Analysis And Synthesis Of Data About Drought In Cape Town Pdf
Examining four major climate-related disasters, , and their impacts on food security. Precipitation in Somaliland and especially Somalia is on average higher during El Niño and lower during La Niña. As a measure of the strength of La Niña we use a detrended Niño3.4 index, which is the same area average as the normal Niño3.4 index (5ºS-5ºN, 120º-170ºW) but with the average SST over 30ºS-30ºN subtracted. The trends in these two series are very similar, so they cancel in the difference (H. Hendon, pers. comm.). The resulting series agrees much better with non-temperature ENSO indices such as the Southern Oscillation Index or projections on precipitation patterns . Sign up to our newsletters and get the latest analysis, research, commentary and details of upcoming events.
Businesses requiring water or electricity for their operations often came to a standstill. More people are moving to cities – the size of the urban population is set to double in the next 25 years from today’s 472 million. As the incomers set up businesses and connect, often for the first time, to water and electricity grids, causing a surge in demand, the existing infrastructure faces unprecedented pressure. Combined with a changing climate, and droughts in El Niño years, this is placing energy and water infrastructure under severe stress in some areas. The EUROSIP multi-model seasonal forecast from 1 September shows some indication of a higher probability of drought in western Kenya and southern Ethiopia, but not in Somalia or Somaliland , in spite of a good La Niña forecast.
Note that in this analysis we consider only meteorological drought, i.e., lack of rain, not the separate effect of temperature. In this region average temperatures have been rising roughly at the same rate as the global mean temperature . However, there are no recent public temperature observation in Somalia or neighboring countries to confirm this, and reanalysis disagree on the pattern of warming. Furthermore, in order to assess the impact of higher temperatures on the current conditions, we would need to assess how higher temperatures affect runoff, evapotranspiration and water scarcity.
The fact that even fairly moderate changes in rainfall can cause major consequences for the businesses that underpin economies should be a wake-up call. In Zambia’s capital Lusaka, meanwhile, low lake levels affected electricity supply, as hydropower accounts for 94 per cent of the country’s electricity generation capacity. As a result of low rainfall and increased dam outflows to meet rising demand for power, low water levels in Lake Kariba contributed to a national power deficit of around 985 megawatts in October 2015.
In this model anthropogenic climate change does increase the likelihood of dry events to occur, in both analysed regions. What is a 1-in-10 year event in the current climate of 2016 in the stippled region would have been a 1-in-25 year event in the natural simulations of 2016. A 1-in-100 year event in Somaliland under 2016 conditions would have been a 1-in-189 year event in the natural 2016 simulations. In contrast to the observations the observed SSTs do not change the likelihood of low rainfall in this model. This highlights that the model potentially does not simulate the rainfall response to large scale variability in the region well, hence results need to be interpreted with caution. East African rainfall studies indicate that coherent projections of precipitation across the region are possible.
Depending on the details of the fitting procedure, one gets a slight but non-significant positive or negative trend in both areas. The uncertainties in the observed trends are very large and easily encompass zero as they range from roughly a factor ten more probability of dry extremes to a factor ten less. Note that this uncertainty range does not yet include systematic uncertainties due to changes in the observing system, but only results from natural variability of the climate. In this analysis we investigate the roles of climate change and El Niño in the observed very low precipitation in Somalia in 2016 using both climate models and observational data.
In Botswana, drought conditions contributed to historically low lake levels in the Gaborone reservoir, which is the main piped water source for the capital. By the end of 2015, demand for water in Gaborone was surpassing supply by almost 33 million litres a day and residents experienced decreased water pressure and in some cases complete cut-off of supply. The annual mean precipitation in Central Somalia has a strong increase in dry extremes in the historical HadGEM3-A ensemble.
The KNMI Climate Change Atlas shows for the mean CMIP5 precipitation on average a slight wetting trend, especially in the north, but with an uncertainty that easily encompasses no change. We did not yet study dry extremes, only the trend in the mean, in the full CMIP5 ensemble as these would require bias corrections for each model separately. The strong La Niña that was active at the time increased the probability of a dry season and explains about one third of the precipitation deficit. The CenTrends dataset goes back to 1900 and is based on an extensive collection of station data in eastern Africa. Overall, we found no trend in the observations but due to the high variability of rain in this area this still allows fairly large underlying trends.
For this rapid attribution we used three models for which the data were readily available to study the climate change signal. The first is the SST-forced HadGEM3-A 15-member ensemble at N219 resolution (~60km) that was created for the EUCLEIA project for . As the 2016 data are not yet available we used the trend in the historical simulations as a proxy for the climate change signal. This model has, within uncertainties, the same variability relative to the mean as the observations so that we can use it with a simple multiplicative bias correction (0.55 for Somalia, 0.72 for Somaliland, the model is too wet). The same GPD fit as to the observations gives a non-significant trend towards fewer dry extremes, both for Somalia and for Somaliland. The historicalNat ensemble, which includes the effects of natural forcings , observed variability in SST and model drift has no significant trends.
However, there is a slight non-significant trend towards more rain in that ensemble as well. For the final result from HadGEM3-A we take the difference between the historical and historicalNat trends . Two of the models show no trend, one a small increase in the likelihood of dry extremes. Taking all the evidence together we therefore conclude that the effect of climate change on dry extremes in Somalia and Somaliland in the autumn rains is small compared to natural variability.
It is unknown whether a spatial bias correction would have yielded more useful forecasts in view of the observed teleconnections. We fitted a Generalised Pareto Distribution to the lowest 40 percent of the data over the period , which is allowed to scale with the smoothed global mean surface temperature as an indicator for the effects of global warming. Geographically, the northwestern part of Somalia, also known as Somaliland, has a somewhat different climate from the rest of the country. We therefore carried out two separate analyses, one for this northwestern region, hereafter referred to as Somaliland, and one for the rest of the country, hereafter referred to as Somalia . Action is needed across sub-Saharan Africa to increase understanding of the vulnerabilities in existing water, energy and urban infrastructure – and of the effects of increasing urbanisation and a changing climate. In particular MSMEs need to be supported to cope with a wider range of climate impacts.
However, the historicalNat ensemble has an even stronger trend, so the difference between the two, which represents the anthropogenic influence, is again compatible with no influence. The CenTrends dataset goes back to 1900 and is based on an extensive collection of station data in eastern Africa, a region that typically has sparse data coverage. It contains more station data than other analyses in this region, with about 20 stations from 1920 to 2000, four stations in . Under-investment in infrastructure and planning, policy uncertainty, governance challenges, and poor local service provision have all combined to limit the development of new urban infrastructure, and the effective management of existing resources. Yet these infrastructure and resources are needed to keep up with the increased demand caused by urbanisation. In southern Africa, these factors have exacerbated the impacts of drought in urban areas.
As of March 2017, over 40 percent of the Somali population was in need of emergency food assistance . The deteriorating situation partly resulted from successive dry spells in 2016, leading to increased risk of mortality and severe long-term impacts on livelihoods and assets . The main rivers along which many people base their livelihoods, the Shabelle, Dawa, and Juba have reached very low levels or have run dry . As almost always, food insecurity does not result from a meteorological drought alone. In Somalia the protracted conflict, lack of access to markets, and underlying structural factors play important roles in determining the risk . The climatic events in southern Africa that followed the El Niño of 2015/16 – one of the strongest El Niño events in the past 50 years – manifested as below-normal precipitation during key parts of the rainy seasons in both years, and heat waves.