Microwave Radiometer - UMBC Microwave Radiometer - Raw Data
Kipp & Zonen Microwave Temperature Profiler (MTP-5) with a 5 min temporal and 50 m vertical resolution.
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Kipp & Zonen Microwave Temperature Profiler (MTP-5) with a 5 min temporal and 50 m vertical resolution.
Monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%) and liquid water (gm-3) up to 10km.
Monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%) and liquid water (gm-3) up to 10km.
The microwave radiometers HATPRO (Humidity and Temperature Profiler) and MiRAC-P (Microwave Radiometer for Arctic Clouds - Passive) continuously measured radiation emitted from the atmosphere throughout the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) expedition on board the research vessel Polarstern. From the measured brightness temperatures, we have retrieved atmospheric variables using statistical methods in a temporal resolution of 1 s covering October 2019 to October 2020. The integrated water vapour (IWV) is derived individually from both radiometers. In addition, we present the liquid water path (LWP), temperature and absolute humidity profiles from HATPRO. To prove the quality and to estimate uncertainty, the data sets are compared to radiosonde measurements from Polarstern. The comparison shows an extremely good agreement for IWV, with standard deviations of 0.08–0.19 kg m -2 (0.39–1.47 kg m -2 ) in dry (moist) situations. The derived profiles of temperature and humidity denote uncertainties of 0.7–1.8 K and 0.6–0.45 gm -3 in 0–2 km altitude.
The microwave radiometer 3-channel (MWR3C) provides time-series measurements of brightness temperatures from three channels centered at 23.834, 30, and 89 GHz. These three channels are sensitive to the presence of liquid water and precipitable water vapor.
The microwave radiometer – 3-channel (MWR3C, RPG-LWP-U90) deployed by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility provides time-series measurements of brightness temperatures from three channels centered at 23.834, 30, and 89 GHz. These three channels are sensitive to the presence of liquid water and precipitable water vapor.
This dataset contains raw data (lv1) from the microwave radiometer (MWR) operated by NOAA Physical Science Laboratory on Nantucket Island for WFIP3.
This dataset contains raw data (lv1) from the microwave radiometer (MWR) operated by NOAA Physical Science Laboratory on Block Island for WFIP3.
This dataset contains raw data (lv1) from the microwave radiometer (MWR) on the barge for WFIP3.
This dataset contains raw data (lv1) from the microwave radiometer (MWR) on the barge for WFIP3.
This dataset contains processed data (lv1) from the microwave radiometer (MWR) operated by NOAA Physical Science Laboratory on Nantucket Island for WFIP3.
This work presents a comparison of integrated water vapor (IWV) data recorded from microwave radiometer (MWR) and sun-photometer (SP) using global navigation satellite system (GNSS) IWV as reference in five mid-latitude sites of Portugal and Spain (2003–2021). A very high correlation is obtained for both instruments (R2 between 0.94 and 0.98), although, while MWR shows a wet bias, SP exhibits a dry one. In addition, a dependence of mean bias error (MBE) and standard deviation (SD) on IWV has been observed, increasing (larger discrepancies) both indices as IWV increases. The solar zenith angle (SZA) dependence is also studied, finding slightly larger discrepancies for the MWR than for SP in comparison with GNSS for very high values of SZA. Finally, a marked seasonal dependence is observed for SP-GNSS differences, modulated by the IWV dependence explained above. In contrast, the seasonal dependence for MWR is quite weaker than it is for SP. Therefore, in spite of the excellent agreement found among the different instruments, it is recommended that: i) the dependence with IWV be studied and corrected to further increase the performance of the instruments, and ii) metadata be used to filter out situations in which the instrument cannot operate properly.
This dataset contains processed data from the CLAMPS 2 Humidity And Temperature PROfiler (HATPRO) Microwave Radiometer and its associated meteorology tower. CLAMPS 2 deployed during fall-winter 2022 (10/3/22-12/27/23) and summer-fall 2023 (6/16/23-10/1/23).
This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous brightness temperature measurements at 35 channels observed with a microwave radiometer MP3000A operated by UND on the Barge for WFIP3. Additional input data in TROPoe are cloud base height from a collocated ceilometer operated by NOAA GML and temperature, water vapor mixing ratio, and pressure from a sensor attached to the MWR housing. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY.
This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous brightness temperature measurements at 35 channels observed with a microwave radiometer MP3000A operated by NOAA Physical Sciences Laboratory on Nantucket Island for WFIP3. Additional input data in TROPoe are cloud base height from a collocated ceilometer operated by NOAA GML and temperature, water vapor mixing ratio, and pressure from a sensor attached to the MWR housing. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY.
This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous brightness temperature measurements at 35 channels observed with a microwave radiometer MP3000A operated by NOAA Physical Sciences Laboratory on the Block Island for WFIP3. Additional input data in TROPoe are cloud base height from a collocated ceilometer operated by NOAA GML and temperature, water vapor mixing ratio, and pressure from a sensor attached to the MWR housing. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY.
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These data monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km.