rain radar
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2022 ◽  
Author(s):  
TIANWEN WEI ◽  
Haiyun Xia ◽  
Kenan Wu ◽  
Yuanjian Yang ◽  
Qi Liu ◽  
...  

2022 ◽  
Vol 14 (1) ◽  
pp. 33-55
Author(s):  
Claudia Acquistapace ◽  
Richard Coulter ◽  
Susanne Crewell ◽  
Albert Garcia-Benadi ◽  
Rosa Gierens ◽  
...  

Abstract. As part of the EUREC4A field campaign, the research vessel Maria S. Merian probed an oceanic region between 6 to 13.8∘ N and 51 to 60∘ W for approximately 32 d. Trade wind cumulus clouds were sampled in the trade wind alley region east of Barbados as well as in the transition region between the trades and the intertropical convergence zone, where the ship crossed some mesoscale oceanic eddies. We collected continuous observations of cloud and precipitation profiles at unprecedented vertical resolution (7–10 m in the first 3000 m) and high temporal resolution (1–3 s) using a W-band radar and micro rain radar (MRR), installed on an active stabilization platform to reduce the impact of ship motions on the observations. The paper describes the ship motion correction algorithm applied to the Doppler observations to extract corrected hydrometeor vertical velocities and the algorithm created to filter interference patterns in the MRR observations. Radar reflectivity, mean Doppler velocity, spectral width and skewness for W-band and reflectivity, mean Doppler velocity, and rain rate for MRR are shown for a case study to demonstrate the potential of the high resolution adopted. As non-standard analysis, we also retrieved and provided liquid water path (LWP) from the 89 GHz passive channel available on the W-band radar system. All datasets and hourly and daily quicklooks are publically available, and DOIs can be found in the data availability section of this publication. Data can be accessed and basic variables can be plotted online via the intake catalog of the online book “How to EUREC4A”.


Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1678
Author(s):  
Nazli Turini ◽  
Boris Thies ◽  
Rütger Rollenbeck ◽  
Andreas Fries ◽  
Franz Pucha-Cofrep ◽  
...  

Ground based rainfall information is hardly available in most high mountain areas of the world due to the remoteness and complex topography. Thus, proper understanding of spatio-temporal rainfall dynamics still remains a challenge in those areas. Satellite-based rainfall products may help if their rainfall assessment are of high quality. In this paper, microwave-based integrated multi-satellite retrieval for the Global Precipitation Measurement (GPM) (IMERG) (MW-based IMERG) was assessed along with the random-forest-based rainfall (RF-based rainfall) and infrared-only IMERG (IR-only IMERG) products against the quality-controlled rain radar network and meteorological stations of high temporal resolution over the Pacific coast and the Andes of Ecuador. The rain area delineation and rain estimation of each product were evaluated at a spatial resolution of 11 km2 and at the time of MW overpass from IMERG. The regionally calibrated RF-based rainfall at 2 km2 and 30 min was also investigated. The validation results indicate different essential aspects: (i) the best performance is provided by MW-based IMERG in the region at the time of MW overpass; (ii) RF-based rainfall shows better accuracy rather than the IR-only IMERG rainfall product. This confirms that applying multispectral IR data in retrieval can improve the estimation of rainfall compared with single-spectrum IR retrieval algorithms. (iii) All of the products are prone to low-intensity false alarms. (iv) The downscaling of higher-resolution products leads to lower product performance, despite regional calibration. The results show that more caution is needed when developing new algorithms for satellite-based, high-spatiotemporal-resolution rainfall products. The radar data validation shows better performance than meteorological stations because gauge data cannot correctly represent spatial rainfall in complex topography under convective rainfall environments.


2021 ◽  
Vol 893 (1) ◽  
pp. 012001
Author(s):  
D Nurheliza ◽  
N J Trilaksono ◽  
F Renggono

Abstract Rain microstructure is a critical aspect to understand the dynamics and microphysics character of the clouds. It is characterized by the distribution of size, fall velocity and shape of raindrop. Raindrop size distribution (DSD) explains the detail of the microphysical process because it represents a process of rain to the surface. One of the phenomena that influence the rain patterns in Indonesia is Madden Julian Oscillation (MJO). Therefore, observing rain microstructure with its relation to MJO can determine the differences in rainfall characteristic and microphysical processes during active and inactive MJO period. The data used in this study are Micro Rain Radar (MRR), disdrometer, and real-time multivariate (RMM) index data. The period/date selection of active MJO event performed using RMM index method is more than 1 in phases 4 and 5 and otherwise for inactive MJO. Types of rain are divided into stratiform and convective rain based on disdrometer data. From that, there are 46 active and 52 inactive MJO events. Rain microstructure in this study focuses on DSD from disdrometer and micro rain radar data analyzed with liquid water content profile, fall velocity, reflectivity, and rain rate from MMR. Besides, there are parameters of DSD, which are the mass-weighted diameter (Dm) and total concentration (Nw), calculated using the moment and gamma distribution method. The result shows that DSD and other parameters are greater during inactive MJO period. It means that process of collision-coalescence, evaporation, and updraft is dominant during inactive MJO period.


2021 ◽  
Author(s):  
Alfonso Ferrone ◽  
Anne-Claire Marie Billault-Roux ◽  
Alexis Berne

Abstract. The Micro Rain Radar (MRR) PRO is a K-band Doppler weather radar, using frequency modulated continuous wave (FMCW) signals, developed by Metek Meteorologische Messtechnik GmbH (Metek) as successor to the MRR-2. Benefiting from four datasets collected during two field campaigns in Antarctica and Switzerland, we developed a processing library for snowfall measurements, named ERUO (Enhancement and Reconstruction of the spectrUm for the MRR-PRO), with a two-fold objective. Firstly, the proposed method addresses a series of issues plaguing the radar variables, which include interference lines, power drops at the extremes of the Doppler spectrum and abrupt cutoff of the transfer function. Secondly, the algorithm aims to improve the quality of the final variables, by lowering the minimum detectable equivalent attenuated reflectivity factor and extending the valid Doppler velocity range through antialiasing. The performance of the algorithm has been tested against the measurements of a co-located W-band Doppler radar. Information from a close-by X-Band Doppler dual-polarization radar has been used to exclude unsuitable radar volumes from the comparison. Particular attention has been dedicated to verify the estimation of the meteorological signal in the spectra covered by interferences.


2021 ◽  
Author(s):  
Claudia Acquistapace ◽  
Richard Coulter ◽  
Susanne Crewell ◽  
Albert Garcia-Benadi ◽  
Rosa T. Gierens ◽  
...  

Abstract. As part of the EUREC4A field campaign, the research vessel Maria S. Merian probed an oceanic region between 6° N and 13.8° N and 51° W to 60° W for approximately 32 days. Trade wind cumulus clouds were sampled in the trade-wind alley region east of Barbados as well as in the transition region between the trades and the intertropical convergence zone, where the ship crossed some mesoscale oceanic eddies. We collected continuous observations of cloud and precipitation profiles at unprecedented vertical resolution (7–10 m in the first 3000 m) and high temporal resolution (1–3 s) using a W-band radar and micro-rain radar (MRR-PRO), installed on an active stabilization platform to reduce the impact of ship motions on the observations. The paper describes the ship motion correction algorithm applied to the Doppler observations to extract corrected hydrometeors vertical velocities and the algorithm created to filter interference patterns in the MRR-PRO observations. Radar reflectivity, mean Doppler velocity, spectral width and skewness for W-band and attenuated reflectivity, mean Doppler velocity and rain rate for MRR-PRO are shown for a case study to demonstrate the potential of the high resolution adopted. As non-standard analysis, we also retrieved and provided liquid water path (LWP) from the 89 GHz passive channel available on the W-band radar system. All datasets and hourly and daily quicklooks are publically available. Data can be accessed and basic variables can be plotted online via the intake catalog of the online book "How to EUREC4A".


2021 ◽  
Vol 22 (1) ◽  
pp. 9-16
Author(s):  
Sara Aisyah Syafira ◽  
Nyayu Fatimah Zahroh ◽  
Saraswati Dewi ◽  
Findy Renggono

Intisari Beberapa penelitian terkait kejadian hujan menggunakan beberapa jenis alat seperti Micro Rain Radar (MRR) dan Disdrometer. Kombinasi kedua instrument tersebut dapat memberikan gambaran yang lebih  komprehensif mengenai kejadian hujan mulai dari lapisan atas atmosfer hingga permukaan. Penelitian ini mengamati beberapa kejadian hujan pada puncak musim hujan tahun 2017 dan pergantian tahun 2019/2020 di Kawasan Puspiptek Serpong, Tangerang Selatan dengan menggunakan instrumen MRR dan Disdrometer untuk mengetahui karakteristik distribusi ukuran butir air hujan. Hasil penelitian ini menunjukkan pola sebaran butir air hujan yang berbeda, antara kejadian hujan dengan intensitas sangat lebat dan sangat ringan hingga lebat, baik pada lapisan atas atmosfer maupun permukaan. Selain itu, hasil penelitian ini menunjukkan bahwa kejadian hujan sangat lebat berasal dari kumpulan awan konvektif dengan durasi hujan selama 15-60 menit. Sedangkan, kejadian hujan ringan hingga sedang pada umumnya berasal dari kumpulan awan nimbostratus di level menengah atmosfer dengan durasi hujan sekitar 2-3 jam. Abstract Several studies used some equipment types to observe rain events, such as the Micro Rain Radar (MRR) and Disdrometer. Combining the two can provide a more comprehensive picture of rain events from the upper atmosphere to the surface. This study observed several rain events at the peak of the rainy season in 2017 and the turn of the year 2019/2020 in the Puspiptek Serpong Area, South Tangerang, using MRR and Disdrometer instruments to determine the characteristics of the droplet size distribution. This study's results indicate a different droplet size distribution pattern, between the incidence of rain with very heavy intensity and very light to dense, both in the upper atmosphere and surface. Besides, this study's results indicate that the very heavy rain events come from convective clouds with a 15-60 minutes rain duration. Meanwhile, light to moderate rain events generally come from a group of nimbostratus clouds in the medium-level atmosphere with a rain duration of roundabout 2-3 hours.


2021 ◽  
Vol 14 (6) ◽  
pp. 4565-4574
Author(s):  
Andreas Foth ◽  
Janek Zimmer ◽  
Felix Lauermann ◽  
Heike Kalesse-Los

Abstract. In this paper, we present two micro rain radar-based approaches to discriminate between stratiform and convective precipitation. One is based on probability density functions (PDFs) in combination with a confidence function, and the other one is an artificial neural network (ANN) classification. Both methods use the maximum radar reflectivity per profile, the maximum of the observed mean Doppler velocity per profile and the maximum of the temporal standard deviation (±15 min) of the observed mean Doppler velocity per profile from a micro rain radar (MRR). Training and testing of the algorithms were performed using a 2-year data set from the Jülich Observatory for Cloud Evolution (JOYCE). Both methods agree well, giving similar results. However, the results of the ANN are more decisive since it is also able to distinguish an inconclusive class, in turn making the stratiform and convective classes more reliable.


Author(s):  
Julia A. Shates ◽  
Claire Pettersen ◽  
Tristan S. L’Ecuyer ◽  
Steve J. Cooper ◽  
Mark S. Kulie ◽  
...  

AbstractThe prevailing snowfall regimes at two Scandinavian sites, Haukeliseter, Norway and Kiruna, Sweden, are documented using ground-based in-situ and remote sensing methods. Micro Rain Radar (MRR) profiles indicate three distinct snowfall regimes occur at both sites: shallow, deep, and intermittent snowfall. The shallow snowfall regime produces the lowest mean snowfall rates and radar echo tops are confined below 1.5 km above ground level (AGL). Shallow snowfall occurs under areas of large scale subsidence with a moist boundary layer and dry air aloft. The atmospheric ridge coinciding with shallow snowfall is highly anomalous over Haukeliseter, but is more common in Kiruna where shallow snowfall was frequently observed. The shallow snowfall particle size distributions (PSDs) are broad with lower particle concentrations than other regimes, especially small particles. Deep snowfall events exhibit MRR profiles that extend above 2 km AGL, and tend to be associated with weak low pressure and high relative humidity throughout the troposphere. The PSDs in deep events are narrower with high concentrations of small particles. Increasing MRR reflectivity towards the surface suggests aggregation as a possible growth process during deep snowfall events. The heaviest mean snowfall rates are associated with intermittent events that are characterized by deep MRR profiles, but have variations in intensity and height. The intermittent regime is associated with anomalous, deep low pressure along the coast of Norway, and enhanced relative humidity at lower levels. The PSDs reveal high concentrations of small and large particles. The analysis reveals that there are unique characteristics of shallow, deep, and intermittent snowfall regimes that are common between the sites.


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