New statistical models could lead to better predictions of ocean patterns

The world's oceans cover more than 72 percent of Earth's surface, impact a major part of the carbon cycle, and contribute to variability in global climate and weather patterns. However, accurately predicting the condition of the ocean is limited by current methods. Now, researchers at the University of Missouri have applied complex statistical models to increase the accuracy of ocean forecasting that can influence the ways in which forecasters predict long-range events such as El Nino and the lower levels of the ocean food chain -- one of the world's largest ecosystems.

"The ocean really is the most important part of the world's environmental system because of its potential to store carbon and heat, but also because of its ability to influence major atmospheric weather events such as droughts, hurricanes and tornados," said Chris Wikle, professor of statistics in the MU College of Arts and Science. "At the same time, it is essential in producing a food chain that is a critical part of the world's fisheries."

The vastness of the world's oceans makes predicting its changes a daunting task for oceanographers and climate scientists. Scientists must use direct observations from a limited network of ocean buoys and ships combined with satellite images of various qualities to create physical and biological models of the ocean. Wikle and Ralph Milliff, a senior research associate at the University of Colorado, adopted a statistical "Bayesian hierarchical model" that allows them to combine various sources of information as well as previous scientific knowledge. Their method helped improve the prediction of sea surface temperature extremes and wind fields over the ocean, which impact important features such as the frequency of tornadoes in tornado alley and the distribution of plankton in coastal regions -- a critical first stage of the ocean food chain.

"Nate Silver of The New York Times combined various sources of information to understand and better predict the uncertainty associated with elections," Wikle said. "So much like that, we developed more sophisticated statistical methods to combine various sources of data -- satellite images, data from ocean buoys and ships, and scientific experience -- to better understand the atmosphere over the ocean and the ocean itself. This led to models that help to better predict the state of the Mediterranean Sea, and the long-lead time prediction of El Nino and La Nina. Missouri, like most of the world, is affected by El Nino and La Nina (through droughts, floods and tornadoes) and the lowest levels of the food chain affect us all through its effect on Marine fisheries."

El Nino is a band of warm ocean water temperatures that periodically develops off the western coast of South America and can cause climatic changes across the Pacific Ocean and the U.S. La Nina is the counterpart that also affects atmospheric changes throughout the country. Wikle and his fellow researchers feel that, through better statistical methods and models currently in development, a greater understanding of these phenomena and their associated impacts will help forecasters better predict potentially catastrophic events, which will likely be increasingly important as our climate changes.

Wikle's study, "Uncertainty management in coupled physical-biological lower trophic level ocean ecosystem models," was funded in part by the National Science Foundation and was published in Oceanography and Statistical Science.

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University of Missouri-Columbia. "New statistical models could lead to better predictions of ocean patterns." ScienceDaily. ScienceDaily, 18 March 2014. .University of Missouri-Columbia. (2014, March 18). New statistical models could lead to better predictions of ocean patterns. ScienceDaily. Retrieved April 19, 2014 from www.sciencedaily.com/releases/2014/03/140318154927.htmUniversity of Missouri-Columbia. "New statistical models could lead to better predictions of ocean patterns." ScienceDaily. www.sciencedaily.com/releases/2014/03/140318154927.htm (accessed April 19, 2014).

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Better climate predictions for West Africa

The population of West Africa is growing rapidly. It has to cope with a complex meteorology, unreliable climate prognoses, and increasing air pollution. Within the next five years, extensive measurements will be accomplished in this region, new weather and climate models will be developed, and development policy is planned to be supported under the DACCIWA EU project. DACCIWA covers the complete chain from natural and anthropogenic emissions to impacts on the climate, ecosystems, and health. The project coordinated by KIT has a budget of nearly nine million euros.

Due to the highest population growth worldwide, massive urbanization, and a stable economic growth, countries in southern West Africa currently are exposed to rapid change. The quickly growing major cities are mainly located on the coast, agricultural production areas and forests can be found directly behind. In the cities, the emissions caused by man are increasing strongly. Among others, these emissions are caused by road traffic due to a largely outdated vehicle technology. As a result of the increasing fine dust pollution, people in the cities are increasingly suffering from respiratory diseases. High ozone concentrations typically occur outside of the cities and represent a risk factor for the health of rural population as well as for agricultural production.

According to the recent World Bank report, West Africa is among the regions that will be affected most by global climate change. Climatic impacts resulting from the massive conversion of natural forests into agricultural areas are accompanied by a change of regional climate. It has hardly been studied so far and is caused by anthropogenic emissions from the combustion of fossil fuels and biomass combined with natural emissions of plants. Formation of solid and liquid aerosol particles is increased. These aerosol particles act as condensation nuclei and modify cloud formation. "We assume that increased cloud formation affects the complete monsoon system," Professor Peter Knippertz of the Institute of Meteorology and Climate Research (IMK) of KIT explains. "These relationships have hardly been studied for West Africa so far." Improved climate prognosis for West Africa will also affect regions located far away. "We know, for example, that the West African monsoon interacts with the Indian monsoon and also represents a major parameter influencing Atlantic hurricanes."

Within the framework of DACCIWA, the researchers will first compile current data in an extensive measurement campaign with satellites, aircraft, and ground-based instruments. With the help of the resulting dataset and numerous modeling activities, all relevant physical and chemical processes, such as emission, cloud formation, solar irradiation, precipitation, regional air circulation, climate, and health, will be understood much better. Work is aimed at developing a new generation of weather and climate models, predicting heavy monsoon rains, and better prognosticating climate change. "The findings obtained under DACCIWA will be transferred to other monsoon regions and highly valuable for development policy," Professor Knippertz says.

Professor Knippertz coordinates the new interdisciplinary project DACCIWA (Dynamics-aerosol-chemistry-cloud interactions in West Africa) that started on December 01, 2013 and will have a duration of four and a half years. The project is funded by the EU under the 7th Framework Programme with EUR 8.75 million. Of these funds, 1.88 million go to KIT. 16 scientific institutions from Germany, Switzerland, France, Great Britain, Ghana, Nigeria as well as additional partners from Benin and the Ivory Coast are involved in DACCIWA. One of the German partners is the German Aerospace Center (DLR). Activities will focus on the investigation of the interactions of aerosols and clouds.

Together with two other projects, DACCIWA makes up the European Research Cluster "Aerosols and Climate." The cluster started in December. Information on the Research Cluster and on the kickoff event is available at http://www.aerosols-climate.org.

Link to the report of the World Bank: http://climatechange.worldbank.org/sites/default/files/Turn_Down_the_heat_Why_a_4_degree_centrigrade_warmer_world_must_be_avoided.pdf

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