# The statistical properties of tropical ice clouds generated by the West African and Australian monsoons, from ground-based radar-lidar observations

Alain Protat, Julien Delanoë, Artemio Plana-Fattori, P. T. May, E. J. O'Connor

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Alain Protat, Julien Delanoë, Artemio Plana-Fattori, P. T. May, E. J. O'Connor. The statistical properties of tropical ice clouds generated by the West African and Australian monsoons, from ground-based radar-lidar observations. Quarterly Journal of the Royal Meteorological Society, 2010, 136 (S1), pp.345-363. 10.1002/qj.490. hal-00414781

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# The statistical properties of tropical ice clouds generated by the West African and Australian monsoons, from ground-based radar–lidar observations

A. Protat,ª,ᵇ* J. Delanoë,ᶜ A. Plana-Fattori,ᵇ P. T. Mayª and E. J. O'Connorᶜ

**ABSTRACT:** In the present paper we characterize the statistical properties of non-precipitating tropical ice clouds (deep ice anvils resulting from deep convection and cirrus clouds) over Niamey, Niger, West Africa, and Darwin, northern Australia, using ground-based radar–lidar observations from the Atmospheric Radiation Measurement (ARM) programme. The ice cloud properties analysed in this paper are the frequency of ice cloud occurrence, cloud fraction, the morphological properties (cloud-top height, base height, and thickness), the microphysical and radiative properties (ice water content, visible extinction, effective radius, terminal fall speed, and concentration), and the internal cloud dynamics (in-cloud vertical air velocity). The main highlight of the paper is that it characterizes for the first time the probability density functions of the tropical ice cloud properties, their vertical variability and their diurnal variability at the same time. This is particularly important over West Africa, since the ARM deployment in Niamey provides the first vertically resolved observations of non-precipitating ice clouds in this crucial area in terms of redistribution of water and energy in the troposphere. The comparison between the two sites also provides an additional observational basis for the evaluation of the parametrization of clouds in large-scale models, which should be able to reproduce both the statistical properties at each site and the differences between the two sites.

The frequency of ice cloud occurrence is found to be much larger over Darwin when compared to Niamey, and with a much larger diurnal variability, which is well correlated with the diurnal cycle of deep convective activity. The diurnal cycle of the ice cloud occurrence over Niamey is also much less correlated with that of deep convective activity than over Darwin, probably owing to the fact that Niamey is further away from the deep convective sources of the region. The frequency distributions of cloud fraction are strongly bimodal and broadly similar over the two sites, with a predominance of clouds characterized either by a very small cloud fraction (less than 0.3) or a very large cloud fraction (larger than 0.9). The ice clouds over Darwin are also much thicker (by 1 km or more statistically) and are characterized by a much larger diurnal variability than ice clouds over Niamey. Ice clouds over Niamey are also characterized by smaller particle sizes and fall speeds but in much larger concentrations, thereby carrying more ice water and producing more visible extinction than the ice clouds over Darwin. It is also found that there is a much larger occurrence of downward in-cloud air motions less than 1 m s⁻¹ over Darwin, which together with the larger fall speeds retrieved over Darwin indicates that the life cycle of ice clouds is probably shorter over Darwin than over Niamey. Copyright © 2009 Royal Meteorological Society

KEY WORDS AMMA; microphysics

Received 9 December 2008; Revised 6 July 2009; Accepted 6 July 2009

## 1. Introduction

The importance of clouds in the evolution of climate through their direct effect on the Earth's radiation budget and water cycle is well recognized. However, despite significant improvements brought to the representation of clouds in models, clouds still remain by far the largest source of spread among future climate projections produced by climate models (e.g. Potter and Cess, 2004; Bony et al., 2006; Dufresne and Bony, 2008). Among the different parameters of a climate model, two have been recently identified, using principal component analysis of

climate model radiative responses from a multi-thousand ensemble of climate model simulations, as responsible for about 70% of the total variance in the simulations, and they are both cloud parameters: the entrainment coefficient in the convection scheme, and the ice terminal fall speed (Sanderson et al., 2008). The way clouds are represented in models also significantly affects the quality of weather forecasts (e.g. Jakob, 2002), especially where observations are sparse, as over West Africa (Redelsperger et al., 2006). Large-scale models have now reached a high level of complexity though, which on the one hand results in a significant improvement of the model physics realism by the introduction of complex processes, and on the other hand makes their evaluation and improvement increasingly difficult (Jakob,

<footnote>ªCentre for Australian Weather and Climate Research, Melbourne, Australia</footnote>

<footnote>ᵇCentre d'Étude des Environnements Terrestre et Planétaires, Vélizy, France</footnote>

<footnote>ᶜUniversity of Reading, Reading, UK</footnote>

<footnote>*Correspondence to: A. Protat, Centre for Australian Weather and Climate Research (CAWCR), 700 Collins Street, Docklands, Melbourne, VIC3008, Australia. E-mail: a.protat@bom.gov.au</footnote>
2003). Further evaluations and improvements of model performances must now rely on a better understanding of the statistical properties of clouds and deep convection, as well as of the variability of these cloud properties (regional, temporal, vertical, or as a function of large-scale atmospheric or cloud regimes, e.g. Jakob and Tsiilioudis, 2003; Mace *et al.*, 2006b; Marchand *et al.*, 2006; Sassen *et al.*, 2008).

Among the different clouds forming in the troposphere and preferential regions of high cloud occurrence, tropical ice clouds are of particular importance, owing to their extensive horizontal and vertical coverage, and their long lifetime (e.g. Sassen *et al.*, 2008). Besides, the accurate estimate of the large-scale radiative effect of tropical ice clouds is very difficult to achieve, because these clouds both tend to reduce the amount of solar radiation reaching the Earth's surface and to absorb the upwelling infrared radiation emitted by this surface and emit it at a lower temperature, thereby reducing the net amount of outgoing infrared radiation to space and heating the upper troposphere. As a result, even the sign of the net radiative effect of these tropical ice clouds is still a matter of debate, both at the scale of a given cloud and statistically. In order to estimate this net radiative effect correctly, both the morphological (cloud base, height, thickness, amount) and the bulk microphysical and radiative properties (ice water content, effective radius, fall velocity, extinction) of these tropical clouds must be accurately characterized, resulting in a very active area of research in cloud physics.

Ground-based continuous active and passive remote sensing (cloud radar, lidar, radiometers) observations such as those conducted in the framework of the US Department of Energy Atmospheric Radiation Measurement program (ARM: Stokes and Schwartz, 1994) are most relevant to the previous objectives of characterizing the statistical properties of tropical ice clouds, because they are the only sets of instruments capable of describing the high-resolution vertical variability of the ice cloud properties, and because long time series of such observations are already available at a number of tropical sites. From the combination of these instruments put together at those sites, the morphological, microphysical, radiative and dynamical properties of clouds can accurately be retrieved. Recently, two pioneer studies (Mace *et al.*, 2006a; Mather *et al.*, 2007) have documented some of the ice cloud properties over the Manus and Nauru ARM sites, providing unprecedented insights into the statistical properties of tropical cirrus clouds (Mace *et al.*, 2006a) and on the vertical structure of radiative heating and net radiative effect of tropical clouds (Mather *et al.*, 2007) in the western Pacific region. The study of Mace *et al.* (2006a) focussed on tropical cirrus clouds from cloud radar observations, thereby excluding tropical anvils from the statistics and not exploiting the additional information provided by the micro-pulse lidars at the ARM sites. The characterization of the microphysical and radiative properties was achieved with state-of-the-art Doppler radar retrieval techniques. In the study of Mather *et al.* (2007), all clouds have been considered but the

microphysical and radiative properties have been derived using relatively simple empirical relationships when compared to the study of Mace *et al.* (2006a).

In the present paper we exploit the unique opportunity offered by the most recent ARM ground-based radar-lidar observations to characterize the statistical properties of tropical ice clouds over two sites (Niamey, Niger, West Africa, and Darwin, northern Australia) which are both under the influence of a monsoonal large-scale forcing. In order to optimize the accuracy of the retrieved cloud properties and therefore provide the most advanced statistical dataset for model and spaceborne product evaluation, the best datasets in terms of instrument performance, and the cloud retrieval method of reference, have been carefully selected (see discussion in section 2). The paper is organized as follows. The observations and methodology adopted are described in section 2. The statistical morphological properties of tropical ice clouds and their variability are then analysed over each site and compared to each other in section 3. In section 4, the bulk microphysical and radiative properties and their variability are described and some insights into differences in microphysical processes between the two sites are discussed. Conclusions and perspectives of this work are finally given in section 5.

## 2. Observations and methodology

The objective of this study is to characterize the statistical properties of tropical ice clouds generated by the West African and Australian monsoons, and to evaluate if these statistical properties are similar. These comparisons will on the one hand shed some light on the variability of the cloud properties along the tropical belt, and will provide on the other hand an observational basis to evaluate large-scale models, because if differences are found, cloud schemes in large-scale models should be able to reproduce them.

The statistical properties of tropical ice clouds discussed in the present paper are derived from continuous vertically pointing radar and lidar observations collected at the Darwin ARM site and by the Niamey ARM Mobile Facility (AMF). As summarized in Table I, the observational period retained for Darwin is from 1 December 2006 to 1 May 2007 (which corresponds to the 2006/2007 wet season), while the period retained for Niamey is from 1 June 2006 to 1 November 2006 (the 2006 wet season in West Africa). The Niamey AMF deployment was part of the African Monsoon Multidisciplinary Analysis (AMMA) ground-based measurement programme (Redelsperger *et al.*, 2006). The 2006/2007 season at Darwin has been preferred to the 2005/2006 season during which the Tropical Warm Pool-International Cloud Experiment (TWP-ICE: May *et al.*, 2008) was held, because the ARM cloud radar had operated with degraded sensitivity that earlier season (struck by lightning). These two radar-lidar datasets are of very high quality and fully continuous, allowing for a detailed characterization of these two monsoon seasons from more
<table><caption>Table I. Ground-based radar characteristics and observational periods used in this study.</caption><thead><tr><th>Location (latitude, longitude)</th><th>Radar frequency (name)</th><th>Radar Sensitivity (dBZ @ 10 km)</th><th>Observational Period</th></tr></thead><tbody><tr><td>Darwin, Australia (12.425°S; 130.891°E)</td><td>35 GHz (MMCR)</td><td>-41 (cirrus mode)</td><td>1 Dec. 2006–1 May 2007</td></tr><tr><td>Niamey, Niger (13.477°N; 2.176°E)</td><td>94 GHz (WACR)</td><td>-36</td><td>1 June 2006–1 November 2006</td></tr></tbody></table>

than 4000 hours of observations. The longitude and latitude of the two sites are also given in Table I.

One potential difficulty when comparing statistical properties derived from one season only is the significance of the differences. This is in particular true over Darwin, which is influenced both by interannual variability associated with the El Niño–Southern Oscillation (ENSO) and by intraseasonal and interannual variabilities associated with the Madden–Julian oscillations (MJO: Madden and Julian, 1972) which substantially modulate the convective activity (and hence presumably the ice cloud production). To our knowledge the modulation of the statistical properties of tropical ice clouds in northern Australia by the El Niño–Southern and Madden–Julian Oscillations is an open question. This will be the subject of future research. The 2006/2007 wet season over Darwin has been characterized by a moderate El Niño episode (according to the Multivariate ENSO Index, MEI, and the Southern Oscillation Index, SOI) and a moderate MJO amplitude. All the eight phases of the MJO as defined in Wheeler and Hendon (2004) have been swept during this wet season (not shown). Overall, it can be considered as a relatively ‘neutral’ season with respect to the ENSO and MJO variabilities.

The radar–lidar observations include ‘ice cloud’ profiles (defined as not having a liquid layer below, such as non-precipitating ice anvils, altocumulus/altostratus clouds, and cirrus clouds) and ‘convective ice’ profiles (the ice part of precipitating systems). Great care has been taken to split the datasets into ice clouds and convective ice using the ‘target categorization’ approach (see http://www.met.rdg.ac.uk/~swrhgnrj/publications/ categorization.pdf for detailed documentation, and also Delanoë and Hogan, 2008), which consists in classifying each observed scene as a meteorological or non-meteorological target from the cloud radar, lidar, and microwave radiometer measurements, and assigning a water phase (liquid, ice, mixed-phase) and a data quality flag to each cloud scene. In what follows we will discuss mostly the statistical properties derived from the ‘ice cloud’ profiles, because the convective ice profiles are contaminated by strong attenuation, which can produce significant statistical biases and does not allow quantitative retrievals of the microphysical and radiative properties. We will therefore use the convective ice statistics only to link the diurnal cycle of ice clouds to that of convection over Darwin and Niamey.

In this paper the morphological, microphysical and radiative properties will be derived and discussed. The

morphological cloud properties are the frequency of cloud occurrence, cloud fraction, cloud-top height, cloud-base height, and cloud geometrical thickness. They are derived using the radar reflectivity and lidar backscatter as tracers of where and when a cloud is present and at which height. For the particular case of cloud fraction, the characteristics of the UK Met Office Unified Model version 6.4 (UM) grid have been considered for these calculations (0.375 degrees, roughly 37 km horizontal resolution, 50 vertical levels), because in the near future we will evaluate the representation of ice clouds in the UM model over Australia. The microphysical and radiative properties are the ice water content (denoted as IWC in the following), the ice particle concentration, the terminal fall speed of the ice particles, the effective radius and the visible extinction.

The way they are derived in the present study needs to be discussed in further detail. In order to access these microphysical and radiative properties, the radar–lidar combination and the Doppler + reflectivity radar combination are clearly the most suitable (e.g. Hogan et al., 2006; Heymsfield et al., 2008). The cloud radar alone will penetrate most clouds but will miss a portion of the thin cirrus clouds (Comstock et al., 2002; Mace et al., 2006a; Protat et al., 2006). The lidar alone will detect these thin cirrus clouds, but will be very often extinguished by clouds of optical depth larger than 2–3 or supercooled liquid cloud layers in mixed-phase clouds (e.g. Sassen and Cho, 1992; Protat et al., 2006). In the radar–lidar overlap regions, radar reflectivity and lidar backscatter can be used simultaneously to retrieve accurate cloud properties (e.g. Donovan and van Lammeren, 2001; Wang and Sassen, 2002; Tinel et al., 2005; Delanoë and Hogan, 2008, which will be hereafter be referred to as DH08). However, it has been estimated at midlatitudes that this overlap corresponded to about 10% of the total ice cloud volume of mixed-phase and ice clouds over the Cloudnet sites (Illingworth et al., 2007). This problem has been recently overcome in a variational radar–lidar retrieval technique which produces a solution for all instrumental combinations, radar alone, radar–lidar, and lidar alone (DH08). Methods relying on radar reflectivity and Doppler measurements (Mace et al., 2002; Matrosov et al., 2002; Delanoë et al., 2007) show considerable promise, because they can be applied to a large percentage of ice clouds (those detected by the radar), they are almost as accurate as radar–lidar retrievals for the ice water content (e.g. Heymsfield et al., 2008), they provide reasonably unbiased estimates of visible extinction
at midlatitudes (Delanoë et al., 2007), and they allow for the retrieval of additional cloud parameters, such as the in-cloud vertical air velocity and terminal fall speed of the hydrometeors. Methods relying on statistical relationships using radar reflectivity and temperature can also be used to produce virtually unbiased estimates of IWC (Hogan et al., 2006; Protat et al., 2007) but with a larger uncertainty. In view of these considerations the microphysical and radiative properties discussed in this paper have been derived using the variational radar–lidar technique of DH08 and the terminal fall speed and in-cloud vertical air velocity using the Doppler cloud radar technique RadOn (Delanoë et al., 2007). We noted in the course of this study that the RadOn technique was providing IWCs in good agreement with the variational radar–lidar technique, but unreliable estimates of visible extinction. This is probably due to the fact that RadOn had been developed and tested for midlatitude ice clouds and needs further refinements to be fully applicable to the tropical ice clouds. However, the first part of the method, which consists of deriving the fall speed and vertical air velocity from the Doppler velocity measurement, can still be used because it does not rely on these required refinements.

Finally, it is important to note that great care has been taken to ensure that differences between the two sites be attributable to microphysical differences and not to instrumental differences. First, when comparing the results from Darwin and Niamey, the radar observations have been degraded to the same detection level (sensitivity), because the Darwin radar in so-called ‘cirrus mode’ is 5 dB more sensitive than the Niamey radar. The difference in frequency between the two radars (see Table I) has also been taken into account by ‘converting’ the Darwin radar observations at 95 GHz, as proposed recently by Protat et al. (2009). It is noteworthy that this conversion only slightly modified the reflectivity statistics, not enough to alter any conclusions drawn in what follows had we decided not to use this conversion from 35 to 95 GHz. Regarding the lidars, the Darwin and Niamey micro-pulse lidars are identical, so there is no need to adapt lidar sensitivities. The only potential issue with the lidars in general is the diurnal variability of the lidar detection level, which might alter the description of the diurnal cycle of the ice cloud properties. However, although we have no way to quantify this effect precisely, looking at lidar observations of continuous thin cirrus lasting over a few days led us to subjectively believe that this may be a minor issue.

### 3. The morphological properties of tropical ice clouds over Darwin and Niamey

In the present section, probability density functions (PDFs) of the morphological properties of tropical ice clouds are first discussed, and for some of them mean vertical profiles are analysed both over Niamey and Darwin. The diurnal cycle of the cloud properties will be characterized by two-dimensional histograms in which time is the abscissa and the cloud parameter the ordinate.

These graphs are a convenient way to analyse the variability of the cloud parameter PDFs with time. The same approach has been adopted to analyse the variability of the cloud parameter PDFs with height. It must be noted here that this approach is different from the Contoured Frequency by Altitude Diagrams (CFADs) proposed by Yuter and Houze (1995), because the CFADs are normalized by the total number of points, while we normalize by the total number of points for each height bin. Using this approach has the advantage of separating the variability due to the frequency of occurrence from the effect really due to the variability of the cloud parameters PDFs, so our graphical representation can truly be interpreted directly as the variation of the PDF with height (or time in the case of the diurnal cycle characterization). For sake of simplicity we will call these two-dimensional histograms HPDFs (Height-dependent PDFs) and TPDFs (Time-dependent PDFs) in what follows. The morphological properties over the two sites are then compared with each other and with previous vertically resolved tropical ice cloud statistics over other tropical sites (Mace et al., 2006a; Mather et al., 2007). In Figure 1 and hereafter, the solid red curves will refer to the Niamey results (which will be our reference climatology over Niamey), the solid blue curves will refer to the Darwin results at the Niamey radar sensitivity (which can be compared directly to the solid red curves), and the dashed blue curve will refer to the reference climatology over Darwin (that is, using the full radar sensitivity).

#### 3.1. Frequency of cloud occurrence

The frequency of cloud occurrence (which will be referred to as ‘cloud occurrence’ in the following) is defined as the ratio of the number of ‘cloudy’ radar and/or lidar gates to the total number of radar–lidar gates. The most interesting properties to investigate for this type of quantity are the mean vertical profile and the diurnal cycle. These quantities can also be calculated for the convective ice profiles. However, it is to be noted that the convective ice cloud occurrence is biased towards lower occurrences in the upper part of the troposphere because of strong attenuation which produces underestimated cloud-top heights. In the following, we will therefore use it only to link the diurnal cycle of ice clouds to that of convection over Darwin and Niamey.

The vertical profiles of cloud occurrence over Darwin and Niamey are given in Figure 1(a) and (b), respectively. The structure of the two profiles appears to be very similar, with increasing occurrences with height up to 12 km height, decreasing then from 12 km to 18 km height. This vertical structure is consistent with the cloud occurrence profiles documented over the Manus and Nauru ARM sites in the Tropics (Mace et al., 2006a; Mather et al., 2007). The cloud occurrence is however much larger over Darwin than over Niamey (a factor 2 to 3 at all heights, see Figure 1(c)). For instance, at 12 km height, there are ice clouds 23% of the time over Darwin and only 9% of the time over Niamey. The peak values
<figure><img src="image_3.png" /><figcaption>Figure 1. Vertical profile of the frequency of ice cloud occurrence (thick solid lines) and convective ice occurrence (thin solid lines) over Darwin with the radar degraded at the sensitivity of the Niamey radar (blue, left panel) and Niamey (red, middle panel), and comparison of the ice cloud occurrence over the two sites (right panel). Also given is the frequency of ice cloud occurrence over Darwin with the radar at full sensitivity (dotted blue line on left panel).</figcaption></figure>

found by Mace *et al.* (2006a) over Manus and Nauru are 11% and 9%, respectively, which is comparable to the values found over Niamey, although it must be noted that only cirrus clouds are included in the Mace *et al.* (2006a) statistics.

It is also interesting to note the existence of a secondary maximum at around 6–7 km height in the Niamey vertical profile (Figure 1(b)), which is not observed on the vertical profiles over Darwin (Figure 1(a)), nor over Manus and Nauru (see Mace *et al.*, 2006a, their Fig. 1). On the other hand this feature is fairly consistent with the increase in frequency distributions of radar reflectivity in Mather *et al.* (2007) over Manus and Nauru (their Fig. 5). This enhanced frequency of ice cloud occurrence has been attributed by these authors to the detrainment from tops of shallow convective storms in a stable layer located in the 5–7 km layer (as observed in statistical studies of tropical soundings: Johnson *et al.*, 1999). The inspection of the daily Darwin and Niamey radar observations also indicates the existence of regular occurrences of thin and persistent altocumulus clouds at these heights over both sites, which certainly contribute to the observed secondary peak over Niamey.

The vertical profile of convective ice occurrence is also characterized by much larger occurrences over Darwin, and exhibits a continuous decrease of occurrence with height over both sites (Figure 1(a) and (b), thin lines), starting above the 5 km height, which corresponds roughly to the 0°C isotherm altitude. However, as discussed previously, these profiles are expected to be biased by attenuation of the radar signal and are not interpreted any further.

Figures 2 and 3 show the diurnal cycle of ice clouds and convective ice over Darwin and Niamey, respectively. The diurnal cycles of ice clouds (Figure 2(a)) and convective ice (Figure 2(b)) over Darwin are very strong and well correlated with each other, with maximum occurrences of ice clouds and convection at night, peaking to cloud occurrences larger than 30% at 12 km height between 2000 and midnight local time. Ice clouds and convective ice during this peak activity are found up to 30–35% and 15–18% of the time, respectively. The ice cloud occurrence remains significant from 8 to 15 km height during daytime, with occurrences peaking at 15–20% (Figure 2(a)). This signature during daytime corresponds to the occurrence of the non-precipitating ice anvils and long-lived cirrus clouds generated by the night-time deep convective activity, which progressively get thinner and with lower cloud tops during their life cycle, as clearly shown in Figure 2 from 0500 to 1500 local time (top panel).

The diurnal cycle is completely different over Niamey (Figure 3). Firstly the diurnal cycle of ice cloud occurrence is much less marked than over Darwin, with relatively constant occurrences of around 10% in a layer centred at around 12 km height (Figure 3(a)). The depth of this layer of enhanced occurrence is however clearly modulated by the deep convective activity peaking from 0700 to 1400 local time over Niamey (Figure 3(b)), which is another major difference between Darwin and Niamey. This increase in depth is probably attributable to the non-precipitating ice anvils generated by deep convection at the time of maximum convective activity, which in turn produce the continuous residual cirrus clouds in the 9–15 km layer later. The secondary peak in Figure 1(b)
<figure><img src="image_4.png" /><figcaption>Figure 2. Time-height cross-section of (a) the frequency of ice cloud occurrence and (b) convective ice occurrence in % over the Darwin site.</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>Figure 3. Same as Figure 2 but for the Niamey site. Note the change of scale with respect to Figure 2.</figcaption></figure>
also corresponds to a well-defined signature on the diurnal cycle in the 5–7 km layer (Figure 3(a)). The diurnal cycle of the frequency of occurrence of these ice clouds is somewhat more marked than that of the cirrus clouds, with two well-defined peaks at around 0400 and 1200 local time, and a much smaller occurrence between 1800 and midnight local time. The convective ice occurrence maximum peaks at around 8–9% during the day (Figure 3(b)), which is about half of the convective ice occurrence over Darwin. The lack of a diurnal variation in Figure 3 would imply longer-lived cirrus over Niamey than over Darwin, beyond the time-scale of a day. As will be shown later, this seems to be fairly consistent with the differences in microphysical properties. It is important to notice that the location of Niamey is very specific, because it is not where convection triggers. Convection usually triggers in the evening further east of Niamey, and especially over the Jos Plateau (e.g. Fink et al., 2006; Laing et al., 2008). Owing to their typical fast-moving propagation speed (~10–15 m s⁻¹) deep convective systems usually reach Niamey early in the morning (as confirmed in Figure 3) and are often in a dissipating stage owing to less favourable conditions at this time of day. Later at noon they are reactivated further west, over Burkina Faso, where they meet more favourable conditions. Further regional studies using recent active remote sensing such as the A-Train (Stephens et al., 2002) and back-trajectory analyses will be required in order to evaluate the variability of the tropical ice cloud properties over West Africa, and especially over the Sahelian band.

This characterization of the diurnal cycle of ice cloud occurrence is very complementary to the results of Mather et al. (2007) over Manus and Nauru. The four diurnal cycles are found to be quite different when analysed together. The diurnal cycle of ice clouds at Nauru, which is a small island far from any large land mass, is very small and dominated by cirrus clouds (Mather et al., 2007, their Fig. 12), and with a maximum at the same 12 km height as the maximum occurrence of cirrus clouds at Niamey (which is a pure continental location). However there are significant occurrences of ice clouds below 10 km height, which is not the case over Nauru. The diurnal cycle at Manus Island, which is strongly influenced by the surrounding large Maritime Continent islands (New Guinea, New Ireland and New Britain) is very strong, as over Darwin, and with a very similar distribution as over Darwin, including the characteristics of the non-precipitating anvils and cirrus clouds. The timing is however different, with a peak ice cloud occurrence in the early afternoon, very well correlated with the deep convective activity as over Darwin (Mather et al., 2007, their Fig. 12), while over Darwin the peak ice cloud occurrence is around midnight.

## 3.2. Cloud fraction

The cloud fraction describes the percentage of the volume of a model grid box filled with clouds. It is one of the two prognostic variables to describe a cloud in state-of-the-art cloud parametrizations of large-scale models. In

order to compute the cloud fraction from cloud radar and lidar observations, we use temporal averaging to yield the equivalent of a two-dimensional slice through the three-dimensional model grid box, as typically done when comparing observed and modelled cloud fractions (e.g. Mace et al., 1998; Hogan et al., 2001). From the horizontal wind speed as a function of height and the horizontal model grid-box size, the appropriate averaging time is calculated. The horizontal wind field used in the present study comes from an interpolation of the 6-hourly and 12-hourly radiosonde measurements performed over Niamey and Darwin. It is assumed that in this time the cloud structure observed is predominantly due to the advection of structure within the grid box across the site, rather than evolution of the cloud during the period. However these time series are bi-dimensional while a model grid box represents a three-dimensional volume. It is then assumed that the fraction of the grid filled by cloud in the two-dimensional grid box represents the amount of cloud in the three-dimensional volume.

In the present study, only HPDFs of cloud fraction are analysed. Indeed as argued in Bouniol et al. (2009) for midlatitude clouds, mean vertical profiles of cloud fraction are not a good reference for model evaluation, because most of the time and for most heights the cloud fraction distribution is not unimodal. In order to compute cloud fraction from the cloud radar–lidar observations, we have considered the horizontal grid size (0.375 degrees) and the 50 vertical levels of the global version of the UM model, because one of the next steps of this study is to evaluate the representation of clouds in this model over Australia. Let us recall that these HPDFs should be interpreted as the frequency of a given cloud fraction value at a given height. The HPDFs are shown for Darwin and Niamey in Figure 4(a) and (b), respectively. We have also computed the fractional difference between the Darwin HPDF and the Niamey HPDF, which is given in Figure 4(c). It is to be noted that to our knowledge this is the first time that the cloud fraction distributions of tropical ice clouds are documented. Firstly, it clearly confirms the findings of Bouniol et al. (2009) for midlatitude clouds, with a well-defined bimodal structure of cloud fraction at all heights. This indicates that tropical ice clouds tend to either fill completely the model grid box (cloud fractions of 0.9 to 1) or not fill it much at all (cloud fractions ranging from 0.05 to 0.3), which produces a well-defined bimodal cloud fractions distribution. Both sites exhibit roughly the same distribution characteristics. It is to be noted that identical results are found when the grid size of the regional version of the UM model (12 km) is considered instead of that of the global version of the model (not shown). The difference of HPDFs (Figure 4(c)) reveals some clear differences though. The main difference is found for the high-level clouds (above 12 km height), which tend to have increased occurrences (by 60% and more) of intermediate and large cloud fraction values over Darwin than over Niamey. Clouds at heights ranging from 8 to 12–13 km over Darwin also clearly tend to be characterized by smaller occurrences (−30%) of small
<figure><img src="image_6.png" /><figcaption>Figure 4. HPDF of cloud fraction (a) over Darwin, (b) Niamey, and (c) the difference HPDF (Darwin–Niamey) in %.</figcaption></figure>

cloud fractions (0.05 to 0.3) than over Niamey. Finally much smaller occurrences (–60% or less) of high cloud fractions are found over Darwin with respect to Niamey for clouds below 7 km height. It is out of the scope of this paper to conduct an evaluation of the representation of clouds in large-scale models, but it is noteworthy that the models should be able to reproduce both the cloud fraction distributions over each site and the difference between sites.

### 3.3. Cloud-top height, cloud-base height, and thickness

The cloud-top height, base and thickness are basic but crucial quantities for model evaluation purposes, for the evaluation of spaceborne passive remote sensing retrievals of these quantities, and for an accurate estimate of the cloud-radiation feedbacks. The ice cloud-top height, base height, and thickness PDFs derived from continuous radar-lidar observations over Darwin and Niamey are given in Figure 5. The cloud-top height PDFs (Figure 5(a)) over Darwin and Niamey are both characterized by a bimodal distribution. The main peak corresponding to the highest levels is clearly broader over Darwin than over Niamey, with a notably higher probability for clouds to reach greater heights than the Niamey ice clouds in the 13–17 km layer, but both distributions peak at exactly the same height (12.5 km). The secondary peak at 6–7 km is much less marked over Darwin, which is consistent with the results previously discussed for cloud occurrence, for which a peak of ice cloud occurrence was also found at 5–7 km height. The PDF derived from the full Darwin MilliMetre wavelength Cloud Radar (MMCR) sensitivity shows an enhanced probability of having ice clouds reaching altitudes from 14 to 17 km height, with a peak value located at 14 km height, which is consistent with the results obtained by Mace *et al.* (2006a) over Manus and Nauru. In a study using both radar and lidar observations at the Nauru site, Comstock *et al.* (2002) have shown that the Nauru ARM MMCR radar was sufficiently sensitive to detect most cirrus clouds below 15 km, while above 15 km the

cirrus clouds were often below the detection level of the MMCR. We therefore assume that the results presented herein can be considered as a reference for comparisons with other sources of data (observations and models) over Darwin up to 15 km.

The cloud-base height PDF over Darwin shows an almost equal probability of 6% of having cloud-base heights from 5 to 11 km (Figure 5(b)), and a linearly decreasing probability of having cloud-base heights from 11 to 15 km height. The distribution of cloud-base heights over Niamey is quite different, clearly bimodal, with two well-marked peaks over Niamey centred at around 5 and 12 km. This probably corresponds to a larger occurrence of thin cirrus clouds over Niamey, which tends to boost the upper-level peak with respect to Darwin. The other large difference between Darwin and Niamey is found for cloud thickness (Figure 5(c)), with much larger occurrences of thicker ice clouds over Darwin, or thinner ice clouds over Niamey, probably corresponding again to a larger occurrence of cirrus clouds over Niamey and deep non-precipitating ice anvils over Darwin.

The diurnal cycle of these three quantities is given as TPDFs in Figure 6. The diurnal cycle of cloud-top height over Darwin (Figure 6(a)) shows a well-marked diurnal cycle of the PDF with largest cloud-top heights of 16 km and higher reached from 1500 to 2000 local time, and lowest cloud-top heights from 0500 to 1000 local time. This marked diurnal cycle is consistent with that of convection depicted in Figure 2(b), with the highest cloud tops at times where convective activity is most intense. Interestingly the cloud-top heights associated with the evening convective activity are much larger than those associated with the early morning convection, which probably indicates that convection is more intense and the probability of updraughts overshooting the tropopause largest in the evening convection. During the moist easterly periods (also called ‘break’ periods), the evening convection in the Darwin area is often associated with squall lines (Keenan and Carbone, 1992), which
<figure><img src="image_7.png" /><figcaption>Figure 5. PDF of (a) cloud-top height, (b) cloud-base height, and (c) cloud thickness over Darwin with the radar degraded to the sensitivity of the Niamey radar (solid blue), over Darwin at full sensitivity (dashed blue), and over Niamey (solid red).</figcaption></figure>

are well organized and characterized by a large horizon-
tal extent, which may explain these highest cloud tops
associated with the evening convection. There is also
some indication of a bimodal distribution with a sec-
ondary peak at around 7 km height between 0500 and
1000 local time. The TPDF of cloud-top height over
Niamey is very different, with a much less marked diur-
nal cycle (Figure 6(d)). It does not exhibit any signif-
icant oscillation of the cloud-top height occurrence or
any change in the PDF structure. The PDF is clearly
bimodal at all times except late in the evening when
the secondary peak located at 7 km height vanishes. The
main peak is centred at 13 km height, with a similar dis-
tribution shape as that of the early morning PDF over
Darwin. This diurnal cycle of cloud-top height does not
seem to be modulated much by the convective activity
(depicted in Figure 3(b)). This feature is probably due to
the fact that the diurnal cycle of cirrus cloud-top heights
dominates the variability. This is somewhat confirmed
when looking at the diurnal cycle of cloud-base heights
over Niamey (Figure 6(e)), which is also characterized
by a clear maximum at 11–12 km height, just below

the cloud-top height maximum, which probably indicates
that the main contribution to the diurnal cycle at these
heights is from the cirrus clouds and not from the deep
non-precipitating anvil clouds. This large frequency of
occurrence of cirrus clouds apparently disconnected from
the deep convective activity over Niamey most likely
results from the fact that a large proportion of the cir-
rus clouds is generated well east of Niamey by deep
convective systems which trigger over the Jos Plateau
and other locations further east from Niamey (e.g. Fink
et al., 2006; Laing et al., 2008). The cirrus clouds gen-
erated by this deep convection are then advected over
Niamey by the Tropical Easterly Jet in the upper tropo-
sphere. In contrast, over Darwin there is no clear diurnal
cycle of cloud-base heights (Figure 6(b)), which suggests
that deep non-precipitating anvil clouds resulting from
deep convection dominate the signal (all cloud bases are
roughly equally probable in deep ice anvils thinning dur-
ing their life cycle). The diurnal cycle of cloud-top and
-base heights over Niamey is also characterized by the
previously discussed relatively large occurrences of thin
cloud layers with cloud-base heights ranging from 5 to
7 km and cloud-top heights around 7–8 km, a feature
which is not found as clearly over Darwin.

The TPDF of cloud thickness over Darwin (Figure 6(c)) shows a slight diurnal cycle signature in phase with the diurnal cycle of cloud occurrence and convection depicted in Figure 2, with slightly lower occurrences of thicker ice clouds (or larger occurrence of thinner clouds) when the convective activity and ice cloud occurrence are smallest (from 0700 to 1500). The TPDF of cloud thickness over Niamey (Figure 6(f)) seems to be in phase with the convective activity as well, with a slight broadening of the PDFs when convective activity is largest (from 1000 to 1500 local time,). It is interesting to note that most ice clouds over Niamey are less than 3 km thick, which probably reflects again the much larger proportion of cirrus clouds, while the PDF over Darwin is much broader, probably indicating that deep anvils are predominant over Darwin.

4. The microphysical and radiative properties of tropical ice clouds over Darwin and Niamey

As discussed in section 2, the microphysical and radiative
properties of ice clouds analysed in this paper have
been derived using the variational radar–lidar technique
of DH08 and the fall speed and in-cloud vertical air
velocity using the Doppler cloud radar technique RadOn
(Delanoë et al., 2007). The main advantage of the DH08
technique is that it allows the radar-only, radar–lidar and
lidar-only cloud samples to be included in our statistics.
Ice water content estimates from a simple statistical
radar-temperature relationship (Protat et al., 2007) will
also be shown for sake of comparisons with the DH08
results and as a second estimate of differences in IWC
statistics between Darwin and Niamey. PDFs, mean
vertical profiles, HPDFs and TPDFs have all been derived
from the ground-based radar–lidar observations.
<figure><img src="image_8.png" /><figcaption>Figure 6. TPDF of the morphological properties of ice clouds. Left column: (a) cloud-top height, (b) cloud-base height (middle panel), and (c) cloud thickness over Darwin. Right column: (d) cloud-top height, (e) cloud-base height (middle panel), and (f) cloud thickness over Niamey.</figcaption></figure>

## 4.1. PDFs

The PDFs of radar reflectivity, terminal fall speed of ice particles, IWC, visible extinction, effective radius, and ice particle concentration are first shown in Figure 7. The first striking result is that although there are clear similarities, the frequency distributions of all these quantities are significantly different between Darwin and Niamey. The frequency distributions of radar reflectivity are both strongly skewed towards smaller values, and exhibit a similar peak value of around −25 dBZ (Figure 7(a)). The shape, width and peak values of the Niamey PDF are in very good agreement with the reflectivity PDFs documented by Mace *et al.* (2006a) over Manus and Nauru. The reflectivity distribution over Darwin is slightly broader, owing to a larger occurrence of reflectivity values ranging from −10 to 5 dBZ at Darwin (or

slightly larger occurrences of reflectivities ranging from −30 to −15 dBZ over Niamey). The PDFs of terminal fall speed are characterized by the same overall distribution shape over Darwin and Niamey (Figure 7(b)), but the ice particle fall-speed distribution is shifted towards smaller values over Niamey. The fall speed PDF peaks at 35 cm s⁻¹ over Niamey and 55 cm s⁻¹ over Darwin. IWC and visible extinction distributions are globally broader over Niamey than over Darwin (Figure 7(c) and (d), respectively), and the extinction PDF seems to be slightly shifted towards larger values over Niamey (Figure 7(d)). The effective radius PDF shows features broadly similar to the reflectivity PDF, with a broader distribution at Darwin (Figure 7(e)), characterised by larger occurrences of smaller particles (radii ranging from 20 to 40 µm) and larger particles (larger than 80 µm). The concentration PDF is also broader at Darwin (Figure 7(f)), owing
<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

<figure><img src="image_15.png" /><figcaption>Figure 7. PDF of the microphysical and radiative properties of ice clouds: (a) radar reflectivity (in dBZ), (b) terminal fall speed (in m s⁻¹), (c) ice water content (in g m⁻³), (d) visible extinction (in km⁻¹), (e) effective radius (in µm), (f) concentration (in L⁻¹), and (g) in-cloud vertical air velocity (in m s⁻¹) over Darwin with the radar degraded to the sensitivity of the Niamey radar (solid blue), over Darwin at full sensitivity (dashed blue), and over Niamey (solid red).</figcaption></figure>

mostly to larger occurrences of concentrations smaller than 20–25 L⁻¹ over Darwin. Nevertheless the peak concentration is about the same over Darwin and Niamey, at about 100 L⁻¹. The in-cloud vertical air velocity PDF at both sites is slightly skewed towards descending motions, but peaking at 0 m s⁻¹ (Figure 7(g)).

## 4.2. Mean vertical profiles

In order to better characterize these differences in microphysical properties and at which heights these differences

occur, we now analyse the mean vertical profiles of the same quantities, as shown in Figure 8. This characterization of the vertical variability of the bulk microphysical properties offers a statistical view of these microphysical properties of tropical non-precipitating ice clouds and anvils, rather than individual views of case-studies conducted in the past using mostly *in situ* microphysical instrumentation (e.g. McFarquhar and Heymsfield, 1996; Stith *et al.*, 2002; McFarquhar *et al.*, 2003). The use of the variational radar–lidar technique of DH08 ensures that most ice clouds in the troposphere are included in our
<figure><img src="image_16.png" /></figure>

<figure><img src="image_17.png" /></figure>

<figure><img src="image_18.png" /></figure>

<figure><img src="image_19.png" /></figure>

<figure><img src="image_20.png" /></figure>

<figure><img src="image_21.png" /></figure>

<figure><img src="image_22.png" /><figcaption>Figure 8. Mean vertical profiles of the microphysical and radiative properties of ice clouds: (a) radar reflectivity (in dBZ), (b) terminal fall speed (in m s⁻¹), (c) in-cloud vertical air velocity (in m s⁻¹), (d) ice water content (in g m⁻³), (e) visible extinction (in km⁻¹), (f) concentration (in L⁻¹), and (g) effective radius (in µm) over Darwin with the radar degraded to the sensitivity of the Niamey radar (solid blue), over Darwin at full sensitivity (dashed blue), and over Niamey (solid red). Also displayed as dotted lines in (d) are the vertical profiles of ice water content derived from the IWC–Z–T method of Protat *et al.* (2007).</figcaption></figure>

statistics, which may provide new insights into ice cloud processes and their relative importance as a function of height.

The first important result is obviously the very large vertical variability of all the microphysical and radiative properties, spanning several orders of magnitude for some of them. The mean vertical profiles of reflectivity (Figure 8(a)) are characterized by a well-defined peak at 8 km height (–10 dBZ over Darwin and Niamey) and there is some indication of a secondary maximum at 14 km over Niamey, but this is probably not significant because it is derived from a much smaller number of data points. The same overall vertical variation is found for the terminal fall speed, IWC, and extinction (Figure 8(b), (d) and (e), respectively). The vertical profiles of IWC retrieved using the DH08 technique and the Protat *et al.* (2007) IWC–Z–T relationships agree reasonably well, the IWC–Z–T technique producing slightly larger

ice water contents though (Figure 8(d)), which gives good confidence in the interpretation of the results and of the differences between the two sites. The ice particle concentration profiles show a large decrease by 2.5 orders of magnitude in concentration from 14 km height down to the melting layer (Figure 8(f)). Three distinct mean slopes in concentration are clearly observed over Niamey (less obvious over Darwin), with a steep slope between 14 and 12 km height, then a smaller slope from 12 to 7 km height, and again a very large slope in the lower part of the ice clouds, probably corresponding to different balances of the microphysical growth processes. The in-cloud vertical air velocity (Figure 8(c)) is also an important quantity, because it is expected to play a major role in ice particle sorting in updraught areas. This mean vertical profile is characterized by upward motions above 10–11 km over both sites with similar magnitudes, peaking at 14 km to a value of 20–25 cm s⁻¹, and downward motions below
11 km altitude which are found to be larger at Darwin than at Niamey.

In terms of microphysical processes, it appears clearly that the mean vertical profiles can be split into two main regions from cloud top down (that is, for increasing temperatures), which are characterized by a very different behaviour: region 1 between 14 km and 8 km, and region 2 from 8 km down to the melting layer. In region 1, reflectivity, fall speed, IWC, visible extinction (to a lesser extent), and particle size tend to increase from top down, while the particle concentration decreases significantly. The fact that extinction increases less than reflectivity and ice water content is due to the much larger impact of an increase in particle size on reflectivity and IWC as compared to extinction, which is more sensitive to the balance between increasing size and decreasing concentration. It is to be noted again that the opposite trends observed above 13 km height are probably unreliable because of the small number of points. The region 1 is characterized by a mean in-cloud upward air motion, which is a favourable condition for particle growth and will act to sort out the small and larger particles in such a way that the smaller particles will remain in the upper part of the ice clouds and grow by deposition of water vapour, while the larger particles (those which have a fall speed larger than the vertical air motion) will fall and start aggregating with other particles. The decrease in concentration and increase in particle size suggests that aggregation is the dominant mechanism in this region 1. Also, as discussed in McFarquhar *et al.* (2003) the rate of decrease of concentration is larger than the rate of decrease in ice water content in this region, which is indicative of a quicker removal of the smaller particles due to aggregation. In region 2, below the 8 km peak, all the microphysical parameters tend to decrease from 8 km down to the melting layer (except the effective radius over Niamey which increases), which is likely due to the increasing importance of sublimation at the ice cloud bases with respect to aggregation. This does not necessarily mean that sublimation is the dominant mechanism in the first 3 km above cloud base for each individual cloud, because what we have here merely reflects the relative importance of microphysical processes in a statistical sense, combining all types of clouds with all possible cloud heights, bases and thicknesses. The investigation of individual clouds shows a different organization, with a predominance of aggregation from a few hundred metres below cloud top down to a few hundred metres above cloud base, and large sublimation taking place within a relatively thin layer of a few hundred metres only above cloud base.

The mean vertical profiles show that the IWCs, visible extinctions and particle concentrations are significantly smaller at all heights over Darwin compared to Niamey, while the terminal fall speeds and effective radii are larger over Darwin compared to Niamey. These differences in microphysical properties imply that ice clouds over Niamey consist of slightly smaller-sized particles but in much larger concentrations, thereby carrying more ice water and producing more visible extinction than the ice clouds over Darwin. It is also noteworthy that the mean

reflectivity profiles are almost identical over both sites, although this agreement is somewhat fortuitous, because it results from a balance of very large differences in concentration and moderate difference (with a different sign) in particle size.

### 4.3. Height-dependent PDFs

In order to gain further insights into the differences in microphysical properties between Darwin and Niamey derived from the PDF and the mean vertical profiles, the HPDFs of IWC, effective radius, concentration, and vertical velocity, as well as the difference between the HPDFs over Darwin and Niamey, are given in Figure 9. The HPDF of visible extinction is not displayed here because it exhibits the same features as the HPDF of IWC. The smaller mean IWCs observed over Darwin (see the vertical profiles of Figure 8(d)) clearly result from a much larger occurrence of IWCs less than $10^{-3.5} \text{ g m}^{-3}$ (Figure 9(c)) and of intermediate IWCs (around $10^{-2} \text{ g m}^{-3}$) over Darwin, and from a much larger occurrence of the largest (from $10^{-1}$ to $3-4 \text{ g m}^{-3}$) IWCs over Niamey. The concentration HPDF differences (Figure 9(i)) show that the larger concentrations of ice particles observed on the vertical profiles of concentration over Niamey in Figure 8(f) are essentially due to a much larger occurrence of large concentration of ice particles over Niamey (larger than $100 \text{ L}^{-1}$) between 5 and 10 km height, and a much larger occurrence of small to intermediate concentration of ice particles over Darwin from 7 to 13–14 km height. The effective radius HPDFs (Figure 9(d) and (e)) show a very different behaviour, with the evidence of a much broader distribution of effective radii over Niamey below 7–8 km height, corresponding to the larger mean effective radii in the vertical profile of Figure 8(g), and conversely a broader, positively skewed distribution of effective radii over Darwin above 8 km height, resulting in larger effective radii at these heights over Darwin in Figure 8(g). The difference field of vertical velocity HPDF also gives some interesting insights into the in-cloud dynamics differences (Figure 9(l)), which was not apparent on the vertical velocity PDF (Figure 7(g)) because the main differences are located in the tail of the distributions. From this figure it appears that Darwin is characterized by a much larger occurrence of upward motions larger than $2 \text{ m s}^{-1}$ and downward motions from -4 to -1 m s⁻¹. The cumulative effect of larger fall velocities and larger occurrences of downdraughts is interesting, because it suggests that the life cycle of ice clouds over Darwin is probably shorter than that over Niamey. However, this result might not appear as fully consistent with the much larger frequencies of cloud occurrence found over Darwin in Figure 1, but in fact it likely reflects the fact that the production of ice clouds locally by deep convection is much smaller over Niamey, as discussed previously and clearly seen in Figures 2 and 3. With these two hints, we postulate that ice clouds over Niamey are less frequent than over Darwin because they are much further from their primary deep convective sources (primarily the Jos
<figure><img src="image_23.png" /><figcaption>Figure 9. HPDF of selected ice cloud properties over Darwin (left column), Niamey (middle column), and their difference in % (right column): (a), (b), (c) ice water content (in gm⁻³), (d), (e), (f) effective radius (in µm), (g), (h), (i) concentration (in L⁻¹), and (j), (k), (l) in-cloud vertical air velocity (in m s⁻¹).</figcaption></figure>

Plateau) but probably have a longer lifetime than the ice clouds over Darwin. This is also consistent with the weak diurnal variability of the frequency of ice cloud occurrence over Niamey (Figure 3), which implies long-lived cirrus beyond the time-scale of a day, which is very different from what is observed over Darwin. It will be quite interesting to see which balance these two

characteristics (lifetime versus occurrence) produce in terms of vertically resolved and net radiative impact, as was done in Mather *et al.* (2007) over Manus and Nauru, which is an objective of our future research. It will also be very interesting in future work to see if the large-scale models are able to reproduce such differences and the associated differences in radiative impact.
<figure><img src="image_24.png" /><figcaption>Figure 10. TPDF of selected ice cloud properties over Darwin: (a) ice water content (in g m⁻³), (b) visible extinction (in km⁻¹), (c) effective radius (in µm), and (d) concentration (in L⁻¹).</figcaption></figure>

4.4. Diurnal cycle of the microphysical and radiative properties

We now turn to a characterization of the diurnal cycle of the microphysical properties of ice clouds, using the TPDFs of IWC, extinction, effective radius and concentration. Over Darwin, the IWC and extinction TPDFs tend to be significantly broader during the period of smaller convective activity (from 0900 to 1800 local time) and skewed towards much larger values (Figure 10(a) and

(b)). In contrast, during the peak convective activity (early morning and late evening, Figure 2(b)), the distributions of IWC and extinction are much narrower and similar in the early morning and late evening, with peak values of about 5.10⁻³ g m⁻³ and 0.1–0.2 km⁻¹, respectively. This well-marked maximum in the diurnal cycle of IWC and extinction is associated with a slightly narrower PDF of particle effective radii during this period (Figure 10(c)), but mostly to a fairly large increase in particle concentration (Figure 10(d)). The diurnal cycle
of particle concentration provides additional insights into
the microphysical processes at the origin of this diur-
nal variability. In the early morning, the concentration
PDF is relatively broad, with the most probable val-
ues ranging from 10 to 100 L⁻¹. During the period of
increased IWCs and extinctions, the concentration peak
is much narrower and shifted towards much larger values
ranging from 100 to 400 L⁻¹, the largest concentrations
being found at around 1600 local time. Then from 1800
local time, the distribution gets much broader again with
most probable values similar to those of the early morn-
ing period. This diurnal cycle seems to be in very good
agreement with what we might expect in terms of the tim-
ing of the microphysical processes. During the convec-
tively active periods, significant amounts of water vapour
and liquid water are transported aloft by the convective
updraughts, triggering ice particle growth through con-
densation, water vapour deposition, and aggregation, and
therefore decreasing particle concentration and increasing
particle size. During the convectively suppressed periods,
the internal life cycle of the ice clouds prevails, with
aggregation and ice particle sorting producing thinner
long-lived cirrus clouds, composed of smaller particles
in large concentration. The large increase in concentra-
tion probably indicates that this convectively suppressed
period also corresponds to a period of large production of
ice crystals from the ice nuclei previously brought upward
by deep convection.

The diurnal cycle of the ice cloud microphysical prop-
erties over Niamey is, as also found for ice cloud occur-
rence and cloud morphology, much less marked than
over Darwin. Some slight signatures of diurnal vari-
ability can nevertheless be found on the TPDF of Fig-
ure 11. The IWC, extinction, and effective radius TPDFs
(Figure 11(a), (b) and (c), respectively) show similar
broadenings of the PDF at 0100, 0600, 1000–1200 and
1800–2000 local time, mostly corresponding to the pro-
duction of larger IWCs and extinctions. The effective
radius TPDF (Figure 11(c)) is bimodal at those time peri-
ods, with the production of effective radii in the range
70–80 µm. The largest broadening of the PDF occurs
from 1000 to 1200, when deep convective activity is
largest (Figure 3). The concentration TPDF does not
seem to have significant variations associated with these
specific time periods, but it is to be noted that the con-
centration PDF tends to get narrower at the time of larger
convective activity (from 0600 to 1800 local time). These
narrower distributions during this time period are mainly
the result of a reduction of the occurrence of large concen-
trations, especially from 1000 to 1400 local time (which
is consistent with the results over Darwin, although much
less marked).

**5. Conclusions and perspectives**

In the present paper, ground-based radar–lidar observa-
tions during a monsoon season over Darwin (northern
Australia) and over Niamey (West Africa) have been used

to characterize the statistical morphological, microphysi-
cal and radiative properties of tropical ice clouds, as well
as their vertical and diurnal variability. Comparing these
two sites is also interesting because they are both under
the large-scale influence of monsoon seasonal cycles and
ice clouds are mostly produced by deep convection in
both cases, while one site is clearly inland (Niamey) and
the other one is characteristic of a costal environment
(Darwin). The additional characterization of two other
tropical ARM sites in recent studies (Mace et al., 2006a;
Mather et al., 2007) – Manus, a large island surrounded
by other large islands, and Nauru, a very small island,
representative of ice clouds produced by oceanic deep
convection – also offers possibilities for further documen-
tation of the variability of the ice cloud properties along
the tropical belt, although satellite observations will in
the near future be used to get a better characterization of
this variability. The frequency of ice cloud occurrence is
particularly large over Darwin (23% of the time at 12 km
height) when compared to Niamey, Manus and Nauru
(from 9% to 11% at the same height), and with a much
larger diurnal variability, which is well correlated with the
diurnal cycle of deep convective activity. The frequency
of ice cloud occurrence is as large as 35% from 2000
to 2400 local time over Darwin. In contrast the diurnal
cycle of the ice cloud occurrence over Niamey is smaller
and not really correlated with that of deep convective
activity, as already noted and discussed previously for
the other cloud properties. The frequency distributions of
cloud fraction are strongly bimodal and broadly similar
over the two sites, with a predominance of clouds char-
acterized either by a very small cloud fraction (less than
0.3) or a very large cloud fraction (larger than 0.9). The
main differences between the two sites are for the ice
clouds above 12 km height which tend to have increased
occurrences of intermediate and large cloud fractions over
Darwin and for the ice clouds below 7 km height which
tend to have increased occurrences of large cloud frac-
tions over Niamey. This description of the cloud fraction
distributions will be very useful in the near future to eval-
uate the representation of ice clouds in large-scale models,
since cloud fraction is generally one of the two prog-
nostics variables held in most advanced prognostic cloud
schemes. The PDFs of cloud-top height, base height and
thickness have also been documented and discussed. In
terms of site difference, it appears clearly that the ice
clouds over Darwin are much thicker (by 1 km or more
statistically) and are characterized by a much larger diur-
nal variability than ice clouds over Niamey. We postulate
that this is due to the fact that unlike Darwin, Niamey is
far from the deep convective sources, which results in a
predominance in the Niamey statistics of high-level cir-
rus clouds generated by deep convection further east (and
primarily over the Jos Plateau) which are then advected
over Niamey by the Tropical Easterly Jet. There clearly
seems to be a more even distribution of cirrus clouds
and non-precipitating ice anvils in the Darwin statistics,
probably owing to the proximity to the deep convective
sources.
<figure><img src="image_25.png" /><figcaption>Figure 11. Same as Figure 10 but over Niamey.</figcaption></figure>

The bulk microphysical and radiative properties of these tropical ice clouds have also been retrieved and analysed in the present paper, providing further insights into potential differences between microphysical processes over Darwin and Niamey. Again, large differences have been obtained between the two sites, with ice clouds over Niamey being characterized by smaller particle sizes and fall speeds but in much larger concentrations, thereby carrying more ice water and producing more visible extinction than the ice clouds over Darwin.

It is also found that there is a much larger occurrence of downward in-cloud air motions less than 1 m s⁻¹ over Darwin, which together with the larger fall speeds retrieved over Darwin indicates that the life cycle of ice clouds is probably shorter over Darwin than over Niamey. The diurnal cycle of these microphysical properties also provides interesting insights into the microphysical processes at the origin of the diurnal variability. The diurnal cycle over Darwin is characterized by a large decrease in particle concentration and increase in particle size during
the convectively active periods of the diurnal cycle, while smaller particles in larger concentration are found during the convectively suppressed part of the diurnal cycle. This seems to be consistent with the ice formation by condensation and the upward transport of additional water vapour and liquid droplets in the convective updraughts during the convective phase, and with aggregation, particle sorting and nucleation of new ice from the ice nuclei brought upward by convection during the convectively suppressed period. The same signatures are found over Niamey, but with a much smaller magnitude, which again probably results from the predominance of high-level cirrus clouds in the statistics.

There are many avenues to expand this work. First, we will investigate in the near future using CloudSat (Stephens et al., 2002) and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations: Winker et al., 2007) the regional variability of the tropical ice cloud properties over West Africa and Australia (and more generally along the tropical belt), as well as the variability of these cloud properties as a function of the large-scale atmospheric state (e.g. Marchand et al., 2006) and the large-scale cloud regime as derived by Jakob and Tselioudis (2003) using these spaceborne observations. Sub-regional variabilities of the tropical ice cloud properties will also be investigated over West Africa, in order to compare with the variability of rainfall characteristics as documented over West Africa by Geerts and Dejene (2005). Finally, the variability of the ice cloud properties in response to the ENSO interannual variability and to the different MJO phases will be evaluated using more seasons of radar-lidar observations in northern Australia and possibly using CloudSat-CALIPSO.

We will also use the derived cloud properties as inputs to a radiative transfer code in order to characterize the heating rates and net radiative impact of those tropical ice clouds, in a manner similar to that done in the pioneer work of Mather et al. (2007). The use of spaceborne sensors could be a good way to extend this characterization to the whole Tropics. Finally, this characterization of the tropical ice cloud properties and their variability will be extensively used as an observational reference for the evaluation of the representation of these clouds in large-scale models and of the spaceborne microphysical products of the A-Train mission.

## Acknowledgements

This work has been partly supported by the US Department of Energy Atmospheric Radiation Measurement (ARM) program. The Niamey AMF and Darwin radar data were obtained from the ARM Program Archive. Based on a French initiative, AMMA was built by an international scientific group and is currently funded by a large number of agencies, especially from France, UK, US and Africa, and by an EU programme. Detailed information on scientific co-ordination and funding is available on the AMMA International web site http://www.amma-international.org. This work is dedicated to the memory

of our dear friend and colleague Vincent Giraud, who should have been using the work done here to evaluate his high-resolution numerical model simulations of West African convective systems.

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