Cloud Liquid Water

Synonyms

CLW; LWP

Definition

Total weight of cloud water in a vertical column of atmosphere for a unit of area.

Introduction

Clouds play a vital role in modulating climate and the earth’s radiation budget. In the atmosphere, the latent heat release or consumption occurs either directly within the clouds or in the precipitation produced from inside the clouds. Clouds strongly affect the radiative fluxes through the atmosphere. Thus, the measurements of hydrometeor variables on clouds in various water phases critically affect the numerical weather prediction (NWP) simulation and climate modeling.

Global measurements of the cloud liquid water path can be determined by satellite-measured microwave brightness temperatures, which quantify the thermal emission of cloud particles. In the early 1970s, the feasibility of the microwave measurement of cloud liquid water was demonstrated by a Nimbus-6 scanning microwave spectrometer. A statistical relationship was first derived between the brightness temperatures at 23 and 31 GHz and cloud liquid water using Nimbus-6 scanning microwave spectrometer data (Grody, 1976). The large-scale distribution of cloud liquid water was obtained over the Pacific Ocean (Grody et al., 1980). This capability was further displayed by Nimbus-7 scanning multichannel microwave radiometer (SMMR) data (Takeda and Liu, 1987). However, more algorithms for cloud liquid water were developed for the Special Sensor Microwave Imager (SSM/I) flown on the defense meteorological satellite program (e.g., Alishouse et al., 1990; Greenwald et al., 1993; Liu and Curry, 1993; Weng and Grody, 1994; Wentz, 1997). The algorithm was further refined for Advanced Microwave Sounding Unit (AMSU) measurements at 23.8, 31.4 GHz (Weng et al., 2003).

Algorithm theoretical database

Cloud liquid water is also referred as the liquid water path. It can be measured from both passive and active remote sensing technology deployed in space and on the ground. From satellites, brightness temperatures at lower microwave frequencies directly respond to the emission signals from clouds and raindrops. Over oceans, the brightness temperatures first increase and then become saturated and decrease as cloud liquid water increases. The nonlinear response is a result of emission and scattering from both small cloud droplets and large raindrops. The saturation point normally varies with frequency and is, for example, 8, 3, and 1 kg/m² (mm) at 10.65, 18.7, and 36.5 GHz, respectively, for a typical warm rain situation. Since the actual liquid water path ranges within several millimeters, it is necessary to use a composite algorithm (Weng and Grody, 1994) to retrieve cloud liquid water to cover the range from non-raining to raining clouds.

In the absence of scattering from precipitation, brightness temperature at a microwave frequency can be derived as the function (Weng et al., 2003):

$$ TB={T_s}\left[ {1-(1-\varepsilon ){T^2}} \right], $$

(1)

where ε and T_s are the surface emissivity and surface temperature, respectively, and the atmospheric transmittance is:

$$ T = \exp \left[ {-({\tau_o}+{\tau_v}+{\tau_l})/\mu } \right], $$

(2)

where τ_o is the optical thicknesses of oxygen. The optical thicknesses of cloud and water vapor are expressed as τ_L = κ_lL and τ_v = κ_lV, respectively, where the liquid water path is $L=\int\limits_{{\Delta Z}} {w(z)\mathrm{ d}z}$ and the water vapor path is $V=\int\limits_0^{\infty } {{\rho_v}\mathrm{ d}z}$. The cloud mass absorption coefficient κ_l is approximated as ${\kappa_l}=\frac{{6\pi }}{{\lambda {\rho_w}}}\operatorname{\rm Im}\left\{ {\frac{{{m^2}-1}}{{{m^2}+2}}} \right\}$ through Rayleigh’s approximation.

Equation 1 provides a fundamental theory for microwave remote sensing of both atmospheric liquid water and water vapor from space over oceanic conditions. In general, at least two frequencies are required, with one being more sensitive to liquid and the other to water vapor. Note that for land conditions where the emissivity is normally high (typically greater than 0.9), brightness temperature decreases as cloud liquid water increases. The depression from non-raining clouds is also typically very small, less than several degrees Kelvin. Thus, it is difficult to detect the liquid-phase clouds over land where its emissivity is high and variable.

Using two channel measurements at 23.8 and 31.4 GHz from the Advanced Microwave Sounding Unit (AMSU), TB₂₃ and TB₃₁, Weng et al. (2003) derived

$$ {V={a_0}\mu \left[ {\ln ({T_s}-T{B_{31 }})-{a_1}\ln ({T_s}-T{B_{23 }})-{a_2}} \right],} $$

(3)

and

$${V={b_0}\mu \left[ {\ln ({T_s}-T{B_{31 }})-{b_1}\ln ({T_s}-T{B_{23 }})-{b_2}} \right],} $$

(4)

respectively, where the coefficients, a₀ and b₀, are functions of cloud and water vapor mass absorption coefficients, and a_1,2 and b_1,2 are functions of surface emissivity and surface temperature, respectively.

The figure below displays a global distribution of cloud liquid water over oceans derived from the use of the AMSU 23.8 and 31.4 GHz measurements. Note that the AMSU measurements during a 24 h period from its descending node do not completely cover the globe because of the presence of orbital gaps. Also, the retrievals are not performed over land, snow, and sea ice conditions due to large emissivity variations. The unit of cloud liquid water is g/m². Note that low clouds over oceans to the west coast of South America are detected very well and their liquid water path is on the order of 100 g/m². The weather systems having relatively high amount of cloud liquid water are associated with those frontal systems and the clouds within the intertropical convergence zone (ITCZ) (Fig. 1).

Figure 1

Global cloud liquid water retrieved from NOAA-15 Advanced Microwave Sounding Unit (AMSU). Only satellite descending node data are used in this retrieval. Land and sea ice areas are shown as missing because of the incapability of calculating surface emissivity.

Summary

Satellite passive microwave measurements provide accurate retrievals of cloud liquid water over oceans. It still remains difficult to retrieve cloud liquid water over land from the emission-based algorithms. Further studies will focus on extending the retrievals with more advanced radiative transfer schemes that include scattering from clouds and precipitation. Also, different algorithms should be developed for high and variable emissivity conditions which are typical of land, snow, and sea ice conditions.