El Niño 2015/2016 impact analysis, monthly outlook December 2015

During the summer and autumn 2015, El Niño conditions in the east and central Pacific have strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during this summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g. droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g. health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work providing information from observations and seasonal forecast models to give a more detailed outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of an ‘Observations and Outlook’ row. This consists of observational information for the past seasons of JJA 2015 and SON 2015, a detailed monthly outlook from 5 modeling centres for Dec 2015 and then longer-term seasonal forecast information from 2 modeling centres for the future seasons of JF 2016 and MAM 2016. The seasonal outlook information is an indication of the average likely conditions for that coming month (or season) and region and is not a definite prediction of weather impacts

El Niño 2015/2016: impact analysis of past El Niños

This is a DfID (Department for International Development) commissioned report on the impact of historical El Niño events on low- and middle-income countries across Africa and elsewhere. The report identifies El Niño events in the past 35 years and highlights regions and countries vulnerable to their impacts. The impacts on rainfall and temperature are broken down by season and country as the El Niño develops, peaks and decays and are represented in at-a-glance Impact Tables. The Impact Tables also include an extensive review of literature (e.g., peer-reviewed, grey literature and media reports) to identify potential socio-economic impacts in vulnerable sectors such as water, infrastructure, energy and health. The risk of such impacts are graded as high, medium or potential depending on the meteorological signal and the robustness of evidence available

La Niña 2016/2017: historical impact analysis

El Niño conditions developed in the tropical Pacific during the latter half of 2015, peaking in December 2015 as one of the strongest El Niño events on record, comparable with the 1997-98 “El Niño of the century”. Conditions in the tropical Pacific are forecast to return to normal over the coming months, with the potential to transition into La Niña conditions during 2016-17. If this was to occur it would act as a further strong perturbation, or ‘kick’, to the climate system and lead to further significant socio-economic impacts affecting many sectors such as infrastructure, agriculture, health and energy. This report analyses La Niña events over the last 37 years of the satellite era (1979-present) and aims to identify regions where there is an increased likelihood of impacts occurring. It is important to note that this analysis is based on past analogous events and is not a prediction for this year. No two La Niña events will be the same – the timing and magnitude of events differs considerably. More importantly, no two La Niña events lead to the same impacts – other local physical and social factors come into play. Therefore, the exact timings, locations and magnitudes of impacts should be interpreted with caution and this should be accounted for in any preparedness measures that are taken. This report has been produced for Evidence on Demand with the assistance of the UK Department for International Development (DFID) contracted through the Climate, Environment, Infrastructure and Livelihoods Professional Evidence and Applied Knowledge Services (CEIL PEAKS) programme, jointly managed by DAI (which incorporates HTSPE Limited) and IMC Worldwide Limited

El Niño 2015/2016 impact analysis, monthly outlook March 2016

During the summer and autumn of 2015, El Niño conditions in the east and central Pacific strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during the summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g., droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g., health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work, providing information from observations and seasonal forecast models to give a more detailed outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of an ‘Observations and Outlook’ row. This consists of observational information for the past seasons of JJA 2015, SON 2015 and DJF 2015/2016, a detailed monthly outlook from 5 modeling centres for Mar 2016 and then longer-term seasonal forecast information from 2 modeling centres for the future seasons of AM 2016 and JJA 2016. The seasonal outlook information is an indication of the average likely conditions for that coming month (or season) and region and is not a definite prediction of weather impacts. This report has been produced by University of Reading for Evidence on Demand with the assistance of the UK Department for International Development (DFID) contracted through the Climate, Environment, Infrastructure and Livelihoods Professional Evidence and Applied Knowledge Services (CEIL PEAKS) programme, jointly managed by DAI (which incorporates HTSPE Limited) and IMC Worldwide Limited

The impact of Indian Ocean mean-state biases in climate models on the representation of the East African short rains

The role of the Indian Ocean Dipole (IOD) in controlling interannual variability in the East African short rains, from October to December, is examined in state-of-the-art models and in detail in one particular climate model. In observations, a wet short-rainy season is associated with the positive phase of the IOD and anomalous easterly low-level flow across the equatorial Indian Ocean. A model's ability to capture the teleconnection to the positive IOD is closely related to its representation of the mean-state. During the short-rains season, the observed low-level wind in the equatorial Indian Ocean is westerly. However, half of the models analysed exhibit mean-state easterlies across the entire basin. Specifically, those models that exhibit mean-state low-level equatorial easterlies in the Indian Ocean, rather than the observed westerlies, are unable to capture the latitudinal structure of moisture advection into East Africa during a positive IOD. Furthermore, the associated anomalous easterly surface wind stress causes upwelling in the eastern Indian Ocean. This upwelling draws up cool sub-surface waters, enhancing the zonal sea-surface temperature gradient between west and east and strengthening the positive IOD pattern, further amplifying the easterly wind stress. This positive Bjerknes coupled feedback is stronger in easterly mean-state models, resulting in a wetter East African short rain precipitation bias in those models

Activity fingerprints in DNA based on a structural analysis of sequence information.

The function of a DNA sequence is commonly predicted by measuring its nucleotide similarity to known functional sets. However, the use of structural properties to identify patterns within families is justified by the discovery that many very different sequences have similar structural properties. The aim of this thesis is to develop tools that detect any unusual structural characteristics of a particular sequence or that identify DNA structure-activity fingerprints common to a set. This work uses the Octamer Database to describe DNA. The database's contents are split into two categories: those parameters that describe minimum energy structure and those that measure flexibility. Information from both of these categories has been combined to describe structural tendencies, offering an alternative measure of sequence similarity. A structural DNA profile gives a graphical illustration of how a parameter from the Octamer Database varies across either a single sequence's length or across a set of sequences. Profile Manager is an application that has been developed to automate single sequence profile generation and is used to study the A-tract phenomenon. The use of profiles to explore patterns in flexibility across a set of pre-aligned promoters is then investigated with interesting transitions in decreasing twist flexibility discovered. Multiple sequence queries are harder to solve than those of single sequences, due to the inherent need for the sequences to be aligned. It is only under rare circumstances that sequences are pre-aligned by an experimentally determined position. More commonly a multiple alignment must be generated. An extended, structure-based, hidden Markov model technique that successfully generates structural alignment~ is presented. Its. application is tested on four DNA protein binding site datasets with comparisons made to the traditional sequence method. Structural alignments of two out of the four datasets were comparable in performance to sequence with useful insights into underlying structural mechanisms

El Niño 2015/2016 impact analysis, monthly outlook January 2016

During the summer and autumn of 2015, El Niño conditions in the east and central Pacific have strengthened, disrupting weather patterns throughout the tropics and into the mid-latitudes. For example, rainfall during this summer’s Indian monsoon was approximately 15% below normal. The continued strong El Niño conditions have the potential to trigger damaging impacts (e.g., droughts, famines, floods), particularly in less-developed tropical countries, which would require a swift and effective humanitarian response to mitigate damage to life and property (e.g., health, migration, infrastructure). This analysis uses key climatic variables (temperature, soil moisture and precipitation) as measures to monitor the ongoing risk of these potentially damaging impacts. The previous 2015-2016 El Niño Impact Analysis was based on observations over the past 35 years and produced Impact Tables showing the likelihood and severity of the impacts on temperature and rainfall by season. The current report is an extension of this work providing information from observations and seasonal forecast models to give a more detailed outlook of the potential near-term impacts of the current El Niño conditions by region. This information has been added to the Impact Tables in the form of an ‘Observations and Outlook’ row. This consists of observational information for the past seasons of JJA 2015, SON 2015 and Dec 2015, a detailed monthly outlook from 4 modeling centres for Jan 2016 and then longer-term seasonal forecast information from 2 modeling centres for the future seasons of Feb 2016, MAM 2016 and Jun 2016. The seasonal outlook information is an indication of the average likely conditions for that coming month (or season) and region and is not a definite prediction of weather impacts

July-September rainfall in the Greater Horn of Africa: the combined influence of the Mascarene and South Atlantic highs

July-September rainfall is a key component of Ethiopia’s annual rainfall and is a source of rainfall variability throughout inland Greater Horn of Africa. In this study we investigate the relative influences of the Mascarene (MH) and South Atlantic (AH) highs on July-September rainfall in a covarying region of the Greater Horn of Africa using CHIRPS observed rainfall and the ERA5 reanalysis. We show that a mixed metric using the circulation at 850 hPa of these two subtropical anticyclones (AH-MH), is better correlated with rainfall than individual high circulations. Variations in remote circulation are translated by changes in Central African westerlies and Turkana Jet wind speeds. We apply the AH-MH mixed metric to the CMIP5 and CMIP6 ensembles and show that it is a good indicator of mean July-September rainfall across both ensembles. Biases in circulation are shown to be related to the Hadley circulation in CMIP5 atmosphere-only simulations, while causes of biases in CMIP6 are more varied. Coupled model biases are related to southern ocean warm biases in CMIP5 and western Indian Ocean warm biases in CMIP6. CMIP6 shows an improved relationship between rainfall and Turkana Jet and Central African westerlies across the ensemble

The potential value of seasonal drought forecasts in the context of climate change: a case study of the African elephant conservation sector

This study investigates meteorological drought in sub-Saharan Africa within the context of elephant conservation. Prolonged drought significantly impacts elephants, leading to increased mortality rates and heightened human– elephant conflicts. We assess both the anticipated 21st century changes in impact-relevant meteorological drought metrics and the efficacy of existing forecasting systems in predicting such droughts on seasonal time scales. The climate change element of our study uses the 6th Coupled Model Intercomparison Project (CMIP6) ensemble to evaluate projected change in 3-month Standardized Precipitation Index (SPI3). We then carry out a quantitative assessment of seasonal forecast skill, utilizing 110 years of precipitation hindcasts generated by the European Centre for Medium Range Forecasting (ECMWF) system. Our findings indicate that persistent drought is projected to become more frequent over the 21st century in southern Africa, where the majority of elephants reside. Analysis of seasonal hindcasts indicates that, while the forecasts have greater skill than climatology, they remain highly uncertain. Previous work suggests that it may be possible to reduce this uncertainty by contextualizing forecasts within specific climate regimes. However,even with improved forecast skill, effective action hinges on the alignment of forecasts with the practical needs of conservation practitioners. Over the next decades, a co-production approach will be critical for leveraging seasonal forecasts for climate change adaptation within the conservation sector

The impact of air-sea coupling and ocean biases on the seasonal cycle of southern West African precipitation

The biannual seasonal rainfall regime over the southern part of West Africa is characterised by two wet seasons, separated by the `Little Dry Season' in July-August. Lower rainfall totals during this intervening dry season may be detrimental for crop yields over a region with a dense population that depends on agricultural output. Coupled Model Intercomparison Project Phase 5 (CMIP5) models do not correctly capture this seasonal regime, and instead generate a single wet season, peaking at the observed timing of the Little Dry Season. Hence, the realism of future climate projections over this region is questionable. Here, the representation of the Little Dry Season in coupled model simulations is investigated, to elucidate factors leading to this misrepresentation. The Global Ocean Mixed Layer configuration of the Met Office Unified Model is particularly useful for exploring this misrepresentation, as it enables separating the effects of coupled model ocean biases in different ocean basins while maintaining air-sea coupling. Atlantic Ocean SST biases cause the incorrect seasonal regime over southern West Africa.Upper level descent in August reduces ascent along the coastline, which is associated with the observed reduction in rainfall during the Little Dry Season. When coupled model Atlantic Ocean biases are introduced, ascent over the coastline is deeper and rainfall totals are higher during July-August. Hence, this study indicates detrimental impacts introduced by Atlantic Ocean biases, and highlights an area of model development required for production of meaningful climate change projections over the West Africa region