure the reliability of the retrievals from multiple platforms at different times of day. Comparisons of cloud fraction, height, optical depth, phase, effective particle size, and ice and liquid water paths from the two satellites show excellent consistency. Initial calibration comparisons are also very favorable. Differences between the Aqua and Terra results are generally due to diurnally dependent changes in the clouds. Additional algorithm refinement is needed over the polar regions for Aqua and at night over those same areas for Terra. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.
The availability of a 15-year data set of radiative fluxes from the Earth Radiation Budget Experiment (ERBE) allows us to investigate the interannual variability of top-of-the-atmosphere (TOA) outgoing longwave radiation (OLR) and reflected shortwave radiation (SWR). Variance maps and empirical orthogonal function (EOF) analysis are used to describe temporal and spatial patterns of variability.
Surface emissivity is essential for many remote sensing applications including the retrieval of the surface skin temperature from satellite-based infrared measurements, determining thresholds for cloud detection and for estimating the emission of longwave radiation from the surface, an important component of the energy budget of the surface-atmosphere interface. In this paper, data from the Terra MODIS (MODerate-resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 10.8, 12.0 micron are used to simultaneously derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of the clear-sky temperatures that are determined by the CERES (Clouds and Earth's Radiant Energy System) scene classification in each channel during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7 micron data. A set of simultaneous equations is then solved to derive the emissivities. Global results are derived from MODIS. Numerical weather analyses are used to provide soundings for correcting the observed radiances for atmospheric absorption. These results are verified and will be available for remote sensing applications.
The NASA CERES Project has developed a combined radiation and cloud property dataset using the CERES scanners and matched spectral data from high-resolution imagers, the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The diurnal cycle can be well-characterized over most of the globe using the combinations of TRMM, Aqua, and Terra data. The cloud properties are derived from the imagers using state-of-the-art methods and include cloud fraction, height, optical depth, phase, effective particle size, emissivity, and ice or liquid water path. These cloud products are convolved into the matching CERES fields of view to provide simultaneous cloud and radiation data at an unprecedented accuracy. Results are available for at least 3 years of VIRS data and 1 year of Terra MODIS data. The various cloud products are compared with similar quantities from climatological sources and instantaneous active remote sensors. The cloud amounts are very similar to those from surface observer climatologies and are 6-7% less than those from a satellite-based climatology. Optical depths are 2-3 times smaller than those from the satellite climatology, but are within 5% of those from the surface remote sensing. Cloud droplet sizes and liquid water paths are within 10% of the surface results on average for stratus clouds. The VIRS and MODIS retrievals are very consistent with differences that usually can be explained by sampling, calibration, or resolution differences. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.
The Clouds and Earth's Radiant Energy System (CERES) experiment, the first satellite project devoted to monitoring cloud macrophysical and microphysical properties simultaneously with the broadband radiation field, is designed to dramatically improve our understanding of the relationship between clouds and the Earth's radiation budget. The first CERES instruments flew on the Tropical Rainfall Measuring Mission (TRMM) satellite between 35 degrees N and 35 degrees S with the Visible Infrared Scanner (VIRS), a 2-km resolution imager with five channels: 0.65, 1.6, 3.75, 10.8, and 12 micrometer beginning in January 1998. Cloud amount, height, temperature, phase, effective particle size, and water path are derived from the VIRS radiances and validated using surface radar and lidar data. Droplet radii are largest over ocean and smallest over land. Mean droplet radius is larger than that from earlier studies. The mean ice diameter is 61 micrometer. Variations of cloud parameters with temperature and viewing and solar zenith angle are given. Surface observations of liquid water path and droplet size agree well with the VIRS retrievals. This is the first analysis of cloud microphysical properties covering all times of day using all available pixels and viewing angles for half of the globe. Seasonal and diurnal variations of the cloud properties are presented.
The first CERES instrument has been placed in orbit on the TRMM Spacecraft. This instrument is designed to measure the Earth's radiation budget and also the anisotropy of reflected solar radiation and outgoing longwave radiation. The TRMM orbit and the combination of CERES with other instruments aboard the spacecraft provide a unique opportunity for a number of scientific studies. Results from the on-board calibration system compared well with ground calibrations. Data products include radiant fluxes at the top of the atmosphere', surface reflected solar and longwave radiant fluxes and cloud-radiative interactions.
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