MASCDB triplet data#
The file MASCdb_triplet.parquet contains the attributes listed in the table below.
Parameter |
Units |
Type |
Long name |
Reference / Format / Algorithm |
|---|---|---|---|---|
Global information |
||||
datetime |
datetime |
|||
campaign |
string |
Field campaign string |
||
latitude |
deg |
float |
WGS84 latitude |
|
longitude |
deg |
float |
WGS84 longitude |
|
altitude |
m |
float |
||
Flake information |
||||
flake_id |
string |
Unique flake ID
|
e.g. 2015.02.10_11.55.10_flake_4
YYYY.MM.DD_HH.mm.ss_flake_flake_number_tmp
|
|
flake_number_tmp |
string |
Temporary flake ID
(not unique)
|
||
flake_quality_xhi |
float |
Average quality ind
(on the three cams)
|
“xi” in Praz et al, 2017 |
|
flake_fallspeed |
m/s |
float |
Recorded fallspeed |
|
flake_n_roi |
int |
Average N. of ROIs
(on the three cams)
|
||
flake_Dmax |
m |
float |
Maximum Dmax
(on the three cams)
|
Table A1:4 Praz et al, 2017 |
Riming estimation information |
||||
riming_deg_level |
float |
Continuous riming
degree level
|
R_c in Praz et al, 2017 |
|
riming_class_id |
int |
Discrete riming
degree class ID
|
Praz et al, 2017
0: undefined, 1: unrimed, 2: rimed
3: densely-rimed, 4: graupel-like, 5: graupel
|
|
riming_class_prob |
float |
Riming classif.
probability
|
Praz et al, 2017 |
|
riming_class_name |
string |
Discrete riming
degree class name
|
See riming_class_id |
|
Melting estimation information |
||||
melting_class_id |
int |
Discrete melting
class ID
|
Praz et al, 2017
0: dry, 1: melting
|
|
melting_prob |
float |
Melting probability |
Praz et al, 2017
If rounded, it yields melting_class_id
|
|
melting_class_name |
string |
Discrete melting
class name
|
See melting_class_id |
|
Hydrometeor type estimation information |
||||
snowflake_class_name |
string |
Hydrometeor
class name
|
Praz et al, 2017 citePraz
See snowflake_class_id
|
|
snowflake_class_id |
int |
Hydrometeor
class ID
|
Praz et al, 2017 citePraz
1: small_particle, 2: columnar_crystal,
3: planar_crystal, 4: aggregate,
5: graupel, 6: columnar_planar_combination
|
|
snowflake_class_prob |
float |
Classification
probability
|
||
3D reconstruction / mass estimation |
||||
gan3d_mass |
kg |
float |
Estimated mass |
Leinonen et al, 2021 |
gan3d_volume |
m^3 |
float |
Estimated volume |
Leinonen et al, 2021 |
gan3d_gyration |
m |
float |
Estimated gyration rd |
Leinonen et al, 2021 |
Co-located environmental information |
||||
env_T |
deg C |
float |
Air temperature |
|
env_P |
hPa |
float |
Pressure |
|
env_DD |
deg |
float |
Wind direction
|
|
env_FF |
m/s |
float |
Wind speed |
|
env_RH |
% |
float |
Relative humidity |
|
Blowing snow estimation |
||||
bs_normalized_angle |
float |
Blowing Snow
normalized angle
|
Schaer et al 2020
Pure precip. if < 0.193, Pure BS if > 0.881
|
|
bs_mixing_ind |
float |
Blowing snow
mixing index
|
Schaer et al 2020
Only defined in mixed BS/precip environments
|
|
bs_precip_class_name |
string |
Blowing snow
class name
|
Schaer et al 2020
See bs_precip_class_id
|
|
bs_precip_class_id |
int |
Blowing snow
class ID
|
Schaer et al 2020,
0: undefined, 1: precip, 2: mixed,
3: blowing_snow
|
|
References#
Praz et al, 2017: Praz, C., Roulet, Y.-A., and Berne, A.: Solid hydrometeor classification and riming degree estimation from pictures collected with a Multi-Angle Snowflake Camera, Atmos. Meas. Tech., 10, 1335-1357, https://doi.org/10.5194/amt-10-1335-2017, 2017.
Schaer et al, 2020: Schaer, M., Praz, C., and Berne, A.: Identification of blowing snow particles in images from a Multi-Angle Snowflake Camera, The Cryosphere, 14, 367-384, https://doi.org/10.5194/tc-14-367-2020, 2020.
Leinonen et al, 2021: Leinonen, J., Grazioli, J., and Berne, A.: Reconstruction of the mass and geometry of snowfall particles from multi-angle snowflake camera (MASC) images, Atmos. Meas. Tech., 14, 6851-6866, https://doi.org/10.5194/amt-14-6851-2021, 2021.