Summer rains have remained steady over the past 20 years, but are less than historic highs. Temperature has increased, and while the farmland per person is decreasing, population growth has been offset with improved yields.
While summer rains have increased during the past 20 years, temperatures have increased as well, amplifying the effects of droughts. Crop yields are low but the population is growing, pointing to rising food insecurity.
Long-term reduction in rainfall and increasing temperature threaten Chad's future food production prospects; combined with rapid population growth and zones of substantial conflict, increasing numbers of people will be at risk.
Recent trends in March-June, June-September, and March-September rainfall and temperature, identifying significant reductions in rainfall and increases in temperature over time in this area.
Crop areas in west central Kenya are affected by decline in rainfall over several decades; the effects may be exacerbated by overall warming in the region
Summer rains have remained steady for the past 20 years, but are below the long-term average. Current population and agricultural trends indicate increasing yields have offset population expansion, keeping per capita cereal production steady.
Modest declines in rainfall, accompanied by increases in air temperatures, declining farmland per person, along with trends in population and agriculture could lead to a 30% reduction in per capita cereal production by 2025.
The data shown here depict drying trends in one of the world's most food insecure regions. Decreasing rainfall since 1980 accompanied increases in air temperature greater than global warming.
Long-term reduction in rainfall and increasing temperature threaten Uganda's future food production prospects; combined with rapid population growth these factors could increase the number of people who are at risk during the next 20 years.
Combining genetic data with current and predicted climate scenarios, we are modeling the predicted future distributions of wildlife populations in the Arctic and identifying key environmental variables that determine important animal habitat.
This fact sheet focuses on climate variability and change and how USGS research can strengthen the Nation with information needed to meet the challenges of the 21st century.
The relation between seasonal forest change and weather is being tracked and analyzed by comparing precise field observations to regional patterns shown in long-term satellite imagery.
Landscapes of interwoven wetlands and uplands offer a rich set of ecosystem goods and services. Changes in climate and land use can affect the value of those services. We study these areas to understand how they may be changing.
Coordinates our efforts to address challenges resulting from climate change and to empower natural resource managers with rigorous scientific information and effective tools for decision-making.
The Arctic is warming faster than other regions of the world due to positive climate feedbacks associated with loss of snow and ice. The USGS has modeled the future responses of polar bear and Pacific walrus populations to this environmental change.
New synoptic data from samples collected in the Arctic Ocean and insights into the patterns and extent of ocean acidification. This foundational geochemical information will help us to understand potential risks to Arctic resources.
Over 30 years of substantial warming, the timing of life cycle events in maize here has changed, threatening the crop yield by exposing the plant at sensitive phases in its life cycle to increased heat and drought, and lowering the weight of its grains.
Mathematical models predict overall streamflow, runoff, subsurface flow, groundwater flow, and soil moisture in this area in response to four different greenhouse gas emission scenarios.
Mathematical models predict overall streamflow, runoff, subsurface flow, groundwater flow, and soil moisture in this area in response to four different greenhouse gas emission scenarios.
Mathematical models predict overall streamflow, runoff, subsurface flow, groundwater flow, and soil moisture in this area in response to four different greenhouse gas emission scenarios.
Mathematical models predict overall streamflow, runoff, subsurface flow, groundwater flow, and soil moisture in this area in response to four different greenhouse gas emission scenarios.
Mathematical models predict overall streamflow, runoff, subsurface flow, groundwater flow, and soil moisture in this area in response to four different greenhouse gas emission scenarios.
Mathematical models predict overall streamflow, runoff, subsurface flow, groundwater flow, and soil moisture in this area in response to four different greenhouse gas emission scenarios.
Mathematical models predict overall streamflow, runoff, subsurface flow, groundwater flow, and soil moisture in this area in response to four different greenhouse gas emission scenarios.
Mathematical models predict overall streamflow, runoff, subsurface flow, groundwater flow, and soil moisture in this area in response to four different greenhouse gas emission scenarios.
Mathematical models predict overall streamflow, runoff, subsurface flow, groundwater flow, and soil moisture in this area in response to four different greenhouse gas emission scenarios.
Mathematical models predict overall streamflow, runoff, subsurface flow, groundwater flow, and soil moisture in this area in response to four different greenhouse gas emission scenarios.
Mathematical models predict overall streamflow, runoff, subsurface flow, groundwater flow, and soil moisture in this area in response to four different greenhouse gas emission scenarios.
Mathematical models predict overall streamflow, runoff, subsurface flow, groundwater flow, and soil moisture in this area in response to four different greenhouse gas emission scenarios.