A Real-Time Algorithm to Identify Convective Precipitation Adjacent to or within the Bright Band in the Radar Scan Domain

2021 ◽  
Vol 22 (5) ◽  
pp. 1139-1151
Author(s):  
Zhe Zhang ◽  
Youcun Qi ◽  
Donghuan Li ◽  
Ziwei Zhu ◽  
Meilin Yang ◽  
...  
Keyword(s):  
Heavy Precipitation ◽  
Rain Gauge ◽  
Polar Coordinates ◽  
Convective Precipitation ◽  
Horizontal Gradient ◽  
Bright Band ◽  
Stratiform Region ◽  
Hydrological Hazards ◽  
Stratiform Precipitation ◽  
Precipitation Events

AbstractHydrological hazards usually occur after heavy precipitation, especially during strong convection. Therefore, accurately identifying convective precipitation is very helpful for hydrological warning and forecasting. However, separating the convective, bright band (BB), and stratiform precipitation is found to be challenging when the convection is adjacent to or within the BB region. A new convection/BB/stratiform precipitation segregation algorithm is proposed in this study to resolve this challenging issue. This algorithm is applicable for a single radar volume scan data in native (polar) coordinates and consists of four processes: 1) check the freezing (0°C) level to roughly assess whether convection is occurring or not; 2) identify the convective cores through analyzing composite reflectivity (maximum reflectivity for a given range gate among all the sweeps), vertically integrated liquid water (VIL), VIL horizontal gradient, and reflectivity at the levels of 0°, −10°, and above −10°C; 3) delineate the whole convective region through the seeded region growing method by taking account of the microphysical differences between the BB and convective regions; and 4) delineate BB features in the stratiform region. The proposed algorithm utilizes the physical characteristics of different precipitation types for precisely segregating the convective, BB, and stratiform precipitation. This algorithm has been tested with radar data of different precipitation events and evaluated with three months of rain gauge data. The results show that the proposed algorithm performs consistently well for challenging precipitation events with the convection adjacent to or within a strong BB. Furthermore, the proposed algorithm could be used to improve the vertical profile of reflectivity (VPR) correction and reduce the overestimation of rainfall in the BB precipitation region.

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.

A Comparison of CMIP3 Simulations of Precipitation over North America with Observations: Daily Statistics and Circulation Features Accompanying Extreme Events

2013 ◽  
Vol 26 (10) ◽  
pp. 3209-3230 ◽  
Author(s):  
Anthony M. DeAngelis ◽  
Anthony J. Broccoli ◽  
Steven G. Decker
Keyword(s):  
North America ◽  
Extreme Events ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Climate Model ◽  
Heavy Precipitation ◽  
Convective Precipitation ◽  
Southern Mexico ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract Climate model simulations of daily precipitation statistics from the third phase of the Coupled Model Intercomparison Project (CMIP3) were evaluated against precipitation observations from North America over the period 1979–99. The evaluation revealed that the models underestimate the intensity of heavy and extreme precipitation along the Pacific coast, southeastern United States, and southern Mexico, and these biases are robust among the models. The models also overestimate the intensity of light precipitation events over much of North America, resulting in fairly realistic mean precipitation in many places. In contrast, heavy precipitation is simulated realistically over northern and eastern Canada, as is the seasonal cycle of heavy precipitation over a majority of North America. An evaluation of the simulated atmospheric dynamics and thermodynamics associated with extreme precipitation events was also conducted using the North American Regional Reanalysis (NARR). The models were found to capture the large-scale physical mechanisms that generate extreme precipitation realistically, although they tend to overestimate the strength of the associated atmospheric circulation features. This suggests that climate model deficiencies such as insufficient spatial resolution, inadequate representation of convective precipitation, and overly smoothed topography may be more important for biases in simulated heavy precipitation than errors in the large-scale circulation during extreme events.

scholarly journals Precipitation over Monsoon Asia: A Comparison of Reanalyses and Observations

2017 ◽  
Vol 30 (2) ◽  
pp. 465-476 ◽  
Author(s):  
Andrej Ceglar ◽  
Andrea Toreti ◽  
Gianpaolo Balsamo ◽  
Shinya Kobayashi
Keyword(s):  
Temporal Evolution ◽  
Heavy Precipitation ◽  
Rain Gauge ◽  
Rain Gauge Data ◽  
Monsoon Asia ◽  
Spatial Performance ◽  
The World ◽  
Gauge Data ◽  
Source Of Information ◽  
Precipitation Events

Reanalysis products represent a valuable source of information for different impact modeling and monitoring activities over regions with sparse observational data. It is therefore essential to evaluate their behavior and their intrinsic uncertainties. This study focuses on precipitation over monsoon Asia, a key agricultural region of the world. Four reanalysis datasets are evaluated, namely ERA-Interim, ERA-Interim/Land, AgMERRA (an agricultural version of MERRA), and JRA-55. APHRODITE and the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset are the two gridded observational datasets used for the evaluation; the former is based on rain gauge data and the latter on a combination of satellite and rain gauge data. Differences in seasonality, moderate-to-heavy precipitation events, daily distribution, and drought characteristics are analyzed. Results show remarkable differences between the APHRODITE and CHIRPS observational datasets as well as between these datasets and the reanalyses. AgMERRA generally achieves the best performance, but it is not updated at near–real time. ERA-Interim/Land shows good spatial performance, but when the interest is on the temporal evolution JRA-55 is recommended, as it exhibits the most stable temporal behavior. This study shows that the use of reanalyses for impact modeling and monitoring over monsoon Asia requires an accurate evaluation and choices to be tailored to the specific needs.

Dynamic Forcing and Mesoscale Variability of Heavy Precipitation Events over the Sierra Nevada Mountains

2008 ◽  
Vol 136 (1) ◽  
pp. 62-77 ◽  
Author(s):  
Heather Dawn Reeves ◽  
Yuh-Lang Lin ◽  
Richard Rotunno
Keyword(s):  
Sierra Nevada ◽  
Heavy Precipitation ◽  
Horizontal Gradient ◽  
First Case ◽  
Northern Half ◽  
Sierra Nevada Mountains ◽  
Dynamic Forcing ◽  
Rain Rates ◽  
Upstream Flow ◽  
Precipitation Events

Abstract The aim of this research is to investigate the causes for an isolated maximum in precipitation that is typically found along the northern half of the Sierra Nevada mountains of California, in the vicinity of Plumas National Forest (PNF), during moderate to heavy precipitation events. Particular attention was paid to the role various mesoscale (i.e., <200 km) terrain features may have played in localizing the precipitation at PNF. Numerical simulations and sensitivity experiments for two cases of heavy precipitation at PNF reveal that the extent to which terrain acts to focus precipitation is case sensitive. In the first case, the upstream flow was characterized by a strong horizontal gradient in wind speed and moisture. This gradient led to differential deflection of airstreams incident to the range and, consequently, localized convergence and enhanced rain rates at PNF. This localized enhancement occurred regardless of whether any terrain variations were present in the simulations or not. The second case was characterized by more a horizontally uniform upstream flow and showed a much stronger sensitivity to terrain variations, in particular, short- and long-wavelength undulations along the leading (west) edge of the Sierra Nevada range. When these undulations were removed, no localized maxima in precipitation occurred.

scholarly journals VHF signal power suppression in stratiform and convective precipitation

2006 ◽  
Vol 24 (1) ◽  
pp. 23-35 ◽  
Author(s):  
A. J. McDonald ◽  
K. P. Monahan ◽  
D. A. Hooper ◽  
C. Gaffard
Keyword(s):  
Signal To Noise Ratio ◽  
Convective Precipitation ◽  
Small Scale ◽  
Signal Power ◽  
Signal To Noise ◽  
Bright Band ◽  
Signal Suppression ◽  
Stratiform Precipitation ◽  
Noise Ratio

Abstract. Previous studies have indicated that VHF clear-air radar return strengths are reduced during periods of precipitation. This study aims to examine whether the type of precipitation, stratiform and convective precipitation types are identified, has any impact on the relationships previously observed and to examine the possible mechanisms which produce this phenomenon. This study uses a combination of UHF and VHF wind-profiler data to define periods associated with stratiform and convective precipitation. This identification is achieved using an algorithm which examines the range squared corrected signal to noise ratio of the UHF returns for a bright band signature for stratiform precipitation. Regions associated with convective rainfall have been defined by identifying regions of enhanced range corrected signal to noise ratio that do not display a bright band structure and that are relatively uniform until a region above the melting layer. This study uses a total of 68 days, which incorporated significant periods of surface rainfall, between 31 August 2000 and 28 February 2002 inclusive from Aberystwyth (52.4° N, 4.1° W). Examination suggests that both precipitation types produce similar magnitude reductions in VHF signal power on average. However, the frequency of occurrence of statistically significant reductions in VHF signal power are very different. In the altitude range 2-4 km stratiform precipitation is related to VHF signal suppression approximately 50% of the time while in convective precipitation suppression is observed only 27% of the time. This statistical result suggests that evaporation, which occurs more often in stratiform precipitation, is important in reducing the small-scale irregularities in humidity and thereby the radio refractive index. A detailed case study presented also suggests that evaporation reducing small-scale irregularities in humidity may contribute to the observed VHF signal suppression.

scholarly journals Precipitation in the Waikato River Catchment

2021 ◽  
Author(s):  
◽  
Stacey Maree Dravitzki
Keyword(s):  
Observational Data ◽  
Extreme Precipitation ◽  
Numerical Models ◽  
Heavy Precipitation ◽  
Convective Precipitation ◽  
River Catchment ◽  
Synoptic Conditions ◽  
Light Precipitation ◽  
Precipitation Events ◽  
Waikato River

<p>Observational data and numerical models were used to investigate precipitation in and around the Waikato River catchment. This economically important catchment relies on a dependable precipitation supply for agriculture and hydroelectric generation, with stations generally receiving 2,000 +/- 300 mm of precipitation annually. Long-term and inter-annual variability of total and extreme precipitation were examined using up to 100 years of observational data. Precipitation volumes within the catchment were represented by a five-day smoothed, area-averaged time series, and extreme events were defined as exceeding the 95th percentile. Atmospheric circulation oscillations correlated with the frequency of light precipitation but not with the probability of occurrence or with the magnitude of heavy precipitation events. Also no significant linear variations in precipitation (either annual totals or extreme precipitation characteristics) were found over this period, although temperature increased by 1.15+/-0.45'. A total of 63 heavy precipitation events were identified between 1996 and 2001. An analysis of the prevailing synoptic conditions reveal that heavy precipitation was associated with the passage of cold fronts of cyclones with minima at both 500 and 1000 mb heights. Extended periods of enhanced baroclinicity (succession of cyclones) or blocking anticyclones east of New Zealand have led to flooding in the Waikato catchment. Storm tracking showed that 10% of cyclones originating in the Tasman Sea result in heavy precipitation in the catchment. The accuracy and value of the GFS global precipitation forecasts <= 180 hours were investigated. Depending on forecast lag, the global models correctly predicted the presence of precipitation in 70-80% of forecasts, but the magnitude and distribution were often inaccurate. The probability of receiving precipitation is increased when more members of a lagged ensemble predict it. Forecasts with lags shorter than approximately 96 hours were appropriate to use as boundary constraints for mesoscale modelling. The ability and limitations of mesoscale models to simulate the spatial distribution of precipitation were examined through high-resolution WRF simulations of three heavy precipitation events, and ten different model settings were compared for the January 2006 event. The model consistently under-predicted precipitation. The timing and location of convective precipitation, which accounted for 50% of the precipitation during two events, was physically unconstrained but regional totals were comparable to observations. A continuous two-year numerical simulation was run to provide a precipitation climatology for data-sparse areas. The simulation gave good spatial representation of precipitation and other meteorological variables but tended to under estimate the magnitude of heavy precipitation and over-estimate light precipitation.</p>

scholarly journals Precipitation in the Waikato River Catchment

2021 ◽  
Author(s):  
◽  
Stacey Maree Dravitzki
Keyword(s):  
Observational Data ◽  
Extreme Precipitation ◽  
Numerical Models ◽  
Heavy Precipitation ◽  
Convective Precipitation ◽  
River Catchment ◽  
Synoptic Conditions ◽  
Light Precipitation ◽  
Precipitation Events ◽  
Waikato River

<p>Observational data and numerical models were used to investigate precipitation in and around the Waikato River catchment. This economically important catchment relies on a dependable precipitation supply for agriculture and hydroelectric generation, with stations generally receiving 2,000 +/- 300 mm of precipitation annually. Long-term and inter-annual variability of total and extreme precipitation were examined using up to 100 years of observational data. Precipitation volumes within the catchment were represented by a five-day smoothed, area-averaged time series, and extreme events were defined as exceeding the 95th percentile. Atmospheric circulation oscillations correlated with the frequency of light precipitation but not with the probability of occurrence or with the magnitude of heavy precipitation events. Also no significant linear variations in precipitation (either annual totals or extreme precipitation characteristics) were found over this period, although temperature increased by 1.15+/-0.45'. A total of 63 heavy precipitation events were identified between 1996 and 2001. An analysis of the prevailing synoptic conditions reveal that heavy precipitation was associated with the passage of cold fronts of cyclones with minima at both 500 and 1000 mb heights. Extended periods of enhanced baroclinicity (succession of cyclones) or blocking anticyclones east of New Zealand have led to flooding in the Waikato catchment. Storm tracking showed that 10% of cyclones originating in the Tasman Sea result in heavy precipitation in the catchment. The accuracy and value of the GFS global precipitation forecasts <= 180 hours were investigated. Depending on forecast lag, the global models correctly predicted the presence of precipitation in 70-80% of forecasts, but the magnitude and distribution were often inaccurate. The probability of receiving precipitation is increased when more members of a lagged ensemble predict it. Forecasts with lags shorter than approximately 96 hours were appropriate to use as boundary constraints for mesoscale modelling. The ability and limitations of mesoscale models to simulate the spatial distribution of precipitation were examined through high-resolution WRF simulations of three heavy precipitation events, and ten different model settings were compared for the January 2006 event. The model consistently under-predicted precipitation. The timing and location of convective precipitation, which accounted for 50% of the precipitation during two events, was physically unconstrained but regional totals were comparable to observations. A continuous two-year numerical simulation was run to provide a precipitation climatology for data-sparse areas. The simulation gave good spatial representation of precipitation and other meteorological variables but tended to under estimate the magnitude of heavy precipitation and over-estimate light precipitation.</p>

scholarly journals Heavy winter precipitation events with extratropical cyclone diagnosed by GPM products and trajectory analysis

2021 ◽  
Author(s):  
Kenichi Ueno ◽  
Morihiro Sawada
Keyword(s):  
Trajectory Analysis ◽  
Heavy Precipitation ◽  
Conveyor Belt ◽  
Extratropical Cyclone ◽  
Japan Meteorological Agency ◽  
Near Surface ◽  
Cyclone Center ◽  
Precipitation System ◽  
Stratiform Precipitation ◽  
Precipitation Events

&lt;p&gt;In Japan, Extratropical cyclone sometimes causes sporadic heavy snow in the coastal cites or heavy rains on snow covers in mountainous areas. Ando and Ueno (2015) identified that heavy precipitation events tend to occur with occluding cyclones. However, three-dimensional structure of precipitation system embedded in the cyclone system are difficult to capture by surface observation network over Japanese archipelago that are composed of complex coastal lines and mountains. This study identified heavy precipitation events during the cold seasons of 2014-2019 by two-day accumulated precipitation data at 137 stations of the Japan Meteorological Agency. The mechanisms for producing heavy precipitation in relation to the structure of an occluding extratropical cyclone were analyzed with the aid of the products of the Dual-frequency Precipitation Radar onboard the Global Precipitation Measurement (GPM) core satellite and trajectory analysis on European Centre for Medium-range Weather Forecasts atmospheric reanalysis data. Upper-ranked events with heavy precipitation were mostly due to extratropical cyclones, and many of them were in mature stages. In the top 50 ranked events, three south-coast cyclones were nominated, and relationships between the development of the mesoscale precipitation system and airstreams were intensively diagnosed. Hourly precipitation changes at stations that recorded heavy precipitation were primary affected by a combination of the warm conveyor belt (WCB), the cold conveyor belt (CCB) and the dry intrusion (DI). Wide-ranging stratiform precipitation in the east of cyclone center was composed of low-level WCB over the CCB and the upper WCB, and convective clouds around the cyclone center was associated with the upper DI over the WCB that provided an extreme precipitation rate at the surface, including formation of a band-shaped precipitation system. The convective cloud activities also contributed to moist air advection over the stationary stratiform precipitation areas recognized as the upper WCB. DPR products also identified deep stratiform precipitation in the cloud-head area behind the cyclone center with mid-level (near-surface) latent heat release (absorption) with increased potential vorticity along the CCB that was made feed-back intensification of the cyclone possible. (This study will be published in GPM special issue of JMSJ)&amp;#12288;&lt;/p&gt;

Statistical Characteristics of Daily Precipitation: Comparisons of Gridded and Point Datasets

2008 ◽  
Vol 47 (9) ◽  
pp. 2468-2476 ◽  
Author(s):  
Leslie A. Ensor ◽  
Scott M. Robeson
Keyword(s):  
Daily Precipitation ◽  
Heavy Precipitation ◽  
Rain Gauge ◽  
Statistical Characteristics ◽  
Precipitation Data ◽  
Spatial Coverage ◽  
Daily Precipitation Data ◽  
Precipitation Total ◽  
Grid Points ◽  
Precipitation Events

Abstract Gridding of daily precipitation data alleviates many of the limitations of data that are derived from point observations, such as problems associated with missing data and the lack of spatial coverage. As a result, gridded precipitation data can be valuable for applied climatological research and monitoring, but they too have limitations. To understand the limitations of gridded data more fully (especially when they are used as surrogates for station data), annual precipitation total, rain-day frequency, and annual maxima are calculated and compared for five Midwestern grid points from the Climate Prediction Center’s Unified Rain Gauge Dataset (URD) and those of its nearest (rain gauge) station. To further examine differences between the two datasets, return periods of daily precipitation were calculated over a region encompassing Illinois and Indiana. These analyses reveal that the gridding process used to create the URD produced nearly the same annual totals as the rain gauge data; however, the gridding significantly increased the frequency of low-precipitation events while greatly reducing the frequency of heavy-precipitation events. Extreme precipitation values also were greatly reduced in the gridded precipitation data. While smoothing nearly always occurs when data are gridded, the gridding of discrete variables such as daily precipitation can produce datasets with statistical characteristics that are very different from those of the original observations.

scholarly journals A Prototype Quantitative Precipitation Estimation Algorithm for Operational S-Band Polarimetric Radar Utilizing Specific Attenuation and Specific Differential Phase. Part II: Performance Verification and Case Study Analysis

2019 ◽  
Vol 20 (5) ◽  
pp. 999-1014 ◽  
Author(s):  
Stephen B. Cocks ◽  
Lin Tang ◽  
Pengfei Zhang ◽  
Alexander Ryzhkov ◽  
Brian Kaney ◽  
...  
Keyword(s):  
Real Time ◽  
Heavy Precipitation ◽  
Estimation Algorithm ◽  
Differential Phase ◽  
Specific Attenuation ◽  
Quantitative Precipitation Estimation ◽  
Precipitation Estimation ◽  
Bias Ratio ◽  
Using Data ◽  
Precipitation Events

Abstract The quantitative precipitation estimate (QPE) algorithm developed and described in Part I was validated using data collected from 33 Weather Surveillance Radar 1988-Doppler (WSR-88D) radars on 37 calendar days east of the Rocky Mountains. A key physical parameter to the algorithm is the parameter alpha α, defined as the ratio of specific attenuation A to specific differential phase KDP. Examination of a significant sample of tropical and continental precipitation events indicated that α was sensitive to changes in drop size distribution and exhibited lower (higher) values when there were lower (higher) concentrations of larger (smaller) rain drops. As part of the performance assessment, the prototype algorithm generated QPEs utilizing a real-time estimated and a fixed α were created and evaluated. The results clearly indicated ~26% lower errors and a 26% better bias ratio with the QPE utilizing a real-time estimated α as opposed to using a fixed value as was done in previous studies. Comparisons between the QPE utilizing a real-time estimated α and the operational dual-polarization (dual-pol) QPE used on the WSR-88D radar network showed the former exhibited ~22% lower errors, 7% less bias, and 5% higher correlation coefficient when compared to quality controlled gauge totals. The new QPE also provided much better estimates for moderate to heavy precipitation events and performed better in regions of partial beam blockage than the operational dual-pol QPE.

Sign in / Sign up

Export Citation Format

Share Document