How accurate is long-term climatology data from the Amazon?
How accurate is long-term climatology data from the Amazon?
March 3, 2008
With some models forecasting significant change in the Amazon rainforest over the next century, it has been unclear whether the temperature and precipitation data upon which the projections are made is accurate. Now, new research by Rafael Rosolem of the University of Arizona, shows that data associated with the Large-scale Biosphere-Atmosphere Experiment in Amazon (LBA) — an international research initiative focusing on how changes in land use and climate will affect the biological, physical, and chemical functioning of Amazonia — is representative of normal climatology for the region. In other words, during most of the LBA data collection period, the data was not taken during severe drought or extreme wet periods.
Mongabay: What is your area of research?
Rosolem: I am currently a PhD candidate in the Hydrology and Water Resources graduate program at the University of Arizona under supervision of Prof. William James Shuttleworth. I am originally from Brazil (Piracicaba, SP) and I have been working with Amazon research since 2002. For my PhD research I am interested to understand the energy, water and carbon exchanges between the land surface and atmosphere using land surface parameterization schemes (a.k.a land surface models) potentially coupled to phenology models to better represent the plant responses to atmospheric forcing throughout the year.
Mongabay: How is your research conducted?
Rosolem: The idea for this climatology studied actually started in the Summer of 2006. After attending a few courses at University of Arizona I had this question “How representative is the period of data collection associated with the Large-scale Biosphere-Atmosphere Experiment in Amazon (LBA) compared to the long-term climatology in the Amazon basin”. I was also motivated because the scientific community knows that the LBA has contributed to a better understanding of the Amazon region and its local and global interactions with climate. However, while searching for references I couldn’t find any study like this, so I decided to answer my question. Because of the extreme importance of the LBA data from eddy covariance flux towers, I decided to emphasize the regions nearby the tower locations, especially because I am currently using the data from the towers in my modeling studies.
Basically, the methods involved are quite simple and in summary I compare the LBA period for each one of the regions associated to the towers with the long-term climatology. Mean annual distribution of monthly precipitation and temperature values are compared for the LBA and long-term climatology and a statistical test (Kolmogorov-Smirnov) was applied to determine whether or not the two distributions are identical or not. In addition to the mean annual distribution, comparison of single years with long-term climatology was also performed, including dry and wet seasons. The precipitation and temperature records were provided by conventional weather stations located over the Amazon basin.
Mongabay: What have your results shown?
Rosolem: The results showed that for precipitation the LBA period can be safely considered similar to the long-term climatology. Some differences were found but overall they are considered to be of small signal. For temperature, although most of the regions were also considered “identical” to the long-term climatology, one of the regions, the Bananal Island region, was found to be significantly different from the long-term climatology, with a tendency of temperature increase in that region. It is important to mention that we can not guarantee that the results are all related to a potential response to the climate and/or to land cover changes (e.g., deforestation) in the region because the methodology has its weaknesses, and in the case of Bananal Island only two years of data were available.
When comparing single years and their respective dry and wet seasons, we found that a few more regions were also found to be significantly different in just a few periods of the data collection. In addition to Bananal Island, the most interesting one is the region nearby Sinop (Mato Grosso state), which showed strong tendency of higher temperatures for almost 1.5 years continuously and could be associated with the response to the land cover changes due to the soybean crop expansion in this region. It is known that the Mato Grosso state has the highest deforestation rate in Brazil and one of the reasons is because of the soybean crops expansion northward. Mato Grosso and south of Para contribute to most of the deforestation in the Amazon and several studies have shown impacts on the regional climate as well as global, depending on the spatial extent these changes occur. Road paving due to the soybean expansion (e.g., Cuiaba-Santarem BR-163 highway) may also affect not only the rainforest and climate but also indigenous communities that depend on the forest to survive.
Mongabay: Are you seeing changes in the Amazon with regard to temperature and precipitation?
Rosolem: As explained above, changes in temperature were captured by the study in two regions of the Amazon basin: i. Bananal Island, and ii. Sinop. The latter may represent a direct response to the fast expansion of soybean crops in the Mato Grosso state. Also, Manaus region showed a weak tendency of higher temperatures but not statistically significant for the statistical test applied. When all the data from all the regions were compared to the climatology, there is clear a tendency of higher temperatures during the LBA period as compared to the long-term climatology, but again this tendency is weak according to the methodology (except for Bananal Island).
Mongabay: Do your findings have implications in helping forecast the future of Amazonia?
Rosolem: Not directly, but indirectly. Our study showed that the Amazon “short-term climate” associated with the LBA project is considered to be very similar to what the long-term climatology shows despite some inter- and intra-annual variances expected. However, there seems to be a tendency for higher temperatures during the LBA period which might be associated with climatic forcing changes and/or land use changes in the region. The study contributes indirectly to the forecast because it would be the basis for other studies carried from all the LBA community, especially the researchers that utilize the data from the eddy covariance towers and/or the modeling community. In other words, a studied carried during this period is know to be following a normal tendency of the climate in the Amazon which would not be true if the LBA period would represent only extreme climatic events, such as strong El Nino, La Nina, droughts, etc. Depending on the region where the study is carried, the changes in temperature and precipitation can be partitioned into climate driven and non-climate driven according to our findings.