Engineering topics

Burrows, John P.

Publications and source records attributed to Burrows, John P..

9 records

DOE OSTI2023

Validation of the Cloud_CCI (Cloud Climate Change Initiative) cloud products in the Arctic

The role of clouds in the Arctic radiation budget is not well understood. Ground-based and airborne measurements provide valuable data to test and improve our understanding. However, the ground-based measurements are intrinsically sparse, and the airborne observations are snapshots in time and space. Passive remote sensing measurements from satellite sensors offer high spatial coverage and an evolving time series, having lengths potentially of decades. However, detecting clouds by passive satellite remote sensing sensors is challenging over the Arctic because of the brightness of snow and ice in the ultraviolet and visible spectral regions and because of the small brightness temperature contrast to the surface. Consequently, the quality of the resulting cloud data products needs to be assessed quantitatively. In this study, we validate the cloud data products retrieved from the Advanced Very High Resolution Radiometer (AVHRR) post meridiem (PM) data from the polar-orbiting NOAA-19 satellite and compare them with those derived from the ground-based instruments during the sunlit months. The AVHRR cloud data products by the European Space Agency (ESA) Cloud Climate Change Initiative (Cloud_CCI) project uses the observations in the visible and IR bands to determine cloud properties. The ground-based measurements from four high-latitude sites have been selected for this investigation: Hyytiälä (61.84°N, 24.29°E), North Slope of Alaska (NSA; 71.32°N, 156.61°W), Ny-Ålesund (Ny-Å; 78.92°N, 11.93°E), and Summit (72.59°N, 38.42°W). The liquid water path (LWP) ground-based data are retrieved from microwave radiometers, while the cloud top height (CTH) has been determined from the integrated lidar–radar measurements. The quality of the satellite products, cloud mask and cloud optical depth (COD), has been assessed using data from NSA, whereas LWP and CTH have been investigated over Hyytiälä, NSA, Ny-Å, and Summit.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2018

Total Ozone Trends from 1979 to 2016 Derived from Five Merged Observational Datasets - The Emergence into Ozone Recovery

We report on updated trends using different merged datasets from satellite and ground-based observations for the period from 1979 to 2016. Trends were determined by applying a multiple linear regression (MLR) to annual mean zonal mean data. Merged datasets used here include NASA MOD v8.6 and National Oceanic and Atmospheric Administration (NOAA) merge v8.6, both based on data from the series of Solar Backscatter UltraViolet (SBUV) and SBUV-2 satellite instruments (1978â€“present) as well as the Global Ozone Monitoring Experiment (GOME)-type Total Ozone (GTO) and GOME-SCIAMACHY-GOME-2 (GSG) merged datasets (1995-present), mainly comprising satellite data from GOME, the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and GOME-2A. The fifth dataset consists of the monthly mean zonal mean data from ground-based measurements collected at World Ozone and UV Data Center (WOUDC). The addition of four more years of data since the last World Meteorological Organization (WMO) ozone assessment (2013-2016) shows that for most datasets and regions the trends since the stratospheric halogen reached its maximum (approximately 1996 globally and approximately 2000 in polar regions) are mostly not significantly different from zero. However, for some latitudes, in particular the Southern Hemisphere extratropics and Northern Hemisphere subtropics, several datasets show small positive trends of slightly below +1 percent decade(exp. -1) that are barely statistically significant at the 2 Sigma uncertainty level. In the tropics, only two datasets show significant trends of +0.5 to +0.8 percent(exp.-1), while the others show near-zero trends. Positive trends since 2000 have been observed over Antarctica in September, but near-zero trends are found in October as well as in March over the Arctic. Uncertainties due to possible drifts between the datasets, from the merging procedure used to combine satellite datasets and related to the low sampling of ground-based data, are not accounted for in the trend analysis. Consequently, the retrieved trends can be only considered to be at the brink of becoming significant, but there are indications that we are about to emerge into the expected recovery phase. However, the recent trends are still considerably masked by the observed large year-to-year dynamical variability in total ozone.

column ozone trends↗

NASA NTRS2014

Anthropogenic and Volcanic Contributions to the Decadal Variations of Aerosols in the Upper Troposphere and Lower Stratosphere

We investigated the anthropogenic and volcanic contributions to sulfate aerosol in the stratosphere through modeling and analysis of satellite data. We use a global model GOCART to simulate SO2 and sulfate aerosol in the period of 2000 to 2010, during which numerous volcanic eruptions occurred although nothing like the magnitudes of El Chichon or Pinatubo. We compared the model results with the column SO2 data from OMI and stratospheric SO2 data from MLS instrument on Aura satellite and the aerosol vertical profiles from the SCIAMACHY instrument on Envisat and the CALIOP instrument on CALIPSO satellites. Finally, we assessed the relative contributions of volcanic aerosols vs. anthropogenic aerosols to the observed decadal stratospheric aerosol trends.

HTAP2/AeroCom3 model↗

NASA NTRS2012

Field and Satellite Observations of the Formation and Distribution of Arctic Atmospheric Bromine Above a Rejuvenated Sea Ice Cover

Recent drastic reduction of the older perennial sea ice in the Arctic Ocean has resulted in a vast expansion of younger and saltier seasonal sea ice. This increase in the salinity of the overall ice cover could impact tropospheric chemical processes. Springtime perennial ice extent in 2008 and 2009 broke the half-century record minimum in 2007 by about one million km2. In both years seasonal ice was dominant across the Beaufort Sea extending to the Amundsen Gulf, where significant field and satellite observations of sea ice, temperature, and atmospheric chemicals have been made. Measurements at the site of the Canadian Coast Guard Ship Amundsen ice breaker in the Amundsen Gulf showed events of increased bromine monoxide (BrO), coupled with decreases of ozone (O3) and gaseous elemental mercury (GEM), during cold periods in March 2008. The timing of the main event of BrO, O3, and GEM changes was found to be consistent with BrO observed by satellites over an extensive area around the site. Furthermore, satellite sensors detected a doubling of atmospheric BrO in a vortex associated with a spiral rising air pattern. In spring 2009, excessive and widespread bromine explosions occurred in the same region while the regional air temperature was low and the extent of perennial ice was significantly reduced compared to the case in 2008. Using satellite observations together with a Rising-Air-Parcel model, we discover a topographic control on BrO distribution such that the Alaskan North Slope and the Canadian Shield region were exposed to elevated BrO, whereas the surrounding mountains isolated the Alaskan interior from bromine intrusion.

Nghiem, Son V.↗

NASA NTRS2008

Remote Sensing of Tropospheric Pollution from Space

We review the progress of tropospheric trace gas observations and address the need for additional measurement capabilities as recommended by the National Academy of Science (NAS, 2007). Tropospheric measurements from current and earlier instruments show pollution in the Northern Hemisphere as a result of fossil fuel burning and a strong seasonal dependence with the largest amounts of photochemically-generated ozone in summer. At low latitudes, where photon flux is stronger throughout the year, trace gas concentrations are driven by the abundance of the emissions, where the largest source, biomass burning, is readily seen in carbon monoxide measurements, but lightning and biogenic trace gases may also contribute to trace gas variability. Although substantive progress has been achieved in seasonal and global mapping of a few tropospheric trace gases, satellite trace-gas observations with considerably better temporal and spatial resolution are essential to forecasting air quality at scales required by policy-makers. The concurrent use of atmospheric composition measurements for both scientific and operational purposes is a new paradigm for the atmospheric chemistry community. The examples presented illustrate both the promise and challenge of merging satellite information with in situ observations in state-of-the-art data assimilation models.

Fishman, Jack↗

NASA NTRS2003

A Model Study of the Impact of Magnetic Field Reversal on Atmospheric Composition during Solar Proton Events

During a polarity transition of the Earth's magnetic field, the structure and strength of the field change significantly from their present values. This will alter the global pattern of charged particle precipitation into the atmosphere. Thus, particle precipitation is possible into regions that are at the moment effectively shielded by the Earth's magnetic field. A two-dimensional global fbHy coupled chemistry, radiation, and transport model of the atmosphere has been used to investigate how the increased particle precipitation affects the chemical composition of the middle and lower atmosphere. Ozone losses resulting from large energetic particle events are found to increase significantly, with resultant losses similar to those observed m the Antarctic ozone hole of the 1990s. This results in significant increases in surface UV-B radiation as well as changes in stratospheric temperature and circulation over a period of several months after large particle events.

Sinnhuber, Miaiam↗

NASA NTRS1994

Ozone profile retrievals from the ESA GOME instrument

The potential of the ESA Global Ozone Monitoring Experiment (GOME) to produce ozone profile information has been examined by carrying out two sample retrievals using simulated GOME data. The first retrieval examines the potential of the GOME instrument to produce stratospheric ozone profiles using the traditional back-scatter ultraviolet technique, while the second examines the possibility of obtaining tropospheric profile information, and improving the quality of the stratospheric profile retrievals, by exploiting the temperature dependence of the ozone Huggins bands.

Munro, Rosemary↗

NASA NTRS1991

Retrieval and molecule sensitivity studies for the global ozone monitoring experiment and the scanning imaging absorption spectrometer for atmospheric chartography

The Global Ozone Monitoring Experiment (GOME) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) are diode based spectrometers that will make atmospheric constituent and aerosol measurements from European satellite platforms beginning in the mid 1990's. GOME measures the atmosphere in the UV and visible in nadir scanning, while SCIAMACHY performs a combination of nadir, limb, and occultation measurements in the UV, visible, and infrared. A summary is presented of the sensitivity studies that were performed for SCIAMACHY measurements. As the GOME measurement capability is a subset of the SCIAMACHY measurement capability, the nadir, UV, and visible portion of the studies is shown to apply to GOME as well.

Chance, Kelly V.↗

NASA NTRS1991

Scanning imaging absorption spectrometer for atmospheric chartography

The SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY is an instrument which measures backscattered, reflected, and transmitted light from the earth's atmosphere and surface. SCIAMACHY has eight spectral channels which observe simultaneously the spectral region between 240 and 1700 nm and selected windows between 1940 and 2400 nm. Each spectral channel contains a grating and linear diode array detector. SCIAMACHY observes the atmosphere in nadir, limb, and solar and lunar occultation viewing geometries.

Burrows, John P.↗