scholarly journals Concurrent wet and dry hydrological extremes at the global scale

2020 ◽  
Vol 11 (1) ◽  
pp. 251-266 ◽  
Author(s):  
Paolo De Luca ◽  
Gabriele Messori ◽  
Robert L. Wilby ◽  
Maurizio Mazzoleni ◽  
Giuliano Di Baldassarre

Abstract. Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions that characterize the former is therefore of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global co-occurrence. We define these using the monthly self-calibrated Palmer Drought Severity Index based on the Penman–Monteith model (sc_PDSI_pm), covering the period 1950–2014, at 2.5∘ horizontal resolution. We find that the land areas affected by extreme wet, dry, and wet–dry events (i.e. geographically remote yet temporally co-occurring wet or dry extremes) are all increasing with time, the trends of which in dry and wet–dry episodes are significant (p value ≪ 0.01). The most geographically widespread wet–dry event was associated with the strong La Niña in 2010. This caused wet–dry anomalies across a land area of 21 million km2 with documented high-impact flooding and drought episodes spanning diverse regions. To further elucidate the interplay of wet and dry extremes at a grid cell scale, we introduce two new metrics: the wet–dry (WD) ratio and the extreme transition (ET) time intervals. The WD ratio measures the relative occurrence of wet or dry extremes, whereas ET quantifies the average separation time of hydrological extremes with opposite signs. The WD ratio shows that the incidence of wet extremes dominates over dry extremes in the USA, northern and southern South America, northern Europe, north Africa, western China, and most of Australia. Conversely, dry extremes are more prominent in most of the remaining regions. The median ET for wet to dry is ∼27 months, while the dry-to-wet median ET is 21 months. We also evaluate correlations between wet–dry hydrological extremes and leading modes of climate variability, namely the El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Atlantic Multi-decadal Oscillation (AMO). We find that ENSO and PDO have a similar influence globally, with the former significantly impacting (p value < 0.05) a larger area (18.1 % of total sc_PDSI_pm area) compared to the latter (12.0 %), whereas the AMO shows an almost inverse pattern and significantly impacts the largest area overall (18.9 %). ENSO and PDO show the most significant correlations over northern South America, the central and western USA, the Middle East, eastern Russia, and eastern Australia. On the other hand, the AMO shows significant associations over Mexico, Brazil, central Africa, the Arabian Peninsula, China, and eastern Russia. Our analysis brings new insights on hydrological multi-hazards that are of relevance to governments and organizations with globally distributed interests. Specifically, the multi-hazard maps may be used to evaluate worst-case disaster scenarios considering the potential co-occurrence of wet and dry hydrological extremes.

2019 ◽  
Author(s):  
Paolo De Luca ◽  
Gabriele Messori ◽  
Robert L. Wilby ◽  
Maurizio Mazzoleni ◽  
Giuliano Di Baldassarre

Abstract. Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions characterising the former is, therefore, of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global co-occurrence. We define these using the monthly self-calibrated Palmer Drought Severity Index based on the Penman-Monteith model (sc_PDSI_pm) covering the period 1950–2014, at 2.5° horizontal resolution. We find that the land areas affected by extreme wet, dry and wet-dry events (i.e. geographically remote, yet temporally co-occurring wet or dry extremes) all display increasing trends with time, of which changes in dry and wet-dry episodes are significant (p-value


Author(s):  
S. W. Franks ◽  
C. J. White ◽  
M. Gensen

Abstract. Hydrological extremes are amongst the most devastating forms of natural disasters both in terms of lives lost and socio-economic impacts. There is consequently an imperative to robustly estimate the frequency and magnitude of hydrological extremes. Traditionally, engineers have employed purely statistical approaches to the estimation of flood risk. For example, for an observed hydrological timeseries, each annual maximum flood is extracted and a frequency distribution is fit to these data. The fitted distribution is then extrapolated to provide an estimate of the required design risk (i.e. the 1% Annual Exceedance Probability – AEP). Such traditional approaches are overly simplistic in that risk is implicitly assumed to be static, in other words, that climatological processes are assumed to be randomly distributed in time. In this study, flood risk estimates are evaluated with regards to traditional statistical approaches as well as Pacific Decadal Oscillation (PDO)/El Niño-Southern Oscillation (ENSO) conditional estimates for a flood-prone catchment in eastern Australia. A paleo-reconstruction of pre-instrumental PDO/ENSO occurrence is then employed to estimate uncertainty associated with the estimation of the 1% AEP flood. The results indicate a significant underestimation of the uncertainty associated with extreme flood events when employing the traditional engineering estimates.


2011 ◽  
Vol 7 (3) ◽  
pp. 957-974 ◽  
Author(s):  
É. Boucher ◽  
J. Guiot ◽  
E. Chapron

Abstract. We present the first spatially explicit field reconstruction of the summer (DJF) Palmer Drought Severity Index (PDSI) for the Southern Hemisphere. Our multi-proxy reconstruction focuses on Southern South America (SSA, south of 20° S) and is based on a novel spectral analogue method that aims at reconstructing low PDSI frequencies independently from higher frequencies. The analysis of past regimes and trends in extreme wet spells and droughts reveals considerable geographical and temporal variations over the last millennium in SSA. Although recent changes are in some cases notorious, most were not exceptional at the scale of the last thousand years. Our reconstruction highlights that low frequency water availability fluctuations in Patagonia were generally in antiphase with the rest of the subcontinent. Providing the fact that modern patterns of changes are transferable to the past, we show that such antiphases within SSA's hydroclimate could be attributed to the spatially contrasted response of summer PDSI to the Antarctic Oscillation (AAO). However, El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) signals are also embedded within the PDSI series during the 20th century. All these ocean-atmospheric forcings acted synergically, but the dominant influence appeared highly compartmentalized through space, highlighting clear AAO- (e.g. South Patagonia) and ENSO- (e.g. the Pampas) dominated regions. Our results therefore emphasize the complexity of water-availability fluctuations in SSA and their important dependence on external ocean-atmospheric forcings.


2021 ◽  
Author(s):  
Markus Deppner ◽  
Bedartha Goswami

&lt;p&gt;The impact of the El Ni&amp;#241;o Southern Oscillation (ENSO) on rivers are well known, but most existing studies involving streamflow data are severely limited by data coverage. Time series of gauging stations fade in and out over time, which makes hydrological large scale and long time analysis or studies of rarely occurring extreme events challenging. Here, we use a machine learning approach to infer missing streamflow data based on temporal correlations of stations with missing values to others with data. By using 346 stations, from the &amp;#8220;Global Streamflow Indices and Metadata archive&amp;#8221; (GSIM), that initially cover the 40 year timespan in conjunction with Gaussian processes we were able to extend our data by estimating missing data for an additional 646 stations, allowing us to include a total of 992 stations. We then investigate the impact of the 6 strongest El Ni&amp;#241;o (EN) events on rivers in South America between 1960 and 2000. Our analysis shows a strong correlation between ENSO events and extreme river dynamics in the southeast of Brazil, Carribean South America and parts of the Amazon basin. Furthermore we see a peak in the number of stations showing maximum river discharge all over Brazil during the EN of 1982/83 which has been linked to severe floods in the east of Brazil, parts of Uruguay and Paraguay. However EN events in other years with similar intensity did not evoke floods with such magnitude and therefore the additional drivers of the 1982/83&amp;#160; floods need further investigation. By using machine learning methods to infer data for gauging stations with missing data we were able to extend our data by almost three-fold, revealing a possible heavier and spatially larger impact of the 1982/83 EN on South America's hydrology than indicated in literature.&lt;/p&gt;


2021 ◽  
Author(s):  
Rogert Sorí ◽  
Raquel Nieto ◽  
Margarida L.R. Liberato ◽  
Luis Gimeno

&lt;p&gt;The regional and global precipitation pattern is highly modulated by the influence of El Ni&amp;#241;o Southern Oscillation (ENSO), which is considered the most important mode of climate variability on the planet. In this study was investigated the asymmetry of the continental precipitation anomalies during El Ni&amp;#241;o and La Ni&amp;#241;a. To do it, a Lagrangian approach already validated was used to determine the proportion of the total Lagrangian precipitation that is of oceanic and terrestrial origin. During both, El Ni&amp;#241;o and La Ni&amp;#241;a, the Lagrangian precipitation in regions such as the northeast of South America, the east and west coast of North America, Europe, the south of West Africa, Southeast Asia, and Oceania is generally determined by the oceanic component of the precipitation, while that from terrestrial origin provides a major percentage of the average Lagrangian precipitation towards the interior of the continents. The role of the moisture contribution to precipitation from terrestrial and oceanic origin was evaluated in regions with statistically significant precipitation anomalies during El Ni&amp;#241;o and La Ni&amp;#241;a. Two-phase asymmetric behavior of the precipitation was found in regions such the northeast of South America, South Africa, the north of Mexico, and southeast of the United States, etc. principally for December-January-February and June-July-August. For some of these regions was also calculated the anomalies of the precipitation from other datasets to confirm the changes. Besides, for these regions was calculated the anomaly of the Lagrangian precipitation, which agrees in all the cases with the precipitation change. For these regions, it was determined which component of the Lagrangian precipitation, whether oceanic or terrestrial, controlled the precipitation anomalies. A schematic figure represents the extent of the most important seasonal oceanic and terrestrial sources for each subregion during El Ni&amp;#241;o and La Ni&amp;#241;a.&lt;/p&gt;


2014 ◽  
Vol 11 (5) ◽  
pp. 7685-7719 ◽  
Author(s):  
M. Broich ◽  
A. Huete ◽  
M. G. Tulbure ◽  
X. Ma ◽  
Q. Xin ◽  
...  

Abstract. Land surface phenological cycles of vegetation greening and browning are influenced by variability in climatic forcing. Quantitative information on phenological cycles and their variability is important for agricultural applications, wildfire fuel accumulation, land management, land surface modeling, and climate change studies. Most phenology studies have focused on temperature-driven Northern Hemisphere systems, where phenology shows annually reoccurring patterns. Yet, precipitation-driven non-annual phenology of arid and semi-arid systems (i.e. drylands) received much less attention, despite the fact that they cover more than 30% of the global land surface. Here we focused on Australia, the driest inhabited continent with one of the most variable rainfall climates in the world and vast areas of dryland systems. Detailed and internally consistent studies investigating phenological cycles and their response to climate variability across the entire continent designed specifically for Australian dryland conditions are missing. To fill this knowledge gap and to advance phenological research, we used existing methods more effectively to study geographic and climate-driven variability in phenology over Australia. We linked derived phenological metrics with rainfall and the Southern Oscillation Index (SOI). We based our analysis on Enhanced Vegetation Index (EVI) data from the MODerate Resolution Imaging Spectroradiometer (MODIS) from 2000 to 2013, which included extreme drought and wet years. We conducted a continent-wide investigation of the link between phenology and climate variability and a more detailed investigation over the Murray–Darling Basin (MDB), the primary agricultural area and largest river catchment of Australia. Results showed high inter- and intra-annual variability in phenological cycles. Phenological cycle peaks occurred not only during the austral summer but at any time of the year, and their timing varied by more than a month in the interior of the continent. The phenological cycle peak magnitude and integrated greenness were most significantly correlated with monthly SOI within the preceding 12 months. Correlation patterns occurred primarily over north-eastern Australia and within the MDB predominantly over natural land cover and particularly in floodplain and wetland areas. Integrated greenness of the phenological cycles (surrogate of productivity) showed positive anomalies of more than two standard deviations over most of eastern Australia in 2009–2010, which coincided with the transition between the El Niño induced decadal droughts to flooding caused by La Niña. The quantified spatial-temporal variability in phenology across Australia in response to climate variability presented here provides important information for land management and climate change studies and applications.


Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1605
Author(s):  
Mary T. Kayano ◽  
Wilmar L. Cerón ◽  
Rita V. Andreoli ◽  
Rodrigo A. F. Souza ◽  
Itamara P. Souza

Contrasting effects of the tropical Indian and Pacific Oceans on the atmospheric circulation and rainfall interannual variations over South America during southern winter are assessed considering the effects of the warm Indian Ocean basin-wide (IOBW) and El Niño (EN) events, and of the cold IOBW and La Niña events, which are represented by sea surface temperature-based indices. Analyses are undertaken using total and partial correlations. When the effects of the two warm events are isolated from each other, the contrasts between the associated rainfall anomalies in most of South America become accentuated. In particular, EN relates to anomalous wet conditions, and the warm IOBW event to opposite conditions in extensive areas of the 5° S–25° S band. These effects in the 5° S–15° S sector are due to the anomalous regional Hadley cells, with rising motions in this band for the EN and sinking motions for the warm IOBW event. Meanwhile, in subtropical South America, the opposite effects of the EN and warm IOBW seem to be due to the presence of anomalous anticyclone and cyclone and associated moisture transport, respectively. These opposite effects of the warm IOBW and EN events on the rainfall in part of central South America might explain the weak rainfall relation in this region to the El Niño–Southern Oscillation (ENSO). Our results emphasize the important role of the tropical Indian Ocean in the South American climate and environment during southern winter.


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