scholarly journals Evaluation of Rainfall Forecasts by Three Mesoscale Models during the Mei-yu Season of 2008 in Taiwan. Part II: Development of an Object-Oriented Method

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 939
Author(s):  
Chung-Chieh Wang ◽  
Sahana Paul ◽  
Dong-In Lee
Keyword(s):  
Object Oriented ◽  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Object Oriented Method ◽  
Rain Area ◽  
Mesoscale Models ◽  
Frequency Distributions ◽  
South West Monsoon ◽  
Blended Data ◽  
Traditional Approaches

This study describes a recently developed object-oriented method suitable for Taiwan for the purpose to verify quantitative precipitation forecasts (QPFs) produced by mesoscale models as a complement to the traditional approaches in existence. Using blended data from the rain-gauge network in Taiwan and the Tropical Rainfall Measuring Mission (TRMM) as the observation, the method developed herein is applied to twice-daily 0–48 h QPFs produced by the Cloud-Resolving Storm Simulator (CReSS) during the South-West Monsoon Experiment (SoWMEX) in May–June 2008. In this method, rainfall objects are identified through a procedure that includes smoothing and thresholding. Various attribute parameters and the characteristics of observed and forecast rain-area objects are then compared and discussed. Both the observed and the QPF frequency distributions of rain-area objects with respect to total water production, object size, and rainfall are similar to chi-distribution, with highest frequency at smaller values and decreased frequencies toward greater values. The model tends to produce heavier rainfall than observation, while the latter exhibits a higher percentage of larger objects with weaker rainfall intensity. The distributions of shape-related attributes are similar between QPF and observed rainfall objects, with more northeast–southwest oriented and fewer northwest–southeast oriented objects. Both observed and modeled object centroid locations have relative maxima over the terrain of Taiwan, indicating reasonable response to the topography. The above results are consistent with previous studies.

scholarly journals Evaluation of Rainfall Forecasts by Three Mesoscale Models during the Mei-Yu Season of 2008 in Taiwan. Part III: Application of an Object-Oriented Verification Method

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 705
Author(s):  
Chung-Chieh Wang ◽  
Sahana Paul ◽  
Dong-In Lee
Keyword(s):  
Object Oriented ◽  
Tropical Rainfall Measuring Mission ◽  
Weather Research And Forecasting ◽  
Total Rainfall ◽  
Mesoscale Models ◽  
Subjective Analysis ◽  
Verification Method ◽  
Rain Gauges ◽  
Object Based ◽  
Central Weather Bureau

In this study, the performances of Mei-yu (May–June) quantitative precipitation forecasts (QPFs) in Taiwan by three mesoscale models: the Cloud-Resolving Storm Simulator (CReSS), the Central Weather Bureau (CWB) Weather Research and Forecasting (WRF), and the CWB Non-hydrostatic Forecast System (NFS) are explored and compared using an newly-developed object-oriented verification method, with particular focus on the various properties or attributes of rainfall objects identified. Against a merged dataset from ~400 rain gauges in Taiwan and the Tropical Rainfall Measuring Mission (TRMM) data in the 2008 season, the object-based analysis is carried out to complement the subjective analysis in a parallel study. The Mei-yu QPF skill is seen to vary with different aspects of rainfall objects among the three models. The CReSS model has a total rainfall production closest to the observation but a large number of smaller objects, resulting in more frequent and concentrated rainfall. In contrast, both WRF and NFS tend to under-forecast the number of objects and total rainfall, but with a higher proportion of bigger objects. Location errors inferred from object centroid locations appear in all three models, as CReSS, NFS, and WRF exhibit a tendency to simulate objects slightly south, east, and northwest with respect to the observation. Most rainfall objects are aligned close to an E–W direction in CReSS, in best agreement with the observation, but many towards the NE–SW direction in both WRF and NFS. For each model, the objects are matched with the observed ones, and the results of the matched pairs are also discussed. Overall, though preliminarily, the CReSS model, with a finer grid size, emerges as best performing model for Mei-yu QPFs.

Rain-Area Identification Using TRMM/TMI Data by Data Mining Approach

2008 ◽  
Vol 12 (3) ◽  
pp. 243-248 ◽  
Author(s):  
Shan-Tai Chen ◽  
◽  
Chien-Chen Wu ◽  
Wann-Jin Chen ◽  
Jen-Chi Hu ◽  
...  
Keyword(s):  
Data Mining ◽  
Tropical Rainfall Measuring Mission ◽  
Identification Problem ◽  
Rain Gauge ◽  
Rain Area ◽  
Data Mining Approach ◽  
Microwave Imager ◽  
Typhoon Season ◽  
Scattering Index ◽  
Trmm Microwave Imager

Rain-area identification distinguishes between rainy and non-rainy areas, which is the first step in some critical real-world problems, such as rain intensity identification and rain-rate estimation. We develop a data mining approach for oceanic rain-area identification during typhoon season, using microwave data from the Tropical Rainfall Measuring Mission (TRMM) satellite. Three schemes tailored for the problem are developed, namely (1) association rule analysis for uncovering the set of potential attributes relevant to the problem, (2) three-phase outlier removal for cleaning data and (3) the neural committee classifier (NCC) for achieving more accurate results. We created classification models from 1998-2004 TRMM Microwave Imager (TRMM-TMI) satellite data and used Automatic Rainfall and Meteorological Telemetry System (ARMTS) rain gauge data measurements to evaluate the model. Experimental results show that our approach achieves high accuracy for the rain-area identification problem. The classification accuracy of our approach, 96%, outperforms the 78.6%, 77.3%, 83.3% obtained by the scattering index, threshold check, and rain flag methods, respectively.

scholarly journals Radar adjusted data versus modelled precipitation: a case study over Cyprus

2006 ◽  
Vol 7 ◽  
pp. 85-90
Author(s):  
M. Casaioli ◽  
S. Mariani ◽  
C. Accadia ◽  
M. Gabella ◽  
S. Michaelides ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Heavy Precipitation ◽  
Radar Data ◽  
Skill Score ◽  
Rain Gauge ◽  
Limited Area ◽  
Rain Area ◽  
Open Questions ◽  
Skill Scores

Abstract. In the framework of the European VOLTAIRE project (Fifth Framework Programme), simulations of relatively heavy precipitation events, which occurred over the island of Cyprus, by means of numerical atmospheric models were performed. One of the aims of the project was indeed the comparison of modelled rainfall fields with multi-sensor observations. Thus, for the 5 March 2003 event, the 24-h accumulated precipitation BOlogna Limited Area Model (BOLAM) forecast was compared with the available observations reconstructed from ground-based radar data and estimated by rain gauge data. Since radar data may be affected by errors depending on the distance from the radar, these data could be range-adjusted by using other sensors. In this case, the Precipitation Radar aboard the Tropical Rainfall Measuring Mission (TRMM) satellite was used to adjust the ground-based radar data with a two-parameter scheme. Thus, in this work, two observational fields were employed: the rain gauge gridded analysis and the observational analysis obtained by merging the range-adjusted radar and rain gauge fields. In order to verify the modelled precipitation, both non-parametric skill scores and the contiguous rain area (CRA) analysis were applied. Skill score results show some differences when using the two observational fields. CRA results are instead quite in agreement, showing that in general a 0.27° eastward shift optimizes the forecast with respect to the two observational analyses. This result is also supported by a subjective inspection of the shifted forecast field, whose gross features agree with the analysis pattern more than the non-shifted forecast one. However, some open questions, especially regarding the effect of other range adjustment techniques, remain open and need to be addressed in future works.

scholarly journals Evaluation of IMERG Level-3 Products in Depicting the July to October Rainfall over Taiwan: Typhoon Versus Non-Typhoon

2021 ◽  
Vol 13 (4) ◽  
pp. 622
Author(s):  
Wan-Ru Huang ◽  
Pin-Yi Liu ◽  
Ya-Hui Chang ◽  
Cheng-An Lee
Keyword(s):  
Real Time ◽  
Tropical Rainfall Measuring Mission ◽  
Temporal Variations ◽  
Rain Gauge ◽  
Advantages And Disadvantages ◽  
Level 3 ◽  
Spatio Temporal ◽  
Typhoon Season ◽  
Early Late ◽  
Better Than

This study assesses the performance of satellite precipitation products (SPPs) from the latest version, V06B, Integrated Multi-satellitE Retrievals for Global Precipitation Mission (IMERG) Level-3 (including early, late, and final runs), in depicting the characteristics of typhoon season (July to October) rainfall over Taiwan within the period of 2000–2018. The early and late runs are near-real-time SPPs, while final run is post-real-time SPP adjusted by monthly rain gauge data. The latency of early, late, and final runs is approximately 4 h, 14 h, and 3.5 months, respectively, after the observation. Analyses focus on the seasonal mean, daily variation, and interannual variation of typhoon-related (TC) and non-typhoon-related (non-TC) rainfall. Using local rain-gauge observations as a reference for evaluation, our results show that all IMERG products capture the spatio-temporal variations of TC rainfall better than those of non-TC rainfall. Among SPPs, the final run performs better than the late run, which is slightly better than the early run for most of the features assessed for both TC and non-TC rainfall. Despite these differences, all IMERG products outperform the frequently used Tropical Rainfall Measuring Mission 3B42 v7 (TRMM7) for the illustration of the spatio-temporal characteristics of TC rainfall in Taiwan. In contrast, for the non-TC rainfall, the final run performs notably better relative to TRMM7, while the early and late runs showed only slight improvement. These findings highlight the advantages and disadvantages of using IMERG products for studying or monitoring typhoon season rainfall in Taiwan.

scholarly journals Estimating Rain Rates from Tipping-Bucket Rain Gauge Measurements

2008 ◽  
Vol 25 (1) ◽  
pp. 43-56 ◽  
Author(s):  
Jianxin Wang ◽  
Brad L. Fisher ◽  
David B. Wolff
Keyword(s):  
Rain Rate ◽  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Radar Reflectivity ◽  
Time Shift ◽  
Estimation Errors ◽  
Rate Estimation ◽  
Reflectivity Data ◽  
Rain Rates ◽  
Event Definition

Abstract This paper describes the cubic spline–based operational system for the generation of the Tropical Rainfall Measuring Mission (TRMM) 1-min rain-rate product 2A-56 from tipping-bucket (TB) gauge measurements. A simulated TB gauge from a Joss–Waldvogel disdrometer is employed to evaluate the errors of the TB rain-rate estimation. These errors are very sensitive to the time scale of rain rates. One-minute rain rates suffer substantial errors, especially at low rain rates. When 1-min rain rates are averaged over 4–7-min intervals or longer, the errors dramatically reduce. Estimated lower rain rates are sensitive to the event definition whereas the higher rates are not. The median relative absolute errors are about 22% and 32% for 1-min rain rates higher and lower than 3 mm h−1, respectively. These errors decrease to 5% and 14% when rain rates are used at the 7-min scale. The radar reflectivity–rain-rate distributions drawn from the large amount of 7-min rain rates and radar reflectivity data are mostly insensitive to the event definition. The time shift due to inaccurate clocks can also cause rain-rate estimation errors, which increase with the shifted time length. Finally, some recommendations are proposed for possible improvements of rainfall measurements and rain-rate estimations.

scholarly journals OORS: An object-oriented rewrite system

2007 ◽  
Vol 4 (2) ◽  
pp. 2-26
Author(s):  
Gernot Gebhard ◽  
Philipp Lucas
Keyword(s):  
Code Generation ◽  
Graphics Processing Units ◽  
Object Oriented ◽  
Graphics Hardware ◽  
Code Optimization ◽  
Target Architecture ◽  
Rewrite Rules ◽  
Graphics Processing ◽  
Traditional Approaches ◽  
Rewrite System

Retargeting a compiler?s back end to a new architecture is a time-consuming process. This becomes an evident problem in the area of programmable graphics hardware (graphics processing units, GPUs) or embedded processors, where architectural changes are faster than elsewhere. We propose the object-oriented rewrite system OORS to overcome this problem. Using the OORS language, a compiler developer can express the code generation and optimization phase in terms of cost-annotated rewrite rules supporting complex non-linearmatching and replacing patterns. Retargetability is achieved by organizing rules into profiles, one for each supported target architecture. Featuring a rule and profile inheritance mechanism, OORS makes the reuse of existing specifications possible. This is an improvement regarding traditional approaches. Altogether OORS increases the maintainability of the compiler?s back end and thus both decreases the complexity and reduces the effort of the retargeting process. To show the potential of this approach, we have implemented a code generation and a code optimization pattern matcher supporting different target architectures using the OORS language and introduced them in a compiler of a programming language for CPUs and GPUs.

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