Department of Computer Science and Electronic, Universidad de la Costa, Barranquilla 080002, Colombia.
Department of Electrical Engineering, University of Puerto Rico at Mayagüez, Mayagüez, PR 00681-9018, USA.
Sensors (Basel). 2022 Aug 2;22(15):5773. doi: 10.3390/s22155773.
During extreme events such as tropical cyclones, the precision of sensors used to sample the meteorological data is vital to feed weather and climate models for storm path forecasting, quantitative precipitation estimation, and other atmospheric parameters. For this reason, periodic data comparison between several sensors used to monitor these phenomena such as ground-based and satellite instruments, must maintain a high degree of correlation in order to issue alerts with an accuracy that allows for timely decision making. This study presents a cross-evaluation of the radar reflectivity from the dual-frequency precipitation radar (DPR) onboard the Global Precipitation Measurement Mission (GPM) and the U.S. National Weather Service (NWS) Next-Generation Radar (NEXRAD) ground-based instrument located in the Caribbean island of Puerto Rico, USA, to determine the correlation degree between these two sensors' measurements during extreme weather events and normal precipitation events during 2015-2019. GPM at Ku-band and Ka-band and NEXRAD at S-band overlapping scanning regions data of normal precipitation events during 2015-2019, and the spiral rain bands of four extreme weather events, Irma (Category 5 Hurricane), Beryl (Tropical Storm), Dorian (Category 1 hurricane), and Karen (Tropical Storm), were processed using the GPM Ground Validation System (GVS). In both cases, data were classified and analyzed statistically, paying particular attention to variables such as elevation angle mode and precipitation type (stratiform and convective). Given that ground-based radar (GR) has better spatial and temporal resolution, the NEXRAD was used as ground-truth. The results revealed that the correlation coefficient between the data of both instruments during the analyzed extreme weather events was moderate to low; for normal precipitation events, the correlation is lower than that of studies that compared GPM and NEXRAD reflectivity located in other regions of the USA. Only Tropical Storm Karen obtained similar results to other comparative studies in terms of the correlation coefficient. Furthermore, the GR elevation angle and precipitation type have a substantial impact on how well the rain reflectivity correlates between the two sensors. It was found that the Ku-band channel possesses the least bias and variability when compared to the NEXRAD instrument's reflectivity and should therefore be considered more reliable for future tropical storm tracking and tropical region precipitation estimates in regions with no NEXRAD coverage.
在热带气旋等极端事件中，用于采样气象数据的传感器的精度对于为风暴路径预测、定量降水估计和其他大气参数提供天气和气候模型至关重要。出于这个原因，必须保持监测这些现象（如地面和卫星仪器）的多个传感器之间的定期数据比较高度相关，以便以允许及时做出决策的准确性发出警报。本研究对搭载在全球降水测量任务（GPM）上的双频降水雷达（DPR）和位于美国波多黎各的美国国家气象局（NWS）下一代雷达（NEXRAD）地面仪器的雷达反射率进行了交叉评估，以确定这两个传感器在 2015-2019 年极端天气事件和正常降水事件期间的测量值之间的相关程度。GPM 在 Ku 波段和 Ka 波段以及 NEXRAD 在 S 波段重叠扫描区域的 2015-2019 年正常降水事件的数据，以及四个极端天气事件（飓风 5 级 Irma、热带风暴 Beryl、飓风 1 级 Dorian 和热带风暴 Karen）的螺旋雨带，使用 GPM 地面验证系统（GVS）进行了处理。在这两种情况下，数据都经过分类和统计分析，特别注意海拔角模式和降水类型（层状和对流）等变量。由于地面雷达（GR）具有更好的空间和时间分辨率，因此将 NEXRAD 用作地面实况。结果表明，在分析的极端天气事件期间，两个仪器的数据之间的相关系数为中等至低等；对于正常降水事件，相关性低于在美国其他地区比较 GPM 和 NEXRAD 反射率的研究。只有热带风暴 Karen 在相关系数方面与其他比较研究相似。此外，GR 仰角和降水类型对两个传感器之间的雨反射率相关性有很大影响。结果发现，与 NEXRAD 仪器的反射率相比，Ku 波段通道的偏差和可变性最小，因此对于未来没有 NEXRAD 覆盖的地区的热带风暴跟踪和热带地区降水估计，应考虑更可靠。
