Evaluation of NCEP TIGGE short-range forecast for Indian summer monsoon intraseasonal oscillation

Potential evapotranspiration (PET) is one of the most critical parameters in the research on agro-ecological systems. The computational methods for the estimation of PET vary in data demands from very simple (empirically based), requiring only information based on air temperatures, to complex ones (more physically based) that require data on radiation, relative humidity, wind speed, etc. The current research is focused on three study areas in Greece that face different climatic conditions due to their location. Twelve PET formulae were used, analyzed and inter-compared in terms of their sensitivity regarding their input coefficients for the Ardas River basin in north-eastern Greece, Sperchios River basin in Central Greece and Geropotamos River basin in South Greece. The aim was to compare all the methods and conclude to which empirical PET method(s) better represent the PET results in each area and thus should be adopted and used each time and which factors influence the results in each case. The results indicated that for the areas that face Mediterranean climatic conditions, the most appropriate method for the estimation of PET was the temperature-based, Hamon’s second version (PET_Ham2). Furthermore, the PET_Ham2 was able to estimate PET almost similarly to the average results of the 12 equations. For the Ardas River basin, the results indicated that both PET_Ham2 and PET_Ham1 can be used to estimate PET satisfactorily. Moreover, the temperature-based equations have proven to produce better results, followed by the radiation-based equations. Finally, PET_ASCE, which is the most commonly used PET equation, can also be applied occasionally in order to provide satisfactory results.     

Warm spells in Northern Europe in relation to atmospheric circulation

This study describes warm spells in Northern Europe and determines the synoptic situations that cause their occurrence. In this article, a relatively warm day was defined as a day when the maximum temperature exceeded the 95th annual percentile, and a warm spell (WS) was considered to be a sequence of at least five relatively warm days. In the analysed multiannual period and within the investigated area, 24 (Kallax) to 53 (Oslo) WSs were observed. The occurrence of WSs was mainly connected with positive anomalies of sea level pressure and a 500-hPa isobaric surface, displaying the presence of high-pressure systems. This occurrence was also accompanied by positive T850 anomalies.     

Long-term trend and variability of precipitation in Chhattisgarh State,India

Spatial and temporal precipitation variability in Chhattisgarh State in India was examined by using monthly precipitation data for 102 years (1901–2002) from 16 stations. The homogeneity of precipitation data was evaluated by the double-mass curve approach and the presence of serial correlation by lag-1 autocorrelation coefficient. Linear regression analysis, the conventional Mann–Kendall (MK) test, and Spearman’s rho were employed to identify trends and Sen’s slope to estimate the slope of trend line. The coefficient of variation (CV) was used to analyze precipitation variability. Spatial interpolation was done by a Kriging process using ArcGIS 9.3. Results of both parametric and non-parametric tests and trend tests showed that at 5 % significance level, annual precipitation exhibited a decreasing trend at all stations except Bilaspur and Dantewada. For both annual and monsoon precipitation, Sen’s test showed a decreasing trend for all stations, except Bilaspur and Dantewada. The highest percentage of variability was observed in winter precipitation (88.75 %) and minimum percentage variability in annual series (14.01 %) over the 102-year periods.     

Variances in the projections,resulting from CLIMEX,Boosted Regression Trees and Random Forests techniques

The aim of this study was to have a comparative investigation and evaluation of the capabilities of correlative and mechanistic modeling processes, applied to the projection of future distributions of date palm in novel environments and to establish a method of minimizing uncertainty in the projections of differing techniques. The location of this study on a global scale is in Middle Eastern Countries. We compared the mechanistic model CLIMEX (CL) with the correlative models MaxEnt (MX), Boosted Regression Trees (BRT), and Random Forests (RF) to project current and future distributions of date palm (Phoenix dactylifera L.). The Global Climate Model (GCM), the CSIRO-Mk3.0 (CS) using the A2 emissions scenario, was selected for making projections. Both indigenous and alien distribution data of the species were utilized in the modeling process. The common areas predicted by MX, BRT, RF, and CL from the CS GCM were extracted and compared to ascertain projection uncertainty levels of each individual technique. The common areas identified by all four modeling techniques were used to produce a map indicating suitable and unsuitable areas for date palm cultivation for Middle Eastern countries, for the present and the year 2100. The four different modeling approaches predict fairly different distributions. Projections from CL were more conservative than from MX. The BRT and RF were the most conservative methods in terms of projections for the current time. The combination of the final CL and MX projections for the present and 2100 provide higher certainty concerning those areas that will become highly suitable for future date palm cultivation. According to the four models, cold, hot, and wet stress, with differences on a regional basis, appears to be the major restrictions on future date palm distribution. The results demonstrate variances in the projections, resulting from different techniques. The assessment and interpretation of model projections requires reservations, especially in correlative models such as MX, BRT, and RF. Intersections between different techniques may decrease uncertainty in future distribution projections. However, readers should not miss the fact that the uncertainties are mostly because the future GHG emission scenarios are unknowable with sufficient precision. Suggestions towards methodology and processing for improving projections are included.     

A new approach to identify the sensitivity and importance of physical parameters combination within numerical models using the Lund–Potsdam–Jena (LPJ) model as an example

Daily global solar irradiation (R _s) is one of the main inputs in environmental modeling. Because of the lack of its measuring facilities, high-quality and long-term data are limited. In this research, R _s values were estimated based on measured sunshine duration and cloud cover of our synoptic meteorological stations in central and southern Iran during 2008, 2009, and 2011. Clear sky solar irradiation was estimated from linear regression using extraterrestrial solar irradiation as the independent variable with normalized root mean square error (NRMSE) of 4.69 %. Daily R _s was calibrated using measured sunshine duration and cloud cover data under different sky conditions during 2008 and 2009. The 2011 data were used for model validation. According to the results, in the presence of clouds, the R _s model using sunshine duration data was more accurate when compared with the model using cloud cover data (NRMSE = 11. 69 %). In both models, with increasing sky cloudiness, the accuracy decreased. In the study region, more than 92 % of sunshine durations were clear or partly cloudy, which received close to 95 % of total solar irradiation. Hence, it was possible to estimate solar irradiation with a good accuracy in most days with the measurements of sunshine duration.     

The impact of different cooling strategies on urban air temperatures: the cases of Campinas,Brazil and Mendoza,Argentina

This paper describes different ways of reducing urban air temperature and their results in two cities: Campinas, Brazil—a warm temperate climate with a dry winter and hot summer (Cwa), and Mendoza, Argentina—a desert climate with cold steppe (BWk). A high-resolution microclimate modeling system—ENVI-met 3.1—was used to evaluate the thermal performance of an urban canyon in each city. A total of 18 scenarios were simulated including changes in the surface albedo, vegetation percentage, and the H/W aspect ratio of the urban canyons. These results revealed the same trend in behavior for each of the combinations of strategies evaluated in both cities. Nevertheless, these strategies produce a greater temperature reduction in the warm temperate climate (Cwa). Increasing the vegetation percentage reduces air temperatures and mean radiant temperatures in all scenarios. In addition, there is a greater decrease of urban temperature with the vegetation increase when the H/W aspect ratio is lower. Also, applying low albedo on vertical surfaces and high albedo on horizontal surfaces is successful in reducing air temperatures without raising the mean radiant temperature. The best combination of strategies—60 % of vegetation, low albedos on walls and high albedos on pavements and roofs, and 1.5 H/W—could reduce air temperatures up to 6.4 °C in Campinas and 3.5 °C in Mendoza.     

策勒沙漠-绿洲输沙及动力环境特征

利用2012年4月9日—5月9日策勒沙漠和绿洲内部测点的输沙及气象资料,分析了沙漠与绿洲内部沙尘传输的差异性,并从风动力环境上揭示了成因。结果表明:(1)观测期间,通过沙漠测点100 cm(宽)×200 cm(高)断面的沙尘总量为117.5 kg,通过绿洲内部棉田相同断面的沙尘总量为15.1 kg,比沙漠测点减少了87.1%;(2)过渡带和防护林带对风速的消减作用明显,观测期间,沙漠测点起沙风的持续时间为97.4 h,棉田测点仅为18.9 h;(3)观测期间,沙漠测点的总输沙势为114.2 VU,合成输沙势为72.8 VU,合成输沙方向为65.5°;棉田测点的总输沙势为16.1 VU,合成输沙势为15.1 VU,合成输沙方向为104.5°。荒漠过渡带和绿洲防护林通过降低绿洲内部的风速,改变动力环境,削弱沙尘在绿洲区的传输。     

我国台风路径突变研究进展

台风路径突变包括其移动方向和移动速度的显著变化,是当今台风路径预报的难题。突变路径预报的巨大误差常导致台风防御失败,这与其机理认识不足等原因有关。本文回顾了我国关于台风突变路径的研究成果和最新进展。从台风与多尺度环流系统相互作用、台风内部动力机制以及下垫面状况等方面,总结了关于台风路径突变的主要环境影响因子、物理过程和动热力结构特征等方面的认识,对台风路径突变的发生概率、预报技术和存在问题进行阐述,并提出关于路径突变研究需要关注的一些问题。     

基于参与式调查与主成分分析的金塔绿洲变化驱动力分析

内陆河流域绿洲变化驱动机制是旱区绿洲学研究的核心内容之一。利用1963~2010年的Keyhole存档相片、KATE-200卫星航片、Landsat遥感影像等多源数据,获取了金塔绿洲空间分布及面积变化信息。在此基础上,结合参与式调查和主成分分析方法定量分析绿洲变化的驱动机制。研究表明：近47 a来金塔绿洲总体呈现增长的趋势,绿洲规模不断扩大,至2010年绿洲面积高达539.47 km²。其主要原因是气候变化、人口增加、水资源的开发利用与科技进步、社会经济发展及政策等因子的相互交织作用。气候变化是背景因子,人文因子是绿洲变化的主成分因素,且在不同历史社会背景下,其主导人文因素也不同。     

Long-term monitoring of wall paintings affected by soluble salts

Long-term monitoring of wall paintings in historical monuments aims at clarifying involved decay processes and at the same time controlling effects of interventions for conservation. Monitored decay processes relate to the crystallisation of various salts – particularly of nitronatrite and gypsum – from hygroscopic solutions accumulated in the zone of ground moisture. The salts crystallise in response to climatic variations and other environmental changes. Measures for conservation such as protection from water infiltration, reduction of heating temperature and reduction of surface salt accumulation cause a significant slow-down but not a stop of decay. The particular dynamics and causes of remaining slow decay processes are described on three sites in Switzerland: the convent church of Müstair, the crypt in the cathedral of Basel and the crypt in the Grossmünster church of Zürich.