2 results
Search Results
Now showing 1 - 2 of 2
- ItemRole of the dew water on the ground surface in HONO distribution: A case measurement in Melpitz(Katlenburg-Lindau : EGU, 2020) Ren, Yangang; Stieger, Bastian; Spindler, Gerald; Grosselin, Benoit; Mellouki, Abdelwahid; Tuch, Thomas; Wiedensohler, Alfred; Herrmann, HartmutTo characterize the role of dew water for the ground surface HONO distribution, nitrous acid (HONO) measurements with a Monitor for AeRosols and Gases in ambient Air (MARGA) and a LOng Path Absorption Photometer (LOPAP) instrument were performed at the Leibniz Institute for Tropospheric Research (TROPOS) research site in Melpitz, Germany, from 19 to 29 April 2018. The dew water was also collected and analyzed from 8 to 14 May 2019 using a glass sampler. The high time resolution of HONO measurements showed characteristic diurnal variations that revealed that (i) vehicle emissions are a minor source of HONO at Melpitz station; (ii) the heterogeneous conversion of NO2 to HONO on the ground surface dominates HONO production at night; (iii) there is significant nighttime loss of HONO with a sink strength of 0.16±0.12ppbv h-1; and (iv) dew water with mean NO-2 of 7.91±2.14 μgm-2 could serve as a temporary HONO source in the morning when the dew droplets evaporate. The nocturnal observations of HONO and NO2 allowed the direct evaluation of the ground uptake coefficients for these species at night: γNO2→HONO = 2.4±10-7 to 3.5±10-6, γHONO;ground = 1.7×10-5 to 2.8×10-4. A chemical model demonstrated that HONO deposition to the ground surface at night was 90 %-100% of the calculated unknown HONO source in the morning. These results suggest that dew water on the ground surface was controlling the temporal HONO distribution rather than straightforward NO2-HONO conversion. This can strongly enhance the OH reactivity throughout the morning time or in other planted areas that provide a large amount of ground surface based on the OH production rate calculation. © 2020 Copernicus GmbH. All rights reserved.
- ItemMultivariate non-parametric Euclidean distance model for hourly disaggregation of daily climate data(Wien [u.a.] : Springer, 2021) Görner, Christina; Franke, Johannes; Kronenberg, Rico; Hellmuth, Olaf; Bernhofer, ChristianThe algorithm for and results of a newly developed multivariate non-parametric model, the Euclidean distance model (EDM), for the hourly disaggregation of daily climate data are presented here. The EDM is a resampling method based on the assumption that the day to be disaggregated has already occurred once in the past. The Euclidean distance (ED) serves as a measure of similarity to select the most similar day from historical records. EDM is designed to disaggregate daily means/sums of several climate elements at once, here temperature (T), precipitation (P), sunshine duration (SD), relative humidity (rH), and wind speed (WS), while conserving physical consistency over all disaggregated elements. Since weather conditions and hence the diurnal cycles of climate elements depend on the weather pattern, a selection approach including objective weather patterns (OWP) was developed. The OWP serve as an additional criterion to filter the most similar day. For a case study, EDM was applied to the daily climate data of the stations Dresden and Fichtelberg (Saxony, Germany). The EDM results agree well with the observed data, maintaining their statistics. Hourly results fit better for climate elements with homogenous diurnal cycles, e.g., T with very high correlations of up to 0.99. In contrast, the hourly results of the SD and the WS provide correlations up to 0.79. EDM tends to overestimate heavy precipitation rates, e.g., by up to 15% for Dresden and 26% for Fichtelberg, potentially due to, e.g., the smaller data pool for such events, and the equal-weighted impact of P in the ED calculation. The OWPs lead to somewhat improved results for all climate elements in terms of similar climate conditions of the basic stations. Finally, the performance of EDM is compared with the disaggregation tool MELODIST (Förster et al. 2015). Both tools deliver comparable and well corresponding results. All analyses of the generated hourly data show that EDM is a very robust and flexible model that can be applied to any climate station. Since EDM can disaggregate daily data of climate projections, future research should address whether the model is capable to respect and (re)produce future climate trends. Further, possible improvements by including the flow direction and future OWPs should be investigated, also with regard to reduce the overestimation of heavy rainfall rates.