How can we use lidar and radar to monitor aerosol-cloud interaction?

Challenge the future

Figure 2. CESAR Observatory in the Netherlands

20091128 Radar reflectivity [dBZ] 95.04 GHz Cloud Radar

Time [UTC] Height [m] 1.5 2 2.5 3 3.5 4 4.5 5 5.5 0 750 1500 2250 3000 −80 −60 −40 −20 0 20

20091128 Attenuated Backscatter Coefficient [1/sr m] MPL

Time [UTC] Height [m] 1.5 2 2.5 3 3.5 4 4.5 5 5.5 0 750 1500 2250 3000 0 2 4 6 8 10 12 x 10−5 1.5 2 2.5 3 3.5 4 4.5 5 5.5 0 50 100 150 200

20091128 Liquid water path

Time [UTC] LWP [g/m 2 ] 3.4 3.6 3.8 4 4.2 4.4 x 10−5 10−4 10−3 10−2 10−1 LWP 15 − 53 g/m2

Attenuated Backscatter Coefficient [ 1/sr m]

Radar Reflectivity [mm 6 m − 3] 3.4 3.6 3.8 4 4.2 4.4 x 10−5 10−4 10−3 10−2 10−1 LWP 54 − 92 g/m2

Attenuated Backscatter Coefficient [ 1/sr m]

Radar Reflectivity [mm 6 m − 3] 3.4 3.6 3.8 4 4.2 4.4 x 10−5 10−4 10−3 10−2 10−1 LWP 93 − 131 g/m2

Attenuated Backscatter Coefficient [ 1/sr m]

Radar Reflectivity [mm 6 m − 3] 3.4 3.6 3.8 4 4.2 4.4 x 10−5 10−4 10−3 10−2 10−1 LWP 132 − 171 g/m2

Attenuated Backscatter Coefficient [ 1/sr m]

Radar Reflectivity [mm 6 m − 3] g/m2 20 40 60 80 100 120 140 160 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 15 − 30 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 31 − 46 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 47 − 62 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 63 − 78 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 79 − 94 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 95 − 110 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 111 − 126 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 127 − 142 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 143 − 158 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 159 − 171 g/m2 g/m2 20 40 60 80 100 120 140 160 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 15 − 22 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 23 − 30 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 31 − 38 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 39 − 46 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 47 − 54 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 55 − 62 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 63 − 70 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 71 − 78 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 79 − 86 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 87 − 94 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 95 − 102 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 103 − 110 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 111 − 118 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 119 − 126 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 127 − 134 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 135 − 142 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 143 − 150 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 151 − 158 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 159 − 166 g/m2 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 167 − 171 g/m2 g/m2 20 40 60 80 100 120 140 160

20101122 Radar reflectivity [dBZ] 95.04 GHz Cloud Radar

Time [UTC] Height [m] 15 15.5 16 16.5 17 17.5 18 18.5 19 19.5 20 20.5 0 750 1500 2250 3000 −80 −60 −40 −20 0 20

20101122 Attenuated Backscatter Coefficient [1/sr m] MPL

Time [UTC] Height [m] 15 15.5 16 16.5 17 17.5 18 18.5 19 19.5 20 20.5 0 750 1500 2250 3000 0 1 2 3 4 x 10−5 15 15.5 16 16.5 17 17.5 18 18.5 19 19.5 20 20.5 0 50 100 150

20101122 Liquid water path

Time [UTC] LWP [g/m 2 ] 1.5 2 2.5 3 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 15 − 42 g/m2

Attenuated Backscatter Coefficient [ 1/sr m]

Radar Reflectivity [mm 6 m − 3] 1.5 2 2.5 3 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 43 − 70 g/m2

Attenuated Backscatter Coefficient [ 1/sr m]

Radar Reflectivity [mm 6 m − 3] 1.5 2 2.5 3 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 71 − 98 g/m2

Attenuated Backscatter Coefficient [ 1/sr m]

Radar Reflectivity [mm 6 m − 3] 1.5 2 2.5 3 3.5 4 4.5 x 10−5 10−4 10−3 10−2 10−1 LWP 99 − 126 g/m2

Attenuated Backscatter Coefficient [ 1/sr m]

Radar Reflectivity [mm 6 m − 3] g/m2 20 40 60 80 100 120 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 15 − 25 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 26 − 36 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 37 − 47 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 48 − 58 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 59 − 69 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 70 − 80 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 81 − 91 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 92 − 102 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 103 − 113 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 114 − 126 g/m2 g/m2 20 40 60 80 100 120 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 15 − 20 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 21 − 26 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 27 − 32 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 33 − 38 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 39 − 44 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 45 − 50 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 51 − 56 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 57 − 62 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 63 − 68 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 69 − 74 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 75 − 80 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 81 − 86 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 87 − 92 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 93 − 98 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 99 − 104 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 105 − 110 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 111 − 116 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 117 − 122 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 123 − 128 g/m2 2 3 4 x 10−5 10−4 10−3 10−2 10−1 LWP 129 − 126 g/m2 g/m2 20 40 60 80 100 120

Figure 3. Map of ACTRIS sites

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Aerosol­Cloud Interactions

How to monitor ACI?

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Karolina Sarna

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_{, H.W.J. Russchenberg}

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_{, D.P. Donovan}

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_{TU Delft Climate Institute, Delft University of Technology, The Netherlands (k.sarna@tudelft.nl)}

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_{Royal Netherlands Meteorological Institute (KNMI), The Netherlands}

Study Cases

28 November 2009

22 November 2010

Compared measurements

Benefits of the method

Outlook

T

he first indirect effect of aerosols on clouds has a well established underlying physical process. If the same amount of water is available, an increased amount of aerosols in the atmosphere will result in more cloud condensation nuclei for the cloud droplet formations. That will lead to an elevated concentration of cloud droplets and consequently the formed droplets will be smaller.

T

o observe interaction between aerosols and clouds we need three components: the cloud properties, the aerosol properties below the cloud and the amount of water available.

We propose a method of ACI monitoring based on the direct measurements from widely available instruments. For an aerosol proxy we propose to use Attenuated Backscatter Coefficient

from lidar. To obtain information about changes in the cloud we use Radar Reflectivity Factor from a cloud radar. We supplement these observations with Liquid Water Path from a radiometer.

M

any different strategies have been used to investigate the Aerosol­Cloud Interactions. Unfortunately, the wide scope of methods and scales applied makes it difficult to quantitatively compare results from different studies. We propose a new scheme of measurements that will provide more consistent observations. The main benefits include:

1

It is a simple method. We use direct observables from widely spread remote sensing instruments.

2

We make no assumptions about the microphysical properties of clouds.

3

We use widely available instruments. This method can be easily implemented at other observatories.

4

It is less restrictive in the selection of study cases which will allow us to analyse more data.

5

It can (and should) be complemented by microphysical properties for the interpretation of the data.

N

umber concentration of cloud droplets depends on number concentration of

aerosols with some factor gamma. If we combine the formulas for reflectivity and backscatter coefficient and add to that the equation for the Liquid Water Content, we can derive a relation between the Attenuated Backscatter Coefficient and the Radar Reflectivity Factor.

T

he adjacent graphs present two study cases of Stratocumulus clouds. The meteorological conditions during both episodes were similar. Variables we compare are: 1. An integrated value of the Attenuated Backscatter

Coefficient. This value is integrated over a column starting at the height of the complete overlap to 400 m below the cloud base;

2. An integrated value of the Radar Reflectivity Factor. In both cases this value is integrated over the whole cloud. The colours of the dots on the plots represent the values of the Liquid Water Path in an observed column.

We expect that an increase of the Attenuated Backscatter Coefficient will correspond to an increase of the Radar Reflectivity Factor. However, the slope of this correlation will vary.

W

e plan to implement this framework over the cloud profiling sites of the ACTRIS network in Europe to enable monitoring of the Aerosol­Cloud Interaction close to real­time. In the next step we will use

back­trajectory models to identifytheaerosolsources. We will also analyse study cases based on similar meteorological and microphysical conditions.

R a d a r R e fl e c ti v it y F a c to r ­ in c re a s e in th e c lo u d d ro p le t c o n c e n tr a ti o n

Attenuated Backscatter Coefficient ­ increase in the aerosol number concentration

Figure 1. Schematic of the aerosol indirect effects. CDNC stands for cloud droplet number concentration and LWC stands for liquid water content.

ATTENUATED BACKSCATTER COEFFICIENT aerosol n = const. no change in the cloud aerosol n

increases more cloud droplets RADAR REFLECTIVITY FACTOR cloud droplets n = const.

big increase ­ due to droplets size cloud droplets n increases small increase ­ by factor dn