Shibata and Naoe (2022)
Plain Language Summary: Analyses of Singapore radiosonde and reanalysis data from 1950s show that the quasi-biennial oscillation (QBO) in the equatorial stratosphere is decadally modulated in the amplitude as well as in the period. These two decadal variations are positively correlated with each other after 1980s, while they show approximately negative correlation before 1980s. The decadal amplitude variations of the QBO are not correlated with the solar cycle, but closely and positively correlated with the decadal components of Niño 3.4 sea surface temperature anomalies (SSTa), Pacific decadal oscillation (PDO) index, and North Pacific gyre oscillation (NPGO) index, suggesting that the tropical SSTa in the central Pacific substantially influences the QBO in the decadal time-scales.
- In the time series of the QBO amplitude from 1950s to 2014, there are four maxima (QBOmax) around 1967, 1983, 1995, and 2005, and three minima (QBOmin) around 1973, 1988, and 2000.
- Composite analyses of QBOmax and QBOmin based on these extrema reveal that the decadal amplitude variations have maximum amplitude of about 3 m s−1 at 20 hPa in the vertical.
- In the horizontal structure there appear off-equator extrema of about 3.5 m s−1 around 5ºN at 20 hPa, while at 50 hPa extrema of about 1.8 m s−1 are situated around 5ºS.
Notes and Correspondence: Special Edition on Global Precipitation Measurement (GPM): 5th Anniversary
Nakai et al. (2022)
Nakai, S., K. Yamashita, H. Motoyoshi, T. Kumakura, S. Murakami, and T. Katsushima, 2021: Relationships between radar reflectivity factor and liquid-equivalent snowfall rate derived by direct comparison of X-band radar and disdrometer observations in Niigata Prefecture, Japan. J. Meteor. Soc. Japan, 100,
Special Edition on Global Precipitation Measurement (GPM): 5th Anniversary,
https://doi.org/10.2151/jmsj.2022-002. Graphical Abstract
Plain Language Summary: The relationships between the radar reflectivity factor for horizontal polarization (Zh) at X-band and liquid-equivalent snowfall rate (R), of the form Zh = B R1.67, are presented for six hydrometeor classes of solid precipitation. Snow aggregates demonstrated a stronger or weaker backscattering than graupel of the same R depending on the riming degree and types of constituent ice crystals in the X-band.
- The average B value for the “heavily rimed snow aggregate” was smaller than that for the “rimed snow aggregate”.
- The largest B value was derived for a case of aggregates of unrimed dendritic particle (unrimed-D class). The case involving the aggregates of unrimed low-temperature-type crystals (unrimed-C class) showed the smallest B value.
- For graupel cases, the average B value was roughly twice that of the rimed and heavily rimed snow aggregate classes and much smaller than that of the unrimed-D class.
Chang et al. (2022)
Chang, Y., Q. Ma, L. Guo, J. Duan, J. Li, X. Zhang, X. Guo, X. Lou, and B. Chen, 2022: Characteristics of raindrop size distributions during Meiyu season in Mount Lushan, eastern China. J. Meteor. Soc. Japan, 100,
https://doi.org/10.2151/jmsj.2022-003. Graphical Abstract
Plain Language Summary: This paper aims to develop a graupel and hail identification algorithm for GPM DPR. This algorithm is constructed using a precipitation type index (PTI) defined for DPR. The PTI is effective in separating hydrometeor types and is calculated using measurements of reflectivity, dual-frequency ratio, and storm top height data. The output of the algorithm is a Boolean product representing the existence of graupel or hail along with the vertical profile for each Ku- and Ka-band matched footprint. Cross validation is performed with the Weather Service Radar (WSR-88D) network over continental United States as well as during the Remote sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) experiment. Evaluation of this identification algorithm is performed on a global basis, which illustrates promising comparisons with the global lightning and hail precipitation maps generated using radar and radiometer.
- Graupel and hail identification algorithm is developed for GPM DPR in this paper. The Boolean output is available at each Ku- and Ka- matched footprint.
- Successful ground validations have been performed in both continental United States and RELAMPAGO campaign in South America.
- Figure 1 illustrates the global distribution of “flagGraupelHail” count mapping to the 2° x 2° Lat / Lon box for year 2018. Promising comparisons are found between this product and the global lightning and hail precipitation maps.