One of the primary missions of the National Weather Service (NWS) is to use a network of more than 150 NEXRAD radar installations to monitor weather for threats to life and property. Large hail produced by severe thunderstorms is a major focus of this mission. An algorithm known as the Maximum Estimated Size of Hail (MESH) algorithm is in operational use to diagnose the presence and size of hail. This study aims to use dual-Doppler observations as well as the MESH algorithm to test the idea that storms that rotate produce larger hail. Previous studies have used polarimetric radar products to detect the presence of large hail and dual-Doppler methods have been used to study embryonic hail, but no research has tested the theory of hail and rotating storms with observational evidence. A set of 59 case studies was gathered; each included a hail report submitted by a trained weather spotter or NWS employee and complete radar observations through the depth of a storm from two radars. The radar observations were resampled to a three-dimensional Cartesian grid and a dual-Doppler analysis was run on each case study. A strong correlation (stronger even than the MESH algorithm) was found between measured vorticity and hail size, lending credence to the idea that rotating storms do indeed have a higher ceiling for hail production. However, no correlation was found between MESH error and rotation. Further research will be required to evaluate whether or not this relationship can be used to augment the MESH algorithm so as to improve its skill. / Master of Science / The National Weather Service (NWS) uses a nationwide network of long-range weather radars to monitor the atmosphere over the United States. One of the primary applications of that network is to protect life and property by identifying and monitoring storms capable of producing large hail. The probable size of hail is estimated using an algorithm on raw radar data. This study uses multi-radar analysis methods to establish a metric for storm rotation, which is used in conjunction with the operational hail size algorithm to test the theory that rotating storms produce larger hail. A set of 59 case studies, each composed of data from a pair of radars as well as a measured hail size from a storm spotter, was gathered and analyzed. Analysis resulted in three values per case study: actual hail size, predicted hail size, and storm rotation intensity. Storm rotation and actual hail size were found to be strongly correlated, lending credence to the idea that rotation increases a storm’s hail production ceiling. However, no strong correlation was found between the operational algorithm’s error and storm rotation. Additional research will be required to determine if the relationship between rotation and actual hail size can be used to improve the skill of current operational algorithms.

As wind energy plants continue to grow in size and complexity, advanced measurement technologies such as scanning Doppler LiDAR are essential for assessing site conditions and prospecting new development areas.   The RUNE project was initiated to determine best practices for the use of scanning LiDARs in resource assessments for near shore wind farms. The purpose of this thesis is to determine the optimum configuration for the plan position indicator (PPI) scan type of a scanning LiDAR. A task specific Automated Analysis Software (AAS) is created, and the sensitivity of the integrated velocity azimuth process (iVAP) reconstruction algorithm is examined using sector sizes ranging from 4 to 60 degrees. Further, a comparison to simultaneous dual Doppler measurement is presented in order to determine the necessity of deploying two LiDARs rather than one.    DTU has developed a coordinated long range coherent scanning multi-LiDAR array (the WindScanner system) based on modified Leosphere WindCube 200S devices and an application specific software framework and communication protocol. The long range WindScanner system was deployed at DTU’s test station in Høvsøre, Denmark and measurement data was collected over a period of 7 days. One WindScanner was performing 60 degree sector scans, while two others were placed in staring dual Doppler mode. All three beams were configured to converge atop a 116.5m instrumented meteorological mast.   A significant result was discovered which indicates that the accuracy of the reconstructed measurements do not differ significantly between sector sizes of 30 and 60 degrees. Using the smallest sector size which does not introduce systematic error has numerous benefits including: increasing the scan speed, measurement distance and angular resolution.   When comparing collocated dual Doppler, sector scan and in-situ met-mast instrumentation, we find very good agreement between all techniques. Dual Doppler is able to measure wind speeds within 0.1%, and 60 degree sector scan within 0.2% on average of the reference values. For retrieval of wind direction, the sector scan approach performs particularly well. This is likely attributable to lower errors introduced by the assumption of flow field homogeneity over the scanned area, in contract to wind direction which tends to be more non-uniform. For applications such as site resource assessments, where generally accurate 10 minute wind speed and direction values are required, a scanning LiDAR performing PPI scans with a sector size of between 30 and 38 degrees is recommended. The laser’s line of sight path should be directed parallel to the predominant wind direction and at the lowest elevation angle possible. / RUNE