Multivariate ENSO Index Research Articles

The impact of El Niño-southern oscillation to the wind and solar data in Malaysia

Malaysia has initiated initiatives to use renewable energy as a resource of electricity generation since 2011 through the establishment of laws and policies related to renewable energy. The geographical location of Malaysia has led to limited of intermittent renewable energy resources and requires a more detailed study of the various factors impacting electricity generation. This paper aims to understand the impact of El Niño-Southern Oscillation (ENSO) events on the reanalysis wind and solar data. The Wavelet Transform will be used to study the relationship between the reanalysis wind and solar dataset with the Multivariate ENSO index in the Malaysia region. During Very Strong and Strong El Nino, the site experienced an increment of both wind velocity and solar irradiance and reduced during La-Nina. This ENSO impact study is essential as a reference for future wind and solar energy development planning, energy predicting, and risk valuation in Malaysia.

On the relationship of climatic and monsoon teleconnections with monthly precipitation over meteorologically homogenous regions in India: Wavelet & global coherence approaches

The hydro-climatic variables are greatly influenced by the large-scale phenomena at global and regional scales. The present study attempts to characterise the influence of large-scale climatic oscillations on the monthly precipitation over meteorologically homogeneous regions in India. To accomplish the study, the monthly precipitation over selected six different regions are obtained during 1951–2015 and correlations with the eight large-scale climatic oscillations namely, Indian Ocean Dipole (IOD), Sea Surface Temperature (SST), Multivariate ENSO Index (MEI), Southern Oscillation Index (SOI), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), Arctic Oscillation (AO), and Indian Summer Monsoon Index (ISMI) are examined using wavelet and global coherence. The outcomes from the analysis suggest that though other climatic indices have noticeable effects on the monthly precipitation over India, the ISMI is the most effective climatic teleconnection. The predominant and effective period of ISMI is at intra-annual scale influencing Central Northeast India (CNI), Peninsular India (PI), and West Central India (WCI), while the major effective period of IOD is in between 8 and 16 months. For the El Niño–Southern Oscillation (ENSO) indices like SST, SOI, and MEI the most prominent period is noticed during 20 to 54 months time scale over different parts of India. The phase difference is not uniform between the studied climatic oscillations and monthly precipitation across the country. For long terms of ISMI, an in-phase situation is observed over all the meteorologically homogenous regions in India. The present study advocates that the wavelet and global coherence approaches are very powerful tools to analysing the relationship between multiple time-series in a time-frequency space and its application in hydrology enables the water resources managers in developing better understanding of meteorological connections with the large-scale low frequency climatic oscillations.

Delineation of possible influence of solar variability and galactic cosmic rays on terrestrial climate parameters

The present paper has investigated the associations of solar activity (SA), represented by total solar irradiance (TSI), galactic cosmic rays (GCR) and terrestrial climate parameters in particular the global cloudiness and global surface temperature. To that end, we have analysed thirty five years (1983–2018) data of these parameters and have applied the Granger-causality test in order to assess whether there is any potential predictability power of one indicator to the other. The correlations among the involved parameters are tested using Vector Auto Regression (VAR) model and variance decomposition method. As a result of the above analysis, we have found that the TSI is an important factor and has contributed about 8.77 ± 0.42% in the cosmic ray intensity variations. In case of cloud cover variations, the other three parameters (TSI, cosmic ray and global surface temperature) have played a significant role. Further, the TSI changes have contributed 1.68 ± 0.03% fluctuations in the variance of the cloud cover while the cosmic ray intensity and global surface temperature have contributed about 4.89 ± 0.08% and 10.87 ± 1.41% respectively. In case of the global surface temperature anomaly both TSI and cloud covers have contributed about 5.07 ± 0.47% and 14.42 ± 2.13% fluctuations respectively. Additionally, we have also assessed the impact of internal climate oscillations like multivariate ENSO index (MEI), north Atlantic oscillations (NAO) and quasi biennial oscillations (QBO) on cloud cover variations. The contribution of these internal oscillations e.g. ENSO, NAO and QBO in cloud cover variation were reported as 7.48 ± 1.02%, 5.51 ± 0.16% and 1.36 ± 0.43% respectively.

Spatio-temporal analysis of the droughts in Cali, Colombia and their primary relationships with the El Niño-Southern Oscillation (ENSO) between 1971 and 2011

This paper analyzed the spatio-temporal variability of droughts in Cali, Colombia and their primary relations to the El Nino Southern Oscillation (ENSO). The Standardized Precipitation Index (SPI) was used to detect drought events from monthly rainfall data of 24 stations well spread over Cali during 1971-2011. The SPI provided the drought intensity, magnitude, frequency, and the minimum rainfall thresholds, mainly on an annual scale (SPI-12). Eighty percent of the stations reported four events with dry conditions in Cali: 1976-1977, 1983-1984, 1990-1992 and 2009-2010. The ENSO influence was evaluated using the correlation and wavelet transform analyses. Significant (non-significant) negative correlations between SPI-12 in the northern (southern) part of Cali, the multivariate ENSO Index (MEI), and Sea Surface Temperature (SST) Nino 3.4 and Nino 4 indices were observed. The wavelet coherence analysis showed significant coherencies between ENSO and SPI-12: at interannual scale (4-6 years), the phase difference of –135o generates a lag of 6-9 months between the minimum peak of the SPI-12 and the maximum peak of the indices. On the quasi-biennial scale (2-3 years), the phase difference of –180o suggests that the maximum wet (dry) conditions coincide with the mature stage of the La Nina (El Nino) event; and on the decadal scale (8-16 years), the decreases (increases) in rainfall precede the El Nino (La Nina) mature stage by approximately 10-18 months. These results are relevant for seasonal forecasting, since changes in SST in the equatorial Pacific may take place 6-18 months ahead of the dry conditions in Cali.

A 50-year hydro-climatological assessment of climatic modes over the world’s major mountain ranges

The observed climate response and variability that has occurred over the five decades since 1960 of 13 largest global mountain regimes (i.e. the European Alps, Anatolia, Andes, Applach, Atlas, Australian, Brooks, Ethiopian, Himalaya, Kolyma, Rocky, Pyrenees, and Scandinavian) to climate variability. This study covers the period 1960-2013, with a particular emphasis on changes in air temperature and precipitation conditions and their joint modes. Results demonstrate that mountains of high-latitudes in the Northern Hemisphere (e.g. Brooks, Kolyma, and Scandenavia) experienced the largest trends of air temperature (0.24 - 0.45° C/decade). In contrast, changes in air temperature in mountains of the Southern Hemisphere (e.g. Australian and most of the Andes) and the subtropics (e.g. Ethiopian mountains) were generally weaker than those of the mid- and high-latitudes of the Northern Hemisphere. Notably, temperature changes were stronger in low- and mid-elevation regions (e.g. Alps, Pyrenees, Brooks, and Kolyma), compared to the most elevated regions (e.g. Himalaya and Andes). Precipitation exhibited heterogeneous changes, with pronounced decrease over the Alps, Pyrenean and Ethiopian mountains and conversely significant increase across the northern high-latitudes mountains (e.g. Scandinavian and Applach). Factor analysis was also used to identify common patterns of interannual variability among all mountain systems. Results suggest three components with distinctive temporal evolution that explain together 72.72% of air temperature variability. In contrast, the temporal evolution of annual precipitation was more heterogeneous, with six components accounting for 68.59% of precipitation variability. This study also accounted for the possible joint changes in air temperature and precipitation by assessing changes in four different climatic modes (i.e. warm and wet [WW], warm and dry [WD], cold and wet [CW] and cold and dry [CD]), Changes in air temperature, precipitation and their joint modes were further linked to a range of the key circulation patterns over the Northern and Southern Hemispheres, e.g. the Atlantic Meridional Mode [AMO], the Atlantic Multidecadal Oscillation [AMO], the Arctic Oscillation [AO], the Multivariate ENSO Index [MEI], and the North Atlantic Oscillation [NAO]. Results of this work can advances our knowledge of the role of climate variability and change in mountain environments, giving insights into their possible ramifications for different environmental and socioeconomic sectors (e.g. freshwater supply, hydropower generation, biodiversity conservation, …etc).

Temporal variation of dust emissions in dust sources over Central Asia in recent decades and the climate linkages

The temporal variation of dust emissions over Central Asia in recent decades and the linkages with atmospheric factors have not been well documented. This study investigated the annual and interannual variations of dust emissions in the six main dust emission regions (i.e., Sor Mertvyy Kultuk (SMK), Ustyurt Plateau (UP), Southeast of Aralkum (SA), Eastern shore of the southern Caspian (ESC), Central Karakum desert (CK), and Trans-Unguz Karakum desert (TK)), using the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) data from 1980 to 2018. The climate linkages with the variation trend were explored using reanalysis data and the climate indices from NOAA Climate Prediction Center (CPC). The results indicated that, in early spring, dust emissions are distinct in all these sources (except for ESC) due to the cold air intrusions from north, northwest, and northeast directions, and the effect of precipitation was limited by the high evaporation. Whereas in summer and/or early autumn, dust emissions were primarily in SA, ESC, CK, and TK because of the strong northeasterly winds, low vegetation, and dry soils. The overall interannual change of dust emissions in Central Asia showed that relatively larger emissions occurred during 1980–1986 and 1993–2003, especially in April. The dust emissions in SA, ESC, and TK in summer were positively correlated with the pressure gradient between northwestern Kazakhstan and Hindu Kush (NWKHKI), while those in SMK were negatively correlated with Caspian Sea High. The dust emissions in the six dust sources were highly correlated with the maximum wind speeds but showed different sensitivities to drought. The Multivariate El Niño-Southern Oscillation Index (MEI) was related to dust emissions in April over coastal Caspian-Sea areas (SMK and ESC), while those in February over the southern parts (ESC, CK, and TK) were significantly correlated with North Atlantic Oscillation/Arctic Oscillation (NAO/AO). These conclusions could contribute to the meteorology research related to dust emissions and also to the decisions made for environmental protection.

Assessing spatiotemporal variation of heat waves during 1961–2016 across mainland China

AbstractHeat waves (HWs) are one of the current topics of scientific research in the context of global warming, as they can have a disastrous impact on both environment and society. Therefore, detailed studies of variations of HWs that assess variability on spatiotemporal scales are becoming increasingly necessary. The main objective of this study is to detect and analyse variation in HWs and potential climate drivers across China based on Köppen climate classifications. Daily observation data (maximum and minimum temperature) from 1961 to 2016 were used in the study to define HWs based on excess heat factors (EHFs). Linear trend analysis, Bayesian change‐point analysis, cross‐wavelet transform method, and Pearson correlation analysis method were adopted to identify the trends, variability and resonance periodicity of EHFs in sub‐regional, and the possible links between EHFs and large‐scale climate patterns, respectively. Results show that there was an overall significantly increasing trend of EHFs over six climatic zones except for HWM in the Polar tundra (ET). The spatiotemporal characteristics of EHFs in mainland China vary considerably. The spatial patterns of the mean annual EHFs are similar to their change trend. The spatial pattern of the number of individual HWs, the number of days that contribute to HWs, and the length of the longest HW in arid (BB), semi‐arid (BS) and cold semi‐humid (DW) areas of study is the west exceeding the east; temperate humid (CF) is contrary to that, with the south exceeding the north in temperate semi‐humid (CW) and ET. In addition, the mean temperature of all heatwaves (HWM) and the peak daily value in the hottest HW appeared in parts of northern DW, CF and BS. Change point first occurs in the northern and then in the southern region across mainland China, excepting HWM. A dominant positive correlation was found for Multivariate ENSO Index (MEI) and Arctic Oscillation Index (AOI) with EHFs, while a dominant negative correlation was detected for Pacific Decadal Oscillation (PDO) and the North Atlantic Oscillation (NAO) across China. A common significant 2–4 year periodical oscillation was detected in the EHFs series at the nationwide scale. Strengthening anti‐cyclone circulation in the Mongolian Plateau, and weakening monsoon flow and speed have contributed to the changes in EHFs across China.

Spatial and Temporal Variation of Wind Erosion Climatic Erosivity and Its Response to ENSO in the Otindag Desert, China

Wind erosion is a major cause of soil losses in China’s drylands which is further stimulated by climate variability and fragile ecological conditions. Climatic erosivity is an important index of wind erosion, therefore, evaluation of its spatiotemporal variations and relationship with the El Niño–Southern Oscillation (ENSO) will provide a theoretical basis for the comprehensive management and prevention of soil erosion. In this study, by using the climatic erosivity equation, geographic information system (GIS) and geostatistical analysis, we quantified the climatic erosivity, explored its spatiotemporal variations, and detected the effects of the Multivariate ENSO Index (MEI) on climatic erosivity in the Otindag Desert during the period of 1980–2016. The results indicated that the climatic erosivity (C-factor value) ranged from 82–445, and it decreased from the western margin to the eastern margin of the desert. The climatic erosivity showed a significant downward trend at seasonal and annual scales (p < 0.05). As far as spring, autumn and annual climatic erosivity, the whole region showed a downward trend, however, the summer and winter climatic erosivity varied spatially, in which the central and western regions showed a downward trend, but the eastern region showed an upward trend. The results showed that the average climatic erosivity is weaker during La Niña events than during El Niño events. The climatic erosivity recorded by 14 of the 20 meteorological stations, all located in central and west regions, exhibited a significant correlation with MEI (p < 0.05). The ENSO has a significant impact on climatic erosivity.

Impacts of the El Niño-Southern Oscillation (ENSO) on Paddy Production in Southeast Asia

ABSTRACT Stronger intensity and frequent arrival of the El Niño- Southern Oscillation (ENSO) caused varied temperature and wildly varying precipitation with drought and flood conditions that threaten paddy production. Using the Pooled Mean Group estimation method, this study investigates the long run and short run relationship of ENSO impact on Southeast Asia paddy production from 1961 to 2014 with Oceanic Niño Index, Niño 3.4 sea surface temperature anomalies, Southern Oscillation Index and Multivariate ENSO Index. This study also investigates four different ENSO intensities with Multivariate ENSO Index to determine their long run and short run impact on paddy production. The findings reveal that the ENSO effect is exclusively captured by Multivariate ENSO Index among four climate change variables. Furthermore, ENSO arrival during the paddy planting season caused a paddy reduction in the long run. Specifically, the arrival of a moderate La Niña during the paddy planting season has a greater impact on paddy reduction in the long run compared to a strong El Niño. In addition, moderate and strong La Niña caused higher paddy production in the short run. Further research can be carried out by including spatial and temporal ENSO impacts on paddy planting season with single cultivation method.

Sigmodontine community and species responses to El Niño and precipitation in different levels of forest degradation.

Few studies have focused on rodent communities at the margins of an ecoregion or the limits of species’ distributions, where the community may be more sensitive to extrinsic variables, both biotic and abiotic. This study evaluates sigmodontine rodent species diversity and overall abundance, and variation associated with climatic variables, in three locations with differing levels of habitat degradation. The study was conducted in northeastern Paraguay, near the western limit of the Upper Parana Atlantic Forest and near the distributional limits of the three most abundant species in the study sites. Three mark-recapture grids were established and classified as least, moderately and most-degraded based on an analysis of several vegetation parameters. The grids were sampled for five consecutive nights, six times during two years. Shannon diversity and overall abundance were calculated for each sample. Monthly Multivariate ENSO Index and rainfall values were obtained from publicly available resources. Product-moment correlations were calculated between community and climatic parameters, including cumulative values for the climatic variables. The same correlations were calculated for the three common sigmodontine species. 1,632 captures were recorded, representing 13 sigmodontine species. Species richness in the samples (one session on one grid) varied from four to seven. Akodon montensis, Hylaeamys megacephalus and Oligoryzomys nigripes were the three most abundant species. In general, species diversity was negatively correlated with ENSO index, precipitation and precipitation anomaly, including cumulative one- to six-month cumulative values of each. Total sigmodontine abundance was positively correlated with the climatic variables. However, these correlations were not uniform among the three levels of habitat degradation, nor did the three abundant species show similar correlation patterns. The three most abundant species are each near their distributional limits, whereas several less abundant species have distributions that extend well beyond the study area. This somewhat counterintuitive result bears further investigation in other sites at ecoregional margins, to determine whether it is a commonly observed pattern, or an exception. Overall sigmodontine abundances were generally reflective of Akodon montensis abundance, which generally correlated with precipitation (including cumulative amounts). Our analyses of these longitudinal data showed two major effects on sigmodontine species diversity and population. First, they are impacted by habitat and secondly, they are affected by climate (ENSO, precipitation). However, individual species are not impacted similarly. Akodon montensis abundances primarily were correlated with abiotic (climatic) variables, and the correlations were consistent across habitats (biotic factors). In contrast, Hylaeamys megacephalus abundance was correlated with climatic variables in two habitats, but not the moderately-degraded habitat, and Oligoryzomys nigripes abundance was not correlated with climate in the most-degraded habitat.

Effects of environmental variability on abundance of commercial marine species in the northern Gulf of California

Studies have shown that environmental variables significantly affect variation in stock abundance of marine populations. The northern Gulf of California (NGC) is a highly productive region of interest due to its fish resources and diversity. Conservation of the marine species inhabiting the region is of public interest. Our study analysed the influence of physical environmental factors on several commercial marine species, using catch per unit effort (CPUE) as a proxy for abundance. Generalized additive models were used to test the significance of selected environmental variables on stock abundance. Deseasonalized cross-correlation analysis was used to examine time-lagged correlations between CPUE and abiotic variables to identify response timings. The results suggest that for most commercial species the sea surface temperature and the long-term climate Pacific Decadal Oscillation index are the predominant predictors for species abundance, followed by the Colorado River discharge. The Multivariate ENSO Index and the Pacific-North American pattern indices also showed specific effects on certain species. The NGC is a highly dynamic region, where species respond to environmental changes according to the characteristics of their life histories.

Time-Series Study of Associations between Rates of People Affected by Disasters and the El Niño Southern Oscillation (ENSO) Cycle.

The El Niño Southern Oscillation (ENSO) is a major driver of climatic variability that can have far reaching consequences for public health globally. We explored whether global, regional and country-level rates of people affected by natural disasters (PAD) are linked to ENSO. Annual numbers of PAD between 1964–2017 recorded on the EM-DAT disaster database were combined with UN population data to create PAD rates. Time-series regression was used to assess de-trended associations between PAD and 2 ENSO indices: Oceanic Niño Index (ONI) and multivariate El Niño Index (MEI). Over 95% of PAD were caused by floods, droughts or storms, with over 75% of people affected by these three disasters residing in Asia. Globally, drought-related PAD rate increased sharply in El Niño years (versus neutral years). Flood events were the disaster type most strongly associated with El Niño regionally: in South Asia, flood-related PAD increased by 40.5% (95% CI 19.3% to 65.6%) for each boundary point increase in ONI (p = 0.002). India was found to be the country with the largest increase in flood-related PAD rates following an El Niño event, with the Philippines experiencing the largest increase following La Niña. Multivariate ENSO Index (MEI)-analyses showed consistent results. These findings can be used to inform disaster preparedness strategies.

Thirty Years of Atmospheric CO2 Observations at the Plateau Rosa Station, Italy

The atmospheric background CO2 concentration is a key quantity for the analysis and evaluation of the ongoing climate change. Long-term CO2 observations have been carried out at the high Plateau Rosa mountain station, in the north-western Alps since 1989. The complete time series covers thirty years, and it is suitable for climatological analysis. The continuous CO2 measurements, collected since 1993, were selected, by means of a BaDS (Background Data Selection) filter, to obtain the hourly background data. The monthly background data series was analysed in order to individuate the parameters that characterise the seasonal cycle and the long-term trend. The growth rate was found to be 2.05 ± 0.03 ppm/year, which is in agreement with the global trend. The increased background CO2 concentration at the Plateau Rosa site is the consequence of global anthropic emissions, whereas the natural variability of the climatic system taken from the SOI (South Oscillation Index) and MEI (Multivariate ENSO Index) signals was detected in the inter-annual changes of the Plateau Rosa growth rate.

Variation characteristics of rainfall erosivity in Guizhou Province and the correlation with the El Niño Southern Oscillation.

Rainfall erosivity is an important indicator that can be used to measure the ability of rain to cause erosion and is connected with the El Niño Southern Oscillation (ENSO) through the transmission of rainfall. This work aimed to explore the characteristics of rainfall erosivity in Guizhou Province and determine its correlation with ENSO. Rainfall erosivity was calculated from daily rainfall data from January 1960 to December 2017. The analyses were conducted using a daily rainfall erosivity model, inverse distance weighted (IDW) interpolation, linear regression analysis, Mann-Kendall test and correlation analysis. The long-term (1960-2017) average rainfall erosivity was 5825.60 MJ·mm·ha-1·h-1 in the study area and showed a high temporal variability with the estimates from the linear trend line ranging from -449.5 MJ·mm·ha-1·h-1/10a to 496.8 MJ·mm·ha-1·h-1/10a. According to rainfall and erosive rainfall, an uneven spatial distribution of rainfall erosivity was observed with an increasing trend from south to north. Temporal distribution of monthly rainfall erosivity was consistent with that of seasonal rainfall erosivity, and concentrated in the summer months (June to August). As the representation indices of ENSO phenomena, the Oceanic Niño Index (ONI), Southern Oscillation Index (SOI) and multivariate ENSO Index (MEI) were selected for correlation analysis with rainfall erosivity. During El Niño events, the ONI, SOI and MEI showed significant correlations (>95% confidence level) with rainfall erosivity, while during La Niña events, only the ONI and MEI were significantly correlated with rainfall erosivity, but no significant correlation was detected during the neutral period or for the entire study period. The degree of rainfall erosion is proportional to the ENSO duration; the longer the ENSO duration, the greater the rainfall erosivity. These findings could help predict soil erosion and be used to develop further adaptation measures to prevent water and soil loss.

Population dynamics of oceanic manta rays (Mobula birostris) in the Raja Ampat Archipelago, West Papua, Indonesia, and the impacts of the El Niño–Southern Oscillation on their movement ecology

AbstractAimOur aim was to collect sightings data on oceanic manta rays (Mobula birostris) within the Raja Ampat Archipelago to better understand their population dynamics within the region. These data were compared with environmental variables to seek correlates that may explain any variations in observed sightings frequency. Combined, it is hoped this knowledge will be used to aid effective management of this species in the region.LocationRaja Ampat Archipelago, West Papua, Indonesia.MethodsWe collected and catalogued photo‐identification of individuals to create a sightings database. To generate estimates of abundance, survival, sighting probability and recruitment to the population, we used a POPAN mark–recapture model. We considered time‐varying and fixed values for each parameter and possible covariate relationships of the El Niño–Southern Oscillation (ENSO) and sex.ResultsA total of 588 individuals were identified over six years, of which 72.4% were female, and 28.2% of individuals were resighted. There was an exponential increase in sightings during the 2015–2016 ENSO event despite constant effort; significant correlation was found between sightings and the multivariate ENSO index and with sea surface temperatures but not with chlorophyll‐a. Mark–recapture analysis shows a clear relationship between ENSO and entry probability, and the most parsimonious model estimated a superpopulation size N of 1875 individuals.Main conclusionOceanic manta ray distributions appear to be impacted by ENSO‐related climate phenomena. Our findings on the relationship of ENSO to manta sightings and distribution indicate that oceanic manta rays are likely sensitive to large‐scale climatic variability. This illustrates the potential impacts of climate change on oceanic manta populations and the need to consider climate impacts in developing management strategies. Continued photo‐ID, tagging and population genetics would greatly enhance knowledge and help develop management strategies that bolster conservation of the species.

Trend of rainfall over Indonesian major lakes from tropical rainfall measuring mission data

Establishing patterns of natural variability of water resources in lakes is important for water management. However, the availability of reliable data often becomes obstacles, especially in ungauged regions. Rainfall products from Tropical Rainfall Measuring Mission (TRMM) potentially fill this gap. The aim of this study is to assess the trend of rainfall over Indonesian major lakes using TRMM rainfall estimates to investigate the natural variability of rainfall over the lakes. TRMM 3B43 monthly data over the period of 1998–2017 obtained from Giovanni data portal maintained by NASA were used to assess the trend of rainfall over Indonesian major lakes. Rainfall correlation with El Niño-Southern Oscillation (ENSO) variability was also investigated using Southern Oscillation Index (SOI) and Multivariate ENSO Index (MEI). Trend analysis was carried out using Mann-Kendall test. Rainfall depths over Lake Laut Tawar in Sumatra tend to gradually decline, which is confirmed by the Mann-Kendall test. Result of the test of rainfall over all other investigated lakes on Kalimantan, Sulawesi, Papua, and Java indicate no trends except for that of Lake Paniai on Papua, which indicates an increasing trend.

Sea Level Variation around Australia and Its Relation to Climate Indices

This study aims at investigating the intradecadal and decadal signals of the sea level using 25 years of altimetry data around Australia. We have used the multivariable spectral analysis to extract six periodic signals at the 95% confidence level from altimetry-derived sea-level time series in the study area. They are signals with periods of 1, 1.5, 3, 4.3, 5.7 and 11.17 years, which can also be detected in the estimated power spectra from climate indices of the Interdecadal Pacific Oscillation, Multivariate ENSO Index, and Pacific Decadal Oscillation. A parametric model including the detected periodic signals is used to estimate sea-level trends. The determined trends in the area are in a good agreement with recent studies that consider effects of climate indices through a multivariate regression model. The advantage of our model is to present more descriptive explanation of the sea level signals around Australia in terms of periodicity and spatial variability.

The Variation of the Intensity, Height, and Size of Precipitation Systems with El Niño–Southern Oscillation in the Tropics and Subtropics

AbstractA 16-yr (1998–2013) Tropical Rainfall Measuring Mission (TRMM) Precipitation Feature (PF) database is used to examine the impacts of El Niño–Southern Oscillation (ENSO) on the characteristics of precipitation systems in the tropics and subtropics. Noticeable differences in the fractions of deep systems (20-dBZ radar echo tops greater than 10 km) and mesoscale convective systems (MCSs) (an area greater than 2000 km2) between different phases of ENSO are found over specific regions, including the central Pacific (CPACI), the western Maritime Continent (WMC), the eastern Maritime Continent (EMC), Gulf of Mexico (GM), Argentina (ARGEN), and Australia (AUS). The coefficients of determination R2 between the multivariate ENSO index (MEI) and the population fractions of deep convection and MCSs are analyzed seasonally over these regions. The responses from these precipitation systems to ENSO are found to be more pronounced in the winter half-year than in the summer half-year. An increase of rainfall during El Niño periods over the CPACI, GM, and ARGEN is found to be associated with more precipitation events and a higher fraction of intense, deep, and large precipitation systems. AUS has fewer precipitation events and a higher fraction of shallow and small precipitation systems during El Niño conditions. Both EMC and WMC have a higher fraction of MCSs during La Niña than El Niño conditions. The EMC observes a higher fraction of deep convection during La Niña conditions. However, the WMC has a higher fraction of deep convection during El Niño conditions, possibly related to the effect of the Indian Ocean dipole.

The Effect of El Niño on Flood Damages in the Western United States

Abstract This paper quantifies insured flood losses across the western United States from 1978 to 2017, presenting a spatiotemporal analysis of National Flood Insurance Program (NFIP) daily claims and losses over this period. While considerably lower (only 3.3%) than broader measures of direct damages measured by a National Weather Service (NWS) dataset, NFIP insured losses are highly correlated to the annual damages in the NWS dataset, and the NFIP data provide flood impacts at a fine degree of spatial resolution. The NFIP data reveal that 1% of extreme events, covering wide spatial areas, caused over 66% of total insured losses. Connections between extreme events and El Niño–Southern Oscillation (ENSO) that have been documented in past research are borne out in the insurance data. In coastal Southern California and across the Southwest, El Niño conditions have had a strong effect in producing more frequent and higher magnitudes of insured losses, while La Niña conditions significantly reduce both the frequency and magnitude of losses. In the Pacific Northwest, the opposite pattern appears, although the effect is weaker and less spatially coherent. The persistent evolution of ENSO offers the possibility for property owners, policy makers, and emergency planners and responders that unusually high or low flood damages could be predicted in advance of the primary winter storm period along the West Coast. Within the 40-yr NFIP history, it is found that the multivariate ENSO index would have provided an 8-month look-ahead for heightened damages in Southern California.

Evolution properties between meteorological, agricultural and hydrological droughts and their related driving factors in the Luanhe River basin, China

Abstract To fully reveal drought propagation mechanism and effectively mitigate drought, it is of importance to synthesize investigating different types of droughts; specifically, the propagation from meteorological to agricultural droughts and from agricultural to hydrological droughts, as well as their potential driving factors. The results suggested that: (1) the Standardized Precipitation Evapotranspiration Index (SPEI) is a better indicator for detecting drought onset, the Standardized Soil Index (SSI) can better describe drought persistence, and the Standardized Runoff Index (SRI) can depict the termination of drought; (2) the propagation time from meteorological to agricultural droughts, as well as that from agricultural to hydrological droughts, showed remarkable seasonal characteristics in the Luanhe River basin; (3) the significant influence of the Niño 1 + 2 + 3 + 4, Niño 3.4, Southern Oscillation Index (SOI), Multivariate ENSO Index (MEI), and Atlantic Multidecadal Oscillation (AOM) on meteorological drought was concentrated in the 16–88-month periods, as well as the decadal scale of 99–164-month periods, the significant influence of Niño 4, Niño 3.4, MEI, and SOI on agricultural drought was concentrated in the 16–99-month periods, as well as the decadal scale of 99–187-month periods, and the significant influence of Niño 4 and AOM on hydrological drought was concentrated in the 16–64-month periods, as well as the decadal scale of 104–177-month periods.