6 resultados para Errors in variables models
em Publishing Network for Geoscientific
Resumo:
Secchi depth is a measure of water transparency. In the Baltic Sea region, Secchi depth maps are used to assess eutrophication and as input for habitat models. Due to their spatial and temporal coverage, satellite data would be the most suitable data source for such maps. But the Baltic Sea's optical properties are so different from the open ocean that globally calibrated standard models suffer from large errors. Regional predictive models that take the Baltic Sea's special optical properties into account are thus needed. This paper tests how accurately generalized linear models (GLMs) and generalized additive models (GAMs) with MODIS/Aqua and auxiliary data as inputs can predict Secchi depth at a regional scale. It uses cross-validation to test the prediction accuracy of hundreds of GAMs and GLMs with up to 5 input variables. A GAM with 3 input variables (chlorophyll a, remote sensing reflectance at 678 nm, and long-term mean salinity) made the most accurate predictions. Tested against field observations not used for model selection and calibration, the best model's mean absolute error (MAE) for daily predictions was 1.07 m (22%), more than 50% lower than for other publicly available Baltic Sea Secchi depth maps. The MAE for predicting monthly averages was 0.86 m (15%). Thus, the proposed model selection process was able to find a regional model with good prediction accuracy. It could be useful to find predictive models for environmental variables other than Secchi depth, using data from other satellite sensors, and for other regions where non-standard remote sensing models are needed for prediction and mapping. Annual and monthly mean Secchi depth maps for 2003-2012 come with this paper as Supplementary materials.
Resumo:
High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover data sets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing Earth system models. Earth system models also require specific land cover classification systems based on plant functional types (PFTs), rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover data sets against one another and with auxiliary data to identify key uncertainties that contribute to variability in PFT classifications that would introduce errors in Earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, vegetation continuous fields (MODIS VCFs) and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation). The GlobCover data set, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFT maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT data set, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to represent the water and carbon cycles in northern latitudes better. Updated land cover data sets are critical for improving and maintaining the relevance of Earth system models for assessing climate and human impacts on biogeochemistry and biophysics.
Resumo:
Culture and mesocosm experiments are often carried out under high initial nutrient concentrations, yielding high biomass concentrations that in turn often lead to a substantial build-up of DOM. In such experiments, DOM can reach concentrations much higher than typically observed in the open ocean. To the extent that DOM includes organic acids and bases, it will contribute to the alkalinity of the seawater contained in the experimental device. Our analysis suggests that whenever substantial amounts of DOM are produced during the experiment, standard computer programmes used to compute CO2 fugacity can underestimate true fCO2 significantly when the computation is based on AT and CT. Unless the effect of DOM-alkalinity can be accounted for, this might lead to significant errors in the interpretation of the system under consideration with respect to the experimentally applied CO2 perturbation. Errors in the inferred fCO2 can misguide the development of parameterisations used in simulations with global carbon cycle models in future CO2-scenarios. Over determination of the CO2-system in experimental ocean acidification studies is proposed to safeguard against possibly large errors in estimated fCO2.
Resumo:
The Neogene carbonate stratigraphy of five sites drilled on Ontong Java Plateau during Leg 130 reveals a number of patterns which are unexpected, and which we refer to as loss paradox, equatorial insensitivity, and climate paradox. They denote the following unresolved questions. 1 The loss of carbonate at depth (as derived from differences in accumulation rates) is much greater than suggested by the change in carbonate percentages (calculated under the assumption that carbonate dissolution is the cause of loss). This indicates an important role for redeposition processes, such as winnowing (bottom currents), sifting (resuspension and catabatic flow) and episodic sloughing or solifluction (presumably stimulated by earthquakes). 2 Accumulation rates are not markedly increased at the time a site crosses the equator. There are several possible reasons. Equatorial upwelling may be unimportant in controlling sedimentation rates this far in the western Pacific, or its output may be spread over a considerable distance from the equator. Alternatively, increased supply below the equator is compensated for by increased removal (e.g. from resuspension by bioturbation, combined with catabatic flow). It is conceivable that errors in the timescale could also produce the effect seen. 3 There is an overall tendency for agreement between the stratigraphic patterns of carbonate content and of accumulation rates, but neither pattern is readily explained by reference to changes in climate (represented by benthic delta18O) or in sea-level (as derived from sequence stratigraphy).
Resumo:
The recently proposed global monsoon hypothesis interprets monsoon systems as part of one global-scale atmospheric overturning circulation, implying a connection between the regional monsoon systems and an in-phase behaviour of all northern hemispheric monsoons on annual timescales (Trenberth et al., 2000). Whether this concept can be applied to past climates and variability on longer timescales is still under debate, because the monsoon systems exhibit different regional characteristics such as different seasonality (i.e. onset, peak, and withdrawal). To investigate the interconnection of different monsoon systems during the pre-industrial Holocene, five transient global climate model simulations have been analysed with respect to the rainfall trend and variability in different sub-domains of the Afro-Asian monsoon region. Our analysis suggests that on millennial timescales with varying orbital forcing, the monsoons do not behave as a tightly connected global system. According to the models, the Indian and North African monsoons are coupled, showing similar rainfall trend and moderate correlation in rainfall variability in all models. The East Asian monsoon changes independently during the Holocene. The dissimilarities in the seasonality of the monsoon sub-systems lead to a stronger response of the North African and Indian monsoon systems to the Holocene insolation forcing than of the East Asian monsoon and affect the seasonal distribution of Holocene rainfall variations. Within the Indian and North African monsoon domain, precipitation solely changes during the summer months, showing a decreasing Holocene precipitation trend. In the East Asian monsoon region, the precipitation signal is determined by an increasing precipitation trend during spring and a decreasing precipitation change during summer, partly balancing each other. A synthesis of reconstructions and the model results do not reveal an impact of the different seasonality on the timing of the Holocene rainfall optimum in the different sub-monsoon systems. They rather indicate locally inhomogeneous rainfall changes and show, that single palaeo-records should not be used to characterise the rainfall change and monsoon evolution for entire monsoon sub-systems.