Radar-estimated Precipitation Research Articles

Characteristics of Lake-Effect Precipitation over the Black River Valley and Western Adirondack Mountains

Abstract Potential factors affecting the inland penetration and orographic modulation of lake-effect precipitation east of Lake Ontario include the environmental (lake, land, and atmospheric) conditions, mode of the lake-effect system, and orographic processes associated with flow across the downstream Tug Hill Plateau (herein Tug Hill), Black River valley, and Adirondack Mountains (herein Adirondacks). In this study we use data from the KTYX WSR-88D, ERA5 reanalysis, New York State Mesonet, and Ontario Winter Lake-effect Systems (OWLeS) field campaign to examine how these factors influence lake-effect characteristics with emphasis on the region downstream of Tug Hill. During an eight-cool-season (16 November–15 April) study period (2012/13–2019/20), total radar-estimated precipitation during lake-effect periods increased gradually from Lake Ontario to upper Tug Hill and decreased abruptly where the Tug Hill escarpment drops into the Black River valley. The axis of maximum precipitation shifted poleward across the northern Black River valley and into the northwestern Adirondacks. In the western Adirondacks, the heaviest lake-effect snowfall periods featured strong, near-zonal boundary layer flow, a deep boundary layer, and a single precipitation band aligned along the long-lake axis. Airborne profiling radar observations collected during OWLeS IOP10 revealed precipitation enhancement over Tug Hill, spillover and shadowing in the Black River valley where a resonant lee wave was present, and precipitation invigoration over the western Adirondacks. These results illustrate the orographic modulation of inland-penetrating lake-effect systems downstream of Lake Ontario and the factors favoring heavy snowfall over the western Adirondacks. Significance Statement Inland penetrating lake-effect storms east of Lake Ontario affect remote rural communities, enable a regional winter-sports economy, and contribute to a snowpack that contributes to runoff and flooding during thaws and rain-on-snow events. In this study we illustrate how the region’s three major geographic features—Tug Hill, the Black River valley, and the western Adirondacks—affect the characteristics of lake-effect precipitation, describe the factors contributing to heavy snowfall over the western Adirondacks, and provide an examples of terrain effects in a lake-effect storm observed with a specially instrumented research aircraft.

Accuracy of radar-estimated precipitation in a mountain catchment in Slovakia

Abstract Accurate estimation of precipitation in mountain catchments is challenging due to its high spatial variability and lack of measured ground data. Weather radar can help to provide precipitation estimates in such conditions. This study investigates the differences between measured and radar-estimated daily precipitation in the mountain catchment of the Jalovecký Creek (area 22 km2, 6 rain gauges at altitudes 815–1900 m a.s.l.) in years 2017–2020. Despite good correlations between measured and radar-based precipitation at individual sites (correlation coefficients 0.68–0.90), the radar-estimated precipitation was mostly substantially smaller than measured precipitation. The underestimation was smaller at lower altitude (on average by –4% to –17% at 815 m a.s.l.) than at higher altitudes (–35% to –59% at 1400–1900 m a.s.l.). Unlike measured data, the radar-estimated precipitation did not show the differences in precipitation amounts at lower and higher altitudes (altitudinal differences). The differences between the measured and radar-estimated precipitation were not related to synoptic weather situations. The obtained results can be useful in preparation of more accurate precipitation estimates for the small mountain catchments.

Flood Simulation in South Carolina Watersheds Using Different Precipitation Inputs

Flooding induced by extreme rainfall events causes tremendous loss of life and property and infrastructure failure. Accurate representation of precipitation, which has high variation in space and time, is critical to hydrologic model simulations and flood analyses. In this study, we examined responses of differently sized United States Geological Survey (USGS) hydrologic units to heavy precipitation using three different data sets. The first consists of rainfall observed at individual meteorological gauges. The second uses the National Centers for Environmental Prediction (NCEP) Environmental Modeling Center (EMC) 4 km gridded radar-estimated precipitation (GRIB) Stage IV data. The third one derives from the method we developed that blends gauge data with the spatial coverage of the Parameter-elevation Relationships on Independent Slopes Model (PRISM) data. We examined how two watersheds in South Carolina respond to the three different representations of heavy rainfall, using the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) developed by the U.S. Army Corps of Engineers. We found that the latter two precipitation inputs that consider spatial representation of rainfall yielded similar performance and improved simulated streamflow as compared to simulation using rainfall observed at individual meteorological gauges. The method we developed overcomes the spatial sparsity of rain gauges required for interpolation and extends availability of precipitation surfaces. Our study advances the understanding of advantages and limitations of different precipitation products for flood simulation.

Factors Affecting the Inland and Orographic Enhancement of Lake-Effect Precipitation over the Tug Hill Plateau

The factors affecting the inland and orographic enhancement of lake-effect precipitation are poorly understood, yet critical for operational forecasting. Here we use nine cool seasons (16 November–15 April) of radar data from the Montague/Ft. Drum, New York (KTYX), WSR-88D, the North American Regional Reanalysis (NARR), and observations from the Ontario Winter Lake-effect Systems (OWLeS) field campaign to examine variations in lake-effect precipitation enhancement east of Lake Ontario and over the Tug Hill Plateau (hereafter Tug Hill). Key factors affecting the inland and orographic enhancement in this region include the strength of the incident boundary layer flow, the intensity of the lake-induced convective available potential energy (LCAPE), and the mode of the lake-effect system. Stronger flow favors higher precipitation rates, a precipitation maximum displaced farther downwind, and greater inland and orographic enhancement. The effects of LCAPE depend upon the strength of the flow. During periods of weak flow, higher LCAPE favors lower precipitation rates, a maximum closer to the shoreline, and lesser inland and orographic enhancement. During periods of strong flow, higher LCAPE favors higher precipitation rates, a maximum displaced farther downwind, and greater inland and orographic enhancement. Banded (nonbanded) modes favor higher (lower) precipitation rates, lesser (greater) inland and orographic enhancement, and a maximum closer to the shoreline (over Tug Hill). These results, for both manually measured and radar-estimated precipitation, are robust when many lake-effect events are considered, but substantial variability exists during individual events.

Understanding Heavy Lake-Effect Snowfall: The Vertical Structure of Radar Reflectivity in a Deep Snowband over and downwind of Lake Ontario

AbstractThe distribution of radar-estimated precipitation from lake-effect snowbands over and downwind of Lake Ontario shows more snowfall in downwind areas than over the lake itself. Here, two nonexclusive processes contributing to this are examined: the collapse of convection that lofts hydrometeors over the lake and allows them to settle downwind; and stratiform ascent over land, due to the development of a stable boundary layer, frictional convergence, and terrain, leading to widespread precipitation there. The main data sources for this study are vertical profiles of radar reflectivity and hydrometeor vertical velocity in a well-defined, deep long-lake-axis-parallel band, observed on 11 December 2013 during the Ontario Winter Lake-effect Systems (OWLeS) project. The profiles are derived from an airborne W-band Doppler radar, as well as an array of four K-band radars, an X-band profiling radar, a scanning X-band radar, and a scanning S-band radar.The presence of convection offshore is evident from deep, strong (up to 10 m s−1) updrafts producing bounded weak-echo regions and locally heavily rimed snow particles. The decrease of the standard deviation, skewness, and peak values of Doppler vertical velocity during the downwind shore crossing is consistent with the convection collapse hypothesis. Consistent with the stratiform ascent hypothesis are (i) an increase in mean vertical velocity over land; and (ii) an increasing abundance of large snowflakes at low levels and over land, due to depositional growth and aggregation, evident from flight-level and surface particle size distribution data, and from differences in reflectivity values from S-, X-, K-, and W-band radars at nearly the same time and location.

Precipitation estimation over radar gap areas based on satellite and adjacent radar observations

Abstract. Continuous rainfall measurements from ground-based radars are crucial for monitoring and forecasting heavy rainfall-related events such as floods and landslides. However, complete coverage by ground-based radars is often hampered by terrain blockage and beam-related errors. In this study, we presented a method to fill the radar gap using surrounding radar-estimated precipitation and observations from a geostationary satellite. The method first estimated the precipitation over radar gap areas using data from the Communication, Ocean, and Meteorological Satellite (COMS); the first geostationary satellite of Korea. The initial precipitation estimation from COMS was based on the rain rate-brightness temperature relationships of a priori databases. The databases were built with temporally and spatially collocated brightness temperatures at four channels (3.7, 6.7, 10.8, and 12 μm) and Jindo (126.3° E, 34.5° N) radar rain rate observations. The databases were updated with collocated data sets in a timespan of approximately one hour prior to the designated retrieval. Then, bias correction based on an ensemble bias factor field (Tesfagiorgis et al., 2011b) from radar precipitation was applied to the estimated precipitation field. Over the radar gap areas, this method finally merged the bias-corrected satellite precipitation with the radar precipitation obtained by interpolating the adjacent radar observation data. The merging was based on optimal weights determined from the root-mean-square error (RMSE) with the reference sensor observation or equal weights in the absence of reference data. This method was tested for major precipitation events during the summer of 2011 with assumed radar gap areas. The results suggested that successful merging appears to be closely related to the quality of the satellite precipitation estimates.

Model-Based Estimation of Dynamic Effect on Twenty-First-Century Precipitation for Swiss River Basins

AbstractProjections of twenty-first-century precipitation for seven Swiss river basins are generated by linking high-resolution (2 km × 2 km) radar-estimated precipitation observations to a global climate model (GCM) via synoptic weather patterns. The use of synoptic patterns characterizes the effect of changes in large-scale circulation, or dynamic effects, on precipitation. In each basin observed total daily precipitation received during advective synoptic patterns is shown to be dependent on the basin’s general topographic aspect. Across all basins convective synoptic patterns follow the same trend in total daily precipitation with cyclonic patterns consistently producing a larger amount of precipitation than anticyclonic patterns. Identification of synoptic patterns from a GCM for the twenty-first century [Community Climate System Model, version 3.0, (CCSM3)] shows increasing frequency of anticyclonic synoptic patterns, decreasing frequency of cyclonic patterns, and constant frequency of advective patterns over Switzerland. When coupled with observed radar-estimated precipitation for each synoptic pattern, the changes in synoptic pattern frequencies result in an approximately 10%–15% decrease in decadal precipitation over the course of the twenty-first century for seven Swiss river basins. The study results also show an insignificant change in the future (twenty-first century) probability of exceeding the current (2000–08) 95th quantile of total precipitation. The lack of a trend in exceeding the 95th quantile of precipitation in combination with a decreasing trend in total precipitation provides evidence that dynamic effects will not result in increased frequency of heavy precipitation events, but that heavy precipitation will account for a greater proportion of total precipitation in Swiss river basins by the end of the twenty-first century.

Relationship between Radar-Estimated Precipitation and Synoptic Weather Patterns in the European Alps

AbstractA 9-yr (2000–08) analysis of precipitation characteristics for the central and western European Alps has been generated from ground-based operational weather radar data provided by the Swiss radar network. The radar-based precipitation analysis focuses on the relationship between synoptic-scale weather patterns and mesoscale precipitation distribution over complex alpine terrain. The analysis divides the Alps into six regions (each approximately 200 × 200 km2 in size)—one on the northern side, two each on the western and southern sides of the Alps, and one in the Massif Central—representing various orographic aspects and localized climates within the radar coverage area. For each region, estimated precipitation rate derived from radar data is analyzed on a seasonal basis for total daily precipitation and frequency of high-precipitation-rate events. The summer season has the highest total daily precipitation for all regions in the study, whereas median values of daily precipitation in winter are less than one-half of median daily precipitation for summer. For all regions, high-precipitation-rate events occur most frequently in the summer. Daily synoptic-scale weather patterns are associated with total daily precipitation and frequency of high precipitation rate to show that an advective synoptic-scale pattern with southerly midtropospheric flow results in the highest median and 90th-quantile values for total daily precipitation and that a convective synoptic-scale pattern results in elevated frequency of extreme-precipitation-rate events.

The impact of assimilating radar-estimated rain rates on simulation of precipitation in the 17–18 July 1996 Chicago floods

Rainfall prediction remains one of the most challenging problems in weather forecasting. In order to improve high-resolution quantitative precipitation forecasts (QPF), a new procedure for assimilating rainfall rate derived from radar composite reflectivity has been proposed and tested in a numerical simulation of the Chicago floods of 17–18 July 1996. The methodology is based on the one-dimensional variation scheme (1DVAR) assimilation approach introduced by Fillion and Errico but applied here using the Kain-Fritsch convective parameterization scheme (KF CPS). The novel feature of this work is the continuous assimilation of radar estimated rain rate over a three hour period, rather than a single assimilation at the initial (analysis) time. Most of the characteristics of this precipitation event, including the propagation, regeneration of mesoscale convective systems, the frontal boundary across the Midwest and the evolution of the low-level jet are better captured in the simulation as the radar-estimated precipitation rate is assimilated. The results indicate that precipitation assimilation during the early stage can improve the simulated mesoscale feature of the convection system and shorten the spin-up time significantly. Comparison of precipitation forecasts between the experiments with and without the 1DVAR indicates that the 1DVAR scheme has a positive impact on the QPF up to 36 hours in terms of the bias and bias equalized threat scores.

Evaluation of Surface and Radar-Estimated Precipitation Data Sources Over the Lower Mississippi River Alluvial Plain

The Mississippi River floodplain in northwestern Mississippi and eastern Arkansas, often referred to as the Mississippi Delta, is extremely important for regional economic stability and growth due to the widespread agriculture in the area. Precipitation is often the limiting factor in crop production, and thus knowledge of precipitation variability is essential. The region is unique in currently having three sources of precipitation observations: (1) multi-sensor precipitation estimates from the National Weather Service (NWS) NEXRAD network; (2) surface observations from NWS recording stations; and (3) surface observations from U.S. Department of Agriculture (USDA) Soil Climate Analysis Network (SCAN) recording stations. For meteorological and climatological precipitation research, quantitatively defining the biases associated with available precipitation data sources is critical in selecting which source to use for a given application. Results of this research indicate that the multi-sensor data are in best agreement with surface observations during the cool season (October-March) when stratiform precipitation dominates, whereas only moderate correlations exist during the warm season. Additionally, overall bias values among the data sources decrease after 2002, at which point the remotely sensed and surface-based estimates show improved agreement.

Cinrad data quality control and precipitation estimation

Cinrad is the acronym describing China's next-generation weather radar that inherits the technology of the US national weather system Nexrad (WSR-88D) through a joint agreement between the two countries. More than 100 Cinrad systems have currently been deployed in China, but challenges exist for their wider application. The data quality assessment and the development of quantitative precipitation estimation for flood risk management will pose a significant challenge as the national system is both commissioned and further developed. This paper is based on an assessment of the data quality of a Cinrad system deployed in southern China and describes aspects of the initial data quality-control procedure. Precipitation was estimated for the Liuxihe River basin using 11 observed storms. The data quality-control procedure presented in this paper has four components, including volume-scan data, missing-data interpolation, abnormal-reflectivity detection and correction and fine-day reflectivity removal. The results indicate that the radar-estimated precipitation is consistent with that measured by conventional rain-gauge networks; also radar estimated precipitation can provide a better representation of the spatial distribution of the precipitation over the whole basin, and thereby has the potential to improve flood forecasting and warning systems. Given the importance of flooding to China, the continued quantitative development of the radar system is of national importance, particularly in terms of the tropical-cyclone-induced flooding prevalent in south China.

Comparison of gage and multi-sensor precipitation estimates over a range of spatial and temporal scales in the Midwestern United States

An intercomparison of radar-estimated precipitation and gage precipitation at a monthly time scale with a county spatial resolution was undertaken for a nine-state region of the Midwestern United States. Daily gage and radar-estimated precipitation data also were examined at the county and grid cell scale for several smaller regions. Precipitation data were collected from February 2002 to August 2005 from three sources: (1) gridded radar (stage II, RDR) and multi-sensor precipitation estimates (MPE) based on the stage III/IV algorithm developed by the Office of hydrology/NWS River Forecast Centers, (2) quality-controlled National Weather Service (NWS) cooperative gage (QC_Coop) data from the National Climatic Data Center (NCDC), and (3) gage data from three high density networks in Illinois. Both the QC_Coop and high density gage data were employed as the reference standard. Sixty-four percent of QC_Coop versus MPE county-averaged monthly precipitation estimates agreed to within ±25%, with a median difference of 5.6% (QC_Coop greater than MPE) for the Midwest region. The difference between gage and MPE monthly values decreased somewhat through the 41-month period of study, and the correlation between monthly estimates increased, averaging 0.80. Data from three regional gage networks indicated that on a daily basis, network-averaged MPE and gage data also agreed to within about ±25%, and the MPE values tended to be lower than gage amounts at higher precipitation values. When examining multiple gages within single MPE grid cells, it was found that the number of gages employed in computing the gage average did not appreciably affect the correspondence between MPE and gage precipitation amounts. This also was found examining monthly values at the county level. For daily precipitation at the grid cell scale, for daily networked-averaged precipitation for each of the regional networks, and for monthly county-averaged precipitation values across the Midwest, MPE values are often larger than gage values for lower gage precipitation totals, and as precipitation totals increase, MPE values are more likely to be the same or smaller than the gage value.

Relationships between Large-Scale Motion and Convective Precipitation During GATE

Upper air and surface data from the GARP Atlantic Tropical Experiment (GATE) are used to examine the interrelationships between convective-scale precipitation and the larger scale wind field. The upper air winds from the inner (B) and outer (A/B) hexagonal observational arrays are fit with second-order polynomials to provide smooth estimates of the vorticity, divergence and vertical motion in the observational array. In these analyses we examined archived validated data from all three phases of the experiment and we formed averages based on the radar-estimated precipitation rates. Mean profiles for 19-day periods during each of the three observational phases establish the basic similarity of the kinematics during each phase. Strong boundary-layer convergence balanced, for the most part, by upper tropospheric divergence, is common to all three phases. Radar-estimated precipitation rates are used to define suppressed (precipitation rates <0.1 mm h−1) and highly disturbed (precipitation rates >0.5 mm h−1) states over the observational array. Mean profiles for the disturbed states in each phase show weaker easterly winds and much larger upward vertical velocities than do the mean profiles for the suppressed states. The mean vorticity profiles for each state do not show such clear-cut differences. Time series of 12 h averages indicate that the precipitation events in Phase III corresponded very closely to the cyclonic maxima of the 700 mb relative vorticity, reflecting the influence of the easterly waves described by Reed et al. (1977). During Phases I and II, when easterly waves were poorly organized, the precipitation events did not correspond closely to the cyclonic vorticity maxima. On the other hand, precipitation events showed good correspondence with the large-scale (A/B) 700 mb upward vertical velocity maxima and surface meridional convergence ∂v/∂y during all three phases. This shows that the precipitation is clearly related to events on a larger scale. The effects of convective activity on the large-scale flow are examined through the vorticity budget. The vorticity budget residual profiles were similar from phase to phase with cyclonic production maxima in the mid and upper troposphere. The upper tropospheric residual maximum is as strong during the suppressed state as it is during the highly disturbed side. At the surface, individual values of the residual are almost always opposite in sign to the vorticity. The mean vorticity budget for the A/B array shows the tipping term to have magnitudes comparable to other terms in the vorticity budget.