Publications
Found 380 publication(s)
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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.
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DOI: 10.1080/22797254.2021.1884002
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Abstract:
Abstract:
A new satellite-based algorithm for rainfall retrieval in high spatio-temporal resolution fo
Ecuador is presented. The algorithm relies on the precipitation information from the Integrated
Multi-SatEllite Retrieval for the Global Precipitation Measurement (GPM) (IMERG) and infrared
(IR) data from the Geostationary Operational Environmental Satellite-16 (GOES-16). It wa
developed to (i) classify the rainfall area (ii) assign the rainfall rate. In each step, we selected
the most important predictors and hyperparameter tuning parameters monthly. Between 19
April 2017 and 30 November 2017, brightness temperature derived from the GOES-16 IR
channels and ancillary geo-information were trained with microwave-only IMERG-V06 using
random forest (RF). Validation was done against independent microwave-only IMERG-V06
information not used for training. The validation results showed the new rainfall retrieva
technique (multispectral) outperforms the IR-only IMERG rainfall product. This offers using
the multispectral IR data can improve the retrieval performance compared to single-spectrum
IR approaches. The standard verification scored a median Heidke skill score of ~0.6 for the rain
area delineation and R between ~0.5 and ~0.62 for the rainfall rate assignment, indicating
uncertainties for Andes’s high elevation. Comparison of RF rainfall rates in 2 km2
resolution
with daily rain gauge measurements reveals the correlation of R = ~0.33.
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Keywords: |
Ecuador |
GOES |
rainfall |
Random forests |
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.
Neuwirth, B.; Rabbel, I.; Bendix, J.; Bogena, H.R. & Thies, B. (2021): The European Heat Wave 2018: The Dendroecological Response of Oak and Spruce in Western Germany. Forests 12(3), 283.
Sokol, Z.; Szturc, J.; Orellana-Alvear, J.; Popová, J.; Jurczyk, A. & Celleri, R. (2021): The role of weather radar in rainfall estimation and its application in meteorological and hydrological modelling—A Review. Remote Sensing 13(3), 351.
Hamm, A.; Arndt, A.; Kolbe, C.; Wang, X.; Thies, B.; Boyko, O.; Reggiani, P.; Scherer, D.; Bendix, J. & Schneider, C. (2020): Intercomparison of Gridded Precipitation Datasets over a Sub-Region of the Central Himalaya and the Southwestern Tibetan Plateau. Water 12(3271), 1-23.
Pauli, E.; Andersen, H.; Bendix, J.; Cermak, J. & Egli, S. (2020): Determinants of fog and low stratus occurrence in continental central Europe – a quantitative satellite-based evaluation. Journal of Hydrology 591, 125451.
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DOI: 10.1016/j.jhydrol.2020.125451
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Abstract:
Abstract:
The formation and development of fog and low stratus clouds (FLS) depend on meteorological and land surface conditions and their interactions with each other. While analyses of temporal and spatial patterns of FLS in Europe exist, the interactions between FLS determinants underlying them have not been studied explicitly and quantitatively at a continental scale yet. In this study, a state-of-the-art machine learning technique is applied to model FLS occurrence over continental Europe, using meteorological and land surface parameters from geostationary satellite and reanalysis data. Spatially explicit model units are created to test for spatial and seasonal differences in model performance and FLS sensitivities to changes in predictors, and effects of different data preprocessing procedures are evaluated. The statistical models show good performance in predicting FLS occurrence during validation, with R2>0.9 especially in winter high pressure situations.The predictive skill of the models seems to be dependent on data availability, data preprocessing, time period, and geographic characteristics. It is shown that atmospheric proxies are more important determinants of FLS presence than surface characteristics, in particular mean sea level pressure, near-surface wind speed and evapotranspiration are crucial, together with FLS occurrence on the previous day. Higher wind speeds, higher land surface temperatures and higher evapotranspiration tend to be negatively related to FLS. Spatial patterns of feature importance show the dominant influence of mean sea level pressure on FLS occurrence throughout the central European domain. When only high pressure situations are considered, wind speed (in the western study region) and evapotranspiration (in the eastern study region) gain importance, highlighting the influence of moisture advection on FLS occurrence in the western parts of the central European domain. This study shows that FLS occurrence can be accurately modeled using machine learning techniques in large spatial domains based on meteorological and land surface predictors. The statistical models used in this study provide a novel analysis tool for investigating empirical relationships in the FLS – land surface system and possibly infer processes.
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Keywords: |
Europe |
Fog |
Low stratus |
Machine learning |
Land surface |
Atmosphere-land surface interactions |
Kolbe, C.; Thies, B.; Turini, N.; Liu, Z. & Bendix, J. (2020): Precipitation Retrieval over the Tibetan Plateau from the Geostationary Orbit—Part 2: Precipitation Rates with Elektro-L2 and Insat-3D. Remote Sensing 12(13), 2114.
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DOI: 10.3390/rs12132114
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Abstract:
Abstract:
We present the new Precipitation REtrieval covering the TIbetan Plateau (PRETIP) as a
feasibility study using the two geostationary (GEO) satellites Elektro-L2 and Insat-3D with reference
to the GPM(Global PrecipitationMeasurementMission) IMERG (IntegratedMulti-satellitE Retrievals
for GPM) product. The present study deals with the assignment of the rainfall rate. For precipitation
rate assignment, the best-quality precipitation estimates from the gauge calibrated microwave (MW)
within the IMERG product were combined with the GEO data by Random Forest (RF) regression.
PRETIP was validated with independent MWprecipitation information not considered for model
training and revealed a good performance on 30 min and 11 km spatio-temporal resolution with a
correlation coefficient of R = 0.59 and outperforms the validation of the independentMWprecipitation
with IMERG’s IR only product (R = 0.18). A comparison of PRETIP precipitation rates in 4 km
resolution with daily rain gauge measurements from the Chinese Ministry of Water Resources
revealed a correlation of R = 0.49. No differences in the performance of PRETIP for various elevation
ranges or between the rainy (July, August) and the dry (May, September) season could be found.
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Keywords: |
Tibetan Plateau |
rain retrieval |
Elektro L |
Szymczak, S.; Barth, J.; Bendix, J.; Huneau, F.; Garel, E.; Häusser, M.; Juhlke, T.; Knerr, I.; Santoni, S.; Mayr, C.; Trachte, K.; van Geldern, R. & Bräuning, A. (2020): First indications of seasonal and spatial variations of water sources in pine trees along an elevation gradient in a Mediterranean ecosystem derived from δ18O. Chemical Geology 549, 119695.
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DOI: 10.1016/j.chemgeo.2020.119695
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Abstract:
Abstract:
Water availability is the most important factor for the vitality of forest ecosystems, especially in dry environments. The Mediterranean region is one of the hotspots of future climate change; therefore, data on the water cycle are urgently needed. We measured oxygen isotope compositions in creek water, precipitation, stem water, needle water, and tree-ring cellulose over one growing season to establish the relationship between isotope compositions in different compartments along a fractionation pathway. We analyzed plant material from pine trees (Pinus nigra J.F. Arn subsp. laricio (Poiret) Maire var. Corsicana Hyl. and Pinus pinaster Aiton) at five locations along an elevation gradient from sea level to 1600 m asl. We traced back the oxygen isotope composition from source to sink in tree-ring cellulose in order to identify the water sources used by the trees, and to quantify the extent of isotope fractionation processes. Our results showed that the trees used different water sources over the course of the growing season, ranging from winter snow meltwater to summer precipitation at higher sites and deep soil water reservoirs at coastal sites. Needle water enrichment was higher at higher elevation sites than at coastal locations, highlighting the importance of site-specific climate conditions on the isotopic composition values in tree material. Water availability seems to be most restricted at the highest site, making these trees most vulnerable to climate change.
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Keywords: |
Oxygen isotopes |
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Needle water enrichment |
Xylem water |
Water source |
Knerr, I.; Trachte, K.; Garel, E.; Huneau, F.; Santoni, S. & Bendix, J. (2020): Partitioning of Large-Scale and Local-Scale Precipitation Events by Means of Spatio-Temporal Precipitation Regimes on Corsica. Atmosphere 11(4), 417.
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DOI: 10.3390/atmos11040417
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Abstract:
The island of Corsica in the western Mediterranean is characterized by a pronounced topography in which local breeze systems develop in the diurnal cycle. In interaction with the large-scale synoptic situation, various precipitation events occur, which are classified in this study with regard to their duration and intensity. For this purpose, the island was grouped into five precipitation regimes using a cluster analysis, namely the western coastal area, the central mountainous region, the southern coastal area, the northeast coastal area, and the eastern coastal area. Based on principal component analysis using mean sea level pressure (mslp) obtained from ERA5 reanalysis (the fifth generation of the European Centre for Medium-Range Weather Forecasts, ECMWF), six spatial patterns were identified which explain 98% of the large-scale synoptic situation, while the diurnal breeze systems within the regimes characterize local drivers. It is shown that on radiation days with weak large-scale pressure gradients, pronounced local circulations in mountainous regions are coupled with sea breezes, leading to a higher number of short and intense precipitation events. Meridional circulation patterns lead to more intensive precipitation events on the eastern part of the island (30% intensive events with meridional patterns on the east side compared to 11% on the west side). On the west side of Corsica, however, coastal precipitation events are seldom and less intense than further inland, which can be attributed to the influence of the topography in frontal passages.
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Keywords: |
precipitation |
clustering |
corsica |
era-5 |
mediterranean |
principal component analysis |
Knoke, T.; Paul, C.; Rammig, A.; Gosling, E.; Hildebrandt, P.; Härtl, F.; Peters, T.; Richter, M.; Diertl, K.; Castro, L.M.; Calvas, B.; Ochoa, 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.
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DOI: 10.1111/gcb.15003
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Abstract Conversion of tropical forests is among the primary causes of global environmental change. The loss of their important environmental services has prompted calls to integrate ecosystem services (ES) in addition to socio-economic objectives in decision-making. To test the effect of accounting for both ES and socio-economic objectives in land-use decisions, we develop a new dynamic approach to model deforestation scenarios for tropical mountain forests. We integrate multi-objective optimization of land allocation with an innovative approach to consider uncertainty spaces for each objective. These uncertainty spaces account for potential variability among decision-makers, who may have different expectations about the future. When optimizing only socio-economic objectives, the model continues the past trend in deforestation (1975–2015) in the projected land-use allocation (2015–2070). Based on indicators for biomass production, carbon storage, climate and water regulation, and soil quality, we show that considering multiple ES in addition to the socio-economic objectives has heterogeneous effects on land-use allocation. It saves some natural forest if the natural forest share is below 38%, and can stop deforestation once the natural forest share drops below 10%. For landscapes with high shares of forest (38%–80% in our study), accounting for multiple ES under high uncertainty of their indicators may, however, accelerate deforestation. For such multifunctional landscapes, two main effects prevail: (a) accelerated expansion of diversified non-natural areas to elevate the levels of the indicators and (b) increased landscape diversification to maintain multiple ES, reducing the proportion of natural forest. Only when accounting for vascular plant species richness as an explicit objective in the optimization, deforestation was consistently reduced. Aiming for multifunctional landscapes may therefore conflict with the aim of reducing deforestation, which we can quantify here for the first time. Our findings are relevant for identifying types of landscapes where this conflict may arise and to better align respective policies.
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Keywords: |
Ecuador |
biodiversity |
ecosystem services |
land allocation |
landscape restoration |
robust optimization |
Jung, P.; Baumann, K.; Lehnert, L.; Samolov, E.; Achilles, S.; Schermer, M.; Wraase, L.M.; Eckhardt, K.; Bader, M.; Leinweber, P.; Karsten, U.; Bendix, J. & Büdel, B. (2020): Desert breath—How fog promotes a novel type of soil biocenosis, forming the coastal Atacama Desert’s living skin. Geobiology n/a(n/a), 1-12.
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DOI: 10.1111/gbi.12368
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Abstract:
Abstract The Atacama Desert is the driest non-polar desert on Earth, presenting precarious conditions for biological activity. In the arid coastal belt, life is restricted to areas with fog events that cause almost daily wet–dry cycles. In such an area, we discovered a hitherto unknown and unique ground covering biocenosis dominated by lichens, fungi, and algae attached to grit-sized (~6 mm) quartz and granitoid stones. Comparable biocenosis forming a kind of a layer on top of soil and rock surfaces in general is summarized as cryptogamic ground covers (CGC) in literature. In contrast to known CGC from arid environments to which frequent cyclic wetting events are lethal, in the Atacama Desert every fog event is answered by photosynthetic activity of the soil community and thus considered as the desert's breath. Photosynthesis of the new CGC type is activated by the lowest amount of water known for such a community worldwide thus enabling the unique biocenosis to fulfill a variety of ecosystem services. In a considerable portion of the coastal Atacama Desert, it protects the soil from sporadically occurring splash erosion and contributes to the accumulation of soil carbon and nitrogen as well as soil formation through bio-weathering. The structure and function of the new CGC type are discussed, and we suggest the name grit–crust. We conclude that this type of CGC can be expected in all non-polar fog deserts of the world and may resemble the cryptogam communities that shaped ancient Earth. It may thus represent a relevant player in current and ancient biogeochemical cycling.
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Keywords: |
fog |
Biological soil crust |
Atacama Desert |
Rösner, B.; Egli, S.; Thies, B.; Beyer, T.; Callies, D.; Pauscher, L. & Bendix, J. (2020): Fog and Low Stratus Obstruction of Wind Lidar Observations in Germany—A Remote Sensing-Based Data Set for Wind Energy Planning. Energies 13(15), 3859.
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DOI: 10.3390/en13153859
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Abstract:
Coherent wind doppler lidar (CWDL) is a cost-effective way to estimate wind power
potential at hub height without the need to build a meteorological tower. However, fog and low
stratus (FLS) can have a negative impact on the availability of lidar measurements. Information
about such reductions in wind data availability for a prospective lidar deployment site in advance is
beneficial in the planning process for a measurement strategy. In this paper, we show that availability
reductions by FLS can be estimated by comparing time series of lidar measurements, conducted
with WindCubes v1 and v2, with time series of cloud base altitude (CBA) derived from satellite
data. This enables us to compute average maps (2006–2017) of estimated availability, including
FLS-induced data losses for Germany which can be used for planning purposes. These maps show
that the lower mountain ranges and the Alpine regions in Germany often reach the critical data
availability threshold of 80% or below. Especially during the winter time special care must be taken
when using lidar in southern and central regions of Germany. If only shorter lidar campaigns are
planned (3–6 months) the representativeness of weather types should be considered as well, because
in individual years and under persistent weather types, lowland areas might also be temporally
affected by higher rates of data losses. This is shown by different examples, e.g., during radiation fog
under anticyclonic weather types.
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Keywords: |
fog |
wind energy |
wind LiDAR |
Egli, S. & Höpke, M. (2020): CNN-Based Tree Species Classification Using High Resolution RGB Image Data from Automated UAV Observations. Remote Sensing 12(23), 3892.
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DOI: 10.3390/rs12233892
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Abstract:
Data on the distribution of tree species are often requested by forest managers, inventory agencies, foresters as well as private and municipal forest owners. However, the automated detection of tree species based on passive remote sensing data from aerial surveys is still not sufficiently developed to achieve reliable results independent of the phenological stage, time of day, season, tree vitality and prevailing atmospheric conditions. Here, we introduce a novel tree species classification approach based on high resolution RGB image data gathered during automated UAV flights that overcomes these insufficiencies. For the classification task, a computationally lightweight convolutional neural network (CNN) was designed. We show that with the chosen CNN model architecture, average classification accuracies of 92% can be reached independently of the illumination conditions and the phenological stages of four different tree species. We also show that a minimal ground sampling density of 1.6 cm/px is needed for the classification model to be able to make use of the spatial-structural information in the data. Finally, to demonstrate the applicability of the presented approach to derive spatially explicit tree species information, a gridded product is generated that yields an average classification accuracy of 88%.
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Keywords: |
cnn |
rgb |
tree species classification |
uav |
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.
Urbich, I.; Bendix, J. & Müller, R. (2020): Development of a Seamless Forecast for Solar Radiation Using ANAKLIM++. Remote Sensing 12(21), 1-19.
Dashpurev, B.; Bendix, J. & Lehnert, L. (2020): Monitoring Oil Exploitation Infrastructure and Dirt Roads with Object-Based Image Analysis and Random Forest in the Eastern Mongolian Steppe. Remote Sensing 12(1), 1-21.
Muenchow, J.; Dieker, P.; Böttcher, T.; Brock, J.; Didenko, G.; Fremout, T.; Jakubka, D.; Jentsch, A.; Nüst, D.; Richter, M.; Rodriguez, E.F.; Rodriguez, R.; Rollenbeck, R.; Salazar Zarsosa, P.; Schratz, P. & Brenning, A. (2020): Monitoring and predictive mapping of floristic biodiversity along a climatic gradient in ENSO's terrestrial core region, NW Peru. Ecography 43(12), 1878--1890.
Lehnert, L.; Thies, B. & Bendix, J. (2020): A new high spatial resolution low stratus/fog retrieval for the Atacama Desert. Remote Sensing of Environment 236, 111445.
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DOI: 10.1016/j.rse.2019.111445
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Abstract:
The Atacama Desert is considered as one of the driest places on Earth. At the coastline, however, small-scale fog
oases harbor a specialized vegetation and fauna, living from moisture by fog, which is used by humans to feed
water demands of industrial projects. To date, knowledge about fog and low stratus (FLS) clouds as well as their
physical properties is limited in that only local observations or spatial products from satellites with coarse
resolutions are available generally failing to capture local patterns resulting from the complex topography.
Consequently, we provide the first climatology of FLS with 30m spatial resolution based on over 400 Landsat
scenes acquired since 1986. The new product provides valuable estimates of FLS optical and micro-physical
properties. FLS over the Pacific Ocean featured cloud optical depth values around 13.5 declining over land to
4.2. Effective radii were around 5.3 μm. Liquid water path was between 71.0 − gm 2 over the Ocean and 14.9 − gm 2
over land surfaces. The climatologies of the new Landsat product were successfully validated against those of the
MODIS cloud property product over homogeneous surfaces. Over areas with heterogeneous topographies, the
new product outperforms existing ones with coarse spatial resolutions if compared against in situ measurements.
This shows the general need for cloud products with high spatial resolutions in areas where the development of
small scale clouds is favored e.g., by a complex topography leading to systematical biases in existing retrievals.
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Keywords: |
Landsat |
fog |
Atacama Desert |
Las Lomitas |
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.
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DOI: 10.1016/j.scitotenv.2019.135372
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Abstract:
Interest in atmosphere-surface flux modeling over the mountainous regions of the globe has increased recently, with a major focus on the prediction of water, carbon and other functional indicators in natural and disturbed conditions. However, less research has been centered on exploring energy fluxes (net radiation; sensible, latent and soil heat) and actual evapotranspiration (ETa) over the Neotropical Andean biome of the páramo. The present study assesses the implementation and parameterization of a state-of-art Land-Surface Model (LSM) for simulation of these fluxes over two representative páramo catchments of southern Ecuador. We evaluated the outputs of the LSM Community Land Model (CLM ver. 4.0) with (i) ground-level flux observations from the first (and highest) Eddy Covariance (EC) tower of the Northern Andean páramos; (ii) spatial ETa estimates from the energy balance-based model METRIC (based on Landsat imagery); and (iii) derived ETa from the closure of the water balance (WB). CLM’s energy predictions revealed a significant underestimation on net radiation, which impacts the sensible and soil heat fluxes (underestimation), and delivers a slight overestimation on latent heat flux. Modeled CLM ETa showed acceptable goodness-of-fit (Pearson R = 0.82) comparable to ETa from METRIC (R = 0.83). Contrarily, a poor performance of ETa WB was observed (R = 0.46). These findings provide solid evidence on the CLM’s accuracy for the ETa modeling, and give insights in the selection of other ETa methods. The study contributes to a better understanding of ecosystem functioning in terms of water loss through evaporative processes, and might help in the development of future LSMs’ implementations focused on climate / land use change scenarios for the páramo.
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Keywords: |
Tropical Andes |
Eddy covariance |
Páramo |
CLM |
METRIC |
Evapotranspiration |
Szymczak, S.; Häusser, M.; Garel, E.; Santoni, S.; Huneau, F.; Knerr, I.; Trachte, K.; Bendix, J. & Bräuning, A. (2020): How Do Mediterranean Pine Trees Respond to Drought and Precipitation Events along an Elevation Gradient?. Forests 11(7), 1.