the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
High-resolution hydrometeorological and snow data for the Dischma catchment in Switzerland
Abstract. We present a high-resolution hydrometeorological and snow dataset from the alpine Dischma watershed and its surroundings in eastern Switzerland, including station measurements of variables such as snow depth and catchment runoff. This dataset is particularly suited for different modelling experiments using distributed and process-based models, including physics-based snow and hydrological models. Additionally, the data is highly useful for testing various snow data assimilation schemes and for developing models representing snow-forest interactions. The dataset covers seven water years from 1 October 2016 to 30 September 2023. The complete domain spans an area of 333 km² with altitudes ranging from 1250 to 3228 meters. The Dischma basin, with its outlet at 1671 m elevation, occupies 42.9 km². Included in the dataset are high-resolution (100 m) hourly meteorological data (air temperature, relative humidity, wind speed and direction, precipitation, as well as long- and shortwave radiation), land cover characteristics (primarily forest properties), and a digital elevation model. Noteworthy, the dataset includes snow depth acquisitions obtained from airborne lidar and photogrammetry surveys, constituting the most extensive spatial snow depth dataset in the European Alps. Along with these gridded datasets, we provide daily quality-controlled snow depth recordings from seven sites, biweekly snow water equivalent measurements from two locations, and hourly runoff and stream temperature observations for the Dischma watershed. The data compiled in this study will be useful for further developing our ability to forecast snow and hydrological conditions in high-alpine headwater catchments that are particularly sensitive to ongoing climate change.
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RC1: 'Comment on essd-2024-374', Francesco Avanzi, 26 Oct 2024
I read with pleasure the very nice manuscript by Magnusson et al. on data from the Dischma catchment in Switzerland. This is one of the most important research catchments in snow hydrology in Europe, and the manuscript is a very welcome addition to the existing literature at it outlines and delivers a hydrologically complete dataset to pursue snow hydrology science using data from this catchment.
I have only some very minor comments and recommend the manuscript to undergo a round of minor revision.
SPECIFIC COMMENT
- Abstract, line 9: may be worth starting by mentioning the exact spatial / temporal resolution rather than saying “high resolution” (as later done at line 15).
- line 18: “the most extensive spatial snow depth dataset”: I guess you mean from lidar and/or photogrammetry correct? This does not include reanalyses or satellite observations. Perhaps it would be good to mention this by simply saying “the most extensive spatial snow depth dataset derived using such techniques” (as you already mention lidar and photogrammetry before)
- line 79: mention which is the latest inventory used?
- Section 3.1: I was a bit surprised to see a constant temperature lapse rate here. One could consider at least seasonal or monthly values. Why was this choice made?
- Section 3.4: what do you mean with “optimal assimilation scheme”? Also, I am a bit puzzled by the fact that all weather variables but precipitation are from COSMO, while precipitation comes from CombiPrecip. How is correlation and consistency between precipitation and other variables (e.g., relative humidity or incoming shortwave radiation) preserved?
- line 182: “of” after “impact”?
- line 264: isn’t this underestimation of precip a bit in contradiction with the previous statement of CombiPrecip providing unbiased hourly precip fields (line 121)? I am not surprised about the potential underestimation at high elevations, so perhaps mention this in the description of CombiPrecip too (see also the discussion about the runoff ratio later)?
Citation: https://doi.org/10.5194/essd-2024-374-RC1 -
RC2: 'Comment on essd-2024-374', Anonymous Referee #2, 14 Nov 2024
This is a review of “High-resolution hydrometeorological and snow data for the Dischma catchment in Switzerland”. Overall, this is a very well written manuscript. The data are well described, and other than a few points of clarity that need to be added, it is in good shape.
My main issue was getting the zip file decompressed. It seems to require a zip64 compliant decompressor (e.g., 7z) as Macos' Finder or CLI `unzip` could extract the files. I recommend that the authors either explicitly note that the file is in zip64 and requires a decompression program that can handle this format. Or, use a different format (tar.gz). I would also recommend the authors
The met netcdf time units appear to be incorrect
double time(time) ;
time:standard_name = "time" ;
time:units = "days since 2016-10-01T00:00:00+01:00" ;
I believe this should be "hours since".Neither Panoply nor Paraview (both CF compliant nc loaders) correctly load the time component and cannot produce a xy-time visualization. I think it is because although it is not required, CF recommends Time x Z x Y x X and the data here have time dim last. https://cfconventions.org/Data/cf-conventions/cf-conventions-1.11/cf-conventions.html#dimensions
The CF standards page lists the incoming fluxes (e.g., downwelling_longwave_flux_in_air) to have a canonical unit of W m-2 – is there a reason the authors deviate from this?
The GeoTIFFs are missing a no-data value. It is presumed to be -9999 but this should be explicitly set, e.g.,
```
gdal_edit.py -a_nodata
```
Specific points:
l15: here and throughout, the use of a debiased NWP output needs to be clearly noted to be NWP output and not observations.
L60 note hourly met data
L70 throughout this section with respect to the percentages of land cover: it is not clear if the authors are describing the sub-set area, or the entire basin. For example, on L76 “accounting for 33% of the area” it is not clear if it is 33% of the lower elevations or of the total basin. Please clarify this throughout
LL74 83% being steeper than 15 degrees is not a particularly interesting stat for a steep mountain basin. Perhaps the authors could add some binning or a steeper threshold?Citation: https://doi.org/10.5194/essd-2024-374-RC2
Data sets
High-resolution hydrometeorological and snow data for the Dischma catchment in Switzerland Jan Magnusson et al. https://drive.switch.ch/index.php/s/ofy2ZW4yVH7dhET
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