Southern African summer-rainfall variability, and its teleconnections, on interannual to interdecadal timescales in CMIP5 models

23 pagesInternational audienceThis study provides the first assessment of CMIP5 model performances in simulating southern Africa (SA) rainfall variability in austral summer (Nov–Feb), and its teleconnections with large-scale climate variability at different timescales. Observed SA rainfall varies at three major timescales: interannual (2–8 years), quasi-decadal (8–13 years; QDV) and interdecadal (15–28 years; IDV). These rainfall fluctuations are, respectively, associated with El Niño Southern Oscillation (ENSO), the Interdecadal Pacific Oscillation (IPO) and the Pacific Decadal Oscillation (PDO), interacting with climate anomalies in the South Atlantic and South Indian Ocean. CMIP5 models produce their own variability, but perform better in simulating interannual rainfall variability, while QDV and IDV are largely underestimated. These limitations can be partly explained by spatial shifts in core regions of SA rainfall variability in the models. Most models reproduce the impact of La Niña on rainfall at the interannual scale in SA, in spite of limitations in the representation of ENSO. Realistic links between negative IPO are found in some models at the QDV scale, but very poor performances are found at the IDV scale. Strong limitations, i.e. loss or reversal of these teleconnections, are also noted in some simulations. Such model errors, however, do not systematically impact the skill of simulated rainfall variability. This is because biased SST variability in the South Atlantic and South Indian Oceans strongly impact model skills by modulating the impact of Pacific modes of variability. Using probabilistic multi-scale clustering, model uncertainties in SST variability are primarily driven by differences from one model to another, or comparable models (sharing similar physics), at the global scale. At the regional scale, i.e. SA rainfall variability and associated teleconnections, while differences in model physics remain a large source of uncertainty, the contribution of internal climate variability is increasing. This is particularly true at the QDV and IDV scales, where the individual simulations from the same model tend to differentiate, and the sampling error increase

Southern Africa Climate Over the Recent Decades:Description, Variability and Trends

South of 15°S, southern Africa has a subtropical climate, which is affected by temperate and tropical weather systems and comes under the influence of the Southern Hemisphere high-pressure systems. Most rainfall occurs in austral summer, but the southwest experiences winter rainfall. Much of the precipitation in summer is of convective origin forced by large-scale dynamics. There is a marked diurnal cycle in rainfall in summer. The El Niño Southern Oscillation (ENSO) influences interannual rainfall variability. In austral summer, drought tends to occur during El Niño, while above-normal rainfall conditions tend to follow La Niña. During El Niño, higher than normal atmospheric pressure anomalies, detrimental to rainfall, occur due to changes in the global atmospheric circulation. This also weakens the moisture transport from the Indian Ocean to the continent. The opposite mechanisms happen during La Niña. On top of the variability related to ENSO, the Pacific Ocean also influences the decadal variability of rainfall. Additionally, the Angola Current, the Agulhas Current, the Mozambique Channel and the southwest Indian Ocean affect rainfall variability. Over the last 40 to 60 years, near-surface temperatures have increased over almost the whole region, summer precipitation has increased south of 10°S, and winter precipitation has mostly decreased in South Africa. Meanwhile, the Agulhas Current and the Angola Current have warmed, and the Benguela Current has cooled

Impact of the Agulhas Current on Southern Africa Precipitation: A Modeling Study

Postponed access: the file will be available after 2022-05-22The Agulhas Current (AC) creates a sharp temperature gradient with the surrounding ocean, leading to a large turbulent flux of moisture from ocean to atmosphere. We use two simulations of the Weather Research and Forecasting (WRF) Model to show the seasonal impact of the warm core of the AC on southern Africa precipitation. In one simulation the sea surface temperature (SST) of the AC is similar to satellite observations, while the second uses satellite SST observations spatially smoothed to reduce the temperature of the core of the AC by ~1.5°C. We show that decreasing the SST of the AC reduces the precipitation of the wettest seasons (austral summer and autumn) inland. Over the ocean, reducing the SST reduces precipitation, low-level wind convergence, SST, and SLP Laplacians above the AC in all seasons, consistent with the pressure adjustment mechanism. Moreover, winter precipitation above the AC may also be related to increased latent flux. In summer and autumn, the AC SST reduction is also associated with decreased precipitation farther inland (more than 1.5 mm day−1), caused by an atmospheric circulation that decreases the horizontal moisture flux from the AC to South Africa. The reduction is also associated with higher geopotential height extending from the surface east and over the AC to the midtroposphere over southeastern Africa. The westward tilted geopotential height is consistent with the linear response to shallow diabatic heating in midlatitudes. An identical mechanism occurs in spring but is weaker. Winter rainfall response is confined above the AC.publishedVersio

Structure and origin of the subtropical South Indian Ocean Countercurrent

The structure of the subtropical South Indian Ocean Countercurrent (SICC) is revealed by altimeter-derived absolute geostrophic surface velocities. It is a narrow, eastward-flowing current between 22° and 26°S confined to planetary wave trains which propagate westward through the Indian Ocean. Multi-year averaging identifies it as a well-defined current between Madagascar and 80°E, continuing with lower intensity between 90° and 100°E. It virtually coincides with the northern limit of Subtropical Underwater subduction. Geostrophic currents from hydrographic sections closely correspond to these surface patterns. Volume transports of the countercurrent down to 800 dbar are of order (107 m3 s−1). Evidence is provided for a narrow branch of the South Equatorial Current (SEC) approaching Madagascar near 18°S and feeding the southern East Madagascar Current (EMC) which appears to continue westward around the southern tip of Madagascar. It then partially retroflects and nourishes the SICC

Interannual memory effects for spring NDVI in semi-arid South Africa

Almost 20 years of Normalized Difference Vegetative Index (NDVI) and precipitation (PPT) data are analysed to better understand the interannual memory effects on vegetation dynamics observed at regional scales in Southern Africa (SA). The study focuses on a semi-arid region (25°S–31°S; 21°E–26°E) during the austral early summer (September–December). The memory effects are examined using simple statistical approaches (linear correlations and regressions) which require the definition of an early summer vegetation predictand (December NDVI minus September NDVI) and a consistent set of potential predictors (rainfall amount, number of rainy days, rainfall intensity, NDVI and Rain-Use-Efficiency) considered with 4 to 15-month time-lag. An analysis over six SA sub-regions, corresponding to the six major land-cover types of the area reveals two distinct memory effects. A “negative” memory effect (with both rainfall and vegetation) is detected at 7 to 10-month time-lag while a “positive” memory effect (with vegetation only) is observed at 12 to 14-month time-lag. These results suggest that interannual memory effects in early summer vegetation dynamics of semi-arid South Africa may preferably be driven by biological rather than hydrological mechanisms

Scaling Observation Error for Optimal Assimilation of CCI SST Data into a Regional HYCOM EnOI System

South Africa currently possesses no operational ocean forecasting system for the purpose of predicting ocean state variables including temperature,salinity and velocity. Substantial initial efforts towards this goal have been made and resulted in a system using a regional Hybrid Coordinate Ocean Model (HYCOM) along with the Ensemble Optimal Interpolation (EnOI)assimilation scheme. Assimilating only sea surface temperature (SST) observations from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) product into the system resulted in a degraded forecast. Aiming to address this, Climate Change Initiative (CCI) SSTs are assimilated into the system in an effort to improve the forecast skill. Observation errors in the assimilated product are used in the EnOI to determine whether more confidence should be placed in the model or observations in producing the analysis, but overconfidence in observations can shock the model and result in failure. To tweak the impact of the assimilation, a scaling factor is applied in the assimilation code. A scaling factor of 25 was found to produce a favourable result with lowest mean root mean square error (RMSE;1.098C) between the model and observations over time. Postulating the error to be overconfident, a floor value is introduced in order to set a minimum value for the observation error thereby reducing confidence in the observations. These experiments fared less favourably with a floor value of 0.5 and a scaling factor of 15 producing the best mean RMSE (1.118C)

A 1000-year carbon isotope rainfall proxy record from South African baobab trees (Adansonia digitata L.)

A proxy rainfall record for northeastern South Africa based on carbon isotope analysis of four baobab ( Adansonia digitata L.) trees shows centennial and decadal scale variability over the last 1,000 years. The record is in good agreement with a 200-year tree ring record from Zimbabwe, and it indicates the existence of a rainfall dipole between the summer and winter rainfall areas of South Africa. The wettest period was c. AD 1075 in the Medieval Warm Period, and the driest periods were c. AD 1635, c. AD 1695 and c. AD1805 during the Little Ice Age. Decadal-scale variability suggests that the rainfall forcing mechanisms are a complex interaction between proximal and distal factors. Periods of higher rainfall are significantly associated with lower sea-surface temperatures in the Agulhas Current core region and a negative Dipole Moment Index in the Indian Ocean. The correlation between rainfall and the El Niño/Southern Oscillation Index is non-static. Wetter conditions are associated with predominantly El Niño conditions over most of the record, but since about AD 1970 this relationship inverted and wet conditions are currently associated with la Nina conditions. The effect of both proximal and distal oceanic influences are insufficient to explain the rainfall regime shift between the Medieval Warm Period and the Little Ice Age, and the evidence suggests that this was the result of a northward shift of the subtropical westerlies rather than a southward shift of the Intertropical Convergence Zone

Latent Heat Flux in the Agulhas Current

In-situ observation, climate reanalyses, and satellite remote sensing are used to study the annual cycle of turbulent latent heat flux (LHF) in the Agulhas Current system. We assess if the datasets do represent the intense exchange of moisture that occurs above the Agulhas Current and the Retroflection region, especially the new reanalyses as the former, the National Centers for Environmental Prediction Reanalysis 2 (NCEP2) and the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis second-generation reanalysis (ERA-40) have lower sea and less distinct surface temperature (SST) in the Agulhas Current system due to their low spatial resolution thus do not adequately represent the Agulhas Current LHF. We use monthly fields of LHF, SST, surface wind speed, saturated specific humidity at the sea surface (Qss), and specific humidity at 10 m (Qa). The Climate Forecast System Reanalysis (CFSR), the European Centre for Medium-Range Weather Forecast fifth generation (ERA-5), and the Modern-Era Retrospective analysis for Research and Applications version-2 (MERRA-2) are similar to the air–sea turbulent fluxes (SEAFLUX) and do represent the signature of the Agulhas Current. ERA-Interim underestimates the LHF due to lower surface wind speeds than other datasets. The observation-based National Oceanography Center Southampton (NOCS) dataset is different from all other datasets. The highest LHF of 250 W/m2 is found in the Retroflection in winter. The lowest LHF (~100 W/m2) is off Port Elizabeth in summer. East of the Agulhas Current, Qss-Qa is the main driver of the amplitude of the annual cycle of LHF, while it is the wind speed in the Retroflection and both Qss-Qa and wind speed in between. The difference in LHF between product are due to differences in Qss-Qa wind speed and resolution of datasets

From synoptic to interdecadal variability in southern African rainfall: towards a unified view across timescales

International audienceDuring the austral summer season (November–February), southern African rainfall, south of 20°S, has been shown to vary over a range of time scales, from synoptic variability (3–7 days, mostly tropical temperate troughs) to interannual variability (2–8 years, reflecting the regional effects of El Niño–Southern Oscillation). There is also evidence for variability at quasi-decadal (8–13 years) and interdecadal (15–28 years) time scales, linked to the interdecadal Pacific oscillation and the Pacific decadal oscillation, respectively. This study aims to provide an overview of these ranges of variability and their influence on regional climate and large-scale atmospheric convection and quantify uncertainties associated with each time scale. We do this by applying k-means clustering onto long-term (1901–2011) daily outgoing longwave radiation anomalies derived from the 56 individual members of the Twentieth Century Reanalysis. Eight large-scale convective regimes are identified. Results show that 1) the seasonal occurrence of the regimes significantly varies at the low-frequency time scales mentioned above; 2) these modulations account for a significant fraction of seasonal rainfall variability over the region; 3) significant associations are found between some of the regimes and the aforementioned modes of climate variability; and 4) associated uncertainties in the regime occurrence and convection anomalies strongly decrease with time, especially the phasing of transient variability. The short-lived synoptic anomalies and the low-frequency anomalies are shown to be approximately additive, but even if they combine their respective influence at both scales, the magnitude of short-lived perturbations remains much larger

The impact of ENSO on Southern African rainfall in CMIP5 ocean atmosphere coupled climate models

We study the ability of 24 ocean atmosphere global coupled models from the Coupled Model Intercomparison Project 5 (CMIP5) to reproduce the teleconnections between El Niño Southern Oscillation (ENSO) and Southern African rainfall in austral summer using historical forced simulations, with a focus on the atmospheric dynamic associated with El Niño. Overestimations of summer rainfall occur over Southern Africa in all CMIP5 models. Abnormal westward extensions of ENSO patterns are a common feature of all CMIP5 models, while the warming of the Indian Ocean that happens during El Niño is not correctly reproduced. This could impact the teleconnection between ENSO and Southern African rainfall which is represented with mixed success in CMIP5 models. Large-scale anomalies of suppressed deep-convection over the tropical maritime continent and enhanced convection from the central to eastern Pacific are correctly simulated. However, regional biases occur above Africa and the Indian Ocean, particularly in the position of the deep convection anomalies associated with El Niño, which can lead to the wrong sign in rainfall anomalies in the northwest part of South Africa. From the near-surface to mid-troposphere, CMIP5 models underestimate the observed anomalous pattern of pressure occurring over Southern Africa that leads to dry conditions during El Niño years