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A Characterization of the Variation in Relative Humidity across West Africa during the Dry Season
Abstract
The variation of relative humidity across West Africa during the dry season is evaluated using the Modern Era Retrospective Analysis for Research and Applications (MERRA) dataset and the method of self-organizing maps. Interest in the dry season of West Africa is related to the connection between near-surface atmospheric moisture and the occurrence of meningitis across West Africa, most notably in the region known as the meningitis belt. The patterns in relative humidity are analyzed in terms of frequency of each pattern as well as the sequencing from one pattern to the next. The variations in relative humidity are characterized subannually for individual years from 1979 to 2009 as well as decadally over the entire 30-yr duration of dry seasons in West Africa. The progression from relatively moist patterns to relatively dry patterns and back to the moist patterns over the course of the dry season corresponds to the northward and then southward migration of the intertropical convergence zone. The results indicate distinctly different frequency and sequencing of relative humidity patterns from year to year. The year-to-year changes in relative humidity patterns are gradual. There is some indication of a larger, possibly decadal, pattern to the year-to-year changes in the variation of relative humidity over the course of the dry season. The results are reflective of the reanalysis data including potentially unusual and erroneously dry conditions in central Africa after the mid-1990s.
... Attempts to aid mitigation efforts for the climate-sensitive epidemics also motivated few studies over West Africa during the boreal spring season (e.g. Seefeldt et al., 2012;Mera et al., 2014). Both studies recognize the critical role of high humidity, resulting from moisture influx, in ending meningitis epidemic outbreaks. ...
... These make the outputs from SOM to be less dependent on a specific data distribution. In view of these, several studies, such as Hewitson and Crane (2002), Reusch et al. (2005 and, Seefeldt et al. (2012), etc. have used SOM algorithm to extract spatial classes and or patterns from climatological datasets and they got robust results. ...
... The recorded ambient humidity values for the dry season (range 15.0 to 90.0%; mean 69.9%; mode 78.0%) were lower compared to those of the rainy season (range 35.0 to 97.0%; mean 76.6%; mode 87.0%). The dry season is characterized by prevailing north-easterly winds [21], including a period of "harmattan" from December to March bringing dry and dusty conditions across West Africa, therefore, there is a wider temperature range during the day (lower at night, higher during the day time) and lower humidity [22]. This is unlike winter seasons in which lower humidity values are accompanied by lower temperature values [22]. ...
Air pollution is a concern in the West Africa region where it is known that meteorological parameters such as ambient temperature and humidity can affect the particulate matter loading through atmospheric convection and dry deposition. In this study, we extend the investigation of these relationships to particulate matter less than 1 µm in diameter (PM1), nitrogen dioxide (NO2), nitrogen monoxide (NO) and ozone (O3), for a complete period of rainy and dry seasons in Lagos. Regression analysis of the results indicate that there is a negligible to weak correlation (r < 0.39) between the temperature, humidity and air pollutants during the year, except for NO2 and O3 which respond moderately to humidity during the dry season, an observation previously unreported. The mean monthly values for all the air pollutants are lower during the rainy season compared to the dry season, indicating a potential higher contribution of the transport of pollutants from the north-eastern desert regions and the reduction of the wet removal of particles during the dry season. The World Health Organization air quality guidelines are mostly exceeded for fine particles with diameters less than 2.5 µm (PM2.5), supporting previous studies, as well as for the NO2 concentration levels. As PM2.5 contributes to at least 70% of the particulate matter pollution throughout the year, policy guidelines could be enacted for people with chronic respiratory issues during the January/February months of intense high air pollution, high temperature but low humidity values.
... From a macroecological perspective, climate-richness models based on water-energy dynamics 4 have also displayed solid predictive ability to forecast responses to climate change (e.g., woody plants 5 ). These models are built with environmental variables such as temperature and specific humidity, which are also physiologically meaningful [6][7][8][9][10][11][12] in different parts of the globe [13][14][15] . The advent of GIS and the increased availability of global environmental data in recent years have favoured the proliferation of diverse kinds of SDMs intended to answer a wide range of applied ecological questions 2 (e.g., discovering biodiversity, conservation planning, health security, invasion ecology). ...
Species Distribution Models (SDMs) combine information on the geographic occurrence of species with environmental layers to estimate distributional ranges and have been extensively implemented to answer a wide array of applied ecological questions. Unfortunately, most global datasets available to parameterize SDMs consist of spatially interpolated climate surfaces obtained from ground weather station data and have omitted the Antarctic continent, a landmass covering c. 20% of the Southern Hemisphere and increasingly showing biological effects of global change. Here we introduce MERRAclim, a global set of satellite-based bioclimatic variables including Antarctica for the first time. MERRAclim consists of three datasets of 19 bioclimatic variables that have been built for each of the last three decades (1980s, 1990s and 2000s) using hourly data of 2 m temperature and specific humidity. We provide MERRAclim at three spatial resolutions (10 arc-minutes, 5 arc-minutes and 2.5 arc-minutes). These reanalysed data are comparable to widely used datasets based on ground station interpolations, but allow extending their geographical reach and SDM building in previously uncovered regions of the globe.
... As with temperature, this has evolved over time to encompass an assessment of climate variability across more remote locations (Cohen et al., 2013) and more data sources, such as radar-estimated rainfall (Rudolph et al., 2011) and satellite-estimated rainfall (Tubi and Dayan, 2014). Research has focused on systems on various scales, from the West African monsoon (Seefeldt et al., 2012) to sea breeze-generated convection in Java (Qian et al., 2010). Given their significant impact, extreme and unusual events have been frequently assessed using the synoptic methodology, such as floods (Collins et al., 2014;Kahana et al., 2002), heavy snowfall (Esteban et al., 2005), drought (Hryciw et al., 2013), and freezing rain (Cheng et al., 2004). ...
... As with temperature, this has evolved over time to encompass an assessment of climate variability across more remote locations (Cohen et al., 2013) and more data sources, such as radar-estimated rainfall (Rudolph et al., 2011) and satellite-estimated rainfall (Tubi and Dayan, 2014). Research has focused on systems on various scales, from the West African monsoon (Seefeldt et al., 2012) to sea breeze-generated convection in Java (Qian et al., 2010). Given their significant impact, extreme and unusual events have been frequently assessed using the synoptic methodology, such as floods (Collins et al., 2014;Kahana et al., 2002), heavy snowfall (Esteban et al., 2005), drought (Hryciw et al., 2013), and freezing rain (Cheng et al., 2004). ...
Synoptic climatology incorporates the assessment of the range of atmospheric conditions that exist over a given location or region. Within the discipline, this assessment is usually done via a classification of patterns into discrete categories. Many different, diverse methods are used to accomplish this classification, involving a host of different decisions that need to be made. Synoptic climatological assessments have spanned a diverse array of applications, from climate change and variability to air quality and biometeorology.
... Temperature reaches its lowest values in December/January and steadily increases until April, while relative humidity stays below 40% during the dry season with values decreasing as temperature increases, reaching a minimum of around 20% at the end of March. Humidity exhibits strong yearto-year variability during the transition from the dry to the wet season and year-to-year changes have been shown to be gradual (Seefeldt et al. 2012). ...
Meningococcal meningitis is a climate sensitive infectious disease. The regional extent of the Meningitis Belt in Africa, where the majority of epidemics occur, was originally defined by Lapeysonnie in the 1960s. A combination of climatic and environmental conditions and biological and social factors have been associated to the spatial and temporal patterns of epidemics observed since the disease first emerged in West Africa over a century ago. However, there is still a lack of knowledge and data that would allow disentangling the relative effects of the diverse risk factors upon epidemics. The Meningitis Environmental Risk Information Technologies Initiative (MERIT), a collaborative research-to-practice consortium, seeks to inform national and regional prevention and control strategies across the African Meningitis Belt through the provision of new data and tools that better determine risk factors. In particular MERIT seeks to consolidate a body of knowledge that provides evidence of the contribution of climatic and environmental factors to seasonal and year-to-year variations in meningococcal meningitis incidence at both district and national scales. Here we review recent research and practice seeking to provide useful information for the epidemic response strategy of National Ministries of Health in the Meningitis Belt of Africa. In particular the research and derived tools described in this paper have focused at “getting science into policy and practice” by engaging with practitioner communities under the umbrella of MERIT to ensure the relevance of their work to operational decision-making. We limit our focus to that of reactive vaccination for meningococcal meningitis. Important but external to our discussion is the development and implementation of the new conjugate vaccine, which specifically targets meningococcus A.
... There, the increase in monthly cases in meningitis occur during the dry season and falls with the onset of the Monsoon. The University Corporation for Atmospheric Research evokes the hypothesis of a threshold in relative humidity of 40% (Seefeldt et al., 2012) above which there is no case in meningitis anymore. Our results confirm this interpretation even though we did not analyse the relative humidity but the PW parameter that does not depend on temperature. ...
Recently, mineral dust has been suspected to be one of the important environmental risk factor for meningitis epidemics in West Africa. The current study is one of the first which relies on long-term robust aerosol measurements in the Sahel region to investigate the possible impact of mineral dust on meningitis cases (incidence). Sunphotometer measurements, which allow to derive aerosol and humidity parameters, i.e., aerosol optical thickness, Angström coefficient, and precipitable water, are combined with quantitative epidemiological data in Niger and Mali over the 2004–2009 AMMA (African Monsoon Multidisciplinary Analysis) program period. We analyse how the extremely high aerosol loads in this region may influence both the calendar (onset, peaks, end) and the intensity of meningitis. We highlight three distinct periods: (i) from November to December, beginning of the dry season, humidity is weak, there is no dust and no meningitis cases; (ii) from January to April, humidity is still weak, but high dust loads occur in the atmosphere and this is the meningitis season; (iii) from May to October, humidity is high and there is no meningitis anymore, in presence of dust or not, which flow anyway in higher altitudes. More specifically, the onset of the meningitis season is tightly related to mineral dust flowing close to the surface at the very beginning of the year. During the dry, and the most dusty season period, from February to April, each meningitis peak is preceded by a dust peak, with a 0–2 week lead-time. The importance (duration, intensity) of these meningitis peaks seems to be related to that of dust, suggesting that a cumulative effect in dust events may be important for the meningitis incidence. This is not the case for humidity, confirming the special contribution of dust at this period of the year. The end of the meningitis season, in May, coincides with a change in humidity conditions related to the West African Monsoon. These results, which are interpreted in the context of recent independent epidemiological studies on meningitis highlight, (i) the particular role of dust during the dry season (low humidity conditions) on the onset and the intra-seasonal variability of the meningitis season; (ii) the specific role of high humidity at the end of the meningitis season in two Sahelian countries particularly affected by the disease.
Background
Diarrhea remains one of the biggest public health threats in Ghana, and is the most common cause of morbidity and mortality among children in sub-Saharan Africa. Several preventive and adaptive public health measures, such as pneumococcal vaccination, Rota Virus vaccination, and improving access to potable water, are being implemented. Research exploring the climate resilience of preventive and adaptive measures in Ghana is sparse. This study aimed to determine whether preventative and adaptive interventions are climate resilient using morbidity data.
Methods
This study employs time series data of monthly all-cause diarrhea morbidity, rainfall, temperature, and relative humidity, spanning the period from January 2014 to December 2020. This study used the Auto Regression Distributed Lag cointegration approach to model the impact of climatic variables on all-cause Diarrheal Morbidity.
Results
The findings of the analysis demonstrate that public health prevention and adaptation strategies are climate-robust and unresponsive to changes in climatic variables. The residuals in the estimated models are white noise and do not exhibit serial autocorrelation or conditional heteroscedasticity.
Conclusion
In the Tamale Metropolitan Area, climate change does not affect diarrhea morbidity, supporting the claim that climate resilience is an important component of public health preventive interventions against diarrhea
This study examines the relationship between Meningitis and weather parameters (air temperature, maximum temperature, relative humidity, and rainfall) in Kaduna state, Nigeria on a weekly basis from 2007–2019. Meningitis data was acquired weekly from Nigeria Centre for Disease Control (NCDC), Bureau of Statistics and weather parameters were sourced from daily satellite data set National Oceanic and Atmospheric Administration (NOAA), International Research Institute for Climate and Society (IRI). The daily data were aggregated weekly to suit the study. The data were analysed using linear trend and Pearson correlation for relationship. The linear trend results revealed a weekly decline in Cerebro Spinal Meningitis (CSM), wind speed, maximum and air temperature and an increase in relative humidity and rainfall. Generally, results reveal that the most important explanatory weather variables influencing CSM amongst the five (5) are the weekly maximum temperature and air temperature with a positive correlation of 0.768 and 0.773. This study recommends that keen interest be placed on temperature as they play an essential role in the transmission of this disease and most times aggravate the patients' condition.
Degradation processes reduce the service life of concrete structures, resulting in social, environmental and economic damage. Many of these processes are closely related to the climate variables of the external environment. Oftentimes, investments for repair and maintenance is required when the durability of a concrete structure is compromised, resulting in high costs for a country's economy. The main climate variables that interfere with the concrete degradation mechanisms are: temperature, relative humidity, precipitation, wind, waves and tides. The knowledge about the performance of the environmental variables in the degradation mechanisms needs constant updating, mainly due to climatic changes. Climate changes are any changes in weather over time that remain for a long time. This issue has become of great concern in practically all sectors of society, since the consequences of climate changes are already present on the planet Earth. This chapter discusses some effects of climatic variables on concrete durability. Some scenarios of climate change are also discussed. An example of a numerical application about the corrosion of reinforcements on the Brazilian coast is applied. This chapter shows that, mainly in the long term, climate change can contribute to reducing the service life of concrete structures.
Spatial and temporal variability of relative humidity over the Western African Monsoon (WAM) region is investigated. In particular, the variability during the onset and retreat periods of the monsoon is considered. A K-means cluster analysis was performed to identify spatially coherent regions of relative humidity variability during the two periods. The cluster average of the relative humidity provides a robust representative index of the strength and timing of the transition periods between the dry and wet periods. Correlating the cluster indices with large-scale circulation and sea surface temperatures indicate that the land-ocean temperature gradient and the corresponding circulation, tropical Atlantic sea surface temperatures (SSTs), and to a somewhat lesser extent SSTs over the tropical Pacific, all play a role in modulating the timing of the monsoon season relative humidity onset and retreat. These connections to large-scale climate features were also found to be persistent over interseasonal time scales and thus best linear predictive models were developed to enable skillful forecasts of relative humidity during the two periods at 15-75 day lead times. The public health risk due to meningitis epidemics are of grave concern to the population in this region, and these risks are strongly tied to regional humidity levels. Because of this linkage, the understanding and predictability of relative humidity variability is of use in meningitis epidemic risk mitigation, which motivated this research.
Self-organizing maps (SOMs) are a relative newcomer to synoptic climatology; the method itself has only been utilized in the field for around a decade. In this article, we review the major developments and climatological applications of SOMs in the literature. The SOM can be used in synoptic climatological analysis in a manner similar to most other clustering methods. However, as the results from a SOM are generally represented by a two-dimensional array of cluster types that 'self-organize', the synoptic categories in the array effectively represent a continuum of synoptic categorizations, compared with discrete realizations produced through most traditional methods. Thus, a larger number of patterns can be more readily understood, and patterns, as well as transitional nodes between patterns, can be discerned. Perhaps the most intriguing development with SOMs has been the new avenues of visualization; the resultant spatial patterns of any variable can be more readily understood when displayed in a SOM. This improved visualization has led to SOMs becoming an increasingly popular tool in various research with climatological applications from other disciplines as well.
Precipitation during the boreal winter dry season in tropical West
Africa is rare but occasionally connected to high-impacts for the local
population. The dynamics and predictability of this phenomenon have been
studied very little. Here a statistical evaluation of the climatology,
dynamics, and predictions of dry-season wet events is presented for the
region 7.5-15°N, 10°W-10°E. The analysis is based upon GPCP
merged satellite-gauge pentad rainfall estimates and five-day ERA-40
precipitation forecast, and covers the 23 dry seasons
(November-February) 1979/80-2001/02. Wet events are defined as pentads
with an area-averaged precipitation anomaly of more than +200% with
respect to the mean seasonal cycle. Composites of the 43 identified
events indicate an association with a trough over northwestern Africa, a
tropical plume on its eastern side, unusual precipitation at the
northern and western fringes of the Sahara, and reduced surface pressure
over the Sahara, which allows an inflow of moist southerlies from the
Gulf of Guinea to feed the unusual dry-season rainfalls. The results
give evidence for a pre-conditioning by another disturbance about one
week prior to the precipitation event. The ERA-40 forecasts show a
high temporal correlation with observations, a general wet bias, but a
somewhat too low number of wet events. With 53% of all identified events
correctly forecasted and only 32% of forecasted events not verified the
model shows a moderate skill in contrast to the prediction of many other
tropical precipitation systems. A separate consideration of hits,
misses, and false alarms corroborates the previously proposed hypothesis
that a strong extratropical influence enhances the quality of
predictions in this region. The results should encourage weather
services in West Africa to take advantage of available dry-season
precipitation forecasts in terms of the dissemination of early warnings.
In January 2002 the Cape Verde region in tropical West Africa was hit by an exceptionally heavy precipitation event. Rain rates of up to 116 mm (48 h)-1 caused harmful impacts on the local population. The rainfall was triggered by a series of two upper-level disturbances penetrating from the extratropics to the West African coast. This study investigates the dynamics and predictability of this event on the basis of simulations with the global model Global Model Europe (GME) of the German Weather Service [i.e., Deutscher Wetterdienst (DWD)] initialized by the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis data. Free forecasts satisfactorily reproduce the upper-level disturbances and the precipitation up to a lead time of 7 days. Several sensitivity experiments are conducted to unveil the reasons for this comparably high predictability and to identify dynamical precursors. The relevance of the upper-level wave structure in the extratropics is examined by modifications of the initial conditions using a quasigeostrophic potential vorticity (PV) inversion technique. While a reservoir of high PV over the North Atlantic and a PV ridge over Europe are found to be crucial for the upper-level wave amplification and the rainfall over West Africa, latent heating over the North Atlantic affects the event rather little in contrast to previous case studies. Surface properties like orography and sea surface temperature anomalies modify the precipitation quantity, but appear not to be essential for the occurrence of the extreme event on the simulated time scale.
Self organizing maps (SOMs) are used to locate archetypal points that describe the multi-dimensional distribution function of a gridded sea level pressure data set for the northeast United States. These points-nodes on the SOM-identify the primary features of the synoptic-scale circulation over the region. In effect, the nodes represent a non-linear distribution of overlapping, non-discreet, circulation types. The circulation patterns are readily visualized in a 2-dimensional array (the SOM) that places similar types adjacent to one another and very different types far apart in the SOM space. The SOM is used to describe synoptic circulation changes over time, and to relate the circulation to January station precipitation data (for State College, Pennsylvania) in the center of the domain. The paper focuses on the methodology; however, the analysis suggests that circulation systems that promote precipitation have decreased over the last 40 yr-although January precipitation at State College has actually increased. Further analysis with the SOM indicates that this is due to a change in precipitation characteristics of the synoptic-scale circulation features, rather than to their frequency of occurrence.
As a contribution toward improving our ability to identify robust patterns of variability in complex, noisy climate datasets, we have compared a relatively new technique, Self-Organizing Maps (SOMs), to the well-established method of principal component analysis (PCA). Recent results suggest that SOMs offer advantages over PCA for use in climatological and other studies. Here each analysis technique was applied to synthetic datasets composed of positive and negative modes of four idealized North Atlantic sea-level-pressure fields, with and without noise components, to identify the predefined patterns of variability. PCA, even with component rotation, fails to adequately extract the known spatial patterns, mixes patterns into single components, and incorrectly partitions the variance among the components. The SOMs-based analyses are more robust and, with a sufficiently large set of generalized patterns, are able to isolate all the predefined patterns with correct attribution of variance. With PCA, it is difficult, if not impossible, to detect pattern mixing without prior knowledge of the patterns being mixed.
Bacterial (meningococcal) meningitis is a devastating infectious disease with outbreaks occurring annually during the dry season in locations within the ‘Meningitis Belt’, a region in sub-Saharan Africa stretching from Ethiopia to Senegal. Meningococcal meningitis occurs from December to May in the Sahel with large epidemics every 5–10 years and attack rates of up to 1000 infections per 100,000 people. High temperatures coupled with low humidity may favor the conversion of carriage to disease as the meningococcal bacteria in the nose and throat are better able to cross the mucosal membranes into the blood stream. Similarly, respiratory diseases such as influenza and pneumonia might weaken the immune defenses and add to the mucosa damage. Although the transmission dynamics are poorly understood, outbreaks regularly end with the onset of the rainy season and may begin anew with the following dry season. In this paper, we employ a generalized additive modeling approach to assess the association between number of reported meningitis cases and a set of weather variables (relative humidity, rain, wind, sunshine, maximum and minimum temperature). The association is adjusted for air quality (dust, carbon monoxide), as well as varying degrees of unobserved time-varying confounding processes that co-vary with both the disease incidence and weather. We present the analysis of monthly reported meningitis counts in Navrongo, Ghana, from 1998–2008.
African Monsoon Multidisciplinary Analysis (AMMA) is an international project to improve our knowledge and understanding of the West African monsoon (WAM) and its variability with an emphasis on daily-to-interannual time scales. AMMA is motivated by an interest in fundamental scientific issues and by the societal need for improved prediction of the WAM and its impacts on West African nations. Recognizing the societal need to develop strategies that reduce the socioeconomic impacts of the variability of the WAM, AMMA will facilitate the multidisciplinary research required to provide improved predictions of the WAM and its impacts. This will be achieved and coordinated through the following five international working groups: i) West African monsoon and global climate, ii) water cycle, iii) surface-atmosphere feedbacks, iv) prediction of climate impacts, and v) high-impact weather prediction and predictability. AMMA promotes the international coordination of ongoing activities, basic research, and a multiyear field campaign over West Africa and the tropical Atlantic. AMMA is developing close partnerships between those involved in basic research of the WAM, operational forecasting, and decision making, and is establishing blended training and education activities for Africans.
The diurnal cycle of the Intertropical discontinuity (ITD), i.e. the interface at the ground between moist monsoon air and dry Harmattan air, is an important factor in the West African monsoon system. During the whole of 2006, high-resolution ground-based remote-sensing measurements were performed in the area of Djougou, Benin, which made it possible to observe the ITD and the associated sharp gradient of temperature and humidity in detail. In order to extend the point measurements to a three-dimensional view of the ITD and to enhance the knowledge of the related processes, the mesoscale atmospheric model Meso-NH was run for a case study (84 h period) in April 2006. In addition Meteosat infrared observations were used to determine the ITD position and its movement. From these observations a northward propagation of the moist air front (ITD) of 8–12 m s−1 was calculated. The propagation speed of the front evaluated from the satellite observations was replicated by the model and the time of the front arrival over Djougou was simulated with a maximum error of 1 hour. With respect to the ground-based observations, the model was able to reproduce the dynamics and thermodynamics of the front as well as the diurnal cycle of the planetary boundary layer over the study area. This agreement suggests the use of the model to further describe processes in the lower atmosphere at high resolution. Copyright © 2009 Royal Meteorological Society
Epidemics of meningococcal meningitis occur in areas with particular environmental characteristics. We present evidence that the relationship between the environment and the location of these epidemics is quantifiable and propose a model based on environmental variables to identify regions at risk for meningitis epidemics. These findings, which have substantial implications for directing surveillance activities and health policy, provide a basis for monitoring the impact of climate variability and environmental change on epidemic occurrence in Africa.
Every year West African countries within the Sahelo-Sudanian band are afflicted with major meningococcal meningitis (MCM) disease outbreaks, which affect up to 200,000 people, mainly young children, in one of the world's poorest regions. The timing of the epidemic year, which starts in February and ends in late May, and the spatial distribution of disease cases throughout the "Meningitis Belt" strongly indicate a close linkage between the life cycle of the causative agent of MCM and climate variability. However, mechanisms responsible for the observed patterns are still not clearly identified.
By comparing the information on cases and deaths of MCM from World Health Organization weekly reports with atmospheric datasets, we quantified the relationship between the seasonal occurrence of MCM in Mali, a West African country, and large-scale atmospheric circulation. Regional atmospheric indexes based on surface wind speed show a clear link between population dynamics of the disease and climate: the onset of epidemics and the winter maximum defined by the atmospheric index share the same mean week (sixth week of the year; standard deviation, 2 wk) and are highly correlated.
This study is the first that provides a clear, quantitative demonstration of the connections that exist between MCM epidemics and regional climate variability in Africa. Moreover, this statistically robust explanation of the MCM dynamics enables the development of an Early Warning Index for meningitis epidemic onset in West Africa. The development of such an index will undoubtedly help nationwide and international public health institutions and policy makers to better control MCM disease within the so-called westward-eastward pan-African Meningitis Belt.
Every year, West Africa is afflicted with Meningococcal Meningitis (MCM) disease outbreaks. Although the seasonal and spatial patterns of disease cases have been shown to be linked to climate, the mechanisms responsible for these patterns are still not well identified.
A statistical analysis of annual incidence of MCM and climatic variables has been performed to highlight the relationships between climate and MCM for two highly afflicted countries: Niger and Burkina Faso. We found that disease resurgence in Niger and in Burkina Faso is likely to be partly controlled by the winter climate through enhanced Harmattan winds. Statistical models based only on climate indexes work well in Niger showing that 25% of the disease variance from year-to-year in this country can be explained by the winter climate but fail to represent accurately the disease dynamics in Burkina Faso.
This study is an exploratory attempt to predict meningitis incidence by using only climate information. Although it points out significant statistical results it also stresses the difficulty of relating climate to interannual variability in meningitis outbreaks.
: The Self-Organizing Map (SOM) represents the result of a vector quantization algorithm that places a number of reference or codebook vectors into a high-dimensional input data space to approximate to its data sets in an ordered fashion. The SOM PAK program package contains all programs necessary for the correct application of the SelfOrganizing Map algorithm in the visualization of complex experimental data. The first version 1.0 of this program package was published in 1992 and since then the package has been updated regularly to include latest improvements in the SOM implementations. This report that contains the last documentation was prepared for bibliographical purposes. 1 Contents 1 General 3 2 The principle of the SOM 4 3 Practical advices for the construction of good maps 6 4 Installation of the program package 7 4.1 Getting the program code : : : : : : : : : : : : : : : : : : : : : : : : 8 4.2 Installation in UNIX : : : : : : : : : : : : : : : : : : : : : : : : :...
The arrival of the summer monsoon over West Africa has been documented
by using daily gridded rainfall data and NCEP-NCAR reanalyses during the
period 1968-90, and OLR data over the period 1979-90. Two steps have
been characterized through a composite approach: the preonset and the
onset of the summer monsoon.The preonset stage corresponds to the
arrival in the intertropical front (ITF) at 15°N, that is, the
confluence line between moist southwesterly monsoon winds and dry
northeasterly Harmattan, bringing sufficient moisture for isolated
convective systems to develop in the Sudano-Sahelian zone while the
intertropical convergence zone (ITCZ) is centered at 5°N. The mean
date for the preonset occurrence is 14 May and its standard deviation is
9.5 days during the period 1968-90. This leads to a first clear increase
of the positive rainfall slope corresponding to the beginning of the
rainy season over this Sudano-Sahelian area.The onset stage of the
summer monsoon over West Africa is linked to an abrupt latitudinal shift
of the ITCZ from a quasi-stationary location at 5°N in May-June to
another quasi-stationary location at 10°N in July-August. The mean
date for the onset occurrence is 24 June and its standard deviation is 8
days during the period 1968-90. This leads to a second increase of the
positive rainfall slope over the Sudano-Sahelian zone signing the
northernmost location of the ITCZ and the beginning of the monsoon
season. This abrupt shift occurs mostly between 10°W and 5°E,
where a meridional land-sea contrast exists, and it is characterized by
a temporary rainfall and convection decrease over West Africa. Preonset
dates, onset dates, and summer rainfall amount over the Sahel are
uncorrelated during the period 1968-90.The atmospheric dynamics
associated with the abrupt ITCZ shift has been investigated. Between the
preonset and the onset stages, the heat low dynamics associated with the
ITF controls the circulation in the low and midlevels. Its meridional
circulation intensity is the highest at the beginning of the monsoon
onset. This can lead to 1) increased convective inhibition in the ITCZ
through intrusion of dry and subsiding air from the north, and 2)
increased potential instability through a greater inland moisture
advection and a higher monsoon depth induced by a stronger cyclonic
circulation in the low levels, through higher vertical wind shear due to
westerly monsoon wind and midlevel African easterly jet (AEJ) increases,
through enhancement of the instability character of the AEJ, and through
increased shortwave radiation received at the surface. During the
monsoon onset, once the rainfall minimum occurred due to the convective
inhibition, the accumulated potential instability breaks the convective
inhibition, the inertial instability of the monsoon circulation is
released, and the associated regional-scale circulation increases,
leading to the abrupt shift of the ITCZ. Then the ITCZ moves north up to
10°N, where thermodynamical conditions are favorable.It is suggested
by the authors that the abrupt shift of the ITCZ, initiated by the
amplification of the heat low dynamics, could be due to an interaction
with the northern orography of the Atlas-Ahaggar Mountains. Subsidence
over and north of this orography, due to both the northern branches of
the heat low and of the northern Hadley-type cell, contributes to
enhance the high geopotentials north of these mountains and the
associated northeasterly winds. This leads to the development of a
leeward trough that reinforces the heat low dynamics, maintaining an
active convective ITCZ through enhanced moist air advection from the
ocean, increasing the northern Hadley circulation, which reinforces the
high geopotentials and the interaction with the orography through a
positive feedback. The fact that an abrupt shift of the ITCZ is only
observed on the western part of West Africa may result from the
enhancement of moisture advection, which comes from the west and has a
stronger impact west of the Greenwich meridian.The northwest-southeast
orientation of the Atlas-Ahaggar crest can induce the interaction with
the heat low, first in the east where the mountains are nearer to the
ITF than in the west, and second in the west. Another consequence of the
possible orography-induced interaction with the atmospheric circulation
is that the induced leeward trough, increasing the cyclonic vorticity in
the heat low, may stimulate moisture convergence in the oceanic ITCZ
near the western coast of West Africa.
Reanalyses, retrospectively analyzing observations over climatological time scales, represent a merger between satellite observations and models to provide globally continuous data and have improved over several generations. Balancing the earth’s global water and energy budgets has been a focus of research for more than two decades. Models tend to their own climate while remotely sensed observations have had varying degrees of uncertainty. This study evaluates the latest NASA reanalysis, the Modern Era Retrospective-Analysis for Research and Applications (MERRA), from a global water and energy cycles perspective, to place it in context of previous work and demonstrate the strengths and weaknesses.
MERRA was configured to provide complete budgets in its output diagnostics, including the incremental analysis update (IAU), the term that represents the observations influence on the analyzed states, alongside the physical flux terms. Precipitation in reanalyses is typically sensitive to the observational analysis. For MERRA, the global mean precipitation bias and spatial variability are more comparable to merged satellite observations [the Global Precipitation and Climatology Project (GPCP) and Climate Prediction Center Merged Analysis of Precipitation (CMAP)] than previous generations of reanalyses. MERRA ocean evaporation also has a much lower value, which is comparable to independently derived estimate datasets. The global energy budget shows that MERRA cloud effects may be generally weak, leading to excess shortwave radiation reaching the ocean surface.
Evaluating the MERRA time series of budget terms, a significant change occurs that does not appear to be represented in observations. In 1999, the global analysis increments of water vapor changes sign from negative to positive and primarily lead to more oceanic precipitation. This change is coincident with the beginning of Advanced Microwave Sounding Unit (AMSU) radiance assimilation. Previous and current reanalyses all exhibit some sensitivity to perturbations in the observation record, and this remains a significant research topic for reanalysis development. The effect of the changing observing system is evaluated for MERRA water and energy budget terms.
The Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA’s Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA’s Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses. Focusing on the satellite era, from 1979 to the present, MERRA has achieved its goals with significant improvements in precipitation and water vapor climatology. Here, a brief overview of the system and some aspects of its performance, including quality assessment diagnostics from innovation and residual statistics, is given.
By comparing MERRA with other updated reanalyses [the interim version of the next ECMWF Re-Analysis (ERA-Interim) and the Climate Forecast System Reanalysis (CFSR)], advances made in this new generation of reanalyses, as well as remaining deficiencies, are identified. Although there is little difference between the new reanalyses in many aspects of climate variability, substantial differences remain in poorly constrained quantities such as precipitation and surface fluxes. These differences, due to variations both in the models and in the analysis techniques, are an important measure of the uncertainty in reanalysis products. It is also found that all reanalyses are still quite sensitive to observing system changes. Dealing with this sensitivity remains the most pressing challenge for the next generation of reanalyses.
Production has now caught up to the current period and MERRA is being continued as a near-real-time climate analysis. The output is available online through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC).
This paper examines the mean annual cycle of rainfall and general circulation features over West Africa and central Africa for 1958–97. Rainfall is examined using a 1400-station archive compiled by the first author. Other circulation features are examined using the NCEP–NCAR reanalysis dataset. Important features of the reanalysis zonal wind field are shown to compare well with the seasonal evolution described by the radiosonde observations.
In addition to the well-known African easterly jet (AEJ) of the Northern Hemisphere, the seasonal evolution of its Southern Hemisphere counterpart is also described. Thermal wind calculations show that although the southern jet is weaker, its existence is also due to a local reversal of the surface temperature gradient. In the upper troposphere, a strong semiannual cycle is shown in the 200-mb easterlies and a feature like the tropical easterly jet (TEJ) is evident south of the equator in January and February. The paper describes the movement of the rainbelt between central and West Africa. An asymmetry in the northward and southward migration of the rainbelt is evident.
The paper discusses the influence that the jets may have on rainfall and possible feedback effects of rainfall on the jets. Evidence suggests that the midtropospheric jets influence the development of the rainy season, but also that the rainfall affects the surface temperature gradient and in turn the jets. In the Northern Hemisphere, east of 20°E, the axis of the TEJ is located so that it may promote convection by increasing upper-level divergence. However, west of 10°E and in the Southern Hemisphere, the location of the TEJ is consistent with the suggestion that it is the equatorward outflow of convection that produces the TEJ.
Precipitation is a major socioeconomic factor in the Guineo-Soudanian zone of tropical West Africa with its distinct summer rainy season from May to October. Albeit rare, precipitation during the dry season can have substantial impacts on the local hydrology and human activities reaching from the rotting of harvests to improved grazing conditions. This study provides an observationally based synoptic and dynamical analysis of an abundant rainfall event during the dry season of 2003/04 that affected the countries of Nigeria, Benin, Togo, and Ghana. The results point to a forcing of the rainfalls from the extratropics in the following ways: 1) Upper-level clouds and moisture to the east of a weak, quasi-stationary extratropical disturbance enhance the greenhouse effect over the Sahel and the adjacent Sahara, and thereby cause a net-column warm anomaly and falling surface pressure. 2) One day before the precipitation event, negative pressure tendencies are further enhanced through warm advection and subsidence associated with the penetration of a more intense upper-trough into Algeria. 3) The resulting northward shift and intensification of the weak wintertime heat low allows low-level moist southerlies from the Gulf of Guinea to penetrate into the Soudanian zone. 4) Finally, daytime heating of the land surface and convective dynamics initiate heavy rainfalls. Operational forecasts of this event were promising, pointing to a strong control by the compara- tively well-predicted extratropical upper-level circulation.
An analysis of late twentieth and twenty-first century predictions of Arctic circulation patterns in a ten-model ensemble of global climate system models, using the method of self-organizing maps (SOMs), is presented. The model simulations were conducted in support of the fourth assessment report of the intergovernmental panel on climate change (IPCC). The analysis demonstrates the utility of SOMs for climate analysis, both as a tool to evaluate the accuracy of climate model predictions, and to provide a useful alternative view of future climate change.
It is found that not all models accurately simulate the frequency of occurrence of Arctic circulation patterns. Some of the models tend to overpredict strong high-pressure patterns while other models overpredict the intensity of cyclonic circulation regimes. In general, the ensemble of models predicts an increase in cyclonically dominated circulation patterns during both the winter and summer seasons, with the largest changes occurring during the first half of the twenty-first century. Analysis of temperature and precipitation anomalies associated with the different circulation patterns reveals coherent patterns that are consistent with the different circulation regimes and highlight the dependence of local changes in these quantities to changes in the synoptic scale circulation patterns. Copyright
Every year, meningococcal meningitis causes thousands of deaths within the meningitis belt in sub-Saharan African countries. Large epidemic waves occur with a periodicity of 5-12 years. The waves do correspond to molecular changes in the expression of capsular or subcapsular antigens, which allow the bug to spread in susceptible populations. Serogroup A remains the major killer, even if in 2002, serogroup W135 ST-11 emerged in Burkina Faso, causing an important epidemic. However, the surveillance in the following years has showed a decrease in the W135 incidence and a clear predominance of serogroup A. Moreover, a new serogroup A strain belonging to ST-2859 seems to emerge and does represent a new threat for the coming seasons. In a vaccine perspective, and especially in the context of the development of an A conjugate vaccine; it is the key to strengthen the surveillance systems and to include molecular epidemiology as a tool for monitoring the molecular evolution of Neisseria meningitidis in Africa.
Climate and Circulation of the
- S Hastenrath
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La meningite cerebro-spinale en Afrique (Cerebrospinal meningitis in Africa). World Health Organization Bull
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Diurnal cycle of the intertropical discontinuity over West Africa analysed by remote sensing and mesoscale modeling
- B Pospichal
- D Karam
- S Crewell
- C Flamant
- A Hunderbein
- O Bock
- F Said
Pospichal, B., D. Bou Karam, S. Crewell, C. Flamant, A. Hunderbein,
O. Bock, and F. Said, 2010: Diurnal cycle of the intertropical
discontinuity over West Africa analysed by remote sensing
and mesoscale modeling. Quart. J. Roy. Meteor. Soc., 136 (S1),
92-106.