Donna V. Kliche

First estimates of the radiative forcing of aerosols generated from biomass burning using satellite data

Collocated measurements from the Advanced Very High Resolution Radiometer (AVHRR) and the Earth Radiation Budget Experiment (ERBE) scanner are used to examine the radiative forcing of atmospheric aerosols generated from biomass burning for 13 images in South America. Using the AVHRR, Local Area Coverage (LAC) data, a new technique based on a combination of spectral and textural measures is developed for detecting these aerosols. Then, the instantaneous shortwave, longwave, and net radiative forcing values are computed from the ERBE instantaneous scanner data. Results for the selected samples from 13 images show that the mean instantaneous net radiative forcing for areas with heavy aerosol loading is about -36 W/sq m and that for the optically thin aerosols are about -16 W/sq m. These results, although preliminary, provide the first estimates of radiative forcing of atmospheric aerosols from biomass burning using satellite data.

The Bias in Moment Estimators for Parameters of Drop Size Distribution Functions: Sampling from Exponential Distributions

Abstract The moment estimators frequently used to estimate parameters for drop size distribution (DSD) functions being “fitted” to observed raindrop size distributions are biased. Consequently, the fitted functions often do not represent well either the raindrop samples or the underlying populations from which the samples were taken. Monte Carlo simulations of the process of sampling from a known exponential DSD, followed by the application of a variety of moment estimators, demonstrate this bias. Skewness in the sampling distributions of the DSD moments is the root cause of this bias, and this skewness increases with the order of the moment. As a result, the bias is stronger when higher-order moments are used in the procedures. Correlations of the sample moments with the size of the largest drop in a sample (Dmax) lead to correlations of the estimated parameters with Dmax, and, in turn, to spurious correlations between the parameters. These things can lead to erroneous inferences about characteristics of...

Satellite investigations of fire, smoke, and carbon monoxide during April 1994 MAPS mission: Case studies over tropical Asia

During April 9–19, 1994, the Measurement of Air Pollution from Satellites (MAPS) measured free tropospheric carbon monoxide (CO) concentrations on a near-global basis. For these eleven days the global 1 km advanced very high resolution radiometer (AVHRR) Pathfinder data are used to detect fires and smoke over the Indo-Burma region (85°E-110°E; 10°N-30°N). The fire activities are categorized for four major ecosystems that include (1) cropland/natural vegetation mosaic (CNVM), (2) evergreen broadleaf forest (EBF), (3) mixed forest (MFD), and (4) grassland (GL). Using published emission rates between particulate matter and carbon monoxide concentrations from temperate areas, the fire counts along with other information are used to obtain estimates of CO concentrations from the AVHRR data. More than 7000 fires are detected during the study period with 23%, 43%, 24%, and 10% fires in the CNVM, EBF, MFD, and GL ecosystems, respectively. The enhanced CO concentrations over the area of study are either over or downwind of the fires detected by the AVHRR. The preliminary AVHRR estimates of CO concentrations are smaller than the MAPS-measured values by a factor of 4 to 5 for fire counts greater than 200. The differences are attributed to the lack of transport mechanisms and other assumptions in the current model. However, these results show a good potential for using the AVHRR measurements to detect fires and smoke and also to estimate CO concentrations.

The Bias and Error in Moment Estimators for Parameters of Drop Size Distribution Functions: Sampling from Gamma Distributions

Abstract This paper complements an earlier one that demonstrated the bias in the method-of-moments (MM) estimators frequently used to estimate parameters for drop size distribution (DSD) functions being “fitted” to observed raindrop size distributions. Here the authors consider both the bias and the errors in MM estimators applied to samples from known gamma DSDs (of which the exponential DSD treated in the earlier paper is a special case). The samples were generated using a similar Monte Carlo simulation procedure. The skewness in the sampling distributions of the DSD moments that causes this bias is less pronounced for narrower population DSDs, and therefore the bias problems (and also the errors) diminish as the gamma shape parameter increases. However, the bias still increases with the order of the moments used in the MM procedures; thus it is stronger when higher-order moments (such as the radar reflectivity) are used. The simulation results also show that the errors of the estimates of the DSD param...

L-Moment Estimators as Applied to Gamma Drop Size Distributions

Abstract The traditional approach with experimental raindrop size data has been to use the method of moments in the fitting procedure to estimate the parameters for the raindrop size distribution function. However, the moment method is known to be biased and can have substantial errors. Therefore, the L-moment method, which is widely used by hydrologists, was investigated as an alternative. The L-moment method was applied, along with the moment and maximum likelihood methods, to samples taken from simulated gamma raindrop populations. A comparison of the bias and the errors involved in the L-moments, moments, and maximum likelihood procedures shows that, with samples covering the full range of drop sizes, L-moments and maximum likelihood outperform the method of moments. For small sample sizes the moment method gives a large bias and large error while the L-moment method gives results close to the true population values, outperforming even maximum likelihood results. Because the goal of this work is to un...

Comparison of Estimators for Parameters of Gamma Distributions with Left-Truncated Samples

Abstract When fitting a raindrop size distribution using a gamma model from data collected by a disdrometer, some consideration needs to be given to the small drops that fail to be recorded (typical disdrometer minimum size thresholds being in the 0.3–0.5-mm range). To this end, a gamma estimation procedure using maximum likelihood estimation has recently been published. The current work adds another procedure that accounts for the left-truncation problem in the data; in particular, an L-moments procedure is developed. These two estimation procedures, along with a traditional method-of-moments procedure that also accounts for data truncation, are then compared via simulation of volume samples from known gamma drop size distributions. For the range of gamma distributions considered, the maximum likelihood and L-moments procedures—which perform comparably—are found to outperform the procedure of method-of-moments. As these three procedures do not yield simple estimates in closed form, salient details of the...

Modeling Raindrop Size.

Being able to characterize the size of raindrops is useful in a number of fields including meteorology, hydrology, agriculture and telecommunications. Associated with this article are data sets containing surface (i.e. ground-level) measurements of raindrop size from two different instruments and two different geographical locations. Students may begin to develop some sense of the character of raindrop size distributions through some basic exploratory data analysis of these data sets. Teachers of mathematical statistics students will find an example useful for discussing the beta, gamma, lognormal and Weibull probability density models, as well as fitting these by maximum likelihood and assessing the quality of fit. R software is provided by the authors to assist students in these investigations.

Creating the Long-Term T-28 Instrumented Research Aircraft Data Archive

The T-28 armored research aircraft was developed beginning in 1968 with a grant from the National Science Foundation (NSF) to the South Dakota School of Mines and Technology (SDSMT). The modification of the stock military trainer was done under the direction of Paul MacCready with much of the engineering work performed by Robin Williamson. Once it went into service it was operated by the Institute of Atmospheric Sciences (IAS) at the SDSMT. From 1970 through 2003 it participated in regional, national and international convective storm research projects.

Remote sensing of global fire patterns, aerosol optical thickness, and carbon monoxide during April 1994

The current study examines global fire patterns, aerosol optical thickness (AOT) and carbon monoxide concentrations during April 9-19, 1994. Recently, global Advanced Very High Resolution Radiometer (AVHRR) data at nadir ground spatial resolution of 1 km are made available through the NASANOAA Pathfinder project. These data from April 9-19, 1994 are used to map fires over the Earth. Daytime data with equatorial crossing time of 1340 Local Solar time (LST) from NOAA11 during the ascending orbit is used in this investigation. The main reason for choosing this time period is to compare the fire patterns observed by the astronauts aboard space shuttle SRL-1. During this time, global mid-tropospheric measurements of carbon monoxide were also made from the MAPS instrument onboard the same space shuttle. The elevated levels of CO in the troposphere are often attributed to biomass burning. This provides a unique opportunity to obtain fire distributions from independent methods and to compare fire activities with carbon monoxide concentrations measured by MAPS. One hundred thirty-nine global strips of AVHRR images were used to create this figure. More than 500 fires were detected in the belt between 10-20/spl deg/N which correspond to fire activities in Africa, Mexico, and the Indo-Burma region. These fire activities correspond to biomass burning due to agricultural practices. A comparison with the Olson ecosystem data base shows the majority of fires are in the savanna, grass shrub, and farm settlement categories. When compared to the Northern hemisphere, the Southern hemisphere has a fewer number of fires because April is the dry season in the Northern hemisphere.

Global survey of jet contrails using AVHRR data: spatial distributions and optical property retrievals

Jet contrails are considered to be a subset of thin cirrus clouds. Due to their semitransparent nature, thin cirrus are thought to be enhancers of the greenhouse effect. They are almost transparent to the incoming solar energy reaching the surface, and also they reduce the planetary emissions to space due to their cold temperatures. Jet contrails are considered responsible not so much for increases of cloudiness, but rather to enhance the formation of natural cloudiness. In the present study, one month of daytime global Advanced Very High Resolution Radiometer (AVHIR) data are used to 1) automatically detect contrails, 2) estimate the global frequency of occurrence of contrails, and 3) estimate the optical depth and particle size of jet contrails. One month (April, 1993) of daily AVHRR LAC (Local Area Coverage) satellite data on board the NOAA-11 satellite is used in this investigation.