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2022 ◽  
Author(s):  
Kelly S. Aho ◽  
Jennifer H. Fair ◽  
Jake D. Hosen ◽  
Ethan D. Kyzivat ◽  
Laura A. Logozzo ◽  
...  

2022 ◽  
Vol 12 (2) ◽  
pp. 582
Author(s):  
Aleksandra Kolarski ◽  
Vladimir A. Srećković ◽  
Zoran R. Mijić

The lower ionosphere influences the propagation of electromagnetic (EM) waves, satellite and also terrestrial (anthropic) signals at the time of intense perturbations and disturbances. Therefore, data and modelling of the perturbed lower ionosphere are crucial in various technological areas. An analysis of the lower ionospheric response induced by sudden events during daytime-solar flares and during night-time-lightning-induced electron precipitation was carried out. A case study of the solar flare event recorded on 7 September 2017 and lightning-induced electron precipitation event recorded on 16 November 2004 were used in this work. Sudden events induced changes in the ionosphere and, consequently, the electron density height profile. All data are recorded by Belgrade (BEL) radio station system and the model computation is used to obtain the ionospheric parameters induced by these sudden events. According to perturbed conditions, variation of estimated parameters, sharpness and reflection height differ for analysed cases. Data and results are useful for Earth observation, telecommunication and other applications in modern society.


2022 ◽  
Vol 14 (2) ◽  
pp. 616
Author(s):  
Zheng Wang ◽  
Yang Pan ◽  
Junxia Gu ◽  
Yu Zhang ◽  
Jianrong Wang

High-resolution and high-quality precipitation data play an important role in Numerical Weather Prediction Model testing, mountain flood geological disaster monitoring, hydrological monitoring and prediction and have become an urgent need for the development of modern meteorological business. The 0.01° multi-source fusion precipitation product is the latest precipitation product developed by the National Meteorological Information Center to meet the above needs. Taking the hourly precipitation observation data of 2400 national automatic stations as the evaluation base, independent and non-independent test methods are used to evaluate the 0.01° multi-source fusion precipitation product in 2020. The product quality differences between the 0.01° precipitation product and the 0.05° precipitation product are compared, and their application in extreme precipitation events are analyzed. The results show that, in the independent test, the product quality of the 0.01° precipitation product and the 0.05° precipitation product are basically the same, which is better than that of each single input data source, and the product quality in winter and spring is slightly lower than that in summer, and both products have better quality in the east in China. The evaluation results of the 0.01° precipitation product in the non-independent test are far better than that of the 0.05° product. The root mean square error and the correlation coefficient of the 0.01° multi-source fusion precipitation product are 0.169 mm/h and 0.995, respectively. In the extreme precipitation case analysis, the 0.01° precipitation product, which is more consistent with the station observation values, effectively improves the problem that the extreme value of the 0.05° product is lower than that of station observation values and greatly improves the accuracy of the precipitation extreme value in the product. The 0.01° multi-source fusion precipitation product has better spatial continuity, a more detailed description of precipitation spatial distribution and a more accurate reflection of precipitation extreme values, which will better provide precipitation data support for refined meteorological services, major activity support, disaster prevention and reduction, etc.


2022 ◽  
Vol 12 ◽  
Author(s):  
Hu Yao ◽  
Haijun Peng ◽  
Bing Hong ◽  
Qian Guo ◽  
Hanwei Ding ◽  
...  

Peatlands are characterized by their large carbon storage capacity and play an essential role in the global carbon cycle. However, the future of the carbon stored in peatland ecosystems under a changing climate remains unclear. In this study, based on the eddy covariance technique, we investigated the net ecosystem CO2 exchange (NEE) and its controlling factors of the Hongyuan peatland, which is a part of the Ruoergai peatland on the eastern Qinghai-Tibet Plateau (QTP). Our results show that the Hongyuan alpine peatland was a CO2 sink with an annual NEE of −226.61 and −185.35 g C m–2 in 2014 and 2015, respectively. While, the non-growing season NEE was 53.35 and 75.08 g C m–2 in 2014 and 2015, suggesting that non-growing seasons carbon emissions should not be neglected. Clear diurnal variation in NEE was observed during the observation period, with the maximum CO2 uptake appearing at 12:30 (Beijing time, UTC+8). The Q10 value of the non-growing season in 2014 and 2015 was significantly higher than that in the growing season, which suggested that the CO2 flux in the non-growing season was more sensitive to warming than that in the growing season. We investigated the multi-scale temporal variations in NEE during the growing season using wavelet analysis. On daily timescales, photosynthetically active radiation was the primary driver of NEE. Seasonal variation in NEE was mainly driven by soil temperature. The amount of precipitation was more responsible for annual variation of NEE. The increasing number of precipitation event was associated with increasing annual carbon uptake. This study highlights the need for continuous eddy covariance measurements and time series analysis approaches to deepen our understanding of the temporal variability in NEE and multi-scale correlation between NEE and environmental factors.


2022 ◽  
Author(s):  
Christoph Fischer ◽  
Andreas H. Fink ◽  
Elmar Schömer ◽  
Roderick van der Linden ◽  
Michael Maier-Gerber ◽  
...  

Abstract. Potential vorticity (PV) analysis plays a central role in studying atmospheric dynamics and in particular in studying the life cycle of weather systems. The three-dimensional (3-D) structure and temporal evolution of the associated PV anomalies, however, are not yet fully understood. An automated technique to objectively identify 3-D PV anomalies can help to shed light on 3-D atmospheric dynamics in specific case studies, as well as facilitate statistical evaluations within climatological studies. Such a technique to identify PV anomalies fully in 3-D, however, does not yet exist. This study presents a novel algorithm for the objective identification of PV anomalies in gridded data, as commonly output by numerical simulation models. The algorithm is inspired by morphological image processing techniques and can be applied to both two-dimensional (2-D) and 3-D fields on vertically isentropic levels. The method maps input data to a horizontally stereographic projection and relies on an efficient computation of horizontal distances within the projected field. Candidates for PV anomaly features are filtered according to heuristic criteria, and feature description vectors are obtained for further analysis. The generated feature descriptions are well suited for subsequent case studies of 3-D atmospheric dynamics as represented by the underlying numerical simulation, or for generation of climatologies of feature characteristics. We evaluate our approach by comparison with an existing 2-D technique, and demonstrate the full 3-D perspective by means of a case study of an extreme precipitation event that was dynamically linked to a prominent subtropical PV anomaly. The case study demonstrates variations in the 3-D structure of the detected PV anomalies that would not have been captured by a 2-D method. We discuss further advantages of using a 3-D approach, including elimination of temporal inconsistencies in the detected features due to 3-D structural variation, and elimination of the need to manually select a specific isentropic level on which the anomalies are assumed to be best captured. The method is made available as open-source for straightforward use by the atmospheric community.


2021 ◽  
Author(s):  
Alexandre Tuel ◽  
Bettina Schaefli ◽  
Jakob Zscheischler ◽  
Olivia Martius

Abstract. River discharge is impacted by the sub-seasonal (weekly to monthly) temporal structure of precipitation. One example is the successive occurrence of extreme precipitation events over sub-seasonal timescales, referred to as temporal clustering. Its potential effects on discharge have received little attention. Here, we address this question by analysing discharge observations following extreme precipitation events either clustered in time or occurring in isolation. We rely on two sets of precipitation and discharge data, one centered on Switzerland and the other over Europe. We identify "clustered" extreme precipitation events based on the previous occurrence of another extreme precipitation within a given time window. We find that clustered events are generally followed by a more prolonged discharge response with a larger amplitude. The probability of exceeding the 95th discharge percentile in the five days following an extreme precipitation event is in particular up to twice as high for situations where another extreme precipitation event occurred in the preceding week compared to isolated extreme precipitation events. The influence of temporal clustering decreases as the clustering window increases; beyond 6–8 weeks the difference with non-clustered events is negligible. Catchment area, streamflow regime and precipitation magnitude also modulate the response. The impact of clustering is generally smaller in snow-dominated and large catchments. Additionally, particularly persistent periods of high discharge tend to occur in conjunction with temporal clusters of precipitation extremes.


2021 ◽  
Vol 67 (4) ◽  
pp. 368-381
Author(s):  
N. A. Tebenkova ◽  
A. A. Ekaykin ◽  
T. Laepple ◽  
D. Notz ◽  
A. V., Kozachek ◽  
...  

Water isotopes are key proxies to reconstruct past climatic conditions on our planet based on Antarctic ice core data. The accuracy of climate reconstructions depends on understanding the whole range of the processes involved in the formation of precipitation isotopic composition. The isotopic composition of precipitation in Central Antarctica has been studied in a number of works, but the difference between the isotopic composition of different types of precipitation has not yet been fully described.There are three main type of precipitation in Central Antarctica: snow, ice needles and hoar. The aim of this work is to establish the dependence of isotopic composition of different precipitation types on temperature. Precipitation samples were collected at Vostok station in Central Antarctica from 1998 to 2020 and further analyzed for δ18O and δD. For each precipitation event we have meteorological data, averaged over the time of precipitation fallout. Mean values of δD for each precipitation type were defined as follows: –444±6.5 ‰ for diamond dust, –480± 6 ‰ for hoar and –95±11 ‰ for snow. The seasonal variability of the temperature dependence of the isotopic composition was studied using the example of ice needles. According to our data, the dependence is insignificant in winter, but this needs to be confirmed by an extended dataset. The largest slope of the isotope-temperature dependence regression line is observed for the summer period and is equal to 5.34±3.11 ‰·°С–1, the autumn season has a slope of 2.1±1.3 ‰·°С–1, while for the spring period we do not have enough data for analysis. There is an insignificant difference in the slopes of the isotope-temperature dependence for different types of precipitation: 2.93±0.51 ‰·°С–1 for ice needles, 2.32±1.34 ‰·°С–1 for snow and 2.52±0.35 ‰·°С–1 for hoar. We studied the effect of blizzards on the isotopic composition of samples and concluded that one should avoid using data collected during a blizzard to study the differences in the formation of the isotopic signal for different types of precipitation.This work brings us closer to understanding how isotopic composition is formed in each type of precipitation and what information it provides. This will contribute to a more accurate interpretation of the isotope signal from ice cores.


Abstract Flooding from extreme precipitation can have major impacts on society in Alaska. Understanding how these extremes may change in the future is needed for better planning under climate change. Data on future changes in extreme precipitation over Alaska from dynamically downscaled output of two global climate models (GFDL and CCSM) were employed in this study. Threshold amounts for duration of the precipitation event (1 hour, 1 day and 30 day) and return intervals (2, 10, and 50 years) are evaluated and further downscaled onto NOAA Atlas 14. For each duration and return interval, the models’ fractional changes of threshold amounts are applied to the Atlas 14 estimates to remove the model bias. The threshold amounts for nearly all event durations and return intervals are projected to increase from present (1979-2005) amounts to higher values in later decadal periods (2020-2049, 2050-2079, and 2080-2099), and the percentage increases generally exceed the changes in the mean amounts. The percentage increases are comparable in the various geographical regions of Alaska, but the increases in the actual amounts are greatest in the wetter Southeast. While the downscaled GFDL model shows larger increases than the CCSM model in amounts for nearly all durations and return intervals, both models indicate that convective precipitation will become an increasingly greater fraction of the total precipitation during the warm season. The increase in the proportion of convective precipitation is consistent with the more rapid increase in extreme amounts than in mean amounts.


Agriculture ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 1220
Author(s):  
Petra Oppeltová ◽  
Pavel Kasal ◽  
František Krátký ◽  
Jana Hajšlová

When growing wide-row crops on sloped lands, there is significant surface runoff. In relation to the runoff process, potatoes are classified as a risk crop. This study aimed to grow potatoes in the Bohemian-Moravian Highlands, where the protection zone of the water supply reservoir of Švihov is also located. At selected experimental areas, water samples were taken after precipitation events when surface runoff and water erosion occurred. These samples were analysed (nitrates, total P, and selected pesticides used for potato growing) in an accredited laboratory. We located three different variants of nitrogen fertilisation in each experimental area. Precipitation and the amount of water from surface runoff after each higher precipitation event were also measured in the experimental areas. By knowing the acreage of each experimental area, the volume of surface runoff water and the concentration of nitrates, phosphorus, and pesticides, it was possible to calculate the balance of these substances. We also calculated the percentage of surface runoff. The results imply that a new potato cultivator in the technology of stone windrowing should be designed for weed control as part of a weed control system with reduced herbicide application requirements. Innovative agrotechnical processes reducing pollution of water sources by phosphorus and nitrates should also be enhanced. These are based on a precise application of mineral fertiliser into the root area of plants within the period of an intensive intake of nutrients.


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