Changes in Climate Extremes over North Thailand, 1960–2099

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.

Temporal and Spatial Variability of Air Temperatures in Estonia during 1756–2014

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 t-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.

Amplified Feedback Mechanism of the Forests-Aerosols-Climate System

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%.

Comparative Study of M5 Model Tree and Artificial Neural Network in Estimating Reference Evapotranspiration Using MODIS Products

Reference evapotranspiration (ETO) 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 ETO 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 ETO values and their results were compared with calculated ETO 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 ETO. 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 (R2) values for comparison between calculated ETO by FAO-PM and estimated ETO by ANN and M5 tree model were 0.79 and 0.80, respectively. In a similar manner, R2 values for Shoeybie station were 0.86 and 0.85. In general, the results showed that both models can properly estimate ETO by means of LST data derived from MODIS sensor.

Analysis and Comparison of Trends in Extreme Temperature Indices in Riyadh City, Kingdom of Saudi Arabia, 1985–2010

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.

Interglacials, Milankovitch Cycles, Solar Activity, and Carbon Dioxide

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.

Coastal Boundary Layer Characteristics of Wind, Turbulence, and Surface Roughness Parameter over the Thumba Equatorial Rocket Launching Station, India

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 (M), Obukhov length (L), frictional velocity (u*), w-component, turbulent heat flux (H), drag coefficient (CD), turbulent intensities, standard deviation of wind directions (σθ), wind steadiness factor-σθ relationship, bivariate normal distribution (BND) wind model, surface roughness parameter (z0), z0 and wind direction (θ) relationship, and variation of z0 with the Indian South West monsoon activity are discussed.

Six Temperature Proxies of Scots Pine from the Interior of Northern Fennoscandia Combined in Three Frequency Ranges

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 (R2 = 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.

On the Differences in the Intraseasonal Rainfall Variability between Western and Eastern Central Africa: Case of 10–25-Day Oscillations

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.

Influence of Northwest Cloudbands on Southwest Australian Rainfall

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.