Seeing and turbulence profile simulations over complex terrain at the Thai National Observatory using a chemistry-coupled regional forecasting model

This study utilized advanced numerical simulations with the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to predict anticipated astronomical seeing conditions at the Thai National Observatory (TNO). The study evaluated the effects of both gas-phase and aerosol-phase chemical processes in the Earth’s atmosphere, along with the impact of spatial and temporal resolution on model performance. These simulations were validated against measurements from the Differential Image Motion Monitor (DIMM) and the Slope Detection and Ranging (SLODAR) technique. Due to the inherent temporal variability of the DIMM observations, a 24-h moving average window was applied to both DIMM data and WRF-Chem model outputs. This reduced the percentage root-mean-square error in the comparison between the two data sets from 23 per cent to 11 per cent and increased the correlation coefficient from 0.21 to 0.59. Chemistry played a minor role during the study period, contributing 3.49 per cent to astronomical seeing. However, it did affect the model’s accuracy. Additionally, the study revealed that higher spatial and temporal resolution simulations did not necessarily improve the model’s accuracy. When compared to SLODAR observations of the refractive index structure constant (Cn2dh), the simulations captured altitude variations within ±25 per cent above 5 km and 25–50 per cent below 5 km. Dome seeing also played a role, contributing to around 90 per cent or more in the lowest altitude layer. The results emphasized the significance of seeing predictions in providing valuable insights into complex atmospheric phenomena and how to mitigate the effects of atmospheric turbulence on telescopes

Simultaneous retrieval of atmospheric CO_2 and light path modification from space-based spectroscopic observations of greenhouse gases: methodology and application to GOSAT measurements over TCCON sites

This paper presents an improved photon path length probability density function method that permits simultaneous retrievals of column-average greenhouse gas mole fractions and light path modifications through the atmosphere when processing high-resolution radiance spectra acquired from space. We primarily describe the methodology and retrieval setup and then apply them to the processing of spectra measured by the Greenhouse gases Observing SATellite (GOSAT). We have demonstrated substantial improvements of the data processing with simultaneous carbon dioxide and light path retrievals and reasonable agreement of the satellite-based retrievals against ground-based Fourier transform spectrometer measurements provided by the Total Carbon Column Observing Network (TCCON)

Toward accurate CO2 and CH4 observations from GOSAT

The column-average dry air mole fractions of atmospheric carbon dioxide and methane (XCO2 and XCH4) are inferred from observations of backscattered sunlight conducted by the Greenhouse gases Observing SATellite (GOSAT). Comparing the first year of GOSAT retrievals over land with colocated ground-based observations of the Total Carbon Column Observing Network (TCCON), we find an average difference (bias) of-0.05% and-0.30% for XCO2 and XCH4 with a station-to-station variability (standard deviation of the bias) of 0.37% and 0.26% among the 6 considered TCCON sites. The root-mean square deviation of the bias-corrected satellite retrievals from colocated TCCON observations amounts to 2.8 ppm for XCO2 and 0.015 ppm for X CH4. Without any data averaging, the GOSAT records reproduce general source/sink patterns such as the seasonal cycle of XCO2 suggesting the use of the satellite retrievals for constraining surface fluxes. Copyright 2011 by the American Geophysical Union

Rifaximin has a Marginal Impact on Microbial Translocation, T-cell Activation and Inflammation in HIV-Positive Immune Non-responders to Antiretroviral Therapy – ACTG A5286

Background. Rifaximin, a nonabsorbable antibiotic that decreases lipopolysaccharide (LPS) in cirrhotics, may decrease the elevated levels of microbial translocation, T-cell activation and inflammation in human immunodeficiency virus (HIV)-positive immune nonresponders to antiretroviral therapy (ART)

Levels of HIV-1 persistence on antiretroviral therapy are not associated with markers of inflammation or activation

Antiretroviral therapy (ART) reduces levels of HIV-1 and immune activation but both can persist despite clinically effective ART. The relationships among pre-ART and on-ART levels of HIV-1 and activation are incompletely understood, in part because prior studies have been small or cross-sectional. To address these limitations, we evaluated measures of HIV-1 persistence, inflammation, T cell activation and T cell cycling in a longitudinal cohort of 101 participants who initiated ART and had well-documented sustained suppression of plasma viremia for a median of 7 years. During the first 4 years following ART initiation, HIV-1 DNA declined by 15-fold (93%) whereas cell-associated HIV-1 RNA (CA-RNA) fell 525-fold (>99%). Thereafter, HIV-1 DNA levels continued to decline slowly (5% per year) with a half-life of 13 years. Participants who had higher HIV-1 DNA and CA-RNA before starting treatment had higher levels while on ART, despite suppression of plasma viremia for many years. Markers of inflammation and T cell activation were associated with plasma HIV-1 RNA levels before ART was initiated but there were no consistent associations between these markers and HIV-1 DNA or CA-RNA during long-term ART, suggesting that HIV-1 persistence is not driving or driven by inflammation or activation. Higher levels of inflammation, T cell activation and cycling before ART were associated with higher levels during ART, indicating that immunologic events that occurred well before ART initiation had long-lasting effects despite sustained virologic suppression. These findings should stimulate studies of viral and host factors that affect virologic, inflammatory and immunologic set points prior to ART initiation and should inform the design of strategies to reduce HIV-1 reservoirs and dampen immune activation that persists despite ART

ATMOSPHERIC CARBON DIOXIDE: RETRIEVAL FROM GROUND-BASED FOURIER TRANSFORM INFRARED SOLAR ABSORPTION MEASUREMENTS AND MODELLING USING A COUPLED GLOBAL-REGIONAL SCALE APPROACH

Atmospheric carbon dioxide (CO2) was retrieved from ground-based solar absorption measurements using Fourier transform infrared (FTIR) spectrometry in three European stations (Biscarrosse, Bremen and Ny-Alesund). Functioning as an internal standard and a means to determine the dry air mixing ratio, molecular oxygen (O2) was likewise retrieved. The effects of instrumental parameters such as the resolution, the aperture size and high folding limits were assessed to identify correlated errors in both the CO2 and the O2. Changes in the field of view, the maximum optical path difference and the high folding limit seem to change the trace gas column concentrations of O2 and CO2 and just partially cancels out in the CO2/O2 ratio. Correction factors on the O2 column to minimize these instrumental effects were determined and applied to the FTS data. These correction factors seem to be more effective in Ny-Alesund than in Bremen as the degree of these instrumental changes appear to be more subtle in Ny-à �lesund. Additional correction strategies, particularly for the CO2, are still being examined and investigated. Comparisons of FTIR CO2 with integrated CO2 aircraft data were performed in the Biscarrosse station as a means of calibrating the FTIR data. Aside from this, the Stochastic Time Inverted Lagrangian Transport (STILT) model was also used as a 'transfer standard' between FTIR column concentrations and measurements made in situ by a co-located tower. STILT and tower data compared reasonably well. However, comparison of STILT with the FTIR showed a large bias. This bias is attributed to the scaling factor used in calibrating the FTIR data with the integrated CO2 aircraft data. The scaling factor was derived to a large extent from aircraft measurements that sampled within a 50 km distance from the FTS and this introduces spatial heterogeneity in the carbon dioxide volume mixing ratios around the FTIR station. Long-term time series of column averaged carbon dioxide volume mixing ratios for the Bremen and Ny-à �lesund stations were compared to STILT (only the Bremen station) and to CarbonTracker. A 'clear sky' bias was pin pointed as models see increased CO2 during frontal zone conditions - a meteorological condition when FTIRs often cannot measure. The spatial heterogeneity of carbon dioxide around the Bremen station was also assessed by comparing FTIR data with varying resolutions of STILT and it was found that column concentrations are not sensitive to small scale local carbon dioxide emission sources amidst Bremen being situated in an urban setting. The difference in variability between fine to coarse scales are approximately 0.2 ppm

Wavelet de-noising of images using an empirically-derived adaptive shrinkage function

A technique to de-noise images, based from the research of Piz urica, Philips, Lemahieu and Acheroy, was developed and tested on a synthetic test image and a medical phantom image with added Gaussian, Salt and Pepper and Speckle noise. It was also applied to a synthetic aperture radar image, to a flourescence image, to a metaphase spread image and to a Landsat7 image. The standard deviation instead of the median absolute deviation was utilized and the adaptive shrinkage function was empirically derived instead of estimating it. A two-dimensional discrete stationary wavelet transform was performed on the input images using the Haar wavelet. Image quality measures, namely the mean squared error (MSE), the root mean squared error (RMSE), the peak signal to noise ratio (PSNR), Linfoot\u27s criteria of fidelity (F), structural content (S), and correlation quality (Q) and the equivalent number of looks (ENL) were calculated before and after image de-noising. The noise structures in the images were estimated and the effect of varying the local spatial neighborhood importance parameter (y) of the shrinkage function was investigated. For the synthetic test image, the medical phantom image and the synthetic aperture radar image optimum results were obtained when y is equal to 0.2. However, a trend outside of the norms was obtained for the fluorescence image, for the Landsat7 image and especially for the metaphase spread image. The local spatial neighborhood importance parameter for the metaphase spread image was further varied to 0.025, 0.05, and 0.075 and 0.1 and optimum results occurred when y is equal to 0.05. The study showed that the effectiveness of the emperically-derived shrinkage function depended on the signal and noise distribution in the image

Side by side measurements of CO2 by ground-based Fourier transform spectrometry (FTS)

High resolution solar absorption Fourier transform spectrometry (FTS) is the most precise ground-based remote sensing technique to measure the total column of atmospheric carbon dioxide. For carbon cycle studies as well as for the calibration and validation of spaceborne sensors the instrumental comparability of FTS systems is of critical importance. Retrievals from colocated measurements by two identically constructed FTS systems have been compared for the first time. Under clear sky conditions a precision for the retrieved xCO2 better than ∼0.1% is demonstrated and the instruments agree within ∼0.07%. An important factor in achieving such good comparability of the xCO2 is an accurate sampling of the internal reference laser. A periodic laser mis-sampling leads to ghosts (artificial spectral lines), which are mirrored images from original spectral lines. These ghosts can interfere with the spectral range of interest. The influence of the laser mis-sampling on the retrieved xCO2 and xO2 in the near-IR has been quantified. For a typical misalignment, the ratio of the ghost intensity compared to the intensity of the original spectral line is about 0.18% and in this case the retrieved xCO2 is wrong by 0.26% (1 ppm) and the retrieved xO2 is wrong by 0.2%