ALBERT

Description: The goal of this study was to determine, through modeling, the impact of aircraft emissions on regional air quality, especially in regard to fine particulate matter (PM(2.5)) as well as ozone and other pollutants. For this, we focused on Hartsfield-Jackson Atlanta International Airport which is the busiest airport in the world based on passenger traffic (AIC, 2003). Hartsfield-Jackson serves the metropolitan Atlanta area where air quality does not meet national standards. Emissions from mobile and industrial sources (including several large electric power generating utilities) are the major contributors to the area's air pollution. In this study, we assessed the impact of Hartsfield-Jackson Airport on air quality around Atlanta, Georgia, and compared it to the impacts of other emission sources in the area. The assessment was built upon other, related air quality studies involving both field and modeling components. To achieve the objectives, first a detailed inventory was developed for aircraft and other emissions at Hartsfield-Jackson Atlanta International Airport. Then, air quality simulations were performed to relate these emissions to regional air quality around Atlanta. The Community Multiscale Air Quality Model (CMAQ) was used as the modeling platform. The period of August 11-20 2000 was selected as the episode to be modeled in this study. Prior modeling of this episode during the Fall Line Air Quality Study (FAQS) and availability of additional PM(2.5) measurements for evaluation played a major role in this selection. Meteorological data for this episode as well as emission data for sources other than aircrafts were already available from FAQS.

Description: The project goals are: Make data analysis faster and cheaper. Increase use of NASA data by removing barriers to data access. Cope with data heterogeneity. Support code reuse and rapid application development. Support multiple applications, users. Including fire and health domains. Improve QOS. Always provide an answer. Tell user how good it is, where it come from.

Description: A 3-D weather radar visualization software program was developed and implemented as part of an experimental Launch Pad 39 Hail Monitor System. 3DRadPlot, a radar plotting program, is one of several software modules that form building blocks of the hail data processing and analysis system (the complete software processing system under development). The spatial and temporal mapping algorithms were originally developed through research at the University of Central Florida, funded by NASA s Tropical Rainfall Measurement Mission (TRMM), where the goal was to merge National Weather Service (NWS) Next-Generation Weather Radar (NEXRAD) volume reflectivity data with drop size distribution data acquired from a cluster of raindrop disdrometers. In this current work, we adapted these algorithms to process data from a cluster of hail disdrometers positioned around Launch Pads 39A or 39B, along with the corresponding NWS radar data. Radar data from all NWS NEXRAD sites is archived at the National Climatic Data Center (NCDC). That data can be readily accessed at 〈http://www.ncdc.noaa.gov /nexradin/〉. 3DRadPlot plots Level III reflectivity data at four scan elevations (this software is available at Open Channel Software, 〈http://www.openchannelfoundation.org/projects/3DRadPlot〉). By using spatial and temporal interpolation/extrapolation based on hydrometeor fall dynamics, we can merge the hail disdrometer array data coupled with local Weather Surveillance Radar-1988, Doppler (WSR-88D) radial velocity and reflectivity data into a 4-D (3-D space and time) picture of hail size distributions. Hail flux maps can then be generated and used for damage prediction and assessment over specific surfaces corresponding to structures within the disdrometer array volume. Immediately following a hail storm, specific damage areas and degree of damage can be identified for inspection crews.

Description: Several meteorological datasets, including U.K. Met Office (MetO), European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP), and NASA's Goddard Earth Observation System (GEOS-4) analyses, are being used in studies of the 2002 Southern Hemisphere (SH) stratospheric winter and Antarctic major warming. Diagnostics are compared to assess how these studies may be affected by the meteorological data used. While the overall structure and evolution of temperatures, winds, and wave diagnostics in the different analyses provide a consistent picture of the large-scale dynamics of the SH 2002 winter, several significant differences may affect detailed studies. The NCEP-NCAR reanalysis (REAN) and NCEP-Department of Energy (DOE) reanalysis-2 (REAN-2) datasets are not recommended for detailed studies, especially those related to polar processing, because of lower-stratospheric temperature biases that result in underestimates of polar processing potential, and because their winds and wave diagnostics show increasing differences from other analyses between similar to 30 and 10 hPa (their top level). Southern Hemisphere polar stratospheric temperatures in the ECMWF 40-Yr Re-analysis (ERA-40) show unrealistic vertical structure, so this long-term reanalysis is also unsuited for quantitative studies. The NCEP/Climate Prediction Center (CPC) objective analyses give an inferior representation of the upper-stratospheric vortex. Polar vortex transport barriers are similar in all analyses, but there is large variation in the amount, patterns, and timing of mixing, even among the operational assimilated datasets (ECMWF, MetO, and GEOS-4). The higher-resolution GEOS-4 and ECMWF assimilations provide significantly better representation of filamentation and small-scale structure than the other analyses, even when fields gridded at reduced resolution are studied. The choice of which analysis to use is most critical for detailed transport studies (including polar process modeling) and studies involving synoptic evolution in the upper stratosphere. The operational assimilated datasets are better suited for most applications than the NCEP/CPC objective analyses and the reanalysis datasets.

Description: This document is a chart showing the inputs to and outputs from various parts of the integrated climate model.

Description: The general climate of the island of Puerto Rico is dominated by the easterly trade winds from the Atlantic Ocean, and during synoptically calm days by the topographic and local land surface characteristics [1]. The urban canopy of the metropolitan area of San Juan, capital city of the Island, may introduce a new microclimate that changes the characteristics of the low atmosphere and interacts with the other microclimates already present in the island. The primitive land cover and land use (LCLU) of the metropolitan area of San Juan was composed by broadleaf trees, moist soils, and very dense vegetation in general. The urban LCLU changes the balance for the mass, momentum and energy between the bottom boundary and the lower atmosphere, creating different climate conditions over urban and rural regions. Some of these differences are low relative humidity and high temperatures observed in urban areas when compared to rural areas. These in turn produces a convective circulation over the urban areas, a phenomenon compared to the sea and land breezes, commonly known as heat islands (UHI). Factors that contribute to the formation of the UHI are anthropogenic heat sources, aerosols from pollutants, fast water canalization due to the presence of buildings and streets, among others. The comparison between urban and rural climates is the most common approach to analyze the UHI. These contrasts are larger in clear and calm conditions and tend to disappear in cloudy and windy weather. The UHI was recognized in the early 1950 s as closed isotherms that separates the city from the general temperature field [2]. The impact of the urban LCLU in San Juan, Puerto Rico, was quantified calculating the difference between historical data sets for the air temperature over an identified urban area and a rural area dT(U-R). The analysis of the climatological data revealed that a UHI exists in the metropolitan area of San Juan, Puerto Rico. The data reveals a permanent urban heat island effect present in the SJMA during the year, which is increasing at a rate of 0.41oC/decade. These findings encouraged the planning and execution of an intense field campaign in February 2004 referred as the ATLAS San Juan mission. The focus of the remaining of this report is the analysis of the data for this field campaign.

Description: During its first three years, the Tropical Rainfall Measuring Mission (TRMM) satellite observed nearly six million precipitation features. The population of precipitation features is sorted by lightning flash rate, minimum brightness temperature, maximum radar reflectivity. areal extent, and volumetric rainfall. For each of these characteristics, essentially describing the convective intensity or the size of the features, the population is broken into categories consisting of the top 0.001%, top 0.01%, top 0.1%, top 1%, top 2.4%. and remaining 97.6%. The set of weakest/smallest features composes 97.6% of the population because that fraction does not have detected lightning, with a minimum detectable flash rate of 0.7 flashes (fl) per minute. The greatest observed flash rate is 1351 fl per minute; the lowest brightness temperatures are 42 K (85 GHz) and 69 K (37 GHz). The largest precipitation feature covers 335 000 square kilometers and the greatest rainfall from an individual precipitation feature exceeds 2 x 10 kg per hour of water. There is considerable overlap between the greatest storms according to different measures of convective intensity. The largest storms are mostly independent of the most intense storms. The set of storms producing the most rainfall is a convolution of the largest and the most intense storms. This analysis is a composite of the global Tropics and subtropics. Significant variability is known to exist between locations. seasons, and meteorological regimes. Such variability will be examined in Part II. In Part I, only a crude land-ocean separation is made. The known differences in bulk lightning flash rates over land and ocean result from at least two differences in the precipitation feature population: the frequency of occurrence of intense storms and the magnitude of those intense storms that do occur. Even when restricted to storms with the same brightness temperature, same size, or same radar reflectivity aloft, the storms over water are considerably less likely to produce lightning than are comparable storms over land.

Description: The existence of the Saharan air layer (SAL), a layer of warm, dry, dusty air that frequently moves westward off of the Saharan desert of Africa and over the tropical Atlantic Ocean, has long been appreciated. As air moves over the desert, it is strongly heated from below, producing a very hot air mass at low levels. Because there is no moisture source over the Sahara, the rise in temperature causes a sharp drop in relative humidity, thus drying the air. In addition, the warm air produces a very strong jet of easterly flow in the middle troposphere called the African easterly jet that is thought to play a critical role in hurricane formation. In recent years, there has been an increased focus on the impact that the SAL has on the formation and evolution of hurricanes in the Atlantic. However, the nature of its impact remains unclear, with some researchers arguing that the SAL amplifies hurricane development and with others arguing that it inhibits it. The argument for positively influencing hurricane development is based upon the fact that the African easterly jet produces the waves that eventually form hurricanes and that it leads to rising motion south of the jet that favors the development of deep thunderstorm clouds. The potential negative impacts of the SAL include 1) low-level vertical wind shear associated with the African easterly jet; 2) warm SAL air aloft, which increases thermodynamic stability and suppresses cloud development; and 3) dry air, which produces cold downdrafts in precipitating regions, thereby removing energy needed for storm development. As part of this recent focus on the SAL and hurricanes (which motivated a 2006 NASA field experiment), there has been little emphasis on the SAL s potential positive influences and almost complete emphasis on its possible negative influences, almost to the point of claims that the SAL is the major suppressing influence on hurricanes in the Atlantic. Multiple NASA satellite data sets (TRMM, MODIS, and AIRS/AMSU) and National Centers for Environmental Prediction global analyses are used to characterize the SAL s properties and evolution in relation to developing hurricanes. The results show that storms generally form on the southern side of the jet, where favorable background rotation is high. The jet often helps to form the northern side of the storms and rarely moves over their inner cores, so jet-induced vertical wind shear does not appear to be a negative influence on developing storms. Warm SAL air is confined to regions north of the jet and generally does not impact the tropical cyclone precipitation south of the jet. Of the three proposed negative influences, dry air appears to be the key influence; however, the presence of dry SAL air is not a good indicator of whether a storm will weaken since many examples of intensifying storms surrounded by such dry air can be found. In addition, a global view of relative humidity shows moisture distributions in other ocean basins that are almost identical to the Atlantic. The dry zones correspond to regions of descending air on the eastern and equatorward sides of semi-permanent oceanic high pressure systems. Thus, the dry air over the Atlantic appears to be primarily a product of the large-scale flow, but with enhanced drying at low levels associated with the Sahara. As a result, we conclude that the SAL is not a major negative influence on hurricanes. It is just one of many possible influences and can be both positive and negative.

Description: Vertical and latitudinal changes in the stratospheric ozone in the post-chlorofluorocarbon (CFC) era are investigated using simulations of the recent past and the 21st century with a coupled chemistry-climate model. Model results reveal that, in the 2060s when the stratospheric halogen loading is projected to return to its 1980 values, the extratropical column ozone is significantly higher than that in 1975-1984, but the tropical column ozone does not recover to 1980 values. Upper and lower stratospheric ozone changes in the post- CFC era have very different patterns. Above 15 hPa ozone increases almost latitudinally uniformly by 6 Dobson Unit (DU), whereas below 15 hPa ozone decreases in the tropics by 8 DU and increases in the extratropics by up to 16 DU. The upper stratospheric ozone increase is a photochemical response to greenhouse gas induced strong cooling, and the lower stratospheric ozone changes are consistent with enhanced mean advective transport due to a stronger Brewer-Dobson circulation. The model results suggest that the strengthening of the Brewer-Dobson circulation plays a crucial role in ozone recovery and ozone distributions in the post-CFC era.

Description: Over the years, hurricane track and intensity forecasts and storm surge models and the digital terrain and bathymetry data they depend on have improved significantly. Strides have also been made in knowledge of the detailed variation of the surface wind field driving the surge. The area of least improvement has been in obtaining data on the details of the temporal/spatial variation of the storm surge dome of water as it evolves and inundates the land to evaluate the performance of the numerical models. Tide gages in the vicinity of the landfall are frequently destroyed by the surge. Survey crews dispatched after the event provide no temporal information and only indirect indications of the maximum surge envelope over land. The landfall of Hurricane Bonnie on 26 August 1998, with a surge less than 2 m, provided an excellent opportunity to demonstrate the potential benefits of direct airborne measurement of the temporal/spatial evolution of storm surge. Despite a 160 m variation in aircraft altitude, an 11.5 m variation in the elevation of the mean sea surface relative to the ellipsoid over the flight track, and the tidal variation over the 5 hour data acquisition interval, a survey-quality Global Positioning System (GPS) aircraft trajectory allowed the NASA Scanning Radar Altimeter carried by a NOAA hurricane research aircraft to produce storm surge measurements that generally fell between the predictions of the NOAA SLOSH model and the North Carolina State University storm surge model.