scholarly journals Long-term trends of precipitation in Europe in different datasets

2021 ◽  
Author(s):  
Radan Huth ◽  
Václav Vít
Keyword(s):  
Kendall Test ◽  
Detailed Examination ◽  
Gridded Data ◽  
Southeastern Europe ◽  
Data Types ◽  
Station Data ◽  
Interpolation Procedure ◽  
Drying Trend ◽  
In The Beginning ◽  
Precipitation Trends

<p>It is already a well known fact that different types of climate datasets (station, gridded, reanalyses) and even individual datasets differ in how they describe statistical properties of climate variables. Here we compare precipitation trends in Europe between station data (taken from the ECA&D database), gridded data (E-OBS and CRU TS), and reanalyses (JRA-55 and NCEP/NCAR) for period 1961-2011, both annually and for individual seasons. Theil-Sen non-parametric trend estimator is used for the quantification of the trend magnitude; Mann-Kendall test is used to evaluate the significance of trends.</p><p>On the annual basis, station data indicate precipitation increases in northern Europe and decreases in southern and southeastern Europe. Whereas trends in the gridded datasets roughly agree with station data, reanalyses provide much more negative trends with a different geographical distribution. There is a tendency for reanalyses to overestimate precipitation in the beginning of the period at some places, whereas they underestimate precipitation near the end of the period elsewhere. The disagreement among different data types and datasets is larger in all seasonal analyses except winter. Particularly notable is an excessive drying trend in central, southwestern, and southeastern Europe in NCEP/NCAR in most seasons. Reanalyses thus do not appear to be suitable data sources for estimation of precipitation trends.  </p><p>Reasons for the disagreement are varied and are conjectured by a detailed examination of station / point or regional time series: station series may suffer from inhomogeneities; gridded data may be affected by different sets of stations entering the interpolation procedure at different times; while reanalyses may be affected by different kinds of data being assimilated into them in different periods.</p>

scholarly journals Ba Jin, “Offspring of May 4th”, Time Bomb and Utopian Impulse

2020 ◽  
Author(s):  
Yinde Zhang
Keyword(s):  
Detailed Examination ◽  
Social Revolution ◽  
Ba Jin ◽  
In The Beginning ◽  
Voluntary Servitude

Ba Jin 巴金 (1904-2005) is well-known for his adherence to anarchist ideas in his youth, which actually hides a profound utopianism characterized by a social revolution without purpose and end. By a detailed examination of A Dream on the Sea, a novel published in the beginning of 1930’s, this paper aims to rehabilitate such an utopian spirit as it formulates criticism of reality, oppressive and inegalitarian, by adopting an otherness which warns against both revanchist statism and voluntary servitude. The author’s loyalty to the legacy of May 4th will be highlighted as his work embodies an ever renewed desire for the freedom of thinking and imagining, if not of acting.

scholarly journals Precipitation Trends over the Indus Basin

Climate ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 116 ◽  
Author(s):  
Nir Y. Krakauer ◽  
Tarendra Lakhankar ◽  
Ghulam H. Dars
Keyword(s):  
Remote Sensing ◽  
Large Population ◽  
Tropical Rainfall Measuring Mission ◽  
Indus Basin ◽  
Data Sets ◽  
Precipitation Trend ◽  
Precipitation Data ◽  
Data Set ◽  
Station Data ◽  
Precipitation Trends

A large population relies on water input to the Indus basin, yet basinwide precipitation amounts and trends are not well quantified. Gridded precipitation data sets covering different time periods and based on either station observations, satellite remote sensing, or reanalysis were compared with available station observations and analyzed for basinwide precipitation trends. Compared to observations, some data sets tended to greatly underestimate precipitation, while others overestimate it. Additionally, the discrepancies between data set and station precipitation showed significant time trends in such cases, suggesting that the precipitation trends of those data sets were not consistent with station data. Among the data sets considered, the station-based Global Precipitation Climatology Centre (GPCC) gridded data set showed good agreement with observations in terms of mean amount, trend, and spatial and temporal pattern. GPCC had average precipitation of about 500 mm per year over the basin and an increase in mean precipitation of about 15% between 1891 and 2016. For the more recent past, since 1958 or 1979, no significant precipitation trend was seen. Among the remote sensing based data sets, the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) compared best to station observations and, though available for a shorter time period than station-based data sets such as GPCC, may be especially valuable for parts of the basin without station data. The reanalyses tended to have substantial biases in precipitation mean amount or trend relative to the station data. This assessment of precipitation data set quality and precipitation trends over the Indus basin may be helpful for water planning and management.

scholarly journals Trends of mean annual river discharges in the Zapadna Morava river basin

2017 ◽  
Vol 97 (2) ◽  
pp. 19-45
Author(s):  
Marko Langovic ◽  
Sanja Manojlovic ◽  
Zoran Cvorovic
Keyword(s):  
River Basin ◽  
Linear Trend ◽  
Active Surface ◽  
Kendall Test ◽  
Past Century ◽  
The Republic ◽  
Morava River ◽  
In The Beginning ◽  
The Given ◽  
Morava River Basin

Zapadna Morava River basin covers a surface of 15850 km2, which is approximately 18% of the territory of the Republic of Serbia. In its basin, 38 active surface stations are registered. The goal of this paper is the trend analysis of the mean annual river discharges in the Zapadna Morava River basin and their noticing in a longer series of time, as well as determining their intensity. Fifty years period of time (1965 - 2014) is taken for a time series. Because there is no empirical data for mean annual discharge values for all stations for the given period, the number of the hydrological stations, which are processed in this paper, is reduced to 21. Mann-Kendall test has been used for noticing the trend, Sen test has been used for estimating the curves inclinations of the linear trend, while Pettitt?s test has been used for determining the turning point of change. Also, classification of the years by water richness has been performed in this paper in order to determine wet and dry periods. For the needs of identification of medium watery, wet and dry years, the combined method has been used on the data examples from representative stations in the basin. Based on the processed data and the obtained results, it has been established that the most rivers in the basin of the Zapadna Morava River have a slightly decreasing trend of the flow values, whereby the change of the trend is not significant. On the most rivers, the change period has begun in the early eighties of the past century. On a large number of profiles, the watery period was appearing in the beginning of eighties, while the dry season is characteristic for the period from 1990 to 1994.

scholarly journals Evaluation of hydrological modeling using climatic station and gridded precipitation dataset

MAUSAM ◽  
2021 ◽  
Vol 71 (4) ◽  
pp. 717-728
Author(s):  
KHAN WISAL ◽  
KHAN ASIF ◽  
KHAN AFED ULLAH ◽  
KHAN MUJAHID
Keyword(s):  
Hydrological Modeling ◽  
Assessment Tool ◽  
Swat Model ◽  
Indus Basin ◽  
Gridded Data ◽  
Flow Data ◽  
Rainfall Events ◽  
Station Data ◽  
Measured Flow ◽  
Water Assessment

The conventional rainfall data estimates are relatively accurate at some points of the region. The interpolation of such type of data approximates the actual rainfield however in data scarce regions; the resulted rainfield is the rough estimate of the actual rainfall events. In data scarce regions like Indus basin Pakistan, the data obtained through remote sensing can be very useful. This research evaluates two types of gridded data i.e., European Reanalysis (ERA) interim and Japanese Reanalysis 55 years (JRA-55) along with the climatic station data for three small dams in Pakistan. Since no measured flow data is available at these dams, the nearest possible catchments where flow data is available are calibrated and the calibrated parameters of these catchments are then used in actual dams for simulating the flow from all the three types of data using Soil and Water Assessment Tool (SWAT). The results of the comparison of gridded and rainguage precipitation shows that gridded data highly overestimates the climatic station data. Similar results were observed in the comparison of flow simulated by SWAT model. The Peak flood calculated from JRA-55 overestimates while the Era-Interim peak floods are comparable to that of climatic stations in two of the three catchments.

scholarly journals Trends of Runoff Variation and Effects of Main Causal Factors in Mun River, Thailand During 1980–2018

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 831 ◽  
Author(s):  
Renzhi Li ◽  
Heqing Huang ◽  
Guoan Yu ◽  
Hong Yu ◽  
Arika Bridhikitti ◽  
...  
Keyword(s):  
Kendall Test ◽  
Detailed Examination ◽  
Annual Runoff ◽  
Mekong River ◽  
Runoff Variation ◽  
Basin Scale ◽  
Cumulative Curve ◽  
Runoff Decrease ◽  
Detailed Assessment ◽  
Morlet Wavelet Transform

Mun River is the largest tributary of the Mekong River in Thailand and provides abundant water resources not only for an important agricultural area in Thailand but also for the lower Mekong River. To understand how the runoff of Mun River responds to climate change and human activities in recent decades, this study performed a detailed examination of the characteristics of runoff variation based on measurements at two hydrological gauging stations on the main stem of Mun River during 1980–2018. Using the Mann-Kendall test, Morlet wavelet transform and Double Cumulative Curve methods, this study identifies that the variation of annual runoff of Mun River encountered an abruption in 1999/2000, with an increased trend taking place since then. Furthermore, a detailed assessment of the effects of the variations in rainfall, temperature, evaporation, and land use types extracted from remote sensing images at the basin scale reveals that a significant reduction in forest area and slight reductions in evaporation and farmland area taking place since 1999 can lead to an increase in the runoff of Mun River, while the dramatic increase in garden area since 1999 tends to make the runoff decrease.

scholarly journals Ancestral Home of Indo-Aryan Peoples and Migration of Iranian Tribes to Southeastern Europe

2018 ◽  
Vol 50 ◽  
pp. 01237
Author(s):  
Saydali Mukhidinov
Keyword(s):  
Central Asia ◽  
Historical Period ◽  
Eastern European ◽  
Southeastern Europe ◽  
Economic Basis ◽  
Huge Impact ◽  
Points Of View ◽  
And Migration ◽  
In The Beginning ◽  
Modern Population

The article attempts to clarify and analyze the opinions, hypotheses, ideas and assumptions of scientists studying the issues of ancestral home of the Indo-Aryan peoples from the historical, archaeological and linguistic points of view. The Eastern European localization of the ancestral home of the Indo-Aryan peoples in Southeastern Europe and their migration is considered in the article. The territory of Central Asia was occupied by the Iranian nationalities in the beginning of the historical period (VII-VI centuries BC): Bactrians, Sogdians, Khorezmians, Parthians, Saka tribes. The analysis of relict phenomena in the languages and culture of modern population of Central Asia, in particular the population of the Pamirs, shows the presence of an ancient Indo-Aryan layer. In this case, a specific convergence is identified, which is precisely oriented on the ancient Indian tradition. At the same time, even more ancient traces associated with the pre-Indo-Iranian population of Central Asia are revealed. The substrate layer played a huge role in the genesis of the culture, ideology and ethnos of the most ancient Iranian-speaking population of Central Asia. It had a huge impact on the establishment of its social and economic basis.

scholarly journals Shifts in the Statistics of Daily Rainfall in South America Conditional on ENSO Phase

2008 ◽  
Vol 21 (5) ◽  
pp. 849-865 ◽  
Author(s):  
C. F. Ropelewski ◽  
M. A. Bell
Keyword(s):  
South America ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Daily Rainfall ◽  
Detailed Comparison ◽  
Gridded Data ◽  
Climate Data ◽  
Station Data ◽  
Geographical Regions

Abstract There are several well-documented studies showing the shifts in seasonal mean rainfall and temperature conditional on El Niño–Southern Oscillation (ENSO) phase. Here the shifts in the seasonal histograms of daily rainfall over South America conditional on ENSO phase are examined. The authors are motivated to analyze daily rainfall statistics over seasons by the demands for information on the shorter temporal scales voiced by users of climate data. In the first stage of the analysis the Kolmogorov–Smirnov (K-S) test is used, comparing El Niño to La Niña histograms of daily station data, to identify regions where there are significant shifts in the histograms. The K-S statistic analyses of daily station data are then compared to the same analyses performed on existing publicly available gridded station datasets. The degree to which the station and gridded data agree in showing geographical regions of significance provides evidence that the gridded fields might provide guidance on the nature of the ENSO signal where station data are not available. Further, the analysis of the gridded datasets can be used to motivate and guide efforts to obtain more complete daily data where the gridded datasets suggest an ENSO signal. As an example a detailed comparison of one station in southern Brazil and its nearest neighbors in the gridded data are presented, suggesting that, despite biases, the gridded fields are generally consistent with the station data where both are available. For many regions of the world neither daily station data nor daily gridded datasets are available for analysis. Thus despite documented and well-known regional biases in the precipitation fields available in the NCEP–NCAR reanalysis the extent to which shifts in the daily statistics of the NCEP–NCAR reanalysis precipitation are consistent with station and gridded station analyses is also examined. The preliminary work described here suggests that while the reanalysis does not ideally replicate the gridded station results the reanalysis may be useful as a tool for indicating candidate regions for further analysis with station or gridded data.

Regionalization of Intensity-Duration-Frequency Curves for different data types in Germany

2021 ◽  
Author(s):  
Bora Shehu ◽  
Winfried Willems ◽  
Luisa Thiele ◽  
Henrike Stockel ◽  
Uwe Haberlandt
Keyword(s):  
Time Series ◽  
Bootstrap Method ◽  
Return Periods ◽  
Data Types ◽  
Long Time Series ◽  
Station Data ◽  
Long Time ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
The Given

<p><span>Rainfall intensity-duration-frequency (IDF) curves are required for the design of several water systems and protection works. These curves are typically generated from the station data by fitting a theoretical distribution either to the annual extremes (AMS) or partial extremes (PE) series. Nevertheless, two main problems arise: i) for generating intensity depth for high return periods, long time series are needed (more than 40 years). While this is the case mainly for daily recordings, for sub-hourly time series only few point measurements are available. ii) as the station data are only local measurements, there is a need for regionalization of the of IDF curves to ungauged locations. Thus, the aim of this study is to investigate the use of different data types and methods in generating reliable IDF curves for ungauged locations. </span></p><p><span>For this purpose, the available gauge data from the German Weather Service (DWD) in Germany are employed, which include: 5000 daily stations with more than 40 years available, 1100 sub-hourly (5min) recordings with observations period shorter than 20 years, and finally 89 sub-hourly (5min) recordings with 60-70 years of observations. Annual extremes are extracted for each location for different durations D=5, 10, 15, 30, 60, 120, 180, 240, 360, 720, 2880 minutes, and a Generalized Extreme Value (GEV) probability distribution is fitted to each duration level as well as across all duration levels by the methods of the L-moments and Maximum-Likelihood, in order to derive the intensity quantiles for the given return periods Ta=2, 10, 20 and 100 years. First, a disaggregation scheme to 5 min resolution is performed on the daily recordings in order to investigate if disaggregated daily data can be useful for the IDF estimation of sub-daily durations. Then, the rainfall extremes of short observations are corrected by a correlation-based augmentation method. Finally, as the extreme intensities and durations are co-dependent, a normalization of the AMS over all the durations is performed.</span></p><p><span>To evaluate the regionalization of the IDF curves to ungauged regions, three methods are investigated: i) flood index method ii) regionalization with normalization of extremes over the durations and ii) kriging interpolation (ordinary and external drift kriging) of local AMS quantiles or parameters of the fitted distribution. The performance of these regionalization techniques is then evaluated by cross-validation, where the local IDF from the long sub-hourly time series are considered the true reference. Based on the relative bias, rmse and correlation the best method is selected and used for the regionalization of the IDF curves in Germany. Different data products are fed in the regionalization methods to answer the following questions: are the disaggregated long time series useful in regionalizing sub-hourly IDF? Can space be traded for time (and vice versa) when regionalizing IDF? What is the best incorporation of different data sets for the regionalization of the IDF? Lastly, a bootstrap method is as well employed to account for the uncertainties in estimation intensity-duration extremes for the given return periods. </span></p>

Detailed basin structure and tectonic evolution of the Midcontinent Rift System in eastern Lake Superior from reprocessing of GLIMPCE deep reflection seismic data

1994 ◽  
Vol 31 (4) ◽  
pp. 629-639 ◽  
Author(s):  
C. Samson ◽  
G. F. West
Keyword(s):  
Lake Superior ◽  
Detailed Examination ◽  
Structural Features ◽  
Seismic Survey ◽  
Rift System ◽  
Midcontinent Rift ◽  
Reflection Seismic ◽  
Basic Wavelet ◽  
Midcontinent Rift System ◽  
In The Beginning

Line F of the GLIMPCE deep marine reflection seismic survey has been reprocessed according to a data-dependent strategy aimed at enhancing the fine structural features of the Midcontinent Rift System in eastern Lake Superior. The processing sequence was specially designed to attenuate first-order water reverberations and to reduce the excessive oscillatory character of the basic wavelet. A detailed examination of the final migrated stacked section reveals that, beneath line F, the Midcontinent Rift System is an almost perfectly symmetric syncline. The structure appears to have formed in the beginning by the extrusion of lavas on a horizontal platform subsiding without major deformation. The initial phase was followed by local crustal sagging in the centre. The transition is marked by a major reflector, which is hypothesized to correspond to the boundary between reverse- and normal-polarity volcanics in eastern Lake Superior. Integrating the results of several recent investigations, a five-stage evolutionary scenario is proposed for the Midcontinent Rift System in eastern Lake Superior: (1) onset of extrusive volcanism, (2) platform subsidence, (3) local crustal sagging, (4) deposition of postrift sediments, and (5) tectonic inversion.

scholarly journals Spatiotemporal Variations of Precipitation over Iran Using the High-Resolution and Nearly Four Decades Satellite-Based PERSIANN-CDR Dataset

2020 ◽  
Vol 12 (10) ◽  
pp. 1584 ◽  
Author(s):  
Hamidreza Mosaffa ◽  
Mojtaba Sadeghi ◽  
Negin Hayatbini ◽  
Vesta Afzali Gorooh ◽  
Ata Akbari Asanjan ◽  
...  
Keyword(s):  
Kendall Test ◽  
Rain Gauge ◽  
Annual Precipitation ◽  
Management Decision ◽  
Monthly Precipitation ◽  
Precipitation Trend ◽  
Climate Data ◽  
Suitable Alternative ◽  
Precipitation Estimation ◽  
Precipitation Trends

Spatiotemporal precipitation trend analysis provides valuable information for water management decision-making. Satellite-based precipitation products with high spatial and temporal resolution and long records, as opposed to temporally and spatially sparse rain gauge networks, are a suitable alternative to analyze precipitation trends over Iran. This study analyzes the trends in annual, seasonal, and monthly precipitation along with the contribution of each season and month in the annual precipitation over Iran for the 1983–2018 period. For the analyses, the Mann–Kendall test is applied to the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) estimates. The results of annual, seasonal, and monthly precipitation trends indicate that the significant decreases in the monthly precipitation trends in February over the western (March over the western and central-eastern) regions of Iran cause significant effects on winter (spring) and total annual precipitation. Moreover, the increases in the amounts of precipitation during November in the south and south-east regions lead to a remarkable increase in the amount of precipitation during the fall season. The analysis of the contribution of each season and month to annual precipitation in wet and dry years shows that dry years have critical impacts on decreasing monthly precipitation over a particular region. For instance, a remarkable decrease in precipitation amounts is detectable during dry years over the eastern, northeastern, and southwestern regions of Iran during March, April, and December, respectively. The results of this study show that PERSIANN-CDR is a valuable source of information in low-density gauge network areas, capturing spatiotemporal variation of precipitation.

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