Temperature stability of the sky quality meter

The stability of radiance measurements taken by the Sky Quality Meter (SQM)was tested under rapidly changing temperature conditions during exposure to a stable light field in the laboratory. The reported radiance was found to be negatively correlated with temperature, but remained within 7% of the initial reported radiance over a temperature range of -15 °C to 35 °C, and during temperature changes of -33 °C/h and +70 °C/h.This is smaller than the manufacturer’s quoted unit-to-unit systematic uncertainty of 10%,indicating that the temperature compensation of the SQM is adequate under expected outdoor operating conditions

The Added Value of Large-Eddy and Storm-Resolving Models for Simulating Clouds and Precipitation

More than one hundred days were simulated over very large domains with fine (0.156 km to 2.5 km) grid spacing for realistic conditions to test the hypothesis that storm (kilometer) and large-eddy (hectometer) resolving simulations would provide an improved representation of clouds and precipitation in atmospheric simulations. At scales that resolve convective storms (storm-resolving for short), the vertical velocity variance becomes resolved and a better physical basis is achieved for representing clouds and precipitation. Similarly to past studies we found an improved representation of precipitation at kilometer scales, as compared to models with parameterized convection. The main precipitation features (location, diurnal cycle and spatial propagation) are well captured already at kilometer scales, and refining resolution to hectometer scales does not substantially change the simulations in these respects. It does, however, lead to a reduction in the precipitation on the time-scales considered – most notably over the ocean in the tropics. Changes in the distribution of precipitation, with less frequent extremes are also found in simulations incorporating hectometer scales. Hectometer scales appear to be more important for the representation of clouds, and make it possible to capture many important aspects of the cloud field, from the vertical distribution of cloud cover, to the distribution of cloud sizes, and to the diel (daily) cycle. Qualitative improvements, particularly in the ability to differentiate cumulus from stratiform clouds, are seen when one reduces the grid spacing from kilometer to hectometer scales. At the hectometer scale new challenges arise, but the similarity of observed and simulated scales, and the more direct connection between the circulation and the unconstrained degrees of freedom make these challenges less daunting. This quality, combined with already improved simulation as compared to more parameterized models, underpins our conviction that the use and further development of storm-resolving models offers exciting opportunities for advancing understanding of climate and climate change

Advancing Ground-Based Water Vapor Profiling through Synergy of Microwave Radiometer and Dual-Frequency Radar

Continuous water vapor profiling methods are crucial for advancing the understanding of the role of clouds and water vapor in Earth's climate system. Particularly in the maritime trade wind driven environment, where shallow cumulus clouds prevail, the interplay between cloud and convection processes is not quantified satisfactorily. Current instrumentation techniques are limited by low temporal resolution in the case of soundings, signal saturation at cloud boundaries in the case of optical methods, or too coarse vertical resolutions in the case of passive microwave measurements. Therefore, in this thesis, the feasibility of a novel synergy concept is assessed by combining synthetic microwave radiometer (MWR) and dual-frequency radar measurements. The synergy benefits are evaluated for a combination of seven MWR K-band brightness temperatures (TBs) with a Ka- and W-band radar combination (KaW), e.g. available at Barbados Cloud Observatory (BCO), and a Differential Absorption Radar (DAR) frequency combination of 167.0 and 174.8 GHz (G2). An optimal estimation framework retrieving the absolute humidity profile was selected to evaluate the synergy concept by deriving the retrieval uncertainty, information content through Degrees of Freedom of Signal (DFS), as well as the accuracy of the retrieved profile and partial water vapor amount. By varying the observation vector configuration to include both MWR TBs and radar Dual-Wavelength Ratio (DWR) in the synergistic configuration, or only TBs or only DWR in the single-instrument runs, the synergistic impacts were analyzed for an idealized single-cloud scenario frequently observed at BCO, and for three selected, more complex cases observed during the EUREC4A field study. Additional 2m humidity and cloud boundary measurements further constrain the retrieval. Based on the single-layered cloud scenario with varying water vapor conditions, the analyses show that the total information content of a MWR+KaW combination only increases marginally by less than 6%, while the DFS in case of the MWR+G2 synergy increases by 1.2 DFS on average compared to the MWR-only configuration. While the sub- and in-cloud information content is increased by 1 DFS, driven by the radar measurements, the synergistic information content above the cloud layer is enhanced by 13.5% compared to the MWR-only configuration. Meanwhile, the synergistic MWR+G2 retrieval uncertainty decreases around cloud base to 1.0gm-3, corresponding to a 28% reduction compared to the MWR-only configuration. The synergistic benefits are most sensitive to the assumed radar measurement error, leading to an uncertainty increase of 0.1gm-3 in the cloud layer when the DWR error is doubled, as well as to radar signal saturation before reaching cloud top. Case study analyses of two double-layered cloud scenarios confirm the findings of the single-cloud layer case as the information content above each cloud layer is increased in all cases by up to 0.3 DFS. A modified retrieval concept serves to evaluate the role of the synergy when reconstructing the atmospheric state at 12 hours between 24-hour spaced operational radiosondes based on the EUREC4A case scenarios. While the total synergistic information gain is reduced to 0.2 - 0.6 DFS due to the more accurate prior assumptions, the derived dry free tropospheric water vapor amount agrees better, by up to 3.6kgm-2, with the observed sounding reality than the interpolated prior amount. As expected, the addition of synthetic Raman lidar measurements improves the retrieval performance particularly in the sub-cloud layer, leading to increasing sub-cloud information content of 0.8 - 1.3 DFS, and decreasing optimal to prior uncertainty ratio of 13.6 - 26.2 percentage points compared to the MWR+G2 retrieval. A modified observation vector configuration including the simulated in-cloud humidity, as would e.g. be available by an independent direct inversion retrieval, further decreases the retrieval uncertainty in respect to the prior by 11.4 percentage points between the cloud layers. Under realistic instrument deployment, the simulated measurements suggest that current G-band radar signal sensitivity would impair profiling the whole vertical cloud extent for the simulated thin liquid clouds in the trades. First simulated cases show similar restrictions for an airborne deployment in the trades, for example on HALO. Simulated radar measurements for an idealized mixed-phase cloud scenario in the drier Arctic environment as observed at Ny-Ålesund, Spitsbergen, suggest that current G-band radar sensitivities would allow evaluating the concept in drier conditions than observed in the tropics. The analyzed benefits suggest that a synergy of MWR and G-band DAR could contribute to closing the current observational gap of continuous high-resolution water vapor profile measurements

Temperature Stability of the Sky Quality Meter

The stability of radiance measurements taken by the Sky Quality Meter (SQM)was tested under rapidly changing temperature conditions during exposure to a stable lightfield in the laboratory. The reported radiance was found to be negatively correlated withtemperature, but remained within 7% of the initial reported radiance over a temperaturerange of -15 °C to 35 °C, and during temperature changes of -33 °C/h and +70 °C/h.This is smaller than the manufacturer’s quoted unit-to-unit systematic uncertainty of 10%,indicating that the temperature compensation of the SQM is adequate under expected outdoor operating conditions

Precipitation amount of Pluvio rain gauge at AWIPEV, Ny-Ålesund (2020)

The OTT Pluvio2 Version 400 is an all-weather precipitation gauge that measures the amount of precipitation using the weighing principle. It measures the weight of the collecting bucket including its content. The difference between the current bucket content and the previous one recorded gives the precipitation amount. The data set includes the non-real-time output of the OTT software which is particularly suited for daily and monthly totals. The non-real-time output provides a more precise precipitation sum due to better filtering: fine precipitation is collected over a maximum of one hour and output after reaching the threshold of 0.05 mm within that hour. If the fine precipitation does not reach the threshold within an hour, there will be no output. The resolution of the precipitation values is 0.01 mm. The measurement uncertainty is the larger value of ± 0.1 mm or ±1%

Precipitation amount of Pluvio rain gauge at AWIPEV, Ny-Ålesund (2017-2021)

The OTT Pluvio2 Version 400 is an all-weather precipitation gauge that measures the amount of precipitation using the weighing principle. It measures the weight of the collecting bucket including its content. The difference between the current bucket content and the previous one recorded gives the precipitation amount. The data set includes the non-real-time output of the OTT software which is particularly suited for daily and monthly totals. The non-real-time output provides a more precise precipitation sum due to better filtering: fine precipitation is collected over a maximum of one hour and output after reaching the threshold of 0.05 mm within that hour. If the fine precipitation does not reach the threshold within an hour, there will be no output. The resolution of the precipitation values is 0.01 mm. The measurement uncertainty is the larger value of ± 0.1 mm or ±1%. In each of the datasets for the years 2017-2021 daily netCDF files are provided