Spatial Analysis of Seasonal Precipitation over Iran: Co-Variation with Climate Indices

The influence of large-scale climate variability on winter river discharge and precipitation across western Europe is investigated. We analyze 60 years of monthly precipitation and river flow data from 18 major western-European rivers and its relationship with dominant teleconnection patterns and climate indices in this region. Results show that winter river flow is characterized by large interannual variability, best correlates with (a) the North Atlantic Oscillation (NAO) at the far-northern (R up to 0.56) and southern latitudes (R up to −0.72), and (b) the West Europe Pressure Anomaly (WEPA) at the middle and northern latitudes, from 42° N to 55° N (R up to 0.83). These indices also explain the interannual variability in autumn and spring discharge in rivers characterized by secondary floods. Compared to the other leading modes of atmospheric variability, WEPA increases the correlations with winter precipitation up to 0.8 in many regions of western and central Europe. A positive WEPA corresponds to a southward shift and an intensification of the Icelandic-Low/Azores-High dipole, driving enhanced precipitation and river discharge in these regions. The correlations with precipitation are slightly higher than those with river discharge, particularly in France, with clear latitudinal gradient. This trend suggests that water storage variability and other catchment characteristics may also influence the interannual variability of river discharge. Seasonal forecasting of the WEPA and NAO winter indices can become a powerful tool in anticipating hydrological risks in this region.

Section: Introductionmentioning

confidence: 99%

Climate Control of Multidecadal Variability in River Discharge and Precipitation in Western Europe

Jalón‐Rojas

Castelle

2021

“…To classify them, we considered three main classes of each index, as shown in Table 2. Several studies [52,53] adopted similar classifications. The Pearson linear correlation and Spearman correlation coefficients between monthly NAO, SOI, Niño 3.4, AO, and EAWR indices, and the SP values over the Gaza region were computed.…”

Section: Climate Indicesmentioning

confidence: 99%

“…Spearman correlation is a non-parametric test. Both correlation methods are widely used to detect regional rainfall teleconnection with climate indices [10,43,45,52,54,55].…”

Section: Climate Indicesmentioning

confidence: 99%

Variation in Seasonal Precipitation over Gaza (Palestine) and Its Sensitivity to Teleconnection Patterns

Ajjur

Al-Ghamdi

2021

The seasonal precipitation (SP) trend and its sensitivity to teleconnection patterns over the East Mediterranean (EM) region remain inconsistent. Based on rainfall records during 1974–2016 at seven meteorological stations in the Gaza region, this study aims to (1) analyze the observed SP trend over the Gaza region, and (2) examine the SP sensitivity to climate indices. Pearson and Spearman correlations between climate indices and SP in the current and following years were calculated, and the seasonal period (particular month) with the highest correlation was identified. Results show that the climate indices, with greater impact on SP over the Gaza region in the autumn and spring, were in the order; El Niño-Southern Oscillation (ENSO) > East Atlantic/Western Russia (EAWR) > North Atlantic Oscillation (NAO) > Arctic Oscillation (AO). The indices’ impact was minimal in the winter precipitation. ENSO types’ correlations (Southern Oscillation Index-SOI and Niño 3.4) were moderate and significant at α = 0.05. Rainfall at most stations positively correlates with AO and EAWR in spring and autumn. During the study period, warm phases of ENSO (i.e., El Niño) intensified autumn precipitation. Simultaneously with warm phases of EAWR or AO, more influence on autumn precipitation is exerted. Cold phases of ENSO (i.e., La Niña) have an adverse impact compared to El Niño. EAWR co-variation was evident only with the ENSO. Regarding AO, a non-meaningful action was noticed during the neutral phases of ENSO and EAWR. The findings of this study help understand and predict the seasonal trend of precipitation over the Gaza region. This is essential to set up climate change mitigation and adaptation strategies in the EM region.

“…Extreme rainfall events are one of the most frequent natural disasters around the world, which brings huge economic losses to human society. The changing of extreme rainfall is not only caused by the internal forces of the climatic system (e.g., solar radiation), but also by human activities (e.g., changes of land cover types and emission of greenhouse gases) [1,2]. With the increasing population and the expanding impervious surfaces, the urbanization process is an important human activity [3,4].…”

Section: Introductionmentioning

confidence: 99%

Impacts of Urbanization on Variations of Extreme Precipitation over the Yangtze River Delta

Congxuan

Luo

Zong

et al. 2021

The urbanization process is the hallmark of the population’s economic activities and land-use types, including population-, economic-, and landscape-urbanization. The question of how to classify the stations into urbanized and suburbanized stations is important for detecting the contribution rates of urbanization to precipitation extremes. This study used the fuzzy c-means clustering method to classify different urbanized level stations by population, economy, and impervious surface in the Suzhou-Wuxi-Changzhou urban agglomeration. Based on the change trends of six extreme precipitation indices, the contribution rates of urbanization to the precipitation extremes were estimated. The results show that the increasing indices were the intensity indices, while the decreasing indices were the duration indices during 1980–2015. Moreover, high urbanization tended to have a higher contribution to the most extreme precipitation indices, especially the intensity indices, than urbanization in the medium-size cities, indicating the urbanization leads to the phenomenon of extreme precipitation enhancement. The results of the three kinds of classification methods were different, especially the classification by the impervious area. This paper investigated the spatiotemporal changes in precipitation extremes and the contribution of urbanization to extreme precipitation, which will provide support for the development of urban agglomeration in the future.