Columnar water vapor retrievals from multifilter rotating shadowband radiometer data

Abstract

[1] The multifilter rotating shadowband radiometer (MFRSR) measures direct and diffuse irradiances in the visible and near-infrared spectral range. In addition to characteristics of atmospheric aerosols, MFRSR data also allow retrieval of precipitable water vapor (PWV) column amounts, which are determined from the direct normal irradiances in the 940-nm spectral channel. The HITRAN 2004 spectral database was used in our retrievals to model the water vapor absorption. We present a detailed error analysis describing the influence of uncertainties in instrument calibration and spectral response, as well as those in available spectral databases, on the retrieval results. The results of our PWV retrievals from the Southern Great Plains (SGP) site operated by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program were compared with correlative standard measurements by microwave radiometers (MWRs) and a global positioning system (GPS) water vapor sensor, as well as with retrievals from other solar radiometers (AERONET's CIMEL, AATS-6). Some of these data are routinely available at the SGP's Central Facility; however, we also used measurements from a wider array of instrumentations deployed at this site during the water vapor intensive observation period (WVIOP2000) in September-October 2000. The WVIOP data show better agreement between different solar radiometers or between different microwave radiometers (both groups showing relative biases within 4%) than between these two groups of instruments, with MWR values being consistently higher (up to 14%) than those from solar instruments (especially in the large PWV column amount range). We also demonstrate the feasibility of using MFRSR network data for creation of 2D data sets comparable with that of the MODIS satellite water vapor product.

A multi-site intercomparison of integrated water vapour observations for climate change analysis

“…Uncertainties in this parameterisation and the Langley plot regression (due to variable atmospheric water vapour amounts) as well as deficits in the filter characterisation are the leading error sources. Alexandrov et al (2009) estimate an IWV precision of about 10 % for this technique.…”

“…b Miloshevich et al (2009);Smit et al (2013); Wang et al (2013). c Alexandrov et al (2009). d EUMETSAT (2010).…”

Continuous quality assessment of atmospheric water vapour measurement techniques: FTIR, Cimel, MFRSR, GPS, and Vaisala RS92

“…Uncertainties in this parameterisation and the Langley regression (due to variable atmospheric water vapour amounts) as well as deficits in the filter characterisation are the leading error sources. Alexandrov et al (2009) estimate a PWV precision of about 10%.…”

“…For operational and, in particular, for research applications, it is essential to know the long-term quality of these measurements, since the expected trends in the PWV values due to global warming are on the order of a few tenths of mm per decade (Trenberth et al, 2005). Great effort has been put into theoretically and empirically estimating the quality of these automated techniques (e.g., Revercomb et al, 2003;Van Baelen et al, 2005;Sapucci et al, 2007;Bokoye et al, 2007;Wang et al, 2007;Alexandrov et al, 2009). However, most of the empirical intercomparison studies are limited to intensive campaign periods.…”

A long-term study of aerosol modulation of atmospheric and surface solar heating over Pune, India

“…Aerosol optical depth (AOD) at 440, 675, 870 and 1020 nm, with an uncertainty of Â0.01Á0.02, can be derived from direct radiance measurements (Eck et al, 1999). The measurements at 940 nm are used for the derivation of the water vapour column amount (Alexandrov et al, 2009). The aerosol size distribution, refractive index, and single scattering albedo are retrieved from the sky radiance measurements and AODs at 440, 675, 870, and 1020 nm (Dubovik and King, 2000;Dubovik et al, 2006).…”