Fractal geometry of aggregate snowflakes revealed by triple wavelength radar measurements

Radar reflectivity measurements from three different wavelengths are used to retrieve information about the shape of aggregate snowflakes in deep stratiform ice clouds. Dual-wavelength ratios are calculated for different shape models and compared to observations at 3, 35 and 94 GHz. It is demonstrated that many scattering models, including spherical and spheroidal models, do not adequately describe the aggregate snowflakes that are observed. The observations are consistent with fractal aggregate geometries generated by a physically-based aggregation model. It is demonstrated that the fractal dimension of large aggregates can be inferred directly from the radar data. Fractal dimensions close to 2 are retrieved, consistent with previous theoretical models and in-situ observations

Vitamin D status in irritable bowel syndrome and the impact of supplementation on symptoms: what do we know and what do we need to know?

BACKGROUND: Low vitamin D status is associated with risk of colorectal cancer and has been implicated in inflammatory bowel disease. Irritable bowel syndrome (IBS) is a chronic, relapsing, functional bowel disorder. A nascent literature suggests a role for vitamin D in IBS, but this has not been collated or critiqued. To date, seven studies have been published: four observational studies and three randomised controlled trials (RCTs). All observational studies reported that a substantial proportion of the IBS population was vitamin D deficient. Two intervention studies reported improvement in IBS symptom severity scores and quality of life (QoL) with vitamin D supplementation. There are limited data around the role of vitamin D in IBS. CONCLUSIONS: The available evidence suggests that low vitamin D status is common among the IBS population and merits assessment and rectification for general health reasons alone. An inverse correlation between serum vitamin D and IBS symptom severity is suggested and vitamin D interventions may benefit symptoms. However, the available RCTs do not provide strong, generalisable evidence; larger and adequately powered interventions are needed to establish a case for therapeutic application of vitamin D in IBS

Multi-Year Analysis of Rain-Snow Levels at Marquette, Michigan

This study uses observations from a ground-based instrument suite to investigate the rain-snow level (RSL) in stratiform rainfall from January 2014 to April 2020 in the Upper Great Lakes Region. The height above the surface where ice melts to rain, the rain-snow level, influences microphysical assumptions in remote sensing precipitation retrievals and the ability of space-based radar to discriminate surface precipitation phase because of ground clutter. The instrument suite is installed at the Marquette, MI (MQT) National Weather Service station adjacent to Lake Superior. Rain events and the RSLs are studied through a ground-based vertically profiling radar (Micro Rain Radar), a custom NASA-developed video disdrometer (Precipitation Imaging Package), and reanalysis products from ECMWF ERA5 and NASA MERRA-2. Distinct macro and microphysical characteristics are observed in precipitation events with shallow RSLs (1.8 km AGL). Intermediate RSLs correspond to rain events with relatively higher rain rates and a higher concentration of small drops in the drop size distributions (DSDs). Shallow RSL DSDs contain relatively higher concentrations of large drops with lower fall speeds suggesting that partially melted snowflakes may be reaching the surface. Reflectivity-rain-rate relationships are also impacted by microphysical differences associated with RSL regimes. Radar-detected RSLs agree with reanalysis-derived melt levels-especially at wet-bulb isotherms of 0.5°C and 1°C. Seasonal differences such as shallow RSLs in winter, fall, and spring have subsequent implications for satellite detectability.Plain Language SummaryThe height above the surface where falling snow melts to rain, the rain-snow level (RSL), can be detected by both ground-based and space-based radars. However, space-based radars are limited in their ability to capture precipitation near the surface due to interference. This work investigates RSLs between January 2014 and April 2020 from ground-based observations at the Marquette, MI National Weather Service office. This work includes observations from ground-based profiling radar and a custom NASA-developed instrument that records high resolution videos of precipitation at the surface. In addition, profile temperature and moisture data are used. These products are commonly used with satellite observations to determine the surface precipitation phase. The results show different characteristics for rain events with shallow and intermediate RSLs. The radar-detected RSLs illustrate good agreement with melt levels derived from reanalysis profile data, which is useful for satellite retrievals of precipitation. Seasonal differences such as shallow rain-snow levels in winter, fall, and spring have subsequent implications for satellite detectability.Key PointsRain-snow levels (RSLs) are shallow in winter. In autumn and spring, RSLs span the full range of the profiling radarRainfall microphysical characteristics and rates vary with RSLsRSLs determined from vertically profiling radar Doppler velocity correlate well with reanalysis derived melt levelsPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/175770/1/jgrd58447_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/175770/2/jgrd58447.pd

Evaluation of the GPM-DPR snowfall detection capability: Comparison with CloudSat-CPR

© 2017 An important objective of the Global Precipitation Measurement (GPM) mission is the detection of falling snow, since it accounts for a significant fraction of precipitation in the mid-high latitudes. The GPM Core Observatory carries the first spaceborne Dual-frequency Precipitation Radar (DPR), designed with enhanced sensitivity to detect lighter liquid and solid precipitation. The primary goal of this study is to assess the DPR\u27s ability to identify snowfall using near-coincident CloudSat Cloud Profiling Radar (CPR) observations and products as an independent reference dataset. CloudSat near global coverage and high sensitivity of the W-band CPR make it very suitable for snowfall-related research. While DPR/CPR radar sensitivity disparities contribute substantially to snowfall detection differences, this study also analyzes other factors such as precipitation phase discriminators that produce snowfall identification discrepancies. Results show that even if the occurrence of snowfall events correctly detected by DPR products is quite small compared to CPR (around 5–7%), the fraction of snowfall mass is not negligible (29–34%). A direct comparison of CPR and DPR reflectivities illustrates that DPR misdetection is worsened by a noise-reducing DPR algorithm component that corrects the measured reflectivity. This procedure eliminates the receiver noise and side lobe clutter effects, but also removes radar signals related to snowfall events that are associated with relatively low reflectivity values. In an effort to increase DPR signal fidelity associated with snowfall, this paper proposes a simple algorithm using matched DPR Ku/Ka radar reflectivities producing an increase of the fraction of snowfall mass detected by DPR up to 59%

The IPWG satellite precipitation validation effort

The estimation of precipitation (rainfall and snowfall) across the Earth’s surface is important for both science and user applications, ranging from understanding and improving our knowledge of the global energy and water cycle, to water resources and hydrological modelling, and to societal applications such as water availability and monitoring of waterborne diseases (see Kirschbaum DB, Huffman GJ, Adler RF, Braun S, Garrett K, Jones E, McNally A, Skofronick-Jackson G, Stocker E, Wu H, Zaitchik BF, Bull Am Meteorol Soc 98:1169–1194, 2017). The global mapping of precipitation through conventional means is essentially limited to land areas due to the reliance upon rain (and snow) gauges and/or radar (see Kidd C, Becker A, Huffman GJ, Muller CL, Joe P, Skofronick-Jackson G, Kirschbaum DB, Bull Am Meteorol Soc 98:69–78, 2017a). For truly global precipitation mapping satellite observations must be used. A range of techniques, algorithms and schemes have been developed to exploit these satellite observations and generate quantitative precipitation products, many with (quasi-) global coverage. Alongside these techniques, there is a need for the inter-comparison, verification, and validation of such products in order to quantify their accuracy and performance (and consistency) for both developers and users. The International Precipitation Working Group (IPWG) has supported a long-term effort to inter-compare and validate precipitation products through the exploitation of large-scale regional surface reference data sets. Here, we present the current and future validation efforts of the IPWG together with examples of satellite-surface inter-comparisons