The climate, particularly rainfall, in East Africa is known for its inter-annual variability, which has contributed to the devastating droughts and floods 5, 8. In Africa, particularly East Africa, more than 80% of the population depends on agriculture and the income from this sector contributes about 40% to the regional GDP 7. Africa is one of the most vulnerable continents to climate change and variability due to its low adaptive capacity 5 and a change in climate variables may lead to significant reduction in agricultural production 6. In particular, the impact of climate variability and change on the agriculture sector is significant 4, threatening food security and livelihoods particularly in developing countries 3. The increase in air temperature and variability in precipitation are already evident in different parts of the world and their impacts on the environment (e.g., ecosystem and biodiversity) and human system are becoming evident 3. Global climate has changed in recent decades and exposes a significant impact on the environment and on social and economic well-being 1, 2. Our results demonstrate the need and added value of analysing climate trends based on data with high spatial resolution allowing sustainable adaptation measures at local scales. With regard to annual trends, results largely confirm seasonal analyses: only a few significant trends in rainfall, but significant increasing trends in T-max (up to 1.9 ☌) and T-min (up to 1.2 ☌) for virtually the whole region. On the other hand, a non-significant increasing trend in large parts of the region is observed during the short rain season. Long-term seasonal trend analysis shows a non-significant (except for small areas), decreasing (increasing) trend in rainfall in eastern (western) parts of Ethiopia and Kenya and a decreasing trend in large parts of Tanzania during the long rainy season. High resolution gridded rainfall (1981–2016) and temperature (1979–2010) data from international databases like the Climate Hazards Group are used. In this study long-term trends in rainfall and maximum and minimum temperature (T-max and T-min) were analysed on seasonal and annual time scales for East Africa. Thanks.Detecting changes in climate is a prerequisite for a better understanding of the climate and developing adaptation and mitigation measures at a regional and local scale. I am open to any suggestion that could bring be closer to the solution, not only the final solution to the problem. Is it possible to do this with RNCEP package? Or what other options could I try?įinal results should be similar to this: longitude latitude month year temperature But I need the weather conditions (such as mean temperature for the month) for the precise locations, based on my longitude and latitude columns for each month for all the years (2001 to 2018). My result just extracts the historical weather data for the entire region, setting the range for longitude and latitude. (w, layer = 1, show.pts = TRUE, ntours = TRUE, cols = lors(64), transparency = 0.4) #Visualize temperature as heatmap for 1 day W <- NCEP.aggregate(weather, YEARS = TRUE, MONTHS = TRUE, HOURS = FALSE, fxn='mean') Lon <- dimnames(weather)] # in increments of 2.5 Lat <- dimnames(weather)] # in increments of 2.5 # extract longitude & latitude based on created weather dataset # extract date and time based on created weather dataset Weather <- NCEP.gather(variable = "air.sig995", level = "surface", months.minmax = c(1,12), # define arguments for latitude and longitude Max_lon <- max(data$longitude, na.rm = TRUE) Min_lon <- min(data$longitude, na.rm = TRUE) Max_lat <- max(data$latitude, na.rm = TRUE) Min_lat <- min(data$latitude, na.rm = TRUE) #Define limits for latitude and longitude This is the code that extracts the weather data at the 2.5 increment. How can I extract it for the precise latitude and longitude I need? But to extract it I have to insert the interval for latitude and longitude (for example from 0 to 60), which gets the weather data at increments of 2.5 for latitude and longitude. I looked into RNCEP package in R, which stores weather data. I have the longitude and latitude stored in separate columns: longitude latitude I need to extract historical weather data at a monthly basis, from 2001 to 2018, based on specific locations in Europe (all locations are in the sea).
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