GUIA PARA LA ATENCIÓN DEL PARTO NORMAL O EUTOCICO EVALUACIÓN PREPARTO

In situ field observations from airborne platforms such as aircraft, helicopters, drones, and balloons, provide a valuable opportunity to measure cloud microphysical properties in their natural setting. Clouds are typically far from the surface and are often transient in nature, and cloud properties vary widely over different portions of the globe due to thermodynamic and aerosol conditions. Airborne measurements are ideal for reaching cloud systems ranging from marine stratocumulus, to deep convection, to high-altitude cirrus. Instrumentation suitable for airborne deployment has advanced to a very sophisticated and specialized levels

and thorough reviews are available in the literature [313]. Airborne measurements typically provide much more detailed information than ground-based remote sensing, and in fact are necessary in assessing retrieval methods. Through airborne measurements, spatial variation of cloud microphysics, thermodynamic, and turbulent flow properties can be measured in cloud as well as properties of the air above and below cloud. The cloud sampling strategy using airborne instruments depends on the purpose of the study: for example, vertical profiles of cloud properties for cloud optical depth studies may require multiple up and down ‘porpoise dive’ patterns for the aircraft path. On the other hand, for cloud fraction or mesoscale cloud structure, a long, horizontal flight pattern may be required. Ever-present challenges of airborne measurements are the expense and complexity of operating an aircraft, and the high-speed nature of most measurement platforms. The emergence of un-crewed aerial vehicles (drones) for scientific purposes has the potential to significantly alter the type, frequency, duration, and range of in situ measurements available to the community [66].

Airborne instrumentation for measuring hydrometeor size distributions and moments (such as liquid water content) are mainly of the following categories: a) Hotwire b) Forward scattering c) Phase Doppler d) Shadowgraph e) Imaging f) Holographic. More detailed classifications of these instrumentations and descriptions of each type can be found in Baum- gardner et al. [14] and Brenguier et al. [33]. Table 1.1 lists some of the latest instruments with their specifications Baumgardner et al. [14].

Airborne Instruments for Cloud Particle Measurement Instrument Name Working Princi-

ple

Size Range Sampling Rate Hot-Wire Liquid Water Sensor (LWC-300) Resistance Change L: 0.05-3 g m−3 4 l s−1

CAS Forward Scatter-

ing

D: 0.5-50 µm 25 cm3 s−1 Fast-CDP Forward Scatter-

ing

D: 1.5-50 µm 25 cm3 s−1 Fast-FSSP Forward Scatter-

ing

D: 1.5-50 µm 40 cm3 s−1 Small Ice Detec-

tor (SID-2) Scattering D: 2-140 µm 100 cm3 s−1 Artium Flight PDI Doppler Effect D: 0.5-2500 µm ≈ 100 cm3 _s−1 2D-C Shadowgraph D: 25-800 µm 5 l s−1 2D-S Shadowgraph D: 10-1260 µm 8 l s−1 CIP Imaging D: 25-1550 µm 16 l s−1 CPI Imaging D > 3 µm 400 cm3 s−1 Holodec / Halo- Holo Holography D > 6 µm Instantaneous sample volume ≈ 20 cm3 Table 1.1

List of airborne instruments for measuring hydrometeor size distribution and moments. The volume sampling rates correspond to a flight speed of 100 m s−1.

The table is adapted from Baumgardner et al. [14].

phase. The SID-2, 2D-S, CIP, CPI and holographic instruments can be used for both liquid and ice phases. Hotwire instruments are based on the change in resistance of a hot wire junction due to the evaporation of droplets, and it provides an estimate of the liquid water content and therefore the third moment of the droplet size distribution. The second class of instruments operate by collecting light scattered by spherical droplets in the near-forward direction. They provide individual, drop-by-drop measurement of the diameter within a relatively small instrument cross section that is swept through the cloud the the aircraft. Examples of instruments in this category are the Forward Scattering Spectrometer Probe

forward scattering probes are based on the intensity of scattered light, care must be taken to maintain clean optics and regular calibration.

Phase-Doppler-Interferometry (PDI) is based on detection of phase difference rather than intensity, and thereby avoids some of the challenges of forward-scattering instruments. The phase difference between scattered Doppler bursts measured at two angles from a moving droplet is directly proportional to the diameter of that droplet. The coefficient of propor- tionality is a function of geometrical properties and wavelength of the source light. As with forward-scattering instruments, phase-Doppler instruments have a relatively small sample cross section that is swept through the cloud.

The other class of instruments provides volumetric or at least two-dimensional informa- tion about the particle distribution and size. The Shadowgraph system (e.g., 2D Stereo Probe, 2D-S) records the shadow of an illuminated particle in the focal plane of a detec- tor. Similarly, there are other imaging probes which capture two-dimensional images of particles illuminated by light sources (e.g., Cloud Particle Imager (CPI) and Cloud Imaging Probe (CIP)). Holographic instruments have the unique capability of capturing the three- dimensional information about particle position, as well as particle size. These instruments capture the interference pattern created between a reference wave and the light scattered from a dilute population of particles within the measurement volume. Reconstruction of the hologram is performed digitally in modern systems. These instruments provided de- tailed information on cloud microphysical properties, although, they have a limitation of high computation cost and lower time resolution.

Example: Cloud droplet size distribution moments. As discussed in the previous section, the shape of the cloud droplet size distribution is relevant to radiative properties of clouds. As an example of airborne measurement with a focus on assessing the shape of droplet size distributions in stratocumulus clouds, we refer to the extensive compilation of Miles et al. [210]. They show moments of the droplet size distribution at different altitude and for different aerosol concentrations. Among the other significant aspects, they reported that the cloud droplet distribution gets broader with height contrary to predictions from parcel models.

Microphysical properties of stratocumulus clouds, comparison to satellite-derived proper- ties. Glienke et al. [97], Witte et al. [319] have recently demonstrated the importance of measuring the full droplet size distribution, from cloud droplet to precipitation diameters, for calculating cloud radiative properties. By carefully measuring the full size distribution with phase-Doppler interferometry [319] and digital holography [97], it was shown that effective radius values retrieved from satellite measurements do now show the strong dis- crepancies previously indicated. Example size distributions from the CSET field project are shown in Figure 1.4. The three panels illustrate how the size distribution responds to different relevant powers of droplet diameter: the top shows a number distribution, the middle shows a surface area (d2) distribution, and the bottom shows a volume (d3) distribu- tion. The shaded region shows the range of droplet diameters that are in the ‘gap’ between cloud droplet and drizzle sizes, with the corresponding contributions to total number, sur- face area, and volume. Some of the most common aircraft instruments for measuring cloud droplet size distributions miss this gap region, and therefore miss significant contributions

Figure 1.4: Cloud droplet size distributions, weighted by number concentration, by surface area, and by volume. HOLODEC data span the gap between the CDP and 2DC measurement ranges. Intriguingly, no gap is observed between cloud droplet and drizzle sizes, as is typically expected from parcel model calculations. The shaded region indicates this ‘autoconversion gap’ and the numbers in that region indicate the number, surface area, and volume contributed by hydrometeors in this ‘drizzlet’ size range. The figure is from Glienke et al. [97].

to radiative properties.

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Example: Digital holographic measurements of cloud microphysics. The HOLODEC instrument has a novel sampling strategy based on digital in-line holography,

Figure 1.5: Mixing diagrams generated from HOLODEC data obtained in small, liquid-phase cumulus clouds. Each dot represents the mean-volume diameter and the cloud droplet concentration estimated from a single HOLODEC sample volume. The dashed curve represents homogeneous mixing, and the solid blue line represents extremely inhomogeneous mixing. The figure is from Beals et al. [16].

which provides an estimate of the cloud particle size distribution from a single sample vol- ume. This is in contrast to the typical approach of counting droplets one at a time along a thin line through the cloud. Each instantaneous sample volume is approximately 20 cm3_, repeated at 3.3 Hz; the time-averaged volume sampling rate is therefore comparable to other instruments (e.g., the CDP), but the local sampling approach means assumptions of spatial homogeneity and ergodicity required when averaging can be relaxed. The ‘local volume’ configuration allows for investigation of the influence of averaging and the variability of local-scale size distributions [16, 74]. The ability to look at three-dimensional locations of particles within the sample volume allows for the investigation of droplet clustering and particle breakup [90, 168].

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Data from HOLODEC has helped clarify whether entrainment and mixing leads to uni- form evaporation of all droplets (homogeneous mixing) or total evaporation of a subset of droplets (inhomogeneous mixing). This is relevant to determining microphysical properties at cloud boundaries and is therefore important for both drizzle formation and cloud radia- tive properties. For example, Figure 1.5 shows mixing diagrams acquired with HOLODEC data from liquid-phase cumulus clouds, and the scatter of points along a horizontal line are indicative of extremely inhomogeneous mixing [16]. Each point corresponds to a single hologram, so the spatial averaging that was previously identified as an ambiguity within mixing diagrams [38], was bypassed.