Measurements of rainfall rate, drop size distribution, and variability at middle and higher latitudes: application to the combined DPR-GMI algorithm

The Global Precipitation Measurement mission is a major U.S.–Japan joint mission to understand the physics of the Earth’s global precipitation as a key component of its weather, climate, and hydrological systems. The core satellite carries a dual-precipitation radar and an advanced microwave imager which provide measurements to retrieve the drop size distribution (DSD) and rain rates using a Combined Radar-Radiometer Algorithm (CORRA). Our objective is to validate key assumptions and parameterizations in CORRA and enable improved estimation of precipitation products, especially in the middle-to-higher latitudes in both hemispheres. The DSD parameters and statistical relationships between DSD parameters and radar measurements are a central part of the rainfall retrieval algorithm, which is complicated by regimes where DSD measurements are abysmally sparse (over the open ocean). In view of this, we have assembled optical disdrometer datasets gathered by research vessels, ground stations, and aircrafts to simulate radar observables and validate the scattering lookup tables used in CORRA. The joint use of all DSD datasets spans a large range of drop concentrations and characteristic drop diameters. The scaling normalization of DSDs defines an intercept parameter NW, which normalizes the concentrations, and a scaling diameter Dm, which compresses or stretches the diameter coordinate axis. A major finding of this study is that a single relationship between NW and Dm, on average, unifies all datasets included, from stratocumulus to heavier rainfall regimes. A comparison with the NW–Dm relation used as a constraint in versions 6 and 7 of CORRA highlights the scope for improvement of rainfall retrievals for small drops (Dm lt; 1 mm) and large drops (Dm gt; 2 mm). The normalized specific attenuation–reflectivity relationships used in the combined algorithm are also found to match well the equivalent relationships derived using DSDs from the three datasets, suggesting that the currently assumed lookup tables are not a major source of uncertainty in the combined algorithm rainfall estimates

Triple frequency radar retrieval of microphysical properties of snow

An algorithm based on triple-frequency (X, Ka, W) radar measurements that retrieves the size, water content and degree of riming of ice clouds is presented. This study exploits the potential of multi-frequency radar measurements to provide information on bulk snow density that should underpin better estimates of the snow characteristic size and content within the radar volume. The algorithm is based on Bayes' rule with riming parameterised by the “fill-in” model. The radar reflectivities are simulated with a range of scattering models corresponding to realistic snowflake shapes. The algorithm is tested on multi-frequency radar data collected during the ESA-funded Radar Snow Experiment For Future Precipitation Mission. During this campaign, in situ microphysical probes were mounted on the same aeroplane as the radars. This nearly perfectly co-located dataset of the remote and in situ measurements gives an opportunity to derive a combined multi-instrument estimate of snow microphysical properties that is used for a rigorous validation of the radar retrieval. Results suggest that the triple-frequency retrieval performs well in estimating ice water content (IWC) and mean mass-weighted diameters obtaining root-mean-square errors of 0.13 and 0.15, respectively, for log 10IWC and log 10Dm. The retrieval of the degree of riming is more challenging, and only the algorithm that uses Doppler information obtains results that are highly correlated with the in situ data.</p

A Radar-Based Hail Climatology of Australia

In Australia, hailstorms present considerable public safety and economic risks, where they are considered the most damaging natural hazard in terms of annual insured losses. Despite these impacts, the current climatological distribution of hailfall across the continent is still comparatively poorly understood. This study aims to supplement previous national hail climatologies, such as those based on environmental proxies or satellite radiometer data, with more direct radar-based hail observations. The heterogeneous and incomplete nature of the Australian radar network complicates this task and prompts the introduction of some novel methodological elements. We introduce an empirical correction technique to account for hail reflectivity biases at C-band, derived by comparing overlapping C- and S-band observations. Furthermore, we demonstrate how object-based hail swath analysis may be used to produce resolution-invariant hail frequencies, and describe an interpolation method used to create a spatially continuous hail climatology. The Maximum Estimated Size of Hail (MESH) parameter is then applied to a mixture of over fifty operational radars in the Australian radar archive, resulting in the first nationwide, radar-based hail climatology. The spatiotemporal distribution of hailstorms is examined, including their physical characteristics, seasonal and diurnal frequency, and regional variations of such properties across the continent.Comment: Revision 1 of manuscript submitted to Monthly Weather Revie

On the observation of unusual high concentration of small chain-like aggregate ice crystals and large ice water contents near the top of a deep convective cloud during the CIRCLE-2 experiment

During the CIRCLE-2 experiment carried out over Western Europe in May 2007, combined in situ and remote sensing observations allowed to describe microphysical and optical properties near-top of an overshooting convective cloud (11 080 m/−58 °C). The airborne measurements were performed with the DLR Falcon aircraft specially equipped with a unique set of instruments for the extensive in situ cloud measurements of microphysical and optical properties (Polar Nephelometer, FSSP-300, Cloud Particle Imager and PMS 2-D-C) and nadir looking remote sensing observations (DLR WALES Lidar). Quasi-simultaneous space observations from MSG/SEVIRI, CALIPSO/CALIOP-WFC-IIR and CloudSat/CPR combined with airborne RASTA radar reflectivity from the French Falcon aircraft flying above the DLR Falcon depict very well convective cells which overshoot by up to 600 m the tropopause level. Unusual high values of the concentration of small ice particles, extinction, ice water content (up to 70 cm&lt;sup&gt;−3&lt;/sup&gt;, 30 km&lt;sup&gt;−1&lt;/sup&gt; and 0.5 g m&lt;sup&gt;−3&lt;/sup&gt;, respectively) are experienced. The mean effective diameter and the maximum particle size are 43 μm and about 300 μm, respectively. This very dense cloud causes a strong attenuation of the WALES and CALIOP lidar returns. The SEVIRI retrieved parameters confirm the occurrence of small ice crystals at the top of the convective cell. Smooth and featureless phase functions with asymmetry factors of 0.776 indicate fairly uniform optical properties. Due to small ice crystals the power-law relationship between ice water content (IWC) and radar reflectivity appears to be very different from those usually found in cirrus and anvil clouds. For a given equivalent reflectivity factor, IWCs are significantly larger for the overshooting cell than for the cirrus. Assuming the same prevalent microphysical properties over the depth of the overshooting cell, RASTA reflectivity profiles scaled into ice water content show that retrieved IWC up to 1 g m&lt;sup&gt;−3&lt;/sup&gt; may be observed near the cloud top. Extrapolating the relationship for stronger convective clouds with similar ice particles, IWC up to 5 g m&lt;sup&gt;−3&lt;/sup&gt; could be experienced with reflectivity factors no larger than about 20 dBZ. This means that for similar situations, indication of rather weak radar echo does not necessarily warn the occurrence of high ice water content carried by small ice crystals. All along the cloud penetration the shape of the ice crystals is dominated by chain-like aggregates of frozen droplets. Our results confirm previous observations that the chains of ice crystals are found in a continental deep convective systems which are known generally to generate intense electric fields causing efficient ice particle aggregation processes. Vigorous updrafts could lift supercooled droplets which are frozen extremely rapidly by homogeneous nucleation near the −37 °C level, producing therefore high concentrations of very small ice particles at upper altitudes. They are sufficient to deplete the water vapour and suppress further nucleation as confirmed by humidity measurements. These observations address scientific issues related to the microphysical properties and structure of deep convective clouds and confirm that particles smaller than 50 μm may control the radiative properties in convective-related clouds. These unusual observations may also provide some possible insights regarding engineering issues related to the failure of jet engines commonly used on commercial aircraft during flights through areas of high ice water content. However, large uncertainties of the measured and derived parameters limit our observations

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

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 CWCIKP measurements. The differences between the CWCIKP 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 CWCIKP. 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

The variability of tropical ice cloud properties as a function of the large-scale context from ground-based radar-lidar observations over Darwin, Australia

The high complexity of cloud parameterizations now held in models puts more pressure on observational studies to provide useful means to evaluate them. One approach to the problem put forth in the modelling community is to evaluate under what atmospheric conditions the parameterizations fail to simulate the cloud properties and under what conditions they do a good job. It is the ambition of this paper to characterize the variability of the statistical properties of tropical ice clouds in different tropical "regimes" recently identified in the literature to aid the development of better process-oriented parameterizations in models. For this purpose, the statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden-Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The vertical variability of ice cloud occurrence and microphysical properties is largest in all regimes (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98 % of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). In the ice part of the troposphere three distinct layers characterized by different statistically-dominant microphysical processes are identified. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is large, producing mean differences of up to a factor 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes and mean differences of a factor 2 typically in all microphysical properties. Finally, the diurnal cycle of the frequency of occurrence of ice clouds is also very different between regimes and MJO phases, with diurnal amplitudes of the vertically-integrated frequency of ice cloud occurrence ranging from as low as 0.2 (weak diurnal amplitude) to values in excess of 2.0 (very large diurnal amplitude). Modellers should now use these results to check if their model cloud parameterizations are capable of translating a given atmospheric forcing into the correct statistical ice cloud properties

A Comparison of Airborne In Situ Cloud Microphysical Measurement with Ground-Based C-Band Radar Observations in Deep Stratiform Regions of African Squall Lines

This study addresses clouds with significant ice water content (IWC) in the stratiform regions downwind of the convective cores of African squall lines in the framework of the French–Indian satellite Megha-Tropiques project, observed in August 2010 next to Niamey (13.5°N, 2°E) in the southwestern part of Niger. The objectives included comparing the IWC–Z reflectivity relationship for precipitation radars in deep stratiform anvils, collocating reflectivity observed from ground radar with the calculated reflectivity from in situ microphysics for all aircraft locations inside the radar range, and interpreting the role of large ice crystals in the reflectivity of centimeter radars through analysis of their microphysical characteristics as ice crystals larger than 5 mm frequently occurred. It was found that, in the range of 20–30 dBZ, IWC and C-band reflectivity are not really correlated. Cloud regions with high IWC caused by important crystal number concentrations can lead to the same reflectivity factor as cloud regions with low IWC formed by a few millimeter-sized ice crystals

Earth-system-model evaluation of cloud and precipitation occurrence for supercooled and warm clouds over the Southern Ocean's Macquarie Island

Over the remote Southern Ocean (SO), cloud feedbacks contribute substantially to Earth system model (ESM) radiative biases. The evolution of low Southern Ocean clouds (cloud-top heights &lt; ∼ 3 km) is strongly modulated by precipitation and/or evaporation, which act as the primary sink of cloud condensate. Constraining precipitation processes in ESMs requires robust observations suitable for process-level evaluations. A year-long subset (April 2016–March 2017) of ground-based profiling instrumentation deployed during the Macquarie Island Cloud and Radiation Experiment (MICRE) field campaign (54.5∘ S, 158.9∘ E) combines a 95 GHz (W-band) Doppler cloud radar, two lidar ceilometers, and balloon-borne soundings to quantify the occurrence frequency of precipitation from the liquid-phase cloud base. Liquid-based clouds at Macquarie Island precipitate ∼ 70 % of the time, with deeper and colder clouds precipitating more frequently and at a higher intensity compared to thinner and warmer clouds. Supercooled cloud layers precipitate more readily than layers with cloud-top temperatures &gt; 0 ∘C, regardless of the geometric thickness of the layer, and also evaporate more frequently. We further demonstrate an approach to employ these observational constraints for evaluation of a 9-year GISS-ModelE3 ESM simulation. Model output is processed through the Earth Model Column Collaboratory (EMC2) radar and lidar instrument simulator with the same instrument specifications as those deployed during MICRE, therefore accounting for instrument sensitivities and ensuring a coherent comparison. Relative to MICRE observations, the ESM produces a smaller cloud occurrence frequency, smaller precipitation occurrence frequency, and greater sub-cloud evaporation. The lower precipitation occurrence frequency by the ESM relative to MICRE contrasts with numerous studies that suggest a ubiquitous bias by ESMs to precipitate too frequently over the SO when compared with satellite-based observations, likely owing to sensitivity limitations of spaceborne instrumentation and different sampling methodologies for ground- versus space-based observations. Despite these deficiencies, the ESM reproduces the observed tendency for deeper and colder clouds to precipitate more frequently and at a higher intensity. The ESM also reproduces specific cloud regimes, including near-surface clouds that account for ∼ 25 % of liquid-based clouds during MICRE and optically thin, non-precipitating clouds that account for ∼ 27 % of clouds with bases higher than 250 m. We suggest that the demonstrated framework, which merges observations with appropriately constrained model output, is a valuable approach to evaluate processes responsible for cloud radiative feedbacks in ESMs.</p