scholarly journals Subpixel-Scale Rainfall Variability and the Effects on Separation of Radar and Gauge Rainfall Errors

2007 ◽  
Vol 8 (6) ◽  
pp. 1348-1363 ◽  
Author(s):  
Yu Zhang ◽  
Thomas Adams ◽  
James V. Bonta
Keyword(s):  
Spatial Correlation ◽  
Rainfall Variability ◽  
Domain Size ◽  
Error Variance ◽  
Rainfall Analysis ◽  
Rain Gauges ◽  
Size Number ◽  
Proportional Contribution ◽  
Error Terms ◽  
Areal Rainfall

Abstract This paper presents an extended error variance separation method (EEVS) that allows explicit partitioning of the variance of the errors in gauge- and radar-based representations of areal rainfall. The implementation of EEVS demonstrated in this study combines a kriging scheme for estimating areal rainfall from gauges with a sampling method for determining the correlation between the gauge- and radar-related errors. On the basis of this framework, this study examines scale- and pixel-dependent impacts of subpixel-scale rainfall variability on the perceived partitioning of error variance for four conterminous Hydrologic Rainfall Analysis Project (HRAP) pixels in central Ohio with data from Next-Generation Weather Radar (NEXRAD) stage III product and from 11 collocated rain gauges as input. Application of EEVS for 1998–2001 yields proportional contribution of two error terms for July and October for each HRAP pixel and for two fictitious domains containing the gauges (4 and 8 km in size). The results illustrate the importance of considering subpixel variation of spatial correlation and how it varies with the size of domain size, number of gauges, and the subpixel locations of gauges. Further comparisons of error variance separation (EVS) and EEVS across pixels results suggest that accounting for structured variations in the spatial correlation under 8 km might be necessary for more accurate delineation of domain-dependent partitioning of error variance, and especially so for the summer months.

Commercial microwave links instead of rain gauges: fiction or reality?

2014 ◽  
Vol 71 (1) ◽  
pp. 31-37 ◽  
Author(s):  
Martin Fencl ◽  
Jörg Rieckermann ◽  
Petr Sýkora ◽  
David Stránský ◽  
Vojtěch Bareš
Keyword(s):  
Rainfall Variability ◽  
A Priori ◽  
Rain Gauges ◽  
Precipitation Estimates ◽  
Spatio Temporal ◽  
Areal Rainfall ◽  
Quantitative Precipitation Estimates ◽  
Commercial Microwave Links ◽  
Unique Dataset

Commercial microwave links (MWLs) were suggested about a decade ago as a new source for quantitative precipitation estimates (QPEs). Meanwhile, the theory is well understood and rainfall monitoring with MWLs is on its way to being a mature technology, with several well-documented case studies, which investigate QPEs from multiple MWLs on the mesoscale. However, the potential of MWLs to observe microscale rainfall variability, which is important for urban hydrology, has not been investigated yet. In this paper, we assess the potential of MWLs to capture the spatio-temporal rainfall dynamics over small catchments of a few square kilometres. Specifically, we investigate the influence of different MWL topologies on areal rainfall estimation, which is important for experimental design or to a priori check the feasibility of using MWLs. In a dedicated case study in Prague, Czech Republic, we collected a unique dataset of 14 MWL signals with a temporal resolution of a few seconds and compared the QPEs from the MWLs to reference rainfall from multiple rain gauges. Our results show that, although QPEs from most MWLs are probably positively biased, they capture spatio-temporal rainfall variability on the microscale very well. Thus, they have great potential to improve runoff predictions. This is especially beneficial for heavy rainfall, which is usually decisive for urban drainage design.

scholarly journals A Field Experiment on the Small-Scale Variability of Rainfall Based on a Network of Micro Rain Radars and Rain Gauges

2015 ◽  
Vol 54 (1) ◽  
pp. 243-255 ◽  
Author(s):  
Yong Chen ◽  
Huizhi Liu ◽  
Junling An ◽  
Ulrich Görsdorf ◽  
Franz H. Berger
Keyword(s):  
Spatial Scales ◽  
Rainfall Variability ◽  
Summer Rainfall ◽  
Small Scale ◽  
Precipitation Radar ◽  
River Catchment ◽  
Rain Gauges ◽  
Straight Line ◽  
Areal Rainfall ◽  
Xilin River Catchment

AbstractSmall-scale summer rainfall variability in a semiarid zone was studied by deploying five vertically pointing Micro Rain Radars (MRRs) along a nearly straight line and by using 12 rain gauges in the study area of the Xilin River catchment in China. The spatial scales of 4 and 9 km correspond to the resolution of precipitation radar and rainfall products from satellites. The dataset of the MRRs and rain gauges covers two months in the summer of 2009. Three parameters, that is, spatial correlation, intermittency, and the coefficient of variation (CV), were used to describe the rainfall variability as based on the data from the MRRs and rain gauges. The probability of partial beamfilling in a 4-km (9 km) pixel over a 30-min temporal scale was 17%–20% (28%–37%). More accurate equipment can measure lower rainfall intermittency. For scales of 4 and 9 km, the median CV of the accumulation times that were longer than 3 h with rainfall > 1 mm was 0.17–0.42. The accuracy of areal rainfall measured by different quantities of equipment was also evaluated. One MRR was sufficient for measuring the daily areal rainfall at a 4-km scale, with a fraction of prediction within a factor of 2 of observations of 1.0 and a correlation coefficient of ≥0.58 when daily mean rainfall was >1 mm.

scholarly journals A Comparison of Various Correction and Blending Techniques for Creating an Improved Satellite-Gauge Rainfall Dataset over Australia

2022 ◽  
Vol 14 (2) ◽  
pp. 261
Author(s):  
Zhi-Weng Chua ◽  
Yuriy Kuleshov ◽  
Andrew B. Watkins ◽  
Suelynn Choy ◽  
Chayn Sun
Keyword(s):  
High Performance ◽  
Error Variance ◽  
Rain Gauge ◽  
Rainfall Analysis ◽  
Rain Gauges ◽  
The World ◽  
Potential Applicability ◽  
Complementary Nature ◽  
Improved Accuracy ◽  
Specific Correction

Satellites offer a way of estimating rainfall away from rain gauges which can be utilised to overcome the limitations imposed by gauge density on traditional rain gauge analyses. In this study, Australian station data along with the Japan Aerospace Exploration Agency’s (JAXA) Global Satellite Mapping of Precipitation (GSMaP) and the Bureau of Meteorology’s (BOM) Australian Gridded Climate Dataset (AGCD) rainfall analysis are combined to develop an improved satellite-gauge rainfall analysis over Australia that uses the strengths of the respective data sources. We investigated a variety of correction and blending methods with the aim of identifying the optimal blended dataset. The correction methods investigated were linear corrections to totals and anomalies, in addition to quantile-to-quantile matching. The blending methods tested used weights based on the error variance to MSWEP (Multi-Source Weighted Ensemble Product), distance to the closest gauge, and the error from a triple collocation analysis to ERA5 and Soil Moisture to Rain. A trade-off between away-from- and at-station performances was found, meaning there was a complementary nature between specific correction and blending methods. The most high-performance dataset was one corrected linearly to totals and subsequently blended to AGCD using an inverse error variance technique. This dataset demonstrated improved accuracy over its previous version, largely rectifying erroneous patches of excessive rainfall. Its modular use of individual datasets leads to potential applicability in other regions of the world.

scholarly journals Assessment of Snowfall Accumulation from Satellite and Reanalysis Products Using SNOTEL Observations in Alaska

2021 ◽  
Vol 13 (15) ◽  
pp. 2922
Author(s):  
Yang Song ◽  
Patrick D. Broxton ◽  
Mohammad Reza Ehsani ◽  
Ali Behrangi
Keyword(s):  
Snow Water Equivalent ◽  
Stage Iv ◽  
Microwave Remote Sensing ◽  
Rain Gauge ◽  
Snow Accumulation ◽  
Correction Factors ◽  
Rainfall Analysis ◽  
Rain Gauges ◽  
Snow Properties ◽  
Precipitation Estimates

The combination of snowfall, snow water equivalent (SWE), and precipitation rate measurements from 39 snow telemetry (SNOTEL) sites in Alaska were used to assess the performance of various precipitation products from satellites, reanalysis, and rain gauges. Observation of precipitation from two water years (2018–2019) of a high-resolution radar/rain gauge data (Stage IV) product was also utilized to give insights into the scaling differences between various products. The outcomes were used to assess two popular methods for rain gauge undercatch correction. It was found that SWE and precipitation measurements at SNOTELs, as well as precipitation estimates based on Stage IV data, are generally consistent and can provide a range within which other products can be assessed. The time-series of snowfall and SWE accumulation suggests that most of the products can capture snowfall events; however, differences exist in their accumulation. Reanalysis products tended to overestimate snow accumulation in the study area, while the current combined passive microwave remote sensing products (i.e., IMERG-HQ) underestimate snowfall accumulation. We found that correction factors applied to rain gauges are effective for improving their undercatch, especially for snowfall. However, no improvement in correlation is seen when correction factors are applied, and rainfall is still estimated better than snowfall. Even though IMERG-HQ has less skill for capturing snowfall than rainfall, analysis using Taylor plots showed that the combined microwave product does have skill for capturing the geographical distribution of snowfall and precipitation accumulation; therefore, bias adjustment might lead to reasonable precipitation estimates. This study demonstrates that other snow properties (e.g., SWE accumulation at the SNOTEL sites) can complement precipitation data to estimate snowfall. In the future, gridded SWE and snow depth data from GlobSnow and Sentinel-1 can be used to assess snowfall and its distribution over broader regions.

scholarly journals Rainfall spatio-temporal correlation and intermittency structure from micro-γ to meso-β scale in the Netherlands

2021 ◽  
Author(s):  
Thomas C. van Leth ◽  
Hidde Leijnse ◽  
Aart Overeem ◽  
Remko Uijlenhoet
Keyword(s):  
The Netherlands ◽  
Spatial Scales ◽  
Rainfall Variability ◽  
Temporal Structure ◽  
Temporal Correlation ◽  
Exponential Model ◽  
Rain Gauges ◽  
Wide Range ◽  
Spatio Temporal ◽  
Two Parameter

AbstractWe investigate the spatio-temporal structure of rainfall at spatial scales from 7m to over 200 km in the Netherlands. We used data from two networks of laser disdrometers with complementary interstation distances in two Dutch cities (comprising five and six disdrometers, respectively) and a Dutch nationwide network of 31 automatic rain gauges. The smallest aggregation interval for which raindrop size distributions were collected by the disdrometers was 30 s, while the automatic rain gauges provided 10-min rainfall sums. This study aims to supplement other micro-γ investigations (usually performed in the context of spatial rainfall variability within a weather radar pixel) with new data, while characterizing the correlation structure across an extended range of scales. To quantify the spatio-temporal variability, we employ a two-parameter exponential model fitted to the spatial correlograms and characterize the parameters of the model as a function of the temporal aggregation interval. This widely used method allows for a meaningful comparison with seven other studies across contrasting climatic settings all around the world. We also separately analyzed the intermittency of the rainfall observations. We show that a single parameterization, consisting of a two-parameter exponential spatial model as a function of interstation distance combined with a power-law model for decorrelation distance as a function of aggregation interval, can coherently describe rainfall variability (both spatial correlation and intermittency) across a wide range of scales. Limiting the range of scales to those typically found in micro-γ variability studies (including four of the seven studies to which we compare our results) skews the parameterization and reduces its applicability to larger scales.

scholarly journals Rainfall trend analysis using Mann-Kendall and Sen’s slope estimator test in West Kalimantan

2021 ◽  
Vol 893 (1) ◽  
pp. 012006
Author(s):  
F Aditya ◽  
E Gusmayanti ◽  
J Sudrajat
Keyword(s):  
Climate Change ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Sen’S Slope Estimator ◽  
West Kalimantan ◽  
Rainfall Analysis ◽  
Sen’S Slope ◽  
Rainfall Trends ◽  
Slope Estimator ◽  
The Impact

Abstract Climate change has been a prominent issue in the last decade. Climate change on a global scale does not necessarily have the same effect in different regions. Rainfall is a crucial weather element related to climate change. Rainfall trends analysis is an appropriate step in assessing the impact of climate change on water availability and food security. This study examines rainfall variations and changes at West Kalimantan, focusing on Mempawah and Kubu Raya from 2000-2019. The Mann-Kendall (MK) and Sen's Slope estimator test, which can determine rainfall variability and long-term monotonic trends, were utilized to analyze 12 rainfall stations. The findings revealed that the annual rainfall pattern prevailed in all locations. Mempawah region tends to experience a downward trend, while Kubu Raya had an upward trend. However, a significant trend (at 95% confidence level) was identified in Sungai Kunyit with a slope value of -33.20 mm/year. This trend indicates that Sungai Kunyit will become drier in the future. The results of monthly rainfall analysis showed that significant upward and downward trends were detected in eight locations. Rainfall trends indicate that climate change has occurred in this region.

Domain size, layer number and morphology control for graphene grown by chemical vapor deposition

2017 ◽  
Vol 10 (04) ◽  
pp. 1730003 ◽  
Author(s):  
Ruiwen Xue ◽  
Irfan H. Abidi ◽  
Zhengtang Luo
Keyword(s):  
Chemical Vapor Deposition ◽  
Vapor Deposition ◽  
Chemical Vapor ◽  
Domain Size ◽  
Past Research ◽  
Production Methods ◽  
The Past ◽  
Number Of Layers ◽  
Size Number ◽  
Wide Range

Over the past a few years, high-quality graphene preparation has been evolved from low-yield micromechanical exfoliation in including a wide range of production methods, in particular by chemical vapor deposition (CVD). Here, we review the state-of-the-art on synthesis of graphene using CVD method and the strategies to control the graphene grain size, number of layers and morphology, mainly focusing on the graphene growth that uses Cu as substrate. We highlight the success of the past research in the field and provide a review of the methods that were used for such controlled synthesis.

scholarly journals Analysis of the Behavior of Daily Maximum Rainfall within the Department of Atlántico, Colombia

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2453
Author(s):  
Orlando M. Viloria-Marimón ◽  
Álvaro González-Álvarez ◽  
Javier A. Mouthón-Bello
Keyword(s):  
Time Series ◽  
Daily Rainfall ◽  
Information Criterion ◽  
Rain Gauge ◽  
Caribbean Region ◽  
Daily Maximum ◽  
Maximum Rainfall ◽  
Rain Gauges ◽  
Stationary Conditions ◽  
Areal Rainfall

In the Colombian Caribbean region, there are few studies that evaluated the behavior of one of the most commonly used variables in hydrological analyses: the maximum daily rainfall (Pmax-24h). In this study, multiannual Pmax-24h time series from 19 rain gauges, located within the department of Atlántico, were analyzed to (a) determine possible increasing/decreasing trends over time, (b) identify regions with homogeneous behavior of Pmax-24h, (c) assess whether the time series are better suited under either a stationary or non-stationary frequency analysis, (d) generate isohyetal maps under stationary, non-stationary, and mixed conditions, and (e) evaluate the isohyetal maps by means of the calculation of areal rainfall (Pareal) in nine watersheds. In spite of the presence of both increasing and decreasing trends, only the Puerto Giraldo rain gauge showed a significant decreasing trend. Also, three regions (east, central, and west) with similar Pmax-24h behavior were identified. According to the Akaike information criterion test, 79% of the rain gauges showed better fit under stationary conditions. Finally, statistical analysis revealed that, under stationary conditions, the errors in the calculation of Pareal were more frequent, while the magnitude of the errors was larger under non-stationary conditions, especially in the central–south region.

scholarly journals Evaluation of X-Band Dual-Polarization Radar-Rainfall Estimates from OLYMPEX

2019 ◽  
Vol 20 (9) ◽  
pp. 1941-1959 ◽  
Author(s):  
Yagmur Derin ◽  
Emmanouil Anagnostou ◽  
Marios Anagnostou ◽  
John Kalogiros
Keyword(s):  
Rainfall Variability ◽  
Dual Polarization ◽  
Significant Information ◽  
Radar Rainfall ◽  
Rain Gauges ◽  
X Band ◽  
Error Characterization ◽  
Median Volume ◽  
Multiparameter Measurements

Abstract The difficulty of representing high rainfall variability over mountainous areas using ground-based sensors is an open problem in hydrometeorology. Observations from locally deployed dual-polarization X-band radar have the advantage of providing multiparameter measurements near ground that carry significant information useful for estimating drop size distribution (DSD) and surface rainfall rate. Although these measurements are at fine spatiotemporal scale and are less inhibited by complex topography than operational radar network observations, uncertainties in their estimates necessitate error characterization based upon in situ measurements. During November 2015–February 2016, a dual-polarized Doppler on Wheels (DOW) X-band radar was deployed on the Olympic Peninsula of Washington State as part of NASA’s Olympic Mountain Experiment (OLYMPEX). In this study, rain gauges and disdrometers from a dense network positioned within 40 km of DOW are used to evaluate the self-consistency and accuracy of the attenuation and brightband/vertical profile corrections, and rain microphysics estimation by SCOP-ME, an algorithm that uses optimal parameterization and best-fitted functions of specific attenuation coefficients and DSD parameters with radar polarimetric measurements. In addition, the SCOP-ME precipitation microphysical retrievals of median volume diameter D0 and normalized intercept parameter NW are evaluated against corresponding parameters derived from the in situ disdrometer spectra observations.

Mean areal rainfall improvement using radar rainfall estimation technique by considering geographic character for dam operation

2020 ◽  
Author(s):  
Seongsim Yoon ◽  
Hongjoon Shin ◽  
Gian Choi
Keyword(s):  
Nuclear Power ◽  
Heavy Rainfall ◽  
Mountainous Area ◽  
Accuracy Improvement ◽  
Radar Rainfall ◽  
Rain Gauges ◽  
Dam Operation ◽  
Areal Precipitation ◽  
Areal Rainfall ◽  
Dam Inflow

<p>Efficiently dam operation is necessary to secure water resources and to respond to floods. For the dam operation, the amount of dam inflow should be accurately calculate. Rainfall information is important for the amount of dam inflow estimation and prediction therefore rainfall should be observed accurately. However, it is difficult to observe the rainfall due to poor density of rain gauges because of the dam is located in the mountainous region. Moreover, ground raingauges are limitted to localized heavy rainfall, which is increasing in frequency due to climate changes. The advantage of radar is that it can obtain high-resolution grid rainfall data because radar can observe the spatial distribution of rainfall. The radar rainfall are less accurate than ground gauge data. For the accuracy improvement of radar rainfall, many adjustment methods using ground gauges, have been suggested. For dam basin, because the density of ground gauge is low, there are limitations when apply the bias adjustment methods. Especially, the localized heavy rainfall occurred in the mountainous area depending on the topography. In this study, we will develop a radar rainfall adjustment method considering the orographic effect. The method considers the elevation to obtain kriged rainfall and apply conditional merging skill for the accuracy improvement of the radar rainfall. Based on this method, we are going to estimate the mean areal precipitation for hydropower dam basin. And, we will compare and evaluate the results of various adjustment methods in term of mean areal precipitation and dam inflow.</p><p>This work was supported by KOREA HYDRO & NUCLEAR POWER CO., LTD (No. 2018-Tech-20)</p><div> </div><div> </div>

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