Potential use of the GLM for nowcasting and data assimilation

Vendrasco, Éder Paulo; Machado, Luiz A. T.; Araujo, Carolina S.; Ribaud, Jean-François; Ferreira, Rute

doi:10.1016/j.atmosres.2020.105019

Cited by 7 publications

(3 citation statements)

References 74 publications

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“…The IWP values (Figure 5b) were highest in the T4 sub-region, followed by the T3 sub-region. This fact corroborates the importance of this variable for charge generation in storm clouds and the consequent lightning occurrence, since the highest (smallest) densities occurred in the sub-region with the highest (smallest) amount of ice, reinforcing the close relationship between ice content and cloud electrification [14,20,27,35,37,84,96]. The Tukey multiple comparison test (Figure 6b), indicated that the IWC of the T4 sub-region is statistically different from the others (p-value < 0.1) and no significant difference between T1 and T2, and between T1 and T3.…”

Section: Microphysical Properties As a Function Of Lightning Tertilessupporting

confidence: 76%

Clouds’ Microphysical Properties and Their Relationship with Lightning Activity in Northeast Brazil

et al. 2021

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The Northeast region of Brazil (NEB) has a high rate of deaths from lightning strikes (18% of the country’s total). The region has states, such as Piauí, with high mortality rates (1.8 deaths per million), much higher than the national rate (0.8) and the NEB rate (0.5). In this sense, the present work analyzes the microphysical characteristics of clouds with and without the occurrence of total lightning. For this purpose, data from the Lightning Imaging Sensor (LIS), TRMM Microwave Imager (TMI) and Precipitation Radar (PR), aboard the Tropical Rainfall Measuring Mission (TRMM) satellite from 1998 to 2013 were used. The TRMM data were analyzed to establish a relationship between the occurrence of lightning and the clouds’ microphysical characteristics, comparing them as a function of lightning occurrence classes, spatial location and atmospheric profiles. A higher lightning occurrence is associated with higher values of ice water path (>38.9 kg m−2), rain water path (>2 kg m−2), convective precipitation (>5 mm h−1) and surface precipitation (>7 mm h−1), in addition to slightly higher freezing level height values. Reflectivity observations (>36 dBZ) demonstrated typical convective profile curves, with higher values associated with classes with higher lightning densities (class with more than 6.8 flash km−2 year−1).

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Section: Microphysical Properties As a Function Of Lightning Tertilessupporting

confidence: 76%

Clouds’ Microphysical Properties and Their Relationship with Lightning Activity in Northeast Brazil

et al. 2021

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“…Correspondingly, more studies are required to assess the performance of GPM IMERG against other satellite and reanalysis products to find the advantages and limitations of the GPM satellite. Furthermore, other precipitation specific properties such as spatial and temporal heterogeneity, spatial and temporal intermittence, extreme variability and multi-fractal comparisons is necessary to overcome substantial uncertainties rainfall estimations [57][58][59]. Cristiano et al [60] also depicted in their review that the rainfall variability may need wider range of conditions and scenario based in observational datasets for urban hydrological basins, which need proper analysis for development of better hydrological response system with higher sensitivity.…”

Section: Future Studies and Shortcomingsmentioning

confidence: 99%

GPM Annual and Daily Precipitation Data for Real-Time Short-Term Nowcasting: A Pilot Study for a Way Forward in Data Assimilation

Wang

Kong

Yang

et al. 2021

Water

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This study explores the quality of data produced by Global Precipitation Measurement (GPM) and the potential of GPM for real-time short-term nowcasting using MATLAB and the Short-Term Ensemble Prediction System (STEPS). Precipitation data obtained by rain gauges during the period 2015 to 2017 were used in this comparative analysis. The results show that the quality of GPM precipitation has different degrees efficacies at the national scale, which were revealed at the performance analysis stage of the study. After data quality checking, five representative precipitation events were selected for nowcasting evaluation. The GPM estimated precipitation compared to a 30 min forecast using STEPS precipitation nowcast results, showing that the GPM precipitation data performed well in nowcasting between 0 to 120 min. However, the accuracy and quality of nowcasting precipitation significantly reduced with increased lead time. A major finding from the study is that the quality of precipitation data can be improved through blending processes such as kriging with external drift and the double-kernel smoothing method, which enhances the quality of nowcast over longer lead times.

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“…Lightning data assimilation (LDA) has been widely used to improve the intense precipitation forecast worldwide because of the ability of lightning to precisely locate areas of deep convection. Different techniques have been used for LDA as follows: (a) The forcing of water vapour and other hydrometeors, with both nudging [22][23][24][25][26][27][28] and 3D-Var [21,29,30], (b) retrieving the convective precipitation and latent heat profile by lightning and adjusting the initial three-dimensional thermo-dynamic field of NWP models [31,32], (c) retrieving the radar reflectivity by lightning and assimilating it in NWP models [33][34][35][36], and (d) forcing convection through the adjustment of thermo-dynamical fields [37]. Attempts to suppress spurious convection through lightning data assimilation have also been reported in the literature [38].…”

Section: Introductionmentioning

confidence: 99%

Study of the Intense Meteorological Event Occurred in September 2022 over the Marche Region with WRF Model: Impact of Lightning Data Assimilation on Rainfall and Lightning Prediction

Torcasio,

Papa,

Del Frate

et al. 2023

Atmosphere

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A destructive V-shaped thunderstorm occurred over the Marche Region, in Central Italy, on 15 September 2022. Twelve people died during the event, and damage to properties was extensive because the small Misa River flooded the area. The synoptic-scale conditions that caused this disastrous event are analysed and go back to the presence of tropical cyclone Danielle in the eastern Atlantic. The performance of the weather research and forecasting (WRF) model using lightning data assimilation (LDA) is studied in this case by comparing the forecast with the control forecast without lightning data assimilation. The forecast performance is evaluated for precipitation and lightning. The case was characterised by four intense 3-h (3 h) periods. The forecasts of these four 3-h phases are analysed in a very short-term forecast (VSF) approach, in which a 3 h data assimilation phase is followed by a 3 h forecast. A homemade 3D-Var is used for lightning data assimilation with two different configurations: ANL, in which the lightning is assimilated until the start of the forecasting period, and ANL-1H, which assimilates lightning until 1 h before the 3 h forecasting period. A sensitivity test for the number of analyses used is also discussed. Results show that LDA has a significant and positive impact on the precipitation and lightning forecast for this case.

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Potential use of the GLM for nowcasting and data assimilation

Cited by 7 publications

References 74 publications

Clouds’ Microphysical Properties and Their Relationship with Lightning Activity in Northeast Brazil

Clouds’ Microphysical Properties and Their Relationship with Lightning Activity in Northeast Brazil

GPM Annual and Daily Precipitation Data for Real-Time Short-Term Nowcasting: A Pilot Study for a Way Forward in Data Assimilation

Study of the Intense Meteorological Event Occurred in September 2022 over the Marche Region with WRF Model: Impact of Lightning Data Assimilation on Rainfall and Lightning Prediction

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