Long-Term Band Encounters of Rehabilitated North American Eagles

Between 1973 and 2020, 122 Golden Eagles and 115 Bald Eagles submitted to veterinary medical rehabilitation were banded and released upon recovery in three western states. Adults of both species comprised the most commonly banded age class of rehabilitated (rehab) eagles. Bald Eagles admitted for toxins spent less time in rehabilitation than for those admitted for collision trauma. Encounter (band read for any reason) data from banded eagles provided by the Bird Banding Laboratory (BBL) were analyzed and fitted to appropriate functions in an attempt to describe underlying distributions inherent in the data. Up to March 2020, 28 (12.2%) rehab eagles had been encountered. Encounter rate was 7.4% for rehab Golden Eagles and 16.5% for rehab Bald Eagles, slightly different than those reported by BBL overall (8.0%, 12.2%, respectively). All Golden Eagles were recovered (encountered dead) but 26.3% of Bald Eagles were encountered alive. Days in rehabilitation were not different between species or between Bald Eagles encountered dead or alive. Sex ratio of encountered eagles was not different from ratio of banded eagles of either species. Median time between release and encounter for Golden Eagles was 1.75 yr and 1.42 yr for Bald Eagles. Median distance from banding to encounter site for Golden Eagles was 7.5 km and 115.7 km for Bald Eagles. Number of encounters per year was not related to number of rehab eagles banded that year or for any year previous. Encounters of live Bald Eagles > 30 yr old are discussed. Rehab Golden Eagles may have originated predominantly from western Canada and Alaska while Bald Eagles may have been a mix of a local, non-latitudinal migratory population and seasonal latitudinal migrants. Small sample sizes and lack of precise encounter data prevents utility of rehab eagle encounters to contribute to demographic vital rate estimates needed for effective management of either species. Banding rehab eagles may not justify the manpower investment by BBL required to manage data from banders that band rehab eagles exclusively. Falconry training may be warranted to increase survival potential of rehab Golden Eagles. If recent trends continue, increased rehabilitation effort focused on Golden Eagles may be warranted

EXPLOITING SUN-TRACKING MICROWAVE RADIOMETERS FOR TESTING RADIATIVE TRANSFER MODELS OF PRECIPITATING CLOUDS

The effects of the scattering troposphere on propagating signals are important for several microwave applications such as remote sensing and telecommunication. In particular, passive remote sensing exploits ground-based radiometers to retrieve profile information of the atmosphere. On the other hand, telecommunication applications (e.g., satellite communications) require an accurate estimation of the atmospheric effects to minimize the outage probability of the link. Within this context, atmospheric effects can be described through the joint knowledge of the radiopropagation parameters: atmospheric brightness temperature TB and total path attenuation At (also referred to as atmospheric extinction). These two quantities can be described by the radiative transfer theory that formalizes the spatial evolution of the atmospheric radiance and is implemented trough radiative transfer models (RTM). For successfully testing and validating RTM, measurements of both TB and At are needed. A typical approach to get these two quantities is to exploit combined measurements of satellite-beacon receivers (which provide measurements of At) and ground-based radiometers (which measures the TB). The disadvantage of this approach is that At and TB would be affected by different errors because they are derived using two distinct measuring instruments, each of them with different calibration and accuracy. Moreover, radiometers and beacon receivers typically work at different frequencies. This would imply that a frequency scaling approach would be required before using At and TB pairs for quantitative analysis. Actually, most of microwave radiometers are able to provide attenuation products as result of retrievals approaches based on forward models. However, such retrievals can suffer of large uncertainties in rainy conditions due to poor modeling of scattering. The only instruments able to provide simultaneous measurements of At and TB in all-weather conditions are ground based Sun-tracking radiometers (STR) that exploit the Sun as a stable radiance source. STR performs the retrieval of At exploiting two nearly simultaneous measurements of TB at the same elevation. This is accomplished by alternatively pointing the receiving antenna toward-the-Sun and off-the-Sun during the Sun tracking. The aim of this work is to exploit STR measurements to test and validate RTM simulations in cloudy and rainy conditions. We have considered two different models. First, a Sky Noise Eddington Model (SNEM): a 1D-model that gives an analytical approximation of the solution of the radiative transfer equation. SNEM simulations provide a synthetic clouds dataset through random generation of seasonal-dependent and time-decorrelated meteorological variables with statistics driven by radiosounding profiles. Second: a pseudo-3D radiative transfer model based on the Goddard Satellite Data Simulator Unit (G-SDSU, Matsui et al. JGR 2014) that is able to produce synthetic radiances and path attenuation as measured by ground-based microwave radiometers at several elevation angles and frequencies. In this work we use G-SDSU to convert 3D temporal profiles of meteorological variables, produced by Numerical Weather Forecasts, into predicted TB and At. RTMs are tested exploiting measurements from a STR installed at the Air Force Research Laboratory in Rome, NY, USA. The STR has four receiving channels at K (23.8 GHz), Ka (31.4 GHz), V (72.5 GHz) and W (82.5 GHz) band providing measurements for the years 2015-2016 at elevation angles varying between 20° and 70° (due to the antenna pointing-switching for the Sun tracking). The agreement between measurements and models highlights the reliability of the produced radiation database that can be exploited to develop and update parametric prediction models of attenuation. The use of RTM simulations driven by numerical weather forecasts paves the way to new approaches based on the prediction of radio-propagation parameters for specific target areas and temporal periods (as opposed to common prediction schemes based on stationary path attenuation models statistics)

Validating weather-forecast-driven propagation models at millimeter waves using multisource ground-based radiometric data

In this work, several sources are used to characterize, in both deterministic and statistical ways, the atmospheric propagation channel in terms of brightness temperature and path attenuation at high frequency bands (such as K- Ka-, V- and W-band). We have used two different models: a weather-forecast-driven 3-dimensional radiative transfer model (RTM) and a stochastic 1-dimensional model (SNEM) with synthetic clouds dataset provided as inputs. We have compared the outputs of such radiative transfer simulations with actual measurements of two co-located microwave radiometers: a humidity and temperature profiler and a Sun-tracking radiometer. The comparisons show satisfactory results and a good agreement among all sources, with some small inaccuracies to be investigated in future works. RTM successfully reproduced correlations between brightness temperature and path attenuation at several frequency bands, confirming the advantage of using weather forecast models combined with physically-based radiative transfer models. Also, the SNEM model showed to be able to reproduce the atmospheric channel but a proper fine tuning is needed to better represent the climatological conditions of the area of interest