A1 Atmospheric fluxes and optical trait diversity under climate and land use changes - observations and LSM modelling [funded by DFG]
Project staff:
Prof. Dr. Jörg Bendix
Prof. Dr. Katja Trachte
Jorge Gribaldo Castillo Armijos
Prof. Dr. Katrin Heer
Oliver Limberger
Abstract:
Interactions between optical trait variations and atmospheric exchanges along an altitudinal gradient will be investigated to assess feedback effects related to environmental changes. The project has the aims to derive (i) optical traits for land surface model (LSM) parametrization and evaluation, (ii) water and carbon flux measurements for the determination of microclimates and LSM evaluation, (iii) local climate change scenarios and climate extremes for LSM forcing and (iv) uncoupled and coupled LSM simulations, the latter as a contribution to the joint LSM synthesis. Beyond the central hypotheses, we will test if (i) PFT albedo changes due to water and nutrient stress, (ii) if latent heat flux and the carbon sink function are less resistant against climate stress in the anthropogenic systems, (iii) if these extremes are most pronounce in the RC8.5 climate change scenario and (iv) if changes in albedo trait diversity under climate extremes lead to a reduction of the resistance in latent heat fluxes especially in the anthropogenic systems. For this, hyperspectral remote sensing will be used to derive PFT and plot optical traits such as spectral leaf and canopy albedo. The data will be taken by field spectrometry and an unmanned aerial vehicle (UAV) for the natural forest and the anthropogenic systems during wet and dry periods along the elevational gradient. On the basis of long-term eddy covariance (ECov) flux measurements (water and carbon fluxes) supported by large eddy simulations (LES) over the natural forest and the anthropogenic systems, exchanges between land surface characteristics and the adjacent atmosphere will be explored. The Bowen-Ratio as well as the carbon sink function (CSF) will be used as a proxi to unveil environmental controls on microclimatic conditions. The impact of land use changes on the microclimates will be analyzed by between-site comparisons, which will reveal insights in the resistance of the TFs in different land categories against climatic stress (drier periods). The uncoupled LSM will be applied to test the interactions of optical trait diversity and microclimate under varying forcings to analyze the resistance of the latent heat fluxes against environmental changes. For this, it will be parameterized by the derived optical traits (average PFT albedo versus albedo trait diversity) and will be driven by (i) current weather situations from automatic weather stations, (ii) climate extremes from long-term climatologies (ENSO related dry, wet, hot, cold periods) and (iii) climate change scenarios. The latter will be obtained by statistically downscaled RCP4.5 and RCP8.5 scenarios from the CMIP5 multi-model ensemble. Comparisons with ECov measurements will evaluate the LSM simulations, which strengthen the robustness of the analysis of the feedback effects.
Publications and poster presentations:
2021 - Limberger, O.; Homeier, J.; Farwig, N.; Pucha-Cofrep, F.; Fries, A.; Leuschner, C.; Trachte, K. & Bendix, J. (2021): Classification of Tree Functional Types in a Megadiverse Tropical Mountain Forest from Leaf Optical Metrics and Functional Traits for Two Related Ecosystem Functions. Forests 12(5), 649.
- Urgilés, G.; Celleri, R.; Trachte, K.; Bendix, J. & Orellana-Alvear, J. (2021): Clustering of Rainfall Types Using Micro Rain Radar and LaserDisdrometer Observations in the Tropical Andes. Remote Sensing 13(5), 1-22.
- Contreras, P.; Orellana-Alvear, J.; Muñoz, P.; Bendix, J. & Celleri, R. (2021): Influence of Random Forest Hyperparameterization on Short-Term Runoff Forecasting in an Andean Mountain Catchment. Atmosphere 12(2), 1-16.
- Turini, N.; Thies, B.; Horna, N. & Bendix, J. (2021): Random forest-based rainfall retrieval for Ecuador using GOES-16 and IMERG-V06 data. European Journal of Remote Sensing 54(1), 117-139.
- Núñez, P.Á.; Silva, B.; Schulz, M.; Rollenbeck, R. & Bendix, J. (2021): Evapotranspiration estimates for two tropical mountain forest using high spatial resolution satellite data. International Journal of Remote Sensing 42(8), 2940--2962.
2020 - Carrillo-Rojas, G.; Schulz, H.M.; Orellana-Alvear, J.; Ochoa-Sánchez, A.; Trachte, K.; Celleri, R. & Bendix, J. (2020): Atmosphere-surface fluxes modeling for the high Andes: The case of páramo catchments of Ecuador. Science of The Total Environment 704, 135372.
- Knoke, T.; Paul, C.; Rammig, A.; Gosling, E.; Hildebrandt, P.; Härtl, F.; Peters, T.; Richter, M.; Diertl, K.; Castro, L.M.; Calvas, B.; Ochoa Moreno, S.; Valle-Carrión, L.A.; Hamer, U.; Tischer, A.; Potthast, K.; Windhorst, D.; Homeier, J.; Wilcke, W.; Velescu, A.; Gerique, A.; Pohle, P.; Adams, J.; Breuer, L.; Mosandl, R.; Beck, E.; Weber, M.; Stimm, B.; Silva, B.; Verburg, P.H. & Bendix, J. (2020): Accounting for multiple ecosystem services in a simulation of land-use decisions: Does it reduce tropical deforestation?. Global Change Biology 26( ), 1-22.
- Orellana-Alvear, J.; Celleri, R.; Rollenbeck, R.; Muñoz, P.; Contreras, P. & Bendix, J. (2020): Assessment of Native Radar Reflectivity and Radar Rainfall Estimates for Discharge Forecasting in Mountain Catchments with a Random Forest Model. Remote Sensing 12(12), 1.
2019 - Seidel, J.; Trachte, K.; Orellana-Alvear, J.; Figueroa, R.; Celleri, R.; Bendix, J.; Fernandez, C. & Huggel, C. (2019): Precipitation Characteristics at Two Locations in the Tropical Andes by Means of Vertically Pointing Micro-Rain Radar Observations. Remote Sensing 11(24), 2985.
- Wallis, C.; Homeier, J.; Pena Tamayo, J.E.; Brandl, R.; Farwig, N. & Bendix, J. (2019): Modeling tropical montane forest biomass, productivity and canopy traits with multispectral remote sensing data. Remote Sensing of Environment 225, 77 - 92.
- Guallpa, M.; Orellana-Alvear, J. & Bendix, J. (2019): Tropical Andes Radar Precipitation Estimates Need High Temporal and Moderate Spatial Resolution. Water 11(5), 1-22.
- González-Jaramillo, V.; Fries, A. & Bendix, J. (2019): AGB Estimation in a Tropical Mountain Forest (TMF) by Means of RGB and Multispectral Images Using an Unmanned Aerial Vehicle (UAV). Remote Sensing 11(12), 1-22.
- Orellana-Alvear, J.; Celleri, R.; Rollenbeck, R. & Bendix, J. (2019): Optimization of X-Band Radar Rainfall Retrieval in the Southern Andes of Ecuador Using a Random Forest Model. Remote Sensing 11(14), 1632.