Takmeng Wong

Toward Optimal Closure of the Earth's Top-of-Atmosphere Radiation Budget

Abstract Despite recent improvements in satellite instrument calibration and the algorithms used to determine reflected solar (SW) and emitted thermal (LW) top-of-atmosphere (TOA) radiative fluxes, a sizeable imbalance persists in the average global net radiation at the TOA from satellite observations. This imbalance is problematic in applications that use earth radiation budget (ERB) data for climate model evaluation, estimate the earth’s annual global mean energy budget, and in studies that infer meridional heat transports. This study provides a detailed error analysis of TOA fluxes based on the latest generation of Clouds and the Earth’s Radiant Energy System (CERES) gridded monthly mean data products [the monthly TOA/surface averages geostationary (SRBAVG-GEO)] and uses an objective constrainment algorithm to adjust SW and LW TOA fluxes within their range of uncertainty to remove the inconsistency between average global net TOA flux and heat storage in the earth–atmosphere system. The 5-yr global mean...

Clouds and the Earth's Radiant Energy System (CERES): algorithm overview

The Clouds and the Earths Radiant Energy System (CERES) is part of NASAs Earth Observing System (EOS), CERES objectives include the following. (1) For climate change analysis, provide a continuation of the Earth Radiation Budget Experiment (ERBE) record of radiative fluxes at the top-of-the-atmosphere (TOA), analyzed using the same techniques as the existing ERBE data. (2) Double the accuracy of estimates of radiative fluxes at TOA and the Earths surface. (3) Provide the first long-term global estimates of the radiative fluxes within the Earths atmosphere. (4) Provide cloud property estimates collocated in space and time that are consistent with the radiative fluxes from surface to TOA. In order to accomplish these goals, CERES uses data from a combination of spaceborne instruments: CERES scanners, which are an improved version of the ERBE broadband radiometers, and collocated cloud spectral imager data on the same spacecraft. The CERES cloud and radiative flux data products should prove extremely useful in advancing the understanding of cloud-radiation interactions, particularly cloud feedback effects on the Earths radiation balance. For this reason, the CERES data should be fundamental to the ability to understand, detect, and predict global climate change. CERES results should also be very useful for studying regional climate changes associated with deforestation, desertification, anthropogenic aerosols, and ENSO events. This overview summarizes the Release 3 version of the planned CERES data products and data analysis algorithms. These algorithms are a prototype for the system that will produce the scientific data required for studying the role of clouds and radiation in the Earths climate system.

Reexamination of the Observed Decadal Variability of the Earth Radiation Budget Using Altitude-Corrected ERBE/ERBS Nonscanner WFOV Data

Abstract This paper gives an update on the observed decadal variability of the earth radiation budget (ERB) using the latest altitude-corrected Earth Radiation Budget Experiment (ERBE)/Earth Radiation Budget Satellite (ERBS) Nonscanner Wide Field of View (WFOV) instrument Edition3 dataset. The effects of the altitude correction are to modify the original reported decadal changes in tropical mean (20°N to 20°S) longwave (LW), shortwave (SW), and net radiation between the 1980s and the 1990s from 3.1, −2.4, and −0.7 to 1.6, −3.0, and 1.4 W m−2, respectively. In addition, a small SW instrument drift over the 15-yr period was discovered during the validation of the WFOV Edition3 dataset. A correction was developed and applied to the Edition3 dataset at the data user level to produce the WFOV Edition3_Rev1 dataset. With this final correction, the ERBS Nonscanner-observed decadal changes in tropical mean LW, SW, and net radiation between the 1980s and the 1990s now stand at 0.7, −2.1, and 1.4 W m−2, respectivel...

δ-Fit: A fast and accurate treatment of particle scattering phase functions with weighted singular-value decomposition least-squares fitting

Abstract With a limited number of polynomial terms (so-called “streams”), there are significant differences between a phase function and its Legendre polynomial expansion at large scattering angles, which are important to satellite observations. This study finds that while it takes hundreds of Legendre polynomial expansion terms to simulate the backscattering portion of cloud phase functions accurately, the backscattered radiance pattern can be accurately estimated with only 30 Legendre polynomial expansion terms by replacing the regular Legendre polynomial expansion coefficients by coefficients obtained by a weighted singular-value decomposition least-squares fitting procedure. Thus the computing time can be significantly reduced. For satellite remote-sensing purposes, the weighted least-squares Legendre polynomial fitting is an optimal estimation of the cloud phase function.

Temporal Interpolation Methods for the Clouds and the Earth’s Radiant Energy System (CERES) Experiment

Abstract The Clouds and the Earth’s Radiant Energy System (CERES) is a NASA multisatellite measurement program for monitoring the radiation environment of the earth–atmosphere system. The CERES instrument was flown on the Tropical Rainfall Measuring Mission satellite in late 1997, and will be flown on the Earth Observing System morning satellite in 1998 and afternoon satellite in 2000. To minimize temporal sampling errors associated with satellite measurements, two methods have been developed for temporally interpolating the CERES earth radiation budget measurements to compute averages of top-of-the-atmosphere shortwave and longwave flux. The first method is based on techniques developed from the Earth Radiation Budget Experiment (ERBE) and provides radiation data that are consistent with the ERBE processing. The second method is a newly developed technique for use in the CERES data processing. This technique incorporates high temporal resolution data from geostationary satellites to improve modeling of d...

A Bayesian approach to microwave precipitation profile retrieval

Abstract A multichannel passive microwave precipitation retrieval algorithm is developed. Bayes theorem is used to combine statistical information from numerical cloud models with forward radiative transfer modeling. Amultivariate lognormal prior probability distribution contains the covariance information about hydrometeor distributions that resolves the nonuniqueness inherent in the inversion process. Hydrometeor profiles are retrieved by maximizing the posterior probability density for each vector of observations. The hydrometeor profile retrievalmethod is tested with data from the Advanced Microwave Precipitation Radiometer (IO, 19, 37, and 85 GHz) of convection over ocean and land in Florida. The CP-2 multiparameter radar data are used to verify theretrieved profiles. The results show that the method can retrieve approximate hydrometeor profiles, with larger errors over land than water. There is considerably greater accuracy in the retrieval of integrated hydrometeor contents than of profiles. Many o...

Multi-Instrument Comparison of Top-of-Atmosphere Reflected Solar Radiation

Abstract Observations from the Clouds and the Earth’s Radiant Energy System (CERES), Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Sea-Viewing Wide-Field-of-View Sensor (SeaWiFS) between 2000 and 2005 are analyzed in order to determine if these data are meeting climate accuracy goals recently established by the climate community. The focus is primarily on top-of-atmosphere (TOA) reflected solar radiances and radiative fluxes. Direct comparisons of nadir radiances from CERES, MODIS, and MISR aboard the Terra satellite reveal that the measurements from these instruments exhibit a year-to-year relative stability of better than 1%, with no systematic change with time. By comparison, the climate requirement for the stability of visible radiometer measurements is 1% decade−1. When tropical ocean monthly anomalies in shortwave (SW) TOA radiative fluxes from CERES on Terra are compared with anomalies in Photosynthetically Active Radiation (PAR) from SeaWiF...

Relationships between tropical sea surface temperature and top‐of‐atmosphere radiation

[ 1] To assess climate sensitivity from Earth radiation observations of limited duration and observed sea surface temperatures (SSTs) requires a closed and therefore global domain, equilibrium between the fields, and robust methods of dealing with noise. Noise arises from natural variability in the atmosphere and observational noise in precessing satellite observations. This paper explores the meaning of results that use only the tropical region. We compute correlations and regressions between tropical SSTs and top-of-atmosphere (TOA) longwave, shortwave and net radiation using a variety of methods to test robustness of results. The main changes in SSTs throughout the tropics are associated with El Nino Southern Oscillation (ENSO) events in which the dominant changes in energy into an atmospheric column come from ocean heat exchange through evaporation, latent heat release in precipitation, and redistribution of that heat through atmospheric winds. These changes can be an order of magnitude larger than the net TOA radiation changes, and their effects are teleconnected globally, and especially into the subtropics. Atmospheric model results are explored and found to be consistent with observations. From 1985 to 1999 the largest perturbation in TOA radiative fluxes was from the eruption of Mount Pinatubo and clearly models which do not include that forcing will not simulate the effects. Consequently, regressions of radiation with SSTs in the tropics may have nothing to say about climate sensitivity.

Statistical Analyses of Satellite Cloud Object Data from CERES. Part I: Methodology and Preliminary Results of the 1998 El Niño/2000 La Niña

Abstract This study presents an objective classification methodology that uses Earth Observing System (EOS) satellite data to classify distinct “cloud objects” defined by cloud-system types, sizes, geographic locations, and matched large-scale environments. This analysis method identifies a cloud object as a contiguous region of the earth with a single dominant cloud-system type. It determines the shape and size of the cloud object from the satellite data and the cloud-system selection criteria. The statistical properties of the identified cloud objects are analyzed in terms of probability density functions (PDFs) based upon the Clouds and the Earth’s Radiant Energy System (CERES) Single Satellite Footprint (SSF) data. Four distinct types of oceanic cloud objects—tropical deep convection, boundary layer cumulus, transition stratocumulus, and solid stratus—are initially identified from the CERES data collected from the Tropical Rainfall Measuring Mission (TRMM) satellite for this study. Preliminary results...

Statistical analyses of satellite cloud object data from ceres. Part II Tropical convective cloud objects during 1998 El Niño and evidence for supporting the fixed anvil temperature hypothesis

Abstract Characteristics of tropical deep convective cloud objects observed over the tropical Pacific during January–August 1998 are examined using the Tropical Rainfall Measuring Mission/Clouds and the Earth’s Radiant Energy System Single Scanner Footprint (SSF) data. These characteristics include the frequencies of occurrence and statistical distributions of cloud physical properties. Their variations with cloud object size, sea surface temperature (SST), and satellite precession cycle are analyzed in detail. A cloud object is defined as a contiguous patch of the earth composed of satellite footprints within a single dominant cloud-system type. It is found that statistical distributions of cloud physical properties are significantly different among three size categories of cloud objects with equivalent diameters of 100–150 (small), 150–300 (medium), and >300 km (large), except for the distributions of ice particle size. The distributions for the larger-size category of cloud objects are more skewed towa...