scholarly journals SHIFTS OF START AND END OF SEASON IN RESPONSE TO AIR TEMPERATURE VARIATION BASED ON GIMMS DATASET IN HYRCANIAN FORESTS

2017 ◽  
Vol XLII-4/W4 ◽  
pp. 155-160
Author(s):  
K. H. Kiapasha ◽  
A. A. Darvishsefat ◽  
N. Zargham ◽  
Y. Julien ◽  
J. A. Sobrino ◽  
...  
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Environmental Changes ◽  
Growing Season ◽  
Kendall Test ◽  
Hyrcanian Forests ◽  
Vegetation Activity ◽  
Iterative Interpolation ◽  
Ndvi Time Series ◽  
Original Time

Climate change is one of the most important environmental challenges in the world and forest as a dynamic phenomenon is influenced by environmental changes. The Hyrcanian forests is a unique natural heritage of global importance and we need monitoring this region. The objective of this study was to detect start and end of season trends in Hyrcanian forests of Iran based on biweekly GIMMS (Global Inventory Modeling and Mapping Studies) NDVI3g in the period 1981-2012. In order to find response of vegetation activity to local temperature variations, we used air temperature provided from I.R. Iran Meteorological Organization (IRIMO). At the first step in order to remove the existing gap from the original time series, the iterative Interpolation for Data Reconstruction (IDR) model was applied to GIMMS and temperature dataset. Then we applied significant Mann Kendall test to determine significant trend for each pixel of GIMMS and temperature datasets over the Hyrcanian forests. The results demonstrated that start and end of season (SOS & EOS respectively) derived from GIMMS3g NDVI time series increased by -0.16 and +0.41 days per year respectively. The trends derived from temperature time series indicated increasing trend in the whole of this region. Results of this study showed that global warming and its effect on growth and photosynthetic activity can increased the vegetation activity in our study area. Otherwise extension of the growing season, including an earlier start of the growing season, later autumn and higher rate of production increased NDVI value during the study period.

scholarly journals Changes in the Occurrence of Late Spring Frost in Poland

Agronomy ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1835
Author(s):  
Dariusz Graczyk ◽  
Małgorzata Szwed
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Growing Season ◽  
Significant Trend ◽  
Similar Time ◽  
Spring Frost ◽  
Late Spring Frost ◽  
Low Probability ◽  
Spring Frosts ◽  
Agricultural Regions

Trends in the appearance of the last spring frost for three thresholds of minimum daily air temperature at the height of 2 m and near the ground were examined for six meteorological stations located in two agricultural regions in Poland. For most time series, the last spring frost, calculated as a consecutive day of the year, showed a statistically significant trend indicating its earlier appearance from 1.6 to about 3.5 days per decade. The date of the last spring frost was also calculated in relation to the ongoing growing season. In this case, few statistically significant changes in the dates of the last frosts were found. The probability of the last spring frost on a specific day of the calendar year and the day of the growing season was also examined for two periods: 1961–1990 and 1991–2020. For low probability levels corresponding to the early dates of the last spring frost, the last frost usually occurred much earlier (6–14 days) in 1991–2020. With the probability levels of 80–90% describing the late occurrence of the last frost with a frequency of once every 5–10 years, at some stations, the last spring frosts occurred at a similar time for both periods.

scholarly journals Intra-annual Secondary Growth Rate-Climate Relations of Fagus orientalis Lipsky in the Center of Hyrcanian Forests

2012 ◽  
Vol 4 (2) ◽  
pp. 136-140 ◽  
Author(s):  
Reza OLADI ◽  
Kambiz POURTAHMASI
Keyword(s):  
Growth Rate ◽  
Tree Ring ◽  
Air Temperature ◽  
Secondary Growth ◽  
Ring Width ◽  
Growing Season ◽  
Water Evaporation ◽  
Optimum Level ◽  
Hyrcanian Forests ◽  
Fagus Orientalis Lipsky

Weekly rate of Beech tree ring increment were related to the changes of climatic factors in weekly intervals. In order to do so, small samples were extracted from 5 Oriental beech trees located in Nowshahr educational forest in the central part of the Hyrcanian forests of Iran during 2008 growing season. Microscopic sections were prepared and average increases in tree ring width were measured, standardized and modeled using Gompertz equation. The results showed that the minimum air temperature and water evaporation had the strongest and positive effect on the secondary growth rate while the role of precipitation was minor and negative. Air temperature and evaporation variations during growing season were assumed to remain in their optimum level; increasing xylem formation by accelerating carbohydrate production and carbon uptake of trees, respectively. Since the studied site had warm and humid climate receiving sufficient amount of rainfall before and during growing season, water availability was not a limiting factor of radial growth and its minor negative relation was interpreted according to its small hampering effect on the air temperature and sunlight absorption of trees. It was concluded that meteorological factors affecting secondary growth rate of trees should be interpreted as a package rather than analyzed disconnectedly.

scholarly journals Interaction of Seasonal Sun-Angle and Savanna Phenology Observed and Modelled using MODIS

2019 ◽  
Vol 11 (12) ◽  
pp. 1398 ◽  
Author(s):  
Xuanlong Ma ◽  
Alfredo Huete ◽  
Ngoc Nguyen Tran
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Growing Season ◽  
The Sun ◽  
Space And Time ◽  
Ndvi Time Series ◽  
Angle Effect ◽  
Phenological Metrics

Remote sensing of phenology usually works at the regional and global scales, which imposes considerable variations in the solar zenith angle (SZA) across space and time. Variations in SZA alters the shape and profile of the surface reflectance and vegetation index (VI) time series, but this effect on remote-sensing-derived vegetation phenology has not been adequately evaluated. The objective of this study is to understand the behaviour of VIs response to SZA, and to further improve the interpretation of satellite observed vegetation dynamics, across space and time. In this study, the sensitivity of two widely used VIs—the normalised difference vegetation index (NDVI) and the enhanced vegetation index (EVI)—to SZA was investigated at four northern Australian savanna sites, over a latitudinal distance of 9.8° (~1100 km). Complete time series of surface reflectances, as acquired with different SZA configurations, were simulated using Bidirectional Reflectance Distribution Function (BRDF) parameters provided by MODerate Resolution Imaging Spectroradiometer (MODIS). The sun-angle dependency of the four phenological transition dates were assessed. Results showed that while NDVI was very sensitive to SZA, such sensitivity was nearly absent for EVI. A negative correlation was also observed between NDVI sensitivity to SZA and vegetation cover, with sensitivity declining to the same level as EVI when vegetation cover was high. Different sun-angle configurations resulted in considerable variations in the shape and magnitude of the phenological profiles. The sensitivity of VIs to SZA was generally greater during the dry season (with only active trees present) than in the wet season (with both active trees and grasses), thus, the sun-angle effect on VIs was phenophase-dependent. The sun-angle effect on NDVI time series resulted in considerable differences in the phenological metrics across different sun-angle configurations. Across four sites, the sun-angle effect caused 15.5 days, 21.6 days, and 20.5 days differences in the start, peak, and the end of the growing season derived from NDVI time series, with seasonally varying SZA at local solar noon, as compared to those metrics derived from NDVI time series with fixed SZA. In comparison, those differences in the start, peak, and end of the growing season for EVI were significantly smaller, with only 4.8 days, 4.9 days, and 3 days, respectively. Our results suggest the potential importance of considering the seasonal SZA effect on VI time series prior to the retrieval of phenological metrics.

scholarly journals Detection of Changes in Hydrological Time Series During Recent Decades

2020 ◽  
Vol 28 (2) ◽  
pp. 56-62
Author(s):  
Mária Ďurigová ◽  
Kamila Hlavčová ◽  
Jana Poórová
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Time Series Data ◽  
Kendall Test ◽  
Change Points ◽  
Series Data ◽  
Data Series ◽  
Time Data ◽  
Air Temperatures ◽  
Pettitt’S Test

AbstractAn analysis of a hydrological time-series data offers the possibility of detecting changes that have arisen due to climate change or change in land use. This paper deals with the detection of changes in the hydrological time data series. The trend analysis was applied at 58 stage-discharge gauging stations that are located throughout Slovakia, with the measurement period from 1962 to 2017. The Mann-Kendall test show a declining trends in the summer and a few rising trends in the winter in discharges. In the town of Banská Bystrica at a station on the Hron River, decades of discharges, air temperatures, and precipitation totals were analyzed. The five decades from the 1960s to the 2000s were used. The hydrological time data series were also analyzed by the Pettitt’s test, which is used to detect change points. The decadal analysis at the Banská Bystrica station shows an increase in the air temperature but insignificant changes in discharges and precipitation. Pettitt’s test identified many change points in the 1990s in the air temperature.

scholarly journals Influência da Urbanização no Clima da Cidade de Campina Grande-PB (Influence of Urbanization on Climate of the Campina Grande City–PB)

2011 ◽  
Vol 4 (1) ◽  
pp. 134 ◽  
Author(s):  
Francisco de Assis Salviano de Sousa ◽  
Heliene Ferreira de Morais ◽  
Vicente De Paulo Rodrigues da
Keyword(s):  
Time Series ◽  
Relative Humidity ◽  
Air Temperature ◽  
Anthropogenic Activities ◽  
Urban Climate ◽  
Kendall Test ◽  
Annual Rainfall ◽  
Abrupt Changes ◽  
Mann Kendall Test ◽  
Deviation Coefficient

A expansão de cidades produz diversos impactos no ambiente urbano causado por atividades antropogênicas. Este estudo avaliou o efeito da urbanização no clima da cidade de Campina Grande com base em dados mensais de temperatura média do ar, precipitação pluvial, umidade relativa do ar e insolação no período de 1963 a 2004. O método de desvios cumulativos foi utilizado para detectar mudanças abruptas nas séries temporais. Dois períodos de estudo foram estabelecidos: pré-urbano intenso PRÉ-UI (1963-1985) e pós-urbano intenso PÓS-UI (1986-2004). Para cada variável climática foram obtidas estatísticas como: médias, desvio-padrão, coeficiente de variação (CV) e autocorrelação serial. Foram avaliadas as diferenças entre as médias dos períodos PRÉ-UI e PÓS-UI através do teste de t-Student. Também foi usado o teste Mann-Kendall para avaliar as tendências das séries temporais no período total estudado. A temperatura média do ar apresentou tendência crescente, enquanto umidade relativa apresentou tendência decrescente, todas estatisticamente significativas ao nível de 1% através do teste de Mann-Kendall. A série de precipitação pluvial não apresentou tendência estatisticamente significativa. A variabilidade da precipitação pluvial intra-anual, expressa pelo CV, é muito alta e variou de 30 a 89% durante o período analisado. A variabilidade anual da precipitação pluvial é cerca de 30% da variabilidade intra-anual. A temperatura do ar demonstrou persistência natural através dos valores do coeficiente de autocorrelação, para os primeiros lags.Palavras-chave: Clima urbano, Mann-Kendall e variáveis climáticas  Influence of Urbanization on Climate of the Campina Grande City–PB ABSTRACTThe expansion of cities produces different impacts in the urban environment caused by anthropogenic activities. This study evaluated the effect of urbanization on climate of the Campina Grande city based on monthly data of average air temperature, rainfall, relative humidity and sunshine in the period 1963 to 2004. The cumulative deviation method was used to detect abrupt changes in time series. Two study periods were established: intense urban pre-PRE-UI (1963-1985) and after intense urban POST-IU (1986-2004). For each climate variable, statistics were obtained as averages, standard deviation, coefficient of variation (CV) and serial autocorrelation. We evaluated the differences between the mean pre-and post-IU through the IU Student t test. It was also used Mann-Kendall test to assess trends in time series over the entire period studied. The average air temperature showed an ascending trend, while relative humidity showed a declining trend, all statistically significant at 1% through the Mann-Kendall test. The series of rainfall did not show a statistically significant trend. The variability of intra-annual precipitation, expressed as CV, is very high and ranged from 30 to 89% during the period analyzed. The variability of annual rainfall is about 30% of intra-annual variability.The air temperature showed persistence through the natural values the autocorrelation coefficient for the first lags.  Keywords: Urban climate, Mann-Kendall and climatic variables

scholarly journals Forecasting mean monthly maximum and minimum air temperature of Jalandhar district of Punjab, India using seasonal ARIMA model

2022 ◽  
Vol 24 (1) ◽  
Author(s):  
BALJEET KAUR ◽  
NAVNEET KAUR ◽  
K. K. GILL ◽  
JAGJEEVAN SINGH ◽  
S. C. BHAN ◽  
...  
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Goodness Of Fit ◽  
Time Series Data ◽  
Arima Model ◽  
Kendall Test ◽  
Series Data ◽  
Data Series ◽  
Augmented Dickey Fuller ◽  
Minimum Air Temperature

The long-term air temperature data series from 1971-2019 was analyzed and used for forecasting mean monthly air temperature at the district level. The Augmented Dickey-Fuller test, Kwiatkowski-Phillips-Schmidt-Shin test, and Mann-Kendall test were employed to test the stationarity and trend of the time series. The mean monthly maximum air temperature did not show any significant variation while an increasing trend of 0.04°C per annum was observed in mean monthly minimum air temperature, which was detrended. Box-Jenkins autoregressive integrated moving–averages were used to forecast the forthcoming 5 years (2020-2024) air temperature in the district Jalandhar of Punjab. The goodness of fit was tested against residuals, the autocorrelation function, and the histogram. The fitted model was able to capture dynamics of the time series data and produce a sensible forecast.

scholarly journals Dynamic Changes of NDVI in the Growing Season of the Tibetan Plateau During the Past 17 Years and Its Response to Climate Change

2019 ◽  
Vol 16 (18) ◽  
pp. 3452 ◽  
Author(s):  
Xianglin Huang ◽  
Tingbin Zhang ◽  
Guihua Yi ◽  
Dong He ◽  
Xiaobing Zhou ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Tibetan Plateau ◽  
Time Series Analysis ◽  
Environmental Changes ◽  
Climatic Factors ◽  
Growing Season ◽  
Lag Time ◽  
The Tibetan Plateau ◽  
Series Analysis

The fragile alpine vegetation in the Tibetan Plateau (TP) is very sensitive to environmental changes, making TP one of the hotspots for studying the response of vegetation to climate change. Existing studies lack detailed description of the response of vegetation to different climatic factors using the method of multiple nested time series analysis and the method of grey correlation analysis. In this paper, based on the Normalized Difference Vegetation Index (NDVI) of TP in the growing season calculated from the MOD09A1 data product of Moderate-resolution Imaging Spectroradiometer (MODIS), the method of multiple nested time series analysis is adopted to study the variation trends of NDVI in recent 17 years, and the lag time of NDVI to climate change is analyzed using the method of Grey Relational Analysis (GRA). Finally, the characteristics of temporal and spatial differences of NDVI to different climate factors are summarized. The results indicate that: (1) the spatial distribution of NDVI values in the growing season shows a trend of decreasing from east to west, and from north to south, with a change rate of −0.13/10° E and −0.30/10° N, respectively. (2) From 2001 to 2017, the NDVI in the TP shows a slight trend of increase, with a growth rate of 0.01/10a. (3) The lag time of NDVI to air temperature is not obvious, while the NDVI response lags behind cumulative precipitation by zero to one month, relative humidity by two months, and sunshine duration by three months. (4) The effects of different climatic factors on NDVI are significantly different with the increase of the study period.

scholarly journals Effects of the prewhitening method, the time granularity, and the time segmentation on the Mann–Kendall trend detection and the associated Sen's slope

2020 ◽  
Vol 13 (12) ◽  
pp. 6945-6964
Author(s):  
Martine Collaud Coen ◽  
Elisabeth Andrews ◽  
Alessandro Bigi ◽  
Giovanni Martucci ◽  
Gonzague Romanens ◽  
...  
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Statistical Significance ◽  
Parametric Method ◽  
Kendall Test ◽  
Trend Detection ◽  
Temporal Segmentation ◽  
Sen’S Slope ◽  
Power Of The Test ◽  
Original Time

Abstract. The Mann–Kendall test associated with the Sen's slope is a very widely used non-parametric method for trend analysis. It requires serially uncorrelated time series, yet most of the atmospheric processes exhibit positive autocorrelation. Several prewhitening methods have therefore been designed to overcome the presence of lag-1 autocorrelation. These include a prewhitening, a detrending and/or a correction of the detrended slope and the original variance of the time series. The choice of which prewhitening method and temporal segmentation to apply has consequences for the statistical significance, the value of the slope and of the confidence limits. Here, the effects of various prewhitening methods are analyzed for seven time series comprising in situ aerosol measurements (scattering coefficient, absorption coefficient, number concentration and aerosol optical depth), Raman lidar water vapor mixing ratio, as well as tropopause and zero-degree temperature levels measured by radio-sounding. These time series are characterized by a broad variety of distributions, ranges and lag-1 autocorrelation values and vary in length between 10 and 60 years. A common way to work around the autocorrelation problem is to decrease it by averaging the data over longer time intervals than in the original time series. Thus, the second focus of this study evaluates the effect of time granularity on long-term trend analysis. Finally, a new algorithm involving three prewhitening methods is proposed in order to maximize the power of the test, to minimize the number of erroneous detected trends in the absence of a real trend and to ensure the best slope estimate for the considered length of the time series.

DEVELOPMENT OF STREAMFLOW DROUGHT INDICES IN THE MORAVA RIVER BASIN

2020 ◽  
Author(s):  
Ondrej Ledvinka ◽  
◽  
Pavel Coufal ◽  
Keyword(s):  
Time Series ◽  
Kendall Test ◽  
Drought Indices ◽  
Drought Period ◽  
Left Hand ◽  
Low Flows ◽  
Current Period ◽  
Catchment Size ◽  
Morava River ◽  
The Stability

The territory of Czechia currently suffers from a long-lasting drought period which has been a subject of many studies, including the hydrological ones. Previous works indicated that the basin of the Morava River, a left-hand tributary of the Danube, is very prone to the occurrence of dry spells. It also applies to the development of various hydrological time series that often show decreases in the amount of available water. The purpose of this contribution is to extend the results of studies performed earlier and, using the most updated daily time series of discharge, to look at the situation of the so-called streamflow drought within the basin. 46 water-gauging stations representing the rivers of diverse catchment size were selected where no or a very weak anthropogenic influences are expected and the stability and sensitivity of profiles allow for the proper measurement of low flows. The selected series had to cover the most current period 1981-2018 but they could be much longer, which was considered beneficial for the next determination of the development direction. Various series of drought indices were derived from the original discharge series. Specifically, 7-, 15- and 30-day low flows together with deficit volumes and their durations were tested for trends using the modifications of the Mann– Kendall test that account for short-term and long-term persistence. In order to better reflect the drivers of streamflow drought, the indices were considered for summer and winter seasons separately as well. The places with the situation critical to the future water resources management were highlighted where substantial changes in river regime occur probably due to climate factors. Finally, the current drought episode that started in 2014 was put into a wider context, making use of the information obtained by the analyses.

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