Spatiotemporal bias adjustment of IMERG satellite precipitation data across Canada

Moazami, Saber; Na, Wooyoung; Najafi, Mohammad Reza; Souza, Camila P. E. de

doi:10.1016/j.advwatres.2022.104300

Cited by 10 publications

(2 citation statements)

References 99 publications

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“…The validation of IMERG is of paramount importance for understanding and addressing estimation errors, both for algorithm improvements and to document the capabilities and limitations for further applications developed by the scientific and operational communities [13]. Past research has confirmed IMERG ability to reproduce global spatial features of precipitation fields at yearly and seasonal scales [14][15][16]. However, spaceborne precipitation estimates at shorter time scales, particularly in case of heavy rainfall events, pose more challenges, with a general tendency to underestimation [12,[16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Disentangling Satellite Precipitation Estimate Errors of Heavy Rainfall at Daily and Sub-daily scale in the Western Mediterranean.

Peinó,

Bech,

Udina

et al. 2024

Preprint

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The performance of Integrated Multisatellite Retrievals for GPM (V06B-IMERG) is evaluated at subdaily and daily scale using 10 years of heavy precipitation over a region in the Western Med-iterranean for different temporal aggregations with a dense network of rain gauges. On a half-hourly scale, the contribution of passive microwave (PMW) and infrared (IR) sources in the satellite estimates was considered, as well as the relation of various microphysical properties of cloud tops using Cloud Microphysics (CMIC- NWC SAF) data. IMERG shows a marked tendency to underestimate precipitation compared to rain gauges as the rainfall intensity threshold and temporal resolution increases. Results indicate that the negative bias is weaker when retrievals are due to PMW data. On the other hand, the benefits of filling the PMW gaps of IMERG by including IR information come at the expense of increasing the bias. IMERG performs dramatically better in the presence of precipitating ice clouds compared to warm and mixed phase clouds, which seems to be related with microphysical properties such as cloud optical thickness and cloud top effective radius. This work contributes to the understanding of the factors affecting satellite estimates of extreme precipitation and their relationship with the microphysical characteristics of clouds, which generates added value for further downstream applications and users’ decision making.

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Section: Introductionmentioning

confidence: 99%

Disentangling Satellite Precipitation Estimate Errors of Heavy Rainfall at Daily and Sub-daily scale in the Western Mediterranean.

Peinó,

Bech,

Udina

et al. 2024

Preprint

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show abstract

“…The extreme rain event caused extensive flooding that washed out roads and damaged essential infrastructures such as storm sewers and electrical systems. Both flood and tornado events are common natural hazards in many regions around the world with drastic consequences (Moazami et al, 2022; Sorboni et al, 2022; Wang et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Probabilistic assessment of concurrent tornado and storm‐related flash flood events

Ngui

Najafi

Souza

et al. 2023

Intl Journal of Climatology

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The concurrent occurrence of extreme events can significantly impact societies and infrastructure systems, especially when the instructions provided to the exposed communities demand conflicting responses. In this study, a probabilistic assessment of concurrent tornado and storm-related flash flood (TORFF) events is performed across southern Canada. We quantify the interdependencies between tornadoes and flash floods (extreme precipitation as proxy) using ground-based and reanalysis datasets. Windspeed values corresponding to tornado events, categorized based on the recorded Fujita rating, are derived through a resampling approach. The TORFF events are clustered and the corresponding bivariate probability distributions of the resampled windspeed and associated precipitation are characterized based on Copula framework. The individual and joint return periods of concurrent tornadoes and flash floods are then assessed under the AND (when both variables exceed predefined thresholds), OR (when either one of the two variables exceeds predefined thresholds), and conditional hazard scenarios across Canada. Results show positive strong dependencies between resampled windspeed and associated precipitation in Saskatchewan, and weaker dependencies followed by Alberta, Manitoba, Ontario, and Quebec. The Saskatchewan region shows the highest risk underestimation considering the independence scenario compared to the other regions. Higher precipitation is also expected during extreme windspeed, as observed in the conditional assessment of precipitation given windspeed. This study provides insights for more robust recurrence interval estimation for tornadoes and flash floods to aid in emergency planning of evacuation decision-making process.

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Rising risks of hydroclimatic swings: A large ensemble study of dry and wet spell transitions in North America

Na,

Najafi

2024

Global and Planetary Change

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Spatiotemporal bias adjustment of IMERG satellite precipitation data across Canada

Cited by 10 publications

References 99 publications

Disentangling Satellite Precipitation Estimate Errors of Heavy Rainfall at Daily and Sub-daily scale in the Western Mediterranean.

Disentangling Satellite Precipitation Estimate Errors of Heavy Rainfall at Daily and Sub-daily scale in the Western Mediterranean.

Probabilistic assessment of concurrent tornado and storm‐related flash flood events

Rising risks of hydroclimatic swings: A large ensemble study of dry and wet spell transitions in North America

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