The climate in Maryland has changed in the past and will continue to change in the future due to natural forces such as changes in the amount of solar radiation, ocean circulation, and volcanoes. Humans can impact climate on local, regional, and global scales, through the continuous emissions of greenhouse gases, changing aerosols, and land use changes (change from prairie to agriculture to cities). We can see climate change is the result of complex interactions between natural and human-induced forces and remains a challenge for understanding future climate change.
The 2014 National Climate Assessment reviewed climate trends across the Nation, including the Midwest and Maryland. Heat waves, heavy downpours, and sea level rise pose growing challenges to many aspects of life in the Northeast. Infrastructure, agriculture, fisheries, and ecosystems will be increasingly compromised. Many states and cities are beginning to incorporate climate change into their planning. Explore how climate change is affecting the Northeast. The report also has chapters by sectors such as water, agriculture, transportation, forestry, and human health. In addition, there are response strategies presented to help mitigate or adapt to the current and forecasted trends. An updated report can be found at the Climate Science Sepcial Report. The next National Climate Assessment is currently underway and is expected to be released by late 2018.
Below are plots of temperate and precipitaion for Maryland, the Northeast region, and the contiguous United States. The data was obtained from NECI's State Trend Charts and depict historical temperature averages for U.S. states since 1895. The data is derived from the current U.S. Climate Division Database.
The data are plotted as points with the average value between 1895-1965 depicted as a black line. The shaded area around the regressions (colored lines) is the confidence interval for the regression. There is a 95 percent probability that the true regression line for the population lies within the confidence interval for our estimate of the regression line calculated from the data. We can examine whether the regression range excludes 0. If it does, then we can rule out the likelihood that the slope is 0. Thus, we conclude that there is a significant linear relationship. There is a statistically significant increase in temperatures since 1895, but the same can not be said for precipitaiton totals.