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1.
West-central Uganda, a biodiversity hotspot on the eastern edge of central equatorial Africa (CEA), is a region coping with balancing food security needs of a rapidly growing human population dependent on subsistence agriculture with the conservation of critically endangered species. Documenting and understanding rainfall trends is thus of critical importance in west-central Uganda, but sparse information exists on rainfall trends in CEA during the past several decades. The recently created African Rainfall Climatology version 2 (ARC2) dataset has been shown to perform satisfactorily at identifying rainfall days and estimating seasonal rainfall totals in west-central Uganda. Therefore, we use ARC2 data to assess rainfall trends in west-central Uganda and other parts of equatorial Africa from 1983–2012. The core variables examined were three-month rainfall variables for west-central Uganda, and annual rainfall variables and seasonal rainfall totals for a transect that extended from northwestern Democratic Republic of the Congo to southern Somalia. Significant decreases in rainfall in west-central Uganda occurred for multiple three-month periods centered on boreal summer, and rainfall associated with the two growing seasons decreased by 20 % from 1983–2012. The drying trend in west-central Uganda extended westward into the Congo rainforest. Rainfall in CEA was significantly correlated with the Atlantic Multidecadal Oscillation (AMO) at the annual scale and during boreal summer and autumn. Two other possible causes of the decreasing rainfall in CEA besides North Atlantic Ocean sea-surface temperatures (e.g., AMO), are the warming of the Indian Ocean and increasing concentrations of carbonaceous aerosols over tropical Africa from biomass burning.  相似文献   

2.
Summary Variability of rainfall in the semi-arid regions can cause problems in evaluating experimental trials. To describe the spatial rainfall patterns over a large experimental station, rainfall was monitored during the 1986 and 1987 rainy seasons using 18 raingages over the 500 ha experimental station of ICRISAT Sahelian Center, in Niger, West Africa. Average relative variability of individual rain storms, defined as the percentage deviation from the mean, varied from 2 to 62%, while the variability over the rainy season was 17.1%. Isohyetal patterns of individual rain storms as well as seasonal totals showed distinct coherence in the spatial pattern over the station. The effects of total volume, duration, direction and intensity of storms and the time of year on the spatial correlations were analyzed. Storm value showed a large influence on the correlation decay with distance. Correlations in the W — E and SW — NE directions were higher in comparison to those in the N — S and NW — SE directions. Point rainfall measurements were better correlated with the network average rainfall than with the rainfall recorded at the meteorological station. Variograms among raingages revealed that the distance of independence was approximately 1 000 m for almost all storms. Use of a network of raingages over agricultural experiment stations reduces the average relative variability of areal rainfall estimates and provides a means to develop simple relations for estimation of point rainfall for individual applications.With 8 Figures  相似文献   

3.
Systematic evaluation of food security throughout the Sahel has been attempted for nearly two decades. Food security analyses have used both food prices to determine the ability of the population to access food, and satellite-derived vegetation indices that measure vegetation production to establish how much food is available each year. The relationship between these two food security indicators is explored here using correspondence analysis and through the use of Markov chain models. Two sources of quantitative data were used: 8 km normalized difference vegetation index (NDVI) data from the Advanced Very High Resolution Radiometers (AVHRR) carried on the NOAA series of satellites, and monthly millet prices from 445 markets in Mali, Niger and Burkina Faso. The results show that the growing season vegetation production is related to the price of millet at the annual and the seasonal time scales. If the growing season was characterized by erratic, sparse rainfall, it resulted in higher prices, and well-distributed, abundant rainfall resulted in lower prices. The correspondence between vegetation production and millet prices is used to produce maps of millet prices for West Africa.  相似文献   

4.
Summary This study investigates the onset and cessation dates of the main summer rainy season over Zambia, their interannual variability, and potential relationships with ENSO and regional circulation anomalies. Focus is placed on onset and cessation dates because these rainy season characteristics are often of more relevance than seasonal rainfall totals to user groups such as farmers, water resource managers, health and tourism officials. It is found that there is substantial interannual variability in these parameters with some indications of a relationship between anomalies in onset date and those in Ni?o3.4 SST, particularly over the northern part of the country. A strong gradient exists between the south and the north in terms of rainfall amount, mean onset date and mean cessation date and all areas of the country experience significant variability. Analysis of circulation anomalies for early (late) onset seasons over northern Zambia shows that they are characterised by anomalous ridging (troughing) over and south of South Africa, a weaker (stronger) Angola heat low and enhanced (reduced) low level moisture flux into eastern Zambia from the Indian Ocean. The connection with ENSO during the onset season of austral spring appears to arise both through changes in the amount of subsidence over southern Africa as well as via the so-called Pacific South America pattern that extends across the South Pacific and South Atlantic towards southern Africa. Authors’ address: S. Hachigonta, C. J. C. Reason, M. Tadross, Department of Oceanography, University of Cape Town, Private Bag, Rondebosch 7701, South Africa.  相似文献   

5.
Changes in growing seasons for 2041–2060 across Africa are projected using a regional climate model at 90-km resolution, and confidence in the predictions is evaluated. The response is highly regional over West Africa, with decreases in growing season days up to 20% in the western Guinean coast and some regions to the east experiencing 5–10% increases. A longer growing season up to 30% in the central and eastern Sahel is predicted, with shorter seasons in parts of the western Sahel. In East Africa, the short rains (boreal fall) growing season is extended as the Indian Ocean warms, but anomalous mid-tropospheric moisture divergence and a northward shift of Sahel rainfall severely curtails the long rains (boreal spring) season. Enhanced rainfall in January and February increases the growing season in the Congo basin by 5–15% in association with enhanced southwesterly moisture transport from the tropical Atlantic. In Angola and the southern Congo basin, 40–80% reductions in austral spring growing season days are associated with reduced precipitation and increased evapotranspiration. Large simulated reductions in growing season over southeastern Africa are judged to be inaccurate because they occur due to a reduction in rainfall in winter which is over-produced in the model. Only small decreases in the actual growing season are simulated when evapotranspiration increases in the warmer climate. The continent-wide changes in growing season are primarily the result of increased evapotranspiration over the warmed land, changes in the intensity and seasonal cycle of the thermal low, and warming of the Indian Ocean.  相似文献   

6.
Improving the adaptive capacity of small-scale irrigation systems to the impacts of climate change is crucial for food security in Asia. This study analyzes the capacity of small-scale irrigation systems dependent on the Asian monsoon to adapt to variability in river discharge caused by climate change. Our study is motivated by the Pumpa irrigation system, a small-scale irrigation system located in Nepal that is a model for this type of system. We developed an agent-based model in which we simulated the decisions farmers make about the irrigation strategy to use according to available water flow. Given the uncertainty associated with how climate change may affect the Asian monsoon, we simulated the performance of the system under different projections of climate change in the region (increase and decrease in rainfall, reduction and expansion of the monsoon season, and changes in the timing of the onset of the monsoon). Accordingly to our simulations, farmers might need to adapt to rainfall intensification and a late onset in the monsoon season. The demands for collective action among farmers (e.g. infrastructure repair, meetings, decisions, etc.) might increase considerably due to climate change. Although our model suggests that investment in new infrastructure might increase the performance of the system under some climate change scenarios, the high inequality among farmers when water availability is reduced might hinder the efficiency of these measures due to a reduction of farmers’ willingness to cooperate. Our modeling exercise helps to hypothesize about the most sensitive climate change scenarios for smallscale irrigation farming in Nepal and helps to frame a discussion of some possible solutions and fundamental trade-offs in the process of adaptation to improve for food and water security under climate change.  相似文献   

7.
Mahlalela  P. T.  Blamey  R. C.  Hart  N. C. G.  Reason  C. J. C. 《Climate Dynamics》2020,55(9-10):2743-2759

Much of the Eastern Cape province in South Africa has been experiencing a severe drought since 2015. This drought has had major socio-economic effects particularly on the large impoverished rural population as well as on some urban areas where supplied water services have broken down in several cases. The region is influenced by both midlatitude and tropical systems leading to a complex regional meteorology that hitherto has not been much studied compared to other parts of South Africa. Here, the ongoing drought is examined in the context of long-term trends and the interannual rainfall variability of the region. Although the region has experienced drought in all seasons since 2015, focus here is placed on the spring (September–November) which shows the most consistent and robust signal. On average, this season contributes between about 25–35% of the annual rainfall total. Based on CHIRPS data, it is found that this season shows a significant decreasing trend in both rainfall totals as well as the number of rainfall days (but not heavy rainfall days) for spring over most of the province since 1981. On interannual time scales, the results indicate that dry (wet) springs over the Eastern Cape are associated with a cyclonic (anticyclonic) anomaly southeast of South Africa as part of a shift in the zonal wavenumber 3 pattern in the midlatitudes. Over the landmass, a stronger (weaker) Botswana High is also apparent with increased (decreased) subsidence over and near the Eastern Cape which is less (more) favourable for cloud band development and hence reduced (enhanced) rainfall during dry (wet) springs. Analysis of mid-century (2040–2060) CMIP5 rainfall projections suggests that there may be a flattening of the annual cycle over the Eastern Cape with the winter becoming wetter and the summer drier. For the spring season of interest here, the multi-model projections also indicate drying but less pronounced than that projected for the summer.

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8.
Summary A general circulation model is used to study the response of the atmosphere to an idealised sea surface temperature (SST) anomaly pattern (warm throughout the southern midlatitudes, cool in the tropics) in the South Indian Ocean region. The anomaly imposed on monthly SST climatology captures the essence of patterns observed in the South Indian Ocean during both ENSO events and multidecadal epochs, and facilitates diagnosis of the model response. A previous study with this anomaly imposed in the model examined differences in the response between that on the seasonal scale (favours enhancement of the original SST anomaly) and that on the decadal scale (favours damping of the anomaly). The current study extends that work firstly by comparing the response on the intraseasonal, seasonal and interannual scales, and secondly, by assessing the changes in the circulation and rainfall over the adjoining African landmass.It is found that the atmospheric response is favourable for enhancement of the original SST anomaly on scales up to, and including, annual. However, as the scale becomes interannual (i.e., 15–21 months after imposition of the anomaly), the model response suggests that damping of the original SST anomaly becomes likely. Compared to the shorter scale response, the perturbation pressure and wind distribution on the interannual scale is shifted poleward, and is more reminiscent of the decadal response. Winds are now stronger over the warm anomaly in the southern midlatitudes suggesting enhanced surface fluxes, upper ocean mixing, and consequently, a damping of the anomaly.Examination of the circulation and rainfall patterns indicates that there are significant anomalies over large parts of southern Africa during the spring, summer and autumn seasons for both short (intraseasonal to interannual) and decadal scales. It appears that rainfall anomalies are associated with changes in the advection of moist tropical air from the Indian Ocean and its related convergence over southern Africa. Over eastern equatorial Africa, the austral autumn season (the main wet season) showed rainfall increases on all time scales, while parts of central to eastern subtropical southern Africa were dry. The signals during summer were more varied. Spring showed generally dry conditions over the eastern half of southern Africa on both short and decadal time scales, with wet areas confined to the west. In all cases, the magnitude of the rainfall anomalies accumulated over a 90 day season were of the order of 90–180 mm, and therefore represent a significant fraction of the annual total of many areas. It appears that relatively modest SST anomalies in the South Indian Ocean can lead to sizeable rainfall anomalies in the model. Although precipitation in general circulation models tends to be less accurately simulated than many other variables, the model results, together with previous observational work, emphasize the need for ongoing monitoring of SST in this region.With 14 Figures  相似文献   

9.
Tropical-extratropical cloud band systems over southern Africa, known as tropical temperate troughs (TTTs), are known to contribute substantially to South African summer rainfall. This study performs a comprehensive assessment of the seasonal cycle and rainfall contribution of TTTs by using a novel object-based strategy that explicitly tracks these systems for their full life cycle. The methodology incorporates a simple assignment of station rainfall data to each event, thereby creating a database containing detailed rainfall characteristics for each TTT. This is used to explore the importance of TTTs for rain days and climatological rainfall totals in October–March. Average contributions range from 30 to 60 % with substantial spatial heterogeneity observed. TTT rainfall contributions over the Highveld and eastern escarpment are lower than expected. A short analysis of TTT rainfall variability indicates TTTs provide substantial, but not dominant, intraseasonal and interannual variability in station rainfall totals. TTTs are however responsible for a high proportion of heavy rainfall days. Of 52 extreme rainfall events in the 1979–1999 period, 30 are associated with these tropical-extratropical interactions. Cut-off lows were included in the evolution of 6 of these TTTs. The study concludes with an analysis of the question: does the Madden-Julian Oscillation influence the intensity of TTT rainfall over South Africa? Results suggest a weak but significant suppression (enhancement) of intensity during phase 1(6).  相似文献   

10.
Interannual fluctuations in rainfall and ocean-atmosphere fields over and around Africa were studied in the satellite era of 1979–2007 using singular value decomposition. The leading modes of rainfall variability in GPCP satellite-gauge merged fields include a leading mode over central Africa, two modes of marine origin in the Gulf of Guinea and Eastern Africa, and two sub-tropical modes over the Sahel and Southern Africa. This differs from earlier gauge-based studies that tend to isolate three leading modes over western, eastern, and southern Africa. In the sea-surface temperature, sea-level pressure and upper wind fields, ENSO signals dominate the leading modes. However, for the low-level wind field, a trough circulation over the southeast Atlantic – Kalahari is the leading mode. It demonstrates predictive potential when cross-correlated with rainfall at 6- to 12-month lead time. Based on continuous filtered data, the value of various indices and the predictability of different zones are examined. The Sahel achieves the highest rank followed by the Congo and southern zones in the next tier. The Guinea and East African rains, which peak in the March-to-May season, appear least predictable. The seasonal rainfall is shown to modulate economic growth rate, and multi-variate predictive algorithms are tested at 6-month lead time.  相似文献   

11.
Summary The seek for variability of factors is suggested in detecting variabilities that could not have been detected in other ways. The proposed methodology may be appropriate to evaluate the rainfall distribution during wetter or drier periods or regions. Tested on rainfall data from Israel, the present method detected a seasonal cycle in the dependence of rainfall totals on daily rainfall (P) and on the Number of Rain Days (NRD). At the beginning and at the end of the rainy season and in the drier parts of the country, there is a greater dependence of the total rainfall on P. During the main rainy season, and in the wetter parts of the country, variations in the total monthly rainfall (RAIN) from year to year, are caused mainly by variations in values of NRD rather by variations in P.With 6 Figures  相似文献   

12.
Rainfall patterns influence water usage and revenue from user payments in rural Africa. We explore these dynamics by examining monthly rainfall against 4,888 records of rural piped water revenue in Ghana, Rwanda, and Uganda and quantifying revenue changes over 635 transitions between dry and wet seasons.Results show operators experience revenue variability at regional and intra-seasonal scales. Revenues fall by an average of 30 percent during the wettest months of the year in climate regimes with consistent wet season rainfall. However, seasonally stable revenues are observed in areas where consecutive dry days are common during the wet season, potentially reflecting a dependency on reliable services. We also find changes in tariff level, waterpoint connection type, and payment approach do not consistently prevent or increase seasonal revenue variability.Local revenue generation underpins delivery of drinking water services. Where rainfall patterns remain consistent, piped water operators can expect to encounter seasonal revenue reductions regardless of whether services are provided on or off premises and of how services are paid for. Revenue projections that assume consistent volumetric demand year-round may lead to shortfalls that threaten sustainability and undermine the case for future investment. Intra-seasonal rainfall analysis can enhance rural piped water revenue planning by offering localised insight into demand dynamics and revealing where climate variability may increase dependency on reliable services.  相似文献   

13.
Despite the strong signal of El Niño/Southern Oscillation (ENSO) events on climate in the Indo-Pacific region, models linking ENSO-based climate variability to seasonal rice production and food security in the region have not been well developed or widely used in a policy context. This study successfully measures the connections among sea surface temperature anomalies (SSTAs), rainfall, and rice production in Indonesia during the past three decades. Regression results show particularly strong connections on Java, where 55% of the country's rice is grown. Two-thirds of the interannual variance in rice plantings and 40% of the interannual variance in rice production during the main (wet) season on Java are explained by year-to-year fluctuations in SSTAs measured 4 and 8 months in advance, respectively. These effects are cumulative; during strong El Niño years, production shortfalls in the wet season are not made up later in the crop year. The analysis demonstrates that quantitative predictions of ENSO's effects on rice harvests can provide an additional tool for managing food security in one of the world's most populous and important rice-producing countries.  相似文献   

14.
This study reveals homogeneous sub-regions over the poorly studied area of western equatorial Africa (10S?C7N and 7E?C30E). Monthly totals of 141 stations covering the period 1955?C1984 are used. The stations are grouped based on the similarity of their interannual rainfall variability. In addition to annual totals, four different seasons are examined separately for regionalization, an approach that has lacked in previous studies. The four 3-month seasons are defined as follows: January?CFebruary?CMarch (JFM), April?CMay?CJune (AMJ), July?CAugust?CSeptember (JAS), and October?CNovember?CDecember (OND). Two different algorithms are applied and compared: the rotated principal component analysis (RPCA) in conjunction with Ward's method, and the RPCA in conjunction with k-means method. The principal components that explain about 65% of total variance are retained and then varimax rotated. The corresponding scores are utilized as input for cluster analysis. Using Ward's method, five sub-regions are recognized for AMJ, JAS and OND and 4 sub-regions for JFM and annual data. The regions are geographically well distributed over the area and consist of roughly the same number of stations. The F-test is used to evaluate the homogeneity of each sub-region. The results show that all sub-regions are strongly homogeneous. Assuming the same number of clusters, the k-means method provides comparable spatial patterns with those of Ward's method. However, there are some differences, which are more evident in JAS and OND. Like Ward's method, the values of F-ratio for the k-means algorithm also confirm the homogeneity of all seasons/sub-regions. The interannual variability of rainfall for each season/sub-region is also provided and compared.  相似文献   

15.
Temporal precipitation irregularities, extreme rainfall, or droughts represent great climate concerns and have major impacts on the natural environment. The present study focuses on 41 stations spread over the entire Mediterranean region. The datasets contain daily rainfall totals, with a median length of 56?years within the period of 1931?C2006. The study aims at detecting significant trends in the time series and the uncertainties of four parameters: annual rainfall total, number of rain spells, the rain-spells yields, and rainy season length. In addition, it aims to detect significant temporal changes in the occurrence of extreme events of these parameters. Several methodologies have been used in this study, and the main conclusion is that despite the general assumption of tremendous changes in the rainfall regime, no significant temporal trends or uncertainty trends were found in most of the stations, neither in their annual totals, their number of rain spells, and their rain-spell yields, nor in their rainy season length. However, in the few cases that a significant trend was detected, former years tended to be wetter, longer, and with more abundant rain spells, while the opposite is seen in the later years; and uncertainty, tends to increase more than to decrease.  相似文献   

16.
The changing rainy season climatology of mid-Ghana   总被引:1,自引:0,他引:1  
Daily rainfall data are examined through the temporal analysis of various definitions of variable temporal units (VTUs) consisting of combinations of various starting dates and durations over mid-Ghana. These VTUs are independent of, yet encompass, the starting dates and durations of the major and minor rainy seasons. Within each VTU, total rainfall and number of rainy days are calculated to describe the rainfall characteristics of the unit. Means and variances of each variable are calculated for each unit over two 20-year periods, 1951–1970 (P1) and 1981–2000 (P2). In P2, the major and minor rainy seasons have undergone varying degrees of desiccation. This reduction in rainfall is, however, not temporally or spatially uniform. The widespread decline of mean rainfall totals and number of rainy days during the minor rainy season, often associated with greater inter-annual variability, is particularly threatening to the production of a second crop.  相似文献   

17.
This article describes an experimental Hunger and Climate Vulnerability Index showing the relative vulnerability of food insecure populations to climate risks at country level, as a tool for better understanding risks to food security presented by climate change. Data from socioeconomic and environmental indicators were analysed, and the most relevant indicators were aggregated using a composite index to compare differential vulnerabilities. The paper shows the high correlation between hunger and climate risk, especially for the regions of the world most affected by food insecurity. The analysis goes beyond the impact of climate on crop yields and provides a multidimensional analysis of vulnerability, while demonstrating the critical role that adaptive capacity has in determining vulnerability. The paper also presents a method for analysing food security vulnerability to climate risks that is replicable at different scales to provide a robust planning tool for policy makers. This approach can also be used to monitor vulnerability, evaluate potential effectiveness of programmes, and/or examine plausible impacts of climate change by introducing scenarios into the vulnerability model.  相似文献   

18.
Twenty-first century climate model projections show an amplification of the annual cycle in tropical precipitation with increased strength in both wet and dry seasons, but uncertainty is large and few studies have examined transition seasons. Here we analyze coupled climate model projections of global land monsoons and show a redistribution of precipitation from spring to summer in northern (North America, West Africa and Southeast Asia) and southern (South America, Southern Africa) regions. The annual cycle changes are global in scale. Two mechanisms, remote (based on tropospheric stability) and local (based on low level and surface moisture), are evaluated through the annual cycle. Increases in tropospheric stability persist from winter into spring and are reinforced by a reduction in surface moisture conditions, suggesting that in spring both remote and local mechanisms act to inhibit convection. This enhanced spring convective barrier leads to reduced early season rainfall; however, once sufficient increases in moisture (by transport) are achieved, decreases in tropospheric stability result in increased precipitation during the late rainy season. Further examination of this mechanism is needed in observations and models, as the projected changes would have substantial implications for agriculture, water management, and disaster preparedness.  相似文献   

19.
Level 3 (3A25) TRMM Precipitation Radar (PR) data are used for 13 years period (1998–2010) to prepare climatology of TRMM PR derived near surface rain (Total rain) and rain fractions for the 4-months duration of Indian Summer Monsoon season (June–September) as well as for individual months. It is found that the total rain is contributed mostly (99 %) by two rain fractions i.e. stratiform and convective rain fractions for the season as well as on the monthly basis. It is also found that total rain estimates by PR are about 65 % of the gauge measured rain over continental India as well as on sub-regional basis. Inter-annual variability of TRMM-PR rain estimates for India mainland and its sub-regions as well as over the neighboring oceanic regions, in terms of coefficient of variability (CV) is discussed. The heaviest rain region over north Bay of Bengal (BoB) is found to have the lowest CV. Another sub-region of low CV lies over the eastern equatorial Indian ocean (EEIO). The CVs of total rain as well as its two major constituents are found to be higher on monthly basis compared to seasonal basis. Existence of a well known dipole between the EEIO and the north BoB is well recognized in PR data also. Significant variation in PR rainfall is found over continental India between excess and deficit monsoon seasons as well as between excess and deficit rainfall months of July and August. Examination of rainfall fractions between the BoB and Central India on year to year basis shows that compensation in rainfall fractions exists on monthly scale on both the regions. Also on the seasonal and monthly scales, compensation is observed in extreme monsoon seasons between the two regions. However, much less compensation is observed between the north BoB and EEIO belts in extreme rain months. This leads to speculation that the deficit and excess seasons over India may result from slight shift of the rainfall from Central India to the neighboring oceanic regions of north BoB. Contribution of stratiform and convective rain fractions have been also examined and the two fractions are found to contribute almost equally to the total rain. Results are further discussed in terms of the possible impact of the two rain fractions on circulation based on possible difference is vertical profiles of latent heat of two types of rain. Substantial differences in the lower and upper tropospheric circulation regimes are noticed in both deficit and excess monsoon months/seasons, emphasizing the interaction between rainfall (latent heat) and circulation.  相似文献   

20.
Climatic conditions such as relatively cold temperatures and dryness are able to limit malaria transmission. Climate change is therefore expected to alter malaria spread. A previous assessment of the potential impacts of climate change on the seasonality of malaria in Africa is revisited. Bias-corrected regional climate projections with a horizontal resolution of 0.5° are used from the Regional Model (REMO), which include land use and land cover changes. The malaria model employed is the climate-driven seasonality model (MSM) from the Mapping Malaria Risk in Africa project for which a comparison with data from the Malaria Atlas Project (MAP) and the Liverpool Malaria Model (LMM), and a novel validation procedure lends more credence to results. For climate scenarios A1B and B1 and for 2001–2050, REMO projects an overall drying and warming trend in the African malaria belt, that is largely imposed by the man-made degradation of vegetation. As a result, the malaria projections of the MSM show a decreased length of the malaria season in West Africa. The northern Sahel is no more longer suitable for malaria in the projections and shorter malaria seasons are expected for various areas farther south. In East Africa, higher temperatures and nearly unchanged precipitation patterns lead to longer transmission seasons and an increase in highland malaria. Assuming constant population numbers, an overall increase in person-months of exposure of up to 6 % is found. The results of this simple seasonality model are similar to previous projections from the more complex LMM. However, a different response to the warming of highlands is found for the two models. It is concluded that the MSM is an efficient tool to assess the climate-driven malaria seasonality and that an uncertainty analysis of future malaria spread would benefit from a multi-model approach.  相似文献   

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