scholarly journals Temporal Trend Analysis of Meteorological Variables and Reference Evapotranspiration in the Inter-mountain Region of Wyoming

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2159 ◽  
Author(s):  
Vivek Sharma ◽  
Christopher Nicholson ◽  
Antony Bergantino ◽  
Suat Irmak ◽  
Dannele Peck
Keyword(s):  
Reference Evapotranspiration ◽  
Statistical Significance ◽  
Homogeneity Test ◽  
Positive Trend ◽  
Climate Variables ◽  
Time Step ◽  
Mk Test ◽  
Standard Normal Homogeneity Test ◽  
Average Annual Temperature ◽  
Non Parametric

Long-term trends in reference evapotranspiration (ETref) and its controlling factors are critical pieces of information in understanding how agricultural water requirements and water resources respond to a variable and changing climate. In this study, ETref, along with climate variables that directly and indirectly impact it, such as air temperature (T), incoming solar radiation (Rs), wind speed (u), relative humidity (RH), and precipitation (P), are discussed. All variables are analyzed for four weather stations located in irrigated agricultural regions of inter-mountain Wyoming: Pinedale, Torrington, Powell, and Worland. Non-parametric Mann−Kendall (MK) trend test and Theil–Sen’s slope estimator were used to determine the statistical significance of positive or negative trends in climate variables and ETref. Three non-parametric methods—(i) Pettitt Test (PT), (ii) Alexandersson’s Standard Normal Homogeneity Test (SNHT), and (iii) Buishand’s Range Test (BRT)—were used to check the data homogeneity and to detect any significant Trend Change Point (TCP) in the measured data time-series. For the data influenced by serial correlation, a modified version of the MK test (pre-whitening) were applied. Over the study duration, a statistically significant positive trend in maximum, minimum, and average annual temperature (Tmax, Tmin, and Tavg, respectively) was observed at all stations, except for Torrington in the southeast part of Wyoming, where these temperature measures had negative trends. The study indicated that the recent warming trends are much more pronounced than during the 1930s Dust Bowl Era. For all the stations, no TCPs were observed for P; however, significant changes in trends were observed for Tmax and Tmin on both annual and seasonal timescales. Both grass and alfalfa reference evapotranspiration (ETo and ETr) had statistically significant positive trends in at least one season (in particular, the spring months of March, April, and May (MAM) or summer months of June, July, and August (JJA) at all stations, except the station located in southeast Wyoming (Torrington) where no statistically significant positive trends were observed. Torrington instead experienced statistically significant negative trends in ETo and ETr, particularly in the fall months of SON and winter months of DJF. Over the period-of-record, an overall change of +26, +31, −48, and +34 mm in ETo and +28, +40, −80, and +39 mm in ETr was observed at Pinedale, Powell, Torrington, and Worland, respectively. Our analysis indicated that both ETo (−3.4 mm year−1) and ETr (−5.3 mm year−1) are decreasing at a much faster rate in recent years at Torrington compared to other stations. Relationships between climate variables and ETo and ETr on an annual time-step reveal that ETo and ETr were significantly and positively correlated to Tavg, Tmax, Rs, Rn, and VPD, as well as significantly and negatively correlated to RH.

scholarly journals Inhomogeneity detection in the rainfall series for the Mae Klong River Basin, Thailand

2021 ◽  
Vol 11 (9) ◽  
Author(s):  
Alamgir Khalil
Keyword(s):  
River Basin ◽  
Curve Analysis ◽  
Rainfall Series ◽  
Rainfall Data ◽  
Homogeneity Test ◽  
Significance Level ◽  
Von Neumann ◽  
Standard Normal Homogeneity Test ◽  
Double Mass ◽  
Climate Studies

AbstractAn accurate and complete rainfall record is prerequisite for climate studies. The purpose of this research study was to evaluate the homogeneity of the rainfall series for the Mae Klong River Basin in Thailand. Monthly rainfall data of eight stations in the Mae Klong River Basin for the period 1971–2015 were used. The double mass curve analysis was used to check the consistency of rainfall data, whereas the absolute homogeneity was assessed using the Pettitt test, standard normal homogeneity test, Buishand test, and von Neumann test at a 5% significance level. The results of these tests were qualitatively classified as ‘useful’, ‘doubtful’, and ‘suspect’ according to the null hypothesis. Results of the monthly time series indicated the rainfall data as ‘useful’ for 75% of the stations, while two stations’ data were classified as ‘doubtful’ (Stn130221) and ‘suspect’ (Stn376401). On an annual scale, seven out of eight stations data were classified as ‘useful,’ while one station (Stn376401) data were classified as ‘suspect’. Double mass curve analysis technique was used for the adjustment of inhomogeneous data. The results of this study can help provide reliable rainfall data for climate studies in the basin.

The Application of the Smirnov Test in the Homogeneity Test for Non-Normal Distribution Temperature Series

2012 ◽  
Vol 516-517 ◽  
pp. 530-535
Author(s):  
Xin Jie Deng ◽  
Yang Sheng You ◽  
Yan Ying Chen ◽  
Xue Mei Yang
Keyword(s):  
Normal Distribution ◽  
Classical Method ◽  
Temperature Series ◽  
Homogeneity Test ◽  
Test Results ◽  
Standard Normal Homogeneity Test ◽  
Standard Normal ◽  
Better Than ◽  
Smirnov Test

The homogeneity test is the first stage to revise the climate records. Its accuracy will directly affect the follow-up work. The classic method SNHT (Standard Normal Homogeneity Test) can only be applied in climatic sequences obey normal distribution, but lots of non-normality climate sequences need to be examined. In this paper, the Smirnov Test was introduced to test the homogeneity of the temperature series, which is a classical method for distribution test, and it can apply for the temperature sequences obey any distribution. The homogeneity test results by testing Chongqing Municipality's temperature sequences show that: the Smirnov Test is better than SNHT

Trends in reference evapotranspiration and associated climate variables over the last 30 years (1984–2014) in the Pampa region of Argentina

2018 ◽  
Vol 136 (3-4) ◽  
pp. 1371-1386 ◽  
Author(s):  
M.F. D’Andrea ◽  
A.N. Rousseau ◽  
Y. Bigah ◽  
N.N. Gattinoni ◽  
J.C. Brodeur
Keyword(s):  
Reference Evapotranspiration ◽  
Climate Variables ◽  
Pampa Region

NOPAPROD Non-Parametric Testing on Projections from Multivariate Data. Applications to near Infrared Spectroscopy in Clinical Studies

2009 ◽  
Vol 17 (2) ◽  
pp. 101-107 ◽  
Author(s):  
Josefina Nyström ◽  
Britta Lindholm-Sethson ◽  
Paul Geladi
Keyword(s):  
Data Reduction ◽  
Clinical Studies ◽  
Radiation Effects ◽  
Near Infrared ◽  
Radiation Treatment ◽  
Statistical Significance ◽  
Skewed Distribution ◽  
Breast Cancer Patients ◽  
Parametric Testing ◽  
Non Parametric

Clinical studies may be carried out using non-invasively collected near infrared spectra of patient skin. Two problems encountered are: (1) data reduction to go from thousands of wavelengths to some clinically relevant estimator and (2) getting statistical significance from noisy data with sometimes very skewed distributions. The problem of data reduction can usually be solved by principal component analysis to get a few meaningful components. In the space spanned by these components, a direction of discrimination may have to be found, typically discrimination between treated and control. A visual difference in a score plot is often not enough; statistical significance has to be demonstrated. Once a univariate estimator is found, non-parametric testing can show significant differences, even if the data are noisy and have an unknown and skewed distribution. The NOPRAPOD method com bines the actions of finding a direction in a reduced data space and performing the non-parametric significance testing by producing a disk of significance. Two examples are included. Example one is from a study of diabetes-related neuropathy where it is shown that significant differences show up in the NIR spectra. Example two is from a study of post-operative radiation treatment of breast cancer patients, where it is shown that radiation effects (erythema) and the effect of lotion can be determined with an indication of significance from the NIR spectra.

scholarly journals Creating long-term gridded fields of reference evapotranspiration in Alpine terrain based on a recalibrated Hargreaves method

2016 ◽  
Vol 20 (3) ◽  
pp. 1211-1223 ◽  
Author(s):  
Klaus Haslinger ◽  
Annett Bartsch
Keyword(s):  
High Resolution ◽  
Reference Evapotranspiration ◽  
Grid Point ◽  
Temperature Fields ◽  
Time Step ◽  
Digital Elevation ◽  
Maximum Temperatures ◽  
Elevation Model ◽  
Relative Errors ◽  
Mean Square Errors

Abstract. A new approach for the construction of high-resolution gridded fields of reference evapotranspiration for the Austrian domain on a daily time step is presented. Gridded data of minimum and maximum temperatures are used to estimate reference evapotranspiration based on the formulation of Hargreaves. The calibration constant in the Hargreaves equation is recalibrated to the Penman–Monteith equation in a monthly and station-wise assessment. This ensures, on one hand, eliminated biases of the Hargreaves approach compared to the formulation of Penman–Monteith and, on the other hand, also reduced root mean square errors and relative errors on a daily timescale. The resulting new calibration parameters are interpolated over time to a daily temporal resolution for a standard year of 365 days. The overall novelty of the approach is the use of surface elevation as the only predictor to estimate the recalibrated Hargreaves parameter in space. A third-order polynomial is fitted to the recalibrated parameters against elevation at every station which yields a statistical model for assessing these new parameters in space by using the underlying digital elevation model of the temperature fields. With these newly calibrated parameters for every day of year and every grid point, the Hargreaves method is applied to the temperature fields, yielding reference evapotranspiration for the entire grid and time period from 1961–2013. This approach is opening opportunities to create high-resolution reference evapotranspiration fields based only temperature observations, but being as close as possible to the estimates of the Penman–Monteith approach.

scholarly journals Gaia DR2 reveals a star formation burst in the disc 2–3 Gyr ago

2019 ◽  
Vol 624 ◽  
pp. L1 ◽  
Author(s):  
R. Mor ◽  
A. C. Robin ◽  
F. Figueras ◽  
S. Roca-Fàbrega ◽  
X. Luri
Keyword(s):  
Star Formation ◽  
Statistical Significance ◽  
Formation Rate ◽  
External Perturbation ◽  
Initial Mass Function ◽  
Star Formation History ◽  
Thin Disc ◽  
Galaxy Model ◽  
Non Parametric ◽  
The Imf

We use Gaia data release 2 (DR2) magnitudes, colours, and parallaxes for stars with G <  12 to explore a parameter space with 15 dimensions that simultaneously includes the initial mass function (IMF) and a non-parametric star formation history (SFH) for the Galactic disc. This inference is performed by combining the Besançon Galaxy Model fast approximate simulations (BGM FASt) and an approximate Bayesian computation algorithm. We find in Gaia DR2 data an imprint of a star formation burst 2–3 Gyr ago in the Galactic thin disc domain, and a present star formation rate (SFR) of ≈1 M⊙/yr. Our results show a decreasing trend of the SFR from 9–10 Gyr to 6–7 Gyr ago. This is consistent with the cosmological star formation quenching observed at redshifts z <  1.8. This decreasing trend is followed by a SFR enhancement starting at ∼5 Gyr ago and continuing until ∼1 Gyr ago which is detected with high statistical significance by discarding the null hypothesis of an exponential SFH with a p-value = 0.002. We estimate, from our best fit model, that about 50% of the mass used to generate stars, along the thin disc life, was expended in the period from 5 to 1 Gyr ago. The timescale and the amount of stellar mass generated during the SFR enhancement event lead us to hypothesise that its origin, currently under investigation, is not intrinsic to the disc. Thus, an external perturbation is needed for its explanation. Additionally, for the thin disc we find a slope of the IMF of α3 ≈ 2 for masses M >  1.53 M⊙ and α2 ≈ 1.3 for the mass range between 0.5 and 1.53 M⊙. This is the first time that we consider a non-parametric SFH for the thin disc in the Besançon Galaxy Model. This new step, together with the capabilities of the Gaia DR2 parallaxes to break degeneracies between different stellar populations, allow us to better constrain the SFH and the IMF.

Effects of inter-annual climate variability on grape harvest timing in rainfed hilly vineyards of Piedmont (NW Italy)

2020 ◽  
Author(s):  
Danilo Rabino ◽  
Marcella Biddoccu ◽  
Giorgia Bagagiolo ◽  
Guido Nigrelli ◽  
Luca Mercalli ◽  
...  
Keyword(s):  
Climate Variability ◽  
Weather Data ◽  
Maximum Temperature ◽  
Data Series ◽  
Positive Trend ◽  
Climate Variables ◽  
Climate Data ◽  
Historical Series ◽  
Nw Italy ◽  
Level Of Significance

&lt;p&gt;Historical weather data represent an extremely precious resource for agro-meteorology for studying evolutionary dynamics and for predictive purposes, to address agronomical and management choices, that have economic, social and environmental effect. The study of climatic variability and its consequences starts from the observation of variations over time and the identification of the causes, on the basis of historical series of meteorological observations. The availability of long-lasting, complete and accurate datasets is a fundamental requirement to predict and react to climate variability. Inter-annual climate changes deeply affect grapevine productive cycle determining direct impact on the onset and duration of phenological stages and, ultimately, on the grape harvest and yield. Indeed, climate variables, such as air temperature and precipitation, affect evapotranspiration rates, plant water requirements, and also the vine physiology. In this respect, the observed increase in the number of warm days poses a threat to grape quality as it creates a situation of imbalance at maturity, with respect to sugar content, acidity and phenolic and aromatic ripeness.&lt;/p&gt;&lt;p&gt;A study was conducted to investigate the relationships between climate variables and harvest onset dates to assess the responses of grapevine under a global warming scenario. The study was carried out in the &amp;#8220;Monferrato&amp;#8221; area, a rainfed hillslope vine-growing area of NW Italy. In particular, the onset dates of harvest of different local wine grape varieties grown in the Vezzolano Experimental Farm (CNR-IMAMOTER) and in surrounding vineyards (affiliated to the Terre dei Santi Cellars) were recorded from 1962 to 2019 and then related to historical series of climate data by means of regression analysis. The linear regression was performed based on the averages of maximum and minimum daily temperatures and sum of precipitation (1962&amp;#8211;2019) calculated for growing and ripening season, together with a bioclimatic heat index for vineyards, the Huglin index. The climate data were obtained from two data series collected in the Experimental farm by a mechanical weather station (1962-2002) and a second series recorded (2002-2019) by an electro-mechanical station included in Piedmont Regional Agro-meteorological Network. Finally, a third long-term continuous series covering the period from 1962 to 2019, provided by Italian Meteorological Society was considered in the analysis.&lt;/p&gt;&lt;p&gt;The results of the study highlighted that inter-annual climate variability, with a general positive trend of temperature, significantly affects the ripening of grapes with a progressive anticipation of the harvest onset dates. In particular, all the considered variables excepted precipitation, resulted negatively correlated with the harvest onset date reaching a high level of significance (up to P&lt; 0.001). Best results have been obtained for maximum temperature and Huglin index, especially by using the most complete dataset. The change ratios obtained using datasets including last 15 years were greater (in absolute terms) than results limited to the period 1962-2002, and also correlations have greater level of significance. The results indicated clearly the relationships between the temperature trend and the gradual anticipation of harvest and the importance of having long and continuous historical weather data series available.&lt;/p&gt;

scholarly journals Relative Humidity in the Troposphere with AIRS

2014 ◽  
Vol 71 (7) ◽  
pp. 2516-2533 ◽  
Author(s):  
Alexander Ruzmaikin ◽  
Hartmut H. Aumann ◽  
Evan M. Manning
Keyword(s):  
Relative Humidity ◽  
Surface Temperature ◽  
Radiative Forcing ◽  
General Circulation ◽  
Large Scale ◽  
Statistical Significance ◽  
General Circulation Models ◽  
Positive Trend ◽  
Drying Time ◽  
Clear Sky

Abstract New global satellite data from the Atmospheric Infrared Sounder (AIRS) are applied to study the tropospheric relative humidity (RH) distribution and its influence on outgoing longwave radiation (OLR) for January and July in 2003, 2007, and 2011. RH has the largest maxima over 90% in the equatorial tropopause layer in January. Maxima in July do not arise above 60%. Seasonal variations of about 20% in zonally averaged RH are observed in the equatorial region of the low troposphere, in the equatorial tropopause layer, and in the polar regions. The seasonal variability in the recent decade has increased by about 5% relative to that in 1973–88, indicating a positive trend. The observed RH profiles indicate a moist bias in the tropical and subtropical regions typically produced by the general circulation models. The new data and method of evaluating the statistical significance of bimodality confirm bimodal probability distributions of RH at large tropospheric scales, notably in the ascending branch of the Hadley circulation. Bimodality is also seen at 500–300 hPa in mid- and high latitudes. Since the drying time of the air is short compared with the mixing time of moist and dry air, the bimodality reflects the large-scale distribution of sources of moisture and the atmospheric circulation. Analysis of OLR dependence on surface temperature shows a 0.2 W m−2 K−1 difference in sensitivities between clear-sky and all-sky OLR, indicating a positive longwave cloud radiative forcing. Diagrams of the clear-sky OLR as functions of percentiles of surface temperature and relative humidity in the tropics are designed to provide a new measure of the supergreenhouse effect.

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