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Heat is one of the most serious hazards in the world as it affects human health and is extremely dangerous to vulnerable populations such as the elderly, people with preexisting cardiovascular or respiratory conditions, and even healthy people with prolonged sunlight exposure during heat waves. As the globe has warmed over the past several decades, extreme heat has become more frequent and intense than ever before, and Africa, especially the Sahel in West Africa, is one of the regions of the world where heat is a major public health concern exacerbated by livelihood activities during the heat season. Yet, there is a major gap in monitoring and forecasting heat waves in Africa. This paper describes NOAA's role in enabling heat–health early warning in Africa, working with meteorological services and health professionals. Emphasis is on real-time heat wave forecasting at week 2, including the postprocessing of the NCEP model outputs, and providing the information to the meteorological services in Africa to serve as guidance in national heat wave forecasts. In addition, the paper describes the end-to-end process of heat hazard outlooks and translating the forecasts into early action and early planning to reduce heat risk to human health. Furthermore, the paper addresses the very important aspect of capacity development tailored at enhancing forecasters' skills to prepare and issue heat wave forecasts and training of a cadre of health professionals to work with meteorologists to coproduce heat–health bulletins and to issue heat–health early warnings. [ABSTRACT FROM AUTHOR]

A simple—yet powerful—indicator for monitoring agricultural drought is the water requirement satisfaction index (WRSI). In data-sparse, food-insecure areas, the WRSI is used to guide billions of dollars of aid every year. The WRSI uses precipitation (PPT) and reference evapotranspiration (RefET) data to estimate water availability relative to water demand experienced over the course of a growing season. If the season is in progress, to-date conditions can be combined with climatological averages to provide insight into potential end-of-season (EOS) crop performance. However, if the average is misrepresented, these forecasts can hinder early warning and delay precious humanitarian aid. While many agencies use arithmetic average climatologies as proxies for "average conditions," little published research evaluates their effectiveness in crop-water balance models. Here, we use WRSI hindcasts of three African regions' growing seasons, from 1981 to 2019, to assess the adequacy of the arithmetic mean climatological forecast—the Extended WRSI. We find that the Extended WRSI is positively biased, overestimating the actual EOS WRSI by 2%–23% in East, West, and southern Africa. The presented alternative combines to-date conditions with data from previous seasons to produce a series of historically realistic conclusions to the current season. The mean of these scenarios is the WRSI Outlook. In comparison with the Extended WRSI, which creates a single forecast scenario using average inputs that are not covarying, the WRSI Outlook employs an ensemble of scenarios, which more adequately capture the historical distribution of distribution of rainfall events along with the covariability between climate variables. More specifically, the impact of dry spells in individual years is included in the WRSI Outlook in a way that is smoothed over in the Extended WRSI. We find that the WRSI Outlook has a near-zero bias score and generally has a lower RMSE. In total, this paper highlights the inadequacies of the arithmetic mean climatological forecast and presents a less biased and more accurate scenario-based approach. To this end, the WRSI Outlook can improve our ability to identify agricultural drought and the concomitant need for humanitarian aid. [ABSTRACT FROM AUTHOR]

The ability to predict heavy rain and floods in Africa is urgently needed to reduce the socioeconomic costs of these events and increase resilience as climate changes. Numerical weather prediction in this region is challenging, and attention is being drawn to observationally based methods of providing short-term nowcasts (up to ∼6-h lead time). In this paper a freely available nowcasting package, pySTEPS, is used to assess the potential to provide nowcasts of satellite-derived convective rain rate for West Africa. By analyzing a large number of nowcasts, we demonstrate that a simple approach of "optical flow" can have useful skill at 2-h lead time on a 10-km scale and 4-h lead time at larger scales (200 km). A diurnal variation in nowcast skill is observed, with the worst-performing nowcasts being those that are initialized at 1500 UTC. Comparison with existing nowcasts is presented. Such nowcasts, if implemented operationally, would be expected to have significant benefits. Significance Statement: A freely available, easy-to-use nowcasting package has been applied to satellite-retrieved rainfall rates for West Africa, and extrapolations have useful skill at up to 4 h of lead time. [ABSTRACT FROM AUTHOR]

Africa is poised for a revolution in the quality and relevance of weather predictions, with potential for great benefits in terms of human and economic security. This revolution will be driven by recent international progress in nowcasting, numerical weather prediction, theoretical tropical dynamics, and forecast communication, but will depend on suitable scientific investment being made. The commercial sector has recognized this opportunity and new forecast products are being made available to African stakeholders. At this time, it is vital that robust scientific methods are used to develop and evaluate the new generation of forecasts. The Global Challenges Research Fund (GCRF) African Science for Weather Information and Forecasting Techniques (SWIFT) project represents an international effort to advance scientific solutions across the fields of nowcasting, synoptic and short-range severe weather prediction, subseasonal-to-seasonal (S2S) prediction, user engagement, and forecast evaluation. This paper describes the opportunities facing African meteorology and the ways in which SWIFT is meeting those opportunities and identifying priority next steps. Delivery and maintenance of weather forecasting systems exploiting these new solutions requires a trained body of scientists with skills in research and training, modeling and operational prediction, and communications and leadership. By supporting partnerships between academia and operational agencies in four African partner countries, the SWIFT project is helping to build capacity and capability in African forecasting science. A highlight of SWIFT is the coordination of three weather forecasting "Testbeds"—the first of their kind in Africa—which have been used to bring new evaluation tools, research insights, user perspectives, and communications pathways into a semioperational forecasting environment. [ABSTRACT FROM AUTHOR]

In southern Africa, models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) predict robust future drying associated with a delayed rainy-season onset in the austral spring and a range of wetting and drying patterns in the austral summer. This paper relates these rainfall changes to dynamical shifts in two classes of weather systems: the Congo Air Boundary (CAB) and tropical lows. Objective algorithms are used to track these features in CMIP5 model output. It is then established that the climatological locations and frequencies of these systems are reasonably well represented in the CMIP5 models. RCP8.5 end-of-twenty-first-century projections are compared with historical end-of-twentieth-century simulations. Future projections in tropical-low locations and frequencies diverge, but indicate an overall average decrease of 15% and in some cases a northward shift. The projected spatial change in the tropical-low frequency distribution is weakly positively correlated to the projected spatial change in the austral summer rainfall distribution. Meanwhile, future projections indicate a 13% increase in CAB frequency from October to December. This is associated with the gradual climatological CAB breakdown occurring half a month later on average in end-of-twenty-first-century RCP8.5 projections. A delay in the gradual seasonal decline of the CAB prevents rainfall to the south of the CAB’s mean position, most of which is shown to occur on CAB breakdown days, hence creating the austral spring drying signal and delayed wet-season onset. Intermodel variability in the magnitude of CAB frequency increase is able to explain intermodel variability in the projected drying. [ABSTRACT FROM AUTHOR]

Africa is one of the three key regions of deep convection in the global tropics. There is a wealth of information on the intensity, variability, and change of convection and associated rainfall in regions across the continent but almost all of this literature is regionally focused and confined to specific seasons. This fragmented approach precludes a continent-wide view of deep convection leaving the following key issues unanswered: When is deep convection the most widespread across Africa? Where on the continent is deep convection most active? Where does widespread convection have the most interannual variability? This paper confronts these questions using a satellite-derived integral of deep convection. At the continental scale, March exhibits the most extensive deep convection whereas the West African monsoon during June-July exhibits the least. El Niño generally suppresses pan-African convective activity while La Niña enhances this activity. These pan-African signals are largely determined by regional hotspots: the eastern Congo hosts the most persistent widespread deep convection, southeastern southern Africa displays the highest interannual variability, and regional highlands maintain local convective activity hotspots. Furthermore, pan-African annual mean convective activity has increased ;10% between 1983 and 2015 with increases of .20% recorded in local hotspots. Results in this study provide a climatological baseline for both observational and model-based studies of African climates and offer insights into when African convection has the greatest potential impact on the general circulation. [ABSTRACT FROM AUTHOR]

An intense mesoscale convective system (MCS) in the Guinea Coast region caused one of the highest ever recorded daily rainfall amounts at the Nigerian station Abakaliki on 12 June 2016 (223.5 mm). This paper provides a detailed analysis of the meso- and synoptic-scale factors leading to this event, including some so far undocumented dynamical aspects for southern West Africa. The MCS formed over the Darfur Mountains due to diurnal heating, then moved southwestward along a mid- to lower-tropospheric trough, and developed into a classical West African squall line in a highly sheared environment with pronounced midlevel dryness. Strong moisture flux convergence over Nigeria prior to the MCS passage led to extreme values in precipitable water and was caused by the formation of a local, short-lived heat low. According to the pressure tendency equation, the latter resulted from tropospheric warming due to MCS-forced subsidence as well as surface insolation in the resulting almost cloud-free atmosphere. In this extremely moist environment, the MCS strongly intensified and initiated the formation of a lower-tropospheric vortex, which resulted in a deceleration of the MCS and high rainfall accumulation at Abakaliki. Following the vorticity equation, the vortex formation was realized through strong low-level vortex stretching and upper-level vertical vorticity advection related to the MCS, which became "dynamically large" compared to the Rossby radius of deformation. Eventually, moisture supply and lifting associated with the vortex are suggested to promote the longevity of the MCS during the subsequent westward movement along the Guinea Coast. [ABSTRACT FROM AUTHOR]

Forecasting convective rainfall in the tropics is a major challenge for numerical weather prediction. The use of convection-permitting (CP) forecast models in the tropics has lagged behind the midlatitudes, despite the great potential of such models in this region. In the scientific literature, there is very little evaluation of CP models in the tropics, especially over an extended time period. This paper evaluates the prediction of convective storms for a period of 2 years in the Met Office operational CP model over East Africa and the global operational forecast model. A novel localized form of the fractions skill score is introduced, which shows variation in model skill across the spatial domain. Overall, the CP model and the global model both outperform a 24-h persistence forecast. The CP model shows greater skill than the global model, in particular on subdaily time scales and for storms over land. Forecasts over Lake Victoria are also improved in the CP model, with an increase in hit rate of up to 20%. Contrary to studies in the midlatitudes, the skill of both models shows a large dependence on the time of day and comparatively little dependence on the forecast lead time within a 48-h forecast. Although these results provide more motivation for forecasters to use the CP model to produce subdaily forecasts with increased detail, there is a clear need for more in situ observations for data assimilation into the models and for verification. A move toward ensemble forecasting could have further benefits. [ABSTRACT FROM AUTHOR]

Future projections of precipitation at regional scales are vital to inform climate change adaptation activities. Therefore, is it important to quantify projected changes and associated uncertainty, and understand model processes responsible. This paper addresses these challenges for southern Africa and the adjacent Indian Ocean focusing on the local wet season. Precipitation projections for the end of the twenty-first century indicate a pronounced dipole pattern in the CMIP5 multimodel mean. The dipole indicates future wetting (drying) to the north (south) of the climatological axis of maximum rainfall, implying a northward shift of the ITCZ and south Indian Ocean convergence zone that is not consistent with a simple "wet get wetter" pattern. This pattern is most pronounced in early austral summer, suggesting a later and shorter wet season over much of southern Africa. Using a decomposition method we determine physical mechanisms underlying this dipole pattern of projected change, and the associated intermodel uncertainty. The projected dipole pattern is largely associated with the dynamical component of change indicative of shifts in the location of convection. Over the Indian Ocean, this apparent northward shift in the ITCZ may reflect the response to changes in the north-south SST gradient over the Indian Ocean, consistent with a "warmest get wetter" mechanism. Over land subtropical drying is relatively robust, particularly in the early wet season. This has contributions from dynamical shifts in the location of convection, which may be related to regional SST structures in the southern Indian Ocean, and the thermodynamic decline in relative humidity. Implications for understanding and potentially constraining uncertainty in projections are discussed. [ABSTRACT FROM AUTHOR]

Africa lags the rest of the world in climate model development. This paper explores the potential for region-specific, process-based evaluation to promote progress in modeling and confidence assessments. [ABSTRACT FROM AUTHOR]

This paper reports on the development of a new statistical tool that generates probabilistic outlooks of seasonal precipitation anomaly categories over Africa. Called the seasonal performance probability (SPP), it quantitatively evaluates the probability of precipitation to finish at predefined percent-of-normal anomaly categories corresponding to below-average (<80% of normal), average (80%-120% of normal), and above-average (>120% of normal) conditions. This is accomplished by applying methods for kernel density estimation (KDE), which compute smoothed, continuous density functions on the basis of more than 30 years of historical precipitation data from the Africa Rainfall Climatology, version 2, dataset (ARC2) for the remaining duration of a monsoon season. Discussion of various parameterizations of KDE and testing to determine optimality of density estimates (and thus performance of SPP for operational monitoring) are presented. Verification results from 2006 to 2015 show that SPP reliably provides probabilistic outcomes of seasonal rainfall anomaly categories by after the early to midstages of rain seasons for the major monsoon regions in East Africa, West Africa, and southern Africa. SPP has proven to be a useful tool by enhancing operational climate monitoring at CPC for its prognostic capability for famine early warning scenarios over Africa. These insights are anticipated to translate into better decision-making in food security, planning, and response objectives for the U.S. Agency for International Development/Famine Early Warning Systems Network (USAID/FEWS NET). [ABSTRACT FROM AUTHOR]

This paper extends the work of Dinku and Anagnostou overland rain retrieval algorithm for use with Special Sensor Microwave Imager (SSM/I) observations. In Dinku and Anagnostou, Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) rainfall estimates were used to calibrate TRMM Microwave Imager (TMI) retrieval. Regional differences in PR-based TMI calibration were investigated by testing the algorithm over four geographic regions, consisting of Africa, northern South America (containing the Amazon basin), the continental United States, and south Asia. In this paper the performance of Dinku and Anagnostou's technique applied on SSM/I data over three of these regions (Africa, Amazon, and South Asia) is demonstrated. Two approaches are investigated for using PR rainfall products to calibrate the algorithm parameters. In the first approach, TMI channels are remapped to the spatial resolutions of the corresponding SSM/I channels; then, PR is used to calibrate the rain retrieval on the remapped TMI data. In the second approach, the PR-based TMI algorithm calibration is performed at a coarser (0.25°) resolution. To assess the quality of algorithm estimates with respect to PR, rainfall fields derived from Dinku and Anagnostou, applied to SSM/I observations (using parameters determined from both approaches), are compared with matched (within ±15 min of the satellites' overpass time difference) PR surface rain rates. Calibration data come from the wet seasons (January–March) of 2000 and 2001. To assess the quality of the estimates with respect to PR, data from a 5-month period (December–April) of 2002, 2003, and 2004 are used. In comparison with the latest version of the Goddard profiling (GPROF) algorithm rain estimates, the current algorithm shows significant improvements in terms of both bias and random error reduction. The paper also shows that rain estimation based on TMI observations is associated with lower error statistics in comparison with the corresponding SSM/I retrievals. [ABSTRACT FROM AUTHOR]

In this paper the progress made in producing predictions of the Normalized Difference Vegetation Index (NDVI) over Kenya in the Greater Horn of Africa (GHA) for the October–December (OND) season is discussed. Several studies have identified a statistically significant relationship between rainfall and NDVI in the region. Predictability of seasonal rainfall by global climate models (GCMs) during the OND season over the GHA has also been established as being among the best in the world. Information was extracted from GCM seasonal prediction output using statistical transformations. The extracted information was then used in the prediction of NDVI. NDVI is a key variable for management of various climate-sensitive problems. For example, it has been shown to have the potential to predict environmental conditions associated with Rift Valley Fever (RVF) viral activity and this is referred to throughout the paper as a motivation for the study. RVF affects humans and livestock and is particularly economically important in the GHA. The establishment of predictability for NDVI in this paper is therefore part of a methodology that could ultimately generate information useful for managing RVF in livestock in the GHA. It has been shown that NDVI can be predicted skillfully over the GHA with a 2–3-month lead time. Such information is crucial for tailoring forecast information to support RVF monitoring and prediction over the region, as well as many other potential applications (e.g., livestock forage estimation). More generally, the Famine Early Warning System (FEWS), a project of the U.S. Agency for International Development (USAID) and the National Aeronautics and Space Administration (NASA) and other specialized technical centers routinely use NDVI images to monitor environmental conditions worldwide. The high predictability for NDVI established in this paper could therefore supplement the routine monitoring of environmental conditions for a wide range of applications. [ABSTRACT FROM AUTHOR]

Tropical Applications of Meteorology Using Satellite Data and Ground-Based Observations (TAMSAT) rainfall monitoring products have been extended to provide spatially contiguous rainfall estimates across Africa. This has been achieved through a new, climatology-based calibration, which varies in both space and time. As a result, cumulative estimates of rainfall are now issued at the end of each 10-day period (dekad) at 4-km spatial resolution with pan-African coverage. The utility of the products for decision making is improved by the routine provision of validation reports, for which the 10-day (dekadal) TAMSAT rainfall estimates are compared with independent gauge observations. This paper describes the methodology by which the TAMSAT method has been applied to generate the pan-African rainfall monitoring products. It is demonstrated through comparison with gauge measurements that the method provides skillful estimates, although with a systematic dry bias. This study illustrates TAMSAT's value as a complementary method of estimating rainfall through examples of successful operational application. [ABSTRACT FROM AUTHOR]

This paper describes a new gridded, daily 29-yr precipitation estimation dataset centered over Africa at 0.1° spatial resolution. Called the African Rainfall Climatology, version 2 (ARC2), it is a revision of the first version of the ARC. Consistent with the operational Rainfall Estimation, version 2, algorithm (RFE2), ARC2 uses inputs from two sources: 1) 3-hourly geostationary infrared (IR) data centered over Africa from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) and 2) quality-controlled Global Telecommunication System (GTS) gauge observations reporting 24-h rainfall accumulations over Africa. The main difference with ARC1 resides in the recalibration of all Meteosat First Generation (MFG) IR data (1983-2005). Results show that ARC2 is a major improvement over ARC1. It is consistent with other long-term datasets, such as the Global Precipitation Climatology Project (GPCP) and Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP), with correlation coefficients of 0.86 over a 27-yr period. However, a marginal summer dry bias that occurs over West and East Africa is examined. Daily validation with independent gauge data shows RMSEs of 11.3, 13.4, and 14, respectively, for ARC2, Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis 3B42, version 6 (3B42v6), and the CPC morphing technique (CMORPH) for the West African summer season. The ARC2 RMSE is slightly higher for Ethiopia than those of CMORPH and 3B42v6. Both daily and monthly validations suggested that ARC2 underestimations may be attributed to the unavailability of daily GTS gauge reports in real time, and deficiencies in the satellite estimate associated with precipitation processes over coastal and orographic areas. However, ARC2 is expected to provide users with real-time monitoring of the daily evolution of precipitation, which is instrumental in improved decision making in famine early warning systems. [ABSTRACT FROM AUTHOR]

This paper examines the factors governing rainfall variability in western equatorial Africa (WEA) during the April-June rainy season. In three of the five regions examined some degree of large-scale forcing is indicated, particularly in the region along the Atlantic coast. Interannual variability in this coastal sector also demonstrates a strong link to changes in local sea surface temperatures (SSTs) and the South Atlantic subtropical high. To examine potential causal mechanisms, various atmospheric parameters are evaluated for wet and dry composites. The results suggest that the intensity of the zonal circulation in the global tropics is a crucial control on rainfall variability over WEA. A La Niña (El Niño)-like signal in both SSTs and zonal circulation over the Pacific is apparent in association with the wet (dry) conditions in the western sector. However, remote forcing from the Pacific modulates the circulation over Africa indirectly by way of synchronous changes in the entire Indian or Atlantic Ocean. Anomalies in the local zonal winds are similar in all three regions: the wet (dry) composite is associated with an intensification (weakening) of the upper-tropospheric easterlies and low-level westerlies, but a weakening (intensification) of the midlevel easterlies. This work also suggests that, in most cases, the relationship between local SSTs and rainfall reflects a common remote forcing by the large-scale atmosphere-ocean system. This forcing is manifested via changes in the zonal circulation. Thus, the statistical associations between rainfall and SSTs do not indicate direct forcing by local SSTs. One point of evidence for this conclusion is the stronger association with atmospheric parameters than with SSTs. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of different ocean initialization strategies on the forecast skill of decadal prediction experiments performed with the ECHAM5/Max Planck Institute Ocean Model (MPI-OM) coupled model. The ocean initializations assimilate three-dimensional temperature and salinity anomalies from two different ocean state estimates, the ocean reanalysis of the German contribution to Estimating the Circulation and Climate of the Ocean (GECCO) and an ensemble of MPI-OM ocean experiments forced with the NCEP-NCAR atmospheric reanalysis. The results show that North Atlantic and Mediterranean sea surface temperature (SST) variations can be skillfully predicted up to a decade ahead and with greater skill than by both uninitialized simulations and persistence forecasts. The regional distribution of SST predictive skill is similar in both initialization approaches; however, higher skill is found for the NCEP hindcasts than for the GECCO hindcasts when a combination of predictive skill measures is used. Skillful predictions of surface air temperature are obtained over northwestern Europe, northern Africa, and central-eastern Asia. The North Atlantic subpolar gyre region stands out as the region with the highest predictive skill beyond the warming trend, in both SST and upper-ocean heat-content predictions. Here the NCEP hindcasts deliver the best results due to a more accurate initialization of the observed variability. The dominant mechanism for North Atlantic climate predictability is of dynamical origin and can be attributed to the initialization of the Atlantic meridional overturning circulation, thus explaining the reoccurrence of high predictive skill within the second pentad of the hindcasts experiments. The results herein demonstrate that ocean experiments forced with the observed history of the atmospheric state constitute a simple but successful alternative strategy for the initialization of skillful climate predictions over the next decade. [ABSTRACT FROM AUTHOR]

This paper explores a three-way interaction between an African easterly wave (AEW), the diurnal cycle of convection over the Guinea Highlands (GHs), and a convectively coupled atmospheric equatorial Kelvin wave (CCKW). These interactions resulted in the genesis of Tropical Storm Debby over the eastern tropical Atlantic during late August 2006. The diurnal cycle of convection downstream of the GHs during the month of August is explored. Convection associated with the coherent diurnal cycle is observed off the coast of West Africa during the morning. Later, convection initiates over and downstream of the GHs during the afternoon. These convective features were pronounced during the passage of the pre-Debby AEW. The superposition between the convectively active phase of a strong CCKW and the pre-Debby AEW occurred shortly after merging with the diurnally varying convection downstream of the GHs. The CCKW-AEW interaction preceded tropical cyclogenesis by 18 h. The CCKW provided a favorable environment for deep convection. An analysis of high-amplitude CCKWs over the tropical Atlantic and West Africa during the Northern Hemisphere boreal summer (1979-2009) highlights a robust relationship between CCKWs and the frequency of tropical cyclogenesis. Tropical cyclogenesis is found to be less frequent immediately prior to the passage of the convectively active phase of the CCKW, more frequent during the passage, and most frequent just after the passage. [ABSTRACT FROM AUTHOR]

This paper evaluates rainfall detection capabilities of seven satellite rainfall estimates over the desert locust recession regions of the world. The region of interest covers the arid and semiarid region from northwestern Africa to northwestern India. The evaluated satellite rainfall products are the African rainfall climatology (ARC), rainfall estimation algorithm (RFE), Tropical Rainfall Measuring Mission 3B42 and its real-time version (3B42RT), NOAA/Climate Prediction Center morphing technique (CMORPH), and two versions of the Global Satellite Mapping of Precipitation moving vector with Kalman filter (GSMaP-MVK and GSMaP-MVK+). The reference data were obtained from the Desert Locust Information Service of the United Nations Food and Agriculture Organization (FAO). The FAO data are qualitative information collated by desert locust survey teams from different countries during field campaigns. Such data can only be used to assess the rainfall detection capabilities of the satellite products. The validation region is divided into four subregions and validations statistics are computed for each region. The probability of detection varies from 70% for the relatively wet part of the validation region to less than 20% for the driest part. The main weakness of the satellite products is overestimation of rainfall occurrences. The false-alarm ratio was as high as 84% for the driest part and as high as 57% for the wetter region. The satellite products still exhibit positive detection skill for all of the subregions. A comparison of the different products shows that no single product stands out as having the best or the worst overall performance. [ABSTRACT FROM AUTHOR]

This paper provides an understanding of essential differences between developing and nondeveloping African easterly waves, which was a major goal of NAMMA, NASA’s field program in the eastern Atlantic, which functioned as an extension of the African Monsoon Multidisciplinary Analysis (AMMA) program during 2006. Three NAMMA waves are studied in detail using FNL analysis: NAMMA wave 2, which developed into Tropical Storm Debby; NAMMA wave 7, which developed into Hurricane Helene; and NAMMA wave 4, which did not develop within the NAMMA domain. Diagnostic calculations are performed on the analyzed fields using energy transformation equations and the isentropic potential vorticity equation. The results show that the two developing waves possess clear and robust positive barotropic energy conversion in conjunction with positive diabatic heating that includes a singular burst of heating at a particular time in the wave’s history. This positive barotropic energy conversion is facilitated in waves that have a northeast–southwest tilt to the trough axis and a wind maximum to the west of this axis. The nondeveloping wave is found to have the same singular burst of diabatic heating at one point in its history, but development of the wave does not occur due to negative barotropic energy conversion. Such conversion is facilitated by a northwest–southeast tilt to the trough axis and a wind maximum to the east of this axis. The conclusions about wave development and nondevelopment formulated in this research are viewed as important and significant, but they require additional testing with detailed observational- and numerical-based studies. [ABSTRACT FROM AUTHOR]

This paper is part of a series of studies addressing the dynamics of the West African summer monsoon at intraseasonal time scales between 10 and 90 days. The dominant mode of 25–90-day convective variability in the African monsoon was investigated, starting from previous results involving the excitation of dry equatorial Kelvin and Rossby waves by a negative diabatic heat source located over the warm pool. This evolution is consistent with a significant contribution by a convectively coupled equatorial Rossby wave and the MJO. On the other hand, convectively coupled Kelvin waves as well as the dry Kelvin wave signal have a very weak impact. However, there is more to the global control of the African summer monsoon than convectively coupled wave dynamics. The active/break cycle of the Indian monsoon, controlled by a northward-moving dipole of diabatic heating in the Indian sector, can also influence the African monsoon through atmospheric teleconnections. Simulations performed with a dry primitive equation model show that this influence may be transferred through the northern Indian heat source, which excites a Rossby cyclonic circulation propagating westward over North Africa that is cut off by the northward arrival of the equatorial Indian heat source and the associated intrusion of an anticyclonic ridge. Low-level westerly winds and moisture advection within the ITCZ consequently increase over Africa. The mean time lag between an active phase over India and over Africa is about 15–20 days. [ABSTRACT FROM AUTHOR]

This paper promotes the view that African easterly waves (AEWs) are triggered by localized forcing, most likely associated with latent heating upstream of the region of observed AEW growth. A primitive equation model is used to show that AEWs can be triggered by finite-amplitude transient and localized latent heating on a zonally varying basic state that is linearly stable. Heating close to the entrance region of the African easterly jet (AEJ) is shown to initiate AEWs downstream. The heating leads to an initial trough that reaches the West African coast about 5–7 days later, depending on the nature of the heating profile. After this, a structure that projects strongly onto the leading linear normal mode of the basic state becomes established, characterized by a number of westward-propagating disturbances that strongly resemble AEWs. The sensitivity of the forced AEWs to the nature and location of the heating profile is examined. AEWs are most efficiently triggered by heating profiles that establish lower tropospheric circulations close to the entrance region of the AEJ. In the present study, this was best achieved by lower tropospheric heating from shallow convection or upper-level heating and lower-level cooling from a stratiform precipitation profile. Both profiles have significant heating gradients in the vertical in the mid-to-lower troposphere. This triggering paradigm for the genesis of AEWs has consequences for the variability and predictability of AEWs at weather and climate time scales. In addition to the nature of the AEJ, often emphasized, it is crucial to consider the nature and variability of upstream heating triggers. [ABSTRACT FROM AUTHOR]

This paper provides new information on the low-level (850 hPa) structure and behavior of African easterly waves (AEWs) and relates this information to previous studies. Individual AEWs that occurred during June–September of 2001 are studied by a synoptic approach that employs Hovmöller diagrams, wave track maps, and case studies. The focus is on two AEW regimes in the lower troposphere over North Africa: a dry regime to the north of the African easterly jet (AEJ) coincident with the surface position of the monsoon trough near 20°N, and a wet regime to the south of the jet coincident with the near-equatorial rainbelt near 10°N. The following issues are addressed: the origin of the waves seen in the two wave regimes, relation of the wave activity to the mean positions of the surface monsoon trough and the 600–700-hPa AEJ, collocation of the tracks of the two wave regimes off the African coast, and diversity in low-level wave behavior that includes merging, splitting, and dissipation of the cyclonic vorticity centers associated with the wave troughs. The relationship between the waves following the two tracks is examined as well as the relationship between the low-level wave activity and Atlantic tropical cyclogenesis in 2001. It is shown that the two wave regimes can interact, and that both regimes were instrumental in Atlantic tropical cyclogenesis in 2001. [ABSTRACT FROM AUTHOR]

During the past 20 years, organized experimental campaigns as well as continuous development and implementation of air-pollution modeling have led to significant gains in the understanding of the paths and scales of pollutant transport and transformation in the greater Mediterranean region (GMR). The work presented in this paper has two major objectives: 1) to summarize the existing knowledge on the transport paths of particulate matter (PM) in the GMR and 2) to illustrate some new findings related to the transport and transformation properties of PM in the GMR. Findings from previous studies indicate that anthropogenically produced air pollutants from European sources can be transported over long distances, reaching Africa, the Atlantic Ocean, and North America. The PM of natural origin, like Saharan dust, can be transported toward the Atlantic Ocean and North America mostly during the warm period of the year. Recent model simulations and studies in the area indicate that specific long-range transport patterns of aerosols, such as the transport from Asia and the Indian Ocean, central Africa, or America, have negligible or at best limited contribution to air-quality degradation in the GMR when compared with the other sources. Also, new findings from this work suggest that the imposed European Union limits on PM cannot be applicable for southern Europe unless the origin (natural or anthropogenic) of the PM is taken into account. The impacts of high PM levels in the GMR are not limited only to air quality, but also include serious implications for the water budget and the regional climate. These are issues that require extensive investigation because the processes involved are complex, and further model development is needed to include the relevant physicochemical processes properly. [ABSTRACT FROM AUTHOR]

The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) currently operates three geostationary satellites: Meteosat-5, Meteosat-7, and Meteosat-8. Observations by Meteosat-5 can be combined with observations from either Meteosat-7 or Meteosat-8 to allow geostationary stereo height retrievals within the overlap area over the Indian Ocean and east Africa. This paper aims to demonstrate the capabilities of the geostationary stereophotogrammetric cloud-top height retrieval—in particular, with the new high-resolution visible channel (HRV) of Meteosat-8. Conceived as a proof-of-concept study, the retrieval was limited to four distinct cloud areas in northeast Africa. The effects of the geolocation, spatial resolution, satellite position, and acquisition time on the cloud-top height accuracy were studied. It is demonstrated that the matching accuracy is sensitive to the acquisition-time difference and spatial resolution. As a result, there is only a marginal benefit from the good spatial resolution offered by the Meteosat-8 HRV channel because of the low spatial resolution of Meteosat-5 and the poor time synchronization between the observations of the two satellites. On the contrary, the good time synchronization between Meteosat-5 and Meteosat-7 observations offsets the errors in the height assignment resulting from the relatively coarse spatial resolution, if the geolocation accuracy is locally enhanced with additional landmarks from higher-resolution images. With the geolocation correction and the newly implemented time information in the Meteosat-5 and -7 header information, the stereo cloud-top height assignment for the Meteosat-5/-7 and Meteosat-5/-8 HRV combination resulted in about the same accuracy of approximately ±1 km. For the Meteosat-5/-8 HRV combination, the time differences of up to 7.5 min preclude higher accuracy. To validate the cloud-top heights, observations by the Multiangle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) were used. [ABSTRACT FROM AUTHOR]

Surface broadband emissivity in the thermal infrared region is an important parameter for the studies of the surface energy balance. This paper focuses on estimating a broadband window emissivity from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectrometer (MODIS) data. Both sensors are on board the NASA Earth Observing System (EOS) Terra satellite, which was launched in 1999. First, several definitions of the broadband emissivity were investigated, and it was found that the emissivity integrated between 8 and 13.5 μm is the best for estimating the net longwave radiation under clear-sky conditions. Then, a method to estimate broadband emissivity at the continental scale was developed. The method uses two regressions. The first regression is to relate the broadband emissivity to the emissivities for the five ASTER channels using measured emissivities in the laboratory from spectral libraries. The second regression relates the broadband emissivity map from ASTER data to the emissivity and reflectance derived from MODIS data. The first regression was used for mapping the broadband emissivity using ASTER data in a 500 km × 1400 km area of North Africa, which includes Tunisia, eastern Algeria, and western Libya. This emissivity map was used to calibrate the second regression, which was applied to MODIS data and generated a broadband emissivity map over North Africa and the Arabian Peninsula. The range of the broadband emissivity was found to be between 0.85 and 0.96 for the desert area. The resulting broadband emissivity maps and the methodology for generating them will contribute to future climate modeling studies. [ABSTRACT FROM AUTHOR]