@article{MayerUllmannHeinrichetal.2019,
  author    = {Mayer, Martin and Ullmann, Wiebke and Heinrich, Rebecca and Fischer, Christina and Blaum, Niels and Sunde, Peter},
  title     = {Seasonal effects of habitat structure and weather on the habitat selection and home range size of a mammal in agricultural landscapes},
  series = {Landscape ecology},
  volume    = {34},
  journal   = {Landscape ecology},
  number    = {10},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {0921-2973},
  doi       = {10.1007/s10980-019-00878-9},
  pages     = {2279 -- 2294},
  year      = {2019},
  abstract  = {Context Human land use intensified over the last century and simultaneously, extreme weather events have become more frequent. However, little is known about the interplay between habitat structure, direct short-term weather effects and indirect seasonal effects on animal space use and behavior. Objectives We used the European hare (Lepus europaeus) as model to investigate how habitat structure and weather conditions affect habitat selection and home range size, predictors for habitat quality and energetic requirements. Methods Using > 100,000 GPS positions of 60 hares in three areas in Denmark and Germany, we analyzed habitat selection and home range size in response to seasonally changing habitat structure, measured as vegetation height and agricultural field size, and weather. We compared daily and monthly home ranges to disentangle between direct short-term weather effects and indirect seasonal effects of climate. Results Habitat selection and home range size varied seasonally as a response to changing habitat structure, potentially affecting the availability of food and shelter. Overall, habitat structure and seasonality were more important in explaining hare habitat selection and home range size compared to direct weather conditions. Nevertheless, hares adjusted habitat selection and daily home range size in response to temperature, wind speed and humidity, possibly in response to thermal constrains and predation risk. Conclusions For effective conservation, habitat heterogeneity should be increased, e.g. by reducing agricultural field sizes and the implementation of set-asides that provide both forage and shelter, especially during the colder months of the year.},
  language  = {en}
}
@misc{CrisologoHeistermann2020,
  author    = {Crisologo, Irene and Heistermann, Maik},
  title     = {Using ground radar overlaps to verify the retrieval of calibration bias estimates from spaceborne platforms},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {863},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-45963},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-459630},
  pages     = {17},
  year      = {2020},
  abstract  = {Many institutions struggle to tap into the potential of their large archives of radar reflectivity: these data are often affected by miscalibration, yet the bias is typically unknown and temporally volatile. Still, relative calibration techniques can be used to correct the measurements a posteriori. For that purpose, the usage of spaceborne reflectivity observations from the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) platforms has become increasingly popular: the calibration bias of a ground radar (GR) is estimated from its average reflectivity difference to the spaceborne radar (SR). Recently, Crisologo et al. (2018) introduced a formal procedure to enhance the reliability of such estimates: each match between SR and GR observations is assigned a quality index, and the calibration bias is inferred as a quality-weighted average of the differences between SR and GR. The relevance of quality was exemplified for the Subic S-band radar in the Philippines, which is greatly affected by partial beam blockage. The present study extends the concept of quality-weighted averaging by accounting for path-integrated attenuation (PIA) in addition to beam blockage. This extension becomes vital for radars that operate at the C or X band. Correspondingly, the study setup includes a C-band radar that substantially overlaps with the S-band radar. Based on the extended quality-weighting approach, we retrieve, for each of the two ground radars, a time series of calibration bias estimates from suitable SR overpasses. As a result of applying these estimates to correct the ground radar observations, the consistency between the ground radars in the region of overlap increased substantially. Furthermore, we investigated if the bias estimates can be interpolated in time, so that ground radar observations can be corrected even in the absence of prompt SR overpasses. We found that a moving average approach was most suitable for that purpose, although limited by the absence of explicit records of radar maintenance operations.},
  language  = {en}
}
@article{CrisologoHeistermann2020,
  author    = {Crisologo, Irene and Heistermann, Maik},
  title     = {Using ground radar overlaps to verify the retrieval of calibration bias estimates from spaceborne platforms},
  series = {Atmospheric Measurement Techniques},
  volume    = {13},
  journal   = {Atmospheric Measurement Techniques},
  number    = {2},
  publisher = {Copernicus Publications},
  address   = {G{\"o}ttingen},
  issn      = {1867-1381},
  doi       = {10.5194/amt-13-645-2020},
  pages     = {645 -- 659},
  year      = {2020},
  abstract  = {Many institutions struggle to tap into the potential of their large archives of radar reflectivity: these data are often affected by miscalibration, yet the bias is typically unknown and temporally volatile. Still, relative calibration techniques can be used to correct the measurements a posteriori. For that purpose, the usage of spaceborne reflectivity observations from the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) platforms has become increasingly popular: the calibration bias of a ground radar (GR) is estimated from its average reflectivity difference to the spaceborne radar (SR). Recently, Crisologo et al. (2018) introduced a formal procedure to enhance the reliability of such estimates: each match between SR and GR observations is assigned a quality index, and the calibration bias is inferred as a quality-weighted average of the differences between SR and GR. The relevance of quality was exemplified for the Subic S-band radar in the Philippines, which is greatly affected by partial beam blockage. The present study extends the concept of quality-weighted averaging by accounting for path-integrated attenuation (PIA) in addition to beam blockage. This extension becomes vital for radars that operate at the C or X band. Correspondingly, the study setup includes a C-band radar that substantially overlaps with the S-band radar. Based on the extended quality-weighting approach, we retrieve, for each of the two ground radars, a time series of calibration bias estimates from suitable SR overpasses. As a result of applying these estimates to correct the ground radar observations, the consistency between the ground radars in the region of overlap increased substantially. Furthermore, we investigated if the bias estimates can be interpolated in time, so that ground radar observations can be corrected even in the absence of prompt SR overpasses. We found that a moving average approach was most suitable for that purpose, although limited by the absence of explicit records of radar maintenance operations.},
  language  = {en}
}