Total Annual Precipitation Research Articles

Spatiotemporal Variations in Light Precipitation Events in the Yellow River Basin, China, and Relationships with Large-Scale Atmospheric Circulation Patterns

Light precipitation events are an essential feature of rainfall for agricultural production, risk prediction of drought or flood disasters, and natural resource management in a certain area. We investigated the spatiotemporal variations in light precipitation events with intensities of 0.1–10 mm/day, based on daily precipitation data for the Yellow River Basin (YRB), China, during 1960–2018, and explored their relationships with large-scale atmospheric circulation patterns (LSACPs) and altitude. For further analysis of the changes in the light precipitation events, we classified light rain (0.1 ≤ P < 10.0 mm/day) into five grades of intensity by using equal interval division. Results indicate that the mean annual light precipitation amount and days were 182.7 mm and 80 days, respectively, from 1960 to 2018 over the YRB, accounting for 39.2% and 85.2% of the total annual precipitation amount and days, respectively. Both the amount of light rain and the number of light precipitation days declined by −1.3 mm/decade and −1.4 days/decade, respectively, and suggested that most rain events were of low intensity (0.1 ≤ P < 2.0 mm/day). Light precipitation events mainly occurred in the upper and middle reaches of the YRB and decreased from the southwest to the north. Additionally, changes in light rain events appear to be complex and possibly related to LSACPs and altitude. We found that the LSACPs were a possible mechanism for light precipitation events in the YRB over the past decades. With increasing elevation, light precipitation events decreased significantly throughout the study period. Thus, the decrease in precipitation days mainly occurred at lower altitudes in the YRB. The results also reflect the complexity of regional climate change in the YRB because atmospheric circulation related to climate phenomena not only causes the complex variation in precipitation but also changes its altitude dependence.

Climate extremes related with rainfall in the State of Rio de Janeiro, Brazil: a review of climatological characteristics and recorded trends.

This paper presents a synthesis of the main characteristics of precipitation in the State of Rio de Janeiro (Brazil) based on extreme rainfall indicators. Daily precipitation data are derived from 56 rainfall stations during the second half of the twentieth century and the 2000s. Eight indices related to extreme precipitation were analyzed. The Mann–Kendall nonparametric test and the Sen's Curvature were employed to evaluate the significance and magnitude of trends. The primary climatological aspects and identified trends throughout the last decades are discussed, besides the hydrometeorological impacts associated with them. Lower values of annual total precipitation are recorded in northern Rio de Janeiro (around 800 mm) and higher in the southern State (up to 2,200 mm). The Serra do Mar affects the frequency of heavy precipitation, and the areas near the sea and high relief present the highest values of consecutive days with expressive rainfall (more than 150 mm in 5 days). These areas also showed a high concentration of flood and landslides events. Most of Rio de Janeiro exhibits precipitation intensity of about 13 mm/day. The maximum number of consecutive dry days shows a gradient from the coast (about 30 days) to the State's interior (around 50 days). Regarding trends, there is a growth of accumulated extreme precipitation in various stations near the ocean. The extreme rainfall in 24 h displays an increase in most Rio de Janeiro (+ 1 to + 5 mm/decade). The consecutive dry and rainy days present similar signs of decreasing trends, suggesting irregularly distributed precipitation in the State. This study is especially relevant for decision-makers who need detailed information in the short and long term to prevent natural hazards like floods and landslides and the related impacts in the environmental and socioeconomic sectors of the Rio de Janeiro.

Analysis of Climate Change Indices in Musanze District, Rwanda

This study used daily rainfall, minimum temperature, and maximum temperature data from the Rwanda Meteorology Agency (Meteo Rwanda) for the years 1983 - 2016 to analyze climate change indices in the Musanze district of Rwanda. Rainfall and temperature extreme indices were determined using the methodology provided by Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI). Climate Data Tool (CDT), which is R-based package developed by International Research Institute for Climate and Society (IRI) was used to compute the indices. Sen's slope estimator and the modified Mann-Kendall (m-MK) test were both applied to identify trends and determine the degree of change. The Monthly Temperature (TXx, TXn, TNx, and TNn) indices generally showed a warming in the eastern and a cooling in the western parts of the district, according to the trend results; however, the Minimum tail of temperature indices showed a slightly reduced cooling which is a sign of warm nights and hot days in highland areas of volcanic region. For the same period, the district's eastern regions have higher precipitation intensity and wetness, which gradually declines toward the middle and western regions. In addition, a considerable upward trend in the annual total precipitation for days above the 95th percentile (very wet days) and the annual count for precipitation equal or greater than 20 mm (very heavy precipitation days). Additionally, temperature indices showed a large rise in the minimum and maximum values of daily minimum temperatures, annual minimum and maximum values of daily maximum temperatures, and the percentage of days with daily maximum temperatures above the 90th percentile (warm days). In view of these evolving trends in weather and climate patterns, the study recommends local farmers and other stakeholders involved in socioeconomic activities in the district to implement the necessary climate change mitigation and adaptation measures.

Temporal Trends in Agriculturally Relevant Climate Indicators across Nine Agroecosystems of Turkey

Abstract An interaction of trends in a multitude of climate indicators dictate how agricultural production and resource use will be affected. Turkish agroecosystems have not been evaluated for climate trends, especially focusing on spatial and temporal domains relevant for agricultural production. Long-term (1981–2017) temporal trends in agriculturally relevant climate indicators [maximum (Tmax), minimum (Tmin), and mean (Tavg) air temperatures, diurnal temperature range (DTR), growing degree-days (GDD), precipitation, incoming shortwave radiation (Rs), relative humidity (RH), wind speed (u2), saturated and actual vapor pressure (es and ea), vapor pressure deficit (VPD), grass- and alfalfa-reference evapotranspiration (ETo and ETr), and aridity index (AI)] across Turkey (Turkiye) were quantified and analyzed using the NASA-POWER dataset at 0.5° × 0.5° grid cells (n = 323) for nine agricultural zones (AZs) in Turkey. At the growing-season scale, Tmin, Tmax, Tavg, GDD, es, ea, VPD, Rs, precipitation, RH, and AI showed statistically significant positive trends at 100%, 76%, 100%, 100%, 94%, 98%, 22%, 83%, 33%, 10%, and 13% of Turkey’s terrestrial area, respectively. Negative trends were observed in growing-season-scale DTR, u2, ETo, and ETr at 38%, 38%, 10%, and 18% of the total terrestrial area, respectively. At the annual scale, ETo and ETr showed increasing trends over 37% and 19% of the area, respectively. Evaporative demand showed national mean trends of −2.6 and −4.1 mm yr−1 during the growing season, respectively. Aegean AZ showed the most negative trends in growing-season ETo and ETr. The national mean magnitude in annual total precipitation (4.7 mm yr−1) was 39% greater than that in growing-season total precipitation (3.4 mm yr−1).

Glaciers of the Koryak Highlands: assessment of the state using satellite images and field studies

The Koryak Highlands are a poorly explored area in terms of glaciation and its connection to climate. The purpose of this work is, using Sentinel-2 images (2019), to assess the state of glaciers at present against the background of climatic trends. Spatial patterns of trends of mean summer and annual temperatures, total precipitation and precipitation for the cold period from 1966 to 2019 were compiled: the temperature trends increase towards the Kamchatka Peninsula, and the mean summer temperature trends increase from 2 to 3°C. Precipitation trends increase from the continent to the coastal zone, with cold season trends changing from 0 to minus 50 mm. As a result, 212 glaciers and 279 rock glaciers were discovered in the Highlands, whereas 112 objects that had previously been recognised were not identified: either there is no glacier, or its area is less than 0.001 km2. The reduction in glacier areas compared to the USSR Glacier Inventory (1960s) varies widely by river basin, from 35 to 74%. The mean present glacier area varies from basin to basin from 0.4 to 0.11 km2. The glaciers are mainly corrie type of the N, NE and NW aspects. The change of average glacier firn line is from several tens of metres to 400–500 m.

Modeling groundwater nitrate concentrations using spatial and non-spatial regression models in a semi-arid environment

Nitrate nitrogen (NO3−-N) from agricultural activities and in industrial wastewater has become the main source of groundwater pollution, which has raised widespread concerns, particularly in arid and semi-arid river basins with little water that meets relevant standards. This study aimed to investigate the performance of spatial and non-spatial regression models in modeling nitrate pollution in a semi-intensive farming region of Iran. To perform the modeling of the groundwater's NO3−-N concentration, both natural and anthropogenic factors affecting groundwater NO3−-N were selected. The results of Moran's I test showed that groundwater nitrate concentration had a significant spatial dependence on the density of wells, distance from streams, total annual precipitation, and distance from roads in the study area. This study provided a way to estimate nitrate pollution using both natural and anthropogenic factors in arid and semi-arid areas where only a few factors are available. Spatial regression methods with spatial correlation structures are effective tools to support spatial decision-making in water pollution control.

Estimation of design precipitation in Beijing–Tianjin–Hebei region under a changing climate

ABSTRACT Under changing environments, conventional methods based on an assumption of stationarity can lead to unreliable estimates of design rainfall quantiles. In this study, the trend of six extreme precipitation indices in the Beijing–Tianjin–Hebei region was analysed using different methods. Nonstationary models were established for annual maximum one-day precipitation (RX1d) and annual total precipitation when daily precipitation is greater than 95% of daily precipitation in a year (R95p) exhibiting significant trend, while stationary models were established for the two indices showing no significant trend. Finally, the nonstationary and stationary design precipitation were estimated using the average design life level method and the stationary method, respectively. The results indicated that for some stations in the east and south, a significant decreasing trend was observed for RX1d and R95p. This resulted in the overestimation of their design precipitation using the stationary methods and altering the spatial distribution of precipitation extremes for future period near these stations.

Correlation between climate and flood indices in Northwestern Italy at different temporal scales

Abstract The occurrence of river floods is strongly related to specific climatic conditions that favor extreme precipitation events leading to catchment saturation. Although the impact of precipitation and temperature patterns on river flows is a well discussed topic in hydrology, few studies have focused on the relationship between peak discharges and standard Climate Change Indices (ETCCDI) of precipitation and temperature, widely used in climate research. It is of interest to evaluate whether these indices are relevant for characterizing and predicting floods in the Alpine area. In this study, a correlation analysis of the ETCCDI indices annual time series and annual maximum flows is presented for the Piedmont Region, in North-Western Italy. Spearman’s rank correlation is used to determine which ETCCDI indices are temporally correlated with maximum discharges, allowing to hypothesize which climate drivers better explain the interannual variability of floods. Moreover, the influence of climate (decadal) variability on the tendency of annual maximum discharges is examined by spatially correlating temporal trends of climate indices with temporal trends of the discharge series in the last twenty years, calculated using the Theil-Sen slope estimator. Results highlight that, while extreme precipitation indices are highly correlated with extreme discharges at the annual timescale, with different indices that are consistent with catchment size, the decadal tendencies of extreme discharges may be better explained by the decadal tendencies of the total annual precipitation over the study area. This suggests that future projections of the annual precipitation available from climate models simulations, whose reliability is higher compared to precipitation extremes, may be used as covariates for non-stationary flood frequency analysis.

Spatial analysis of echinococcosis in pastoral area of Qinghai province, 2019

Objective: To understand the spatial characteristics of echinococcosis and associated factors in the pastoral area of Qinghai province, and provide evidence for the effective prevention and control of echinococcosis. Methods: The number of echinococcosis cases in the pastoral areas of Qinghai in 2019 was collected to perform spatial epidemiological analysis. The thematic map of the distribution of echinococcosis cases was generated with software ArcGIS 10.8 for visual analysis and spatial autocorrelation analysis. The spatial autocorrelation and spatial scanning analysis were performed to estimate the clustering of echinococcosis with software SaTScan 9.5. Software GeoDa 1.14 and ArcGIS 10.8 were used to establish spatial lag model and geographical weighted regression model to analyze the related factors of echinococcosis epidemic. Results: In 2019, the echinococcosis surveillance covered 64 741 people in the pastoral area of Qinghai, and 829 echinococcosis cases were found, with a prevalence rate of 1.28%. The distribution of the cases had spatial correlation (Moran's I=0.41, P<0.001). The most possible clustering areas indicated by spatial scanning analysis included Banma, Jiuzhi, Dari and Gande counties of Guoluo Tibetan Autonomous Prefecture (LLR=460.77, RR=9.20, P<0.001). The prevalence of echinococcosis in the pastoral areas was positively associated with the total annual precipitation (β=0.13, P=0.036), and negatively associated with population density (β=-1.36, P=0.019) and doctors/nurse ratio (β=-25.60, P=0.026). Conclusions: The distribution of echinococcosis cases in the pastoral areas of Qinghai in 2019 had spatial correlation, and the prevalence was affected by total annual precipitation, population density, and doctors/nurse ratio.

Spatiotemporal Variations and Climatological Trends in Precipitation Indices in Shaanxi Province, China

Precipitation, as an important part of the hydrological cycle, is often related to flood and drought. In this study, we collected daily rainfall data from 21 rainfall stations in Shaanxi Province from 1961 to 2017, and calculated eight extreme climate indices. Annual and seasonal concentration indices (CI) were also calculated. The trends in the changes in precipitation were calculated using the M–K test and Sen’s slope. The results show that the precipitation correlation index and CI (concentration index) in Shaanxi Province are higher in the south and lower in the north. For the annual scale, the CI value ranges from 0.6369 to 0.6820, indicating that Shaanxi Province has a high precipitation concentration and an uneven distribution of annual precipitation. The eight extreme precipitation indices of most rainfall stations showed a downward trend during the study period, and more than half of the stations passed the 0.05 confidence interval test. Among them, the Z value of PRCPTOT (annual total precipitation in wet days) at Huashan station reached −6.5270. The lowest slope of PRCPTOT reached −14.3395. This shows that annual rainfall in Shaanxi Province has been decreasing in recent decades. These findings could be used to make decisions about water resources and drought risk management in Shaanxi Province, China.

A Terrestrial‐Aquatic Model Reveals Cross‐Scale Interactions Regulate Lateral Dissolved Organic Carbon Transport From Terrestrial Ecosystems

AbstractLateral carbon transport (LCT), the flux of terrestrial C transported to aquatic ecosystems, displaces carbon (C) across the terrestrial‐aquatic continuum and is on the same order of magnitude as terrestrial net ecosystem production. However, few continental scale C models include LCT or the C‐hydrology linkages necessary for modeling LCT. Those that do exist, borrow processes and conceptual understanding from watershed scale models, assuming that large‐scale and small‐scale drivers of LCT are the same. We develop a conceptual framework of LCT, which focuses on lateral dissolved organic carbon (DOC) transport (LCT‐DOC), and operationalize it with a coupled terrestrial‐aquatic C and hydrology model. After comparing our model LCT‐DOC to previous estimates derived from a summation of landscape scale fluxes for the Contiguous U.S., we use model experiments to partition the importance of LCT‐DOC drivers including total annual precipitation, air temperature, and plant traits, which interact across regional and local scales. We find that climate is the strongest driver of LCT‐DOC, where LCT‐DOC is positively related to precipitation but inversely related to temperature at continental scales. However, the net effect of climate on LCT‐DOC is the product of cross‐scale interactions between climate and vegetation. Plant traits also interact strongly with climate and have a measurable influence on LCT‐DOC, with water use efficiency as the most influential plant trait because it couples terrestrial water and C cycling. We demonstrate that our conceptual framework and relatively simple linked C‐hydrology process model of LCT‐DOC can inform hypotheses and predict LCT‐DOC.

Occurrence of Microplastics from Plastic Fragments in Cultivated Soil of Sichuan Province: The Key Controls

With the continuous increase in the amount of mulch film, “white pollution” caused by plastic fragments (PF) has seriously affected agricultural production progress and poses a great threat to the safety and health of the agricultural environment. In the present study, PFs collected from 20 mulched agricultural farmlands in Sichuan Province were investigated. The PFs were separated and screened following the density flotation method. Optical microscopy was used to assess the fragments’ distribution, abundance, color, size, and morphology, and Raman spectroscopy was used to identify the types. In addition, through the analysis of a questionnaire survey, a random forest (RF) model was conducted to assess the effects of environmental factors on the amount of PF. The results showed that the abundance of PFs was the highest in Lade Town, Zigong City, reaching 1158.33 ± 52.04 particles kg−1. Meanwhile, PFs were less abundant in Foyin Town, Luzhou City, with 50.00 ± 25.00 particles kg−1; the morphology features of PF in the cultivated soil were mainly transparent (60.06%) and flaky-like (83.41%), with sizes &lt; 5 mm (63.61%). In total, 75% of the representative PFs were PE PFs, while PVC PFs were 25%. The RF model indicated that there were significant effects due to the total mulch film amount, annual precipitation, and planting pattern on the number of derived residues (PF). This study provides data indicating the urgent need to prevent and control plastic pollution in mulch farming, specifically in the soils of Sichuan Province.

Twentieth century precipitation trends in the upper Mzingwane sub-catchment of the northern Limpopo basin, Zimbabwe

This study evaluates precipitation trends in the upper Mzingwane sub-catchment (UMS) of Zimbabwe using ten World Meteorological Organization (WMO)’s Expert Team for Climate Change Detection Monitoring and Indices climate indices. Trend analysis for variables such as annual total precipitation, extremely wet days, consecutive wet and dry days is analysed. The UMS is of strategic socio-economic significance in terms of water security and sustenance to livelihoods in this region and the city of Bulawayo. The analysis is undertaken at four stations: Bulawayo Goetz, Filabusi, Mbalabala and Matopos National Park (MNP), for the period 1921–2000. In general, no statistically significant trends were detected for all indices in all stations (with the exception of MNP (in the westernmost extent of UMS)) which showed significant increasing (decreasing) trends for most dryness (total precipitation) extreme indices. This is indicative of persistent drying coupled with a shift towards shorter very wet periods with more intense precipitation in the past twentieth century. There is also an indication of a general north to south-western declining precipitation gradient during the past ~ 69 years over this region. These findings are not only useful in explaining the historical evolution of observed extremes and their associated socio-economic impacts but also present a baseline for comparative follow-up studies assessing the twenty-first century and future trends in precipitation extreme events in the UMS.

Identification of homogeneous regions based on rainfall in the Amazon River basin

AbstractThe identification of homogeneous rainfall regions facilitates the prioritization of watershed management measures. In the present study, it was applied the methodology of data clustering by the non‐hierarchical method of fuzzy C‐means, having as variables the geographic coordinates (latitude and longitude) and average annual precipitation, provided by the Global Precipitation Climatology Center (GPCC). The group formations were validated by Silhouette, PBM, Dunn, Davies Bouldin, and Xie Beni. The total annual precipitation values found for the regions are consistent with the precipitation volume recorded in the analysed region and found in the literature. The results presented satisfactory data from the application of the methodology, from which six homogeneous regions of well‐defined precipitation were formed, each with its own particularity, demonstrating the spatial–temporal variability of annual precipitation totals in the region. When analysing the climatological normals in relation to previous studies, a change in rainfall behaviour was noted, with changes occurring in the months with higher and lower average rainfall records in the area, mainly in homogeneous regions (HRs) 3 and 6. HRs 1 and 6 showed a unique behaviour, with their climatological normals different from the others.

EFFECT OF CLIMATE CHANGE ON GRAPEVINES PHENOLOGICAL STAGES AND YIELD UNDER ARID ENVIRONMENT

Climate change is a dramatic crisis that has left severe impacts on the agricultural sector and especially on viticulture. Phenological sets over 41 years and annual climatic anomalies ’data over the same years’ intervals were procured. An earliness in Al Ahsa region, the first signs of climate change were detected starting 1997, where annual precipitable water and temperature anomalies were the most important climate influencers all phenological events occurred for the varieties White and Red, from the beginning of budburst until harvest. Moreover, the yield of both varieties was slightly reduced between 1997 and 2019 in comparison with the interval of years 1979-1996. Beginning of budburst, budburst, 2-3 leaves unfolded and visible inflorescence were positively correlated with the annual wind speed anomaly. Beginning of flowering, full flowering, beginning of fruit set, full veraison, and harvest were positively with the annual total cloud cover anomaly and annual total precipitation anomaly. In addition, the full fruit set and beginning of veraison were positively correlated with annual wind speed anomaly, and negatively correlated with annual precipitable water anomaly. Yield was positively correlated with annual total precipitation anomaly and annual total cloud cover anomaly. Results suggest the adoption of a drip irrigation system in Al Ahsa vineyards that would overcome the low water availability in hot summers and reduce soil salinity, one of the biggest issues facing Gulf countries.

POTENTIAL DISTRIBUTION OF DOMESTICATED Sechium edule (CUCURBITACEAE) IN MEXICO

Mexico is the centre of origin of the chayote (Sechium edule (Jacq.) Sw), an important plant in human consumption and in pharmaceuticals. The objective of this study was to determine the potential distribution of domesticated S. edule in Mexico using seven species distribution algorithms, to efficiently manage S. edule resources and help its conservation by identifying patterns of geographic distribution. Otherwise, areas of high suitability can be used to produce improved seed at a lower cost. 162 GBIF occurrence points and nine layers in raster format were used to evaluate seven algorithms of species distribution models. To evaluate the reliability and performance of the models, the statistics Area Under the Curve (AUC) and true skill statistic was used. Predominant climate types were Cwb (33.3 %) and Aw (17.9 %); predominant soil types were leptosol (33.3 %) and phaozem (16.7 %). The seven models showed areas of high suitability (&gt; 0.75) in Chiapas, Guerrero, Oaxaca, Veracruz, Tabasco, Puebla and Hidalgo states. AUC values for the seven models were &gt; 0.8 and their performance was adequate (0.4 &gt; TSS &lt; 0.7). Classification tree analysis was found to be the best algorithm measured by AUC (0.90); however, the seven models were adequate to explain S. edule distribution in Mexico. S. edule climatic adaptability also allows to be distributed towards the Yucatan Peninsula and western Mexico. The distribution of S. edule in Mexico, according to the studied algorithms, is limited to total annual precipitation and temperature seasonality.

Пространственно-временные особенности распределения осадков на территории Азербайджана

The characteristics of spatiotemporal distribution of the amount of precipitation within the territory of the Republic of Azerbaijan between 1961 and 2016 were investigated using observational data from 45 hydrometeorological stations. Main attention is paid to regional features. The statistical analysis for three time periods — 1881–1960, 1961–2016 and 1991–2016 — showed that an increase in average annual total precipitation was registered in most of the country in 1961–2016 as opposed to 1881–1960. In addition to this, a decrease in average annual total precipitation for 1991–2016 as compared to 1961–1990 was found for most stations. The results of the study may be useful for scientific research, as well as for developing and implementing projects in agriculture and other economic sectors. Keywords: climate change, precipitation, relief, local process, convective cloudiness, downpour, Doppler radars

East African population exposure to precipitation extremes under 1.5 °C and 2.0 °C warming levels based on CMIP6 models

Understanding population exposure to precipitation-related extreme events is important for effective climate change adaptation and mitigation measures. We analyze extreme precipitation using indices (EPIs), including consecutive dry days (CDD), annual total precipitation, simple daily intensity, and the number of extremely wet days, under the past and future climatic conditions over East Africa. The exposure of the East African population to these extreme events at 1.5 °C and 2.0 °C global warming levels (GWLs) is analyzed based on Climate Model Intercomparison Project phase 6 models. Exposure is computed from extremely wet and dry days (R95p and CDD, respectively). Under both GWLs, EPIs (except CDD) averaged over East Africa are projected to increase under the Shared Socio-economic Pathways (SSP)2-4.5 and SSP5-8.5 scenarios. The largest increase in wet events will likely occur in eastern and northern Kenya. The results also reveal an intensification of precipitation extremes over Burundi, Rwanda, and some parts of Uganda. However, small changes are expected over most parts of Kenya and Tanzania. Examination of population exposure to EPIs shows that the most prominent and net intense occurrence is over Burundi, Rwanda, and some parts of Uganda. In contrast, less change is noted to occur over vast parts of Kenya and Tanzania. Meanwhile, limiting the warming target to less than 1.5 °C but not more than 2.0 °C has 37% (44.2%) and 92% (4%) less impact on the occurrence of EPIs for R95p (CDD) under SSP2-4.5 (SSP5-8.5) scenarios, respectively. The study establishes that future exposure is predominantly driven by changes in population compared to other factors such as climate or concurrent changes in climate and population (the nonlinear interaction effect). For instance, climate effects are anticipated to contribute ∼10.6% (12.6%) of the total change in population exposure under 1.5 °C (2.0 °C) warming levels, while population and interaction effects are expected to contribute ∼77.4% (71.9%) and 12% (15.5%), respectively, under 1.5 °C (2.0 °C) scenarios. Interestingly, the projected changes in regional exposure due to the interaction effects under SSP2-4.5 are greater than the climate effect, while the reverse pattern is observed under SSP5-8.5. For example, under SSP5-8.5, climate effects for 1.5 °C and 2.0 °C are larger (after population effect) with ∼3.8 × 105 (15.7%) and ∼6.1 × 105 (17.5%) billion person-mm, respectively. The high exposure noted over East Africa calls for a shift in policies to instate suitable adaptation measures to cushion the already vulnerable population.

Discrepancies in changes in precipitation characteristics over the contiguous United States based on six daily gridded precipitation datasets

Variability and spatiotemporal changes in precipitation characteristics can have profound socioenvironmental impacts. Several studies have shown that the frequency and/or magnitude of precipitation events have changed over the contiguous United States (CONUS) in the past decades. Most previous studies used only one precipitation dataset and only investigated mean or extreme precipitation. Here, using 6 gridded daily precipitation datasets, we show that there are substantial discrepancies in the changes in characteristics of both extreme and non-extreme precipitation events from 1983 to 2017. Our results highlight that using a single record to study precipitation changes can potentially lead to biased results. Using different datasets enables examining the overall agreements and discrepancies in precipitation characteristics. For example, we show that almost all datasets agree that some areas show statistically significant changes in the annual precipitation maxima; however, the locations and signs of changes are not consistent across datasets. There is a relative agreement between datasets on changes in the total annual precipitation. When examining other percentiles of the precipitation distribution, including non-extreme values, however, we find widespread discrepancies among different precipitation products (e.g., what part of the precipitation distribution is changing). In fact, depending on the source of data, there exist opposing trends and patterns of change in precipitation characteristics. This highlights the need to further investigate non-extreme precipitation events to unravel potential non-extreme but “unexpected” or “unusual” patterns. Finally, we argue that protocols for data selection are needed to address the issue of inter-data variability and to ensure reliability of statistical analysis.

Seasonal Pattern of Hand Foot and Mouth Disease in an Out-patient Clinic of a Tertiary Care Pediatric Hospital at Dhaka

Background &amp; Objective: Hand, foot and mouth disease (HFMD) is a contagious disease of children, occurs primarily under five years of age, characterized by a history of brief febrile illness and a typical skin rash over hands and feet with or without sores in mouth, caused usually by Coxsackievirus A16 viruses. It is mainly the disease of tropical and subtropical countries and bears a complex-relation with meteorological variables, like temperature, rainfall and relative humidity, although no study has yet been done in Bangladesh to explain the complex relationship of the disease with these variables. This study sought to describe the occurrence of HFMD and its association with meteorological factors in Dhaka city.&#x0D; Methods: The present cross-sectional study collected data of 231 HFMD cases from the records of the daily register of Out-patient Department of Dhaka Shisu Hospital, Dhaka between January 2018 to December 2019. According to the study protocol a child was identified as having HFMD who had a history of brief febrile illness accompanied by a typical skin rash with or without mouth ulcers. Total number of cases treated monthly at OPD during the period were also recorded. Meteorological data were provided by Bangladesh Meteorological Department, which among others, included monthly average temperature, relative humidity and amount of rainfall. While the outcome variable was monthly number of HFMD cases, the predictive variables were average temperature, humidity and rainfall during the study period.&#x0D; Result: Majority (85.3%) children in the present study was &lt; 5 years old. A male preponderance was observed in the series (60%) with male to ratio being 3:2. A clustering of HFMD cases was observed to occur between June to October when monthly average temperature, total rainfall and humidity all were at their maximum compared to those found between November to April. The clustering of cases was more intense in the year 2019 than that in the year 2018. During the period average monthly temperature was 29.20C, average rainfall was 62.6% (238 mm) of the total annual precipitation and mean relative humidity was 79%. The proportion of HFMD cases out of total cases treated during the period was 2.2% in 2018 and was 4.1% in 2019, which in the dry season (November to April) was 0.4% and 0.5% in 2018 and 2019 respectively.&#x0D; Conclusion: The study concluded that majority of the HFMD cases occur under five years of age and boys are more likely to have the infection than the girls. A seasonality of HFMD occurrence is observed with a higher number of cases occurring in the monsoon season and fewer cases in the dry season. Clustering of HFMD cases occur between May to October when monthly average temperature, total rainfall and humidity all are at peak compared to those in November to April of the year.&#x0D; Ibrahim Card Med J 2021; 11 (1): 14-20