Spectrally Dependent CLARREO Infrared Spectrometer Calibration Requirement for Climate Change Detection.

Detecting climate trends of atmospheric temperature, moisture, cloud, and surface temperature requires accurately calibrated satellite instruments such as the Climate Absolute Radiance and Reflectivity Observatory (CLARREO). Wielicki et al. have studied the CLARREO measurement requirements for achieving climate change accuracy goals in orbit. Our study further quantifies the spectrally dependent IR instrument calibration requirement for detecting trends of atmospheric temperature and moisture profiles. The temperature, water vapor, and surface skin temperature variability and the associated correlation time are derived using Modern Era Retrospective-Analysis for Research and Applications (MERRA) and European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data. The results are further validated using climate model simulation results. With the derived natural variability as the reference, the calibration requirement is established by carrying out a simulation study for CLARREO observations of various atmospheric states under all-sky. We derive a 0.04 K (k=2, or 95% confidence) radiometric calibration requirement baseline using a spectral fingerprinting method. We also demonstrate that the requirement is spectrally dependent and some spectral regions can be relaxed due to the hyperspectral nature of the CLARREO instrument. We further discuss relaxing the requirement to 0.06 K (k=2) based on the uncertainties associated with the temperature and water vapor natural variability and relatively small delay in time-to-detect for trends relative to the baseline case. The methodology used in this study can be extended to other parameters (such as clouds and CO2) and other instrument configurations.

Association of Serum Levels of Adipocyte Fatty Acid-Binding Protein and High-Sensitivity C Reactive Protein with Severity of Acute Ischemic Stroke.

To evaluate the serum levels of adipocyte fatty acid-binding protein (A-FABP) and high-sensitivity C reactive protein (hs-CRP) in patients with acute ischemic stroke (AIS), and correlations among A-FABP, hs-CRP, and AIS, 108 patients with AIS and 86 healthy controls were examined. The levels of hs-CRP and A-FABP were detected by ELISAs. The stroke severity was determined using the modified Rankin scale (mRS). Patients with AIS were divided into those with mild (mRS ≤ 3) and severe disease (mRS > 3). Regression analysis was performed to test association between hs-CRP and A-FABP. Serum levels of hs-CRP and A-FABP were significantly higher in patients with AIS compared with healthy controls. Furthermore, more severe AIS was associated with higher levels of these markers. Regression analysis demonstrated a weak but significant association between A-FABP and hs-CRP. A-FABP and hs-CRP are associated with AIS, and may be involved in the pathogenesis of AIS.

Far-infrared surface emissivity and climate.

Presently, there are no global measurement constraints on the surface emissivity at wavelengths longer than 15 µm, even though this surface property in this far-IR region has a direct impact on the outgoing longwave radiation (OLR) and infrared cooling rates where the column precipitable water vapor (PWV) is less than 1 mm. Such dry conditions are common for high-altitude and high-latitude locations, with the potential for modeled climate to be impacted by uncertain surface characteristics. This paper explores the sensitivity of instantaneous OLR and cooling rates to changes in far-IR surface emissivity and how this unconstrained property impacts climate model projections. At high latitudes and altitudes, a 0.05 change in emissivity due to mineralogy and snow grain size can cause a 1.8-2.0 W m(-2) difference in the instantaneous clear-sky OLR. A variety of radiative transfer techniques have been used to model the far-IR spectral emissivities of surface types defined by the International Geosphere-Biosphere Program. Incorporating these far-IR surface emissivities into the Representative Concentration Pathway (RCP) 8.5 scenario of the Community Earth System Model leads to discernible changes in the spatial patterns of surface temperature, OLR, and frozen surface extent. The model results differ at high latitudes by as much as 2°K, 10 W m(-2), and 15%, respectively, after only 25 y of integration. Additionally, the calculated difference in far-IR emissivity between ocean and sea ice of between 0.1 and 0.2, suggests the potential for a far-IR positive feedback for polar climate change.

The radiative signature of upper tropospheric moistening.

Climate models predict that the concentration of water vapor in the upper troposphere could double by the end of the century as a result of increases in greenhouse gases. Such moistening plays a key role in amplifying the rate at which the climate warms in response to anthropogenic activities, but has been difficult to detect because of deficiencies in conventional observing systems. We use satellite measurements to highlight a distinct radiative signature of upper tropospheric moistening over the period 1982 to 2004. The observed moistening is accurately captured by climate model simulations and lends further credence to model projections of future global warming.

Use of high-resolution measurements for the retrieval of temperature and gas-concentration profiles from outgoing infrared spectra in the presence of cirrus clouds.

We explore ways in which high-spectral-resolution measurements can aid in the retrieval of atmospheric temperature and gas-concentration profiles from outgoing infrared spectra when optically thin cirrus clouds are present. Simulated outgoing spectra that contain cirrus are fitted with spectra that do not contain cirrus, and the residuals are examined. For those lines with weighting functions that peak near the same altitude as the thin cirrus, unique features are observed in the residuals. These unique features are highly sensitive to the resolution of the instrumental line shape. For thin cirrus these residual features are narrow (< or = 0.1 cm(-1)), so high spectral resolution is required for unambiguous observation. The magnitudes of these unique features are larger than the noise of modern instruments. The sensitivities of these features to cloud height and cloud optical depth are also discussed. Our sensitivity studies show that, when the errors in the estimation of temperature profiles are not large, the dominant contribution to the residuals is the misinterpretation of cirrus. An analysis that focuses on information content is also presented. An understanding of the magnitude of the effect and of its dependence on spectral resolution as well as on spectral region is important for retrieving spacecraft data and for the design of future infrared instruments for forecasting weather and monitoring greenhouse gases.