climate patterns
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The São Francisco River Basin (SFRB) is one of the main watersheds in Brazil, standing out for generating energy and consumption, among other ecosystem services. Hence, it is important to identify hydrological drought events and the anomalous climate patterns associated with dry conditions. The Standard Precipitation Index (SPI) for 12 months was used to identify hydrological drought episodes over SFRB 1979 and 2020. For these episodes, the severity, duration, intensity, and peak were obtained, and SPI-1 was applied for the longest and most severe episode to identify months with wet and dry conditions within the rainy season (Nov–Mar). Anomalous atmospheric and oceanic patterns associated with this episode were also analyzed. The results revealed the longest and most severe hydrological drought episode over the basin occurred between 2012 and 2020. The episode over the Upper portion of the basin lasted 103 months. The results showed a deficit of monthly precipitation up to 250 mm in the southeast and northeast regions of the country during the anomalous dry months identified through SPI-1. The dry conditions observed during the rainy season of this episode were associated with an anomalous high-pressure system acting close to the coast of Southeast Brazil, hindering the formation of precipitating systems.

AbstractThe existing theories for the tropical teleconnections to Indian summer monsoon (ISM) are diverse in approaches. As a result, it is impossible to quantify the relative impacts of different tropical climate patterns on ISM, complying with a single physical mechanism. Here, we show that tropical teleconnections to ISM can be explained through net moisture convergence driven by surface pressure (Ps) gradients surrounding the Indian region. The positive and negative phases of major tropical climate patterns modulate these pressure gradients asymmetrically in the zonal and/or meridional directions leading to asymmetric changes in moisture convergence and ISM rainfall (ISMR). Stronger El Nino droughts than La Nina floods are due to greater decreased eastward moisture flux over the Arabian Sea during El Nino than the corresponding increase during La Nina driven by proportionate meridional Ps gradients. While the equatorial Atlantic Ocean’s sea surface temperature in boreal summer and El Nino Southern Oscillation in the preceding winter changes ISMR significantly, moisture convergence anomalies driven by the Indian Ocean Dipole were insignificant. Moreover, while ISMR extremes during ENSO are due to asymmetric changes in zonal and meridional gradients in Ps, non-ENSO ISMR extremes arise due to the zonal gradient in zonally symmetric Ps anomalies.

The spatial and temporal characteristics of drought in Northeast China are investigated, using monthly meteorological data from 140 stations over the period 1970–2014. The study area was divided into three regions using hierarchical cluster analysis based on the precipitation and potential evapotranspiration data. The standardized precipitation evapotranspiration index (SPEI) was calculated for each station on 3-month and 12-month time scales. The Mann-Kendall (MK) trend test and Sen’s slope method were applied to determine the trends for annual and seasonal SPEI time series. Periodic features of drought conditions in each sub-region and possible relationship with large-scale climate patterns were respectively identified using the continuous wavelet transform (CWT) and cross wavelet transform. The results show mitigations in spring and winter droughts and a significant increasing trend in autumn drought. On the annual scale, droughts became more severe and more intense in the western regions but were mitigated in the eastern region. CWT analysis showed that droughts in Northeast China occur predominantly in 14- to 42-month or 15- to 60-month cycles. Annual and seasonal droughts have 2- to 6-year cycles over the three defined regions. Cross wavelet analysis also shows that the statistically significant influence of large-scale climate patterns (the Southern Oscillation, the Atlantic Multidecadal Oscillation, the Arctic Oscillation, and the Polar–Eurasian Pattern) on drought in Northeast China is concentrated in a 16- to 50-month period, possibly causing drought variability in the different regions. The Southern Oscillation, Polar–Eurasia pattern, and Arctic Oscillation are significantly correlated with drought on decadal scales (around 120-month period). The findings of this study will provide valuable reference for regional drought mitigation and drought prediction.

The study examines the impact of climate variables on wheat production in 10 major wheat-producing districts of Pakistan. In doing so, we apply the Driscoll–Kraay approach to estimate the panel data from 1981 to 2019. Our empirical analysis reveals that climate variables, including temperature, rainfall and humidity, follow a common correlation across districts. We find that wheat productivity and temperature, as well as rainfall, follow an inverted U-shaped relation. The response of the wheat productivity is quadratic rather than linear towards average temperature and rainfall during the specific time of cultivation, including planting, flowering and harvesting. Besides, fertilizer use promotes and humidity impedes wheat productivity. Our findings are robust considering heterogeneity, serial correlation and spatial dependency.

<p><b>Atmospheric Rivers (ARs) are long, narrow jets of intense water vapour flux that are a fundamental component of the global atmospheric circulation, transporting moisture and heat from the tropics to higher latitudes. When an AR makes landfall, especially in areas of steep topography, it releases much of its water vapour as precipitation through orographic uplift. Thus, although ARs play a positive role in the distribution and maintenance of water resources in the mid-latitudes, they are also associated with extreme precipitation and flooding. AR events in New Zealand have had major socio-economic consequences with losses to property, farmland, stock, roads and bridges. However, despite knowledge of their occurrence, focused investigations of ARs in New Zealand have received relatively little scientific attention. In particular, little is known about how large-scale climate patterns, such as the Southern Annular Mode (SAM) and El Niño-Southern Oscillation (ENSO), influence ARs and AR-related precipitation extremes.</b></p> <p>The aim of this study is to quantify the impacts and large-scale drivers of AR landfalls in New Zealand. We employ a new AR detection algorithm, developed specifically for the New Zealand case, to investigate landfalling ARs over a 41-year period from 1979-2019. We investigate the general climatology of ARs, and evaluate the synoptic conditions that drive these events. Using a comprehensive daily rainfall dataset comprising 189 stations, we also investigate the impacts of ARs on NZ rainfall and flooding events. For northern and western regions, over 45% of rainfall fell directly under AR conditions, contributing to daily rainfall totals 2.5 times higher on average compared to non-AR days. Further, we find that AR days were associated with up to 70% of daily rainfall totals above the 99th percentile, with insurance damages exceeding NZ $1.4 billion since 1980.</p> <p>Finally, for the first time in New Zealand, we investigate how large-scale climate patterns influence the occurrence of ARs. We find that changes in the leading modes of climate variability can alter seasonal and regional AR frequency by upwards of 30%. The SAM is identified as the dominant driver of AR activity (other than the seasonal cycle), with the positive SAM phase associated with a 16% reduction in AR occurrence during summer (30-35% reduction for the North Island). The links between AR occurrence and ENSO were less clear, though a few statistically significant relationships were found. The Madden-Julian Oscillation (MJO), the leading mode of intraseasonal tropical variability, was found to significantly influence the frequency and timing of AR landfalls (particularly for the northern North Island). Favourable MJO phases were associated with positive AR frequency anomalies +60% above the mean. These results demonstrate potential use of the AR framework in skilful subseasonal-to-seasonal forecasts of extreme rainfall in New Zealand.</p>

<p><b>Atmospheric Rivers (ARs) are long, narrow jets of intense water vapour flux that are a fundamental component of the global atmospheric circulation, transporting moisture and heat from the tropics to higher latitudes. When an AR makes landfall, especially in areas of steep topography, it releases much of its water vapour as precipitation through orographic uplift. Thus, although ARs play a positive role in the distribution and maintenance of water resources in the mid-latitudes, they are also associated with extreme precipitation and flooding. AR events in New Zealand have had major socio-economic consequences with losses to property, farmland, stock, roads and bridges. However, despite knowledge of their occurrence, focused investigations of ARs in New Zealand have received relatively little scientific attention. In particular, little is known about how large-scale climate patterns, such as the Southern Annular Mode (SAM) and El Niño-Southern Oscillation (ENSO), influence ARs and AR-related precipitation extremes.</b></p> <p>The aim of this study is to quantify the impacts and large-scale drivers of AR landfalls in New Zealand. We employ a new AR detection algorithm, developed specifically for the New Zealand case, to investigate landfalling ARs over a 41-year period from 1979-2019. We investigate the general climatology of ARs, and evaluate the synoptic conditions that drive these events. Using a comprehensive daily rainfall dataset comprising 189 stations, we also investigate the impacts of ARs on NZ rainfall and flooding events. For northern and western regions, over 45% of rainfall fell directly under AR conditions, contributing to daily rainfall totals 2.5 times higher on average compared to non-AR days. Further, we find that AR days were associated with up to 70% of daily rainfall totals above the 99th percentile, with insurance damages exceeding NZ $1.4 billion since 1980.</p> <p>Finally, for the first time in New Zealand, we investigate how large-scale climate patterns influence the occurrence of ARs. We find that changes in the leading modes of climate variability can alter seasonal and regional AR frequency by upwards of 30%. The SAM is identified as the dominant driver of AR activity (other than the seasonal cycle), with the positive SAM phase associated with a 16% reduction in AR occurrence during summer (30-35% reduction for the North Island). The links between AR occurrence and ENSO were less clear, though a few statistically significant relationships were found. The Madden-Julian Oscillation (MJO), the leading mode of intraseasonal tropical variability, was found to significantly influence the frequency and timing of AR landfalls (particularly for the northern North Island). Favourable MJO phases were associated with positive AR frequency anomalies +60% above the mean. These results demonstrate potential use of the AR framework in skilful subseasonal-to-seasonal forecasts of extreme rainfall in New Zealand.</p>

For years, the Arctic region, home to 4 million people, ten percent of whom are indigenous, has provided an example of rapidly changing climate patterns impinging on human ability to adapt to the change (Arctic Centre, University of Lapland). The Circumpolar region has experienced warming at a rate roughly two to three times greater than …

The Last Interglacial (LIG; 130–115 ka) is an important test bed for climate science as an instance of significantly warmer than preindustrial global temperatures. However, LIG climate patterns remain poorly resolved, especially for winter, affected by a suite of strong feedbacks such as changes in sea-ice cover in the high latitudes. We present a synthesis of winter temperature and precipitation proxy data from the Atlantic seaboard of Europe, spanning from southern Iberia to the Arctic. Our data reveal distinct, opposite latitudinal climate trends, including warming winters seen in the European Arctic while cooling and drying occurred in southwest Europe over the LIG. Climate model simulations for 130 and 120 ka suggest these contrasting climate patterns were affected by a shift toward an atmospheric circulation regime with an enhanced meridional pressure gradient and strengthened midlatitude westerlies, leading to a strong reduction in precipitation across southern Europe.