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Bowman, K. W.

Publications and source records attributed to Bowman, K. W..

MUlti-SpEctral, MUlti-SpEcies, MUlti-SatEllite (MUSES) Retrieval Algorithm: Towards Extending Multi-Decadal NASA EOS Atmospheric Composition Data Records

Multi-Spectra, Multi-Species, Multi-Sensors (MUSES): Builds off of heritage from the Tropospheric Emission Spectrometer (TES) optimal estimation (OE) algorithm to combine a priori and satellite data, including rigorous error analysis diagnostics and observation operators needed for trend analysis, climate model evaluation, and data assimilation; has generic design to incorporate forward model radiances from hyperspectral measurements from multiple sensors into the joint retrieval algorithm.

Fu, Dejian↗

The Atmospheric Infrared Sounder Version 6 Cloud Products

The version 6 cloud products of the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) instrument suite are described. The cloud top temperature, pressure, and height and effective cloud fraction are now reported at the AIRS field-of-view (FOV) resolution. Significant improvements in cloud height assignment over version 5 are shown with FOV-scale comparisons to cloud vertical structure observed by the CloudSat 94 GHz radar and the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP). Cloud thermodynamic phase (ice, liquid, and unknown phase), ice cloud effective diameter D(sub e), and ice cloud optical thickness (τ) are derived using an optimal estimation methodology for AIRS FOVs, and global distributions for 2007 are presented. The largest values of tau are found in the storm tracks and near convection in the tropics, while D(sub e) is largest on the equatorial side of the midlatitude storm tracks in both hemispheres, and lowest in tropical thin cirrus and the winter polar atmosphere. Over the Maritime Continent the diurnal variability of tau is significantly larger than for the total cloud fraction, ice cloud frequency, and D(sub e), and is anchored to the island archipelago morphology. Important differences are described between northern and southern hemispheric midlatitude cyclones using storm center composites. The infrared-based cloud retrievals of AIRS provide unique, decadal-scale and global observations of clouds over portions of the diurnal and annual cycles, and capture variability within the mesoscale and synoptic scales at all latitudes.

infrared instruments↗

Tropospheric Ozone Changes, Radiative Forcing and Attribution to Emissions in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP)

Ozone (O3) from 17 atmospheric chemistry models taking part in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) has been used to calculate tropospheric ozone radiative forcings (RFs). All models applied a common set of anthropogenic emissions, which are better constrained for the present-day than the past. Future anthropogenic emissions follow the four Representative Concentration Pathway (RCP) scenarios, which define a relatively narrow range of possible air pollution emissions. We calculate a value for the pre-industrial (1750) to present-day (2010) tropospheric ozone RF of 410 mW m−2. The model range of pre-industrial to present-day changes in O3 produces a spread (+/-1 standard deviation) in RFs of +/-17%. Three different radiation schemes were used - we find differences in RFs between schemes (for the same ozone fields) of +/-10 percent. Applying two different tropopause definitions gives differences in RFs of +/-3 percent. Given additional (unquantified) uncertainties associated with emissions, climate-chemistry interactions and land-use change, we estimate an overall uncertainty of +/-30 percent for the tropospheric ozone RF. Experiments carried out by a subset of six models attribute tropospheric ozone RF to increased emissions of methane (44+/-12 percent), nitrogen oxides (31 +/- 9 percent), carbon monoxide (15 +/- 3 percent) and non-methane volatile organic compounds (9 +/- 2 percent); earlier studies attributed more of the tropospheric ozone RF to methane and less to nitrogen oxides. Normalising RFs to changes in tropospheric column ozone, we find a global mean normalised RF of 42 mW m(−2) DU(−1), a value similar to previous work. Using normalised RFs and future tropospheric column ozone projections we calculate future tropospheric ozone RFs (mW m(−2); relative to 1750) for the four future scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) of 350, 420, 370 and 460 (in 2030), and 200, 300, 280 and 600 (in 2100). Models show some coherent responses of ozone to climate change: decreases in the tropical lower troposphere, associated with increases in water vapour; and increases in the sub-tropical to mid-latitude upper troposphere, associated with increases in lightning and stratosphere-to-troposphere transport. Climate change has relatively small impacts on global mean tropospheric ozone RF.

climate change↗

Pre-industrial to End 21st Century Projections of Tropospheric Ozone from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP)

Present day tropospheric ozone and its changes between 1850 and 2100 are considered, analysing 15 global models that participated in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The ensemble mean compares well against present day observations. The seasonal cycle correlates well, except for some locations in the tropical upper troposphere. Most (75 %) of the models are encompassed with a range of global mean tropospheric ozone column estimates from satellite data, but there is a suggestion of a high bias in the Northern Hemisphere and a low bias in the Southern Hemisphere, which could indicate deficiencies with the ozone precursor emissions. Compared to the present day ensemble mean tropospheric ozone burden of 337+/-23 Tg, the ensemble mean burden for 1850 time slice is approx. 30% lower. Future changes were modelled using emissions and climate projections from four Representative Concentration Pathways (RCPs). Compared to 2000, the relative changes in the ensemble mean tropospheric ozone burden in 2030 (2100) for the different RCPs are: −4% (−16 %) for RCP2.6, 2% (−7%) for RCP4.5, 1% (−9%) for RCP6.0, and 7% (18 %) for RCP8.5. Model agreement on the magnitude of the change is greatest for larger changes. Reductions in most precursor emissions are common across the RCPs and drive ozone decreases in all but RCP8.5, where doubled methane and a 40-150% greater stratospheric influx (estimated from a subset of models) increase ozone. While models with a high ozone burden for the present day also have high ozone burdens for the other time slices, no model consistently predicts large or small ozone changes; i.e. the magnitudes of the burdens and burden changes do not appear to be related simply, and the models are sensitive to emissions and climate changes in different ways. Spatial patterns of ozone changes are well correlated across most models, but are notably different for models without time evolving stratospheric ozone concentrations. A unified approach to ozone budget specifications and a rigorous investigation of the factors that drive tropospheric ozone is recommended to help future studies attribute ozone changes and inter-model differences more clearly.

Troposphere↗

Global Multi-Year O3-CO Correlation Patterns from Models and TES Satellite Observations

The correlation between measured tropospheric ozone (O3) and carbon monoxide (CO) has been used extensively in tropospheric chemistry studies to explore the photochemical characteristics of different regions and to evaluate the ability of models to capture these characteristics. Here, we present the first study that uses multi-year, global, vertically resolved, simultaneous and collocated O3 and CO satellite (Tropospheric Emission Spectrometer) measurements, to determine this correlation in the middle/lower free troposphere for two different seasons, and to evaluate two chemistry-climate models. We find results that are fairly robust across different years, altitudes and timescales considered, which indicates that the correlation maps presented here could be used in future model evaluations. The highest positive correlations (around 0.8) are found in the northern Pacific during summer, which is a common feature in the observations and the G-PUCCINI model. We make quantitative comparisons between the models using a single-figure metric (C), which we define as the correlation coefficient between the modeled and the observed O3-CO correlations for different regions of the globe. On a global scale, the G-PUCCINI model shows a good performance in the summer (C =0.71) and a satisfactory performance in the winter (C = 0.52). It captures midlatitude features very well, especially in the summer, whereas the performance in regions like South America or Central Africa is weaker. The UKCA model (C = 0.46/0.15 for July-August/December-January on a global scale) performs better in certain regions, such as the tropics in winter, and it captures some of the broad characteristics of summer extratropical correlations, but it systematically underestimates the O3-CO correlations over much of the globe. It is noteworthy that the correlations look very different in the two models, even though the ozone distributions are similar. This demonstrates that this technique provides a powerful global constraint for understanding modeled tropospheric chemical processes. We investigated the sources of the correlations by performing a series of sensitivity experiments. In these, the sign of the correlation is, in most cases, insensitive to removing different individual emissions, but its magnitude changes downwind of emission regions when applying such perturbations. Interestingly, we find that the O3-CO correlation does not solely reflect the strength of O3 photochemical production, as often assumed by earlier studies, but is more complicated and may reflect a mixture of different processes such as transport.

Voulgarakis, A.↗

Impact of Surface Emissions to the Zonal Variability of Tropical Tropospheric Ozone and Carbon Monoxide for November 2004

The chemical and dynamical processes governing the zonal variability of tropical tropospheric ozone and carbon monoxide are investigated for November 2004 using satellite observations, in-situ measurements, and chemical transport models in conjunction with inverse-estimated surface emissions. Vertical ozone profile estimates from the Tropospheric Emission Spectrometer (TES) and ozone sonde measurements from the Southern Hemisphere Additional Ozonesondes (SHADOZ) network show the so called zonal 'wave-one' pattern, which is characterized by peak ozone concentrations (70-80 ppb) centered over the Atlantic, as well as elevated concentrations of ozone over Indonesia and Australia (60-70 ppb) in the lower troposphere. Observational evidence from TES CO vertical profiles and Ozone Monitoring Instrument (OMI) NO2 columns point to regional surface emissions as an important contributor to the elevated ozone over Indonesia. This contribution is investigated with the GEOS-Chem chemistry and transport model using surface emission estimates derived from an optimal inverse model, which was constrained by TES and Measurements Of Pollution In The Troposphere (MOPITT) CO profiles (Jones et al., 2007). These a posteriori estimates, which were over a factor of 2 greater than climatological emissions, reduced differences between GEOS-Chem and TES ozone observations by 30-40% and led to changes in GEOS-Chem upper tropospheric ozone of up to 40% over Indonesia. The remaining residual differences can be explained in part by upper tropospheric ozone produced from lightning NOx in the South Atlantic. Furthermore, model simulations from GEOS-Chem indicate that ozone over Indonesian/Australian is more sensitive to changes in surface emissions of NOx than ozone over the tropical Atlantic.

tropical tropospheric ozone↗