Multiscale investigation of precipitation extremes over Ethiopia and teleconnections to large-scale climate anomalies

2021 ◽  
Author(s):  
Tegegn Kassa Beyene ◽  
Manoj Kumar Jain ◽  
Brijesh K. Yadav ◽  
Ankit Agarwal
Keyword(s):  
Large Scale ◽  
Precipitation Extremes ◽  
Climate Anomalies

scholarly journals Multiscale Spatio-Temporal Changes of Precipitation Extremes in Beijing-Tianjin-Hebei Region, China during 1958–2017

Atmosphere ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 462 ◽  
Author(s):  
Xiaomeng Song ◽  
Xianju Zou ◽  
Chunhua Zhang ◽  
Jianyun Zhang ◽  
Fanzhe Kong
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Periodic Oscillation ◽  
Precipitation Extremes ◽  
Climate Indices ◽  
Climate Anomalies ◽  
Wet Precipitation ◽  
Spatio Temporal ◽  
One Year ◽  
Periodic Components

In this study, based on daily precipitation records during 1958–2017 from 28 meteorological stations in the Beijing-Tianjin-Hebei (BTH) region, the spatio-temporal variations in precipitation extremes defined by twelve indices are analyzed by the methods of linear regression, Mann-Kendall test and continuous wavelet transform. The results showed that the spatial patterns of all the indices except for consecutive dry days (CDD) and consecutive wet days (CWD) were similar to that of annual total precipitation with the high values in the east and the low value in the west. Regionally averaged precipitation extremes were characterized by decreasing trends, of which five indices (i.e., very heavy precipitation days (R50), very wet precipitation (R95p), extreme wet precipitation (R99p), max one-day precipitation (R × 1day), and max five-day precipitation (R × 5day)) exhibited significantly decreasing trends at 5% level. From monthly and seasonal scale, almost all of the highest values in R × 1day and R × 5day occurred in summer, especially in July and August due to the impacts of East Asian monsoon climate on inter-annual uneven distribution of precipitation. The significant decreasing trends in annual R×1day and R×5day were mainly caused by the significant descend in summer. Besides, the possible associations between precipitation extremes and large-scale climate anomalies (e.g., ENSO (El Niño Southern Oscillation), NAO (North Atlantic Oscillation), IOD (Indian Ocean Dipole), and PDO (Pacific Decadal Oscillation)) were also investigated using the correlation analysis. The results showed that the precipitation extremes were significantly influenced by ENSO with one-year ahead, and the converse correlations between the precipitation extremes and climate indices with one-year ahead and 0-year ahead were observed. Moreover, all the indices show significant two- to four-year periodic oscillation during the entire period of 1958–2017, and most of indices show significant four- to eight-year periodic oscillation during certain periods. The influences of climate anomalies on precipitation extremes were composed by different periodic components, with most of higher correlations occurring in low-frequency components.

scholarly journals Changes in Temperature and Precipitation Extremes in Superparameterized CAM in Response to Warmer SSTs

2017 ◽  
Vol 30 (24) ◽  
pp. 9827-9845 ◽  
Author(s):  
Xin Zhou ◽  
Marat F. Khairoutdinov
Keyword(s):  
Large Scale ◽  
Rain Rate ◽  
Precipitable Water ◽  
Heavy Precipitation ◽  
Global Scale ◽  
Precipitation Extremes ◽  
Temperature And Precipitation ◽  
Hourly Data ◽  
Cloud Resolving Model ◽  
Cold Extremes

Subdaily temperature and precipitation extremes in response to warmer SSTs are investigated on a global scale using the superparameterized (SP) Community Atmosphere Model (CAM), in which a cloud-resolving model is embedded in each CAM grid column to simulate convection explicitly. Two 10-yr simulations have been performed using present climatological sea surface temperature (SST) and perturbed SST climatology derived from the representative concentration pathway 8.5 (RCP8.5) scenario. Compared with the conventional CAM, SP-CAM simulates colder temperatures and more realistic intensity distribution of precipitation, especially for heavy precipitation. The temperature and precipitation extremes have been defined by the 99th percentile of the 3-hourly data. For temperature, the changes in the warm and cold extremes are generally consistent between CAM and SP-CAM, with larger changes in warm extremes at low latitudes and larger changes in cold extremes at mid-to-high latitudes. For precipitation, CAM predicts a uniform increase of frequency of precipitation extremes regardless of the rain rate, while SP-CAM predicts a monotonic increase of frequency with increasing rain rate and larger change of intensity for heavier precipitation. The changes in 3-hourly and daily temperature extremes are found to be similar; however, the 3-hourly precipitation extremes have a significantly larger change than daily extremes. The Clausius–Clapeyron scaling is found to be a relatively good predictor of zonally averaged changes in precipitation extremes over midlatitudes but not as good over the tropics and subtropics. The changes in precipitable water and large-scale vertical velocity are equally important to explain the changes in precipitation extremes.

scholarly journals Simulating future precipitation extremes in a complex Alpine catchment

2013 ◽  
Vol 13 (2) ◽  
pp. 263-277 ◽  
Author(s):  
C. Dobler ◽  
G. Bürger ◽  
J. Stötter
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Precipitation Extremes ◽  
Climate Projections ◽  
Research Station ◽  
Climate Change Scenarios ◽  
Station Data

Abstract. The objectives of the present investigation are (i) to study the effects of climate change on precipitation extremes and (ii) to assess the uncertainty in the climate projections. The investigation is performed on the Lech catchment, located in the Northern Limestone Alps. In order to estimate the uncertainty in the climate projections, two statistical downscaling models as well as a number of global and regional climate models were considered. The downscaling models applied are the Expanded Downscaling (XDS) technique and the Long Ashton Research Station Weather Generator (LARS-WG). The XDS model, which is driven by analyzed or simulated large-scale synoptic fields, has been calibrated using ECMWF-interim reanalysis data and local station data. LARS-WG is controlled through stochastic parameters representing local precipitation variability, which are calibrated from station data only. Changes in precipitation mean and variability as simulated by climate models were then used to perturb the parameters of LARS-WG in order to generate climate change scenarios. In our study we use climate simulations based on the A1B emission scenario. The results show that both downscaling models perform well in reproducing observed precipitation extremes. In general, the results demonstrate that the projections are highly variable. The choice of both the GCM and the downscaling method are found to be essential sources of uncertainty. For spring and autumn, a slight tendency toward an increase in the intensity of future precipitation extremes is obtained, as a number of simulations show statistically significant increases in the intensity of 90th and 99th percentiles of precipitation on wet days as well as the 5- and 20-yr return values.

scholarly journals Seasonal Forecasts of the Twentieth Century

2020 ◽  
Vol 101 (8) ◽  
pp. E1413-E1426 ◽  
Author(s):  
Antje Weisheimer ◽  
Daniel J. Befort ◽  
Dave MacLeod ◽  
Tim Palmer ◽  
Chris O’Reilly ◽  
...  
Keyword(s):  
Twentieth Century ◽  
Large Scale ◽  
Seasonal Forecast ◽  
Forecast Skill ◽  
Seasonal Forecasts ◽  
Climate Anomalies ◽  
Global Circulation Models ◽  
Skill Scores ◽  
Physically Based ◽  
Forecast Models

Abstract Forecasts of seasonal climate anomalies using physically based global circulation models are routinely made at operational meteorological centers around the world. A crucial component of any seasonal forecast system is the set of retrospective forecasts, or hindcasts, from past years that are used to estimate skill and to calibrate the forecasts. Hindcasts are usually produced over a period of around 20–30 years. However, recent studies have demonstrated that seasonal forecast skill can undergo pronounced multidecadal variations. These results imply that relatively short hindcasts are not adequate for reliably testing seasonal forecasts and that small hindcast sample sizes can potentially lead to skill estimates that are not robust. Here we present new and unprecedented 110-year-long coupled hindcasts of the next season over the period 1901–2010. Their performance for the recent period is in good agreement with those of operational forecast models. While skill for ENSO is very high during recent decades, it is markedly reduced during the 1930s–1950s. Skill at the beginning of the twentieth century is, however, as high as for recent high-skill periods. Consistent with findings in atmosphere-only hindcasts, a midcentury drop in forecast skill is found for a range of atmospheric fields, including large-scale indices such as the NAO and the PNA patterns. As with ENSO, skill scores for these indices recover in the early twentieth century, suggesting that the midcentury drop in skill is not due to a lack of good observational data. A public dissemination platform for our hindcast data is available, and we invite the scientific community to explore them.

Changes in Yangtze Precipitation Extremes and the association with thermodynamic, dynamic, and local drivers  

2021 ◽  
Author(s):  
Xin Li
Keyword(s):  
Global Warming ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Global Climate ◽  
Yangtze River Basin ◽  
Precipitation Extremes ◽  
Spatiotemporal Variability ◽  
Local Effects ◽  
Dynamic Factors ◽  
The Yangtze River Basin

<p>Spatioteporal variability of precipitation extremes is increasingly the focus of attention in both the climate and hydrology communites, especailly in the context of global climate change. Indicated by the Clausius-Clapeyron equation under the constant relative humudity assumption, it is expected, from the thermodynamic perspective, that extreme precipitation would increase as globe warms. However, when it comes to the regional response of precipitation to global warming, the resutls could be highly uncertain due to the influences of dynamic factors such as large-scale circlation patterns and local effects. Here, we investigate trends in a set of extreme precipitation indices (EPIs) over the Yangtze River Basin (YRB) during the period of 1960-2019. Also, we explore the possible associations between spatiotemporal variability of the EPIs and global warming, ENSO, and local effects. Our resutls show marked rising trends in frequency and intensity of Yangtze precipitation extremes. Global warming tends to enhance the frequency and intensity of preciptation extremes over the YRB. The La Niña phase of ENSO could lead to an increase of precipitation extremes in the current year, but a decrease of precipitation extremes in the coming year. Local warming mainly exerts a reducing effect on precipitation extremes, which is likely associated with the significant decrease of relative humidity in the YRB. Our findings highlight the need for a systematic approach to investigate changes in precipitation extremes over the YRB.</p>

Multiscale Variability of Precipitation and Their Teleconnection with Large-scale Climate Anomalies: A Case Study of Xi'an City, China

2019 ◽  
Vol 93 (sp1) ◽  
pp. 417 ◽  
Author(s):  
Xiaojie Wang ◽  
Rengui Jiang ◽  
Jiancang Xie ◽  
Yong Zhao ◽  
Fawei Li ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Anomalies ◽  
Xi’An City

scholarly journals Large-scale dynamics have greater role than thermodynamics in driving precipitation extremes over India

2020 ◽  
Vol 55 (9-10) ◽  
pp. 2603-2614
Author(s):  
Naveen Sudharsan ◽  
Subhankar Karmakar ◽  
Hayley J. Fowler ◽  
Vittal Hari
Keyword(s):  
Large Scale ◽  
Precipitation Extremes
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