Errors and Uncertainties in Microwave Link Rainfall Estimation Explored Using Drop Size Measurements and High-Resolution Radar Data

2010 ◽  
Vol 11 (6) ◽  
pp. 1330-1344 ◽  
Author(s):  
Hidde Leijnse ◽  
Remko Uijlenhoet ◽  
Alexis Berne
Keyword(s):  
High Resolution ◽  
Power Law ◽  
Radar Data ◽  
Mean Bias Error ◽  
Bias Error ◽  
Error Statistics ◽  
Link Length ◽  
Taylor’S Hypothesis ◽  
High Resolution Radar ◽  
Microwave Link

Abstract Microwave links can be used for the estimation of path-averaged rainfall by using either the path-integrated attenuation or the difference in attenuation of two signals with different frequencies and/or polarizations. Link signals have been simulated using measured time series of raindrop size distributions (DSDs) over a period of nearly 2 yr, in combination with wind velocity data and Taylor’s hypothesis. For this purpose, Taylor’s hypothesis has been tested using more than 1.5 yr of high-resolution radar data. In terms of correlation between spatial and temporal profiles of rainfall intensities, the validity of Taylor’s hypothesis quickly decreases with distance. However, in terms of error statistics, the hypothesis is seen to hold up to distances of at least 10 km. Errors and uncertainties (mean bias error and root-mean-square error, respectively) in microwave link rainfall estimates due to spatial DSD variation are at a minimum at frequencies (and frequency combinations) where the power-law relation for the conversion to rainfall intensity is close to linear. Errors generally increase with link length, whereas uncertainties decrease because of the decrease of scatter about the retrieval relations because of averaging of spatially variable DSDs for longer links. The exponent of power-law rainfall retrieval relations can explain a large part of the variation in both bias and uncertainty, which means that the order of magnitude of these error statistics can be predicted from the value of this exponent, regardless of the link length.

scholarly journals Effect of discharge and upstream jam angle on the flow distribution beneath a simulated ice jam

2019 ◽  
Vol 46 (5) ◽  
pp. 413-423 ◽  
Author(s):  
Baafour Nyantekyi-Kwakye ◽  
Tanzim Ahmed ◽  
Shawn P. Clark ◽  
Mark F. Tachie ◽  
Karen Dow
Keyword(s):  
Pressure Gradient ◽  
Power Law ◽  
Reynolds Shear Stress ◽  
Measurement Techniques ◽  
Adverse Pressure Gradient ◽  
Mean Bias Error ◽  
Bias Error ◽  
Particle Image Velocimetry System ◽  
Ice Jam ◽  
Two Parameter

The velocity field beneath simulated rough ice jams under various upstream jam angles and discharge were investigated using a particle image velocimetry system. Three discharges were examined at 2.3 L/s, 3.4 L/s, and 4.0 L/s and two upstream ice jam angles were tested at 4° and 6°. Increasing the discharge resulted in high turbulence production beneath the jam. The adverse pressure gradient exerted on the flow increased the levels of the Reynolds shear stress. The measured velocities beneath the jam were used to assess the performances of three traditional field measurement techniques as well as the validity of the two-parameter power law. The two-point measurement technique performed remarkably well with the least mean bias error of 2.0%. The error associated with the different techniques showed their inability to accurately predict the average velocity under high discharge. The two-parameter power law accurately predicted velocity profiles within the equilibrium section of the jam, but failed within the boundary layers when the flow was subjected to a pressure gradient.

scholarly journals A 16-year dataset (2000–2015) of high-resolution (3 h, 10 km) global surface solar radiation

2019 ◽  
Vol 11 (4) ◽  
pp. 1905-1915 ◽  
Author(s):  
Wenjun Tang ◽  
Kun Yang ◽  
Jun Qin ◽  
Xin Li ◽  
Xiaolei Niu
Keyword(s):  
High Resolution ◽  
Solar Radiation ◽  
Radiant Energy ◽  
Reanalysis Data ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Mean Bias Error ◽  
Bias Error ◽  
Surface Solar Radiation ◽  
Global Surface

Abstract. The recent release of the International Satellite Cloud Climatology Project (ISCCP) HXG cloud products and new ERA5 reanalysis data enabled us to produce a global surface solar radiation (SSR) dataset: a 16-year (2000–2015) high-resolution (3 h, 10 km) global SSR dataset using an improved physical parameterization scheme. The main inputs were cloud optical depth from ISCCP-HXG cloud products; the water vapor, surface pressure and ozone from ERA5 reanalysis data; and albedo and aerosol from Moderate Resolution Imaging Spectroradiometer (MODIS) products. The estimated SSR data were evaluated against surface observations measured at 42 stations of the Baseline Surface Radiation Network (BSRN) and 90 radiation stations of the China Meteorological Administration (CMA). Validation against the BSRN data indicated that the mean bias error (MBE), root mean square error (RMSE) and correlation coefficient (R) for the instantaneous SSR estimates at 10 km scale were −11.5 W m−2, 113.5 W m−2 and 0.92, respectively. When the estimated instantaneous SSR data were upscaled to 90 km, its error was clearly reduced, with RMSE decreasing to 93.4 W m−2 and R increasing to 0.95. For daily SSR estimates at 90 km scale, the MBE, RMSE and R at the BSRN were −5.8 W m−2, 33.1 W m−2 and 0.95, respectively. These error metrics at the CMA radiation stations were 2.1 W m−2, 26.9 W m−2 and 0.95, respectively. Comparisons with other global satellite radiation products indicated that our SSR estimates were generally better than those of the ISCCP flux dataset (ISCCP-FD), the global energy and water cycle experiment surface radiation budget (GEWEX-SRB), and the Earth's Radiant Energy System (CERES). Our SSR dataset will contribute to the land-surface process simulations and the photovoltaic applications in the future. The dataset is available at  https://doi.org/10.11888/Meteoro.tpdc.270112 (Tang, 2019).

scholarly journals Precipitation and Fatal Motor Vehicle Crashes: Continental Analysis with High-Resolution Radar Data

2019 ◽  
Vol 100 (8) ◽  
pp. 1453-1461 ◽  
Author(s):  
Scott E. Stevens ◽  
Carl J. Schreck ◽  
Shubhayu Saha ◽  
Jesse E. Bell ◽  
Kenneth E. Kunkel
Keyword(s):  
United States ◽  
High Resolution ◽  
Motor Vehicle ◽  
Radar Data ◽  
The United States ◽  
Motor Vehicle Crashes ◽  
Vehicle Crashes ◽  
Fatal Crash ◽  
Fatal Crashes ◽  
High Resolution Radar

AbstractMotor vehicle crashes remain a leading cause of accidental death in the United States, and weather is frequently cited as a contributing factor in fatal crashes. Previous studies have investigated the link between these crashes and precipitation typically using station-based observations that, while providing a good estimate of the prevailing conditions on a given day or hour, often fail to capture the conditions present at the actual time and location of a crash. Using a multiyear, high-resolution radar reanalysis and information on 125,012 fatal crashes spanning the entire continental United States over a 6-yr period, we find that the overall risk of a fatal crash increases by approximately 34% during active precipitation. The risk is significant in all regions of the continental United States, and it is highest during the morning rush hour and during the winter months.

scholarly journals Some Considerations for the Use of High-Resolution Mobile Radar Data in Tornado Intensity Determination

2014 ◽  
Vol 29 (4) ◽  
pp. 799-827 ◽  
Author(s):  
Jeffrey C. Snyder ◽  
Howard B. Bluestein
Keyword(s):  
High Resolution ◽  
Rural Areas ◽  
Radar Data ◽  
Radial Velocities ◽  
Wind Speeds ◽  
Rapid Scan ◽  
X Band ◽  
Central United States ◽  
High Resolution Radar ◽  
Single Polarization

Abstract The increasing number of mobile Doppler radars used in field campaigns across the central United States has led to an increasing number of high-resolution radar datasets of strong tornadoes. There are more than a few instances in which the radar-measured radial velocities substantially exceed the estimated wind speeds associated with the enhanced Fujita (EF) scale rating assigned to a particular tornado. It is imperative, however, to understand what the radar data represent if one wants to compare radar observations to damage-based EF-scale estimates. A violent tornado observed by the rapid-scan, X-band, polarimetric mobile radar (RaXPol) on 31 May 2013 contained radar-relative radial velocities exceeding 135 m s−1 in rural areas essentially devoid of structures from which damage ratings can be made. This case, along with others, serves as an excellent example of some of the complications that arise when comparing radar-estimated velocities with the criteria established in the EF scale. In addition, it is shown that data from polarimetric radars should reduce the variance of radar-relative radial velocity estimates within the debris field compared to data from single-polarization radars. Polarimetric radars can also be used to retrieve differential velocity, large magnitudes of which are spatially associated with large spectrum widths inside the polarimetric tornado debris signature in several datasets of intense tornadoes sampled by RaXPol.

scholarly journals Processing of TerraSAR-X/TanDEM-X High Resolution Radar Data using Persistent Scatterers Method

2018 ◽  
Vol 11 (1) ◽  
pp. 86-94
Author(s):  
Anton V. Filatov ◽  
◽  
Arkadi V. Yevtyushkin ◽  
Yuri V. Vasilev ◽  
Peter V. Pogodin ◽  
...  
Keyword(s):  
High Resolution ◽  
Radar Data ◽  
Persistent Scatterers ◽  
High Resolution Radar
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