Spatial and temporal characteristics of Ku-and X-band backscatter signatures of Alpine snow are discussed and related to in situ snow observations. The radar data have been acquired with the airborne SnowSAR sensor over three test sites in the Austrian Alps during the AlpSAR campaign in winter 2012/13. An example for inversion of backscatter images in terms of sow water equivalent (SWE) is presented. The backscatter signatures of three test sites in different elevation zones show significant differences in terms of mean values and temporal trends during the winter season. These variations can be attributed to snow structure and to properties of the medium below the snow pack.

<p><strong>Abstract.</strong> The quantification of ammonia (NH<sub>3</sub>) emissions in ambient air conditions is still a challenge and the corresponding emission factor for grazed pastures have therefore a large uncertainty. This study presents NH<sub>3</sub> emission measurements of two pasture systems in western Switzerland over the entire grazing season 2016. During the measurement campaign, each pasture system was grazed by 12 dairy cows in an intensive rotational management. The cow herds on the two pastures differed in the energy to protein balance of the diet. NH<sub>3</sub> concentrations were measured upwind and downwind of a grazed sub plot with line integrating open path instruments that were able to retrieve small horizontal concentration differences (< 0.2 µg NH<sub>3</sub> m<sup>−3</sup>). The NH<sub>3</sub> emission fluxes were calculated by applying a backward Lagrangian Stochastic (bLS) dispersion model to the difference of paired concentration measurements and prevailed within a range of 0 to 2.5 µg N-NH<sub>3</sub> m<sup>−2</sup> s<sup>−1</sup>. The fluxes increased steadily during a grazing interval from previous non-significant values to reach maximum emissions at the end of the grazing interval. Afterwards they decreased exponentially to near zero values within 3–5 days. A standard emission curve was calculated for each of the two systems and adopted to each rotation in order to account for missing data values and to estimate inflow disturbances due to grazing on upwind paddocks. Dung position measurements and cow position monitoring were performed to account for the non-negligible inhomogeneity of cow excreta on the pasture. The average emission (± std. dev. of individual rotation values) per grazing hour was calculated as 0.64 ± 0.11 g N-NH<sub>3</sub> cow<sup>−1</sup> h<sup>−1</sup> for the herd with the N balanced diet (system M) and 1.07 ± 0.06 g N-NH<sub>3</sub> cow<sup>−1</sup> h<sup>−1</sup> for the herd with the protein rich grass-only diet (system G). Surveys of feed intake, body weight and milk yield of the cow herds were used to estimate the nitrogen (N) excretion by an animal N budget model. Based on that, mean relative emission factors of 6.4 ± 2.0 % and 8.7 ± 2.7 % of the applied urine N were found for the systems M and G, respectively. The results can be used to validate the Swiss national emission inventory and demonstrate the positive effect of a N-balanced diet on pasture NH<sub>3</sub> emission.</p>

Snow extent and water equivalent (SWE) on land and snow accumulation on glaciers are the main parameters to be delivered by the Cold Regions Hydrology High-resolution Observatory (CoReH 2 O) satellite. Detailed scientific and technical studies for the mission are going on within the Earth Explorer Programme of ESA. The CoReH 2 O sensor is a dual frequency SAR, operating at 17.2 and 9.6 GHz, VV and VH polarizations. A main task for mission preparation is the development and validation of algorithms for retrieval of snow parameters. A constrained minimization approach is proposed for SWE retrieval, matching backscatter computed with a radiative transfer model and measurements in the four SAR channels by iterating for SWE and snow grain size. The algorithm was validated with simulated and measured backscatter data. The tests confirm the feasibility of the retrieval approach and help to quantify the requirements for statistical background information which is needed for constraining the solution.

<p><strong>Abstract.</strong> Grazed pastures are strong sources of the greenhouse gas nitrous oxide (N<sub>2</sub>O). The quantification of the emissions is challenging due to the strong spatial and temporal variability of the emission sources and therefore emission estimates are very uncertain. This study presents N<sub>2</sub>O emission measurements of two grazing systems in western Switzerland over the grazing season 2016. Two herds of dairy cows were kept in an intensive rotational grazing management. The diet for the cows consisted of different protein to energy ratios resulting in different N excretion rates. The N in the excretion was estimated by an animal budget model taking into account the measurements of feed intake, milk yield and body weight of the cow herds. Excreta patches and background surfaces on the pasture were identified manually after different grazing rotations and the magnitude and temporal pattern of the single emission sources were measured with a Fast-box (FB) chamber. The field scale fluxes were quantified using two eddy covariance (EC) systems. The FB measurements were finally up-scaled to the field and compared to the EC measurements for quality control by using EC footprint estimates of a backward Lagrangian stochastic dispersion model. Neglecting emission periods influenced by fertilizer applications resulted in significant higher system emissions (960 ± 219 g N<sub>2</sub>O-N, or 25 %) for the full grazing regime (system G) compared to the system with the N balanced diet (system M). Relating the found emissions to the excreta N resulted in grazing related EFs of 1.24 ± 0.20 % for system M and 1.36 ± 0.26 % for system G. The found grazing related EFs were thus significantly smaller compared to the EF of 2 % of the IPCC guidelines. Disaggregating the up-scaled fluxes into single contributors showed that urine patch emission dominated the field scale fluxes (57 %), followed by significant background emissions (38 %) and only a small contribution of dung patch emission (5 %). The resulting EFs of 1.13 ± 0.3 % and 0.17 ± 0.04 % for urine and dung indicates the need to disaggregate the grazing related EFs by excreta type. The study also highlights the advantage of an N optimised diet which resulted in reduced N<sub>2</sub>O emissions on the system level.</p>

No abstract

We'd like to thank the reviewer for his answer and appreciate his valuable comments. Our detailed responses to the referee comments are listed in the attached document.Please also note the supplement to this comment: https://www.biogeosciences-discuss.net/bg-2018-86/bg-2018-86-AC1-supplement.pdfInteractive comment on Biogeosciences Discuss., https://doi

Grazed pastures are strong sources of the greenhouse gas nitrous oxide (N 2 O). The quantification of N 2 O emissions is challenging due to the strong spatial and temporal variabilities of the emission sources and so N 2 O emission estimates are very uncertain. This study presents N 2 O emission measurements from two grazing systems in western Switzerland over the grazing season of 2016. The 12 dairy cows of each herd were kept in an intensive rotational grazing management. The diet for the two herds of cows consisted of different protein-to-energy ratios (system G: grass only diet; system M: grass with additional maize silage) resulting in different nitrogen (N) excretion rates. The N in the excretion was estimated by calculating the animal nitrogen budget taking into account the measurements of feed intake, milk yield, and body weight of the cow herds. Directly after the rotational grazing phases, background and urine patches were identified based on soil electric conductivity measurements while fresh dung patches were identified visually. The magnitude and temporal pattern of these different emission sources were measured with a fast-box (FB) chamber and the field-scale fluxes were quantified using two eddy covariance (EC) systems. The FB measurements were finally upscaled to the field level and compared to the EC measurements for quality control by using EC footprint estimates of a backward Lagrangian stochastic dispersion model. The comparison between the two grazing systems was performed during emission periods that were not influenced by fertilizer applications. This allowed the calculation of the excreta-related N 2 O emissions per cow and grazing hour and resulted in considerably higher emissions for system G compared to system M. Relating the found emissions to the excreta N resulted in excreta-related emission factors (EFs) of 0.74 ± 0.26 % for system M and 0.83 ± 0.29 % for system G. These EF values were thus significantly smaller compared to the default EF of 2 % provided by the IPCC guidelines for cattle excreta deposited on pasture. The measurements showed that urine patch emission dominated the field-scale fluxes (57 %), followed by significant background emissions (38 %), and only a small contribution of dung patch emission (5 %). The resulting source-specific EFs exhibited a clear difference between urine (1.12 ± 0.43 %) and dung (0.16 ± 0.06 %), supporting a disaggregation of the grazing-related EFs by excreta type in emission inventories. The study also highlights the advantage of a N-optimized diet, which resulted in reduced N 2 O emissions from animal excreta.

Grazed pastures are strong sources of the greenhouse gas nitrous oxide (N 2 O). The quantification of N 2 O emissions is challenging due to the strong spatial and temporal variabilities of the emission sources and so N 2 O emission estimates are very uncertain. This study presents N 2 O emission measurements from two grazing systems in western Switzerland over the grazing season of 2016. The 12 dairy cows of each herd were kept in an intensive rotational grazing management. The diet for the two herds of cows consisted of different protein-to-energy ratios (system G: grass only diet; system M: grass with additional maize silage) resulting in different nitrogen (N) excretion rates. The N in the excretion was estimated by calculating the animal nitrogen budget taking into account the measurements of feed intake, milk yield, and body weight of the cow herds. Directly after the rotational grazing phases, background and urine patches were identified based on soil electric conductivity measurements while fresh dung patches were identified visually. The magnitude and temporal pattern of these different emission sources were measured with a fast-box (FB) chamber and the field-scale fluxes were quantified using two eddy covariance (EC) systems. The FB measurements were finally upscaled to the field level and compared to the EC measurements for quality control by using EC footprint estimates of a backward Lagrangian stochastic dispersion model. The comparison between the two grazing systems was performed during emission periods that were not influenced by fertilizer applications. This allowed the calculation of the excreta-related N 2 O emissions per cow and grazing hour and resulted in considerably higher emissions for system G compared to system M. Relating the found emissions to the excreta N resulted in excreta-related emission factors (EFs) of 0.74 ± 0.26 % for system M and 0.83 ± 0.29 % for system G. These EF values were thus significantly smaller compared to the default EF of 2 % provided by the IPCC guidelines for cattle excreta deposited on pasture. The measurements showed that urine patch emission dominated the field-scale fluxes (57 %), followed by significant background emissions (38 %), and only a small contribution of dung patch emission (5 %). The resulting source-specific EFs exhibited a clear difference between urine (1.12 ± 0.43 %) and dung (0.16 ± 0.06 %), supporting a disaggregation of the grazing-related EFs by excreta type in emission inventories. The study also highlights the advantage of a N-optimized diet, which resulted in reduced N 2 O emissions from animal excreta.