scholarly journals Influence of South Atlantic Sea Surface Temperatures on Rainfall Variability and Extremes over Southern Africa

2008 ◽  
Vol 21 (24) ◽  
pp. 6498-6520 ◽  
Author(s):  
C. J. R. Williams ◽  
D. R. Kniveton ◽  
R. Layberry

Abstract It is generally agreed that changing climate variability, and the associated change in climate extremes, may have a greater impact on environmentally vulnerable regions than a changing mean. This research investigates rainfall variability, rainfall extremes, and their associations with atmospheric and oceanic circulations over southern Africa, a region that is considered particularly vulnerable to extreme events because of numerous environmental, social, and economic pressures. Because rainfall variability is a function of scale, high-resolution data are needed to identify extreme events. Thus, this research uses remotely sensed rainfall data and climate model experiments at high spatial and temporal resolution, with the overall aim being to investigate the ways in which sea surface temperature (SST) anomalies influence rainfall extremes over southern Africa. Extreme rainfall identification is achieved by the high-resolution microwave/infrared rainfall algorithm dataset. This comprises satellite-derived daily rainfall from 1993 to 2002 and covers southern Africa at a spatial resolution of 0.1° latitude–longitude. Extremes are extracted and used with reanalysis data to study possible circulation anomalies associated with extreme rainfall. Anomalously cold SSTs in the central South Atlantic and warm SSTs off the coast of southwestern Africa seem to be statistically related to rainfall extremes. Further, through a number of idealized climate model experiments, it would appear that both decreasing SSTs in the central South Atlantic and increasing SSTs off the coast of southwestern Africa lead to a demonstrable increase in daily rainfall and rainfall extremes over southern Africa, via local effects such as increased convection and remote effects such as an adjustment of the Walker-type circulation.

2017 ◽  
Vol 10 (3) ◽  
pp. 1383-1402 ◽  
Author(s):  
Paolo Davini ◽  
Jost von Hardenberg ◽  
Susanna Corti ◽  
Hannah M. Christensen ◽  
Stephan Juricke ◽  
...  

Abstract. The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979–2008) and a climate change projection (2039–2068), together with coupled transient runs (1850–2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate – specifically the Madden–Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small-scale processes on the large-scale climate variability either explicitly (with high-resolution simulations) or stochastically (in low-resolution simulations).


SOLA ◽  
2020 ◽  
Vol 16 (0) ◽  
pp. 132-139
Author(s):  
Sheau Tieh Ngai ◽  
Hidetaka Sasaki ◽  
Akihiko Murata ◽  
Masaya Nosaka ◽  
Jing Xiang Chung ◽  
...  

2007 ◽  
Vol 3 (3) ◽  
pp. 729-753 ◽  
Author(s):  
K. Ljung ◽  
S. Björck ◽  
H. Renssen ◽  
D. Hammarlund

Abstract. One of the most distinct climate fluctuations during the Holocene is the short and rapid event centred around 8200 years ago, the 8.2 kyr event, which was most likely triggered by glacial melt-water forcing from the receding Laurentide ice-sheet. Evidence for this cooling has primarily been reported from sites around the North Atlantic, but an increasing number of observations imply a more wide-spread occurrence. Palaeoclimate archives from the Southern Hemisphere have hitherto failed to uncover a distinct climatic anomaly associated with the 8.2 kyr event. Here we present a lake sediment record from Nightingale Island in the central South Atlantic showing enhanced precipitation between 8275 and 8025 cal. yrs BP, most likely as a consequence of increased sea surface temperature (SST). We show that this is consistent with climate model projections of a warming of the South Atlantic in response to reduced north-ward energy transport during the 8.2 kyr event.


2020 ◽  
Author(s):  
Jonas Olsson ◽  
Johanna Sörensen ◽  
Yiheng Du ◽  
Dong An ◽  
Peter Berg ◽  
...  

<p>In general terms, climate adaptation in cities is highly complicated by the very high required spatial and temporal resolution. The high resolution is needed to capture both the full variability of small-scale high-impact weather phenomena and the associated response from the mosaic of land uses and buildings in urban environments. Most commonly available climate model simulations and projections are too spatially coarse (≥10 km) for a proper assessment of many important urban climate impacts. </p><p>In terms of water-related impacts, a key issue concerns the reproduction of local short-duration rainfall extremes (cloudbursts) that may cause pluvial flooding. An accurate reproduction of the convective generation of such extremes requires a spatial resolution of at least 5 km, preferably even higher, in convection-permitting regional climate models (CPRCM). Conceivably, estimates of future changes in cloudburst characteristics and associated statistics based on CPRCM simulations will be more reliable than today’s estimates based on non-CP RCMs. Because of the extreme computational demand, however, the number of CPRCM simulations made is still rather low and generally limited to small domains and/or short time slices.</p><p>But many efforts are currently being made in this direction and the main focus of this presentation will be a case study evaluation of hourly rainfall extremes from 3×3 km² convection-permitting simulations with the HARMONIE-climate model over the Nordic region. The case study will focus on the region around the Öresund strait, that connects southern Sweden and eastern Denmark. This region contains the cities Malmö and Copenhagen that were both hit by heavy cloudburst in the last decade, that caused severe flooding and substantial damage to infrastructure.</p><p>The presentation will include different aspects of the simulations and their applicability:</p><ul><li><em>Historical performance.</em> Evaluation of reference period simulations, with both ERA-Interim and GCM boundaries, against high-resolution observations, focusing at the reproduction of short-duration (sub-daily) extremes but also e.g. diurnal cycle and spatial variability.</li> <li><em>Future changes.</em> Assessment in terms of climate factors for different durations, return periods and future time horizons. A comparison is made with climate factors estimated from lower-resolution, non-convection permitting downscalings based on the same GCM projections.</li> <li><em>End-user practices.</em> A discussion of what resolution that is needed in order to meet different stakeholders’ needs in the light of climate adaptation. The key question is how the output from CPRCM simulations can be processed and interpreted to provide an added value. </li> </ul><p>Besides the above analyses, two additional related investigations will be presented:</p><ul><li>Lessons learnt from experiments of tailored “urban downscaling” of climate projections down to 1×1 km² and 15 min over selected European urban regions (Stockholm, Bologna, Amsterdam) performed in the Urban SIS project.</li> <li>An evaluation of hourly rainfall extremes over selected European countries in a 11×11 km² EURO-CORDEX ensemble, including spatial patterns and temperature scaling of the estimated future changes.</li> </ul>


2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Charles Onyutha

Trends and variability in series comprising the mean of fifteen highest daily rainfall intensities in each year were analyzed considering entire Uganda. The data were extracted from high-resolution (0.5° × 0.5°) gridded daily series of the Princeton Global Forcings covering the period 1948–2008. Variability was analyzed using nonparametric anomaly indicator method and empirical orthogonal functions. Possible drivers of the rainfall variability were investigated. Trends were analyzed using the cumulative rank difference approach. Generally, rainfall was above the long-term mean from the mid-1950s to the late 1960s and again in the 1990s. From around 1970 to the late 1980s, rainfall was characterized by a decrease. The first and second dominant modes of variability correspond with the variation in Indian Ocean Dipole and North Atlantic Ocean index, respectively. The influence of Niño 3 on the rainfall variability of some parts of the country was also evident. The southern and northern parts had positive and negative trends, respectively. The null hypothesisH0(no trend) was collectively rejected at the significance level of 5% in the series from 7 out of 168 grid points. The insights from the findings of this study are vital for planning and management of risk-based water resources applications.


2008 ◽  
Vol 21 (5) ◽  
pp. 938-962 ◽  
Author(s):  
Gerhard Krinner ◽  
Bérangère Guicherd ◽  
Katia Ox ◽  
Christophe Genthon ◽  
Olivier Magand

Abstract This article reports on high-resolution (60 km) atmospheric general circulation model simulations of the Antarctic climate for the periods 1981–2000 and 2081–2100. The analysis focuses on the surface mass balance change, one of the components of the total ice sheet mass balance, and its impact on global eustatic sea level. Contrary to previous simulations, in which the authors directly used sea surface boundary conditions produced by a coupled ocean–atmosphere model for the last decades of both centuries, an anomaly method was applied here in which the present-day simulations use observed sea surface conditions, while the simulations for the end of the twenty-first century use the change in sea surface conditions taken from the coupled simulations superimposed on the present-day observations. It is shown that the use of observed oceanic boundary conditions clearly improves the simulation of the present-day Antarctic climate, compared to model runs using boundary conditions from a coupled climate model. Moreover, although the spatial patterns of the simulated climate change are similar, the two methods yield significantly different estimates of the amplitude of the future climate and surface mass balance change over the Antarctic continent. These differences are of similar magnitude as the intermodel dispersion in the current Intergovernmental Panel on Climate Change (IPCC) exercise: selecting a method for generating boundary conditions for a high-resolution model may be just as important as selecting the climate model itself. Using the anomaly method, the simulated mean surface mass balance change over the grounded ice sheet from 1981–2000 to 2081–2100 is 43-mm water equivalent per year, corresponding to a eustatic sea level decrease of 1.5 mm yr−1. A further result of this work is that future continental-mean surface mass balance changes are dominated by the coastal regions, and that high-resolution models, which better resolve coastal processes, tend to predict stronger precipitation changes than models with lower spatial resolution.


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