Overview of the D3R Observations during the IFloodS Field Experiment with Emphasis on Rainfall Mapping and Microphysics

Beauchamp, Robert M.; Chandrasekar, V.; Chen, Haonan; Vega, Manuel A.

doi:10.1175/jhm-d-15-0023.1

Cited by 16 publications

(9 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the stratiform, precipitation, and the winter snowfall scenarios with little negative wind effects, the falling hydrometeor in the air may experience complex microphysical processes, especially when the melting layer is captured by radar beams, but (light) liquid rain is the main precipitation type near the surface. The vertical remote sensing devices, such as satellite-based or ground-based Ka-band and Ku-band radar [25], are promising for relating such radar measurements with gauge measurements more adequately if their temporal resolutions are the same.…”

Section: Discussionmentioning

confidence: 99%

Utilization of a C-band Polarimetric Radar for Severe Rainfall Event Analysis in Complex Terrain over Eastern China

Gou

Chen

et al. 2018

Remote Sensing

Self Cite

View full text Add to dashboard Cite

Polarimetric radar measurements and products perform as the cornerstones of modern severe weather warning and nowcast systems. Two radar quantitative precipitation estimation (QPE) frameworks, one based on a radar-gauge feedback mechanism and the other based on standard rain drop size distribution (DSD)-derived rainfall retrieval relationships, are both evaluated and investigated through an extreme severe convective rainfall event that occurred on 23 June 2015 in the mountainous region over eastern China, using the first routinely operational C-band polarimetric radar in China. Complex rainstorm characteristics, as indicated by polarimetric radar observables, are also presented to account for the severe rainfall field center located in the gap between gauge stations. Our results show that (i) the improvements of the gauge-feedback-derived radar QPE estimator can be attributed to the attenuation correction technique and dynamically adjusted Z–R relationships, but it greatly relies on the gauge measurement accuracy. (ii) A DSD-derived radar QPE estimator based on the specific differential phase (KDP) performs best among all rainfall estimators, and the interaction between the mesocyclone and the windward slope of the mountainous terrain can account for its apparent overestimation. (iii) The rainstorm is mainly dominated by small-sized and moderate-sized raindrops, with the mean volume diameter being less than 2 mm, but its KDP column (KDP > 3°·km−1) has a liquid water content that is higher than 2.4815 g·m−3, and a high raindrop concentration (Nw) with log10(Nw) exceeding 5.1 mm−1m−3. In addition, small hailstones falling and melting are also found in this event, which further aggregates Nw upon the severe rainfall center in the gap between gauge stations.

show abstract

Section: Discussionmentioning

confidence: 99%

Utilization of a C-band Polarimetric Radar for Severe Rainfall Event Analysis in Complex Terrain over Eastern China

Gou

Chen

et al. 2018

Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

“…After the Global Precipitation Measurement (GPM) was successfully launched at 17: 37 UTC, February th , 2014, which is a joint mission between the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA), dualfrequency precipitation radars (DPR) have emerged as an important tool for precipitation estimation and microphysical parameters retrieval (Beauchamp et al 2015;Le et al 2012;Le et al 2014;Liao et al 2019aLiao et al , 2019bLiao et al 2020). Previous researchers have worked on studies which focus on scattering properties of snowflakes at different frequencies and observing them via remote sensing at the same time (Eriksson et al 2018;Leinonen et al 2011;Lu et al 2016;Matrosov et al 2019;Tyynela et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Snowfall Estimation Using Dual-wavelength Radar during the Pyeongchang 2018 Olympics and Paralympic Winter Games

Chandrasekar

Xiao

et al. 2021

Journal of the Meteorological Society of Japan

Self Cite

View full text Add to dashboard Cite

Accurate estimation of snowfall rate during snowstorms is crucial. This estimate directly impacts the hydrological and atmospheric models. The density of snow plays a very important role in estimating the snowfall rate. In this paper, the density of snow is investigated during a huge snowstorm event during the International Collaborative Experiment held during the PyeongChang 2018 Olympics and Paralympic winter games (ICE-POP 2018). The density is calculated using the terminal velocities and diameters of the snow particles measured by a disdrometer. In this study, we not only use radar reflectivity factor (Z) for snowfall rate (S) estimation, but also use dual-frequency ratio (DFR). We derive S-Z and S-Z-DFR relations for snowfall estimation during this snowstorm event after considering the density of snow. The comparisons are performed between National Aeronautics and Space Administration (NASA) Dual-frequency Dualpolarization Doppler Radar (D3R) and precipitation gauges using these two power-law relations. The results show that the two relations for snowfall rate estimation agree well with gauges, but the S-Z-DFR method performs the best, which has a lower normalized standard error. The error in the snowfall rate estimates decreases as the time scale becomes large. This shows that the S-Z-DFR algorithm is a promising way for snowfall quantitative precipitation estimation (QPE) and can be used as a ground validation tool for Global Precipitation Measurement (GPM) snowfall production evaluations.

show abstract

“…Olympic Mountains Experiment (Chandrasekar et al, 2017). Furthermore, methods of D3R calibration, attenuation correction and Ku-band QPE were also introduced (Beauchamp et al, 2015;Chen and Chandrasekar, 2015).…”

Section: Introductionmentioning

confidence: 99%

Uncertainties in retrieving microphysical properties of rain profiles using ground‐based dual‐frequency radar

Wang

Liu

2020

Meteorological Applications

View full text Add to dashboard Cite

Dual‐frequency radar (DFR) could improve the accuracy of estimating the microphysical properties of rain profiles. Unfortunately, factors that cause inaccuracies in retrieved rain profiles include uncertainties in raindrop size distribution (DSD) parameterizations, DFR retrieval methods and radar measurement errors. The primary objective of this study was to assess the uncertainties in retrieving rain profiles to offer insight into application considerations for ground‐based DFRs in China. The uncertainties caused by DSD models are assessed by comparing attenuation coefficients and rain rates from DFR algorithms with those directly derived from DSD spectra from disdrometers. Then, based on a DSD model, the impacts of retrieval methods, radar range resolution, measurement error and errors in temperature on DFR retrievals are explored by comparing the rain profiles obtained using DFR algorithms with those directly output from the Weather Research and Forecasting model. Overall, the impact of measurement error on the DFR retrievals is relatively significant for both the forward retrieval method and the iterative backward retrieval method and should be eliminated in practical applications. At an individual uncertainty level, the impact of DSD parameterizations on the retrievals from the dual‐frequency technique is less than ±10% bias when the shape factor μ of the gamma distribution ranges from 2 to 4. The retrieved rain profiles from the forward retrieval method are relatively sensitive to radar range resolution and the retrieval performance can be improved with increasing the range resolution, while the iterative backward retrieval method exhibits stable retrieval performance. The impact of temperature errors on the retrieved rain profiles is negligible.

show abstract

Overview of the D3R Observations during the IFloodS Field Experiment with Emphasis on Rainfall Mapping and Microphysics

Cited by 16 publications

References 11 publications

Utilization of a C-band Polarimetric Radar for Severe Rainfall Event Analysis in Complex Terrain over Eastern China

Utilization of a C-band Polarimetric Radar for Severe Rainfall Event Analysis in Complex Terrain over Eastern China

Snowfall Estimation Using Dual-wavelength Radar during the Pyeongchang 2018 Olympics and Paralympic Winter Games

Uncertainties in retrieving microphysical properties of rain profiles using ground‐based dual‐frequency radar

Contact Info

Product

Resources

About