Dataset for: Compiled weather data from Rusizi, Biurundi
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Weather stations were set up in equal distribution within the watershed areas of Rusizi in Biurundi to cover a strong altitudinal gradient, ranging between 800 to 2200 m a.s.l., in which RTB crops are grown. This close network of weather stations was installed per square kilometer of each other to capture air temperature, relative humidity and precipitation. Weather information was collected hourly; data download and supervision done at monthly intervals and precipitation measured through manual readings' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Life-table parameters","Pest risk assessment","Rainfall","Relative Humidity","Temperature","Temperature-Dependent Phenology Model"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Weather stations were set up in equal distribution within the watershed areas of Rusizi in Biurundi to cover a strong altitudinal gradient, ranging between 800 to 2200 m a.s.l., in which RTB crops are grown. This close network of weather stations was installed per square kilometer of each other to capture air temperature, relative humidity and precipitation. Weather information was collected hourly; data download and supervision done at monthly intervals and precipitation measured through manual readings' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Weather stations were set up in equal distribution within the watershed areas of Rusizi in Biurundi to cover a strong altitudinal gradient, ranging between 800 to 2200 m a.s.l., in which RTB crops are grown. This close network of weather stations was installed per square kilometer of each other to capture air temperature, relative humidity and precipitation. Weather information was collected hourly; data download and supervision done at monthly intervals and precipitation measured through manual readings
Life-table parameters; Pest risk assessment; Rainfall; Relative Humidity; Temperature; Temperature-Dependent Phenology Model