Hi Patrick. Well, there are some satellite data that can help you to mount a first approach to your problem. However, it is important to note that this kind of data must further adjustments to be representative of observed meteorological data as precipitation and temperature. Otherwise, meteorological data is still a difficult task to obtain for several countries.
Take a look at the TRMM data here: https://trmm.gsfc.nasa.gov/
The most trusted sources the requested data have national (state) meteorological agencies of Sudan, Ethiopia and Eritrea. Try to get data from these agencies.
The GHCN-D (ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/) and GSOD (https://data.noaa.gov/dataset/global-surface-summary-of-the-day-gsod) databases, both freely available, definitely contain stations for those countries. Check the GHCN-D first, the data tends to be of a better quality.
Some times rain or temperature gauge are not sufficient considering that many interpolation schemes suffer with the reductions of gauges. Satellite or reanalysis data are a good option to complement the point measurements.
However, validation is requiere first to adjustment. Here you will find an option to validate those sources of complementary information
Article Analysis of precipitation features estimated by reanalysis d...
You can see all the stations and their start of operations here (some have been running for decades, many stations will offer the data for the years you are looking for - note that the NMA has over 1000 stations collecting data):
http://www.ethiomet.gov.et/stations/information
These stations collect the data you are looking for. Data requests have to be made directly to the NMA, and they charge per data point. In theory, you can request data online here:
However, in my experience you need to go to the NMA directly, or have someone go on your behalf. However, before going, determine which stations you are looking for. Once you are in the office, the process is relatively straight forward.
If you use Precipitation from remote sensing products, you can improve their performance using local raingauges. The merging algorithm described in this work have proved to be successful in reducing the remote sensed field error. In the paper the parameters of the merging are analyzed against the raingauges density so that one defines their value with the features of the local raingauge network and, therefore, one will not need to perform a calibration procedure.
Conference Paper Analysis of the kernel bandwidth influence in the double smo...
The Water Cycle Integrator of the eartH2Observe project have several global precipitation dataset at
Hi, You can extent the time frame of data that you have and improve its accuracy by merging information. Want to improve the performance of your hydrological model on a scarce data basin?!! We introduce you to our new article where a satellite-reanalysis-gauge merging algorithm is detailed. Article Improving Rainfall Fields in Data-Scarce Basins: Influence o...