4-year Climatology of Global Drop Size Distribution and its Seasonal Variability Observed by Spaceborne Dual-frequency Precipitation Radar

Yamaji, Moeka; Takahashi, Hiroshi G.; Kubota, Takuji; Oki, Riko; Hamada, Atsushi; Takayabu, Yukari N.

doi:10.2151/jmsj.2020-038

Cited by 22 publications

(7 citation statements)

References 48 publications

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“…This number can be expressed as function of the kinetic energy of drops

N_{d} goodbreak= c {(\frac{1}{12} * ρ * π * D^{3} * v^{2})}^{- m},

where ρ is the density of water, D the diameter of drops and v the impact velocity. The parameters c 18 and m (4.63) are estimated from RET measurements. In a further step, the relation N / N d can be expressed in the same units as rain rate and inserted in Equation for the parameter R.d ( t ) to calculate di ( t ), using the measured rain rate for R ( t ).…”

Section: Methodsmentioning

confidence: 99%

“…Several investigations show that events with a high rain rate tend to have drops with a larger diameter, but still different DSD can lead to the same rain rate. Hence, it is difficult to go the reverse way from rain rate to DSD 18 . Therefore, using the approach from Best 13 introduces some uncertainty.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, it is difficult to go the reverse way from rain rate to DSD. 18 Therefore, using the approach from Best 13 introduces some uncertainty. For example, in case the drop size is used to estimate the kinetic energy of a rainfall event, the fraction of rainfall kinetic energy due to large drops might be underestimated.…”

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confidence: 99%

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Effect of drop‐size parameterization and rain amount on blade‐lifetime calculations considering leading‐edge erosion

2022

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Leading-edge erosion (LEE) of wind turbine blades is caused by the impact of particles, for example, raindrops, and leads to a loss in the power production and high maintenance cost. Investigations have shown that a reduction in tip speed, so-called erosion-safe mode, increases the blade lifetime but the influence of different dropsize parameterizations and rain amounts on the blade lifetime is unclear. This study compares blade lifetime calculations using two different drop-size parameterizations, which both describe a characteristic drop size of a rain measurement. Furthermore, changes in blade lifetime in case rain amount is increased or decreased are investigated as well as the effect of different wind shear exponents. The blade-lifetime calculations are based on a kinetic-energy model and an accumulated rain model. The results show that a drop-size parameterization based on rain rate leads to 44 times longer blade lifetime compared with a parameterization using in situ drop-size measurements. This large difference is probably due to the underestimation of large drops of the first mentioned parameterization. A change in rain amount of about ±17 % results only in a marginal change in blade lifetime. For both cases and models, an extension of blade lifetime was calculated when reducing the tip speed during specific rain events. The change of wind shear exponents caused as well a considerable effect on the lifetime prediction. Overall, blade lifetime is primary depending on the chosen model, where the kinetic-energy model is highly sensitive to the drop-size parameterization.

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“…This number can be expressed as function of the kinetic energy of drops

N_{d} goodbreak= c {(\frac{1}{12} * ρ * π * D^{3} * v^{2})}^{- m},

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Effect of drop‐size parameterization and rain amount on blade‐lifetime calculations considering leading‐edge erosion

2022

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“…The GPM/DPR consists of a Ku‐band (13.6 GHz) phased‐array precipitation radar (KuPR) and a Ka‐band (35.5 GHz) phased‐array precipitation radar (KaPR). High‐sensitivity observations from the KaPR contribute to measure light rain (Hamada and Takayabu, 2016; Masaki et al ., 2020), while the differential scattering properties at the two frequencies provide drop size distribution information (Liao and Meneghini, 2019; Yamaji et al ., 2020). The beam width is about 0.71°, with horizontal resolution on the ground of 5.2 km for both KuPR and KaPR.…”

Section: Methodsmentioning

confidence: 99%

One‐dimensional maximum‐likelihood estimation for spaceborne precipitation radar data assimilation

Ikuta

Okamoto

Kubota

2020

Quart J Royal Meteoro Soc

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Spaceborne precipitation radar such as Global Precipitation Measurement (GPM)/dual‐frequency precipitation radar (DPR) provides valuable observations of precipitation systems in three dimensions. Assimilation of GPM/DPR data is becoming an important technique for improving the accuracy of forecasting to complement scarce ground‐based observations. This study presents a new, one‐dimensional maximum‐likelihood estimation (1D‐MLE) method developed by the authors that enables the estimation of relative humidity profiles according to a non‐Gaussian probability density function. By assimilating the estimated relative humidity profiles using a four‐dimensional variational (4D‐Var) method, mesoscale precipitation forecasts by the Japan Meteorological Agency (JMA) have been considerably improved. The displacement of forecast precipitation during a severe weather event, in particular, is improved significantly. It was found that forecasting accuracy was maintained for a narrow GPM/DPR swath and low revisit frequency by repeating the assimilation–forecast cycle. Since the effectiveness was confirmed, the JMA began assimilating GPM/DPR data using the 1D‐MLE approach from March 2016.

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“…(2019) showed the reasonable performance of GPM DPR in distinguishing between different types of precipitation. This good performance of GPM DPR, alongside other advantages such as improved estimation of precipitation and fine scale resolution, support its immense benefit for precipitation studies (e.g., Marra et al ., 2017; Panegrossi et al ., 2020; Tang et al ., 2020; Yamaji et al ., 2020). Recently, GPM DPR has been employed to analyse precipitation features within cyclones across a number of different regions (e.g., Zhang et al ., 2020 in northern Pacific; Marra et al ., 2019 in the Mediterranean; Hu et al ., 2019 in the northwest Pacific), which revealed helpful results on cyclone characteristics.…”

Section: Introductionmentioning

confidence: 99%

Climatology of cyclones in western and northwestern Iran using reanalysis and remote sensing data

Ghasemifar

Hardy

Minaei

2022

Intl Journal of Climatology

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Agriculture and hydrological management in western and northwestern Iran is highly sensitive to precipitation associated with Mediterranean and Sudanese cyclones particularly during spring and winter. Although many studies have focused on the theoretical basis of these cyclones, statistical analyses, especially with satellite observations, have not been undertaken. In this study, 40 cyclones during all months of 2015-2021 are characterized using data collected by Global Precipitation Measurement (GPM) dual-frequency precipitation radar (DPR), Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) and ERA5 reanalysis within each cyclone quadrant. The results show that about 45% of cyclones have a lifetime between 1 and 2 days, and approximately 25% occur during April with a secondary peak in March (22.5%). Accordingly, cyclonic rainy days and rainfall amounts peak in April with values of 76.1% and 64.1%, respectively. The lowest (most negative) low-and midtropospheric vertical velocity in the southeast and northeast quadrants indicates upward motion, which leads to the most intense latent heat release within the cyclone. Accordingly, the highest rainfall rates occur in the southeast and northeast quadrants, located within and ahead of the highest specific humidity quadrant (southeast) where the warm conveyor belt plays a significant role for rainfall formation. Maximum stratiform and convective rainfall rates are observed in the southwest and southeast quadrants, respectively. The distribution of rainfall rate is consistent with that of the storm-top height pattern in all quadrants. The maximum percentage of warm rain to the total rain (34.6% on average) for both stratiform and convective precipitation falls in the southeast quadrant. The structure of these analysed cyclones is largely similar to that shown previously in the literature. According to the analysed rainfall in different life cycles, it is expected that the cyclones have the greatest impact (i.e., extreme rainfall) during the developing stage in the northeast and southeast quadrants, and during the mature stage in the southwest quadrant. The lowest influence is during the dissipating stage. The results from this study can help decision makers within the hydrological and risk management industries.

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4-year Climatology of Global Drop Size Distribution and its Seasonal Variability Observed by Spaceborne Dual-frequency Precipitation Radar

Cited by 22 publications

References 48 publications

Effect of drop‐size parameterization and rain amount on blade‐lifetime calculations considering leading‐edge erosion

Effect of drop‐size parameterization and rain amount on blade‐lifetime calculations considering leading‐edge erosion

One‐dimensional maximum‐likelihood estimation for spaceborne precipitation radar data assimilation

Climatology of cyclones in western and northwestern Iran using reanalysis and remote sensing data

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