An evaluation of IMERG and ERA5 quantitative precipitation estimates over the Southern Ocean using shipborne observations

IF 2.6 3区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Journal of Applied Meteorology and Climatology Pub Date : 2023-11-01 DOI:10.1175/jamc-d-23-0039.1
E. Montoya Duque, Y. Huang, P.T. May, S.T. Siems
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引用次数: 1

Abstract

Abstract Recent voyages of the Australian R/V Investigator across the remote Southern Ocean have provided unprecedented observations of precipitation made with both an Ocean Rainfall and Ice-Phase Precipitation Measurement Network (OceanRAIN) maritime disdrometer and a dual-polarization C-band weather radar (OceanPOL). This present study employs these observations to evaluate the Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) and the fifth major global reanalysis produced by ECMWF (ERA5) precipitation products. Working at a resolution of 60 min and 0.25° (∼25 km), light rain and drizzle are most frequently observed across the region. The IMERG product overestimated precipitation intensity when evaluated against the OceanRAIN but captured the frequency of occurrence well. Looking at the synoptic/process scale, IMERG was found to be the least accurate (overestimated intensity) under warm-frontal and high-latitude cyclone conditions, where multilayer clouds were commonly present. Under postfrontal conditions, IMERG underestimated the precipitation frequency. In comparison, ERA5’s skill was more consistent across various synoptic conditions, except for high pressure conditions where the precipitation frequency (intensity) was highly overestimated (underestimated). Using the OceanPOL radar, an area-to-area analysis (fractional skill score) finds that ERA5 has greater skill than IMERG. There is little agreement in the phase classification between the OceanRAIN disdrometer, IMERG, and ERA5. The comparisons are complicated by the various assumptions for phase classification in the different datasets. Significance Statement Our best quantitative estimates of precipitation over the remote, pristine Southern Ocean (SO) continue to suffer from a high degree of uncertainty, with large differences present among satellite-based and reanalysis products. New instrumentation on the R/V Investigator , specifically a dual-polarization C-band weather radar (OceanPOL) and a maritime disdrometer (OceanRAIN), provide unprecedented high-quality observations of precipitation across the SO that will aid in improving precipitation estimates in this region. We use these observations to evaluate the IMERG and ERA5 precipitation products. We find that, in general, IMERG overestimated precipitation intensity, but captured the frequency of occurrence well. In comparison, ERA5 was found to overestimate the frequency of precipitation. Using the OceanPOL radar, an area-to-area analysis finds that ERA5 has greater skill than IMERG.
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利用船载观测对南大洋IMERG和ERA5定量降水估计的评价
最近,澳大利亚R/V探测器穿越遥远的南大洋,利用海洋降雨和冰相降水测量网络(OceanRAIN)海洋分差仪和双极化c波段天气雷达(OceanPOL)提供了前所未有的降水观测。本研究利用这些观测资料对全球降水测量(GPM)综合多卫星检索(IMERG)和ECMWF降水产品产生的第五次主要全球再分析(ERA5)进行了评估。在60分钟和0.25°(~ 25公里)的分辨率下,整个地区最常观测到小雨和毛毛雨。IMERG产品在与OceanRAIN进行评估时高估了降水强度,但很好地捕捉到了发生频率。从天气/过程尺度来看,在通常存在多层云的暖锋和高纬度气旋条件下,IMERG是最不准确的(高估强度)。在锋后条件下,IMERG低估了降水频率。相比之下,ERA5的技能在各种天气条件下更加一致,除了高压条件下降水频率(强度)被高度高估(低估)。使用OceanPOL雷达,区域对区域分析(分数技能分数)发现ERA5比IMERG具有更高的技能。在相位分类上,OceanRAIN分差仪、IMERG和ERA5的差异不大。由于在不同的数据集中对相位分类的不同假设,比较变得复杂。我们对遥远的、原始的南大洋(SO)降水的最佳定量估计仍然存在高度的不确定性,卫星产品和再分析产品之间存在很大差异。R/V调查员号上的新仪器,特别是双偏振c波段天气雷达(OceanPOL)和海洋分差仪(OceanRAIN),提供了前所未有的高质量的降水观测,这将有助于改善该地区的降水估计。我们利用这些观测值来评估IMERG和ERA5降水产品。我们发现,总的来说,IMERG高估了降水强度,但很好地捕捉了降水发生的频率。相比之下,ERA5高估了降水频率。使用海洋刑警组织的雷达,区域对区域分析发现,ERA5比IMERG具有更高的技能。
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来源期刊
Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology 地学-气象与大气科学
CiteScore
5.10
自引率
6.70%
发文量
97
审稿时长
3 months
期刊介绍: The Journal of Applied Meteorology and Climatology (JAMC) (ISSN: 1558-8424; eISSN: 1558-8432) publishes applied research on meteorology and climatology. Examples of meteorological research include topics such as weather modification, satellite meteorology, radar meteorology, boundary layer processes, physical meteorology, air pollution meteorology (including dispersion and chemical processes), agricultural and forest meteorology, mountain meteorology, and applied meteorological numerical models. Examples of climatological research include the use of climate information in impact assessments, dynamical and statistical downscaling, seasonal climate forecast applications and verification, climate risk and vulnerability, development of climate monitoring tools, and urban and local climates.
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