scholarly journals Asymmetry of Daytime and Nighttime Warming in Typical Climatic Zones along the Eastern Coast of China and Its Influence on Vegetation Activities

2020 ◽  
Vol 12 (21) ◽  
pp. 3604
Author(s):  
Guangxin He ◽  
Zhongliang Li
Keyword(s):  
Return Period ◽  
Deep Understanding ◽  
Distribution Functions ◽  
Eastern Coast ◽  
Maximum Temperature ◽  
Climate Factor ◽  
Vegetation Growth ◽  
Warming Rate ◽  
Nighttime Warming ◽  
Vegetation Activities

In this dissertation, the author adopted the normalized difference vegetation index (NDVI) and meteorological data from 1982 to 2016 of the typical climate zones in coastal areas of China to analyze the influence of daytime and nighttime warming asymmetric changes in different seasons on vegetation activities during the growing season period according to the copula function theory optimized based on Markov chain Monte Carlo (MCMC). The main conclusions are as follows: (1) The seasonal daytime and nighttime warming trends of Guangdong, Jiangsu and Liaoning over the past 35 years were significant, and the daytime and nighttime warming rates were asymmetric. In spring and summer of Guangdong province, the warming rate in the daytime was higher than that at night, while, in autumn, the opposite law was observed. However, the warming rate in the daytime was lower than that at night in Jiangsu and Liaoning provinces. There were latitude differences in diurnal and nocturnal warming rate. (2) The daytime and nighttime warming influences on vegetation showed significant seasonal differences in these three regions. In Guangdong, the influence of nighttime warming on vegetation growth in spring is greater than that in summer, and the influences of daytime warming on vegetation growth from strong to weak were spring, summer and autumn. In Jiangsu, both the influences of daytime and nighttime warming on vegetation growth in summer were less than that in autumn. In Liaoning, both the influences of daytime and nighttime warming on vegetation growth from strong to weak were autumn, spring and summer. (3) In Guangdong, Jiangsu and Liaoning provinces, their maximum temperature (Tmax) and minimum temperature (Tmin) and the joint probability distribution functions of NDVI, all had little effect on NDVI when Tmax and Tmin respectively reached their minimum values, but their influences on NDVI were obvious when Tmax and Tmin respectively reached their maximum values. (4) The smaller the return period, the larger the range of climate factor and NDVI, which has indicated that when the climate factor is certain, the NDVI is more likely to have a smaller return period, and the frequency of NDVI over a certain period is higher. In addition, the larger the climate factor, the greater the return period is and NDVI is less frequent over a certain period of time. This research can help with deep understanding of the dynamic influence of seasonal daytime and nighttime asymmetric warming on the vegetation in typical coastal temperature zones of China under the background of global climate change.

scholarly journals Elevational Movement of Vegetation Greenness on the Tibetan Plateau: Evidence from the Landsat Satellite Observations during the Last Three Decades

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 161
Author(s):  
Liheng Lu ◽  
Xiaoqian Shen ◽  
Ruyin Cao
Keyword(s):  
Tibetan Plateau ◽  
Spatial Resolution ◽  
Climate Warming ◽  
Vertical Movement ◽  
The Tibetan Plateau ◽  
Upward Movement ◽  
Vegetation Growth ◽  
Vegetation Greenness ◽  
Mountainous Regions ◽  
Vegetation Activities

The Tibetan Plateau, the highest plateau in the world, has experienced strong climate warming during the last few decades. The greater increase of temperature at higher elevations may have strong impacts on the vertical movement of vegetation activities on the plateau. Although satellite-based observations have explored this issue, these observations were normally provided by the coarse satellite data with a spatial resolution of more than hundreds of meters (e.g., GIMMS and MODIS), which could lead to serious mixed-pixel effects in the analyses. In this study, we employed the medium-spatial-resolution Landsat NDVI data (30 m) during 1990–2019 and investigated the relationship between temperature and the elevation-dependent vegetation changes in six mountainous regions on the Tibetan Plateau. Particularly, we focused on the elevational movement of the vegetation greenness isoline to clarify whether the vegetation greenness isoline moves upward during the past three decades because of climate warming. Results show that vegetation greening occurred in all six mountainous regions during the last three decades. Increasing temperatures caused the upward movement of greenness isoline at the middle and high elevations (>4000 m) but led to the downward movement at lower elevations for the six mountainous regions except for Nyainqentanglha. Furthermore, the temperature sensitivity of greenness isoline movement changes from the positive value to negative value by decreasing elevations, suggesting that vegetation growth on the plateau is strongly regulated by other factors such as water availability. As a result, the greenness isoline showed upward movement with the increase of temperature for about 59% pixels. Moreover, the greenness isoline movement increased with the slope angles over the six mountainous regions, suggesting the influence of terrain effects on the vegetation activities. Our analyses improve understandings of the diverse response of elevation-dependent vegetation activities on the Tibetan Plateau.

scholarly journals Evidence of elevation-dependent warming from the Chinese Tian Shan

2021 ◽  
Vol 15 (12) ◽  
pp. 5765-5783
Author(s):  
Lu Gao ◽  
Haijun Deng ◽  
Xiangyong Lei ◽  
Jianhui Wei ◽  
Yaning Chen ◽  
...  
Keyword(s):  
Air Temperature ◽  
Minimum Temperature ◽  
Swiss Alps ◽  
Maximum Temperature ◽  
Current Evidence ◽  
High Mountain ◽  
Regional Warming ◽  
Mean Temperature ◽  
Warming Rate ◽  
Tian Shan

Abstract. The phenomenon in which the warming rate of air temperature is amplified with elevation is termed elevation-dependent warming (EDW). It has been clarified that EDW can accelerate the retreat of glaciers and melting of snow, which can have significant impacts on the regional ecological environment. Owing to the lack of high-density ground observations in high mountains, there is widespread controversy regarding the existence of EDW. Current evidence is mainly derived from typical high-mountain regions such as the Swiss Alps, the Colorado Rocky Mountains, the tropical Andes and the Tibetan Plateau–Himalayas. Rare evidence in other mountain ranges has been reported, especially in arid regions. In this study, EDW features (regional warming amplification and altitude warming amplification) in the Chinese Tian Shan (CTM) were detected using a unique high-resolution (1 km, 6-hourly) air temperature dataset (CTMD) from 1979 to 2016. The results showed that there were significant EDW signals at different altitudes on different timescales. The CTM showed significant regional warming amplification in spring, especially in March, and the warming trends were greater than those of continental China with respect to three temperatures (minimum temperature, mean temperature and maximum temperature). The significance values of EDW above different altitude thresholds are distinct for three temperatures in 12 months. The warming rate of the minimum temperature in winter showed a significant elevation dependence (p<0.01), especially above 3000 m. The greatest altitudinal gradient in the warming rate of the maximum temperature was found above 4000 m in April. For the mean temperature, the warming rates in June and August showed prominent altitude warming amplification but with different significance above 4500 m. Within the CTM, the Tolm Mountains, the eastern part of the Borokoonu Mountains, the Bogda Mountains and the Balikun Mountains are representative regions that showed significant altitude warming amplification on different timescales. This new evidence could partly explain the accelerated melting of snow in the CTM, although the mechanisms remain to be explored.

scholarly journals Joint return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation

2012 ◽  
Vol 9 (5) ◽  
pp. 6781-6828 ◽  
Author(s):  
S. Vandenberghe ◽  
M. J. van den Berg ◽  
B. Gräler ◽  
A. Petroselli ◽  
S. Grimaldi ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Three Dimensional ◽  
Distribution Functions ◽  
Return Periods ◽  
Design Variables ◽  
Joint Return ◽  
Design Values ◽  
Multivariate Frequency Analysis ◽  
Joint Return Period

Abstract. Most of the hydrological and hydraulic studies refer to the notion of a return period to quantify design variables. When dealing with multiple design variables, the well-known univariate statistical analysis is no longer satisfactory and several issues challenge the practitioner. How should one incorporate the dependence between variables? How should the joint return period be defined and applied? In this study, an overview of the state-of-the-art for defining joint return periods is given. The construction of multivariate distribution functions is done through the use of copulas, given their practicality in multivariate frequency analysis and their ability to model numerous types of dependence structures in a flexible way. A case study focusing on the selection of design hydrograph characteristics is presented and the design values of a three-dimensional phenomenon composed of peak discharge, volume and duration are derived. Joint return period methods based on regression analysis, bivariate conditional distributions, bivariate joint distributions, and Kendal distribution functions are investigated and compared highlighting theoretical and practical issues of multivariate frequency analysis. Also an ensemble-based method is introduced. For a given design return period, the method chosen clearly affects the calculated design event. Eventually, light is shed on the practical implications of a chosen method.

scholarly journals A Statistical Adjustment of Regional Climate Model Outputs to Local Scales: Application to Platja de Palma, Spain

2012 ◽  
Vol 25 (3) ◽  
pp. 939-957 ◽  
Author(s):  
A. Amengual ◽  
V. Homar ◽  
R. Romero ◽  
S. Alonso ◽  
C. Ramis
Keyword(s):  
Climate Change ◽  
Regional Climate ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Climate Change Signal ◽  
Daily Maximum ◽  
Climate Projections ◽  
Recent Past

Abstract Projections of climate change effects for the System of Platja de Palma (SPdP) are derived using a novel statistical technique. Socioeconomic activities developed in this settlement are very closely linked to its climate. Any planning for socioeconomic opportunities in the mid- and long term must take into account the possible effects of climate change. To this aim, daily observed series of minimum and maximum temperatures, precipitation, relative humidity, cloud cover, and wind speed have been analyzed. For the climate projections, daily data generated by an ensemble of regional climate models (RCMs) have been used. To properly use RCM data at local scale, a quantile–quantile adjustment has been applied to the simulated regional projections. The method is based on detecting changes in the cumulative distribution functions between the recent past and successive time slices of the simulated climate and applying these, after calibration, to the recent past (observed) series. Results show an overall improvement in reproducing the present climate baseline when using calibrated series instead of raw RCM outputs, although the correction does not result in such clear improvement when dealing with very extreme rainfalls. Next, the corrected series are analyzed to quantify the climate change signal. An increase of the annual means for temperatures together with a decrease for the remaining variables is projected throughout the twenty-first century. Increases in weak and intense daily rainfalls and in high extremes for daily maximum temperature can also be expected. With this information at hand, the experts planning the future of SPdP can respond more effectively to the problem of local adaptation to climate change.

Effects of Landau Damping and Collision on Stimulated Raman Scattering with Various Phase-Space Distributions

2021 ◽  
Author(s):  
Shanxiu XIE ◽  
Yong CHEN ◽  
Junchen YE ◽  
Yugu CHEN ◽  
Na PENG ◽  
...  
Keyword(s):  
Growth Rate ◽  
Raman Scattering ◽  
Stimulated Raman Scattering ◽  
Deep Understanding ◽  
Distribution Functions ◽  
Maxwellian Distribution ◽  
Landau Damping ◽  
Hot Electron ◽  
Collisional Damping ◽  
Stimulated Raman

Abstract Stimulated Raman scattering (SRS) is one of the main instabilities affecting the success of the fusion ignition. Here, we study the relationship between Raman growth and Landau damping with various distribution functions combining the analytic formulas and Vlasov simulations. The Landau damping obtained by Vlasov-Poisson simulation and Raman growth rate obtained by Vlasov-Maxwell simulation are anti-correlated, which is consistent with our theoretical analysis quantitatively. Maxwellian distribution, flattened distribution, and bi-Maxwellian distribution are studied in detail, which represent three typical stages of SRS. We have also demonstrated the effects of plateau width, hot-electron fraction, hot-to-cold electron temperature ratio, and collisional damping on the Landau damping and growth rate. It gives us a deep understanding of SRS and possible ways to mitigate SRS through manipulating distribution functions to a high Landau damping regime.

scholarly journals THERMODYNAMIC q-DISTRIBUTIONS THAT AREN’T

1994 ◽  
Vol 09 (01) ◽  
pp. 1-9 ◽  
Author(s):  
STAMATIS VOKOS ◽  
COSMAS ZACHOS
Keyword(s):  
Energy Distribution ◽  
Critical Frequency ◽  
Black Body ◽  
Distribution Functions ◽  
Maximum Temperature ◽  
Cavity Size ◽  
Free Distribution ◽  
Planck Distribution ◽  
The Subject ◽  
Body Energy

Bosonic q-oscillators commute with themselves and so their free distribution is Planckian. In a cavity, their emission and absorption rates may grow or shrink – and even diverge – but they nevertheless balance to yield the Planck distribution via Einstein’s equilibrium method, (a careless application of which might produce spurious q-dependent distribution functions). This drives home the point that the black-body energy distribution is not a handle for distinguishing q-excitations from plain oscillators. A maximum cavity size is suggested by the inverse critical frequency of such emission/absorption rates at a given temperature, or a maximum temperature at a given frequency. To remedy fragmentation of opinion on the subject, we provide some discussion, context, and references.

scholarly journals Anthropogenic Influence on Long Return Period Daily Temperature Extremes at Regional Scales

2011 ◽  
Vol 24 (3) ◽  
pp. 881-892 ◽  
Author(s):  
Francis W. Zwiers ◽  
Xuebin Zhang ◽  
Yang Feng
Keyword(s):  
Return Period ◽  
Waiting Times ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Human Society ◽  
Multiple Model ◽  
Extreme Temperatures ◽  
Annual Maximum ◽  
Daily Minimum

Abstract Observed 1961–2000 annual extreme temperatures, namely annual maximum daily maximum (TXx) and minimum (TNx) temperatures and annual minimum daily maximum (TXn) and minimum (TNn) temperatures, are compared with those from climate simulations of multiple model ensembles with historical anthropogenic (ANT) forcing and with combined anthropogenic and natural external forcings (ALL) at both global and regional scales using a technique that allows changes in long return period extreme temperatures to be inferred. Generalized extreme value (GEV) distributions are fitted to the observed extreme temperatures using a time-evolving pattern of location parameters obtained from model-simulated extreme temperatures under ANT or ALL forcing. Evaluation of the parameters of the fitted GEV distributions shows that both ANT and ALL influence can be detected in TNx, TNn, TXn, and TXx at the global scale over the land areas for which there are observations, and also regionally over many large land areas, with detection in more regions in TNx. Therefore, it is concluded that the influence of anthropogenic forcing has had a detectable influence on extreme temperatures that have impacts on human society and natural systems at global and regional scales. External influence is estimated to have resulted in large changes in the likelihood of extreme annual maximum and minimum daily temperatures. Globally, waiting times for extreme annual minimum daily minimum and daily maximum temperature events that were expected to recur once every 20 yr in the 1960s are now estimated to exceed 35 and 30 yr, respectively. In contrast, waiting times for circa 1960s 20-yr extremes of annual maximum daily minimum and daily maximum temperatures are estimated to have decreased to fewer than 10 and 15 yr, respectively.

scholarly journals Uncertainty analysis of hydrological return period estimation, taking the upper Yangtze River as an example

2017 ◽  
Author(s):  
Hemin Sun ◽  
Tong Jiang ◽  
Cheng Jing ◽  
Buda Su ◽  
Guojie Wang
Keyword(s):  
Return Period ◽  
Yangtze River ◽  
Distribution Functions ◽  
Return Level ◽  
Return Periods ◽  
Return Levels ◽  
Upper Yangtze River ◽  
Period Estimation ◽  
Peak Over Threshold ◽  
The Upper Yangtze River

Abstract. Return period estimation plays an important role in the engineering practices of water resources and disaster management, but uncertainties accompany the calculation process. Based on the daily discharge records at two gauging stations (Cuntan and Pingshan) on the upper Yangtze River, three sampling methods (SMs; (annual maximum, peak over threshold, and decadal peak over threshold), five distribution functions (DFs; gamma, Gumbel, lognormal, Pearson III, and general extreme value), and three parameterization methods (PMs; maximum likelihood, L-Moment, and method of moment) were applied to analyze the uncertainties in return period estimation. The estimated return levels based on the different approaches were found to differ considerably at each station. The range of discharge for a 20-year return period was 63,800.8–74,024.1 m3 s−1 for Cuntan and 23,097.8–25,595.3 m3 s−1 for Pingshan, when using the 45 combinations of SMs, DFs, and PMs. For a 1000-year event, the estimated discharge ranges increased to 74,492.5–125,658.0 and 27,339.2–41,718.1 m3 s−1 for Cuntan and Pingshan, respectively. Application of the analysis of variance method showed that the total sum of the squares of the estimated return levels increased with the widening of the return periods, suggestive of increased uncertainties. However, the contributions of the different sources to the uncertainties were different. For Cuntan, where the discharge changed significantly, the SM appeared to be the largest source of uncertainty. For Pingshan, where the discharge series remained almost stable, the DF contributed most to the uncertainty. Therefore, multiple uncertainty sources in estimating return periods should be considered to meet the demands of different planning purposes. The research results also suggest that uncertainties of return level estimation could be reduced if an optimized DF were used, or if the decadal peak over threshold SM were used, which is capable of representing temporal changes of hydrological series.

scholarly journals BIVARIATE FREQUENCY ANALYSIS OF FLOOD VARIABLES USING COPULA IN KELANTAN RIVER BASIN

2018 ◽  
Vol 30 (3) ◽  
Author(s):  
Mahiuddin Alamgir ◽  
Tarmizi Ismail ◽  
Muhammad Noor
Keyword(s):  
River Basin ◽  
Frequency Analysis ◽  
Return Period ◽  
Peak Flow ◽  
Distribution Functions ◽  
Flood Frequency Analysis ◽  
Flood Duration ◽  
Flood Volume ◽  
Kelantan River Basin ◽  
Univariate Distribution

A copula-based methodology is presented in this study for bivariate flood frequency analysis of Kelantan river basin located in Northeast Malaysia. The joint dependence structures of three flood characteristics, namely, peak flow (Q), flood volume (V) and flood duration (D) were modelled using t-Copula. Various univariate distribution functions of flood variables were fitted with observed flood variables to find the best distributions. Cumulative joint distribution functions (CDF) of peak flow and volume (Q-F), peak flow and duration (Q-D) and volume and duration (V-D) revealed that return period of joint return periods are much higher compared to univariate return period. The joint probabilities of occurrence of 0.8, 0.6, 0.4, 0.2 and 0 can be expected when flood duration greater than 65 h, 54 h, 46 h, and 32 h, and the flood volume higher than 0.62 km3, 0.33 km3, 0.25 km3, and 0.22 km3 respectively.

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