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Global Attributes:	cloudnet_Conventions: CF-1.0 cloudnet_title: Ice water content from Munich cloudnet_location: Munich cloudnet_day: 25.0 cloudnet_month: 7.0 cloudnet_year: 2018.0 cloudnet_history: 07 Jun 2019 21:12:45 - Generated from categorization data by Patric Seifert <seifert@tropos.de> Categorization history: 07 Jun 2019 21:12:23 - Generated from level 1 data by Ewan O'Connor <e.j.oconnor@reading.ac.uk> Radar history: Original data has been averaged to 30 seconds. Lidar history: Lidar backscatter derived from raw values in arbitrary units: calibrated by user Ewan O'Connor <e.j.oconnor@reading.ac.uk> on 07-Jun-2019. Model history: /e/rhome/routfor/routfox/abs/icon at 20180718 023148 unknown user name on nid00913 (Linux 3.0.101-0.46.1_1.0502.8871-cray_ari_c x86_64) 28-Jul-2018 10:18:02 - NetCDF generated from original data by Ewan O'Connor <ewan.oconnor@fmi.fi> using matlab on cloudnet.fmi.fi. Gauge history: unknown Microwave radiometer history: Unknown cloudnet_source: CloudNet categorization product (software version 0.10.2) comprising: 180725_000001.pds.off; CHX090103; svn://xceh.dwd.de/for0adm/SVN_icon/tags/icon-2.3.0-nwp1@112; Rain gauge; HATPRO microwave radiometer cloudnet_institution: Data processed at the Department of Meteorology, University of Reading. Title: Cloudnet ice water content dataset Institution: Ludwig-Maximilians-Universitaet Muenchen, Meteorologisches Institut Contact_person: Tobias Zinner (tobias.zinner@lmu.de, Meteorologisches Institut, Theresienstr. 37, 80333 Muenchen, Germany) Source: Cloudnet-processed remote-sensing data. See the global argument cloudnet_source for more details. History: Data processed with convert_cloudnet_iwc_to_hdcp.m by TROPOS, Version: 01. [v01, Zinner]: Bug fix. Freezing level in v00 was wrong. Conventions: CF-1.6 where applicable Processing_date: 2019-06-13 19:51:59 Author: Patric Seifert, seifert@tropos.de Comments: This dataset is based on data processed with cloudnet. Cloudnet is member of ACTRIS and data is available for numerous sites in addition to those of HD(CP)2. See http://actris.nilu.no/ for details. There is a distinct data policy agreement between HD(CP)2 and ACTRIS to manage the sharing of datasets between both projects. The nc conventions of the original cloudnet-nc-files were slightly modified to fit HD(CP)2 file conventions. In addition, not all variables of the original cloudnet-nc-files are contained in the HD(CP)2 files. The original comments and global arguments of cloudnet present in the nc files were renamed to cloudnet_ARGUMENT_NAME. Licence: For non-commercial use only. This data is subject to the HD(CP)2 data policy to be found at hdcp2.zmaw.de and in the HD(CP)2 Observation Data Product Standard. In addition the data is subject to the Data Protocol Agreement between ACTRIS and HD(CP)2 for the common use of Cloudnet products: 1. Both ACTRIS and HD(CP)2 scientific steering committees (SSCs) agree, that all Cloudnet products are substantial for multiple applications in atmospheric science related to cloud-processes and should thus be made easily and freely available to atmospheric scientists world-wide. 2. The original and citable Cloudnet data from all ACTRIS and HD(CP)2 atmospheric observatories (AO or termed supersites) are available through the Cloudnet web site (http://www.cloud-net.org) or the ACTRIS data centre (http://actris.nilu.no/). Currently, Cloudnet data is created locally on the respective AO server and then transferred to the Cloudnet server in Reading, UK. 3. An exception to 2.) are the Cloudnet data from the atmospheric observatories LACROS (Leipzig), JOYCE (Juelich) and RAO (Lindenberg) during the course of HD(CP)2. Currently HD(CP)2 is developing an Observation Data Product Standard for its atmospheric column, respectively full-domain data needed for the HD(CP)2 numerical model evaluation and improvement. The main motivation for this is to provide easy access to data from the HD(CP)2 domain in unified formats from one server. HD(CP)2 data will be made available via the ICDC data center (icdc.zmaw.de) in Hamburg. 4. Cloudnet data created at the 3 AOs mentioned above shall be additionally stored in HD(CP)2 compliant file format under the following conditions only. o HD(CP)2-compliant files acknowledge the Cloudnet data origin explicitly in the header in an adequate way. o If Cloudnet data is locally reprocessed and sent to the Cloudnet server, the HD(CP)2 compliant Cloudnet files are also simultaneously recreated and linked with ICDC. o Download statistics of data containing Cloudnet products are created through ICDC once HD(CP)2-compliant Cloudnet files become available. These statistics will be regularly made available to the ACTRIS and HD(CP)2 SSCs to document the use of Cloudnet data. 5. If the above conditions are met during the first phase of HD(CP)2, the HD(CP)2-compliant Cloudnet files may be produced for other AOs in the HD(CP)2 domain. This is subject to the agreement of both ACTRIS and HD(CP)2 SSCs. 6. In the future, ACTRIS and HD(CP)2 agree on an effort towards a unified Cloudnet data portal of all European AOs, strongly linked to the activities already on-going with the US partners from ARM/DOE. Dependencies: external Station_name: LMU Munich Cloudnet Site at munich Unlimited_Dimension: time

Variables:	time: Array of 64 bit Reals [time = 0..2879] time: standard_name: time long_name: time of profile units: seconds since 1970-01-01 00:00:00 bounds: time_bnds
	time_bnds: Array of 64 bit Reals [time = 0..2879][nv = 0..1] time: nv:
	zag: Array of 32 bit Reals [height = 0..475] height: standard_name: height long_name: height above ground units: m bounds: zag_bnds
	zag_bnds: Array of 32 bit Reals [height = 0..475][nv = 0..1] height: nv:
	zsl: 32 bit Real zsl standard_name: altitude long_name: Altitude above mean sea level units: m
	lon: 32 bit Real lon standard_name: longitude units: degree_east
	lat: 32 bit Real lat standard_name: latitude units: degree_north
	iwc: Array of 32 bit Reals [time = 0..2879][height = 0..475] time: height: long_name: mass concentration of frozen water in air units: kg m-3 _FillValue: -999.0 comment: This variable was calculated from the 35.5-GHz radar reflectivity factor after correction for gaseous attenuation, and temperature taken from a forecast model, using the following empirical formula: log10(iwc[g m-3]) = 0.000242Z[dBZ]T[degC] + 0.0699Z[dBZ] + -0.0186T[degC] + -1.63. In this formula Z is taken to be defined such that all frequencies of radar would measure the same Z in Rayleigh scattering ice. However, the radar is more likely to have been calibrated such that all frequencies would measure the same Z in Rayleigh scattering liquid cloud at 0 degrees C. The measured Z is therefore multiplied by \|K(liquid,0degC,35GHz)\|^2/0.93 = 0.9441 before applying this formula. The formula has been used where the "categorization" data has diagnosed that the radar echo is due to ice, but note that in some cases supercooled drizzle will erroneously be identified as ice. Missing data indicates either that ice cloud was present but it was only detected by the lidar so its ice water content could not be estimated, or that there was rain below the ice associated with uncertain attenuation of the reflectivities in the ice. Note that where microwave radiometer liquid water path was available it was used to correct the radar for liquid attenuation when liquid cloud occurred below the ice; this is indicated a value of 3 in the iwc_retrieval_status variable. There is some uncertainty in this prodedure which is reflected by an increase in the associated values in the iwc_error variable. When microwave radiometer data were not available and liquid cloud occurred below the ice, the retrieval was still performed but its reliability is questionable due to the uncorrected liquid water attenuation. This is indicated by a value of 2 in the iwc_retrieval_status variable, and an increase in the value of the iwc_error variable The error variable is determined as follows: iwc_error=10*log[ (X+dX)/X ] with X being the measured value and dX being the absolute uncertainty.
	iwc_error: Array of 32 bit Reals [time = 0..2879][height = 0..475] time: height: long_name: error of mass concentration of frozen water in air units: dB _FillValue: -999.0 comment: This variable is an estimate of the one-standard-deviation random error in ice water content due to both the uncertainty of the retrieval (about +50%/-33%, or 1.7 dB), and the random error in radar reflectivity factor from which ice water content was calculated. When liquid water is present beneath the ice but no microwave radiometer data were available to correct for the associated attenuation, the error also includes a contribution equivalent to approximately 250 g m-2 of liquid water path being uncorrected for. As uncorrected liquid attenuation actually results in a systematic underestimate of ice water content, users may wish to reject affected data; these pixels may be identified by a value of 2 in the iwc_retrieval_status variable. Typical errors in temperature contribute much less to the overall uncertainty in retrieved ice water content so are not considered. Missing data in iwc_error indicates either zero ice water content (for which an error in dB would be meaningless), or no ice water content value being reported. Note that when zero ice water content is reported, it is possible that ice cloud was present but was just not detected by any of the instruments. The error variable is determined as follows: iwc_error=10*log[ (X+dX)/X ] with X being the measured value and dX being the absolute uncertainty.
	iwc_bias: 32 bit Real iwc_bias long_name: bias of mass concentration of frozen water in air units: dB _FillValue: -999.0 comment: This variable is an estimate of the possible systematic error (one-standard-deviation) in ice water content due to the calibration error of the radar reflectivity factor from which it was calculated. The error variable is determined as follows: iwc_error=10*log[ (X+dX)/X ] with X being the measured value and dX being the absolute uncertainty.
	iwc_inc_rain: Array of 32 bit Reals [time = 0..2879][height = 0..475] time: height: long_name: mass concentration of frozen water in air including rainy profiles units: kg m-3 _FillValue: -999.0 comment: This variable is the same as iwc, except that values of iwc in ice above rain have been included. This variable contains values which have been severely affected by attenuation and should only be used when the effect of attenuation is being studied
	iwc_sensitivity: Array of 32 bit Reals [height = 0..475] height: long_name: sensitivity of mass concentration of frozen water in air units: kg m^-3 _FillValue: -999.0 comment: This variable is an estimate of the minimum detectable ice water content as a function of height.
	iwc_retrieval_status: Array of 16 bit Unsigned Integers [time = 0..2879][height = 0..475] time: height: long_name: mass concentration of frozen water in air retrieval status units: 1 definition: 0: No ice 1: Reliable retrieval 2: Unreliable: uncorrected attenuation 3: Retrieval with correction for liquid atten. 4: Ice detected only by the lidar 5: Ice above rain: no retrieval 6: Clear sky above rain 7: Would be identified as ice if below freezing 128: Missing Value long_definition: Use unsigned int8 as reference! 0: No ice present 1: Reliable retrieval 2: Unreliable retrieval due to uncorrected attenuation from liquid water below the ice (no liquid water path measurement available) 3: Retrieval performed but radar corrected for liquid attenuation using radiometer liquid water path which is not always accurate 4: Ice detected only by the lidar 5: Ice detected by radar but rain below so no retrieval performed due to very uncertain attenuation 6: Clear sky above rain, wet-bulb temperature less than 0degC: if rain attenuation were strong then ice could be present but undetected 7: Drizzle or rain that would have been classified as ice if the wet-bulb temperature were less than 0degC: may be ice if temperature is in error 128: Missing Value. Probably no measurement performed _FillValue: 128 comment: Use unsigned int8 as reference! This variable describes whether a retrieval was performed for each pixel, and its associated quality, in the form of 8 different classes. The classes are defined in the definition and long_definition attributes. The most reliable retrieval is that without any rain or liquid cloud beneath, indicated by the value 1, then the next most reliable is when liquid water attenuation has been corrected using a microwave radiometer, indicated by the value 3, while a value 2 indicates that liquid water cloud was present but microwave radiometer data were not available so no correction was performed. No attempt is made to retrieve ice water content when rain is present below the ice; this is indicated by the value 5. bit 7 (2^7=128) is not Cloudnet standard. It was added for HDCP2. _Unsigned: True

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DDS:

Dataset {
    Float64 time[time = 2880];
    Float64 time_bnds[time = 2880][nv = 2];
    Float32 zag[height = 476];
    Float32 zag_bnds[height = 476][nv = 2];
    Float32 zsl;
    Float32 lon;
    Float32 lat;
    Float32 iwc[time = 2880][height = 476];
    Float32 iwc_error[time = 2880][height = 476];
    Float32 iwc_bias;
    Float32 iwc_inc_rain[time = 2880][height = 476];
    Float32 iwc_sensitivity[height = 476];
    UInt16 iwc_retrieval_status[time = 2880][height = 476];
} ftpthredds/samd/data/cln/00/iwc/l4/sups/lmu/2018/sups_lmu_cln00_l4_iwc_v01_20180725000015.nc;

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