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 of the retrieval errors are traced to problems with the cloud model microphysicalinformation, and future improvements to the algorithm are suggested.

Abstract

Continuous monitoring of the earth radiation budget (ERB) is critical to the understanding of Earth’s climate and its variability with time. The Clouds and the Earth’s Radiant Energy System (CERES) instrument is able to provide a long record of ERB for such scientific studies. This manuscript, which is the first of a two-part paper, describes the new CERES algorithm for improving the clear/cloudy scene classification without the use of coincident cloud imager data. This new CERES algorithm is based on a subset of the modern artificial intelligence (AI) paradigm called machine learning (ML) algorithms. This paper describes the development and application of the ML algorithm known as random forests (RF), which is used to classify CERES broadband footprint measurements into clear and cloudy scenes. Results from the RF analysis carried using the CERES Single Scanner Footprint (SSF) data for January and July are presented in the manuscript. The daytime RF misclassification rate (MCR) shows relatively large values (>30%) for snow, sea ice, and bright desert surface types, while lower values (<10%) for the forest surface type. MCR values observed for the nighttime data in general show relatively larger values for most of the surface types compared to the daytime MCR values. The modified MCR values show lower values (<4%) for most surface types after thin cloud data are excluded from the analysis. Sensitivity analysis shows that the number of input variables and decision trees used in the RF analysis has a substantial influence on determining the classification error.

Abstract

Three boundary layer cloud object types—overcast, stratocumulus, and cumulus—that occurred over the Pacific Ocean during January–August 1998 are identified from the Clouds and the Earth’s Radiant Energy System (CERES) single scanner footprint data. Characteristics of each cloud object type matched with atmospheric states are examined for large regions in the tropics and subtropics and for different size categories. Stratocumulus cloud objects dominate the entire boundary layer cloud population in all regions and size categories. Overcast cloud objects, which have the largest average size, are more prevalent in the subtropics and near the coastal regions, while cumulus cloud objects are prevalent over the open oceans and the equatorial regions, particularly within the small-size categories. Cloud objects with equivalent diameters less than 75 km are excluded in the analysis.

The differences between the tropical and subtropical statistical distributions of cloud properties are small for liquid water path (LWP), cloud optical depth, and top-of-the-atmosphere (TOA) albedo, but large for cloud-top temperature and outgoing longwave radiation (OLR), for each of the three cloud object types. The larger cloud objects have higher LWPs, cloud optical depths, TOA albedos, and OLRs, but lower SSTs and cloud-top heights for the stratocumulus and overcast types. Lower-tropospheric stability seems to be the primary factor for the differences in the distributions of cloud physical properties between the regions or between the size categories. Atmospheric dynamics also play a role in determining the differences in the distributions of cloud physical properties between the size categories, but not a significant role for those between the types or between the regions. The latter may be due to uncertainties in the matched vertical velocity data. When the three cloud object types are combined in small regions, lower-tropospheric stability determines the transition of boundary layer cloud types along a Pacific transect. The proportion of each type is the most important factor for diagnosing the combined cloud properties along this transect, such as LWP, cloud optical depth, and TOA albedo. Atmospheric dynamics also play complicated roles in determining the combined cloud properties along this transect.

Abstract

Simulations of climate change have yet to reach a consensus on the sign and magnitude of the changes in physical properties of marine boundary layer clouds. In this study, the authors analyze how cloud and radiative properties vary with SST anomaly in low-cloud regions, based on five years (March 2000–February 2005) of Clouds and the Earth’s Radiant Energy System (CERES)–Terra monthly gridded data and matched European Centre for Medium-Range Weather Forecasts (ECMWF) meteorological reanalaysis data. In particular, this study focuses on the changes in cloud radiative effect, cloud fraction, and cloud optical depth with SST anomaly. The major findings are as follows. First, the low-cloud amount (−1.9% to −3.4% K⁻¹) and the logarithm of low-cloud optical depth (−0.085 to −0.100 K⁻¹) tend to decrease while the net cloud radiative effect (3.86 W m⁻² K⁻¹) becomes less negative as SST anomalies increase. These results are broadly consistent with previous observational studies. Second, after the changes in cloud and radiative properties with SST anomaly are separated into dynamic, thermodynamic, and residual components, changes in the dynamic component (taken as the vertical velocity at 700 hPa) have relatively little effect on cloud and radiative properties. However, the estimated inversion strength decreases with increasing SST, accounting for a large portion of the measured decreases in cloud fraction and cloud optical depth. The residual positive change in net cloud radiative effect (1.48 W m⁻² K⁻¹) and small changes in low-cloud amount (−0.81% to 0.22% K⁻¹) and decrease in the logarithm of optical depth (–0.035 to –0.046 K⁻¹) with SST are interpreted as a positive cloud feedback, with cloud optical depth feedback being the dominant contributor. Last, the magnitudes of the residual changes differ greatly among the six low-cloud regions examined in this study, with the largest positive feedbacks (∼4 W m⁻² K⁻¹) in the southeast and northeast Atlantic regions and a slightly negative feedback (−0.2 W m⁻² K⁻¹) in the south-central Pacific region. Because the retrievals of cloud optical depth and/or cloud fraction are difficult in the presence of aerosols, the transport of heavy African continental aerosols may contribute to the large magnitudes of estimated cloud feedback in the two Atlantic regions.

Abstract

Five years of measurements from the Earth Radiation Budget Satellite (ERBS) have been analyzed to define the diurnal cycle of albedo from 55°N to 55°S. The ERBS precesses through all local times every 72 days so as to provide data regarding the diurnal cycles for Earth radiation. Albedo together with insolation at the top of the atmosphere is used to compute the heating of the Earth–atmosphere system; thus its diurnal cycle is important in the energetics of the climate system. A principal component (PC) analysis of the diurnal variation of top-of-atmosphere albedo using these data is presented. The analysis is done separately for ocean and land because of the marked differences of cloud behavior over ocean and over land. For ocean, 90%–92% of the variance in the diurnal cycle is described by a single component; for land, the first PC accounts for 83%–89% of the variance. Some of the variation is due to the increase of albedo with increasing solar zenith angle, which is taken into account in the ERBS data processing by a directional model, and some is due to the diurnal cycle of cloudiness. The second PC describes 2%–4% of the variance for ocean and 5% for land, and it is primarily due to variations of cloudiness throughout the day, which are asymmetric about noon. These terms show the response of the atmosphere to the cycle of solar heating. The third PC for ocean is a two-peaked curve, and the associated map shows high values in cloudy regions.

Abstract

The Clouds and the Earth’s Radiant Energy System (CERES) is a new National Aeronautics and Space Administration space-borne measurement project for monitoring the radiation environment of the earth–atmosphere system. The first CERES instrument was launched into space on board the Tropical Rainfall Measuring Mission (TRMM) satellite on 27 November 1997. The purpose of this paper is 1) to describe the initial validation of the new CERES/TRMM Earth Radiation Budget Experiment (ERBE)–like monthly mean clear-sky longwave (CLW) dataset and 2) to demonstrate the scientific benefit of this new dataset through a data application study on the 1998 El Niño–Southern Oscillation (ENSO) episode. The initial validation of the CERES CLW data is carried out based on comparisons with both historical ERBE observations and radiative transfer simulations. While the observed CERES CLWs are initially larger than the historical ERBE record during the first part of the 1998 ENSO event, these differences are diminished by the end of the ENSO event in July 1998. These unique ENSO-related CLW radiation signatures are captured well by the radiative transfer model simulations. These results demonstrate that the new CERES CLW fluxes are theoretically consistent with the underlying physics of the atmosphere. A CERES data application study is performed to examine the relationship between the CERES CLW anomaly and changes in sea surface temperature (SST) and atmospheric column precipitable water content (PWC) during the January 1998 ENSO event. While the changes in the SST pattern are basically uncorrelated with changes in the CLW field, a negative correlation is found between the PWC anomaly and the changes in the CLW radiation field. These observed features point to 1) the significant role of the water vapor field in modulating the tropical outgoing CLW radiation field during the 1998 ENSO event and 2) the important effects of water vapor absorption in decoupling the top of the atmosphere tropical outgoing CLW radiation from the surface upward CLW field.

Abstract

The physical and radiative properties of tropical deep convective systems for the period from January to August 1998 are examined with the use of Clouds and the Earth’s Radiant Energy System Single-Scanner Footprint (SSF) data from the Tropical Rainfall Measuring Mission satellite. Deep convective (DC) cloud objects are contiguous regions of satellite footprints that fulfill the DC criteria (i.e., overcast footprints with cloud optical depths >10 and cloud-top heights >10 km). Extended cloud objects (ECOs) start with the original cloud object but include all other cloudy footprints within a rectangular box that completely covers the original cloud object. Most of the non-DC footprints are overcast but have optical depths and/or cloud-top heights that are too low to fit the DC criteria. The histograms of cloud physical and radiative properties are analyzed according to the size of the ECO and the SST of the underlying ocean.

Larger ECOs are associated with greater magnitudes of large-scale upward motion, which supports stronger convection for larger sizes of ECOs. This leads to shifts toward higher values in the DC distributions of cloud-top height, albedo, condensate water path, and cloud optical depth. However, non-DC footprints become less reflective with increasing ECO size, as the longer-lived large convective systems have more time to develop thin cirrus anvils. The proportion of DC footprints remains fairly constant with size. The proportion of DC footprints also remains nearly constant with SST within a given size class, although the number of footprints per object increases with SST for large objects. As SSTs increase, there is a decrease in the proportion of updraft water that goes into detrainment, causing the non-DC distributions of albedo, condensate water path, and cloud optical depth to shift toward lower values. The all-cloud distributions of cloud-top temperature and outgoing longwave radiation (OLR) shift toward lower values as SST increases owing to the increase in convective instability with SST. Both the DC and non-DC distributions of cloud-top temperature do not change much with satellite precession cycle, supporting the fixed anvil temperature hypothesis of Hartmann and Larson. When a joint histogram is formed from the cloud-top pressures and cloud optical depths of the ECOs, it is very similar to the corresponding histogram of the deep convective weather state obtained by cluster analysis of International Satellite Cloud Climatology Project data.

Abstract

Recent studies of the Earth Radiation Budget Satellite (ERBS) nonscanner radiation data indicate decadal changes in tropical cloudiness and unexpected radiative anomalies between the 1980s and 1990s. In this study, the ERBS decadal observations are compared with the predictions of the Iris hypothesis using 3.5-box model. To further understand the predictions, the tropical radiative properties observed from recent Clouds and the Earth's Radiant Energy System (CERES) radiation budget experiment [the NASA Langley Research Center (LaRC) parameters] are used to replace the modeled values in the Iris hypothesis. The predicted variations of the radiation fields strongly depend on the relationship (−22% K⁻¹) of tropical high cloud and sea surface temperature (SST) assumed by the Iris hypothesis.

On the decadal time scale, the predicted tropical mean radiative flux anomalies are generally significantly different from those of the ERBS measurements, suggesting that the decadal ERBS nonscanner radiative energy budget measurements do not support the strong negative feedback of the Iris effect. Poor agreements between the satellite data and model predictions even when the tropical radiative properties from CERES observations (LaRC parameters) are used imply that besides the Iris-modeled tropical radiative properties, the unrealistic variations of tropical high cloud generated from the detrainment of deep convection with SST assumed by the Iris hypothesis are likely to be another major factor for causing the deviation between the predictions and observations.

Abstract

Relationships between physical properties are studied for three types of marine boundary layer cloud objects identified with the Clouds and the Earth’s Radiant Energy System (CERES) footprint data from the Tropical Rainfall Measuring Mission satellite between 30°S and 30°N. Each cloud object is a contiguous region of CERES footprints that have cloud-top heights below 3 km, and cloud fractions of 99%–100% (overcast type), 40%–99% (stratocumulus type), or 10%–40% (shallow cumulus type). These cloud fractions represent the fraction of ∼2 km × 2 km Visible/Infrared Scanner pixels that are cloudy within each ∼10 km × 10 km footprint. The cloud objects have effective diameters that are greater than 300 km for the overcast and stratocumulus types, and greater than 150 km for the shallow cumulus type. The Spearman rank correlation coefficient is calculated between many microphysical/optical [effective radius (r_e ), cloud optical depth (τ), albedo, liquid water path, and shortwave cloud radiative forcing (SW CRF)] and macrophysical [outgoing longwave radiation (OLR), cloud fraction, cloud-top temperature, longwave cloud radiative forcing (LW CRF), and sea surface temperature (SST)] properties for each of the three cloud object types. When both physical properties are of the same category (microphysical/optical or macrophysical), the magnitude of the correlation tends to be higher than when they are from different categories. The magnitudes of the correlations also change with cloud object type, with the correlations for overcast and stratocumulus cloud objects tending to be higher than those for shallow cumulus cloud objects.

Three pairs of physical properties are studied in detail, using a k-means cluster analysis: r_e and τ, OLR and SST, and LW CRF and SW CRF. The cluster analysis of r_e and τ reveals that for each of the cloud types, there is a cluster of cloud objects with negative slopes, a cluster with slopes near zero, and two clusters with positive slopes. The joint OLR and SST probability plots show that the OLR tends to decrease with SST in regions with boundary layer clouds for SSTs above approximately 298 K. When the cloud objects are split into “dry” and “moist” clusters based on the amount of precipitable water above 700 hPa, the associated OLRs increase with SST throughout the SST range for the dry clusters, but the OLRs are roughly constant with SST for the moist cluster. An analysis of the joint PDFs of LW CRF and SW CRF reveals that while the magnitudes of both LW and SW CRFs generally increase with cloud fraction, there is a cluster of overcast cloud objects that has low values of LW and SW CRF. These objects are generally located near the Sahara Desert, and may be contaminated with dust. Many of these overcast objects also appear in the r_e and τ cluster with negative slopes.