Validation of northern latitude Tropospheric Emission Spectrometer stare ozone profiles with ARC-IONS sondes during ARCTAS: sensitivity, bias and error analysis

We compare Tropospheric Emission Spectrometer (TES) versions 3 and 4, V003 and V004, respectively, nadir-stare ozone profiles with ozonesonde profiles from the Arctic Intensive Ozonesonde Network Study (ARCIONS, http://croc.gsfc.nasa.gov/arcions/ during the Arctic Research on the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field mission. The ozonesonde data are from launches timed to match Aura's overpass, where 11 coincidences spanned 44° N to 71° N from April to July 2008. Using the TES "stare" observation mode, 32 observations are taken over each coincidental ozonesonde launch. By effectively sampling the same air mass 32 times, comparisons are made between the empirically-calculated random errors to the expected random errors from measurement noise, temperature and interfering species, such as water. This study represents the first validation of high latitude (>70°) TES ozone. We find that the calculated errors are consistent with the actual errors with a similar vertical distribution that varies between 5% and 20% for V003 and V004 TES data. In general, TES ozone profiles are positively biased (by less than 15%) from the surface to the upper-troposphere (~1000 to 100 hPa) and negatively biased (by less than 20%) from the upper-troposphere to the lower-stratosphere (100 to 30 hPa) when compared to the ozonesonde data. Lastly, for V003 and V004 TES data between 44° N and 71° N there is variability in the mean biases (from −14 to +15%), mean theoretical errors (from 6 to 13%), and mean random errors (from 9 to 19%)

Using airborne HIAPER Pole-to-Pole Observations (HIPPO) to evaluate model and remote sensing estimates of atmospheric carbon dioxide

In recent years, space-borne observations of atmospheric carbon dioxide (CO_2) have been increasingly used in global carbon-cycle studies. In order to obtain added value from space-borne measurements, they have to suffice stringent accuracy and precision requirements, with the latter being less crucial as it can be reduced by just enhanced sample size. Validation of CO_2 column-averaged dry air mole fractions (XCO_2) heavily relies on measurements of the Total Carbon Column Observing Network (TCCON). Owing to the sparseness of the network and the requirements imposed on space-based measurements, independent additional validation is highly valuable. Here, we use observations from the High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole-to-Pole Observations (HIPPO) flights from 01/2009 through 09/2011 to validate CO_2 measurements from satellites (Greenhouse Gases Observing Satellite – GOSAT, Thermal Emission Sounder – TES, Atmospheric Infrared Sounder – AIRS) and atmospheric inversion models (CarbonTracker CT2013B, Monitoring Atmospheric Composition and Climate (MACC) v13r1). We find that the atmospheric models capture the XCO_2 variability observed in HIPPO flights very well, with correlation coefficients (r^2) of 0.93 and 0.95 for CT2013B and MACC, respectively. Some larger discrepancies can be observed in profile comparisons at higher latitudes, in particular at 300 hPa during the peaks of either carbon uptake or release. These deviations can be up to 4 ppm and hint at misrepresentation of vertical transport. Comparisons with the GOSAT satellite are of comparable quality, with an r^2 of 0.85, a mean bias μ of −0.06 ppm, and a standard deviation σ of 0.45 ppm. TES exhibits an r^2 of 0.75, μ of 0.34 ppm, and σ of 1.13 ppm. For AIRS, we find an r^2 of 0.37, μ of 1.11 ppm, and σ of 1.46 ppm, with latitude-dependent biases. For these comparisons at least 6, 20, and 50 atmospheric soundings have been averaged for GOSAT, TES, and AIRS, respectively. Overall, we find that GOSAT soundings over the remote Pacific Ocean mostly meet the stringent accuracy requirements of about 0.5 ppm for space-based CO_2 observations

Profiling tropospheric CO_2 using Aura TES and TCCON instruments

Monitoring the global distribution and long-term variations of CO_2 sources and sinks is required for characterizing the global carbon budget. Total column measurements are useful for estimating regional-scale fluxes; however, model transport remains a significant error source, particularly for quantifying local sources and sinks. To improve the capability of estimating regional fluxes, we estimate lower tropospheric CO_2 concentrations from ground-based near-infrared (NIR) measurements with space-based thermal infrared (TIR) measurements. The NIR measurements are obtained from the Total Carbon Column Observing Network (TCCON) of solar measurements, which provide an estimate of the total CO_2 column amount. Estimates of tropospheric CO_2 that are co-located with TCCON are obtained by assimilating Tropospheric Emission Spectrometer (TES) free tropospheric CO_2 estimates into the GEOS-Chem model. We find that quantifying lower tropospheric CO_2 by subtracting free tropospheric CO_2 estimates from total column estimates is a linear problem, because the calculated random uncertainties in total column and lower tropospheric estimates are consistent with actual uncertainties as compared to aircraft data. For the total column estimates, the random uncertainty is about 0.55 ppm with a bias of −5.66 ppm, consistent with previously published results. After accounting for the total column bias, the bias in the lower tropospheric CO_2 estimates is 0.26 ppm with a precision (one standard deviation) of 1.02 ppm. This precision is sufficient for capturing the winter to summer variability of approximately 12 ppm in the lower troposphere; double the variability of the total column. This work shows that a combination of NIR and TIR measurements can profile CO_2 with the precision and accuracy needed to quantify lower tropospheric CO_2 variability

El Niño, the 2006 Indonesian peat fires, and the distribution of atmospheric methane

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110818/1/grl50937.pd

The vertical distribution of ozone instantaneous radiative forcing from satellite and chemistry climate models

We evaluate the instantaneous radiative forcing (IRF) of tropospheric ozone predicted by four state-of-the-art global chemistry climate models (AM2-Chem, CAM-Chem, ECHAM5-MOZ, and GISS-PUCCINI) against ozone distribution observed from the NASA Tropospheric Emission Spectrometer (TES) during August 2006. The IRF is computed through the application of an observationally constrained instantaneous radiative forcing kernels (IRFK) to the difference between TES and model-predicted ozone. The IRFK represent the sensitivity of outgoing longwave radiation to the vertical and spatial distribution of ozone under all-sky condition. Through this technique, we find total tropospheric IRF biases from -0.4 to + 0.7 W/m(2) over large regions within the tropics and midlatitudes, due to ozone differences over the region in the lower and middle troposphere, enhanced by persistent bias in the upper troposphere-lower stratospheric region. The zonal mean biases also range from -30 to + 50 mW/m(2) for the models. However, the ensemble mean total tropospheric IRF bias is less than 0.2 W/m(2) within the entire troposphere

Increased levels of (class switched) memory B cells in peripheral blood of current smokers

There is increasing evidence that a specific immune response contributes to the pathogenesis of COPD. B-cell follicles are present in lung tissue and increased anti-elastin titers have been found in plasma of COPD patients. Additionally, regulatory T cells (Tregs) have been implicated in its pathogenesis as they control immunological reactions. We hypothesize that the specific immune response in COPD is smoke induced, either by a direct effect of smoking or as a result of smoke-induced lung tissue destruction (i.e. formation of neo-epitopes or auto antigens). Furthermore, we propose that Tregs are involved in the suppression of this smoke-induced specific immune response

Evaluation of ACCMIP Outgoing Longwave Radiation from Tropospheric Ozone Using TES Satellite Observations.

We use simultaneous observations of tropospheric ozone and outgoing longwave radiation (OLR) sensitivity to tropospheric ozone from the Tropospheric Emission Spectrometer (TES) to evaluate model tropospheric ozone and its effect on OLR simulated by a suite of chemistry-climate models that participated in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The ensemble mean of ACCMIP models show a persistent but modest tropospheric ozone low bias (5-20 ppb) in the Southern Hemisphere (SH) and modest high bias (5-10 ppb) in the Northern Hemisphere (NH) relative to TES ozone for 2005-2010. These ozone biases have a significant impact on the OLR. Using TES instantaneous radiative kernels (IRK), we show that the ACCMIP ensemble mean tropospheric ozone low bias leads up to 120mW/ sq. m OLR high bias locally but zonally compensating errors reduce the global OLR high bias to 39+/- 41mW/ sq. m relative to TES data. We show that there is a correlation (Sq. R = 0.59) between the magnitude of the ACCMIP OLR bias and the deviation of the ACCMIP preindustrial to present day (1750-2010) ozone radiative forcing (RF) from the ensemble ozone RF mean. However, this correlation is driven primarily by models whose absolute OLR bias from tropospheric ozone exceeds 100mW/ sq. m. Removing these models leads to a mean ozone radiative forcing of 394+/- 42mW/ sq. m. The mean is about the same and the standard deviation is about 30% lower than an ensemble ozone RF of 384 +/- 60mW/ sq. m derived from 14 of the 16 ACCMIP models reported in a companion ACCMIP study. These results point towards a profitable direction of combining satellite observations and chemistry-climate model simulations to reduce uncertainty in ozone radiative forcing