How Well are We Measuring Snow Post-SPICE?

Accurate snowfall measurements are necessary for meteorology, hydrology, and climate research. Typical uses include creating and calibrating gridded precipitation products, the verification of model simulations, driving hydrologic models, input into aircraft deicing processes, and estimating streamflow runoff in the spring. These applications are significantly impacted by errors in solid precipitation measurements. The recent WMO Solid Precipitation Intercomparison Experiment (SPICE) attempted to characterize and reduce some of the measurement uncertainties through an international effort involving 15 countries utilizing over 20 types and models of precipitation gauges from various manufacturers. Key results from WMO-SPICE are presented herein. Recent work and future research opportunities that build on the results of WMO-SPICE are also highlighted.

Occurrence, Variability and Trends in Snowfall and Rainfall under the background of air temperature and Atmospheric Circulation in Poland

<p>The reaction of precipitation on current warming is ambiguous and differs depending on the region. Particular precipitation phases were found to respond more significantly to recent climate change in many areas located in North America, Asia, Europe and mountains. Since precipitation is an important factor in many environmental processes, trends in its occurrence and totals may trigger various changes in the Earth system and affect life.</p><p>This study aims to recognize the influence of air temperature and atmospheric circulation on the occurrence, variability and trends in precipitation phase indices. We used sub-daily data (every 3h) on air temperature, precipitation totals, notation of weather phenomena in the form of a current (ww) and past weather (W1W2) and cloud types from 38 synoptic stations located in Poland. Moreover, we used various teleconnection patterns to describe macroscale circulation and circulation types to describe regional circulation. Unlike in most studies, precipitation phase was identified based on notation of weather phenomena. Such an approach allowed us to assess a real range of surface air temperature (2m above ground) where snowfall and rainfall occur. Both frequency, totals and quotient of particular precipitation phases were analysed over the period of 1966-2020.  </p><p>Our preliminary results showed that each precipitation phase occurred over a wide range of temperatures; however, most snowfall registered during air temperatures far above freezing point (even 6°C) fell during the existence of cumulonimbus, which indicates strong convection. The highest probability of solid precipitation was linked to air advection from the north-eastern sector under the influence of cyclone (ca.15-20%). Mixed precipitation could be most expected during days with a cyclone centre located over Poland (ca. 20%). The highest probability of liquid precipitation (ca. 70%) was most characteristic of the west and north-west advection under the influence of cyclone and during the cyclone centre or trough over Poland.  </p><p>High year-to-year variability in the indices of precipitation phases impacted their trends. However, liquid precipitation tended to increase in winter over most of the stations. Mixed precipitation exhibited various trend directions depending on the region in winter and decreasing spring and autumn trends. In transitional seasons, a significant decrease was also found in solid precipitation. Most of these changes were significantly related to changes in air temperature except for solid precipitation in winter. Variability in precipitation phases was also correlated with teleconnection patterns, including NAO (negative correlation with solid precipitation in spring and autumn and liquid precipitation in summer, positive correlation with mixed pre in winter), EA (negative correlation with mixed precipitation in autumn) and SCAND (negative correlation with mixed precipitation in winter).</p><p> </p><p>The research performed within the project No. 2017/27/B/ST10/00923, financed by National Science Centre,</p>

Testing the transfer functions for Geonor T-200B and Chinese standard precipitation gauge (CSPG) in the central Qinghai-Tibet Plateau

Geonor T-200B weighing precipitation gauge (Geonor) and Chinese standard precipitation gauge (CSPG) are widely used for measuring precipitaion in the Qinghai-Tibet Plateau. However, their measurements must be adjusted due to wetting, evaporation loss and wind-induced undercatch. Some transfer functions had been proposed in previous studies, but their applicability in the Qinghai-Tibetan Plateau has not been evaluated. In our study, a precipitation measurement intercomparison experiment was carried out from August 2018 to September 2020 at a station in the central Qinghai-Tibet Plateau, and these transfer functions are also evaluated based on the results of the experiment. The results show that: (1) the catch efficiency of Geonor for rain, mixed, snow, hail are 92.06%, 85.32%, 68.08% and 91.82% respectively, and the catch efficiency of CSPG are 92.59%, 81.32%, 46.43% and 95.56% respectively. (2) K2017b has the most accurate correction results for Geonor solid and mixed precipitation at 30 minutes time scale, and the M2007e scheme has the most accurate correction results for Geonor solid precipitation at event scale. (3) The current transfer functions for CSPG underestimate the solid precipitation, while overestimate the liquid precipitation. Based on the results of the comparative observation in our study, new CSPG transfer functions are proposed for the central Qinghai-Tibet Plateau. (4) Hail is also an important precipitation type in the central Qinghai-Tibet Plateau. Because the capture rate of hail precipitation is close to that of rain, and the temperature when hail precipitation occurs is high, it is not necessary to determine the hail precipitation type, and the transfer functions recommended in this study can also get a good correction results.

Future Directions in Precipitation Science

Precipitation science is a growing research field. It is concerned with the study of the water cycle from a broad perspective, from tropical to polar research and from solid precipitation to humidity and microphysics. It includes both modeling and observations. Drawing on the results of several meetings within the International Collaborative Experiments for the PyeongChang 2018 Olympics and Paralympic Winter Games (ICE-POP 2018), and on two Special Issues hosted by Remote Sensing starting with “Winter weather research in complex terrain during ICE-POP 2018”, this paper completes the “Precipitation and Water Cycle” Special Issue by providing a perspective on the future research directions in the field.

Past trends in precipitation and in the ratio of snow to rain in East Greenland

<p>Climate models project a strong increase in Arctic precipitation as well as an increase in the ratio of liquid to solid precipitation for the 21<sup>st</sup> century. While previous studies have explored past trends in precipitation, relatively little is known about the trends in the ratio of liquid to solid precipitation. A regression analysis of the ratio of liquid to solid precipitation in East Greenland will be conducted to better understand if and how precipitation as well as the relative fractions of snow and rain in precipitation have changed in the time period 1958-2019. This will be done in the context of the interdisciplinary project Snow2Rain which focusses on understanding how the transition from snow to rain is influencing quality of life in and around Tasiilaq (Southeast Greenland). Here, in a broader geographical context, a combination of results from the Regional Atmospheric Climate Model (RACMO2.3p2) and meteorological observations from weather stations along the coast of East Greenland between 65° N and 70° N will be used to assess changes in the ratio of liquid to solid precipitation. The station data will serve to cross-check the output from the regional climate model. A simple partitioning scheme based on near-surface temperature will be used. The combination of model data and weather observations can increase our understanding of trends in the relative fraction of precipitation that falls as snow or rain along the data sparse Greenlandic East coast.</p>

Using the measured Particle Size Distribution to assess the wind-induced bias of catching-type raingauges.

<p>Wind-induced biases that affect catching-type precipitation gauges have been largely studied in the literature and dedicated experimental campaigns in the field were carried out to quantify this bias for both liquid and solid precipitation (including the recent WMO intercomparison on solid precipitation – SPICE). Experimental results show a large variability of the Collection Efficiency (CE) curves that depend on the precipitation type, intensity and the Particle Size Distribution (PSD) (see e.g. Colli et al. 2020). This was confirmed by recent studies using Computational Fluid Dynamic simulations to assess the airflow pattern around the gauge body and particle tracking models to simulate the particle trajectories when approaching the collector and calculating the Catch Ratio (CR) associated with various drop size - wind speed combinations (see e.g. Colli et al 2016, Cauteruccio and Lanza 2020).</p><p>In the present study, the CR values derived from the work of Cauteruccio and Lanza (2020) for a catching-type cylindrical gauge as a function of the drop size were fitted with an inverse second-order polynomial. The parameters of such curves were themselves expressed as a function of the wind speed. This formulation was adopted to calculate the CE of a catching-type cylindrical gauge based on contemporary wind and PSD measurements. These were obtained at the field test site of the Hong Kong International Airport using six co-located anemometers and a two-dimensional video disdrometer (2DVD), at one-minute resolution. The obtained CE was used to correct the rainfall intensity measured by three catching-type cylindrical gauges, located at the same site, and was compared with the ratio between the raw data measured by the three cylindrical gauges and the 2DVD rainfall intensity measurements. Results show the improvement due to the correction and suggest that the 2DVD is subject to some wind-induced bias as well.</p><p><strong>References:</strong></p><p>Cauteruccio, A. and L. G. Lanza, 2020. Parameterization of the Collection Efficiency of a Cylindrical Catching-Type Rain Gauge Based on Rainfall Intensity. Water, 12(12), 3431.</p><p>Colli, M., Lanza, L.G., Rasmussen, R. and J.M., Thériault, 2016. The Collection Efficiency of Shielded and Unshielded Precipitation Gauges. Part II: Modeling Particle Trajectories. Journal of Hydrometeorology, 17(1), 245-255.</p><p>Colli, M., Stagnaro, M., Lanza, L.G., Rasmussen, R. and J.M., Thériault, 2020. Adjustments for Wind-Induced Undercatch in Snowfall Measurements based on Precipitation Intensity. Journal of Hydrometeorology, 21, 1039-1050.</p>

Point simulation of snow cover in Peñalara Massif (Sierra de Guadarrama, Central Spain)

<p>The Factorial Snowpack Model (FSM, Essery, 2015) has been applied for the winters ranging from 2008 to 2021 to predict snow height in a location at 1800 m of altitude in Peñalara Massif (Sierra de Guadarrama, Central Spain). Data from an automatic meteorological station is used as input after a thorough validation and completion using different methods. Several configurations of the model have been tested and sensitivity runs regarding long-wave and short-wave radiative flux, air temperature, liquid and solid precipitation rate, surface pressure, relative humidity and wind velocity, have been performed. Comparison of predictions versus automatic and manual in-situ measurements show a coherent evolution of the snow height. A satisfactory degree of precision regarding the beginning and end of the snow cover has been found but also a high sensitivity to radiative flux, mainly long-wave, air temperature and total solid precipitation rates that need further research. Future work will be carried out testing other snowpack models, developing new parametrizations and performing predictions for the  whole basin considering side effects and other factors.</p>

Improvement of Snowgauge Collection Efficiency through a knowledge of solid precipitation fallspeed

The collection efficiency (CE) of a typical gauge-shield configuration decreases with increasing wind speed, with a high scatter for a given wind speed. The scatter in the CE for a given wind speed arises in part from the variability in the characteristics of falling snow and atmospheric turbulence. This study uses weighing gauge data collected at the Marshall Field Site near Boulder, Colorado during the WMO Solid Precipitation InterComparison Experiment (SPICE) to show that the scatter in the collection efficiency can be reduced by considering the fallspeed of solid precipitation particle types. Particle diameter and fallspeed data from a laser disdrometer were used to arrive at this conclusion. In particular, the scatter in the CE of an unshielded snow gauge and a single Alter shield snow gauge is shown to be largely produced by the variation in measured particle fallspeed. The CE was divided into two classes depending on the measured mean-event particle fallspeed. Slower-falling particles were associated with a lower CE. A new transfer function (i.e. the relationship between CE and other meteorological variables, such as wind speed or air temperature) that includes the fallspeed of the hydrometeors was developed. The RMSE of the adjusted precipitation with respect to a weighing gauge placed in a Double Fence Intercomparison Reference was lower than using previously developed transfer functions. This shows that the measured fallspeed of solid precipitation with a laser disdrometer accounts for a large amount of the observed scatter in weighing gauge collection efficiency.

Improvement of solid precipitation measurements using a hotplate precipitation gauge

Accurate snowfall measurement is challenging because it depends on the precipitation gauge used, meteorological conditions, and the precipitation microphysics. Upstream of weighing gauges, the flow field is disturbed by the gauge and any shielding used usually creates an updraft, which deflects solid precipitation from falling in the gauge resulting in significant undercatch. Wind shields are often used with weighing gauges to reduce this updraft and transfer functions are required to adjust the snowfall measurements to consider gauge undercatch. Using these functions reduce the bias in precipitation measurement but not the Root Mean Square Error (RMSE) (Kochendorfer et al. 2017a, b). The analysis performed in this study shows that the hotplate precipitation gauge bias after wind correction is near zero and similar to wind corrected weighing gauges but improves on the RMSE or scatter of the collection efficiency of weighing gauges for a given wind speed. To do this, the accuracy of the hotplate was compared to standard unshielded and shielded weighing gauges collected during the WMO SPICE program. The RMSE of the hotplate measurements is lower than weighing gauges (with or without an Alter shield) for wind speeds up to 5 m s-1; the wind speed limit at which sufficient data were available. This study shows that the hotplate precipitation measurement has a low bias and RMSE due to its aerodynamic shape, making its performance mostly independent of the type of solid precipitation.