scholarly journals Rainfall Characteristics and Regionalization in Peninsular Malaysia Based on a High Resolution Gridded Data Set

Water ◽  
2016 ◽  
Vol 8 (11) ◽  
pp. 500 ◽  
Author(s):  
Chee Wong ◽  
Juneng Liew ◽  
Zulkifli Yusop ◽  
Tarmizi Ismail ◽  
Raymond Venneker ◽  
...  
2021 ◽  
Author(s):  
Tayeb Raziei

Abstract This study introduces the climates of Iran defined by Köppen-Geiger, Feddema’s, and UNPEP classifications that applied to a high-resolution ground-based gridded data set relative to the 1985–2017 period. Ten Köppen-Geiger climate types were found for Iran, from which Bwh, Bsk, Csa, Bsh, and Bwk cumulatively account for more than 98% of the territory. Likewise, from 36 possible Feddema’s climate types, Iran possesses fifteen climate types from which the Dry Cool, Semiarid Torrid, Semiarid Hot, Semiarid Warm, Dry warm, Semiarid Cool, and Moist Cool climates collectively occupied approximately 93% of the country. Similarly, arid, semi-arid, humid, and sub-humid UNEP climate types characterized more than 98% of Iran. A few other vertically stratified climates appeared at the highlands of Iran just because of changes in elevation and slope aspects of the mountains. The combined effect of topography and vicinity to sea also creates very distinct climate types in northern Iran. The climate maps of the three used methods reflect the joint effects of topography, latitudinal variation, and land/sea surface contrast on the climate of Iran. A pairwise comparison made between the three classifications showed a satisfactory agreement between the three schemes in representing the main climate types of Iran.


2011 ◽  
Vol 116 (D11) ◽  
Author(s):  
E. J. M. van den Besselaar ◽  
M. R. Haylock ◽  
G. van der Schrier ◽  
A. M. G. Klein Tank

Author(s):  
M. R. Haylock ◽  
N. Hofstra ◽  
A. M. G. Klein Tank ◽  
E. J. Klok ◽  
P. D. Jones ◽  
...  

2017 ◽  
Vol 38 ◽  
pp. e518-e530 ◽  
Author(s):  
R. Serrano-Notivoli ◽  
J. Martín-Vide ◽  
M. A. Saz ◽  
L. A. Longares ◽  
S. Beguería ◽  
...  

Author(s):  
D. E. Becker

An efficient, robust, and widely-applicable technique is presented for computational synthesis of high-resolution, wide-area images of a specimen from a series of overlapping partial views. This technique can also be used to combine the results of various forms of image analysis, such as segmentation, automated cell counting, deblurring, and neuron tracing, to generate representations that are equivalent to processing the large wide-area image, rather than the individual partial views. This can be a first step towards quantitation of the higher-level tissue architecture. The computational approach overcomes mechanical limitations, such as hysterisis and backlash, of microscope stages. It also automates a procedure that is currently done manually. One application is the high-resolution visualization and/or quantitation of large batches of specimens that are much wider than the field of view of the microscope.The automated montage synthesis begins by computing a concise set of landmark points for each partial view. The type of landmarks used can vary greatly depending on the images of interest. In many cases, image analysis performed on each data set can provide useful landmarks. Even when no such “natural” landmarks are available, image processing can often provide useful landmarks.


2002 ◽  
Vol 5 (3) ◽  
pp. 212-212 ◽  
Author(s):  
U. Tiede ◽  
A. Pommert ◽  
B. Pflesser ◽  
E. Richter ◽  
M. Riemer ◽  
...  

2014 ◽  
Vol 14 (20) ◽  
pp. 10963-10976 ◽  
Author(s):  
J. J. P. Kuenen ◽  
A. J. H. Visschedijk ◽  
M. Jozwicka ◽  
H. A. C. Denier van der Gon

Abstract. Emissions to air are reported by countries to EMEP. The emissions data are used for country compliance checking with EU emission ceilings and associated emission reductions. The emissions data are also necessary as input for air quality modelling. The quality of these "official" emissions varies across Europe. As alternative to these official emissions, a spatially explicit high-resolution emission inventory (7 × 7 km) for UNECE-Europe for all years between 2003 and 2009 for the main air pollutants was made. The primary goal was to supply air quality modellers with the input they need. The inventory was constructed by using the reported emission national totals by sector where the quality is sufficient. The reported data were analysed by sector in detail, and completed with alternative emission estimates as needed. This resulted in a complete emission inventory for all countries. For particulate matter, for each source emissions have been split in coarse and fine particulate matter, and further disaggregated to EC, OC, SO4, Na and other minerals using fractions based on the literature. Doing this at the most detailed sectoral level in the database implies that a consistent set was obtained across Europe. This allows better comparisons with observational data which can, through feedback, help to further identify uncertain sources and/or support emission inventory improvements for this highly uncertain pollutant. The resulting emission data set was spatially distributed consistently across all countries by using proxy parameters. Point sources were spatially distributed using the specific location of the point source. The spatial distribution for the point sources was made year-specific. The TNO-MACC_II is an update of the TNO-MACC emission data set. Major updates included the time extension towards 2009, use of the latest available reported data (including updates and corrections made until early 2012) and updates in distribution maps.


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