Uncertainty analysis of radar rainfall estimates over two different climates in Iran

Ghaemi, Esmail; Kavianpour, Mohammad Reza; Moazami, Saber; Hong, Yang; Ayat, Hooman

doi:10.1080/01431161.2017.1335909

Cited by 10 publications

(6 citation statements)

References 17 publications

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“…Weather radars can provide precipitation products with high spatiotemporal resolution, though they are affected by factors such as poor coverage, beam blockage in complex regions, and expensive operating and maintenance costs (Derin et al 2019;Gebregiorgis et al 2017;Krajewski and Smith 2002;Young et al 2000). These issues limit the applicability of these products to certain populated regions in some countries (Ayat et al 2018;Ghaemi et al 2017;X. Zhang et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Are Storm Characteristics the Same When Viewed Using Merged Surface Radars or a Merged Satellite Product?

Ayat

Evans

Sherwood

et al. 2021

Journal of Hydrometeorology

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High- resolution datasets offer the potential to improve our understanding of spatial and temporal precipitation patterns and storm structures. The goal of this study is to evaluate the similarities and differences of object-based storm characteristics as observed using space or land based sensors. The Method of Object-based Diagnostic Evaluation (MODE) Time Domain (MTD) is used to identify and track storm objects in two high resolution merged datasets: the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) final product V06B and gauge-corrected ground radar based Multi-Radar Multi-Sensor Quantitative Precipitation Estimates (MRMS). Characteristics associated with landfalling hurricanes were also examined as a separate category of storm. The results reveal that IMERG and MRMS agree reasonably well across many object-based storm characteristics. However, there are some discrepancies that are statistically significant. MRMS storms are more concentrated, with smaller areas and higher peak intensities, which implies higher flash-flood risks associated with the storms. On the other hand, IMERG storms can travel longer distances with a higher volume of precipitation, which implies higher risk of riverine flooding. Agreement between the datasets is higher for faster moving hurricanes in terms of the averaged intensity. Finally, MRMS indicates a higher average precipitation intensity during the hurricane's lifetime. However, in non-hurricanes, the opposite result was observed. This is likely related to MRMS having higher resolution; monitoring the hurricanes from many viewing angles, leading to different signal saturation properties compared to IMERG; and/or, the dominance of droplet aggregation effects over evaporation effects at lower altitudes.

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Section: Introductionmentioning

confidence: 99%

Are Storm Characteristics the Same When Viewed Using Merged Surface Radars or a Merged Satellite Product?

Ayat

Evans

Sherwood

et al. 2021

Journal of Hydrometeorology

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“…The plains of this province, however, have a desert climate with very warm and dry summers. Precipitation in this province falls mostly during the winter and ranges from 300 mm in the plains to 500 mm toward highlands (Ghaemi et al, 2017).…”

Section: Methodsmentioning

confidence: 99%

Testing Possible Scenario-Based Responses of Vegetation Under Expected Climatic Changes in Khuzestan Province

Damaneh

Jafari

Damaneh

et al. 2021

Air, Soil and Water Research

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Projections of future scenarios are scarce in developing countries where human activities are increasing and impacting land uses. We present a research based on the assessment of the baseline trends of normalized difference vegetation index (NDVI), precipitation, and temperature data for the Khuzestan Province, Iran, from 1984 to 2015 compiled from ground-based and remotely sensed sources. To achieve this goal, the Sen’s slope estimator, the Mann-Kendall test, and Pearson’s correlation test were used. After that, future trends in precipitation and temperature were estimated using the Canadian Earth System Model (CanESM2) model and were then used to estimate the NDVI trend for two future periods: from 2016 to 2046 and from 2046 to 2075. Our results showed that during the baseline period, precipitation decreased at all stations: 33.3% displayed a significant trend and the others were insignificant ones. Over the same period, the temperature increased at 66.7% of stations while NDVI decreased at all stations. The NDVI–precipitation relationship was positive while NDVI–temperature showed an inverse trend. During the first of the possible future periods and under the RCP2.6, RCP4.5, and RCP8.5 scenarios, NDVI and precipitation decreased, and temperatures significantly increased. In addition, the same trends were observed during the second future period; most of these were statistically significant. We conclude that much assessments are valuable and integral components of effective ecosystem planning and decisions.

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“…High spatio-temporal resolution radar rainfall estimates offer great potential to study a wide range of precipitation systems that appear in their coverage areas, particularly over the regions in which gauge observations are usually sparse or unevenly distributed (Ghaemi et al 2017;Ayat et al 2018;Moazami et al 2014). Radar records in many parts of the globe are temporally limited to just over a decade (Allen 2018).…”

Section: Introductionmentioning

confidence: 99%

An object-based climatology of precipitation systems in Sydney, Australia

et al. 2022

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The climate is warming and this is changing some aspects of storms, but we have relatively little knowledge of storm characteristics beyond intensity, which limits our understanding of storms overall. In this study, we apply a cell-tracking algorithm to 20 years of radar data at a mid-latitude coastal-site (Sydney, Australia), to establish a regional precipitation system climatology. The results show that extreme storms in terms of translation-speed, size and rainfall intensity usually occur in the warm season, and are slower and more intense over land between ~ 10 am and ~ 8 pm (AEST), peaking in the afternoon. Precipitation systems are more frequent in the cold season and often initiate over the ocean and move northward, leading to precipitation mostly over the ocean. Using clustering algorithms, we have found five precipitation system types with distinct properties, occurring throughout the year but peaking in different seasons. While overall rainfall statistics don't show any link to climate modes, links do appear for some system types using a multivariate approach. This climatology for a variety of precipitation system characteristics will allow future study of any changes in these characteristics due to climate change.

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Uncertainty analysis of radar rainfall estimates over two different climates in Iran

Cited by 10 publications

References 17 publications

Are Storm Characteristics the Same When Viewed Using Merged Surface Radars or a Merged Satellite Product?

Are Storm Characteristics the Same When Viewed Using Merged Surface Radars or a Merged Satellite Product?

Testing Possible Scenario-Based Responses of Vegetation Under Expected Climatic Changes in Khuzestan Province

An object-based climatology of precipitation systems in Sydney, Australia

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