Search

Ozone (O3) is a toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address the limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product. TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME (Global Ozone Monitoring Experiment), GOME-2, and OMI (Ozone Monitoring Instrument). This algorithm is suggested to use a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB-Clim) O3 climatology). This study evaluates the TB-Clim dataset and model simulated O3 profiles, which could potentially serve as a priori O3 profile information in TEMPO retrievals, from near-real-time data assimilation model products (NASA GMAO's (Global Modeling and Assimilation Office) operational GEOS-5 (Goddard Earth Observing System, Version 5) FP (Forecast Products) model and reanalysis data from MERRA2 (Modern-Era Retrospective analysis for Research and Applications, Version 2)) and a full chemical transport model (CTM), GEOS-Chem. In this study, vertical profile products are evaluated with surface (0-2 kilometers) and tropospheric (0-10 kilometers) TOLNet (Tropospheric Ozone Lidar Network) observations and the theoretical impact of individual a priori profile sources on the accuracy of TEMPO O3 retrievals in the troposphere and at the surface are presented. Results indicate that while the TB-Clim climatological dataset can replicate seasonally-averaged tropospheric O3 profiles, model-simulated profiles from a full CTM resulted in more accurate tropospheric and surface-level O3 retrievals from TEMPO when compared to hourly and daily-averaged TOLNet observations. Furthermore, it is shown that when large surface O3 mixing ratios are observed, TEMPO retrieval values at the surface are most accurate when applying CTM a priori profile information compared to all other data products.

Ozone (O3) is a greenhouse gas and toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is primarily conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address these limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product. TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME, GOME-2, and OMI. This algorithm uses a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB) O3 climatology). It has been shown that satellite O3 retrievals are sensitive to a priori O3 profiles and covariance matrices. During this work we investigate the climatological data to be used in TEMPO algorithms (TB O3) and simulated data from the NASA GMAO Goddard Earth Observing System (GEOS-5) Forward Processing (FP) near-real-time (NRT) model products. These two data products will be evaluated with ground-based lidar data from the Tropospheric Ozone Lidar Network (TOLNet) at various locations of the US. This study evaluates the TB climatology, GEOS-5 climatology, and 3-hourly GEOS-5 data compared to lower tropospheric observations to demonstrate the accuracy of a priori information to potentially be used in TEMPO O3 algorithms. Here we present our initial analysis and the theoretical impact on TEMPO retrievals in the lower troposphere.

Laminar ozone structure is a ubiquitous feature of tropospheric-ozone distributions resulting from dynamic and chemical atmospheric processes. Understanding the characteristics of these ozone laminae and the mechanisms responsible for producing them is important to outline the transport pathways of trace gases and to quantify the impact of different sources on tropospheric background ozone. In this study, we present a new method to detect ozone laminae to understand their climatological characteristics of occurrence frequency in terms of thickness and altitude. We employ both ground-based and airborne ozone lidar measurements and other synergistic observations and modeling to investigate the sources and mechanisms such as biomass burning transport, stratospheric intrusion, lightning-generated NOx, and nocturnal low-level jets that are responsible for depleted or enhanced tropospheric ozone layers. Spaceborne (e.g., OMI (Ozone Monitoring Instrument), TROPOMI (Tropospheric Monitoring Instrument), TEMPO (Tropospheric Emissions: Monitoring of Pollution)) measurements of these laminae will observe greater horizontal extent and lower vertical resolution than balloon-borne or lidar measurements will quantify. Using integrated ground-based, airborne, and spaceborne observations in a modeling framework affords insight into how to gain knowledge of both the vertical and horizontal evolution of these ubiquitous ozone laminae.

UNKNOWN

Tropospheric ozone lidars are well suited to measuring the high spatio-temporal variability of this important trace gas. Furthermore, lidar measurements in conjunction with balloon soundings, aircraft, and satellite observations provide substantial information about a variety of atmospheric chemical and physical processes. Examples of processes elucidated by ozone-lidar measurements are presented, and modeling studies using WRF-Chem, RAQMS, and DALES/LES models illustrate our current understanding and shortcomings of these processes.

The purpose of this project is to see whether ozone maxima measured by the DIfferential Absorption Lidar (DIAL) instrument in Huntsville, AL may be traced back to lightning events occurring 24‐48 hours beforehand. The methodology is to start with lidar measurements of ozone from DIAL. The HYbrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model is then used to determine the origin of these ozone maxima 24‐48 hours prior. Data from the National Lightning Detection Network (NLDN) are used to examine the presence/absence of lightning along the trajectory. This type of analysis suggests that lightning‐produced NOx may be responsible for some of the ozone maxima over Huntsville.

The purpose of this project is to see whether ozone maxima measured by the DIfferential Absorption Lidar (DIAL) instrument in Huntsville, AL may be traced back to lightning events occurring 24‐ 48 hours beforehand. The methodology is to start with lidar measurements of ozone from DIAL as well as ozonesonde measurements. The HYbrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model is then used to determine the origin of these ozone maxima 24‐48 hours prior. Data from the National Lightning Detection Network (NLDN) are used to examine the presence/absence of lightning along the trajectory. This type of analysis suggests that lightning‐produced NOx may be responsible for some of the ozone maxima over Huntsville.

A tropospheric ozone DIfferential Absorption Lidar (DIAL) system has been developed jointly by NASA and the University of Alabama at Huntsville (UAH). Two separated Nd:YAG pumped dye laser systems produce the laser pulses with wavelengths of 285 and 291 nm at 20 Hz frequency. The receiver is a Newtonian telescope with a 40 cm primary and a two-channel aft optics unit. The detection system currently uses photon counting to facilitate operations at the maximum achievable altitude. This lidar measures free-tropospheric ozone profiles between 4-10 km at Regional Atmospheric Profiling Laboratory for Discovery (RAPCD) in UAH campus (ASL 206 m) under both daytime and nighttime conditions. Frequent coincident ozonesonde flights and theoretical calculations provide evidence to indicate the retrieval accuracy ranges from approx.5% at 4 km to approx.60% at 10 km with 750-m vertical resolution and 30-minute integration. Three Hamamatsu 7400 PMTs and analog detection technique will be added on the current system to extend the measurement to approx.100 m above ground to monitor the PBL and lower tropospheric ozone variations.

Analyses from SAGE I/II version 6.0 data exhibit upper stratospheric ozone trends which are not significantly different from those in version 5.96 data. Trend calculations show larger downward trends at mid-high latitudes in the Southern Hemisphere than in the Northern Hemisphere, particularly in 1980s. There are also indications of decreasing downward trends with time from 1979 to 1999. We have used a chemical box model and the UARS measurements of long lived gases, CH4, H2O, NO(x), and temperature to show that, with a constant Cl(sub y) trend, a hemispheric ozone trend asymmetry of 1%/decade at 45 deg. around 43 km is expected due to the hemispheric differences of temperature and CH4 during late winter/early. Also ozone trends should have been approximately 1%/decade more negative from 1979-1989 than from 1989-1999 because of the chemical feedbacks. The model results further indicate that both the reported decrease in CH4 and the increase in H2O in HALOE measurements will result in a larger downward ozone trend and a decrease in the hemispheric ozone trend asymmetry.

This proposed research sought to use SAGE I and II ozone and aerosol measurements to reduce the variability in ozone trends, principally, but not exclusively, in layer 8 (40 km) derived from multiple Umkehr stations. Building on our experience with both SAGE and Umkehr data, we proposed to commence at the very beginning of the Umkehr process (measured radiance ratios) and proceed through the fitting and inversion processes in conjunction with radiative transfer calculations to establish a consistent, reliable time series of Umkehr ozone profiles at a number of stations. We expected to be able to reconcile the present discrepancies between SAGE and Umkehr trends in the upper stratosphere and, in particular, to reduce the variability in trend estimates among mid-latitude Umkehr stations.