Model parameterization to simulate and compare the PAR absorption potential of two competing plant species

Mountain pastures dominated by the pasture grass Setaria sphacelata in the Andes of southern Ecuador are heavily infested by southern bracken (Pteridium arachnoideum), a major problem for pasture management. Field observations suggest that bracken might outcompete the grass due to its competitive strength with regard to the absorption of photosynthetically active radiation (PAR). To understand the PAR absorption potential of both species, the aims of the current paper are to (1) parameterize a radiation scheme of a two-big-leaf model by deriving structural (LAI, leaf angle parameter) and optical (leaf albedo, transmittance) plant traits for average individuals from field surveys, (2) to initialize the properly parameterized radiation scheme with realistic global irradiation conditions of the Rio San Francisco Valley in the Andes of southern Ecuador, and (3) to compare the PAR absorption capabilities of both species under typical local weather conditions. Field data show that bracken reveals a slightly higher average leaf area index (LAI) and more horizontally oriented leaves in comparison to Setaria. Spectrometer measurements reveal that bracken and Setaria are characterized by a similar average leaf absorptance. Simulations with the average diurnal course of incoming solar radiation (1998–2005) and the mean leaf–sun geometry reveal that PAR absorption is fairly equal for both species. However, the comparison of typical clear and overcast days show that two parameters, (1) the relation of incoming diffuse and direct irradiance, and (2) the leaf–sun geometry play a major role for PAR absorption in the two-big-leaf approach: Under cloudy sky conditions (mainly diffuse irradiance), PAR absorption is slightly higher for Setaria while under clear sky conditions (mainly direct irradiance), the average bracken individual is characterized by a higher PAR absorption potential. (∼74 MJ m−2 year−1). The latter situation which occurs if the maximum daily irradiance exceeds 615 W m−2 is mainly due to the nearly orthogonal incidence of the direct solar beam onto the horizontally oriented frond area which implies a high amount of direct PAR absorption during the noon maximum of direct irradiance. Such situations of solar irradiance favoring a higher PAR absorptance of bracken occur in ∼36% of the observation period (1998–2005). By considering the annual course of PAR irradiance in the San Francisco Valley, the clear advantage of bracken on clear days (36% of all days) is completely compensated by the slight but more frequent advantage of Setaria under overcast conditions (64% of all days). This means that neither bracken nor Setaria show a distinct advantage in PAR absorption capability under the current climatic conditions of the study area

Calibration of X-Band Radar for Extreme Events in a Spatially Complex Precipitation Region in North Peru: Machine Learning vs. Empirical Approach

Cost-efficient single-polarized X-band radars are a feasible alternative due to their high sensitivity and resolution, which makes them well suited for complex precipitation patterns. The first horizontal scanning weather radar in Peru was installed in Piura in 2019, after the devastating impact of the 2017 coastal El Niño. To obtain a calibrated rain rate from radar reflectivity, we employ a modified empirical approach and draw a direct comparison to a well-established machine learning technique used for radar QPE. For both methods, preprocessing steps are required, such as clutter and noise elimination, atmospheric, geometric, and precipitation-induced attenuation correction, and hardware variations. For the new empirical approach, the corrected reflectivity is related to rain gauge observations, and a spatially and temporally variable parameter set is iteratively determined. The machine learning approach uses a set of features mainly derived from the radar data. The random forest (RF) algorithm employed here learns from the features and builds decision trees to obtain quantitative precipitation estimates for each bin of detected reflectivity. Both methods capture the spatial variability of rainfall quite well. Validating the empirical approach, it performed better with an overall linear regression slope of 0.65 and r of 0.82. The RF approach had limitations with the quantitative representation (slope = 0.44 and r = 0.65), but it more closely matches the reflectivity distribution, and it is independent of real-time rain-gauge data. Possibly, a weighted mean of both approaches can be used operationally on a daily basis

Wasser- und Energiehaushalt eines neotropischen Tieflandregenwaldes : klimahydrologische Untersuchungen am Rio Surumoni, Estado Amazonas, Venezuela

Venezuela ; Tropischer Regenwald ; Wasserhaushalt ; Energiehaushalt ; Amazona

Assessment of satellite-based rainfall products using a x-band rain radar network in the complex terrain of the ecuadorian andes

Ground based rainfall information is hardly available in most high mountain areas ofthe world due to the remoteness and complex topography. Thus, proper understanding of spatio-temporal rainfall dynamics still remains a challenge in those areas. Satellite-based rainfall productsmay help if their rainfall assessment are of high quality. In this paper, microwave-based inte-grated multi-satellite retrieval for the Global Precipitation Measurement (GPM) (IMERG) (MW-basedIMERG) was assessed along with the random-forest-based rainfall (RF-based rainfall) and infrared-only IMERG (IR-only IMERG) products against the quality-controlled rain radar network andmeteorological stations of high temporal resolution over the Pacific coast and the Andes of Ecuador.The rain area delineation and rain estimation of each product were evaluated at a spatial resolutionof 11 km2and at the time of MW overpass from IMERG. The regionally calibrated RF-based rainfallat 2 km2and 30 min was also investigated. The validation results indicate different essential aspects:(i) the best performance is provided by MW-based IMERG in the region at the time of MW overpass;(ii) RF-based rainfall shows better accuracy rather than the IR-only IMERG rainfall product. Thisconfirms that applying multispectral IR data in retrieval can improve the estimation of rainfall com-pared with single-spectrum IR retrieval algorithms. (iii) All of the products are prone to low-intensityfalse alarms. (iv) The downscaling of higher-resolution products leads to lower product performance,despite regional calibration. The results show that more caution is needed when developing newalgorithms for satellite-based, high-spatiotemporal-resolution rainfall products. The radar data vali-dation shows better performance than meteorological stations because gauge data cannot correctlyrepresent spatial rainfall in complex topography under convective rainfall environments