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Start Over Author "Ayat, Hooman" Topic climatology
4 results on '"Ayat, Hooman"'

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

Author

Ayat, Hooman, Evans, Jason P., Sherwood, Steven C., and Soderholm, Joshua

Subjects
*CLIMATOLOGY, *GLOBAL warming, *STORMS, *MODES of variability (Climatology), *CLIMATE change
Abstract

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. [ABSTRACT FROM AUTHOR]

Published
2023
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2. Quantifying various thunderstorm characteristics during high impact events using radar and satellite observations

Author

Ayat, Hooman

Subjects
MRMS, satellite, rainfall, climatology, 370201 Climate change processes, extremes, storm track, short-duration, cell tracking, MODE, IMERG, precipitaiton, object-based, Sydney, intensification, radar
Abstract

Climate change is expected to change the intensity and frequency of heavy storms. Thus, understanding different characteristics of this phenomena (i.e., intensity, size, speed, direction, etc.) is vital for the effective climate adaptation. Many extreme storms have small areas and short lifetimes (sub-daily/hourly) and can have destructive impacts, especially over urban areas. Therefore, it is vital to understand the nature of changes in these extremes to reduce the risk of their destructive impacts on cities. The overarching goal of this thesis is to quantify various storm characteristics, including their changes, using radar and satellite observations. Using an object-based technique, I compare the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) and ground radar based Multi-Radar Multi-Sensor Quantitative Precipitation Estimates (MRMS) over the United States and show that the object-based storm properties are not sensitive to the observational platforms. However, there are differences that are statistically significant. Secondly, I investigate the error sources associated with different types of contributing data in the IMERG during the hurricane days occurred in 2016-2018 with MRMS as the reference. The results show that IMERG have better agreement with MRMS during the passive microwave (PMW) observations compared to rainfall estimates come from the combination of the interpolation techniques and infrared observations (morph/IR). Also, the quality of morph/IR estimates deteriorates with the longer absence of PMW observations. Thirdly, I establish an object-based climatology of rain systems using radar data near Sydney, Australia. The results show that rain systems in different seasons have distinct object-based characteristics, and these differences are dependent on their source of origins and also their positions over land and ocean. Using a two-step clustering algorithm, I have found five system types over Sydney 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. Finally, I show that there is a robust increasing trend of 20% per decade in sub-hourly extreme rainfall in the Sydney region over 20 years, despite no evidence of trends on hourly or daily scales. I am able to obtain this new result via a novel analysis of long-term radar data, including cross-checking between neighboring radars.

Published
2022
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3. Intensification of subhourly heavy rainfall.

Author

Ayat, Hooman, Evans, Jason P., Sherwood, Steven C., and Soderholm, Joshua

Subjects
*RAINFALL, *FLOODS, *METEOROLOGICAL precipitation, *CLIMATOLOGY
Abstract

Short-duration rainfall extremes can cause flash flooding with associated impacts. Previous studies of climate impacts on extreme precipitation have focused mainly on daily rain totals. Subdaily extremes are often generated in small areas that can be missed by gauge networks or satellites and are not resolved by climate models. Here, we show a robust positive trend of at least 20% per decade in subhourly extreme rainfall near Sydney, Australia, over 20 years, despite no evidence of trends at hourly or daily scales. This trend is seen consistently in storms tracked using multiple independent ground radars, is consistent with rain-gauge data, and does not appear to be associated with known natural variations. This finding suggests that subhourly rainfall extremes may be increasing substantially faster than those on more widely reported time scales. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
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4. Quantifying various thunderstorm characteristics during high impact events using radar and satellite observations

Author

Ayat, Hooman ; https://orcid.org/0000-0001-9499-5894

Subjects
precipitaiton, extremes, object-based, climatology, radar, satellite, rainfall, intensification, short-duration, IMERG, MRMS, Sydney, MODE, storm track, cell tracking, anzsrc-for: 370201 Climate change processes
Abstract

Climate change is expected to change the intensity and frequency of heavy storms. Thus, understanding different characteristics of this phenomena (i.e., intensity, size, speed, direction, etc.) is vital for the effective climate adaptation. Many extreme storms have small areas and short lifetimes (sub-daily/hourly) and can have destructive impacts, especially over urban areas. Therefore, it is vital to understand the nature of changes in these extremes to reduce the risk of their destructive impacts on cities. The overarching goal of this thesis is to quantify various storm characteristics, including their changes, using radar and satellite observations. Using an object-based technique, I compare the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) and ground radar based Multi-Radar Multi-Sensor Quantitative Precipitation Estimates (MRMS) over the United States and show that the object-based storm properties are not sensitive to the observational platforms. However, there are differences that are statistically significant. Secondly, I investigate the error sources associated with different types of contributing data in the IMERG during the hurricane days occurred in 2016-2018 with MRMS as the reference. The results show that IMERG have better agreement with MRMS during the passive microwave (PMW) observations compared to rainfall estimates come from the combination of the interpolation techniques and infrared observations (morph/IR). Also, the quality of morph/IR estimates deteriorates with the longer absence of PMW observations. Thirdly, I establish an object-based climatology of rain systems using radar data near Sydney, Australia. The results show that rain systems in different seasons have distinct object-based characteristics, and these differences are dependent on their source of origins and also their positions over land and ocean. Using a two-step clustering algorithm, I have found five system types over Sydney 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. Finally, I show that there is a robust increasing trend of 20% per decade in sub-hourly extreme rainfall in the Sydney region over 20 years, despite no evidence of trends on hourly or daily scales. I am able to obtain this new result via a novel analysis of long-term radar data, including cross-checking between neighboring radars.

Published
2022

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