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To better understand the dynamic and physical processes of mei-yu frontal rainfall, the IMFRE-I field campaign was conducted from 10 June to 10 July 2018 in the middle reaches of the YHRV, a region strongly affected by the East Asian summer monsoon. The experiment was organized by the Wuhan Institute of Heavy Rain (IHR), China Meteorological Administration, with primary support from the National Natural Science Foundation of China. The multiscale mei-yu frontal system is responsible for most of the heavy rainfall and flooding events in central China during the boreal warm season, yet observations are seriously lacking for a system of such tremendous scientific and societal importance. To address these critical needs and provide an observational basis for understanding, modeling and predicting the mei-yu frontal systems, the IMFRE-I field campaign was designed in order to lay out the foundation for integrative ground-, satellite-based and aircraft in-situ measurements and monitoring of the mei-yu frontal systems. This field campaign was the first attempt at collecting comprehensive datasets during the mei-yu period over the middle reaches of the YHRV in central China. No attempt has been made to provide an exhaustive climatological dataset of mei-yu frontal systems; rather, the emphasis of IMFRE-I was to provide synthetic datasets. Through an integrative analysis of comprehensive datasets and mesoscale modeling efforts, we can partially answer the posed scientific questions from IMFRE-I.
A special focus is placed upon the dynamic and thermodynamic structures of the mesoscale systems embedded in the mei-yu frontal system with their associated cloud properties and precipitation processes. The ground-based observations include those obtained from the IHR Mesoscale Heavy Rainfall Observing System (MHROS; Cui et al., 2015), regular soundings and surface meteorological variables, located at the Xianning surface site (Fig. 6). IHR-MHROS consists of mobile C-band and X-band polarimetric precipitation radars (C-POL and X-POL), millimeter wavelength cloud radars (MMCR), fixed S-band precipitation radars, micro rain radars (MRR), a GPS network, microwave radiometers (MWR), radiosonde soundings, wind profiler radars (WPR), and Parsivel and 2D video (2DVD) disdrometers. In addition to the Ka-band cloud radar, the Shanxi King-Air (KA350) aircraft participating in the campaign is equipped with the following sensors: a cloud droplet probe (CDP), cloud imaging probe (CIP), precipitation imaging probe (PIP), passive cavity aerosol spectrometer probe (PCASP), cloud condensation nuclei counter (CCN-200), and total water content/liquid water content sensors (TWC/LWC) (Yang et al., 2020), and flew ~25 hours during IMFRE-I, based at the Yichang airport (Fig. 6; ~300 km west of the Xianning site). Table 1 lists all ground-based instruments and aircraft probes, as well as their observational ranges and resolutions during IMFRE-I. Multiple satellite observations and retrievals were collected and processed, including data from the Global Precipitation Measurement Mission Dual-Frequency Precipitation Radar (GPM-DPR) and Integrated Multi-satellite Retrievals (IMERG), Chinese Fengyun and Japanese Himawari-8 (Cui et al., 2020b; Sun et al., 2020). Through building synthetic datasets and mesoscale modeling analysis during IMFRE, we aim to answer the following questions:
Location Instruments Observed variables Range Resolution Ground-based C-band Polarimetric radar Z, V, W, ZDR, ΦDP, ρHV 150 km 150 m and 6 min Microwave radiometer Cloud LWP and PWV 10 km 50–200 m and 2 min Millimeter cloud radar Z, V, W, LDR 30 km 10 m and 5 s Micro rain radar Profiles of raindrop spectrum, terminal velocity, intensity 3 km 100 m and 1 min 2D video disdrometer Raindrop spectrum, falling speed, shape, rain intensity − 1 min Tropospheric wind profiler radar Horizontal wind speed and direction, vertical wind velocity, $C_n^2$ profile 0–16 km 120–480 m Laser ceilometer Cloud base height 0~15 km − Airborne Cloud droplet probe Droplet spectrum 2–50 μm 40 bins and 1 s Cloud imaging probe Droplet spectrum 12.5 μm–1.55 mm 25 μm and 1 s Precipitation imaging probe Particle spectrum 100 μm–6.2 mm 100 μm and 1s Passive cavity aerosol spectrometer probe Number concentration 0.1–3 μm 1 s Cloud condensation nuclei cou-nter Particle size, Number concentration 0.75–10 μm 1 s Total water content/liquid water content sensors Liquid water content 0–10 g m−3 1 s Note: that Z = reflectivity factor; V = Doppler radial velocity; W = Doppler spectrum width; ZDR = differential reflectivity; ΦDP = differential phase shift; ρHV = correlation coefficient; LDR = linear depolarization ratio; $C_n^2$ = structure constant of atmospheric refractive index; LWP = liquid water path; PWV = precipitable water vapor. Table 1. List of ground-based and airborne instruments used in IMFRE-I.
Figure 6. 3D structure of surface-site, satellite and aircraft observations during the IMFRE-I field campaign in June–July 2018 over Hubei Province, central China.
(1) Can we gain more insight into the raindrop formation and growth processes at different stages (developing, mature, dissipating) of the mei-yu stratiform and convective rain systems, the impacts of moisture sources on MCS formation, and cloud and precipitation microphysical properties?
(2) What are the dynamic and thermodynamic mechanisms driving the lifecycle characteristics of MCSs and the mei-yu frontal systems, as well as their associated cloud and precipitation properties?
(3) How can we evaluate the different microphysics schemes in the WRF model and find the best solution of quantitative precipitation forecasting for the middle reaches of the YHRV?
The unique feature of the IHR MHROS is to provide continuous, high temporal, spatial and vertical resolutions of observations from multiple sensors, particularly during the mei-yu seasons. Figure 7 shows a few photos during IMFRE-I and Figs. 8–19 illustrate the comprehensive observations from a suite of remote sensors of the IHR MHROS, as well as radar mosaic and satellite observations used during an event that occurred on 30 June 2018 during IMFRE-I as an example. The rainfall event on 30 June 2018 was the only severe thunderstorm observed at the Xianning site during IMFRE-I. This system (and water vapor) was advected from northwestern Hubei Province, initiated in the early morning over Hubei Province, developed before 1100 LST, then became mature from 1100 LST to 1600 LST, and finally dissipated (or moved out) after 1600 LST (Fig. 8).
Figure 7. (a) The Shanxi Aircraft crew with the IMFRE-I leadership team. (b) Waiting for permission to take off on 30 June 2018. (c) Filling the balloon. (d) Launching the balloon. (e) Weather forecasting. (f) Daily meeting regarding observational results. (g) Discussion meeting. (h) Troubleshooting the MRR.
Figure 8. (a–c) Himawari brightness temperatures at wavelength λ = 10.4 µm, ranging from T = −8°C (red) to 40°C (black); and (d–f) radar mosaic composite images at 0800 (a, d), 1200 (b, e) and 1600 (c, f) LST 30 June 2018. The triangle represents the Xianning surface site. Note that different grid boxes are used for satellite and radar images.
Figure 9. Observations from three radars during IMFRE-Ⅰ, including the (a) S-band precipitation radar, (b) 35-GHz cloud radar, and (c) 24-GHz MRR. (d) Rain rates from the Parsival disdrometer (DSD), 2D video disdrometer (2DVD), and tipping bucket gauge. (e) Retrieval products from the S-band precipitation radar (VIL: vertically integrated liquid water content; VILD: vertically integrated liquid water content density; CRH: composite reflectivity height; ET: echo top height; CR: composite reflectivity) as part of the Institute of Heavy Rain (IHR) Mesoscale Heavy Rainfall Observing System (MHROS) over the Xianning surface site on 30 June 2018.
Figure 10. Vertical distributions of atmospheric (a) temperature, (b) relative humidity, (c) water vapor density, and (d) LWC retrieved from the MWR as part of the Institute of Heavy Rain (IHR) Mesoscale Heavy Rainfall Observing System (MHROS) over the Xianning surface site on 30 June 2018. Horizontal bar indicates the rain condition during measurement, and the red bar and white bar are the period with and without rain, respectively.
Figure 11. GPS radiosonde observations at (a) 0800 LST 30 June, (b) 1400 LST 30 June, (c) 0800 LST 17 June, and (d) 1400 LST 18 June 2018. The profiles of temperature (blue) and dewpoint temperature (red) are displayed on the bottom x-axis, and the profile of mixing ratio (black) is presented on the top x-axis.
Figure 12. Vertical distributions of rain DSDs for the classified rain of (a) light rain (LR), (b) stratiform rain (SR), and (c) convective rain (CR) during IMFRE-1 [reproduced and modified from Zhou et al. (2020)].
Figure 13. (a, e, i) Spatial distributions of column maximum reflectivities measured by the GPM-DPR instrument for the three selected cases during IMFRE-1. (b–d, f–h, j–l) The corresponding brightness temperatures observed by FY-2G/FY-2E satellites from one hour before to one hour after the occurrence (within ±1 h) of precipitation in the (a–d) developing stage, (e–h) mature stage, and (i–l) dissipating stage. The diagonal lines represent the edges of the DPR swaths [reproduced from Sun et al. (2020)].
Figure 14. Three stages of median lgNw (a–b) and Dm (c–d) profiles (thick lines) for (a, c) stratiform and (b, d) convective rain of the mei-yu precipitation systems derived from the GPM 2ADPR product during the period 2016–18. Shaded areas show the interquartile range [reproduced from Sun et al. (2020)].
Figure 15. Histograms of
$ {D}_{\rm m} $ and lgNw for (a, d) all samples (106 544), (b, e) CR (6021), and (c, f) SR (31 876) during the 2016–18 mei-yu seasons, with mean values, standard deviations (STD), and skewnesses (SK) [reproduced from Fu et al. (2020)].Figure 16. (a) Ka-band (35.64 GHz) cloud radar reflectivity onboard the KingAir aircraft on 19 June 2018 during IMFRE-I. The flight track was from 1521:09 LST to 1525:14 LST and labeled every 49 seconds on the time axis. (b) Cloud and drizzle particle size distributions at top (blue), center (red) and bottom (black) of the cloud layer observed by the merged product from CDP (2–50 µm), CIP (25–1550 µm) and PIP (100–6200 µm), respectively.
Figure 17. Composite images of the (a) range height indicator (RHI) of IHR C-POL radar reflectivity and (b) hydrometeor categories, with (c) showing enlarged hydrometeor categories in the area of the red dashed oval in (b). The radar RHI scanning azimuth is 350° at 1729 LST on 24 June 2018 (case 2). (d) Aircraft PIP images sampled every five seconds starting from 1739 LST.
Figure 18. Scatterplots of radar reflectivity (Z) and CR RR (gray crosses). The fitted power-law Z–R relationship for CR is shown by the black line. The red solid line represents the classic Z–R relationship derived from NEXRAD (Fulton et al., 1998), and the dark-green dashed line and double dot-dashed line represent the Z–R relationships derived from the results over Chuzhou and Nanjing. The purple solid line and light-green dotted line represent the Z–R relationship by the Sequential Intensity Filtering Technique (SIFT) and the least-squares method for all samples (CR, SR, mixed rain), respectively. The inset plot represents the amplified black rectangular region in the upper-right corner [reproduced from Fu et al. (2020)].
Figure 19. Vertical profiles of the (a) coefficients and (b) exponents in the Z–R relationships (
$ Z=a{R}^{b}) $ for classified LR, SR, and CR categories [reproduced from Zhou et al. (2020)].The vertical distributions of the system were observed by precipitation radar (reconstructed S-band radar reflectivity over the Xianning site), MMCR and MRR, as well as the surface rainfall amount at the Xianning site. The S-band radar reflectivity (Fig. 9a) and radar mosaic (Figs. 8d–f) illustrate that the radar reflectivity became greater and greater from early morning to noon, and the system started to dissipate after 1700 LST over the Xianning site. The cloud radar was not turned on before noon due to a severe thunderstorm and lightning, and the cloud and precipitation properties below 3 km were derived by MRR with a 100-m vertical resolution, a great addition to the S-band and cloud radar observations. The much higher MRR reflectivity measurements near the surface during the period 0900–1200 LST in Fig. 9c correlate well with the surface rainfall measurements (Fig. 9d). The KA350 aircraft was not allowed to take off due to air control until 1700 LST, and flew over the Xianning site at around 1830 LST. The vertical distributions of atmospheric temperature, relative humidity, water vapor density and LWC retrieved from the MWR over the Xianning site are shown in Fig. 10. The high water vapor density and LWC during the period 0900–1200 LST, although their vertical distributions need to be further validated, strongly correlate with the S-band and MRR reflectivity measurements. To provide more information, the profiles of atmospheric temperature, dewpoint temperature, and mixing ratio observed by GPS radiosonde soundings on 30 June (morning and afternoon) and 17 and 18 June are plotted in Fig. 11. Figures 8–11 demonstrate that it is crucial to have different remote sensors, including both active and passive, as well as surface rainfall and raindrop size distribution measurements, to observe the MCSs in order to have a complete horizontal and vertical distribution of the system due to their different sensitivities. These observations are needed to investigate the formation mechanisms and spatiotemporal evolutions of MCSs and mei-yu frontal systems.