Journal of Climatology The latest articles from Hindawi Publishing Corporation © 2016 , Hindawi Publishing Corporation . All rights reserved. Changes in Climate Extremes over North Thailand, 1960–2099 Tue, 23 Feb 2016 08:01:45 +0000 This study analyzes 24 climate extreme indices over North Thailand using observed data for daily maximum and minimum temperatures and total daily rainfall for the 1960–2010 period, and HadCM3 Global Climate Model (GCM) and PRECIS Regional Climate Model simulated data for the 1960–2100 period. A statistical downscaling tool is employed to downscale GCM outputs. Variations in and trends of historical and future climates are identified using the nonparametric Mann-Kendall trend test and Sen’s slope. Temperature extreme indices showed a significant rising trend during the observed period and are expected to increase significantly with an increase in summer days and tropical nights in the future. A notable decline in the number of cool days and nights is also expected in the study area while the number of warm days and nights is expected to increase. There was an insignificant decrease in total annual rainfall, number of days with rainfall more than 10 and 20 mm. However, the annual rainfall is projected to increase by 9.65% in the future 2011–2099 period compared to the observed 1960–2010 period. Mohammad Badrul Masud, Peeyush Soni, Sangam Shrestha, and Nitin K. Tripathi Copyright © 2016 Mohammad Badrul Masud et al. All rights reserved. Temporal and Spatial Variability of Air Temperatures in Estonia during 1756–2014 Tue, 19 Jan 2016 06:31:45 +0000 The change in the statistical and temporal parameters of air temperatures in the Estonian cities, that is, Tallinn and Tartu, was analyzed for two centuries. The results showed that the change of air temperature in Estonia exceeded 0.5°C per ten years for the time 1979–2012. For the longer period, that is, 1880–2012, the average annual rise in the air temperature was within the range of 0.1°C per ten years. The analysis of frequency distributions of the average annual air temperatures and Welch’s -test demonstrated the considerable rise in air temperature (the significance level of 0.05) in Estonia, which took place in 1901–2014 and was witnessed only in the months from November to April. However, no significant rise in air temperature was detected in Estonia from May to October. Agu Eensaar Copyright © 2016 Agu Eensaar. All rights reserved. Amplified Feedback Mechanism of the Forests-Aerosols-Climate System Thu, 09 Apr 2015 09:30:02 +0000 Climate change very likely has effects on vegetation so that trees grow faster due to carbon dioxide fertilization (a higher partial pressure increases the rate of reactions with Rubisco during photosynthesis) and that trees can be established in new territories in a warmer climate. This has far-reaching significance for the climate system mainly due to a number of feedback mechanisms still under debate. By simulating the vegetation using the Lund-Potsdam-Jena guess dynamic vegetation model, a territory in northern Russia is studied during three different climate protocols assuming a doubling of carbon dioxide levels compared to the year 1975. A back of the envelope calculation is made for the subsequent increased levels of emissions of monoterpenes from spruce and pine forests. The results show that the emissions of monoterpenes at the most northern latitudes were estimated to increase with over 500% for a four-degree centigrade increase protocol. The effect on aerosol and cloud formation is discussed and the cloud optical thickness is estimated to increase more than 2%. Thomas Hede, Caroline Leck, and Jonas Claesson Copyright © 2015 Thomas Hede et al. All rights reserved. Comparative Study of M5 Model Tree and Artificial Neural Network in Estimating Reference Evapotranspiration Using MODIS Products Wed, 17 Dec 2014 13:53:37 +0000 Reference evapotranspiration () is one of the major parameters affecting hydrological cycle. Use of satellite images can be very helpful to compensate for lack of reliable weather data. This study aimed to determine using land surface temperature (LST) data acquired from MODIS sensor. LST data were considered as inputs of two data-driven models including artificial neural network (ANN) and M5 model tree to estimate values and their results were compared with calculated by FAO-Penman-Monteith (FAO-PM) equation. Climatic data of five weather stations in Khuzestan province, which is located in the southeastern Iran, were employed in order to calculate . LST data extracted from corresponding points of MODIS images were used in training of ANN and M5 model tree. Among study stations, three stations (Amirkabir, Farabi, and Gazali) were selected for creating the models and two stations (Khazaei and Shoeybie) for testing. In Khazaei station, the coefficient of determination () values for comparison between calculated by FAO-PM and estimated by ANN and M5 tree model were 0.79 and 0.80, respectively. In a similar manner, values for Shoeybie station were 0.86 and 0.85. In general, the results showed that both models can properly estimate by means of LST data derived from MODIS sensor. Armin Alipour, Jalal Yarahmadi, and Maryam Mahdavi Copyright © 2014 Armin Alipour et al. All rights reserved. Analysis and Comparison of Trends in Extreme Temperature Indices in Riyadh City, Kingdom of Saudi Arabia, 1985–2010 Mon, 03 Nov 2014 07:50:29 +0000 This study employed the time series of thirteen extreme temperature indices over the period 1985–2010 to analyze and compare temporal trends at two weather stations in Riyadh city, Saudi Arabia. The trend analysis showed warming of the local air for the city. Significant increasing trends were found in annual average maximum and minimum temperatures, maximum of minimum temperature, warm nights, and warm days for an urban and a rural station. Significant decreasing trends were detected in the number of cool nights and cool days at both stations. Comparison of the trends suggests that, in general, the station closer to the city center warmed at a slower rate than the rural station. Significant differences were found in a lot of the extreme temperature indices, suggesting that urbanization and other factors may have had negative effects on the rate of warming at the urban station. Ali S. Alghamdi and Todd W. Moore Copyright © 2014 Ali S. Alghamdi and Todd W. Moore. All rights reserved. Interglacials, Milankovitch Cycles, Solar Activity, and Carbon Dioxide Mon, 08 Sep 2014 07:37:07 +0000 The existing understanding of interglacial periods is that they are initiated by Milankovitch cycles enhanced by rising atmospheric carbon dioxide concentrations. During interglacials, global temperature is also believed to be primarily controlled by carbon dioxide concentrations, modulated by internal processes such as the Pacific Decadal Oscillation and the North Atlantic Oscillation. Recent work challenges the fundamental basis of these conceptions. Gerald E. Marsh Copyright © 2014 Gerald E. Marsh. All rights reserved. Coastal Boundary Layer Characteristics of Wind, Turbulence, and Surface Roughness Parameter over the Thumba Equatorial Rocket Launching Station, India Thu, 19 Jun 2014 09:55:49 +0000 The study discusses the features of wind, turbulence, and surface roughness parameter over the coastal boundary layer of the Peninsular Indian Station, Thumba Equatorial Rocket Launching Station (TERLS). Every 5 min measurements from an ultrasonic anemometer at 3.3 m agl from May 2007 to December 2012 are used for this work. Symmetries in mesoscale turbulence, stress off-wind angle computations, structure of scalar wind, resultant wind direction, momentum flux (), Obukhov length (), frictional velocity (), w-component, turbulent heat flux (), drag coefficient (), turbulent intensities, standard deviation of wind directions (), wind steadiness factor- relationship, bivariate normal distribution (BND) wind model, surface roughness parameter (), and wind direction () relationship, and variation of with the Indian South West monsoon activity are discussed. K. V. S. Namboodiri, Dileep Puthillam Krishnan, Rahul Karunakaran Nileshwar, Koshy Mammen, and Nadimpally Kiran kumar Copyright © 2014 K. V. S. Namboodiri et al. All rights reserved. Six Temperature Proxies of Scots Pine from the Interior of Northern Fennoscandia Combined in Three Frequency Ranges Tue, 06 May 2014 07:10:59 +0000 Six chronologies based on the growth of Scots pine from the inland of northern Fennoscandia were built to separately enhance low, medium, and higher frequencies in growth variability in 1000–2002. Several periodicities of growth were found in common in these data. Five of the low-frequency series have a significant oscillatory mode at 200–250 years of cycle length. Most series also have strong multidecadal scale variability and significant peaks at 33, 67, or 83–125 years. Reconstruction models for mean July and June–August as well as three longer period temperatures were built and compared using stringent verification statistics. We describe main differences in model performance ( = 0.53–0.62) between individual proxies as well as their various averages depending on provenance and proxy type, length of target period, and frequency range. A separate medium-frequency chronology (a proxy for June–August temperatures) is presented, which is closely similar in amplitude and duration to the last two cycles of the Atlantic multidecadal oscillation (AMO). The good synchrony between these two series is only hampered by a 10-year difference in timing. Recognizing a strong medium-frequency component in Fennoscandian climate proxies helps to explain part of the uncertainties in their 20th century trends. Markus Lindholm, Maxim G. Ogurtsov, Risto Jalkanen, Björn E. Gunnarson, and Tarmo Aalto Copyright © 2014 Markus Lindholm et al. All rights reserved. On the Differences in the Intraseasonal Rainfall Variability between Western and Eastern Central Africa: Case of 10–25-Day Oscillations Wed, 23 Apr 2014 00:00:00 +0000 In this paper, we analyze the space-time structures of the 10–25 day intraseasonal variability of rainfall over Central Africa (CA) using 1DD GPCP rainfall product for the period 1996–2009, with an emphasis on the comparison between the western Central Africa (WCA) and the eastern Central Africa (ECA) with different climate features. The results of Empirical Orthogonal Functions (EOFs) analysis have shown that the amount of variance explained by the leading EOFs is greater in ECA than WCA (40.6% and 48.1%, for WCA and ECA, resp.). For the two subregions, the power spectra of the principal components (PCs) peak around 15 days, indicating a biweekly signal. The lagged cross-correlations computed between WCA and ECA PCs time series showed that most of the WCA PCs lead ECA PCs time series with a time scale of 5–8 days. The variations of Intraseasonal Oscillations (ISO) activity are weak in WCA, when compared with ECA where the signal exhibits large annual and interannual variations. Globally, the correlation coefficients computed between ECA and WCA annual mean ISO power time series are weak, revealing that the processes driving the interannual modulation of ISO signal should be different in nature or magnitude in the two subregions. Alain Tchakoutio Sandjon, Armand Nzeukou, Clément Tchawoua, and Tengeleng Siddi Copyright © 2014 Alain Tchakoutio Sandjon et al. All rights reserved. Influence of Northwest Cloudbands on Southwest Australian Rainfall Tue, 08 Apr 2014 09:30:07 +0000 Northwest cloudbands are tropical-extratropical feature that crosses the Australian continent originating from Australia’s northwest coast and develops in a NW-SE orientation. In paper, atmospheric and oceanic reanalysis data (NCEP) and Reynolds reconstructed sea surface temperature data were used to examine northwest cloudband activity across the Australian mainland. An index that reflected the monthly, seasonal, and interannual activity of northwest cloudbands between 1950 and 1999 was then created. Outgoing longwave radiation, total cloud cover, and latent heat flux data were used to determine the number of days when a mature northwest cloudband covered part of the Australian continent between April and October. Regional indices were created for site-specific investigations, especially of cloudband-related rainfall. High and low cloudband activity can affect the distribution of cloudbands and their related rainfall. In low cloudband activity seasons, cloudbands were mostly limited to the south and west Australian coasts. In high cloudband activity seasons, cloudbands penetrated farther inland, which increased the inland rainfall. A case study of the southwest Australian region demonstrated that, in a below average rainfall year, cloudband-related rainfall was limited to the coast. In an above average rainfall year, cloudband-related rainfall occurred further inland. Nicola Telcik and Charitha Pattiaratchi Copyright © 2014 Nicola Telcik and Charitha Pattiaratchi. All rights reserved. An Efficient Prediction Model for Water Discharge in Schoharie Creek, NY Wed, 12 Feb 2014 14:36:55 +0000 Flooding normally occurs during periods of excessive precipitation or thawing in the winter period (ice jam). Flooding is typically accompanied by an increase in river discharge. This paper presents a statistical model for the prediction and explanation of the water discharge time series using an example from the Schoharie Creek, New York (one of the principal tributaries of the Mohawk River). It is developed with a view to wider application in similar water basins. In this study a statistical methodology for the decomposition of the time series is used. The Kolmogorov-Zurbenko filter is used for the decomposition of the hydrological and climatic time series into the seasonal and the long and the short term component. We analyze the time series of the water discharge by using a summer and a winter model. The explanation of the water discharge has been improved up to 81%. The results show that as water discharge increases in the long term then the water table replenishes, and in the seasonal term it depletes. In the short term, the groundwater drops during the winter period, and it rises during the summer period. This methodology can be applied for the prediction of the water discharge at multiple sites. Katerina G. Tsakiri, Antonios E. Marsellos, and Igor G. Zurbenko Copyright © 2014 Katerina G. Tsakiri et al. All rights reserved. Species Favourability Shift in Europe due to Climate Change: A Case Study for Fagus sylvatica L. and Picea abies (L.) Karst. Based on an Ensemble of Climate Models Thu, 19 Dec 2013 14:55:32 +0000 Climate is the main environmental driver determining the spatial distribution of most tree species at the continental scale. We investigated the distribution change of European beech and Norway spruce due to climate change. We applied a species distribution model (SDM), driven by an ensemble of 21 regional climate models in order to study the shift of the favourability distribution of these species. SDMs were parameterized for 1971–2000, as well as 2021–2050 and 2071–2100 using the SRES scenario A1B and three physiological meaningful climate variables. Growing degree sum and precipitation sum were calculated for the growing season on a basis of daily data. Results show a general north-eastern and altitudinal shift in climatological favourability for both species, although the shift is more marked for spruce. The gain of new favourable sites in the north or in the Alps is stronger for beech compared to spruce. Uncertainty is expressed as the variance of the averaged maps and with a density function. Uncertainty in species distribution increases over time. This study demonstrates the importance of data ensembles and shows how to deal with different outcomes in order to improve impact studies by showing uncertainty of the resulting maps. Wolfgang Falk and Nils Hempelmann Copyright © 2013 Wolfgang Falk and Nils Hempelmann. All rights reserved. Periods of Excess Energy in Extreme Weather Events Wed, 18 Dec 2013 17:17:50 +0000 The reconstruction of periodic signals that are embedded in noise is a very important task in many applications. This already difficult task is even more complex when some observations are missed or some are presented irregularly in time. Kolmogorov-Zurbenko (KZ) filtration, a well-developed method, offers a solution to this problem. One section of this paper provides examples of very precise reconstructions of multiple periodic signals covered with high level noise, noise levels that make those signals invisible within the original data. The ability to reconstruct signals from noisy data is applied to the numerical reconstruction of tidal waves in atmospheric pressure. The existence of such waves was proved by well-known naturalist Chapman, but due to the high synoptic fluctuation in atmospheric pressure he was unable to numerically reproduce the waves. Reconstruction of the atmospheric tidal waves reveals a potential intensification on wind speed during hurricanes, which could increase the danger imposed by hurricanes. Due to the periodic structure of the atmospheric tidal wave, it is predictable in time and space, which is important information for the prediction of excess force in developing hurricanes. Igor G. Zurbenko and Amy L. Potrzeba-Macrina Copyright © 2013 Igor G. Zurbenko and Amy L. Potrzeba-Macrina. All rights reserved. Recent Extreme Precipitation and Temperature Changes in Djibouti City (1966–2011) Sun, 08 Dec 2013 15:40:59 +0000 A dataset of 23 derived indicators has been compiled to clarify whether the frequency of rainfall and temperature extremes has changed over the last decades in Djibouti City, eastern Africa. Results show that all precipitation indices have declined over the last decades, although only the very wet day frequency and the very wet day proportion present a significant decline. Annual total precipitation has decreased by 17.4% per decade from 1980 to 2011 and recent mean yearly rainfall (44 mm on average from 2007 to 2011) meets a 73% deficit compared to the 30-year (1981–2010) average (164 mm). The average temperature increase is +0.28°C per decade.Extremely warm days (maximum temperature ≥45.0°C) have become 15 times more frequent than in the pastwhile extremely cool nights (minimum temperature ≤8.6°C) have almost disappeared. Current rainfall shortages and increasing temperature extremes are impacting local people who urgently need adaptation strategies. Pierre Ozer and Ayan Mahamoud Copyright © 2013 Pierre Ozer and Ayan Mahamoud. All rights reserved. Climatic Variation at Thumba Equatorial Rocket Launching Station, India Sun, 10 Nov 2013 10:27:06 +0000 Long-term (45 years) diversified surface meteorological records from Thumba Equatorial Rocket Launching Station (TERLS), India, were collected and analysed to study the long-term changes in the overall climatology, climatology pertained to a particular observational time, mean daily climatology in temperature, inter-annual variability in temperature, interannual variability in surface pressure, and rainfall for the main Indian seasons—South West and North East monsoons and inter-annual mean monthly anomaly structure in temperature. Results on various analyses show strong and vivid features contributed by climate change for this South Peninsular Indian Arabian Sea Coastal Station, and this paper may be a first time venture which discusses climate change imparted perturbations in several meteorological parameters in different time domains, like a specific time, daily, monthly, and interannually over a station. Being a coastal rocket launching station, climatic change information is crucial for long-term planning of its facilities as well as for various rocket range operational demands. K. V. S. Namboodiri, P. K. Dileep, and Koshy Mammen Copyright © 2013 K. V. S. Namboodiri et al. All rights reserved. Time Series Analysis: A New Methodology for Comparing the Temporal Variability of Air Temperature Wed, 06 Nov 2013 14:52:12 +0000 Temporal variability of three different temperature time series was compared by the use of statistical modeling of time series. The three temperature time series represent the same physical process, but are at different levels of spatial averaging: temperatures from point measurements, from regional Baltan65+, and from global ERA-40 reanalyses. The first order integrated average model IMA(0, 1, 1) is used to compare the temporal variability of the time series. The applied IMA(0, 1, 1) model is divisible into a sum of random walk and white noise component, where the variances for both white noises (one of them serving as a generator of the random walk) are computable from the parameters of the fitted model. This approach enables us to compare the models fitted independently to the original and restored series using two new parameters. This operation adds a certain new method to the analysis of nonstationary series. Piia Post and Olavi Kärner Copyright © 2013 Piia Post and Olavi Kärner. All rights reserved. Efficiencies of Inhomogeneity-Detection Algorithms: Comparison of Different Detection Methods and Efficiency Measures Sun, 27 Oct 2013 16:01:26 +0000 Efficiency evaluations for change point Detection methods used in nine major Objective Homogenization Methods (DOHMs) are presented. The evaluations are conducted using ten different simulated datasets and four efficiency measures: detection skill, skill of linear trend estimation, sum of squared error, and a combined efficiency measure. Test datasets applied have a diverse set of inhomogeneity (IH) characteristics and include one dataset that is similar to the monthly benchmark temperature dataset of the European benchmarking effort known by the acronym COST HOME. The performance of DOHMs is highly dependent on the characteristics of test datasets and efficiency measures. Measures of skills differ markedly according to the frequency and mean duration of inhomogeneities and vary with the ratio of IH-magnitudes and background noise. The study focuses on cases when high quality relative time series (i.e., the difference between a candidate and reference series) can be created, but the frequency and intensity of inhomogeneities are high. Results show that in these cases the Caussinus-Mestre method is the most effective, although appreciably good results can also be achieved by the use of several other DOHMs, such as the Multiple Analysis of Series for Homogenisation, Bayes method, Multiple Linear Regression, and the Standard Normal Homogeneity Test. Peter Domonkos Copyright © 2013 Peter Domonkos. All rights reserved. Trends of Dust Transport Episodes in Cyprus Using a Classification of Synoptic Types Established with Artificial Neural Networks Thu, 29 Aug 2013 11:21:31 +0000 The relationship between dust episodes over Cyprus and specific synoptic patterns has long been considered but also further supported in recent studies by the authors. Having defined a dust episode as a day when the average PM10 measurement exceeds the threshold of 50 mg/(m3 day), the authors have utilized Artificial Neural Networks and synoptic charts, together with satellite and ground measurements, in order to establish a scheme which links specific synoptic patterns with the appearance of dust transport over Cyprus. In an effort to understand better these complicated synoptic-scale phenomena and their associations with dust transport episodes, the authors attempt in the present paper a followup of the previous tasks with the objective to further investigate dust episodes from the point of view of their time trends. The results have shown a tendency for the synoptic situations favoring dust events to increase in the last decades, whereas, the synoptic situations not favoring such events tend to decrease with time. S. Michaelides, F. Tymvios, S. Athanasatos, and M. Papadakis Copyright © 2013 S. Michaelides et al. All rights reserved.