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EOS MLS Cloud Ice Measurements and Cloudy- Sky Radiative Transfer Model

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EOS MLS Cloud Ice Measurements and Cloudy- Sky Radiative Transfer Model TRANSACTIONS ON GEOPHYSICS AND REMOTE SENSING 1 EOS MLS Cloud Ice Measurements and Cloudy- Sky Radiative Transfer Model Dong L. Wu, Jonathan H. Jiang, and Cory P. Davis Remote sensing of ice clouds with passive microwave Abstract— EOS MLS (Earth Observing System Microwave radiometers is a relatively new research area. A number of Limb Sounder) on the NASA Aura satellite observes upper researchers have attempted to retrieve cloud ice water path tropospheric clouds at frequencies near 118, 190, 240, 640 GHz, (IWP) from nadir-viewing radiances using cloud scattering and 2.5 THz. This paper describes MLS cloud measurement signatures [5,6,7,8,9]. Combined radar-radiometer approaches principles, the methods for cloud detection, and radiative can be used to improve cloud ice measurements with better transfer models used for interpreting and retrieving cloud vertical resolution but the retrieved IWC profiles are limited to properties. MLS 240 GHz data have been used to retrieve ice water content at pressures < 215 hPa. Some early results are airborne radar sampling [10]. shown here and the observed cloud effects are consistent with the This paper describes a cloud ice observing technique with expectation from model simulations in general. Significant cloud- EOS MLS (Earth Observing System Microwave Limb induced radiances are observed at 2.5 THz. The cloud scattering Sounder) on Aura. Cloud radiance characteristics as well as signatures at 122 GHz are polarized but the polarization measurement principles used for cloud ice retrievals are differences are typically less than 10% of the total cloud-induced discussed. EOS MLS employs the limb-viewing technique radiance. with high-frequency narrow beamwidth receivers to achieve better vertical resolution and sensitivity than nadir sounding Index Terms—satellite, microwave, cloud, limb sounding, ice [11][12]. Under limb-viewing geometry the radiative transfer water content, polarization (RT) is greatly simplified, involving only the atmosphere and clouds. These advantages yield better accuracy for cloud detection at high altitudes. I. INTRODUCTION Launched on 15 July 2004, EOS MLS has observed clouds louds play important roles in modulating the Earth’s in all the radiometers and is producing cloud IWC C dynamical, hydrological, radiative, and chemical measurements at pressures < 215 hPa. Cloud IWC and processes [1,2,3,4]. Despite terabytes of satellite cloud horizontal ice water path (hIWP) along the instrument line-of- imagery, our understanding of cloud properties and vertical light (LOS) are two primary cloud products from EOS MLS distributions remain limited, especially on ice clouds in the [Figure 1]. The IWC in the upper troposphere (UT) is upper troposphere. One of the poorly known cloud variables is retrieved from high tangent height (ht) single-frequency ice water content (IWC), which is difficult to measure from measurements assuming spherical homogeneity. This space. Visible/IR techniques are sensitive only to the assumption implies that the MLS IWC represent a volume uppermost cloud layer and often saturated by dense clouds; whereas low-frequency microwave sensors are insensitive to most of ice clouds. To overcome both penetration and sensitivity shortcomings, high-frequency microwave radiometry emerges as a promising technique for observing ice clouds in the upper troposphere. Manuscript received October 9, 2005. This work was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration (NASA). Dong L. Wu is with the Jet Propulsion Laboratory, California Institute of Figure 1. Cloud ice observations in limb viewing geometry. At Technology, Pasadena, California, USA (phone: 818-393-1954; fax: 818-393- high tangent heights, where limb radiation is optically thin for 5065; e-mail: [email protected]). window channels, single-frequency radiances are used to retrieve Jonathan H. Jiang is with the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA (e-mail: IWC at pressures < 215 hPa. At low tangent heights, where limb [email protected]). radiation is optically thick, multiple frequency radiances with Cory P. Davis is with the Institute of Atmospheric and Environmental different penetration depths are used to infer hIWP along the Science, School of GeoSciences, University of Edinburgh, Edinburgh EH9 LOS. 3JZ, Scotland, UK. (e-mail: [email protected]). TRANSACTIONS ON GEOPHYSICS AND REMOTE SENSING 2 average over the instrument’s field-of-view (FOV). The hIWP crossing time of ~1:40 p.m. Excluding instrument calibration, is retrieved from low-ht measurements using multiple each MAF devotes ~120 MIFs for atmospheric measurements frequencies with different penetration depths. Each hIWP with a integration time of 1/6 second for a MIF. In the represents a column in the LOS direction that is nearly nominal operation [14], the GHz radiometers have ~42 MIFs horizontally with an elevation angle of ~3º. In most cases the dedicated to tropospheric measurements (separated by ~300 m MLS hIWP column does not reach the surface due to strong in ht), whereas the THz scan has only ~7 MIFs at ht < 18 km atmospheric absorption along the limb path, but in the polar [15]. regions where air is often dry, the low-ht radiances can reach Clouds reside mostly in the troposphere and occasionally the surface. shoot up to ~18 km. As a result, MLS radiances can be The retrieval technique using high-h radiances has t affected by clouds when viewing at h < ~19 km for the previously applied to UARS (Upper Atmosphere Research t instrument FOV is not infinitesimal. The measured cloud Satellite) MLS 203 GHz data, from which the 100 hPa cloud fields are subject to substantial horizontal smearing due to a ice was derived and studied for the period of 1991-1997 [13]. This work extends the cloud observing technique to EOS long (~200 km) limb path along the LOS. MLS frequencies, and the paper is organized to discuss cloud B. Radiance Uncertainties characteristics in EOS MLS radiances in section II, followed MLS clear-sky algorithms use radiance spectral variations by a description of the cloudy-sky RT model in section III. to measure gas abundances, and therefore spectrally-flat Preliminary MLS cloud observations are highlighted in radiance error has little impact on the quality of the gas section IV. measurements. The cloud measurements, however, depend critically on the absolute radiance value or accuracy of II. EOS MLS CLOUD MEASUREMENTS radiometric calibration. Thus, understanding noise accuracy is A. The EOS MLS Experiment very important for reliable cloud retrieval. Noise EOS MLS is a passive instrument that consists of seven characteristics and calibration issues are detailed in [14][15]. radiometers at frequencies near 118, 190, 240, 640 GHz, and The radiance accuracy can be affected by several factors, 2.5 THz [12][14]. There are dual polarizations for the 118 including errors in baseline, gain, and sideband ratio. The GHz and 2.5 THz receivers. Except for the 118 GHz baseline radiance may come from antenna’s ohmic emissions radiometer, all are double-sideband receivers with key and spillovers that can be removed effectively on a MAF-by- parameters specified in Table I. The GHz and THz systems MAF basis, using the measurements at ht > 85 km [14]. have separate antennas but are synchronized in sampling such Although the gain is calibrated every MAF, it can be noisy that they both produce 240 scans, or major frames (MAFs), in and affected by the sidelope/spillover radiation not accounted each orbit. Each MAF is further divided to 148 minor frames for. The radiometer sideband ratios were measured during pre- (MIFs). Unlike step-scanning with UARS MLS, EOS MLS launch testing but to the accuracy of 0.5-2%. The precision of scans are continuous in tangent height from the surface to the MLS radiances consists of two components, frequency- mesopause (~92 km) in 24.7s. Two adjacent scans are correlated and random, which can be expressed in terms of separated by ~165 km in distance. The latitude coverage variance as follows ranges from 82ºS to 82ºN with a sun-synchronous ascending Table I. Characteristics of the EOS MLS radiometers. Both vertical and horizontal FOVs are estimated at ht = 1 km. MLS Radiometera Polarization Estimated Vertical Cross-Track (frequency range in GHz) 0º = V pol Min. Errb FOV FOV 90º = H pol (K) (km) (km) R1A (115-122) 0º ± 0.5º 0.3 6.5 13 R1B (115-122) 90º ± 0.5º 0.5 6.5 13 R2 (178-184, 200-207) 0º ± 0.5º 0.3 4.5 9 R3 (230-237, 243-250) 90º ± 0.5º 0.2 3.5 7 R4 (625-637, 649-661) 90º ± 0.5º ~2 1.5 3 R5H (2501-2515, 2531-2544) ~113º ~4 2.5 2.5 R5V (2501-2515, 2531-2544) ~23º ~3 2.5 2.5 a) The two frequency ranges in R2, R3, R4, R5H and R5V reflect the receiver’s double-sideband coverage although radiances from two sidebands are inseparable in the radiometric measurements. R1A and R1B are single sideband radiometers with orthogonal polarizations. b) MLS radiance error contains frequency-correlated and random components. The latter can be reduced by averaging radiances from different frequency channels with the radiometer but the correlated component cannot by reduced by averaging, eventually becoming the dominant radiance uncertainty. Values in this column, the minimum radiance error per MIF, reflect such limit after the frequency averaging is applied. TRANSACTIONS ON GEOPHYSICS AND REMOTE SENSING 3 σ 2 = σ 2 + σ 2 (1) important for reliable cloud detection. fc r The basic cloud measurement is called cloud-induced 2 where the random componentσ r is proportional to the radiance (Tcir), defined as the difference between the inverse of the bandwidth and integration time product. For measured radiance and an estimated clear-sky background.
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