scholarly journals Quality Evaluation of the 0.01° Multi-Source Fusion Precipitation Product and Its Application in Extreme Precipitation Event

2022 ◽  
Vol 14 (2) ◽  
pp. 616
Author(s):  
Zheng Wang ◽  
Yang Pan ◽  
Junxia Gu ◽  
Yu Zhang ◽  
Jianrong Wang
Keyword(s):  
Product Quality ◽  
Extreme Precipitation ◽  
Weather Prediction ◽  
Extreme Value ◽  
Precipitation Extreme ◽  
Precipitation Event ◽  
Precipitation Data ◽  
Precipitation Product ◽  
Independent Test ◽  
Better Than

High-resolution and high-quality precipitation data play an important role in Numerical Weather Prediction Model testing, mountain flood geological disaster monitoring, hydrological monitoring and prediction and have become an urgent need for the development of modern meteorological business. The 0.01° multi-source fusion precipitation product is the latest precipitation product developed by the National Meteorological Information Center to meet the above needs. Taking the hourly precipitation observation data of 2400 national automatic stations as the evaluation base, independent and non-independent test methods are used to evaluate the 0.01° multi-source fusion precipitation product in 2020. The product quality differences between the 0.01° precipitation product and the 0.05° precipitation product are compared, and their application in extreme precipitation events are analyzed. The results show that, in the independent test, the product quality of the 0.01° precipitation product and the 0.05° precipitation product are basically the same, which is better than that of each single input data source, and the product quality in winter and spring is slightly lower than that in summer, and both products have better quality in the east in China. The evaluation results of the 0.01° precipitation product in the non-independent test are far better than that of the 0.05° product. The root mean square error and the correlation coefficient of the 0.01° multi-source fusion precipitation product are 0.169 mm/h and 0.995, respectively. In the extreme precipitation case analysis, the 0.01° precipitation product, which is more consistent with the station observation values, effectively improves the problem that the extreme value of the 0.05° product is lower than that of station observation values and greatly improves the accuracy of the precipitation extreme value in the product. The 0.01° multi-source fusion precipitation product has better spatial continuity, a more detailed description of precipitation spatial distribution and a more accurate reflection of precipitation extreme values, which will better provide precipitation data support for refined meteorological services, major activity support, disaster prevention and reduction, etc.

scholarly journals Evaluation of NASA’s MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

2016 ◽  
Vol 17 (2) ◽  
pp. 693-711 ◽  
Author(s):  
Hamed Ashouri ◽  
Soroosh Sorooshian ◽  
Kuo-Lin Hsu ◽  
Michael G. Bosilovich ◽  
Jaechoul Lee ◽  
...  
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Gulf Coast ◽  
The United States ◽  
Value Theory ◽  
Extreme Value ◽  
Precipitation Extremes ◽  
Precipitation Product ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract This study evaluates the performance of NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979–2010. The Climate Prediction Center (CPC) U.S. Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scale patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRA tends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1) MERRA shows a spurious negative trend in Nebraska and Kansas, which is most likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over the Gulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. In addition, the increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.

scholarly journals Characterizing Subdiurnal Extreme Precipitation in the Midwestern United States

2010 ◽  
Vol 11 (1) ◽  
pp. 211-218 ◽  
Author(s):  
Nathan M. Hitchens ◽  
Robert J. Trapp ◽  
Michael E. Baldwin ◽  
Alexander Gluhovsky
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Generalized Pareto Distribution ◽  
Stage Iv ◽  
Return Level ◽  
Precipitation Event ◽  
Precipitation Data ◽  
Midwestern United States ◽  
Extreme Precipitation Events ◽  
Return Levels

Abstract This research establishes a methodology to quantify the characteristics of convective cloud systems that produce subdiurnal extreme precipitation. Subdiurnal extreme precipitation events are identified by examining hourly precipitation data from 48 rain gauges in the midwestern United States during the period 1956–2005. Time series of precipitation accumulations for 6-h periods are fitted to the generalized Pareto distribution to determine the 10-yr return levels for the stations. An extreme precipitation event is one in which precipitation exceeds the 10-yr return level over a 6-h period. Return levels in the Midwest vary between 54 and 93 mm for 6-h events. Most of the precipitation contributing to these events falls within 1–2 h. Characteristics of the precipitating systems responsible for the extremes are derived from the National Centers for Environmental Prediction stage II and stage IV multisensor precipitation data. The precipitating systems are treated as objects that are identified using an automated procedure. Characteristics considered include object size and the precipitation mean, variance, and maximum within each object. For example, object sizes vary between 96 and 34 480 km2, suggesting that a wide variety of convective precipitating systems can produce subdiurnal extreme precipitation.

Using Connectionist Modules for Decision Support

1990 ◽  
Vol 29 (03) ◽  
pp. 167-181 ◽  
Author(s):  
G. Hripcsak
Keyword(s):  
Decision Support ◽  
Standard Deviation ◽  
Confidence Interval ◽  
Posterior Probability ◽  
Back Propagation ◽  
Connectionist Model ◽  
Test Set ◽  
The Third ◽  
Independent Test ◽  
Better Than

AbstractA connectionist model for decision support was constructed out of several back-propagation modules. Manifestations serve as input to the model; they may be real-valued, and the confidence in their measurement may be specified. The model produces as its output the posterior probability of disease. The model was trained on 1,000 cases taken from a simulated underlying population with three conditionally independent manifestations. The first manifestation had a linear relationship between value and posterior probability of disease, the second had a stepped relationship, and the third was normally distributed. An independent test set of 30,000 cases showed that the model was better able to estimate the posterior probability of disease (the standard deviation of residuals was 0.046, with a 95% confidence interval of 0.046-0.047) than a model constructed using logistic regression (with a standard deviation of residuals of 0.062, with a 95% confidence interval of 0.062-0.063). The model fitted the normal and stepped manifestations better than the linear one. It accommodated intermediate levels of confidence well.

scholarly journals Response of a mixed grass prairie to an extreme precipitation event

Ecosphere ◽  
2015 ◽  
Vol 6 (10) ◽  
pp. art172 ◽  
Author(s):  
Amy L. Concilio ◽  
Janet S. Prevéy ◽  
Peter Omasta ◽  
James O'Connor ◽  
Jesse B. Nippert ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Extreme Precipitation Event ◽  
Precipitation Event ◽  
Mixed Grass Prairie ◽  
Mixed Grass

scholarly journals Estimation and evaluation of COSMIC radio occultation excess phase using undifferenced measurements

2017 ◽  
Vol 10 (5) ◽  
pp. 1813-1821
Author(s):  
Pengfei Xia ◽  
Shirong Ye ◽  
Kecai Jiang ◽  
Dezhong Chen
Keyword(s):  
Radio Occultation ◽  
Weather Prediction ◽  
Lower Troposphere ◽  
Double Difference ◽  
Cosmic Radio ◽  
Processing Strategy ◽  
Single Difference ◽  
Excess Phase ◽  
Mean Square Errors ◽  
Better Than

Abstract. In the GPS radio occultation technique, the atmospheric excess phase (AEP) can be used to derive the refractivity, which is an important quantity in numerical weather prediction. The AEP is conventionally estimated based on GPS double-difference or single-difference techniques. These two techniques, however, rely on the reference data in the data processing, increasing the complexity of computation. In this study, an undifferenced (ND) processing strategy is proposed to estimate the AEP. To begin with, we use PANDA (Positioning and Navigation Data Analyst) software to perform the precise orbit determination (POD) for the purpose of acquiring the position and velocity of the mass centre of the COSMIC (The Constellation Observing System for Meteorology, Ionosphere and Climate) satellites and the corresponding receiver clock offset. The bending angles, refractivity and dry temperature profiles are derived from the estimated AEP using Radio Occultation Processing Package (ROPP) software. The ND method is validated by the COSMIC products in typical rising and setting occultation events. Results indicate that rms (root mean square) errors of relative refractivity differences between undifferenced and atmospheric profiles (atmPrf) provided by UCAR/CDAAC (University Corporation for Atmospheric Research/COSMIC Data Analysis and Archive Centre) are better than 4 and 3 % in rising and setting occultation events respectively. In addition, we also compare the relative refractivity bias between ND-derived methods and atmPrf profiles of globally distributed 200 COSMIC occultation events on 12 December 2013. The statistical results indicate that the average rms relative refractivity deviation between ND-derived and COSMIC profiles is better than 2 % in the rising occultation event and better than 1.7 % in the setting occultation event. Moreover, the observed COSMIC refractivity profiles from ND processing strategy are further validated using European Centre for Medium-Range Weather Forecasts (ECMWF) analysis data, and the results indicate that the undifferenced method reduces the noise level on the excess phase paths in the lower troposphere compared to the single-difference processing strategy.

scholarly journals Improvement on Leakage Current Performance of Semiconductor IC Packages by Eliminating ESD Events

2018 ◽  
Vol 6 (5) ◽  
Author(s):  
Frederick Ray Gomez
Keyword(s):  
Product Quality ◽  
Leakage Current ◽  
Integrated Circuit ◽  
Six Sigma ◽  
Electrostatic Discharge ◽  
Assembly Process ◽  
Technical Paper ◽  
High Leakage Current ◽  
Better Than

The technical paper discusses the reduction of high leakage current failures of semiconductor IC (integrated circuit) packages by eliminating the ESD (electrostatic discharge) events during assembly process and ensuring the appropriate machine grounding and ESD controls.  It is imperative to reduce or ideally eliminate the leakage current failures of the device to ensure the product quality, especially as the market becomes more challenging and demanding.  After implementation of the corrective and improvement actions, high leakage current occurrence was reduced from baseline of 5784 ppm to 1567 ppm, better than the six sigma goal of 4715 ppm.

scholarly journals Comparing soil carbon loss through respiration and leaching under extreme precipitation events in arid and semi-arid grasslands

2017 ◽  
Author(s):  
Ting Liu ◽  
Liang Wang ◽  
Xiaojuan Feng ◽  
Jinbo Zhang ◽  
Tian Ma ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Carbon ◽  
Extreme Precipitation ◽  
Dissolved Inorganic Carbon ◽  
Precipitation Event ◽  
Carbon Loss ◽  
Research Attention ◽  
Extreme Precipitation Events ◽  
Leaching Loss ◽  
Arid And Semiarid

Abstract. Respiration and leaching are two main processes responsible for soil carbon loss. While the former has received considerable research attention, studies examining leaching processes are limited especially in semiarid grasslands due to low precipitation. Climate change may increase the extreme precipitation event (EPE) frequency in arid and semiarid regions, potentially enhancing soil carbon loss through leaching and respiration. Here we incubated soil columns of three typical grassland soils from Inner Mongolia and Qinghai-Tibetan Plateau and examined the effect of simulated EPEs on soil carbon loss through respiration and leaching. EPEs induced transient increase of soil respiration, equivalent to 32 % and 72 % of the net ecosystem productivity (NEP) in the temperate grasslands (Xilinhot and Keqi) and 7 % in the alpine grasslands (Gangcha). By comparison, leaching loss of soil carbon accounted for 290 %, 120 % and 15 % of NEP at the corresponding sites, respectively, with dissolved inorganic carbon (DIC) as the main form of carbon loss in the alkaline soils. Moreover, DIC loss increased with re-occuring EPEs in the soil with the highest pH due to increased dissolution of soil carbonates and elevated contribution of dissolved CO2 from organic carbon degradation (indicated by DIC-δ13C). These results highlight that leaching loss of soil carbon (particularly DIC) is important in the regional carbon budget of arid and semiarid grasslands. With a projected increase of EPEs under climate change, soil carbon leaching processes and its influencing factors warrant better understanding and should be incorporated into soil carbon models when estimating carbon balance in grassland ecosystems.

scholarly journals Trend of Extreme Precipitation over Sumatera Island for 1981-2010

Agromet ◽  
2019 ◽  
Vol 33 (1) ◽  
pp. 41-51
Author(s):  
. Misnawati ◽  
Mega Perdanawanti
Keyword(s):  
Extreme Precipitation ◽  
Ecosystem Health ◽  
The Other ◽  
Economic Losses ◽  
Positive Trend ◽  
Climate Extreme ◽  
Precipitation Data ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Climate Events

Extreme climate events have significant impacts on various sectors such as agriculture, ecosystem, health and energy. The issue would lead to economic losses as well as social problems. This study aims to investigate the trend of extreme precipitation in Sumatera Island based on observed data during 30-year period, 1981–2010. There are ten indices of climate extreme as defined by ETCCDMI, which were tested in this study, including PRCPTOT, SDII, CDD, CWD, R10, R50, R95p, R99p, Rx1day and Rx5day. Then, the trend was analyzed based on the Mann-Kendall statistic, performed on the time series of precipitation data. The result shows that there was positive trend of extreme precipitation found in most stations over Sumatera, either statistically significant or insignificant. In each extreme precipitation indices, the number of observed stations indicating the insignificant change is higher than the significant one. This research also found that some indices including SDII, Rx1day, R50, R95p and R99p, showed a significantly-positive trend followed by a higher intensity of wetter and heavier events of extreme precipitation over Sumatera. On the other hand, the wet spell (CWD) index shows a negative trend (α=0.05).

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