Baker I.T.,Colorado State University |
Harper A.B.,Colorado State University |
da Rocha H.R.,University of Sao Paulo |
Denning A.S.,Colorado State University |
And 12 more authors.
Agricultural and Forest Meteorology | Year: 2013
Surface ecophysiology at five sites in tropical South America across vegetation and moisture gradients is investigated. From the moist northwest (Manaus) to the relatively dry southeast (Pé de Gigante, state of São Paulo) simulated seasonal cycles of latent and sensible heat, and carbon flux produced with the Simple Biosphere Model (SiB3) are confronted with observational data. In the northwest, abundant moisture is available, suggesting that the ecosystem is light-limited. In these wettest regions, Bowen ratio is consistently low, with little or no annual cycle. Carbon flux shows little or no annual cycle as well; efflux and uptake are determined by high-frequency variability in light and moisture availability. Moving downgradient in annual precipitation amount, dry season length is more clearly defined. In these regions, a dry season sink of carbon is observed and simulated. This sink is the result of the combination of increased photosynthetic production due to higher light levels, and decreased respiratory efflux due to soil drying. The differential response time of photosynthetic and respiratory processes produce observed annual cycles of net carbon flux. In drier regions, moisture and carbon fluxes are in-phase; there is carbon uptake during seasonal rains and efflux during the dry season. At the driest site, there is also a large annual cycle in latent and sensible heat flux. © 2012.
News Article | October 31, 2016
Serendipity, expertise, foresight and the equivalent of an Earth observation data archaeological dig have led to recovery of almost-40-year-old satellite imagery -- thought lost forever -- which will significantly add to understanding of our planet's climate. The data, from the European Space Agency's prototype Meteosat-1 geostationary meteorological satellite, was found at the University of Wisconsin-Madison's Space Science and Engineering Center (SSEC) in the United States. It has now been provided to EUMETSAT, which operates and disseminates data from Meteosat-1's "descendents" and, crucially, has an uninterrupted record of climate data from these satellites stretching back more than 30 years. That record, although with a small gap, now extends even further back in time. To say that the discovery of this lost data was greeted with enthusiasm would be an understatement, with climate scientists describing it as "like finding a lost child" -- "the first born"! Meteosat-1 was launched on 23 November 1977, and was positioned in a geostationary orbit at 0° degrees longitude, with a constant view of most of Europe, all of Africa, the Middle East and part of South America. From that position, this view of the "full-disk" was scanned every 30 minutes, with the data being provided in near-real time to users. The satellite's mission lasted until 25 November 1979. Meteosat-1 represented cutting-edge technology for its time, introducing the concept of a global system of geostationary platforms capable of observing the atmospheric circulation and weather around the equator in near-real time. It was also the first geostationary meteorological satellite to have a water vapour channel, tracking the motion of moisture in the air. The data found in America comprises 20,790 images, from 1 December 1978 to 24 November 1979. On 27 June 2016, EUMETSAT held an event to celebrate its 30th anniversary, in Darmstadt, Germany. Among the guests was Dr Paul Menzel, Senior Scientist with the Cooperative Institute for Meteorological Satellite Studies, part of the University of Wisconsin-Madison's Space Science and Engineering Center. A memento guests at the event received was a memory stick with links to EUMETSAT's climate data record, from 1 January 1984 up until the anniversary in 2016 -- more than 32 years. "It was pointed out that the data was all there, except for two days, which were missing," Dr Menzel said. "That prompted me to have a look whether we had the data for those two days. When I went back, we started looking for the data but I was told we didn't have any Meteosat data from before 1992. I knew that couldn't be right." The SSEC Data Center didn't have the data for the missing two days but did find something even more valuable. In 1978-79, the First GARP (Global Atmospheric Research Programme) Global Experiment (FGGE) was undertaken -- a project reported by New Scientist at the time as the biggest cooperative international venture ever undertaken. Its aim was to find out which gaps in global weather monitoring could be filled to improve weather forecasting seven to 10 days in advance. Meteosat-1 data was provided to the SSEC for this project. The centre's founder, Verner Suomi, often referred to as the "Father of Satellite Meteorology," had the foresight to recognise the importance of preserving Earth observation data. "I thought we must have the FGGE data," Dr Menzel said. "Vern's mentality was, I don't want to lose any of the data." Dr Menzel's colleague, CIMSS Programme Manager Dr David Santek said teams of experts had worked in three shifts around the clock tracking cloud features in the images from the 1,200 nine-track tapes of Meteosat-1 data that was shipped to them for the FGGE project in 1978-79. "Then those tapes sat around for 20 years," Dr Santek said. "In 1997, we started converting data from old tape media on to more modern media. We could not dispose of those old tapes. "From 2001-2004, new nine-track tape drives were acquired to extract most of the data from the tapes and, over the past 15 years, the original data were stored on disk, although, without any attempt to use it. That's why the old data were able to be found. But finding the data was not the end of the story. The files were stored on disk in the original tape format and needed to be decoded. Dan Forrest, SSEC's Senior Systems Engineer, spent several weeks piecing the files together, dug up old documentation, wrote a decoder and was able to retrieve the data, but it was not quite usable. In another serendipitous twist, Dr Santek was the person who wrote some of the original code and he provided modules for navigating and calibrating the data. Why this data is so important The data from Meteosat-1 will help scientists better understand the climate and how it has changed. EUMETSAT Climate Services and Product Manager Dr Jörg Schulz, said the discovery would not only provide a longer time series of climate data but would be reanalysed and reprocessed using the latest methodology. "It gives us information about the state of Earth's atmosphere from a time when there was less interference from human activity," Dr Menzel added. Dr Schulz said this would help further improve understanding of Earth's climate system. "One of the grand challenges in climate science is to better understand atmospheric circulation in general," Dr Schulz said. "Where is the tropical, warm, moist air going? Where is the polar, cool, dry air going? And how does this change over time? "This data will be very important to support the analysis of position, strength and variability of storm tracks as well as circulation-cloud interactions." The three scientists were keen to stress not only the scientific and historical importance of the data but also how this demonstrates the value of strong collaboration and cooperation. "It's another example of the strong collaboration between SSEC and EUMETSAT and I'm very happy to have found those tapes," Dr Menzel said. "A lot of people were involved," Dr Santek added. "It's history and we are able to make it useful, even though it hasn't been looked at for 30 years." "We are excited about the work done at SSEC and look forward to analysing and improving the data in collaboration with SSEC in the coming years," Dr Schulz concluded. You can see an animation made from one day's worth of imagery from Meteosat-1 on the EUMETSAT YouTube channel: https://www.youtube.com/watch?v=gnN0zrMRYAo
Baker I.T.,Colorado State University |
Denning A.S.,Colorado State University |
Stockli R.,Climate Services
Tellus, Series B: Chemical and Physical Meteorology | Year: 2010
Seasonality and interannual variability in North American photosynthetic activity reflect potential patterns of climate variability. We simulate 24 yr (1983-2006) and evaluate regional and seasonal contribution to annual mean gross primary productivity (GPP) as well as its interannual variability. The highest productivity occurs in Mexico, the southeast United States and the Pacific Northwest. Annual variability is largest in tropical Mexico, the desert Southwest and the Midwestern corridor. We find that no single region or season consistently determines continental annual GPP anomaly. GPP variability is dependent upon soil moisture availability in low- and mid-latitudes, and temperature in the north. Soil moisture is a better predictor than precipitation as it integrates precipitation events temporally. The springtime anomaly is the most frequent seasonal contributor to the annual GPP variability. No climate mode (i.e. ENSO, NAM) can be associated with annual or seasonal variability over the entire continent. We define a region extending from the Northeast United States through the midwest and into the southwestern United States and northern Mexico that explains a significant fraction of the variability in springtime GPP. We cannot correlate this region to a single mechanism (i.e. temperature, precipitation or soil moisture) or mode of climate variability. © 2010 The Authors Tellus B © 2010 International Meteorological Institute in Stockholm.
Stckli R.,Climate Services |
Rutishauser T.,University of Bern |
Baker I.,Colorado State University |
Liniger M.A.,Climate Services |
Denning A.S.,Colorado State University
Journal of Geophysical Research: Biogeosciences | Year: 2011
Simulations of the global water and carbon cycle are sensitive to the model representation of vegetation phenology. Current phenology models are empirical, and few predict both phenological timing and leaf state. Our previous study demonstrated how satellite data assimilation employing an Ensemble Kalman Filter yields realistic phenological model parameters for several ecosystem types. In this study the data assimilation framework is extended to global scales using a subgrid-scale representation of plant functional types (PFTs) and elevation classes. A reanalysis of vegetation phenology for 256 globally distributed regions is performed using 10 years of Moderate Resolution Imaging Spectroradiometer (MODIS) fraction of photosynthetically active radiation (FPAR) absorbed by vegetation and leaf area index (LAI) data. The 9 108 quality screened observations (corresponding to <1% of the globally available MODIS data) successfully constrain a posterior PFT-dependent phenological parameter set. It reduces the global FPAR and LAI prediction error to 20.6% and 14.8%, respectively, compared to the prior prediction error. A 50 year long (1960-2009) daily 1 × 1 global phenology data set with a mean FPAR and LAI prediction error of 0.065 (-) and 0.34 (m2 m-2) is generated. Temperate phenology is best explained by a combination of light and temperature. Tropical evergreen phenology is found to be largely insensitive to moisture and light variations. Boreal phenology can be accurately predicted from local to global scales, while temperate and mediterranean landscapes might benefit from a better subgrid-scale PFT classification or from a more complex canopy radiative transfer model. Copyright 2011 by the American Geophysical Union.
Ceppi P.,Climate Services |
Ceppi P.,University of Washington |
Scherrer S.C.,Climate Services |
Fischer A.M.,Climate Services |
Appenzeller C.,Climate Services
International Journal of Climatology | Year: 2012
Temperature is a key variable for monitoring global climate change. Here we perform a trend analysis of Swiss temperatures from 1959 to 2008, using a new 2 × 2 km gridded data-set based on carefully homogenised ground observations from MeteoSwiss. The aim of this study is twofold: first, to discuss the spatial and altitudinal temperature trend characteristics in detail, and second, to quantify the contribution of changes in atmospheric circulation and local effects to these trends. The seasonal trends are all positive and mostly significant with an annual average warming rate of 0.35 °C/decade (∼1.6 times the northern hemispheric warming rate), ranging from 0.17 in autumn to 0.48 °C/decade in summer. Altitude-dependent trends are found in autumn and early winter where the trends are stronger at low altitudes (<800 m asl), and in spring where slightly stronger trends are found at altitudes close to the snow line. Part of the trends can be explained by changes in atmospheric circulation, but with substantial differences from season to season. In winter, circulation effects account for more than half the trends, while this contribution is much smaller in other seasons. After removing the effect of circulation, the trends still show seasonal variations with higher values in spring and summer. The circulation-corrected trends are closer to the values simulated by a set of ENSEMBLES regional climate models, with the models still tending towards a trend underestimation in spring and summer. Our results suggest that both circulation changes and more local effects are important to explain part of recent warming in spring, summer, and autumn. Snow-albedo feedback effects could be responsible for the stronger spring trends at altitudes close to the snow line, but the overall effect is small. In autumn, the observed decrease in fog frequency might be a key process in explaining the stronger temperature trends at low altitudes. © 2010 Royal Meteorological Society.