Abstract

Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM) digital data are used to remotely sense fog properties. These include fog cell size distribution, cell aspect ratio (the ratio of the length of the major and minor axes of the cells), and cell orientation angle. The analysis is carried out for four fog scenes, three high-inversion radiation fogs in central California, and one advection fog in eastern South Dakota.

Results for these initial fog studies indicate that 1) fogs are stratocumulus in nature, being composed of individual cellular structures; 2) the reflectance properties vary strongly across the cells, suggesting considerable variation in liquid water content; 3) fogs often are patchy, often revealing surface features between fog cells; 4) the ratio of wavelength (λ) between cells and the height of the boundary layer (h) is λ/h ≈ 2–3, in agreement with values obtained for Benard cells and longitudinal rolls observed in cloud systems; 5) the typical horizontal aspect ratio of fog cells is about a factor of 2; and 6) observed quasi-periodic oscillations of measured fog variables may be caused by advection of the cellular structures across the observational site.

Abstract

Landsat Multispectral Scanner (MSS) digital data are used to remotely sense cumulus cloud properties such as cloud fraction and cloud reflectance, along with the distribution of cloud number and cloud fraction as a function of cloud size. The analysis is carried out for four cumulus fields covering regions approximately 150 km square. Results for these initial cloud fields indicate that: (i) the common intuitive model of clouds as nearly uniform reflecting surfaces is a poor representation of cumulus clouds, (ii) the cumulus clouds were often multicelled, even for clouds as small as 1 km in diameter, (iii) cloud fractional coverage derived using a simple reflectance threshold is sensitive to the chosen threshold even for 57-meter resolution Landsat data, (iv) the sensitivity of cloud fraction to changes in satellite sensor resolution is less sensitive than suggested theoretically, and (v) the Landsat derived cloud size distributions show encouraging similarities among the cloud fields examined.

Abstract

Using a new angular distribution model (ADM) for smoke aerosols, the instantaneous top-of-atmosphere (TOA) shortwave aerosol radiative forcing (SWARF) is calculated for selected days over biomass-burning regions in South America. The visible and infrared scanner data are used to detect smoke aerosols and the Clouds and the Earth’s Radiant Energy System (CERES) scanner data from the Tropical Rainfall Measuring Mission are used to obtain the broadband radiances. First, the ADM for smoke aerosols is calculated over land surfaces using a discrete-ordinate radiative transfer model. The instantaneous TOA shortwave (SW) fluxes are estimated using the new smoke ADM and are compared with the SW fluxes from the CERES product. The rms error between the CERES SW fluxes and fluxes using the smoke ADM is 13 W m⁻². The TOA SWARFs per unit optical thickness for the six surface types range from −29 to −57 W m⁻², showing that smoke aerosols have a distinct cooling effect. The new smoke ADM developed as part of this study could be used to estimate radiative impact of biomass-burning aerosols.

Abstract

A fuzzy logic classification (FLC) methodology is proposed to achieve the two goals of this paper: 1) to discriminate between clear sky and clouds in a 32 × 32 pixel array, or sample, of 1.1-km Advanced Very High Resolution Radiometer (AVHRR) data, and 2) if clouds are present, to discriminate between single-layered and multilayered clouds within the sample. To achieve these goals, eight FLC modules are derived that are based broadly on airmass type and surface type (land or water): equatorial over land, marine tropical over land, marine tropical/equatorial over water, continental tropical over land, marine polar over land, marine polar over water, continental polar over land, and continental polar/arctic over water. Derivation of airmass type is performed using gridded analyses provided by the National Centers for Environmental Prediction.

The training and testing data used by the FLC are collected from more than 150 daytime AVHRR local area coverage scenes recorded between 1991 and 1994 over all seasons and over all continents and oceans. A total of 190 textural and spectral features are computed from the AVHRR data. A forward feature selection method is implemented to reduce the number of features used to discriminate between classes in each FLC module. The number of features selected ranges from 13 (marine tropical over land) to 24 (marine tropical/equatorial over water). An estimate of the classifier accuracy is determined using the hold-one-out method in which the classifier is trained with all but one of the data samples; the classifier is applied subsequently to the remaining sample.

The overall accuracies of the eight classification modules are calculated by dividing the number of correctly classified samples by the total number of manually labeled samples of clear-sky and single-layer clouds. Individual module classification accuracies are as follows: equatorial over land (86.2%), marine tropical over land (85.6%), marine tropical/equatorial over water (88.6%), continental tropical over land (87.4%), marine polar over land (86.8%), marine polar over water (84.8%), continental polar over land (91.1%), and continental polar/arctic over water (89.8%). Single-level cloud samples misclassified as multilayered clouds range between 0.5% (continental polar over land) and 3.4% (marine polar over land) for the eight airmass modules.

Classification accuracies for a set of labeled multilayered cloud samples range between 64% and 81% for six of the eight airmass modules (excluded are the continental polar over land and continental polar/arctic over water modules, for which multilayered cloud samples are difficult to find). The results indicate that the FLC has an encouraging ability to distinguish between single-level and multilayered clouds.

Abstract

Using satellite imagery, more than five million square kilometers of the forest and cerrado regions over South America are extensively studied to monitor fires and smoke during the 1985 biomass burning season. The results are characterized for four major ecosystems, namely, 1) tropical rain forest, 2) tropical broadleaf seasonal, 3) savanna/grass and seasonal woods (SGW), and 4) mild/warm/hot grass/shrub (MGS). The spatial and temporal distribution of fires are examined from two different methods using the multispectral Advanced Very High Resolution Radiometer Local Area Coverage data. Using collocated measurements from the instantaneous scanner Earth Radiation Budget Experiment data, the direct regional radiative forcing of biomass burning aerosols is computed. The results show that more than 70% of the fires occur in the MGS and SGW ecosystems due to agricultural practices. The smoke generated from biomass burning has negative instantaneous net radiative forcing values for all four major ecosystems within South America. The smoke found directly over the fires has mean net radiative forcing values ranging from −25.6 to −33.9 W m⁻². These results confirm that the regional net radiative impact of biomass burning is one of cooling. The spectral and broadband properties for clear-sky and smoke regions are also presented that could be used as input and/or validation for other studies attempting to model the impact of aerosols on the earth–atmosphere system.

These results have important applications for future instruments from the Earth Observing System (EOS) program. Specifically, the combination of the Visible Infrared Scanner and Clouds and the Earth’s Radiant Energy System (CERES) instruments from the Tropical Rainfall Measuring Mission and the combination of Moderate Resolution Imaging Spectrometer and CERES instruments from the EOS morning crossing mission could provide reliable estimates of the direct radiative forcing of aerosols on a global scale, thereby reducing the uncertainties in current global aerosol radiative forcing values.

Abstract

Cloud-base heights over tropical montane cloud forests are determined using Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products and National Centers for Environmental Prediction global tropospheric final analysis (FNL) fields. Cloud-base heights are computed by subtracting cloud thickness estimates from cloud-top height estimates. Cloud-top pressures determined from the current MODIS retrieval algorithm often have serious cloud-top pressure retrieval errors at pressures > 700 hPa. The problem can be easily remedied by matching cloud-top temperature derived from the 11-μm channel to the dewpoint temperature profile (instead of the temperature profile) obtained from the FNL dataset. The FNL dataset at 1° spatial resolution produced results that were nearly equivalent to those derived from radiosonde measurements. The following three different approaches for estimating cloud thickness are examined: 1) the constant liquid water method, 2) the empirical method, and 3) the adiabatic model method. The retrieval technique is applied first for stratus clouds over U.S. airports for 12 cases, with cloud-base heights compared with ceilometer measurements. Mean square errors on the order of 200 m result. Then, the approach is applied to orographic clouds over Monteverde, Costa Rica, with estimated cloud-base heights compared with those derived from photographs. Mean square errors on the order of 100 m result. Both the empirical and adiabatic model approaches produce superior results when compared with the constant liquid water (CLW) approach. This is due to the fact that CLW is more sensitive to natural variations in cloud optical thickness.

Abstract

Using in situ measurements of aerosol optical properties and ground-based measurements of aerosol optical thickness (τ _s ) during the Smoke, Clouds and Radiation—Brazil (SCAR-B) experiment, a four-stream broadband radiative transfer model is used to estimate the downward shortwave irradiance (DSWI) and top-of-atmosphere (TOA) shortwave aerosol radiative forcing (SWARF) in cloud-free regions dominated by smoke from biomass burning in Brazil. The calculated DSWI values are compared with broadband pyranometer measurements made at the surface. The results show that, for two days when near-coincident measurements of single-scattering albedo ω ₀ and τ _s are available, the root-mean-square errors between the measured and calculated DSWI for daytime data are within 30 W m⁻². For five days during SCAR-B, however, when assumptions about ω ₀ have to be made and also when τ _s was significantly higher, the differences can be as large as 100 W m⁻². At TOA, the SWARF per unit optical thickness ranges from −20 to −60 W m⁻² over four major ecosystems in South America. The results show that τ _s and ω ₀ are the two most important parameters that affect DSWI calculations. For SWARF values, surface albedos also play an important role. It is shown that ω ₀ must be known within 0.05 and τ _s at 0.55 μm must be known to within 0.1 to estimate DSWI to within 20 W m⁻². The methodology described in this paper could serve as a potential strategy for determining DSWI values in the presence of aerosols. The wavelength dependence of τ _s and ω ₀ over the entire shortwave spectrum is needed to improve radiative transfer calculations. If global retrievals of DSWI and SWARF from satellite measurements are to be performed in the presence of biomass-burning aerosols on a routine basis, a concerted effort should be made to develop methodologies for estimating ω ₀ and τ _s from satellite and ground-based measurements.

Abstract

This study details two unique methods to quantify cloud-immersion statistics for tropical montane cloud forests (TMCFs). The first technique uses a new algorithm for determining cloud-base height using Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products, and the second method uses numerical atmospheric simulation along with geostationary satellite data. Cloud-immersion statistics are determined using MODIS data for March 2003 over the study region consisting of Costa Rica, southern Nicaragua, and northern Panama. Comparison with known locations of cloud forests in northern Costa Rica shows that the MODIS-derived cloud-immersion maps successfully identify known cloud-forest locations in the United Nations Environment Programme (UNEP) World Conservation Monitoring Centre (WCMC) database. Large connected regions of cloud immersion are observed in regions in which the trade wind flow is directly impinging upon the mountain slopes; in areas in which the flow is parallel to the slopes, a fractured spatial distribution of TMCFs is observed. Comparisons of the MODIS-derived cloud-immersion map with the model output show that the MODIS product successfully captures the important cloud-immersion patterns in the Monteverde region of Costa Rica. The areal extent of cloud immersion is at a maximum during morning hours and at a minimum during the afternoon, before increasing again in the evening. Cloud-immersion frequencies generally increase with increasing elevation and tend to be higher on the Caribbean Sea side of the mountains. This study shows that the MODIS data may be used successfully to map the biogeography of cloud forests and to quantify cloud immersion over cloud-forest locations.