scholarly journals Does More Moisture in the Atmosphere Lead to More Intense Rains?

2021 ◽  
Author(s):  
Agostino Manzato
Keyword(s):  
Precipitable Water ◽  
Rain Gauge ◽  
Rain Gauge Station ◽  
Scatter Plot ◽  
North East ◽  
Station Data ◽  
Gauge Station ◽  
Friuli Venezia Giulia

Abstract It is typically interpreted that more moisture in the atmosphere leads to more intense rains. This notion may be supported, for example, by taking a scatter plot between rain and column precipitable water. The present paper suggests, however, that the main consequence of intense rains with more moistures in the atmosphere is that there is a more chance to happen, rather than of an increase in the expected magnitude. This tendency equally applies to any rains above 1 mm/6h to a lesser extent. The result is derived from an analysis of 33 local rain–gauge station data and a shared sounding over Friuli Venezia Giulia, North–East Italy.

scholarly journals Intervention Analysis of Urbanization Effect on Rainfall Data at the Seoul Rain Gauge Station

2007 ◽  
Vol 40 (8) ◽  
pp. 629-641 ◽  
Author(s):  
Chul-Sang Yoo ◽  
Dae-Ha Kim ◽  
Sang-Hyoung Park ◽  
Byung-Su Kim ◽  
Chang-Yeol Park
Keyword(s):  
Rain Gauge ◽  
Rainfall Data ◽  
Intervention Analysis ◽  
Rain Gauge Station ◽  
Urbanization Effect ◽  
Gauge Station

Comparison of TRMM Data with Rain Gauge Observations in the Upper Huaihe River Basin of China

2013 ◽  
Vol 726-731 ◽  
pp. 3385-3390
Author(s):  
Josephine Osei-Kwarteng ◽  
Qiong Fang Li ◽  
Kwaku Amaning Adjei
Keyword(s):  
Hydrological Modeling ◽  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Rain Gauge Station ◽  
Huaihe River ◽  
Resources Management ◽  
Sustainable Water Resources Management ◽  
Rain Gage ◽  
Gauge Station ◽  
Trmm 3B42

In this study, the Tropical Rainfall Measuring Mission (TRMM) version 7 satellite rainfall product, TRMM 3B42 (V7), was validated using rain gauge measurements in the Upper Huaihe Basin, China. This validation was carried out at monthly and annual temporal scales for an 11-year period using four selected grids with six, four, two and one rain gauge station (s) located within the TRMM grid respectively; the rain gage measurements for grids with more than one rain gauge were averaged. This study found that the validation of the TRMM dataset in grids where there were adequate rain gauge were present to capture the distributed and stochastic nature of rainfall with very good correlation (0.87-0.94) and with very little relative bias when the rain gage accumulations were compared with the TRMM estimates. From the study we found that the TRMM dataset can be used as precipitation input for hydrological modeling at monthly and annual scales for sustainable water resources management in the Upper Huaihe River and even in un-gaged or sparsely gaged basins in other parts of the world.

scholarly journals Contamination Vulnerability Analysis of Watershed for Water Quality Monitoring

2016 ◽  
Vol 20 (1) ◽  
Author(s):  
Widyastuti Widyastuti ◽  
Slamet Suprayogi
Keyword(s):  
Water Quality ◽  
Land Surface ◽  
Water Quality Monitoring ◽  
Vulnerability Index ◽  
Rain Gauge ◽  
Vulnerability Analysis ◽  
Quality Monitoring ◽  
Neural Network Modeling ◽  
Rain Gauge Station ◽  
Gauge Station

This research is an early step to determine the location of rain gauge station for artificial neural network modeling. The implementation of this model is very useful for water quality monitoring. The objectives of this study are: 1) to study the distribution of watershed parameter, that are average annual precipitation, land use and land-surface slope, 2) to conduct vulnerability analysis of watershed contamination, 3) to determine the location of rain gauge station. The study was performed by weighing and rating method of watershed parameters. The vulnerability degree of watershedtocontaminationispresentedasvulnerabilityindex.Thisindexisdeterminedbyoverallsumofallmultiplication between score and weigh number of each parameter. All data manipulation and data analysis were performed by using Geographic Information System (ArcView version by 3.2). The vulnerability of watershed contamination map had been generated using overlay operation of parameters. The results show that vulnerability index are varies between 10 up to 40 intervals. Hence, the indexes were categorized into three levels of watershed vulnerability, namely low (10 – 20), moderate (20 – 30) and high (30 – 40). It is found that the study area covered more by high vulnerability of watershed to contamination. The zoning of watershed vulnerability meant to determine the rain gauge location. There are three rain gauge stations on the area that they are in a high vulnerability level, whereas the other vulnerability level area has one rain gauge station. Each level of vulnerability area is able to represent the source of contaminant that it maybe influence the water quality of Gajahwong river.

scholarly journals Accuracy assessment and error cause analysis of GPM (V06) in Xiangjiang river catchment

2021 ◽  
Author(s):  
Bingru Tian ◽  
Hua Chen ◽  
Jialing Wang ◽  
Chong-Yu Xu
Keyword(s):  
Rain Gauge ◽  
Precipitation Intensity ◽  
Intensity Level ◽  
Total Precipitation ◽  
Rain Gauge Station ◽  
Xiangjiang River ◽  
River Catchment ◽  
Satellite Precipitation ◽  
Gauge Station ◽  
The Impact

Abstract Application potential and development prospect of satellite precipitation products such as Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM) have promising implications. This study discusses causes of spatiotemporal differences on GPM data through the following steps: Initially, calculate bias between satellite-based data and rain gauge data of Xiangjiang river catchment to assess the accuracy of GPM (06E, 06 L, and 06F) products. Second, total errors of satellite precipitation data are divided into hit bias (HBIAS: precipitation detected by both GPM and rain gauge station), missed precipitation (MBIAS: precipitation detected only by rain gauge station), and false precipitation (FBIAS: precipitation detected only by GPM). Third, evaluate the impact of precipitation intensity and total precipitation on accuracy of GPM data and their influence on three error components. Several conclusions are drawn from the results above: (1) Satellite-based precipitation measurements perform better on a larger temporal-spatial scale. (2) The accuracy of TRMM and GPM data displays significant variances on space and time. Season, precipitation intensity, and total precipitation are main factors influencing the accuracy of TRMM and GPM data. (3) The detection capability of satellite products change with seasonal variation and different precipitation intensity level.

scholarly journals Toward a practical approach for ergodicity analysis

2015 ◽  
Vol 2 (5) ◽  
pp. 1425-1446 ◽  
Author(s):  
H. Wang ◽  
C. Wang ◽  
Y. Zhao ◽  
X. Lin ◽  
C. Yu
Keyword(s):  
Time Series ◽  
Yellow River ◽  
Rain Gauge ◽  
Ergodic Property ◽  
Practical Approach ◽  
Function Evaluation ◽  
Rain Gauge Station ◽  
Gauge Station ◽  
Mean Ergodicity ◽  
The Mean

Abstract. It is of importance to perform hydrological forecast using a finite hydrological time series. Most time series analysis approaches presume a data series to be ergodic without justifying this assumption. This paper presents a practical approach to analyze the mean ergodic property of hydrological processes by means of autocorrelation function evaluation and Augmented Dickey Fuller test, a radial basis function neural network, and the definition of mean ergodicity. The mean ergodicity of precipitation processes at the Lanzhou Rain Gauge Station in the Yellow River basin, the Ankang Rain Gauge Station in Han River, both in China, and at Newberry, MI, USA are analyzed using the proposed approach. The results indicate that the precipitations of March, July, and August in Lanzhou, and of May, June, and August in Ankang have mean ergodicity, whereas, the precipitation of any other calendar month in these two rain gauge stations do not have mean ergodicity. The precipitation of February, May, July, and December in Newberry show ergodic property, although the precipitation of each month shows a clear increasing or decreasing trend.

scholarly journals End of the Day (EOD) Judgment for Daily Rain-Gauge Data

Atmosphere ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 772 ◽  
Author(s):  
Akiyo Yatagai ◽  
Mio Maeda ◽  
Sunilkumar Khadgarai ◽  
Minami Masuda ◽  
Pingping Xie
Keyword(s):  
Daily Precipitation ◽  
Current Method ◽  
Rain Gauge ◽  
Horizontal Resolution ◽  
Observation Time ◽  
Specific Domain ◽  
Rain Gauge Data ◽  
Station Data ◽  
Gauge Station ◽  
The Difference

Several versions of Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation of Extreme Events (APHRODITE-2) have been released for analyzing rain-gauge-based daily precipitation. APHRODITE-2 constitutes an improvement compared with the previous versions for evaluating extreme precipitation. One advantage of APHRODITE-2 products (versions 1801R1 and 1901) over APHRODITE-1 products is the ability to ensure uniformity in the daily accumulation period (end of the day, EOD) used in a specific domain. To create these EOD segregated or EOD adjusted products, we applied an EOD judgment scheme using multi-satellite merged precipitation products CMORPH V1.0 and ERA-Interim reanalysis. The novelty of the current methodology was tested against rain-gauge datasets with known EOD information. Despite the difference in horizontal resolution, ERA-Interim shows similar EOD detection performance to CMORPH. However, CMORPH showed better performance over India than ERA-Interim. The current method has potential to judge EOD of rain-gauge station data with an unknown observation time. Having prior EOD information as metadata is very important for gridded datasets as well as station data. Here, we also present deterministic/estimated EOD that we used for V1801R1 over Monsoon Asia.

scholarly journals Analysis of intense rainfall events on Madeira Island during the 2009/2010 winter

2012 ◽  
Vol 12 (7) ◽  
pp. 2225-2240 ◽  
Author(s):  
F. T. Couto ◽  
R. Salgado ◽  
M. J. Costa
Keyword(s):  
Precipitable Water ◽  
Heavy Precipitation ◽  
Rain Gauge ◽  
Horizontal Resolution ◽  
Pressure System ◽  
Orographic Effects ◽  
Madeira Island ◽  
High Rainfall ◽  
High Precipitation Events ◽  
Precipitation Events

Abstract. This paper constitutes a step towards the understanding of some characteristics associated with high rainfall amounts and flooding on Madeira Island. The high precipitation events that occurred during the winter of 2009/2010 have been considered with three main goals: to analyze the main atmospheric characteristics associated with the events; to expand the understanding of the interaction between the island and the atmospheric circulations, mainly the effects of the island on the generation or intensification of orographic precipitation; and to evaluate the performance of high resolution numerical modeling in simulating and forecasting heavy precipitation events over the island. The MESO-NH model with a horizontal resolution of 1 km is used, as well as rain gauge data, synoptic charts and measurements of precipitable water obtained from the Atmospheric InfraRed Sounder (AIRS). The results confirm the influence of the orographic effects on precipitation over Madeira as well as the tropical–extratropical interaction, since atmospheric rivers were detected in six out of the seven cases analyzed, acting as a low level moisture supplier, which together with the orographic lifting induced the high rainfall amounts. Only in one of the cases the presence of a low pressure system was identified over the archipelago.

scholarly journals Cloudburst events observed over Uttarakhand during monsoon season 2017 and their analysis

MAUSAM ◽  
2022 ◽  
Vol 73 (1) ◽  
pp. 91-104
Author(s):  
BIKRAM SINGH ◽  
ROHIT THAPLIYAL
Keyword(s):  
Flash Flood ◽  
Monsoon Season ◽  
Convective Available Potential Energy ◽  
Precipitable Water ◽  
Interval Data ◽  
Rain Gauge ◽  
Thermodynamic Conditions ◽  
North Pakistan ◽  
June July ◽  
Head Bay Of Bengal

Cloudburst is an extreme weather event characterised by the occurrence of a large amount of rainfall over a small area within a short span of time with a rainfall of 100 mm or more in one hour. It is responsible for flash flood, inundation of low lying areas and landslides in hills causing extensive damages to life and property. During monsoon season 2017 five number of cloudburst events are observed over Uttarakhand and analysed. Self Recording Rain Gauge (SRRG) and 15 minutes interval data from the newly installed General Packet Radio Service (GPRS) based Automatic Weather Station (AWS) are able to capture the cloudburst events over some areas in Uttarakhand. In this paper, an attempt has been made to find out the significant synoptic and thermodynamic conditions associated with the occurrence of the cloudburst events in Uttarakhand. These 5 cases of cloudburst events that are captured during the month of June, July and August 2017 in Uttarakhand are studied in detail. Synoptically, it is observed that the existence of trough at mean sea level from Punjab to head Bay of Bengal running close to Uttarakhand, the movement of Western Disturbance over north Pakistan and adjoining Jammu & Kashmir and existence of cyclonic circulation over north Rajasthan and neighbourhood are favourable conditions. Also, the presence of strong south-westerly wind flow from the Arabian Sea across West Rajasthan and Haryana on upper air charts are found during these events. Thermodynamically, the Convective Available Potential Energy (CAPE) is found to be high (more than 1100 J/Kg) during most of the cases and vertically integrated precipitable water content (PWC) is more than 55mm. The GPRS based AWS system can help in prediction of the cloud burst event over the specified location with a lead time upto half to one hour in association with radar products.  

Sign in / Sign up

Export Citation Format

Share Document