A conceptual prediction model for seasonal drought processes using atmospheric and oceanic standardized anomalies: application to regional drought processes in China

Liu, Zhenchen; Liu, Guihua; He, Honglin; Wu, Zhiyong; He, Jian

doi:10.5194/hess-22-529-2018

Cited by 11 publications

(12 citation statements)

References 36 publications

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“…The period for computation is from 1 January 1981 to 31 December 2016, and other details can be found in Sect. 3.1 of our previous study (Liu et al, 2018).…”

Section: Three-month Spi (Spi3) Updated Daily 145mentioning

confidence: 61%

“…Details about process identification could be found in Sect. 3.2 of our previous study (Liu et al, 2018), while the critical proportion was set to 25% in the present study. Eventually, only those extreme and severe processes are our concern.…”

Section: Identification Of Severe Drought Processes 150mentioning

confidence: 99%

“…Some atmospheric horizontal circulation patterns (i.e., weather regimes), which are closely related to temperature-and 55 moisture-related advection processes of large-scale atmospheric flows, indirectly affect region-scale drought development (Kingston et al, 2015;Fowler and Kilsby, 2002). Similar to well recognized teleconnection patterns (Wallace and Gutzler, 1981;Hurrell, 1995), they are target-oriented and conceptually extended, which were considered in some physically conceptual models for drought prediction (Layaysse et al, 2018;Liu et al, 2018;Richardson et al, 2018). For example, Lavaysse et al (2018) used 30-day-lead forecasted monthly occurrence anomalies of weather regimes to predict one-month-60 scale meteorological drought over Europe, which helps detect ~65% of droughts in winter in northeastern European continent one month in advance.…”

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confidence: 99%

“…For example, Lavaysse et al (2018) used 30-day-lead forecasted monthly occurrence anomalies of weather regimes to predict one-month-60 scale meteorological drought over Europe, which helps detect ~65% of droughts in winter in northeastern European continent one month in advance. At the same time, Liu et al (2018) developed a conceptual prediction model of regional https://doi.org/10.5194/esd-2019-81 Preprint. Discussion started: 17 January 2020 c Author(s) 2020.…”

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confidence: 99%

“…These preliminary achievements encouraged us to explore the further application of vertical motion in drought simulation and prediction. Liu et al (2017) previously employed anomalies of horizontal divergence that is closely related to vertical motion in nature to build a dynamical index, which highly correlated with season-scale pluvial-drought process transition over Southwest China. Besides, the motivation of the present study also originates from the following points: Firstly, as one physically important causes of meteorological droughts, vertical motion seems to have the potential of being a universal 80 drought indicator, regardless of geographical difference and seasonality.…”

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confidence: 99%

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The Standardized Vertical Velocity Anomaly Index (SVVAI): Using Atmospheric Dynamical Anomalies to Simulate and Predict Meteorological Droughts

Liu

et al. 2020

Preprint

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Abstract. Vertically downward motion of air current is physically drought-inducing, which has the potential of being a simple and universal drought indicator. The core objective of the present study is to employ vertical motion to simulate and predict droughts after investigating dynamically drought-inducing mechanism. Season-scale drought processes and spatial distributions during 2009–2016 are our concerns, and all the drought study regions of China were chosen as the research areas. Three-month SPI (SPI3) updated daily was used to identify drought processes, and original vertical motion and associated horizontal divergence were also transformed to season-scale standardized anomalies (SA) with a daily running window. In situ observation, ERA-Interim reanalysis, and CFSv2 forecast products were comprehensively employed for drought simulation and prediction. To date, the main results and conclusions are as follow: (1) Atmospheric dynamical anomalies during drought processes and key phases were uncovered. Dynamically drought-inducing features are generally characterized as the typically anomalous upper-convergence–lower-divergence patterns and the intensified downward vertical motion as expected. Signal intensities and vertical configurations are time-varying and seemingly coincide with evolution of regional processes. Particularly, vertical velocity exhibited universally strengthened downward anomalies over almost all the droughts. (2) On the basis of dynamically vertical features uncovered above, the SVVAI (Standardized Vertical Velocity Anomaly Index) is newly proposed. The SVVAI is calculated using SA-based values of vertical motion at multiple pressure levels in the troposphere. The SVVAI_ave and SVVAI_max, corresponding to the vertically average- and maximum-based computation schemes, can be adopted. (3) Drought processes and spatial distributions were simulated with the SVVAI_ave and SVVAI_max. They commonly show highly positive correlations with realistic ones over most regions, and the SVVAI_ave outperformed the SVVAI_max. (4) To further understand difference of simulation capacity, temporal correlation coefficients (TCC) of the SVVAI_ave against observed SPI3 at the grid scale were used for analysis. Positive TCCs above +0.3 occupies most areas to the east of 110° E, while large-area low TCCs (−0.1 ~ +0.3) appear to the west of 110° E over China. It is notably seen that East China and Northeast China are the two regions with highly positive TCCs (+0.6 ~ +0.8). (5) Drought prediction using the SVVAI_ave was preliminarily explored. Regarding the prospective 60-day process prediction, the predicted SVVAI_ave was equally matched with or a little better than the forecasted SPI3 in most cases. Predicted spatial distribution is preliminarily assessed via the example of the 2011 summer–autumn drought over Southwest China, and prediction performance at the occurrence, peak and termination times are inconsistent. (6) Overall, the novel SVVAI herein may be complementary to current approaches of operational drought monitoring and prediction. Further study could be focused on the two following aspects: One is index applicability, that is to say, to explore when and where the predicted SVVAI outperforms the forecasted SPI3. The other is to further explore antecedent drought-inducing signals of atmospheric/oceanic anomalies with the bridge of vertical motion, which may provide a fundamental approach for drought prediction with long lead times.

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“…The period for computation is from 1 January 1981 to 31 December 2016, and other details can be found in Sect. 3.1 of our previous study (Liu et al, 2018).…”

Section: Three-month Spi (Spi3) Updated Daily 145mentioning

confidence: 61%

Section: Identification Of Severe Drought Processes 150mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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The Standardized Vertical Velocity Anomaly Index (SVVAI): Using Atmospheric Dynamical Anomalies to Simulate and Predict Meteorological Droughts

Liu

et al. 2020

Preprint

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ENSO and IOD contributions to seasonal meteorological droughts over the Yangtze River basin

Yin,

Fowler,

Blenkinsop

et al. 2023

Intl Journal of Climatology

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The Yangtze River basin (YRB) has experienced frequent extreme drought events in recent years. Many studies have explored the impact of anomalous tropical sea surface temperatures on seasonal meteorological droughts over the YRB, yet two critical issues remain: (1) the regimes of the El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) causing YRB droughts; (2) the timing and spatial pattern of YRB droughts caused by ENSO and IOD. To address these knowledge gaps, we employed a comprehensive investigation. First, the Severity–Area–Density (SAD) method is applied to identify seasonal drought events over the YRB during 1971–2022. Second, we utilize composite analysis to specify the effects of ENSO and IOD. Our findings indicate that YRB droughts are significantly increased in the August of combined Eastern Pacific (EP) El Niño and positive IOD developing years, October of Central Pacific (CP) El Niño developing years, January of EP La Niña years, and April of CP El Niño decaying years. Third, we conduct numerical simulations and conclude that ENSO and IOD events contribute to the YRB droughts by modulating large‐scale circulation patterns, triggering the formation of cyclones and anticyclones over the Western North Pacific (WNP) and the Tibetan Plateau, and affecting the westerlies and other water vapour transport processes. These results on the physical mechanisms causing seasonal drought in the YRB can guide drought monitoring and prediction in the region.

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Characterization of hydro-meteorological droughts based on dynamic future scenarios and effective rainfall over Central Malawi

Chikabvumbwa,

Salehnia,

Gholami

et al. 2023

Theor Appl Climatol

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A conceptual prediction model for seasonal drought processes using atmospheric and oceanic standardized anomalies: application to regional drought processes in China

Cited by 11 publications

References 36 publications

The Standardized Vertical Velocity Anomaly Index (SVVAI): Using Atmospheric Dynamical Anomalies to Simulate and Predict Meteorological Droughts

The Standardized Vertical Velocity Anomaly Index (SVVAI): Using Atmospheric Dynamical Anomalies to Simulate and Predict Meteorological Droughts

ENSO and IOD contributions to seasonal meteorological droughts over the Yangtze River basin

Characterization of hydro-meteorological droughts based on dynamic future scenarios and effective rainfall over Central Malawi

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