Globally, few precipitation records extend to the 18th century. The England Wales Precipitation (EWP) series is a notable exception with continuous monthly records from 1766. EWP has found widespread ...use across diverse fields of research including trend detection, evaluation of climate model simulations, as a proxy for mid‐latitude atmospheric circulation, a predictor in long‐term European gridded precipitation data sets, the assessment of drought and extremes, tree‐ring reconstructions and as a benchmark for other regional series. A key finding from EWP has been the multi‐centennial trends towards wetter winters and drier summers. We statistically reconstruct seasonal EWP using independent, quality‐assured temperature, pressure and circulation indices. Using a sleet and snow series for the UK derived by Profs. Gordon Manley and Elizabeth Shaw to examine winter reconstructions, we show that precipitation totals for pre‐1870 winters are likely biased low due to gauge under‐catch of snowfall and a higher incidence of snowfall during this period. When these factors are accounted for in our reconstructions, the observed trend to wetter winters in EWP is no longer evident. For summer, we find that pre‐1820 precipitation totals are too high, likely due to decreasing network density and less certain data at key stations. A significant trend to drier summers is not robustly present in our reconstructions of the EWP series. While our findings are more certain for winter than summer, we highlight (a) that extreme caution should be exercised when using EWP to make inferences about multi‐centennial trends, and; (b) that assessments of 18th and 19th Century winter precipitation should be aware of potential snow biases in early records. Our findings underline the importance of continual re‐appraisal of established long‐term climate data sets as new evidence becomes available. It is also likely that the identified biases in winter EWP have distorted many other long‐term European precipitation series.
The trend towards wetter winters and drier summers in EWP can be explained by changes in measurement practice and data biases. For winter (Figure below), the timing of divergence aligns with the introduction of the Snowdon Pattern Rain Gauge in the UK around 1863. Given the widespread use of EWP across environmental and climate research, we expect that our findings will challenge understanding of multi‐centennial trends in precipitation in the UK. These changes in measurement practice are also likely to affect other long‐term precipitation records in north‐west Europe.
Tailored products based on climate projections are in demand for climate adaptation planning in different industries. To meet the needs of the tourism industry, the authors applied available ...datatsets to calculate projections for the distribution of precipitation as rain, sleet, and snow in Norway, using daily average temperature to classify the precipitation phases. Amounts and number of days with precipitation in the different phases were calculated. The projections were based on bias-adjusted output from 10 EURO-CORDEX models under two emission scenarios. In general, total precipitation, as well as temperature, was projected to increase, while the number of days with precipitation was not projected to change significantly. The proportion of rainfall was projected to increase while that of snow was expected to decrease. Sleet ratio was projected to decrease in low lying coastal areas, and to increase in mountainous and inland areas. The results were presented for several tourist destinations. However, the authors found that the bias adjustment method applied in the input dataset led to a bias towards too much rain and too little snow, which should be considered when interpreting the results. They concluded that projections of rain, sleet and snow days were considered less affected by that flaw.
•Precipitation types highly depend on surface air temperature, relative humidity and elevation.•A dynamic temperature threshold scheme is developed to discriminate the rain, sleet, and snow.•The new ...parameterization scheme outperforms 11 schemes that have been used in hydrological and land surface models.
Precipitation types (rain, snow, and sleet) have great impacts on the surface runoff and energy balance. However, many weather stations only record precipitation amount without discriminating its type. Based on CMA (China Meteorological Administration) station data over 30years, this study investigates the relationship of precipitation types with surface elevation and meteorological variables. Major findings are (1) wet-bulb temperature is a better indicator than air temperature for discriminating precipitation types; (2) precipitation types are highly dependent on surface elevation, and a higher threshold temperature is needed for differentiating snow and rain over a higher-elevation region; and (3) precipitation types are also dependent on relative humidity, and the probability of sleet event rises greatly with the increase of relative humidity. Based on these findings, a new parameterization scheme is developed to determine the precipitation type, with input of daily mean wet-bulb temperature, relative humidity, and surface elevation. Evaluations for China territory show that the new scheme gives better accuracy than 11 other schemes that are used in hydrological and land surface models.
An emerging and unsolved question is the sensitivity of cloud processes, precipitation, and climate to the atmospheric ice nucleus spectrum. This work revisits estimation of atmospheric ...ice‐nucleating particle concentration derived from cloud water and precipitation samples representing a wide range of geographical locations, seasons, storm systems, precipitation types, instruments, concentrations, and temperatures. Concentrations of ice‐nucleating particles are shown to vary over 10 orders of magnitude. High variability is observed in the −5°C to −12°C range which is suggested to be biologically derived nuclei whose life cycle is associated with intermittent source and efficient sink processes. The highest ever observed nucleus concentrations at −8°C are 3 orders of magnitude lower than observed ice crystal concentrations in tropical cumuli at the same temperature. The observed upper and lower limits of the nucleus spectrum provide a possible constraint on minimum enhancement factors for secondary ice formation processes.
Key Points
New measurements of ice‐nucleating particle in snow, sleet, and rainwater samples
Nucleus concentration varies over 10 orders of magnitude between −5 and −38°C
Ice nucleus spectrum shows high variability between −5 and −12°C
This study compares actual evapotranspiration (ETa) measurements by a set of six weighable lysimeters, ETa estimates obtained with the eddy covariance (EC) method, and evapotranspiration calculated ...with the full-form Penman-Monteith equation (ETPM) for the Rollesbroich site in the Eifel (western Germany). The comparison of ETa measured by EC (including correction of the energy balance deficit) and by lysimeters is rarely reported in the literature and allows more insight into the performance of both methods. An evaluation of ETa for the two methods for the year 2012 shows a good agreement with a total difference of 3.8% (19 mm) between the ETa estimates. The highest agreement and smallest relative differences (< 8%) on a monthly basis between both methods are found in summer. ETa was close to ETPM, indicating that ET was energy limited and not limited by water availability. ETa differences between lysimeter and EC were mainly related to differences in grass height caused by harvest and the EC footprint. The lysimeter data were also used to estimate precipitation amounts in combination with a filter algorithm for the high-precision lysimeters recently introduced by Peters et al. (2014). The estimated precipitation amounts from the lysimeter data differ significantly from precipitation amounts recorded with a standard rain gauge at the Rollesbroich test site. For the complete year 2012 the lysimeter records show a 16 % higher precipitation amount than the tipping bucket. After a correction of the tipping bucket measurements by the method of Richter (1995) this amount was reduced to 3%. With the help of an on-site camera the precipitation measurements of the lysimeters were analyzed in more detail. It was found that the lysimeters record more precipitation than the tipping bucket, in part related to the detection of rime and dew, which contribute 17% to the yearly difference between both methods. In addition, fog and drizzle explain an additional 5.5% of the total difference. Larger differences are also recorded for snow and sleet situations. During snowfall, the tipping bucket device underestimated precipitation severely, and these situations contributed also 7.9% to the total difference. However, 36% of the total yearly difference was associated with snow cover without apparent snowfall, and under these conditions snow bridges and snow drift seem to explain the strong overestimation of precipitation by the lysimeter. The remaining precipitation difference (about 33%) could not be explained and did not show a clear relation to wind speed. The variation of the individual lysimeters devices compared to the lysimeter mean are small, showing variations up to 3% for precipitation and 8% for evapotranspiration.
Abstract
The phase in which precipitation falls—rainfall, snowfall, or sleet—has a considerable impact on hydrology and surface runoff. However, many weather stations only provide information on the ...total amount of precipitation, at other stations series are short or incomplete. To address this issue, data from 40 meteorological stations in Poland spanning the years 1966–2020 were utilized in this study to classify precipitation. Three methods were used to differentiate between rainfall and snowfall: machine learning (i.e., Random Forest), daily mean threshold air temperature, and daily wet bulb threshold temperature. The key findings of this study are: (i) the Random Forest (RF) method demonstrated the highest accuracy in rainfall/snowfall classification among the used approaches, which spanned from 0.90 to 1.00 across all stations and months; (ii) the classification accuracy provided by the mean wet bulb temperature and daily mean threshold air temperature approaches were quite similar, which spanned from 0.86 to 1.00 across all stations and months; (iii) Values of optimized mean threshold temperature and optimized wet bulb threshold temperature were determined for each of the 40 meteorological stations; (iv) the inclusion of water vapor pressure has a noteworthy impact on the RF classification model, and the removal of mean wet bulb temperature from the input data set leads to an improvement in the classification accuracy of the RF model. Future research should be conducted to explore the variations in the effectiveness of precipitation classification for each station.
The purpose of this study is to demonstrate the use of polarimetric observations in a radar-based winter hydrometeor classification algorithm. This is accomplished by deriving bulk electromagnetic ...scattering properties of stratiform, cold-season rain, freezing rain, sleet, dry aggregated snowflakes, dendritic snow crystals, and platelike snow crystals at X-, C-, and S-band wavelengths based on microphysical theory and previous observational studies. These results are then used to define the expected value ranges, or membership beta functions, of a simple fuzzy-logic hydrometeor classification algorithm. To test the algorithms validity and robustness, polarimetric radar data and algorithm output from four unique winter storms are investigated alongside surface observations and thermodynamic soundings. This analysis supports that the algorithm is able to realistically discern regions dominated by wet snow, aggregates, plates, dendrites, and other small ice crystals based solely on polarimetric data, with guidance from a melting-level detection algorithm but without external temperature information. Temperature is still used to distinguish rain from freezing rain or sleet below the radar-detected melting level. After appropriate data quality control, little modification of the algorithm was required to produce physically reasonable results on four different radar platforms at X, C, and S bands. However, classification seemed more robust at shorter wavelengths because the specific differential phase is heavily weighted in ice crystal classification decisions. It is suggested that parts, or all, of this algorithm could be applicable in both operational and research settings.
Abstract
The amount of wind-driven rain (WDR) has been shown to have a major effect on the different deterioration mechanisms of outdoor exposed structures. For example, in recent studies of Finnish ...existing concrete element buildings the amount of WDR has been shown to have strong correlation with the corrosion rate of reinforcements in carbonated concrete and the freeze-thaw damage of concrete. The latter can be related to all porous stone-based materials (e.g., bricks and mortars). In addition, the amount of WDR has a major effect on mould growth potential in different materials or structures sensitive to it. Thus, the effect of the amount of WDR in present climate has been studied comprehensively. In this study, the amount of WDR is calculated for a new 30-year period (1989-2018) presenting the present climate among with two future periods presenting 2050 and 2080 climates. In future climate projections, three different CMPI5 based scenarios are used: RCP2.6, RCP4.5 and RCP8.5. All calculations take into account the wind directions and they are made for four different locations presenting Finland: coastal area, southern Finland, inland and northern Finland (Lapland). Based on the results, the WDR load in the form of rain or sleet is increasing in all locations and from every direction regardless of the used scenario. The highest relative increase is in inland and Lapland, though, the load is still significantly higher in coastal and southern parts of Finland. With all the scenarios the WDR load is still focusing on southern directions, but it will be more evenly divided for other directions than in present climate. In addition, the WDR load is increasing during autumn and wintertime, i.e., during the periods when in the latitudes the drying conditions are weak because of the lack of solar radiation and the high-level relative humidity.
Luminogens with aggregation-induced emission(AIE) characteristics(or AIEgens) have been widely used in various applications due to their excellent luminescent properties in molecular aggregates and ...the solid state. A deep understanding of the AIE mechanism is critical for the rational development of AIEgens. In this work, the “state-crossing from a locally excited to an electron transfer state”(SLEET) model is employed to rationalize the AIE phenomenon of two (bi)piperidylanthracenes. According to the SLEET model, an electron transfer(ET) state is formed along with the rotation of the piperidyl group in the excited state of (bi)piperidylan-thracene monomers, leading to fluorescence quenching. In contrast, a bright state exists in the crystal and molecular aggregates of these compounds, as the intermolecular interactions restrict the formation of the dark ET state. This mechanistic understanding could inspire the deployment of the SLEET model in the rational designs of various functional AIEgens.
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