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We analyzed 4-years of Advanced Scatterometer (ASCAT) incidence angle normalized C-band backscatter, Next-Generation Radar (NEXRAD) precipitation and United States Department of Agriculture (USDA) crop yield data over the contiguous United States (U.S.). Large negative anomalies in backscatter are evident over the U.S. during the 2011 and 2012 growing seasons, coincident with two instances of severe drought. The backscatter anomalies were correlated with diminished growing season precipitation and with reduced crop yields reflecting where drought-induced impacts on above-ground biomass production occurred. During periods of acute drought, differences in diurnal backscatter were reduced and in some cases reversed reflecting diminished nocturnal leave rehydration. The results indicate that the C-band, VV-polarized ASCAT backscatter data is sensitive to interannual variability in agricultural productivity rather than soil moisture, and can offer an important geophysical monitoring tool capable of identifying and assessing drought-related vegetation responses independent of and complementary to satellite optical/near-infrared remote sensing data. This technique is flexible and adaptable, providing a capability to address region-specific needs. The twice-daily, weather independent and near-real time global monitoring capabilities of ASCAT and similar microwave instruments (e.g. RapidSCAT, Sentinel-1) can help improve drought preparedness and mitigation planning allowing improved water resource management for agriculture on the local as well as the state level. [ABSTRACT FROM AUTHOR]

The article discusses the concept of radar which can be used for the detection of distant objects invisible to the human eye. Topics discussed include shortening of the phrase Radio Detection and Ranging into radar by the U.S. Navy in 1940, the use of the telemobiloscope, predecessor of radar, for detecting ships in the fog, and the further development of radar during the World War II.

Validation of precipitation estimates from various products is a challenging problem, since the true precipitation is unknown. However, with the increased availability of precipitation estimates from a wide range of instruments (satellite, ground-based radar, and gauge), it is now possible to apply the triple collocation (TC) technique to characterize the uncertainties in each of the products. Classical TC takes advantage of three collocated data products of the same variable and estimates the mean squared error of each, without requiring knowledge of the truth. In this study, triplets among NEXRAD-IV, TRMM 3B42RT, GPCP 1DD, and GPI products are used to quantify the associated spatial error characteristics across a central part of the continental US. Data are aggregated to biweekly accumulations from January 2002 through April 2014 across a 2° x 2° spatial grid. This is the first study of its kind to explore precipitation estimation errors using TC across the US. A multiplicative (logarithmic) error model is incorporated in the original TC formulation to relate the precipitation estimates to the unknown truth. For precipitation application, this is more realistic than the additive error model used in the original TC derivations, which is generally appropriate for existing applications such as in the case of wind vector components and soil moisture comparisons. This study provides error estimates of the precipitation products that can be incorporated into hydrological and meteorological models, especially those used in data assimilation. Physical interpretations of the error fields (related to topography, climate, etc.) are explored. The methodology presented in this study could be used to quantify the uncertainties associated with precipitation estimates from each of the constellations of GPM satellites. Such quantification is prerequisite to optimally merging these estimates. [ABSTRACT FROM AUTHOR]

The article focuses on the need to improve the efficacy of wide area surveillance (WAS) in order for the U.S. armed forces to get consistent and most powerful information for enabling field operations and policy decisions. It seeks to improve the condition in advancing surveillance tradecraft by defining principles. It looks primarily on motion intelligence systems like wide area motion imagery and ground-scanning moving target indicator radars.

The societal impacts of flash floods are more significant than any other weather-related hazard. They are often manifested in the form of damage to infrastructure, flooding of roadways and bridges, creating deadly hazards to motorists and inundation of crops and pasture. Some of these hazards can be anticipated and thus mitigated given effective warning systems. This study describes the tools proposed over recent decades in the USA to predict flash flooding and evaluates them using a common observational data set. Design recommendations for flash-flood forecasting systems are provided, taking into account today's availability of high-resolution rainfall data at scales commensurate with flash flooding, their archives, spatial data sets to describe physiographic properties, and ever-increasing computational resources.Editor D. Koutsoyiannis; Guest editor R.J. MooreCitation Gourley, J.J., Flamig, Z.L., Hong, Y., and Howard, K.W., 2014. Evaluation of past, present and future tools for radar-based flash-flood prediction in the USA. Hydrological Sciences Journal, 59 (7), 1377–1389. http://dx.doi.org/10.1080/02626667.2014.919391 [ABSTRACT FROM AUTHOR]

A novel method has been proposed for validating satellite radar snowfall retrievals using surface station observations over the western United States mountainous region, where the mean snowfall rate at a station depends on its elevation. First, all station data within a 1° × 1° grid are used to develop a snowfall rate versus elevation relation. This relation is then used to compute snowfall rate in other locations within the 1° × 1° grid, as if surface observations were available everywhere in the grid. Grid mean snowfall rates are then derived, which should be more representative to the mean snowfall rate of the grid than using data at any one station or from a simple mean of all stations in the grid. Comparison of the so-derived grid mean snowfall rates with CloudSat retrievals shows that the CloudSat product underestimates snowfall by about 65% when averaged over all the 768 grids in the western United States mountainous regions. The bias does not seem to have clear dependency on elevation but strongly depends on snowfall rate. As an application of the method, we further estimated the snowfall to precipitation ratio using both ground and satellite measured data. It is found that the rates of increase with elevation of the snowfall to precipitation ratio are quite similar when calculating from ground and satellite data, being about 25% per kilometer elevation up or approximately 4% per every degree Cuisses of temperature drop. [ABSTRACT FROM AUTHOR]

• Potential stage biases caused by the thermal expansion and contraction of supporting structures due to diurnal temperature changes were examined. • Noncontact radar-based discharge estimates can be as accurate as in-situ, conventional streamgauges. • There was a notable phase sequencing between the surface velocity and stage, indicative of unsteady flows. • Real-time alerting capabilities of an impending flash flood are demonstrated in a vulnerable, ungauged basin. Accounting for freshwater resources and monitoring floods are vital functions for societies throughout the world. Remote-sensing methods offer great prospects to expand stream monitoring in developing countries and to smaller, headwater streams that are largely ungauged worldwide. This study evaluates the potential to estimate discharge using eight radar units that have been installed over streams in diverse hydrologic and hydraulic settings across the United States. The research highlights error characteristics associated with the measurements of stage using pulsed wave radars, mean channel velocity from continuous wave Doppler radars, and their combined use to estimate discharge at sites that were collocated with conventional streamgauges. Potential stage biases caused by the thermal expansion and contraction of supporting structures due to diurnal temperature changes were examined. A dry concrete, flume showed the temperature-dependent stage variations were no more than 2 cm. Surface velocity retrievals needed to be adjusted to represent the mean channel velocity when estimating discharge. Different approaches were evaluated and application of two different, depth-dependent adjustment factors was found to yield the most accurate estimates. This study found that it is possible to get accurate discharge estimates from noncontact radar measurements, providing cost-effective solutions for remote sensing of ungauged streams. Lastly, radar measurements of the raw variables (i.e., stage and surface velocity) can be used in an early alerting context to detect flash floods in ungauged streams. [ABSTRACT FROM AUTHOR]

Abstract: Ground-based interferometric radar (GBIR) monitoring was conducted on a slow-moving, translational failure landslide in Granby, Grand County, Colorado, USA. Radar monitoring was completed over two separate surveys in 2011 using a tripod mounted real aperture sensor. The purpose of this work is to evaluate GBIR as a temporally dense monitoring technique for monitoring landslide displacement and compare the monitoring results to ongoing GPS based surveying methods to verify measured displacements. We discuss the strengths and limitations of GBIR displacement monitoring with a variety of available sensors, and place this monitoring platform, sensor, and workflow into context of previous slope stability monitoring with GBIR. For both surveys, displacement time series were created through a small temporal baseline stacking to reduce noise and maintain high temporal resolution. The results of the displacement time series were compared to average displacement rates derived from GPS based surveying. An overall verification of radar and GPS derived displacement rates was achieved, and identifies important differences relating to the precision and uncertainty of the two techniques. This work demonstrates GBIR monitoring capability of establishing high temporal resolution on tracking variable rates of landslide movements. Spatial modeling of total observed displacements was completed for both surveys verifying a conceptual model of uniform translational landslide movement, providing greater confidence for mitigation planning. [Copyright &y& Elsevier]

A specific example of radar navigation versus the new cooperative surveillance system, known as Automatic Dependent Surveillance-Broadcast (ADS-B), illustrates the shift in air transportation from the current National Airspace System (NAS) to the Next Generation Air Transportation System (NextGen). Drawing from system-of-systems concepts provides insights into exploring the shift. An agent-based model simulates this specific transition from radar navigation to ADS-B navigation and the benefits thereof, specifically in terms of fuel efficiency, as one of many benefits due to NextGen. The results of the simulation indicate a significant fuel savings when ADS-B is used. Furthermore, the modeling approach appears promising for other studies of NextGen. [ABSTRACT FROM AUTHOR]

Abstract: A substantial number of wind energy projects have been stalled or abandoned in the United States of America (US) due to concerns over the effects of wind turbines on radar installations. Between 2008 and 2010, military, airspace, or meteorological radar concerns in the US contributed to the delay or abandonment of an estimated 20,000 MW of wind energy capacity. These delays are a likely major factor influencing the current US Administration''s failure to double non-hydro renewable generation from 2008 to 2011; a target stated by the US President in a joint session address to Congress in February 2009. The delays are also a threat to the US Department of Energy''s target to produce 20% of electricity from wind energy by 2030 – unless radar-related barriers are mitigated. This work includes interviews with two senior representatives, from the US Department of Defence (DOD) and the American Wind Energy Association (AWEA), discussing the nature of concerns pertaining to the effects of wind turbines on radar and military/aviation in the US alongside approaches that have been trialled that aim to resolve such concerns. This research finds that the Energy Siting Clearing House, established within the DOD to review delayed wind farm projects, has brought much needed coordination to the approval process. A key challenge for any review body, however, will be to deliver an objective outcome that is not overturned by alternative political agendas. Integral to the success of any approach will be a sufficient capacity and mandate to facilitate the technical and non-technical cross-disciplinary and interagency research generating a balance between military, airspace, meteorological, and wind energy industry/political objectives. [Copyright &y& Elsevier]

There is now a large installed base of high-frequency (HF) coastal ocean radars in the United States able to measure surface currents on an operational basis. However, these instruments also have the potential to provide estimates of the spatially variable surface wind field over distances ranging from 10 to 200 km offshore. This study investigates the ability of direction-finding HF radars to recover spatial maps of wind speed and direction from the dominant first-order region radar returns using empirical models. Observations of radar backscatter from the Martha's Vineyard Coastal Observatory HF radar system were compared to wind observations from an offshore tower, finding significant correlations between wind speed and the backscatter power for a range of angles between the wind and radar loop directions. Models for the directional spreading of wind waves were analyzed in comparison to data-based results, finding potentially significant differences between the model and data-based spreading relationships. Using empirical fits, radar-based estimates of wind speed and direction at the location of the in situ wind sensor had error rates of 2 m/s and 60°, which decreased with hourly averaging. Attempts to extrapolate the results to the larger domain illustrated that spatially dependent transfer functions for wind speed and direction appear possible for large coastal ocean domains based on a small number of temporary, or potentially mobile, in situ wind sensors. [ABSTRACT FROM AUTHOR]

Abstract: The hazards attributed to supercell thunderstorms are primarily considered to be tornadoes, large hail, and damaging winds, but flooding from heavy and extreme rainfall is not as often considered with these storms. As a result there has been little research on the role that supercells play in the production of heavy and extreme rainfall events. In order to assess the contribution of supercells to the climatology of short-duration precipitation extremes the present study uses the Warning Decision Support System — Integrated Information to objectively identify supercell thunderstorms from mosaicked radar data during the year 2009 and associate them with high-resolution, accurate multisensor precipitation estimates at time scales of one hour. Supercells are found to be more likely than non-supercells to produce extreme and heavy precipitation, and comparisons are also made between storm types according to month. [Copyright &y& Elsevier]

Total lightning detection systems have been in development since the mid-1980s and deployed in several areas around the world. Previous studies on total lightning found intra- and intercloud lightning (IC) activity tends to fluctuate significantly during the lifetime of thunderstorms and have indicated that lightning jumps or rapid changes in lightning flash rates are closely linked to changes in the vertical integrated liquid (VIL) reading on the National Weather Service's Weather Surveillance Radar-1988 Doppler (WSR-88D) systems. This study examines the total lightning and its relationship to WSR-88D signatures used operationally to determine thunderstorm severity to highlight the potential benefit of a combined forecast approach. Lightning and thunderstorm data from the Dallas-Fort Worth, Texas, and Tucson, Arizona, areas from 2006 to 2009, were used to relate total lightning behavior and radar interrogation techniques. The results indicate that lightning jumps can be classified into severe wind, hail, or mixed-type jumps based on the behavior of various radar-based parameters. In 25 of 34 hail-type jumps and in 18 of 20 wind-type jumps, a characteristic change in cloud-to-ground (CG) versus IC lightning flash rates occurred prior to the report of severe weather. For hail-type jumps, IC flash rates increased, while CG flash rates were steady or decreased. For wind-type jumps, CG flash rates increased, while IC flash rates either increased (12 of 18) or were steady or decreased (6 of 18). Although not every lightning jump resulted in a severe weather report, the characteristic behavior in flash rates adds information to radar-based approaches for nowcasting the severe weather type. [ABSTRACT FROM AUTHOR]

For the first time ever, convection-resolving forecasts at 1 km grid spacing were produced in realtime in spring 2009 by the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma. The forecasts assimilated both radial velocity and reflectivity data from all operational WSR-88D radars within a domain covering most of the continental United States. In preparation for the realtime forecasts, 1 km forecast tests were carried out using a case from spring 2008 and the forecasts with and without assimilating radar data are compared with corresponding 4 km forecasts produced in realtime. Significant positive impact of radar data assimilation is found to last at least 24 hours. The 1 km grid produced a more accurate forecast of organized convection, especially in structure and intensity details. It successfully predicted an isolated severe-weather-producing storm nearly 24 hours into the forecast, which all ten members of the 4 km real time ensemble forecasts failed to predict. This case, together with all available forecasts from 2009 CAPS realtime forecasts, provides evidence of the value of both convection-resolving 1 km grid and radar data assimilation for severe weather prediction for up to 24 hours. [ABSTRACT FROM AUTHOR]

The Sondrestrom upper atmospheric research facility, located just north of the Arctic Circle near the west coast of Greenland, will soon celebrate 30 yr of operations. The centerpiece of the facility, an incoherent scatter radar, has collected 46 000 h of data on the ionospheric state parameters. This instrument was designed and built to measure the effects of nuclear bombs on radio wave propagation in the South Pacific, but instead was deployed to Alaska to study the effects of auroral structuring on the ionosphere, and was later moved to Greenland to explore the auroral cusp and the dynamics of the polar cap boundary. This is the story of the birth and genesis of the instrument, its travels, and the evolution of its facility. [ABSTRACT FROM AUTHOR]

This study explores error sources of the National Weather Service operational radar-based quantitative precipitation estimation (QPE) during the cool season over the complex terrain of the western United States. A new, operationally geared radar QPE was developed and tested using data from the National Oceanic and Atmospheric Administration Hydrometeorology Testbed executed during the 2005/06 cool season in Northern California. The new radar QPE scheme includes multiple steps for removing nonprecipitation echoes, constructing a seamless hybrid scan reflectivity field, applying vertical profile of reflectivity (VPR) corrections to the reflectivity, and converting the reflectivity into precipitation rates using adaptive Z- R relationships. Specific issues in radar rainfall accumulations were addressed, which include wind farm contaminations, blockage artifacts, and discontinuities due to radar overshooting. The new radar QPE was tested in a 6-month period of the 2005/06 cool season and showed significant improvements over the current operational radar QPE (43% reduction in bias and 30% reduction in root-mean-square error) when compared with gauges. In addition, the new technique minimizes various radar artifacts and produces a spatially continuous rainfall product. Such continuity is important for accurate hydrological model predictions. The new technique is computationally efficient and can be easily transitioned into operations. One of the largest remaining challenges is obtaining accurate radar QPE over the windward slopes of significant mountain ranges, where low-level orographic enhancement of precipitation is not resolved by the operational radars leading to underestimation. Additional high-resolution and near-surface radar observations are necessary for more accurate radar QPE over these regions. [ABSTRACT FROM AUTHOR]

On 2 April 2010, a developing quasi-linear convective system (QLCS) moved rapidly northeastward through central Oklahoma spawning at least three intense, mesoscale vortices. At least two of these vortices caused damage rated as category 0 to 1 on the enhanced Fujita scale (EF0-EF1) in and near the town of Rush Springs. Two radar networks--the National Weather Service Weather Surveillance Radar-1988 Doppler network (WSR-88D) and the Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) radar network--collected high spatial and temporal resolution data of the event. This study is an in-depth polarimetric analysis of mesovortices within a QLCS. In this case study, the storm development and evolution of the QLCS mesovortices are examined. Significant findings include the following: 1) The damage in Rush Springs was caused by a combination of the fast translation speed and the embedded circulations associated with QLCS vortices. The vortices' relative winds nearly negated the storm motion to the left of the vortex, but doubled the ground-relative wind to the right of the vortex. 2) A significant differential reflectivity (ZDR) arc developed along the forward flank of the first vortex. The ZDR arc propagated northeastward along the QLCS with the development of each new vortex. 3) A minimum in the copolar correlation coefficient (phv) in the center of the strongest vortex was observed, indicating the likely existence of a polarimetric tornado debris signature (TDS). A secondary Phv minimum also was found just to the right of the vortex center, possibly associated with lofted debris from straight-line winds. [ABSTRACT FROM AUTHOR]

The article presents a study which uses radar and satellite land-cover data to determine the habitats with which birds are associated during migration stopover habitat in the southwestern U.S. The data has been used to study geographical patterns in densities of migrant passerines and quantifying its associations between migrants and their stopover habitats. Results of the study show that it is too simplistic to consider the arid West as inhospitable landscape which has small habitat resources.

Two satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11- μm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD > 0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions. [ABSTRACT FROM AUTHOR]

Sensitivity of 0-12-h warm-season precipitation forecasts to atmospheric initial conditions, including those from different large-scale model analyses and from rapid cycled (RC) three-dimensional variational data assimilations (3DVAR) with and without radar data, is investigated for a 6-day period during the International H2O Project. Neighborhood-based precipitation verification is used to compare forecasts made with the Advanced Research core of the Weather Research and Forecasting Model (ARW-WRF). Three significant convective episodes are examined by comparing the precipitation patterns and locations from different forecast experiments. From two of these three case studies, causes for the success and failure of the RC data assimilation in improving forecast skill are shown. Results indicate that the use of higher-resolution analysis in the initialization, rapid update cycling via WRF 3DVAR data assimilation, and the additional assimilation of radar observations each play a role in shortening the period of the initial precipitation spinup as well as in placing storms closer to observations, thus improving precipitation forecast skill by up to 8-9 h. Impacts of data assimilation differ for forecasts initialized at 0000 and 1200 UTC. The case studies show that the pattern and location of the forecasted precipitation were noticeably improved with radar data assimilation for the two late afternoon cases that featured lines of convection driven by surface-based cold pools. In contrast, the RC 3DVAR, both with and without radar data, had negative impacts on convective forecasts for a case of morning elevated convection associated with a midlatitude short-wave trough. [ABSTRACT FROM AUTHOR]

Little is known about air traffic controllers' preferred maneuvers to resolve conflicts between pairs of aircraft, despite the topic's importance of to the planned NextGen system. We analyzed 256 cases of conflict resolution maneuvering from radar track data from 5 U.S. air traffic control centers. Our results show the influences of conflict geometries on controllers' maneuver choices. [ABSTRACT FROM AUTHOR]

The current network of weather surveillance radars within the United States readily detects flying birds and has proven to be a useful remote-sensing tool for ornithological study. Radar reflectivity measures serve as an index to bird density and have been used to quantitatively map landbird distributions during migratory stopover by sampling birds aloft at the onset of nocturnal migratory flights. Our objective was to further develop and validate a similar approach for mapping wintering waterfowl distributions using weather surveillance radar observations at the onset of evening flights. We evaluated data from the Sacramento, CA radar (KDAX) during winters 1998-1999 and 1999-2000. We determined an optimal sampling time by evaluating the accuracy and precision of radar observations at different times during the onset of evening flight relative to observed diurnal distributions of radio-marked birds on the ground. The mean time of evening flight initiation occurred 23 min after sunset with the strongest correlations between reflectivity and waterfowl density on the ground occurring almost immediately after flight initiation. Radar measures became more spatially homogeneous as evening flight progressed because birds dispersed from their departure locations. Radars effectively detected birds to a mean maximum range of 83 km during the first 20 min of evening flight. Using a sun elevation angle of -5° (28 min after sunset) as our optimal sampling time, we validated our approach using KDAX data and additional data from the Beale Air Force Base, CA (KBBX) radar during winter 1998-1999. Bias-adjusted radar reflectivity of waterfowl aloft was positively related to the observed diurnal density of radio-marked waterfowl locations on the ground. Thus, weather radars provide accurate measures of relative wintering waterfowl density that can be used to comprehensively map their distributions over large spatial extents. [ABSTRACT FROM AUTHOR]

This paper presents a case study of an EF3 tornado that adversely impacted Greene and Pitt Counties in eastern North Carolina on 16 April 2011. This was one of the most damaging and longest-lived of the multiple tornados that occurred across central and eastern North Carolina that day, the most extensive outbreak in North Carolina since 1984. This event occurred during the month (April 2011) with the largest number of tornadoes on record in the United States. The focus of this case study was to examine the relationship between the mesocyclone evolution and the location and intensity of surface damage associated with the EF3 tornado. Results indicated that the initial contraction and spin up of the mesocyclone circulation preceded EF3 damage by about 20 minutes. At the time of mesocyclone intensification, the damage swath and tornado were situated much closer to the mesocyclone center than in the formative and dissipating stages. The weakened mesocyclone passed directly over a meteorological station at East Carolina University's West Research Campus, providing a rare opportunity for surface measurements associated with a weakening tornadic mesocyclone. [ABSTRACT FROM AUTHOR]