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[en] The Tibetan Plateau (TP), with an average elevation of over 4000 m asl and an area of approximately 2.5 x 106 km2, is the highest and most extensive highland in the world and has been called the 'Third Pole'. The TP exerts a huge influence on regional and global climate through thermal and mechanical forcing mechanisms. Because the TP has the largest cryospheric extent outside the polar region and is the source region of all the large rivers in Asia, it is widely recognized to be the driving force for both regional environmental change and amplification of environmental changes on a global scale. Within China it is recognized as the 'Asian water tower'. In this letter, we summarize the recent changes observed in climate elements and cryospheric indicators on the plateau before discussing current unresolved issues concerning climate change in the TP, including the temporal and spatial components of this change, and the consistency of change as represented by different data sources. Based on meteorological station data, reanalyses and remote sensing, the TP has shown significant warming during the last decades and will continue to warm in the future. While the warming is predominantly caused by increased greenhouse gas emissions, changes in cloud amount, snow-albedo feedback, the Asian brown clouds and land use changes also partly contribute. The cryosphere in the TP is undergoing rapid change, including glacier retreat, inconsistent snow cover change, increasing permafrost temperatures and degradation, and thickening of the active layer. Hydrological processes impacted by glacial retreat have received much attention in recent years. Future attention should be paid to additional perspectives on climate change in the TP, such as the variations of climate extremes, the reliability of reanalyses and more detailed comparisons of reanalyses with surface observations. Spatial issues include the identification of whether an elevational dependency and weekend effect exist, and the identification of spatial contrasts in temperature change, along with their causes. These issues are uncertain because of a lack of reliable data above 5000 m asl.
[en] The duration and extent of snow cover is expected to change rapidly with climate change. Therefore, there is a need for improved monitoring of snow for the benefit of forecasting, impact assessments and the population at large. Remotely sensed techniques prove useful for remote areas where there are few field-based monitoring stations. This paper reports on a study of snow season using snow cover area fraction data from the two northernmost counties in Norway, Troms and Finnmark. The data are derived from the daily 500 m standard snow product (MOD10A1) from the NASA Terra MODerate Resolution Imaging Spectroradiometer (MODIS) sensor for the 2000–2010 period. This dataset has been processed with multi-temporal interpolation to eliminate clouds. The resulting cloud-free daily time series of snow cover fraction maps, have subsequently been used to derive the first and last snow-free day for the entire study area. In spring, the correlation between the first snow-free day mapped by MODIS data and snow data from 40 meteorological stations was highly significant ( p < 0.05) for 36 of the stations, and with a of bias of less than 10 days for 34 of the stations. In autumn, 31 of the stations show highly significant ( p < 0.05) correlation with MODIS data, and the bias was less than 10 days for 27 of the stations. However, in some areas and some years, the start and end of the snow season could not be detected due to long overcast periods. In spring 2002 and 2004 the first snow-free day was early, but arrived late in 2000, 2005 and 2008. In autumn 2009 snowfall arrived more than 7 days earlier in 50% of the study area as compared to the 2000–2010 average. MODIS-based snow season products will be applicable for a wide range of sectors including hydrology, nature-based industries, climate change studies and ecology. Therefore refinement and further testing of this method should be encouraged. (letter)
[en] The question whether to walk slowly or to run when it starts raining in order to stay as dry as possible has been considered for many years-and with different results, depending on the assumptions made and the mathematical descriptions for the situation. Because of the practical meaning for real life and the inconsistent results depending on the chosen parameters, this problem is well suited to undergraduate students learning to decide which parameters are important and choosing reasonable values to describe a physical problem. Dealing with physical parameters is still useful at university level, as students do not always recognize the connection between pure numbers and their qualitative and quantitative influence on a physical problem. This paper presents an intuitive approach which offers the additional advantage of being more detailed, allowing for more parameters to be tested than the simple models proposed in most other publications.
[en] In this paper we propose for the first time a multiplicative continuous model for generating multifractal fields with zero values, as a continuous generalization of the intermittent lognormal β -model proposed by Over and Gupta (1996). It is built using infinitely multiplicative random variables, the multiplicative analog to infinitely divisible distributions for addition. The model also needs stochastic multiplicative measures and multiplicative stochastic integrals. It possesses as a special case a continuous generalization of the classical discrete β -model. Applications are numerous in many fields of applied science, including small-scale rainfall and soil science. (paper)
[en] Using rain gauge and satellite-based rainfall climatologies and the NOAA Storm Prediction Center tornado database (1952-2007), this study found a statistically significant tendency for fall-winter drought conditions to be correlated with below-normal tornado days the following spring in north Georgia (i.e. 93% of the years) and other regions of the Southeast. Non-drought years had nearly twice as many tornado days in the study area as drought years and were also five to six times more likely to have multiple tornado days. Individual tornadic events are largely a function of the convective-mesoscale thermodynamic and dynamic environments, thus the study does not attempt to overstate predictability. Yet, the results may provide seasonal guidance in an analogous manner to the well known Sahelian rainfall and Cape Verde hurricane activity relationships.
[en] The Hindu Kush-Himalayan (HKH) region holds the largest mass of ice in Central Asia and is highly vulnerable to global climate change, experiencing significant warming (0.21 ± 0.08 deg. C/decade) over the past few decades. Accurate monitoring of the timing and duration of snowmelt across the HKH region is important, as this region is expected to experience further warming in response to increased greenhouse gas forcing. Despite the many advantages and applications of satellite-derived radar scatterometer data shown for capturing ice and snow melt dynamics at high latitudes, similar comprehensive freeze/thaw detection studies at lower latitudes (including the HKH region) are still absent from the scientific literature. A comprehensive freeze/thaw detection study is utilized on perennial snow/ice and seasonal snow cover for the first time in the Himalayan and Karakoram regions. A dynamic threshold-based method is applied to enhanced QuikSCAT Ku-band backscatter observations from 2000 to 2008 that (a) provides spatial maps of the timing of melt, freeze, and melt season duration, and (b) emphasizes regional variability in freeze/thaw dynamics. The resulting average melt durations for 2000-2008 are 161 ± 11 days (early May-mid-October) for the eastern Himalayas, 130 ± 16 days (late May-early October) for the central Himalayas, 124 ± 13 days (mid-May-mid-September) for the western Himalayas, and 124 ± 12 days (late May-late September) for the Karakoram region. The eastern Himalayan region has on average an earlier melt onset, a later freeze-up, and therefore a longer melt season (∼5 weeks) relative to the central and western Himalayan and the Karakoram regions. Snowmelt dynamics exhibit regional and interannual variability with clear connections to terrain features, in particular elevation and aspect. With respect to ongoing controversies surrounding melt in the Himalayan region, this study provides an overall perspective of regional differences in melt onset, freeze-up, and melt duration that have important implications for glaciological and hydrological processes across the HKH region.