Evaluation of radar reflectivity factor simulations of ice crystal populations from in situ observations for the retrieval of condensed water content in tropical mesoscale convective systems

Abstract

Abstract. This study presents the evaluation of a technique to estimate cloud condensed water content (CWC) in tropical convection from airborne cloud radar reflectivity factors at 94 GHz and in situ measurements of particle size distributions (PSDs) and aspect ratios of ice crystal populations. The approach is to calculate from each 5 s mean PSD and flight-level reflectivity the variability of all possible solutions of m(D) relationships fulfilling the condition that the simulated radar reflectivity factor (T-matrix method) matches the measured radar reflectivity factor. For the reflectivity simulations, ice crystals were approximated as oblate spheroids, without using a priori assumptions on the mass-size relationship of ice crystals. The CWC calculations demonstrate that individual CWC values are in the range ±32 % of the retrieved average CWC value over all CWC solutions for the chosen 5 s time intervals. In addition, during the airborne field campaign performed out of Darwin in 2014, as part of the international High Altitude Ice Crystals/High Ice Water Content (HAIC/HIWC) projects, CWCs were measured independently with the new IKP-2 (isokinetic evaporator probe) instrument along with simultaneous particle imagery and radar reflectivity. Retrieved CWCs from the T-matrix radar reflectivity simulations are on average 16 % higher than the direct CWC IKP measurements. The differences between the CWC IKP and averaged retrieved CWCs are found to be primarily a function of the total number concentration of ice crystals. Consequently, a correction term is applied (as a function of total number concentration) that significantly improves the retrieved CWC. After correction, the retrieved CWCs have a median relative error with respect to measured values of only −1 %. Uncertainties in the measurements of total concentration of hydrometeors are investigated in order to calculate their contribution to the relative error of calculated CWC with respect to measured CWC IKP . It is shown that an overestimation of the concentration by about +50 % increases the relative errors of retrieved CWCs by only +29 %, while possible shattering, which impacts only the concentration of small hydrometeors, increases the relative error by about +4 %. Moreover, all cloud events with encountered graupel particles were studied and compared to events without observed graupel particles. Overall, graupel particles seem to have the largest impact on high crystal number-concentration conditions and show relative errors in retrieved CWCs that are higher than for events without graupel particles.

Statistical analysis of ice microphysical properties in tropical mesoscale convective systems derived from cloud radar and in situ microphysical observations

“…Assuming that largest hydrometeors (max(D max )) can be considered a proxy for the aggregation process efficiency, the findings of this study reveal that aggregation process efficiency is higher for MCS over land than over islands and higher over islands close to large land masses than over islands in the middle of an ocean. It seems to confirm the results of Frey et al (2011) and Cetrone and Houze (2009).…”

“…MCS over Niamey also show larger max(D max ) in MCS reflectivity zones 2 to 4, illustrating that snow aggregates can reach larger sizes during the West African Monsoon than in other MCS locations. This confirms the conclusions of Frey et al (2011) and Cetrone and Houze (2009), who suggested that there are larger ice hydrometeors in MCS over continental regions than MCS over maritime regions.…”

Microphysical Processes Producing High Ice Water Contents (HIWCs) in Tropical Convective Clouds during the HAIC-HIWC Field Campaign: Evaluation of Simulations Using Bulk Microphysical Schemes

“…Several numerical simulation studies on tropical MCSs sampled during the HAIC-HIWC projects have been conducted using different numerical models and different microphysics schemes. Franklin et al (2016) showed that the Met Office Unified Model (UM) with a single-moment microphysics scheme overestimated the radar reflectivity above the freezing level due to the errors of simulated updraft dynamics and particle sizes, hypothesizing that a double-moment microphysics scheme would improve the model's representation of the observed variability of the ice particle size distribution (PSD). The Stanford et al (2017) WRF simulations of four tropical deep convection events sampled during the HAIC-HIWC Darwin campaign showed that three microphysics schemes (one bin and two double-moment bulk schemes; Lynn et al, 2005;Thompson et al, 2008;Morrison et al, 2009) produced larger MMDs for TWC > 1 g m −3 at temperatures between −10 and −40 • C and a high bias in convective radar reflectivity compared to observations.…”

Dependence of Mass–Dimensional Relationships on Median Mass Diameter

“…Retrievals of ice cloud properties, such as radar reflectivity factor (Z) [1], snow rate [2,3], ice water content (IWC) [3,4] and effective density (ρ e ) [5,6] require estimates of how ice particle mass (m) varies with ice particle dimension (D). Accurate estimates of particle mass are thus essential to the accuracy of cloud products retrieved from remote sensing measurements [7,8].…”

“…Atmosphere 2020, 11, 756 2 of 16 water accretion, and melting/refreezing that lead to variability in ice-air mixtures [12]. Therefore, empirical power law m-D relationships taking the form m = aD b (1) have been widely used in numerical modeling and retrieval schemes. Various techniques and probes have been used to derive the a and b coefficients, and variations with temperature, particle habit, and cloud formation mechanism have been noted [13].…”