Qiang Ji

Sensitivity of off-nadir zenith angles to correlation between visible and near-infrared reflectance for use in remote sensing of aerosol over land

Cloud absorption radiometer (CAR) multispectral and multiangular data, collected during the Smoke, Clouds, and Radiation-Brazil (SCAR-B) Experiment, was used to examine the ratio technique, the official method for remote sensing of aerosols over land from the moderate resolution imaging spectroradiometer (MODIS) data, for view angles from nadir to 650 off-nadir. The strategy used is to first select a pristine, low aerosol optical thickness flight, and then to compute ratios of reflectance at 0.47 and 0.68 /spl mu/m to corresponding values at 2.20 /spl mu/m, separately for backward and forward scattering directions. Similarly, the authors analyzed data from high turbidity flights for comparison purposes. For both flights, they removed the effects of atmospheric absorption and scattering using 6S, a radiative transfer code, and then recomputed the ratios again for different values of aerosol optical thickness. Finally, they analyzed bidirectional reflection function (BRF) data to examine the dependence of the ratio technique on the relative azimuth angle. Results of this analysis show that a relationship between visible reflectance and near infrared (IR) reflectance exists for view angles from nadir to 400 off-nadir, and that simple parametric relationships can be derived.

Anthropogenic air pollution observed near dust source regions in northwestern China during springtime 2008

anthropogenic emissions. Sizable aerosol mass concentration (153 mg/m 3 ) and light scattering (159 Mm −1 at 500 nm) were largely attributable to dust emissions, and aerosol light absorption (10.3 Mm −1 at 500 nm) was dominated by anthropogenic pollution. Distinct diurnal variations in meteorology and pollution were induced by the local valley terrain. Strong daytime northwest valley wind cleaned out pollution and was replaced by southeast mountain wind that allowed pollutants to build up overnight. In the afternoon, aerosols had single scattering albedo (SSA, 500 nm) of 0.95 and were mainly of supermicron particles, presumably dust, while at night smaller particles and SSA of 0.89–0.91 were related to pollution. The diverse local emission sources were characterized: the CO/SO2, CO/NOy, NOy/SO2 (by moles), and BC/CO (by mass) ratios for small point sources such as factories were 24.6–54.2, 25.8–35.9, 0.79–1.31, and 4.1– 6.1 ×1 0 −3 , respectively, compared to the corresponding inventory ratios of 43.7–71.9, 23.7–25.7, 1.84–2.79, and 3.4– 4.0 ×1 0 −3 for the industrial sector in the area. The mixing between dust and pollution can be ubiquitous in this region. During a dust storm shown as an example, pollutants were observed to mix with dust, causing discernible changes in both SSA and aerosol size distribution. Further interaction between dust and pollutants during transport may modify the properties of dust particles that are critical for their large‐scale impact on radiation, clouds, and global biogeochemical cycles.

On the dome effect of Eppley pyrgeometers and pyranometers

Pyrgeometers and Pyranometers are fundamental instruments widely used for quantifying atmosphere-surface energetics in climate studies. The dome effect of these instruments can cause a measurement uncertainty larger than 10 W m−2. Based on careful analysis, the dome factors of our two new pyrgeometers are found to lie in the range between 1.1 and 2.0. These values are far smaller than the value of 4.0 suggested by the World Meteorological Organization. The laboratory-determined dome factors fall within this range, if pyrgeometers approach equilibrium with the blackbody target during calibration cycles. From recent field campaigns, consistent results for the dome factors are also obtained by analyzing nighttime pyrgeometer measurements, which were regarded as approaching equilibrium state. Furthermore, we utilized an energy balance equation to describe the thermal dome effect of pyranometers that is commonly referred to as the nighttime negative outputs or the dark-offset. Lacking direct measurements of the dome and case temperatures of pyranometer, we used measurements from a pyrgeometer to derive and to account for the thermal dome effect of collocated pyranometers. This approximation revealed a reasonable agreement between calculations and measurements.

Spectral derivative analysis of solar spectroradiometric measurements: Theoretical basis

Spectral derivative analysis, a commonly used tool in analytical spectroscopy, is described for studying cirrus clouds and aerosols using hyperspectral, remote sensing data. The methodology employs spectral measurements from the 2006 Biomass-burning Aerosols in Southeast Asia field study to demonstrate the approach. Spectral peaks associated with the first two derivatives of measured/modeled transmitted spectral fluxes are examined in terms of their shapes, magnitudes, and positions from 350 to 750 nm, where variability is largest. Differences in spectral features between media are mainly associated with particle size and imaginary term of the complex refractive index. Differences in derivative spectra permit cirrus to be conservatively detected at optical depths near the optical thin limit of ~0.03 and yield valuable insight into the composition and hygroscopic nature of aerosols. Biomass-burning smoke aerosols/cirrus generally exhibit positive/negative slopes, respectively, across the 500–700 nm spectral band. The effect of cirrus in combined media is to increase/decrease the slope as cloud optical thickness decreases/increases. For thick cirrus, the slope tends to 0. An algorithm is also presented which employs a two model fit of derivative spectra for determining relative contributions of aerosols/clouds to measured data, thus enabling the optical thickness of the media to be partitioned. For the cases examined, aerosols/clouds explain ~83%/17% of the spectral signatures, respectively, yielding a mean cirrus cloud optical thickness of 0.08 ± 0.03, which compared reasonably well with those retrieved from a collocated Micropulse Lidar Network Instrument (0.09 ± 0.04). This method permits extracting the maximum informational content from hyperspectral data for atmospheric remote sensing applications.

Correction to “Simultaneous detection/separation of mineral dust and cirrus clouds using MODIS thermal infrared window data”

[1] In the paper ‘‘Simultaneous detection/separation of mineral dust and cirrus clouds using MODIS thermal infrared window data’’ by R. A. Hansell et al. (Geophysical Research Letters, 34, L11808, doi:10.1029/2007GL029388, 2007), the authors inadvertently omitted the following acknowledgment. [2] This research was also supported in part by NGST contract 97904DDM3S managed by A. Dybdahl and M. Mussetto. GEOPHYSICAL RESEARCH LETTERS, VOL. 34, L13802, doi:10.1029/2007GL031035, 2007

Longwave Radiative Energetics of Mineral Dust Aerosol

Longwave direct radiative effects of mineral dust are investigated during previous field campaigns. Surface measurements and radiative transfer modeling are employed for probing dust radiative impacts for regions frequented by dust aerosol.

Analytically derived thermal correction to reduce overlap bias errors in micro-pulse lidar data

Micro-Pulse Lidar (MPL) systems have been utilized in a wide variety of field campaigns and are currently deployed at multiple sites around the globe to monitor atmospheric aerosols and clouds on a continuous, multi-year basis. These systems contain a commercial-grade telescope that changes focal-length as a function of instrument temperature resulting in a bias error for retrieved lidar profiles. An analytical model is described that predicts the expected thermal-induced signal response, and is used to correct MPL atmospheric data. Results demonstrate a significant reduction in data bias error.