scholarly journals Possible impact of urbanization on extreme precipitation–temperature relationship in East Asian megacities

2021 ◽  
pp. 100401
Author(s):  
Seok-Geun Oh ◽  
Seok-Woo Son ◽  
Seung-Ki Min
2020 ◽  
Vol 47 (18) ◽  
Author(s):  
J. B. Visser ◽  
C. Wasko ◽  
A. Sharma ◽  
R. Nathan

2021 ◽  
Author(s):  
Maria Aleshina ◽  
Vladimir Semenov ◽  
Alexander Chernokulsky

<p>Precipitation extremes are widely thought to intensify with the global warming due to exponential growth, following the Clausius-Clapeyron (C-C) equation of atmosphere water holding capacity with rising temperatures. However, a number of recent studies based on station and reanalysis data for the contemporary period showed that scaling rates between extreme precipitation and temperature are strongly dependent on temperature range, region and moisture availability. Here, we examine the scaling between daily precipitation extremes and surface air temperature over Russian territory for the last four decades using meteorological stations data and ERA-Interim reanalysis. The precipitation-temperature relation is examined for total precipitation amount and, separately, for convective and large-scale precipitation types. In winter, a general increase of extreme precipitation of all types according to C-C relation is revealed. For the Russian Far East region, the stratiform precipitation extremes scale with surface air temperature following even super C-C rates, about two times as fast as C-C. However, in summer we find a peak-like structure of the precipitation-temperature scaling, especially for the convective precipitation in the southern regions of the country. Being consistent with the C-C relationship, extreme precipitation peaks at the temperature range between 15 °C and 20 °C. For the higher temperatures, the negative scaling prevails. Furthermore, it was shown that relative humidity in general decreases with growing temperature in summer. Notably, there appears to be a temperature threshold in the 15-20 °C range, beyond that relative humidity begins to decline more rapidly. This indicates that moisture availability can be the major factor for the peak-shaped relationship between extreme precipitation and temperature revealed by our analysis.</p>


Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 945
Author(s):  
Jing Zhang ◽  
Yu-shu Zhou ◽  
Xin-yong Shen

In this study, an extreme rainstorm that occurred in the Beijing–Tianjin–Hebei (BTH) region in China on 19–20 July 2016 is simulated and analyzed using the Weather Research and Forecasting model, coupled with a multilayer urban canopy scheme, to reveal the impact of urbanization on the extreme precipitation process in the region. The results show that the urban heat island effect (that is, surface warming and an increased near-ground sensible heat flux, which leads to increased vertical motion and atmospheric instability layer strengthening) plays a dominant role in the urban modification of rainfall during the early stages of urbanization, resulting in an increase of 6–10 mm in average hourly precipitation in urban and downwind areas. With the further development of urbanization in the BTH region, particularly in the big cities of Beijing and Tianjin, the large-scale expansion of the urban surface reduces the surface moisture, the evaporation of surface water from the ground, and the height of the atmospheric boundary layer, leading to an urban dry island effect brought about by the lack of near-surface water vapor, which inhibits an increase in precipitation. The positive effect of the urban heat island on precipitation was offset by the urban dry island effect, so the increase in precipitation in the urban areas was not obvious, but an increased range of 8–10 mm was noted. The existence of large cities changes the position of the strong upward movement of air, and convective upward movement is more likely to occur between the suburbs. With the further expansion of the underlying surface of the adjacent cities of Beijing and Tianjin, the upward movement between the two cities coincides, leading to an obvious increase in precipitation between the two cities.


2019 ◽  
Vol 15 (5) ◽  
pp. 1825-1844 ◽  
Author(s):  
Satyaban B. Ratna ◽  
Timothy J. Osborn ◽  
Manoj Joshi ◽  
Bao Yang ◽  
Jianglin Wang

Abstract. We examine the relationships in models and reconstructions between the multidecadal variability of surface temperature in East Asia and two extratropical modes of variability: the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO). We analyse the spatial, temporal and spectral characteristics of the climate modes in the last millennium, historical and pre-industrial control simulations of seven Coupled Model Intercomparison Project phase 5 (CMIP5)/Paleoclimate Model Intercomparison Project phase 3 (PMIP3) global climate models (GCMs) to assess the relative influences of external forcing and unforced variability. These models produce PDO and AMO variability with realistic spatial patterns but widely varying spectral characteristics. AMO internal variability significantly influences East Asian temperature in five models (MPI, HadCM3, MRI, IPSL and CSIRO) but has a weak influence in the other two (BCC and CCSM4). In most models, external forcing greatly strengthens these statistical associations and hence the apparent teleconnection with the AMO. PDO internal variability strongly influences East Asian temperature in two out of seven models, but external forcing makes this apparent teleconnection much weaker. This indicates that the AMO–East Asian temperature relationship is partly driven by external forcing, whereas the PDO–temperature relationship is largely from internal variability within the climate system. Our findings suggest that external forcing confounds attempts to diagnose the teleconnections of internal multidecadal variability. Using AMO and PDO indices that represent internal variability more closely and minimising the influence of external forcing on East Asian temperature can partly ameliorate this confounding effect. Nevertheless, these approaches still yield differences between the forced and control simulations and they cannot always be applied to paleoclimate reconstructions. Thus, we recommend caution when interpreting teleconnections diagnosed from reconstructions that contain both forced and internal variations.


Author(s):  
Conrad Wasko

As climate change alters flood risk, there is a need to project changes in flooding for water resource management, infrastructure design and planning. The use of observed temperature relationships for informing changes in hydrologic extremes takes many forms, from simple proportional change approaches to conditioning stochastic rainfall generation on observed temperatures. Although generally focused on understanding changes to precipitation, there is an implied transfer of information gained from precipitation-temperature sensitivities to flooding as extreme precipitation is often responsible for flooding. While reviews of precipitation-temperature sensitivities and the non-stationarity of flooding exist, little attention has been given to the intersection of these two topics. Models which use temperature as a covariate to assess the non-stationarity of extreme precipitation outperform both stationary models and those using a temporal trend as a covariate. But care must be taken when projecting changes in flooding on the basis on precipitation-temperature sensitivities, as antecedent conditions modify the runoff response. Although good agreement is found between peak flow-temperature sensitivities and historical trends across Australia, there remains little evaluation of flood projections using temperature sensitivities globally. Significant work needs to be done before the use of temperature as a covariate for flood projection can be adopted with confidence. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.


2021 ◽  
Author(s):  
Zhen Su ◽  
Shraddha Gupta ◽  
Norbert Marwan ◽  
Niklas Boers ◽  
Jürgen Kurths

<p>The spatio-temporal patterns of precipitation are of considerable relevance in the context of understanding the underlying mechanism of climate phenomena. The application of the complex network paradigm as a data-driven technique for the investigation of the climate system has contributed significantly to identifying the key regions influencing the climate variability of a target region of interest and, in particular, to improving the predictability of extreme events. In our work, we conduct a comparative study of precipitation patterns by constructing functional climate networks using two nonlinear event similarity measures – event synchronization (ES) and edit-distance (ED). Event synchronization has been widely applied to identify interactions between occurrences of different climate phenomena by counting the number of synchronized events between two event series. Edit-distance measures the similarity between sequences by minimizing the number of operations required to transform one sequence to another. We suggest edit-distance as an alternative approach for network reconstruction that can measure similarity between two event series by incorporating not only event occurrences but also event amplitudes. Here, we compare the global extreme precipitation patterns obtained from both reconstruction methods based on the topological characteristics of the resulting networks. As a case study, we compare selected features of network representations of East Asian heavy precipitation events obtained using both ES and ED. Our results reveal the complex nature of the interaction between the Indian Summer Monsoon (ISM) and the East Asian Summer Monsoon (EASM) systems. Through a systematic comparison, we explore the limitations of both measures and show the robustness of the network structures.</p>


2018 ◽  
Author(s):  
Satyaban B. Ratna ◽  
Timothy J. Osborn ◽  
Manoj Joshi ◽  
Bao Yang ◽  
Jianglin Wang

Abstract. We examine the relationships in models and reconstructions between the multidecadal variability of surface temperature in East Asia and two extratropical modes of variability: the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal oscillation (PDO). We analyze the spatial, temporal and spectral characteristics of the climate modes in Last Millennium, Historical and pre-industrial control simulations of three CMIP5/PMIP3 GCMs, to assess the relative influences of external forcing and unforced variability. These models produce PDO and AMO variability with realistic spatial patterns and their spectral characteristics. AMO internal variability strongly influences East Asia temperature in one model (bcc-csm1-1), but has a weak influence in the other two (CCSM4 and MPI-ESM-P). In all three models, external forcing greatly strengthens these statistical associations and hence the apparent teleconnection with the AMO. PDO internal variability strongly influences East Asian temperature in two of the three models, but external forcing makes this apparent teleconnection much weaker. This indicates that the AMO-East Asian temperature relationship is partly driven by external forcing whereas the PDO-temperature relationship is largely driven by internal variability. External forcing confounds attempts to diagnose the teleconnections of internal multidecadal variability. Using AMO and PDO indices that represent internal variability more closely and minimising the influence of external forcing on East Asia temperature can partly ameliorate this confounding effect. Nevertheless, these approaches still yield differences between the forced and control simulations and they cannot always be applied to paleoclimate reconstructions, so we recommend caution when interpreting internal variability teleconnections diagnosed from reconstructions that contain both forced and internal variations.


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