Ground‐based remote sensing of precipitation in the Arctic

Zhao, Chuanfeng; Garrett, T. J.

doi:10.1029/2007jd009222

Cited by 22 publications

(32 citation statements)

References 36 publications

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“…The role of precipitation in the observed LWP differences between clean and polluted cases can be estimated using characteristic precipitation rates in the Arctic. Analysis of U.S. National Weather Service data from 2000 to 2004 showed precipitation rates ranging from about 0.04–0.4 mm/day at Barrow in April [ Zhao and Garrett , 2008]. Considering the average LWP values in Table 2, there is a difference of ∼48 g/m 2 between clouds in clean and polluted cases.…”

Section: Resultsmentioning

confidence: 99%

Factors influencing the microphysics and radiative properties of liquid-dominated Arctic clouds: Insight from observations of aerosol and clouds during ISDAC

et al. 2011

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[1] Aircraft measurements during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) in April 2008 are used to investigate factors influencing the microphysics and radiative properties of springtime Arctic clouds. The analysis is focused on low-level, liquid-dominated clouds in two separate regimes with respect to cloud and aerosol properties: single-layer stratocumulus with below-cloud aerosol concentrations (N a ) less than 250 cm −3 (clean cases); and layered stratocumulus with N a > 500 cm −3 below cloud base, associated with a biomass burning aerosol (polluted cases). For each regime, vertical profiles through cloud are used to determine cloud microphysical and radiative properties. The polluted cases were correlated with warmer, geometrically thicker clouds, with higher droplet number concentrations (N d ), liquid water paths (LWP), optical depths (t), and albedo (A) relative to clean cases. The mean cloud droplet effective radii (r eff ), however, were similar (5.7 mm) for both aerosol-cloud regimes. This discrepancy resulted mainly from the higher LWP of clouds in polluted cases, which can be explained by both meteorological (temperature, dynamics) and microphysical (precipitation inhibition) factors. Adiabatic parcel model simulations demonstrate that differences in droplet activation between the aerosol-cloud regimes may play a role, as the higher N a in polluted cases limits activation to larger and/or more hygroscopic particles. The observations and analysis presented here demonstrate the complex interactions among environmental conditions, aerosol, and the microphysics and radiative properties of Arctic clouds.

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Section: Resultsmentioning

confidence: 99%

Factors influencing the microphysics and radiative properties of liquid-dominated Arctic clouds: Insight from observations of aerosol and clouds during ISDAC

et al. 2011

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“…The smaller maximum size we measured for ice crystals can be attributed to the sensitivity of our technique to particle widths rather than lengths. Year-round measurements of water droplet and ice particle precipitation with an MMCR at the NSA-AAO site near Barrow yield characteristic radii of 25 to 500 µm from terminal fall speeds (Zhao and Garrett, 2008), and our ice crystal sizes fall within this range.…”

Section: Particle Effective Radiimentioning

confidence: 99%

“…The SHEBA experiment stands out from previous studies in that it collected a year of data from a ship frozen into the Arctic Ocean. Year-round remote sensing measurements from the North Slope of Alaska -Adjacent Arctic Ocean (NSA-AAO) site near Barrow,Alaska (71.3 • N, 156.6 • W) have also been used to investigate particles (Zhao and Garrett, 2008). The PEARL experiment was designed to build upon these earlier activities, and provides an opportunity to obtain comprehensive long-term data sets in the High Arctic.…”

Section: Introductionmentioning

confidence: 99%

Physical properties of High Arctic tropospheric particles during winter

et al. 2009

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Abstract. A climatology of particle scattering properties in the wintertime High Arctic troposphere, including vertical distributions and effective radii, is presented. The measurements were obtained using a lidar and cloud radar located at Eureka, Nunavut Territory (80 • N, 86 • W). Four different particle groupings are considered: boundary-layer ice crystals, ice clouds, mixed-phase clouds, and aerosols. Twodimensional histograms of occurrence probabilities against depolarization, radar/lidar colour ratio and height are given. Colour ratios are related to particle minimum dimensions (i.e., widths rather than lengths) using a Mie scattering model. Ice cloud crystals have effective radii spanning 25-220 µm, with larger particles observed at lower altitudes. Topographic blowing snow residuals in the boundary layer have the smallest crystals at 15-70 µm. Mixed-phase clouds have water droplets and ice crystal precipitation in the 5-40 µm and 40-220 µm ranges, respectively. Ice cloud crystals have depolarization decreasing with height. The depolarization trend is associated with the large ice crystal sub-population. Small crystals depolarize more than large ones in ice clouds at a given altitude, and show constant modal depolarization with height. Ice clouds in the mid-troposphere are sometimes observed to precipitate to the ground. Water clouds are constrained to the lower troposphere (0.5-3.5 km altitude). Aerosols are most abundant near the ground and are frequently mixed with the other particle types. The data are used to construct a classification chart for particle scattering in wintertime Arctic conditions.

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“…With the contribution of precipitation to thermal emission excluded, the contribution of clouds and other trace gases to downwelling surface radiance is Figure 7 shows values of ε P obtained near Barrow, Alaska based on precipitation properties derived by Zhao and Garrett (2008). Retrieved values of ε P range from 0 to 0.14 with lower and upper quartile values of 0.01 and 0.04, respectively.…”

Section: Estimation Of Cloud Emissivity From Measurementsmentioning

confidence: 99%

“…However, cases can exist where below-cloud hydrometeors contribute non-negligibly to downwelling thermal radiance. To address this possibility, we first estimate a characteristic precipitation particle radius and number concentration using a precipitation retrieval method we previously developed in Zhao and Garrett (2008). This technique retrieves precipitation microphysical properties as a function of radar reflectivity and Doppler velocity.…”

Section: Estimation Of Cloud Emissivity From Measurementsmentioning

confidence: 99%

Ground-based remote sensing of thin clouds in the Arctic

Garrett

Zhao

2013

Atmos. Meas. Tech.

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Abstract. This paper describes a method for using interferometer measurements of downwelling thermal radiation to retrieve the properties of single-layer clouds. Cloud phase is determined from ratios of thermal emission in three "micro-windows" at 862.5 cm−1, 935.8 cm−1, and 988.4 cm−1 where absorption by water vapour is particularly small. Cloud microphysical and optical properties are retrieved from thermal emission in the first two of these micro-windows, constrained by the transmission through clouds of primarily stratospheric ozone emission at 1040 cm−1. Assuming a cloud does not approximate a blackbody, the estimated 95% confidence retrieval errors in effective radius re, visible optical depth τ, number concentration N, and water path WP are, respectively, 10%, 20%, 38% (55% for ice crystals), and 16%. Applied to data from the Atmospheric Radiation Measurement programme (ARM) North Slope of Alaska – Adjacent Arctic Ocean (NSA-AAO) site near Barrow, Alaska, retrievals show general agreement with both ground-based microwave radiometer measurements of liquid water path and a method that uses combined shortwave and microwave measurements to retrieve re, τ and N. Compared to other retrieval methods, advantages of this technique include its ability to characterise thin clouds year round, that water vapour is not a primary source of retrieval error, and that the retrievals of microphysical properties are only weakly sensitive to retrieved cloud phase. The primary limitation is the inapplicability to thicker clouds that radiate as blackbodies and that it relies on a fairly comprehensive suite of ground based measurements.

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Ground‐based remote sensing of precipitation in the Arctic

Cited by 22 publications

References 36 publications

Factors influencing the microphysics and radiative properties of liquid-dominated Arctic clouds: Insight from observations of aerosol and clouds during ISDAC

Factors influencing the microphysics and radiative properties of liquid-dominated Arctic clouds: Insight from observations of aerosol and clouds during ISDAC

Physical properties of High Arctic tropospheric particles during winter

Ground-based remote sensing of thin clouds in the Arctic

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