Recent Application of Weather Radar Observation into Hydrologic Forecasting in Japan

ISFRAM 2015 ◽  
2016 ◽  
pp. 3-15
Author(s):  
Eiichi Nakakita ◽  
Sunmin Kim
Keyword(s):  
Weather Radar ◽  
Radar Observation ◽  
Recent Application

scholarly journals Interpreting estimated Observation Error Statistics of Weather Radar Measurements using the ICON-LAM-KENDA System

2021 ◽  
Author(s):  
Yuefei Zeng ◽  
Tijana Janjic ◽  
Yuxuan Feng ◽  
Ulrich Blahak ◽  
Alberto de Lozar ◽  
...  
Keyword(s):  
Covariance Matrix ◽  
A Priori ◽  
Weather Radar ◽  
Radar Observation ◽  
Wind Data ◽  
Observation Error ◽  
Error Statistics ◽  
Error Sources ◽  
Radar Measurements ◽  
Observation Space

Abstract. Assimilation of weather radar measurements including radar reflectivity and radial wind data has been operational at the Deutscher Wetterdienst, with a diagonal observation error (OE) covariance matrix. For an implementation of a full OE covariance matrix, the statistics of the OE have to be a priori estimated, for which the Desroziers method has been often used. However, the resulted statistics consists of contributions from different error sources and are difficult to interpret. In this work, we use an approach that is based on samples for truncation error in radar observation space to approximate the representation error due to unresolved scales and processes (RE) and compare its statistics with the OE statistics estimated by the Desroziers method. It is found that the statistics of the RE help the understanding of several important features in the variances and correlation length scales of the OE for both reflectivity and radial wind data and the other error sources from the microphysical scheme, radar observation operator and the superobbing technique may also contribute, for instance, to differences among different elevations and observation types. The statistics presented here can serve as a guideline for selecting which observations to assimilate and for assignment of the OE covariance matrix that can be diagonal or full and correlated.

scholarly journals Challenges in Estimating Quantitative Precipitation Estimation (QPE) Using Weather Radar Observation Over the Mountainous Country of Nepal

2017 ◽  
Vol 21 ◽  
pp. 50-59
Author(s):  
Shakti P.C. ◽  
Masayuki Maki
Keyword(s):  
Research Work ◽  
Weather Radar ◽  
Radar Observation ◽  
Spatial And Temporal Variation ◽  
Accurate Information ◽  
Mountain Range ◽  
Mountain Areas ◽  
Quantitative Precipitation Estimation ◽  
Precipitation Estimation ◽  
Mountainous Country

South Asian country Nepal characterizes a complex mountain range in this world. The country’s population density is increasing along with rapid growth of population especially over mountainous cities, southern hills and the Terai. On the other hand, a number of fatal natural calamities, such as flash flooding and landslides raised by clutter intensive rainfall, have been increasing since the last decade. To deal with such water hydro meteorological disasters, accurate information on spatial and temporal variation of rainfall distribution is very important. In Nepal, the amount of rainfall has been obtained from limited rain gauge networks, which may leads to many errors in making a Quantitative Precipitation Estimation (QPE). Weather radar observations have recently been highlighted as an alternative option for estimating the spatial and temporal distribution of precipitation across specified time intervals. However, estimating rainfall from radar observation has its own challenges, especially over a mountainous country like Nepal.Another mountainous country Japan is well known for using weather radar observation to make QPE product. Different types of weather radar have been used to record, monitor and forecast precipitation in Japan for both operational and research purposes. A high level research work has also been done on this field. The high spatial and temporal (250-m and 1-min) QPE product obtained from the radar observation is available for the public. It shows good harmony with ground data in the flat and mountain areas of Japan. Though Nepal and Japan are located in different regions, both countries represent complex mountain regions and have been facing natural disaster caused by extreme rainfall. In Nepal, weather radar observation for estimating precipitation amounts has not started on an operational basis till date. Hence, sharing knowledge and skills from Japan’s research on weather radar observation would play a key role to achieve the radar based QPE product in Nepal. Therefore, we discuss about the challenge in obtaining QPE product, considering an example of the progress of weather radar system in Japan. It is believed that any discussion on it will be a reference for weather radar deployment and its QPE product in Nepal in coming days.  HYDRO Nepal JournalJournal of Water Energy and EnvironmentIssue: 21, July, 2017Page: 50-59Upload Date: July 18, 2017

scholarly journals Modifikasi Metode Waldvogel Berdasarkan Identifikasi Karakteristik Hujan Es Yang Dikelompokkan Berdasarkan Jarak Cakupan Radar Cuaca Pada Radar Cuaca Jakarta Tahun 2010-2019

2019 ◽  
Vol 4 ◽  
pp. 69 ◽  
Author(s):  
Marselinus Muaya ◽  
Amalia Khoirunnisa ◽  
Rizky Umul Nisa Fadillah ◽  
Eko Wardoyo ◽  
Fitria Puspita Sari
Keyword(s):  
Satellite Image ◽  
Weather Radar ◽  
Radar Data ◽  
Radar Observation ◽  
Spatial And Temporal Variability ◽  
Freezing Level ◽  
Critical Success ◽  
Observation Area ◽  
Critical Success Index ◽  
Success Index

<p><strong>Abstract: </strong>Hail detection using information from satellite and weather radar is the right choice due to spatial and temporal variability of the phenomenon of high hail. Some algorithms that use single polarization radar data have been developed for hail detection. One method that has been applied in Reflectivity-based Hail Warning or ZHAIL radar product is the Waldvogel method. This research aims to find new threshold criteria for the application of the Waldvogel method in the Jakarta weather radar observation area which is grouped into three regions based on the distance of weather radar observation. In this research, hail events from 2010 to 2019 have been analysed. Analysis of weather and weather radar data was carried out to determine the climatological characteristics of reflectivity values, reflectivit heights, and freezing levels as parameters to be used to determine the criteria for modification in the Waldvogel method. The reflectifity and reflectivity values are obtained from the processing of radar data, while the freezing level is generated from the processing of the Himawari satellite image in the infrared channel. Waldvogel's algorithm with the three modifications that have been produced, then tested using Critical Success Index, Possibility of Detection, and False Alram Ratio, calculations on the percentage value of Probability Of Hail. The results of the research is the reflectivity values, reflectivity altitude and the most accurate freezing level applied to each region that was differentiated according to the weather radar distance radius observation. Better accuracy of the application of Waldvogel method is expected to reduce therougheffects ofthehail phenomenon.</p><p><strong>Abstrak: </strong>Metode Waldvogel merupakan metode deteksi hujan es yang mengubah reflectivity dari pengamatan radar menjadi produk Reflectivity-based Hail Warning atau ZHAIL. Penggunaan metode Waldvogel masih perlu disesuaikan dengan kondisi wilayah tropis termasuk Indonesia. Penelitian ini bertujuan untuk menemukan kriteria ambang batas baru untuk penerapan metode Waldvogel di daerah pengamatan radar cuaca Jakarta sehingga diperoleh akurasi metode Waldvogel yang lebih baik. Kriteria ambang dikelompokkan menjadi tiga wilayah berdasarkan jarak cakupan radar cuaca (wilayah I : &lt;30 km, wilayah II : 30-100 km dan wilayah III : 100-150 km). Analisis data radar cuaca dilakukan untuk menentukan karakteristik klimatologis dari nilai reflectivity maksimum, ketinggian reflectivity maksimum, dan ketinggian freezing level sebagai parameter yang akan digunakan untuk menentukan kriteria modifikasi dalam metode Waldvogel. Verfikasi parameter diujikan dengan nilai Probability of Hail (POH), False Alarm Ratio (FAR), Possibility of Detection (POD), dan Critical Success Index (CSI). Hasil verifikasi menunjukan metode Waldvogel modiifikasi menghasilkan performa yang lebih baik dibandingkan metode Waldvogel awal untuk wilayah I dan II dengan kriteria metode Waldvogel modifikasi yang paling baik yaitu Waldvogel 3. Sedangkan untuk wilayah III, nilai kriteria yang lebih baik adalah Waldvogel tanpa modifikasi. Akurasi yang lebih baik dari penerapan metode Waldvogel diharapkan dapat mengurangi dampak buruk yang ditimbulkan dari fenomena hujan es</p>

scholarly journals Interpreting estimated observation error statistics of weather radar measurements using the ICON-LAM-KENDA system

2021 ◽  
Vol 14 (8) ◽  
pp. 5735-5756
Author(s):  
Yuefei Zeng ◽  
Tijana Janjic ◽  
Yuxuan Feng ◽  
Ulrich Blahak ◽  
Alberto de Lozar ◽  
...  
Keyword(s):  
Covariance Matrix ◽  
A Priori ◽  
Weather Radar ◽  
Radar Observation ◽  
Wind Data ◽  
Observation Error ◽  
Error Statistics ◽  
Error Sources ◽  
Radar Measurements ◽  
Observation Space

Abstract. Assimilation of weather radar measurements including radar reflectivity and radial wind data has been operational at the Deutscher Wetterdienst, with a diagonal observation error (OE) covariance matrix. For an implementation of a full OE covariance matrix, the statistics of the OE have to be a priori estimated, for which the Desroziers method has been often used. However, the resulted statistics consists of contributions from different error sources and are difficult to interpret. In this work, we use an approach that is based on samples for truncation error in radar observation space to approximate the representation error due to unresolved scales and processes (RE) and compare its statistics with the OE statistics estimated by the Desroziers method. It is found that the statistics of the RE help the understanding of several important features in the variances and correlation length scales of the OE for both reflectivity and radial wind data and the other error sources from the microphysical scheme, radar observation operator and the superobbing technique may also contribute, for instance, to differences among different elevations and observation types. The statistics presented here can serve as a guideline for selecting which observations are assimilated and for assignment of the OE covariance matrix that can be diagonal or full and correlated.

The Evaluation on the Observation Accuracy of Phased Array Weather Radar

2014 ◽  
Vol 134 (4) ◽  
pp. 204-210 ◽  
Author(s):  
Yuki Hirano ◽  
Kouichi Maruo ◽  
Shigeharu Shimamura ◽  
Satoru Yoshida ◽  
Tomoo Ushio ◽  
...  
Keyword(s):  
Phased Array ◽  
Weather Radar
Sign in / Sign up

Export Citation Format

Share Document