Retrievals of ice microphysics using dual-wavelength polarimetric radar observations during stratiform precipitation events

Ice growth processes within clouds affect the type as well as the amount of precipitation. Hence, the importance of an accurate representation of ice microphysics in numerical weather and numerical climate models has been confirmed by several studies. To better constrain ice processes in models, we need to study ice cloud regions before and during monitored precipitation events. For this purpose, two radar instruments facing each other were used to collect complementary measurements. The C-band POLDIRAD weather radar from the German Aerospace Center (DLR), Oberpfaffenhofen and the Ka-band MIRA-35 cloud radar from the Ludwig Maximilians University of Munich (LMU) were used to monitor stratiform precipitation in the vertical cross-section area between both instruments. The logarithmic difference of radar reflectivities at two different wavelengths (54.5 and 8.5 mm), known as dual-wavelength ratio, was exploited to provide information about the size of the detected ice hydrometeors, taking advantage of the different scattering behavior in the Rayleigh and Mie regime. Along with the dual-wavelength ratio, differential radar reflectivity measurements from POLDIRAD provided information about the apparent shape of the detected ice hydrometeors. Scattering simulations using the T-matrix method were performed for oblate and horizontally aligned prolate ice spheroids of varying shape and size using a realistic particle size distribution and a well-established mass-size relationship. The combination of dual-wavelength ratio, radar reflectivity and differential radar reflectivity measurements as well as scattering simulations was used for the development of a novel retrieval for ice cloud microphysics. The development of the retrieval scheme also comprised a method to estimate the hydrometeor attenuation in both radar bands. To demonstrate this approach, a feasibility study was conducted on three stratiform snow events which were monitored over Munich in January 2019. The ice retrieval can obtain ice particle shape, size and mass which are in line with differential radar reflectivity, dual-wavelength ratio and radar reflectivity observations when a suitable mass-size relation is used and when ice hydrometeors are assumed to be represented by oblate ice spheroids. A furthermore finding was the importance of the differential radar reflectivity for the particle size retrieval directly above the MIRA-35 cloud radar. Especially for that observation geometry, the simultaneous slantwise observation from the polarimetric weather radar POLDIRAD could reduce ambiguities in retrieval of the ice particle size by constraining the ice particle shape.

Cirrus cloud thinning using a more physically-based ice microphysics scheme in the ECHAM-HAM GCM

Cirrus cloud thinning (CCT) is a relatively new radiation management proposal to counteract anthropogenic climate warming by targeting Earth’s terrestrial radiation balance. The efficacy of this method was presented in several general circulation model (GCM) studies that showed widely varied radiative responses, originating in part from the differences in the representation of cirrus ice microphysics between the different GCMs. The recent implementation of a new, more physically based ice microphysics scheme (Predicted Particle Properties, P3) that abandons ice hydrometeor size class separation into the ECHAM-HAM GCM, coupled to a new approach for calculating cloud fractions that increases the relative humidity (RH) thresholds for cirrus cloud formation, motivated a reassessment of CCT efficacy. In this study, we first compared CCT sensitivity between the new cloud fraction approach and the original ECHAM-HAM cloud fraction approach. With the P3 scheme and the higher RH thresholds for cirrus cloud formation, we find a significant cooling response of −0.36 Wm−2 only for our simulation with a seeding particle concentration of 1 L−1, due mostly to rapid cloud adjustments. The most notable response is the reduction of the maximum global-mean net top-of-atmosphere (TOA) radiative anomalies from overseeding by more than 50 %, from 9.0 Wm−2 with the original cloud fraction approach, down to 4.3 Wm−2 using the new cloud fraction RH thresholds by avoiding artificial ice-cloud expansion upon ice nucleation. We attribute the large positive TOA anomalies to seeding particles overtaking both homogeneous nucleation and heterogeneous nucleation on mineral dust particles within cirrus clouds to produce more numerous and smaller ice crystals. This effect is amplified by longer ice residence times in clouds due to the more realistic, slower removal of ice via sedimentation in the P3 scheme. In an effort to avoid this overtaking effect of seeding particles, we increased the default critical ice saturation ratio (Si,seed) for ice nucleation on seeding particles from the default value of 1.05 to 1.35 in a second sensitivity test. With the higher Si,seed we eliminate overseeding and are able to produce cooling responses over a broader range of seeding particle concentrations, with the largest cooling of −0.32 Wm−2 for a seeding particle concentration of 10 L−1, which suggests that Si,seed is a key factor to consider for future CCT studies. However, the global-mean TOA anomalies contain high uncertainty. In response, we examined the TOA responses regionally and found that specific regions only show a small potential for targeted CCT, which is partially enhanced by using the larger Si,seed. Finally, in a seasonal analysis of TOA responses to CCT, we find that our results do not support the previous finding that high-latitude wintertime seeding is a feasible strategy to enhance CCT efficacy, as seeding in our model enhances the already positive cirrus longwave cloud radiative effect. Instead, our results show that summertime cooling occurs due to adjustments of lower-lying mixed-phase and liquid clouds. Therefore, we conclude that CCT is unlikely to act as a feasible climate intervention strategy on a global scale, and should be investigated further with higher-resolution studies in potential target regions and with studies dedicated to assessing potentially realistic seeding particle materials.

Processes influencing lower stratospheric water vapour in monsoon anticyclones: insights from Lagrangian modelling

We investigate the influence of different chemical and physical processes on the water vapour distribution in the lower stratosphere (LS), in particular in the Asian and North American monsoon anticyclones (AMA and NAMA, respectively). Specifically, we use the chemistry transport model CLaMS to analyse the effects of large-scale temperatures, methane oxidation, ice microphysics, and small-scale atmospheric mixing processes in different model experiments. All these processes hydrate the LS and, particularly, the AMA. While ice microphysics has the largest global moistening impact, it is small-scale mixing which dominates the specific signature in the AMA in the model experiments. In particular, the small-scale mixing parameterization strongly contributes to the water vapour transport to this region and improves the simulation of the intra-seasonal variability, resulting in a better agreement with the Aura Microwave Limb Sounder (MLS) observations. Although none of our experiments reproduces the spatial pattern of the NAMA as seen in MLS observations, they all exhibit a realistic annual cycle and intra-seasonal variability, which are mainly controlled by large-scale temperatures. We further analyse the sensitivity of these results to the domain-filling trajectory set-up, here-called Lagrangian trajectory filling (LTF). Compared with MLS observations and with a multiyear reference simulation using the full-blown chemistry transport model version of CLaMS, we find that the LTF schemes result in a drier global LS and in a weaker water vapour signal over the monsoon regions, which is likely related to the specification of the lower boundary condition. Overall, our results emphasize the importance of subgrid-scale mixing and multiple transport pathways from the troposphere in representing water vapour in the AMA.

Advantages and limitations on combining radar dual - wavelength and polarimetric observations for ice microphysics retrievals

<p>The challenge of the ice microphysical processes representation in numerical weather models is a well-known phenomenon as it can lead to high uncertainty due to the variety of ice microphysics. As ice microphysical properties can strongly affect the initiation of precipitation as well as the type and amount of it, we need to better understand the complexity of ice processes. To accomplish this, better microphysics information through ice retrievals from measurements is needed. The multi-wavelength radar method is nowadays becoming more and more popular in such microphysics retrievals. Taking advantage of different scattering regimes (Rayleigh or Mie), information about the size of atmospheric hydrometeors can be inferred using different radar bands. For this study, dual-wavelength reflectivity ratio measurements were combined with polarimetric measurements to estimate the size of ice hydrometeors. The measurements were obtained by using the synergy of the C-band POLDIRAD weather radar from the German Aerospace Center, located in Oberpfaffenhofen, and the Ka-band MIRA-35 cloud radar from the Ludwig Maximilian University of Munich. Along with the dual-wavelength dataset, the Differential Reflectivity (Z<sub>DR</sub>) from POLDIRAD was used as a polarimetric contribution for the shape estimation of the detected ice particles. The radar observations were compared with T-matrix scattering simulations for the development of a retrieval scheme of ice microphysics. In the course of these studies, different assumptions were considered in the simulations. To capture the size variability, a Gamma particle size distribution (PSD) with different values of median volume diameter (MVD) was used. The soft spheroid approximation was used to approximate the ice particle shapes and to simplify the calculation and variation of their aspect ratios and effective densities. The selection of the most representative mass-size relation was the most crucial for the scattering simulations. In this study, we explored the modified Brown and Francis as well as the aggregates mass-size relation. After comparing the simulations to radar observations, we selected the better fitting one, i.e. aggregates, excluding the Brown and Francis as the simulated particles appeared to be too fluffy. Using the aggregates formulas, Look-Up tables (LUTs) for MVD, aspect ratio, and IWC were developed and used in the ice microphysics retrieval scheme. Here, we present preliminary microphysics retrievals of the median size, shape, and IWC of the detected hydrometeors combining the simulations in LUTs with the radar observations from different precipitation events over the Munich area.</p>

How much variability in upper tropospheric cloud-radiative heating can be attributed to ice microphysics?

<p>While large-domain simulations without convective parameterization are now computationally feasible, microphysics, particularly that of the ice phase, remains a persistent problem for high-resolution models. In 2.5-km equivalent resolution simulations with the ICON model, we find that switching between one- and two-moment ice microphysics can alter cloud top cooling by a factor of ten and in-cloud heating by a factor of four above 350 hPa. A consistent ice crystal effective radius between microphysics and radiation increases the cloud-radiative heating another two-fold, while inclusion of aerosol-cloud interactions reduces it at lower levels between 400 and 500 hPa. We also generate 60-hour trajectories from ICON within ice clouds and use them to force a detailed ice microphysics box model, the Chemical Lagrangian Model of the Stratosphere (ClaMs-ice). We compare the ice mass and number tendencies, as well as the sedimentation fluxes, between ICON and CLaMS-ice. These offline simulations also allow us to quantify the strength of microphysical-radiative feedbacks and investigate the impact on heating of particular ice microphysical factors, including gravity wave parameterization, ice-nucleating particle concentrations, and the number concentration of solution droplets.</p>

How does a Homogeneous Nucleation Event respond to changes of Parameterizations of Water Activity and Saturation Vapor Pressure?

<p>Homogeneous nucleation of ice crystals via freezing of small supercooled solution particles represents a major pathway in the formation of cirrus clouds with high ice water content at low temperatures. A reasonable physical explanation of this type of freezing is provided by Koop's nucleation theory, relating the homogeneous nucleation rate to the water activity of the solution particles. While the homogeneous nucleation rate encodes the probability of freezing of solution particles, the water activity represents the ratio of water vapor saturation pressures over the solution to that over pure water in Koop's portrayal.</p><p>By using the ice microphysics model "CLaMS-Ice", we investigate the effect of various formulations of the water activity and the water vapor saturation pressure on the resulting cirrus clouds. Although CLaMS-Ice is a two-moment bulk model, it implements a comparatively detailed ice microphysics formulated by Spichtinger and Gierens. Such a microphysics scheme is suitable to be implemented in full three dimensional atmospheric models in contrast to even more detailed bin microphysics schemes.</p><p>We performed sensitivity simulations over a wide range of temperatures and vertical velocities by using two different direct parameterizations of water activity based on thermodynamic models in addition to the one used by Koop. Also, three different formulations of the water vapor saturation pressure are applied in the simulations. The results are evaluated regarding the predicted number of ice crystals and the ice onset humidities. In particular, one major finding is that the freezing thresholds are increased compared to Koop's freezing lines.</p>

Linking rain into ice microphysics across the melting layer in stratiform rain: a closure study

This study investigates the link between rain and ice microphysics across the melting layer in stratiform rain systems using measurements from vertically pointing multi-frequency Doppler radars. A novel methodology to examine the variability of the precipitation rate and the mass-weighted melted diameter (Dm) across the melting region is proposed and applied to a 6 h long case study, observed during the TRIPEx-pol field campaign at the Jülich Observatory for Cloud Evolution Core Facility and covering a gamut of ice microphysical processes. The methodology is based on an optimal estimation (OE) retrieval of particle size distributions (PSDs) and dynamics (turbulence and vertical motions) from observed multi-frequency radar Doppler spectra applied both above and below the melting layer. First, the retrieval is applied in the rain region; based on a one-to-one conversion of raindrops into snowflakes, the retrieved drop size distributions (DSDs) are propagated upward to provide the mass-flux-preserving PSDs of snow. These ice PSDs are used to simulate radar reflectivities above the melting layer for different snow models and they are evaluated for a consistency with the actual radar measurements. Second, the OE snow retrieval where Doppler spectra are simulated based on different snow models, which consistently compute fall speeds and electromagnetic properties, is performed. The results corresponding to the best-matching models are then used to estimate snow fluxes and Dm, which are directly compared to the corresponding rain quantities. For the case study, the total accumulation of rain (2.30 mm) and the melted equivalent accumulation of snow (1.93 mm) show a 19 % difference. The analysis suggests that the mass flux through the melting zone is well preserved except the periods of intense riming where the precipitation rates were higher in rain than in the ice above. This is potentially due to additional condensation within the melting zone in correspondence to high relative humidity and collision and coalescence with the cloud droplets whose occurrence is ubiquitous with riming. It is shown that the mean mass-weighted diameter of ice is strongly related to the characteristic size of the underlying rain except the period of extreme aggregation where breakup of melting snowflakes significantly reduces Dm. The proposed methodology can be applied to long-term observations to advance our knowledge of the processes occurring across the melting region; this can then be used to improve assumptions underpinning spaceborne radar precipitation retrievals.