Saturday, January 14, 2012

Understand Climate Change and Global Warming; Avert the Spread of Diseases

Who Uses IEDRO’s Historical Weather Data?

IEDRO collects historical data from as far back as the 1600’s. The data we collect holds the power to help every global citizen today. With data spanning 100 years or more, we can successfully forecast and understand the ever-changing climate. The data we collect is digitized and downloaded to an open and unrestricted digital database accessible by all.
Foreign Agricultural Extension Agents to Prevent Starvation
Our newly available data enables rural agricultural and development planners to show 1.8 billion subsistence farmers the real frequency of drought in their countries. Planting more appropriate crops means extra production for famine years.
Public Health Officials and Disease Researchers to Avert the Spread of Diseases
Saved data is correlated with historic disease epidemics and pandemics to stem current outbreaks of airborne diseases, such as Malaria, West Nile Virus, Dengue Fever, and Yellow Fever. The relationship of past disease spread with the historic weather conditions enables researchers to predict disease spread (disease vectorization). Inoculation teams and mosquito spraying equipment can then be allocated to the most vulnerable areas.
Researchers to Understand Climate Change and Global Warming
Newly available data shows scientists the true extent and rate of global warming and climate change. Regardless of which side of the global warming debate scientists are on, all agree more historical weather data is needed for research, and we need it soon.
Hydrologists and Meteorologists to Predict Severe Weather Conditions
Flooding causes more deaths each year than all other natural disasters combined (e.g., lightning, earthquakes, tsunamis, hurricanes and tornados). Collection of historical rainfall records is critical to flood-forecast computer models used by most national weather services (including the U.S.) to forecast river flooding. Accuracy of forecasting increases as the year span of the collected data increases.