Rainfall Anomalies Research Articles

Causes of extreme 2020 Meiyu-Baiu rainfall: a study of combined effect of Indian Ocean and Arctic

A record-breaking Meiyu-Baiu rainfall hit East Asia in June–July 2020. The warm Indian Ocean (IO) has been identified as a primary cause, but it cannot explain the heavy rainfall in July, a striking characteristic of the 2020 Meiyu-Baiu rainfall. A remarkable retreat of Arctic sea ice in the late spring and early summer of 2020 also promoted Meiyu-Baiu rainfall by favoring North Asian blockings and cold air outbreaks. However, its importance compared with IO warming is unclear. Our result shows that the abundant moisture supply to the 2020 Meiyu-Baiu rainfall mainly stems from anomalous meridional wind convergence, while the excessive ascending motions are due to warm advection tied to enhanced mid-troposphere westerlies. AGCM experiments are used to examine the relative importance of IO warming and Arctic sea ice anomalies. In June, IO warming is responsible for the atmospheric circulation anomalies around the Meiyu-Baiu region and accounts for ~ 75% of the Meiyu-Baiu rainfall anomalies, despite the Arctic sea-ice loss explaining most circulation anomalies over Eurasian high latitudes. In July, both IO warming and Arctic sea-ice loss are necessary for meridional convergence, enhanced westerlies, and thus the heavy rainfall over the Meiyu-Baiu region. Their effects are interdependent rather than additive. Strong IO warming is rarely observed alongside severe Arctic sea-ice loss before 2020 because of their discordant interannual variations. In the future, the combined effects of IO warming and Arctic sea-ice loss on the Meiyu-Baiu rainfall may become more pronounced as their long-term trends continue.

How long is the memory of forest growth to rainfall in asynchronous climates?

The out-of-phase rainfall and temperature and deep root system make the sequential connection between past rainfall events, soil water storage, and forest growth response complicated and temporally extended in asynchronous climates with Mediterranean-type settings. Unfortunately, these location-specific deep-soil water stores are rarely measured due to logistic and financial constraints, especially in the forest. Therefore, at a large spatio-temporal scale, forest growth relationship to growth drivers is still unknown in these ecosystems, limiting our knowledge to understand the functioning of these forests and their links with hydrological processes. Although process-based water balance models can analyze vegetation growth response to the input climate forcing, they rely upon some significant assumptions regarding plants access to deep soil water storage. Thus, this study aims to understand how the out-of-phase rainfall events affect the current ecosystem growth response, represented by the observed Normalized Difference Vegetation Index (NDVI), across the landscape. We have used an empirical approach on long term observed data without any assumption on access to deep-soil water stores. We estimated time lags between forest growth and rainfall events using a lagged correlation analysis applied to monthly anomalies of NDVI and rainfall against their climatological averages over 2002–2018. The study found that the forests in asynchronous climates exhibit unexpectedly long (10–25 months) memory to rain, and this memory has a systematic pattern across the landscape, which we contend has highlighted three things: 1) the forest in the middle aridity (∼3–4.5) range are relatively more sensitive to changes in the short-term rainfall than the forest in lower (<3) and higher (>5) aridity regions, could be due to rapid depletion of relatively small soil water storage in between the storms, 2) the variable memory of forest to rain across the landscape can be an indicator of soil depth/rooting depth, and 3) the variable sized location specific antecedent rainfall windows can explain significant variability in forest growth status in asynchronous climates, thus these rainfall windows can be employed to forecast forest growth with a lead time (>4 months).

Seasonal local rainfall and hydrological forecasting for Limpopo communities – A pragmatic approach

This paper describes the development and testing of a simple local seasonal forecast system of rainfall and hydrological conditions. The primary target group is agricultural extension officers who communicate forecasts to small-scale farmers at local level. Two pilot areas within the Limpopo river basin in South Africa were used, one in the Luvuvhu river basin in Vhembe district and the other in the Letaba river basin in Mopani district. Local rainfall and hydrological forecasts of runoff, soil moisture and evapotranspiration were produced, built on readily available deterministic seasonal meteorological forecasts for large-scale rainfall from CSIR (Council for Scientific and Industrial Research, South Africa), produced from an ensemble of seasonal forecasts using the CCAM (Conformal-Cubic Atmospheric Model) global forecast model. Hydrological forecasts were produced through a “proxy” approach, whereby outputs from the ACRU (Agricultural Catchment Research Unit) agrohydrological model provided expected hydrological responses from observed years that are representative of the rainfall anomalies predicted by the global seasonal forecast. Locally monitored soil moisture augmented the hydrological forecasts. The local seasonal forecast system does not require sophisticated calculations or a complex operational environment and complements coarser scale forecasts disseminated by the provincial departments of agriculture. Results of three rainfall seasons from 2013 to 2016 in the pilot areas showed the proxy approach to have relatively good matches between forecasts and available observations, showing better predictability for below normal rainfall seasons with exception for an extreme monthly rainfall event. The forecasts matched observed conditions best during the strong El Niño phase of ENSO (El Niño Southern Oscillation) for 2015/2016.

The interdecadal variations and causes of the relationship between Autumn Precipitation Anomalies in Eastern China and SSTA over the Southeastern tropical Indian Ocean

Eastern China has a large population with rapid development of the economy, where is the important crop producing region. In this region, the spatial and temporal distribution of autumn rainfall in Eastern China is uneven, which has important societal impact. Using the NCEP–NCAR reanalysis and other observational datasets, it is found that the spatial distribution of the first EOF mode of autumn rainfall anomalies in eastern China is consistent across the region, with significant interannual variabilities. Pronounced interdecadal variations are presented in the relationship between autumn rainfall anomalies in eastern China and sea-surface temperature anomaly (SSTA) over the southeastern tropical Indian Ocean (SETIO). The interdecadal changes have been analyzed by considering two epochs: one during 1979–2004 and the other during 2005–2019. It shows weak and insignificant correlations between the autumn rainfall anomalies in eastern China and SSTA over SETIO during the first epoch. On the other hand, they are remarkable and positively correlated with each other during the second epoch. The inter-decadal changes of the above relationship are related to the warming of SST over SETIO during the second epoch. It causes stronger low-level convergence and ascending motion over SETIO, with the co-occurrence of enhanced western Pacific subtropical high and anomalous abundant moisture over eastern China carried by a low-level southerly anomaly originating from the South China Sea. Simultaneously, the local Hadley circulation over eastern China becomes weak, corresponding to the anomalous ascending motion. The collaboration of anomalous water vapour transport and ascending motion strengthens the connection between the SETIO SSTA and the autumn precipitation anomalies in eastern China, and vice versa. In the boreal autumn of 2019, entire eastern China suffered extreme drought. It suggests that this drought event in eastern China is strongly affected by the negative SSTA over SETIO, which is consistent with the statistical results.

Contrasting Responses of Vegetation Production to Rainfall Anomalies Across the Northeast China Transect

AbstractIncreases in rainfall variability due to climate change influence gross primary production (GPP) in drylands, with important consequences for terrestrial carbon budget. However, it is not well understood if GPP responds in heterogeneous or even contrasting ways along the temperate bioclimate gradients. Here, based on satellite observations from 2001 to 2020, we identified rainfall anomalies as the magnitude of rainfall beyond its mean of one standard deviation, and examined differential responses of GPP to rainfall anomalies across Northeast China Transect (NECT). We found wet anomalies caused major GPP increase in western arid part of NECT, and the magnitude of increased GPP declined gradually toward the eastern humid region. As a result, GPP increased in desert steppe while decreased in mesic forest in response to wet anomalies. On the contrary, dry anomalies reduced GPP across the ecosystems except for mesic forest. The meadow steppe in the transition region between semi‐arid and sub‐humid regions, which lacks of drought‐tolerant species, showed greater GPP decline in response to dry anomalies than desert and typical steppe in the arid region. The heterogeneous responses of GPP to wet and dry anomalies resulted in contrasting asymmetries in diverse biomes, showing positive asymmetry in drier region, that is, greater magnitude of GPP increase in response to wet anomalies than GPP decrease in response to dry anomalies, and negative asymmetry in wetter region, with a transition between arid and semi‐arid regions. Our findings highlight that increased rainfall variability will enhance heterogeneous and even contrasting GPP changes along temperate bioclimate gradients.

The Equatorial Pacific Cold Tongue Bias in CESM1 and Its Influence on ENSO Forecasts

Abstract The mean-state bias and the associated forecast errors of the El Niño–Southern Oscillation (ENSO) are investigated in a suite of 2-yr-lead retrospective forecasts conducted with the Community Earth System Model, version 1, for 1954–2015. The equatorial Pacific cold tongue in the forecasts is too strong and extends excessively westward due to a combination of the model’s inherent climatological bias, initialization imbalance, and errors in initial ocean data. The forecasts show a stronger cold tongue bias in the first year than that inherent to the model due to the imbalance between initial subsurface oceanic states and model dynamics. The cold tongue bias affects not only the pattern and amplitude but also the duration of ENSO in the forecasts by altering ocean–atmosphere feedbacks. The predicted sea surface temperature anomalies related to ENSO extend to the far western equatorial Pacific during boreal summer when the cold tongue bias is strong, and the predicted ENSO anomalies are too weak in the central-eastern equatorial Pacific. The forecast errors of pattern and amplitude subsequently lead to errors in ENSO phase transition by affecting the amplitude of the negative thermocline feedback in the equatorial Pacific and tropical interbasin adjustments during the mature phase of ENSO. These ENSO forecast errors further degrade the predictions of wintertime atmospheric teleconnections, land surface air temperature, and rainfall anomalies over the Northern Hemisphere. These mean-state and ENSO forecast biases are more pronounced in forecasts initialized in boreal spring–summer than other seasons due to the seasonal intensification of the Bjerknes feedback.

Assessment of Quarterly, Semiannual and Annual Models to Forecast Monthly Rainfall Anomalies: The Case of a Tropical Andean Basin

Rainfall forecasting is essential to manage water resources and make timely decisions to mitigate adverse effects related to unexpected events. Considering that rainfall drivers can change throughout the year, one approach to implementing forecasting models is to generate a model for each period in which the mechanisms are nearly constant, e.g., each season. The chosen predictors can be more robust, and the resulting models perform better. However, it has not been assessed whether the approach mentioned above offers better performance in forecasting models from a practical perspective in the tropical Andean region. This study evaluated quarterly, semiannual and annual models for forecasting monthly rainfall anomalies in an Andean basin to show if models implemented for fewer months outperform accuracy; all the models forecast rainfall on a monthly scale. Lagged rainfall and climate indices were used as predictors. Support vector regression (SVR) was used to select the most relevant predictors and train the models. The results showed a better performance of the annual models mainly due to the greater amount of data that SVR can take advantage of in training. If the training of the annual models had less data, the quarterly models would be the best. In conclusion, the annual models show greater accuracy in the rainfall forecast.

Perceived Climate Change and Determinants of Adaptation Responses by Smallholder Farmers in Central Ethiopia

Climate change is a global phenomenon but disproportionately affects smallholder farmers, prompting them to use various coping and adaptation strategies to counter the problem. This study aimed to examine the trends of climate parameters, assess farmers’ perception of climate change, and identify the strategies of adaptation measures in central Ethiopia. Climate data were obtained from the National Meteorological Agency. Survey data were collected from 120 randomly selected households in 2017 and complemented with focus group discussions. The Mann–Kendall approach was used to detect climate trends, while a rainfall anomaly was calculated using the rainfall anomaly index. Multinomial logit model was used to examine determinants of farmers’ adaptation to the perceived change. In most of the cases, farmers’ perceptions were in accordance with climate trend analyses. Farmers used crop diversification, adjustments of planting dates, destocking of livestock, seasonal migration, crop rotation, and climate information services to adapt to climate-related shocks. Empirical results showed that the age and education of the household heads, family size, access to extension services, and farm and nonfarm incomes had a significant association with the adaptation practices farmers took. The existence of strong correlations between the demographic, socio-institutional variables, and the choice of adaptation strategies suggests the need to strengthen local institutions to enhance the adaptation of smallholder farmers to climate change.

The Effect of an Equatorial Continent on the Tropical Rain Belt. Part II: Summer Monsoons

Abstract The TRACMIP (Tropical Rain Belts with an Annual Cycle and Continent Model Intercomparison Project) ensemble includes slab-ocean aquaplanet control simulations and experiments with a highly idealized narrow tropical continent (0°–45°W, 30°S–30°N). We compare the two setups to contrast the characteristics of oceanic and continental rainbands and investigate monsoon development in GCMs with CMIP5-class dynamics and physics. Over land, the rainy season occurs close to the time of maximum insolation. Other than in its timing, the continental rainband remains in an ITCZ-like regime akin to deep-tropical monsoons, with a smooth latitudinal transition, a poleward reach only slightly farther than that of the oceanic ITCZ (about 10°), and a constant width throughout the year. This confinement of the monsoon to the deep tropics is the result of a tight coupling between regional rainfall and circulation anomalies: ventilation of the lower troposphere by the anomalous meridional circulation is the main limiting mechanism, while ventilation by the mean westerly jet aloft is secondary. Comparison of two subsets of TRACMIP simulations indicates that a low heat capacity determines, to a first degree, both the timing and the strength of the regional solsticial circulation; this lends support to the choice of idealizing land as a thin slab ocean in much theoretical literature on monsoon dynamics. Yet, the timing and strength of the monsoon are modulated by the treatment of evaporation over land, especially when moisture and radiation can interact. This points to the need for a fuller exploration of land characteristics in the hierarchical modeling of the tropical rainbands.

Distinct impacts of two types of South Asian high on the connection of the summer rainfall over India and north China

AbstractThis study reveals a distinct impact of two types of the South Asian highs (SAH)—the northern mode of the SAH (NSAH) and the traditional SAH in its entirety (ESAH)—on the relation between Indian and north China summer rainfall variation. Specifically, variation of the summer rainfall over India has a strong (weak) relation with that over north China in the anomalous NSAH (ESAH) years. In particular, in association with a reinforced and northwestward shifting NSAH, the westerly jet stream at upper‐level troposphere over mid‐latitude also enhances and shifts northward. This is accompanied by a significant circumglobal teleconnection (CGT)‐like atmospheric wave train over mid‐latitude, with two marked anticyclonic anomalies around western Asia and northeastern China. The associated southerly wind anomalies over tropical northern Indian Ocean transport more water vapour northward to India and lead to above‐normal rainfall there. In addition, the pronounced southerly wind anomalies over East Asia transport abundant water vapour to north China and also result in more rainfall over north China. The above‐normal summer rainfall and associated atmospheric heating over India help maintain the CGT wave train over mid‐latitude, which is beneficial to increasing rainfall over north China, and leading to a close connection between the Indian and north China summer rainfall variation. However, for the ESAH years, the summer rainfall anomalies over India are weak, which cannot induce an obvious CGT‐like wave train over mid‐latitude and thus have a weak impact on the rainfall over north China. Thereby, the relation between Indian and north China summer is weak for the ESAH years.

Simulation of Summer Rainfall in Thailand by IAP-AGCM4.1

Thailand is located in the Southeast Asian region, where the summer rainfall exhibits strong interannual variability, and the successful simulation of rainfall variation in Thailand by current climate models remains a challenge. Therefore, this paper evaluates the capability of the state-of-the-art Atmospheric GCM of the Institute of Atmospheric Physics (IAP-AGCM) in simulating summer rainfall over Thailand by comparing the model’s results with ground-truth observation during 1981–2012. Generally, the model shows a certain skill in reproducing the observed spatial distribution of the summer rainfall climatology and its interannual variability over Thailand, although the model underestimated both rainfall amount and its variability. Using Empirical Orthogonal Function (EOF) analysis, it is found that the IAP climate model reproduced creditably the spatial patterns of the first three dominant modes of summer rainfall in Thailand, whereas it underestimated the explained variance of the observed EOF-1 and overestimated the explained variance of the observed EOF-2 significantly. It was further found that the correlation between the observed rainfall anomalies in Thailand and the Niño3.4 index can be reproduced by the IAP model. However, the observed negative correlation is largely underestimated by the IAP climate model, and this could be the reason for the underestimation of explained variance of the EOF-1 by the IAP model. The evaluation results would be of great importance for further model improvement and thus potential application in seasonal prediction in the region.

Cropping systems intensification and diversification: risk, vulnerability and adaptation in southwest coastal Bangladesh

ABSTRACT Delta ecosystems are vulnerable to climate change from rising temperatures and altered rainfall patterns, as well as further threats from salinity and erosion due to coastline exposure. Smallholder farmers in deltas are adapting to these risks through cropping systems intensification and diversification, but it is unclear which cropping options offer better profitability and less risk and what transformational support is needed. Using qualitative and quantitative primary field data from southwest coastal Bangladesh, this research analysed risk perceptions and adaptation responses and evaluated the profitability of seven cropping systems. Rainfall anomalies, extreme weather events, and seasonal price fluctuations were core risks for farmers. Risk management strategies included adjusting sowing/transplanting dates, changing crop cultivars, increasing chemical applications, storing irrigation water, and seeking market updates. The dominant systems (rice/rice/fallow, rice/fallow/fallow) had the lowest profitability, while systems with vegetables had the highest profitability. The risk analysis estimated that the dominant systems would incur losses every three years and rice/watermelon/fallow every eight years, but vegetable- or jute-based systems’ risk was negligible. However, expanding vegetable-based systems is constrained by higher input costs, lack of capital, labour-intensive practices, market access, and persistent environmental risks. Therefore, multiple strategies are required by public and commercial actors at multiple levels to support smallholders to promote sustainable trade-offs between diverse risks, short-term profitability, and sustainable managing labour, capital, and inputs. The findings highlight the need for agricultural policies and intervention programs to address production technologies, market access, financial services, and extension and training for production and agribusiness skills.

Interannual Variations of Rainfall in Late Spring over Southwest China and Associated Sea Surface Temperature and Atmospheric Circulation Anomalies

Based on rainfall data for the period of 1960–2018 from 382 stations in southwest China and multiple reanalysis datasets, interannual variation of rainfall in late spring over Southwest China and associated sea surface temperature and atmospheric circulation anomalies are examined. The first leading mode of late-spring rainfall anomalies displays a uniform-distribution pattern. The second leading mode shows a zonal dipole pattern. The leading mode is related to an atmospheric wave train over mid-high latitudes of Eurasia, with a center of action of atmospheric anomaly over Southwest China. The atmospheric anomalies over Southwest China modulate late-spring rainfall there via modulating vertical motion and water vapor transport. In addition, the leading mode of late-spring rainfall anomalies has a close relation with sea surface temperature anomalies (SSTA) in the central and eastern equatorial Pacific. SSTA in the central and eastern equatorial Pacific impacts late-spring rainfall anomalies over Southwest China via modulation of the tropical Walker and Hadley circulation. The second leading mode of late-spring rainfall variation over Southwest China is closely associated with SSTA in the tropical western Pacific and a mid-high latitude wave train. SSTA in the tropical western Pacific and the mid-high latitudes wave train together leads to out-of-phase variation of meridional wind anomalies between western and eastern parts of Southwest China, which further results in a zonal dipole rainfall anomaly over Southwest China.

Impacts of City Shape on Rainfall in Inland and Coastal Environments

AbstractUrbanization manifests rainfall anomalies both in and around the city. While prior studies have assessed the effect of urban expansion as well as city size, little is known about the impact of city shape on rainfall. Here, idealized large eddy simulations coupled with the Weather Research and Forecasting model are conducted to bridge the knowledge gap. Results indicate differences in the timing for urban‐induced rainfall in the inland versus coastal environment. This is associated with contrasting diurnal cycles of vertical velocity and cloud water mixing ratio driven by the land‐sea breeze. The impact of city shape on rainfall is more evident in the coastal environment, as buoyancy flows arise from cities alter the interactions between urban‐rural circulation and sea breeze. A circular city shows nearly 22.0% larger rainfall accumulation and 78.6% greater rainfall intensity compared to a triangular city over urban surfaces. The rainfall anomaly is caused by different urban‐rural circulations over various city shapes. The strong low‐level convergence over circular cities favors efficient upward moisture transport and deep convection. Results highlight the need for considering city shape for coastal urban planning, as a potential adaptation strategy to manage rainfall under future climate. The coarse‐resolution climate models that represent the impervious surface area but not the right shape would have a higher uncertainty in simulating rainfall changes.

Linking Equatorial African Precipitation to Kelvin Wave Processes in the CP4-Africa Convection-Permitting Regional Climate Simulation

Abstract Observational studies have shown the link between convectively coupled Kelvin waves (CCKWs) and eastward-propagating rainfall anomalies. We explore the mechanisms in which CCKWs modulate the propagation of precipitation from west to east over equatorial Africa. We examine a multiyear state-of-the-art Africa-wide climate simulation from a convection-permitting model (CP4A) along with a parameterized global driving-model simulation (G25) and evaluate both against observations (TRMM) and ERA-Interim (ERA-I), with a focus on precipitation and Kelvin wave activity. We show that the two important related processes through which CCKWs influence the propagation of convection and precipitation from west to east across equatorial Africa are 1) low-level westerly wind anomalies that lead to increased low-level convergence, and 2) westerly moisture flux anomalies that amplify the lower- to midtropospheric specific humidity. We identify Kelvin wave activity using zonal wind and geopotential height. Using lagged composite analysis, we show that modeled precipitation over equatorial Africa can capture the eastward-propagating precipitation signal that is associated with CCKWs. Composite analysis on strong (high-amplitude) CCKWs shows that both CP4A and G25 capture the connection between the eastward-propagating precipitation anomalies and CCKWs. In comparison to TRMM, however, the precipitation signal is weaker in G25, while CP4A has a more realistic signal. Results show that both CP4A and G25 generally simulate the key horizontal structure of CCKWs, with anomalous low-level westerlies in phase with positive precipitation anomalies. These findings suggest that for operational forecasting, it is important to monitor the day-to-day Kelvin wave activity across equatorial Africa.

Potential risks of climate variability on rice cultivation regions in the Mekong Delta, Vietnam

ABSTRACT In recent decades, the rice cultivation regions in the Mekong Delta have continuously suffered from unprecedented weather events due to a decline in rainfall as part of climate variability. The aim of this study was to perform a comprehensive exploration of the rainfall characteristics across the area, applying the Rainfall Anomaly Index (RAI), Spearman Rho test and Sen slope estimator to help track the weather as well as provide warnings on the potential risks caused by alterations in rainfall amounts. For this goal, the rainfall data sequences at 14 national observation stations across the Mekong Delta were collected for the 1984 - 2019 period. Results indicated that the dry weather seasons occurred more frequently during the normally wet weather seasons. Four typical dry weather seasons were identified for the 1997 - 1998, 2002 - 2004, 2014 - 2016, and 2018 - 2019 periods. Among these, the 2014 - 2016 period was the driest, with 9 out of 12 stations in the area being extremely dry and RAI risk peaks as high as -4.86 at the Moc Hoa station in the province of Long An. A weather trend of decreasing rainfall was evident, mainly in the coastal sub-regions. The discovery of changing rainfall trends is valuable for predicting future climate variability.

Assessment of the Impact of Rainfall Variability and Vegetable Production in Bamenda III Sub-Division, Cameroon

Climate variability has a direct bearing on agricultural production. The relationship between temperature and rainfall provides ideal conditions for the development of crops in rain-fed agricultural systems. This is patent in predominantly rain-fed vegetable production exposed to rainfall variability. This study assesses the impact of rainfall variability on vegetable production in Bamenda III Sub-Division. The data on rainfall was collected for 54 consecutive years (1963–2017) and analysed using Rainfall Anomaly Index to determine the Inter-Annual Rainfall Anomalies. This was to determine the extent of rainfall variability impacts on vegetable production. Results revealed a reliable but fluctuating periodical rainfall rates with highest positive and negative anomalies of +60mm and -55mm respectively. With a Standardized Precipitation Index of 0.41, there was evidence of an increasing trend in decadal rainfall and positive trend on conditions for vegetable cultivation. The high variability of rainfall is associated with a reduction in vegetable production output. Such rainfall variability plays a major role in vegetable production which is generally rain fed. The study posits that stakeholders’ responsive adaptation options in cropland management for vegetable production in the phase of rainfall variability are credible in reversing the increasing negative impact of rainfall variability in the context of climate change.

Variability of the Minor Season Rainfall over Southern Ghana (1981–2018)

The monitoring of rainfall variability over recent decades has become a necessity due to its devastating effects such as floods and droughts, which render humans vulnerable across different parts of the West African region. The current study seeks to provide a good understanding of variability within the minor rainfall season over southern Ghana by employing statistical tools to quantify variability in rainfall. Daily rainfall data from 1981 to 2018 for seventeen (17) synoptic weather stations across southern Ghana are used for this analysis. We perform trend and descriptive statistics of rainfall amount and extreme indices intending to identify the areas with the greatest variability in rainfall. Further, for five recent years (2014–2018), we do an interpolation of the ground station rainfall data and compute anomalies. We find increasing trends of rainfall in the minor rainy season for 16 out of the 17 stations, with rainfall increasing between 0.10 mm and 4.30 mm each season. For extreme rainfall indices, the 17 stations show nonsignificant trends of very wet and extremely wet days. We also find that the middle parts of Ghana have the highest rainfall amounts (262.7 mm/season–400.2 mm/season), while the East Coast has the lowest (125.2 mm/season–181.8 mm/season). Over the whole of southern Ghana, we find high variability in rainfall amount with the coefficient of variations (CV) between 25.3% and 70.8% and moderate to high variability in rainfall frequency (CV = 14.0%–48.8%). The results of rainfall anomalies show that the middle parts had an above-normal rainfall amount. In the same period, the transition areas experienced below-normal rainfall. Our finding of high variability in the minor rainfall season has implications for agricultural productivity in Ghana and countries in the West African region, which rely heavily on rain-fed agriculture. Hence, this study recommends more research to understand the causes of variability in the West African monsoon and how this will change in the region.

Rainfall and other meteorological factors as drivers of urban transmission of leptospirosis.

BackgroundLeptospirosis is an important public health problem affecting vulnerable urban slum populations in developing country settings. However, the complex interaction of meteorological factors driving the temporal trends of leptospirosis remain incompletely understood.Methods and findingsFrom March 1996—March 2010, we investigated the association between the weekly incidence of leptospirosis and meteorological anomalies in the city of Salvador, Brazil by using a dynamic generalized linear model that accounted for time lags, overall trend, and seasonal variation. Our model showed an increase of leptospirosis cases associated with higher than expected rainfall, lower than expected temperature and higher than expected humidity. There was a lag of one-to-two weeks between weekly values for significant meteorological variables and leptospirosis incidence. Independent of the season, a weekly cumulative rainfall anomaly of 20 mm increased the risk of leptospirosis by 12% compared to a week following the expected seasonal pattern. Finally, over the 14-year study period, the annual incidence of leptospirosis decreased significantly by a factor of 2.7 (8.3 versus 3.0 per 100,000 people), independently of variations in climate.ConclusionsStrategies to control leptospirosis should focus on avoiding contact with contaminated sources of Leptospira as well as on increasing awareness in the population and health professionals within the short time window after low-level or extreme high-level rainfall events. Increased leptospirosis incidence was restricted to one-to-two weeks after those events suggesting that infectious Leptospira survival may be limited to short time intervals.

Understanding rainfall prediction skill over the Sahel in NMME seasonal forecast

Sahelian rainfall presents large interannual variability which is partly controlled by the sea surface temperature anomalies (SSTa) over the eastern Mediterranean, equatorial Pacific and Atlantic oceans, making seasonal prediction of rainfall changes in Sahel potentially possible. However, it is not clear whether seasonal forecast models present skill to predict the Sahelian rainfall anomalies. Here, we consider the set of models from the North American Multi-model ensemble (NMME) and analyze their skill in predicting the Sahelian precipitation and address the sources of this skill. Results show that though the skill in predicting the Sahelian rainfall is generally low, it can be mostly explained by a combination of how well models predict the SSTa in the Mediterranean and in the equatorial Pacific regions, and how well they simulate the teleconnections of these SSTa with Sahelian rainfall. Our results suggest that Sahelian rainfall skill is improved for those models in which the Pacific SST—Sahel rainfall teleconnection is correctly simulated. On the other hand, models present a good ability to reproduce the sign of the Mediterranean SSTa—Sahel teleconnection, albeit with underestimated amplitude due to an underestimation of the variance of the SSTa over this oceanic region. However, they fail to correctly predict the SSTa over this basin, which is the main reason for the poor Sahel rainfall skill in models. Therefore, results suggest models need to improve their ability to reproduce the variability of the SSTa over the Mediterranean as well as the teleconnections of Sahelian rainfall with Pacific and Mediterranean SSTa.