A snow depth of 370 cm at Dunderlandsdalen in winter 1919–20 is the largest recorded at stations in Nordland, Norway. During the period 1895–1924, the average maximum annual value there was 150.4 cm; at other stations it ranged from 38.5 to 190.1 cm. The ratio of maxima at other stations to that at Dunderlandsdalen was particularly low in 1919–20. In Nordland generally, that winter's recorded precipitation was slightly above the 30‐year average, but at Dunderlandsdalen it exceeded the average by 34%. At all stations except Dunderlandsdalen, 26 Jan.–1 Feb. was a dry period; at Dunderlandsdalen, 51.7 mm was recorded. Only one day without snowfall was recorded at Dunderlandsdalen between early January and early February, but elsewhere there were few days with snowfall. The difference in snowfall frequency and snow depth at Dunderlandsdalen in 1919–20 from values recorded elsewhere in Nordland contrasts with the relationships in other winters between 1895 and 1924. No observations were made at Dunderlandsdalen in winter 1917–18. Two of the householders there died in 1916. A change of personnel making the observations may have been responsible for the data gap and for the anomalous 1919 data. Changes made to buildings or the recording site in 1917 or 1918 may have resulted in increased snow depths as a result of drifting. Maintaining a record of climatic extremes and their environmental consequences is important. Data must be accurate. In view of this, it would be sensible to regard the validity of the 370 cm Dunderlandsdalen maximum as doubtful. 相似文献
The sea ice cover in the Arctic Ocean has been reducing and hit the low record in the summer of 2007. The anomaly was extremely large in the Pacific sector. The sea level height in the Bering Sea vs. the Greenland Sea has been analyzed and compared with the current meter data through the Bering Strait. A recent peak existed as a consequence of atmospheric circulation and is considered to contribute to inflow of the Pacific Water into the Arctic Basin. The timing of the Pacific Water inflow matched with the sea ice reduction in the Pacific sector and suggests a significant increase in heat flux. This component should be included in the model prediction for answering the question when the Arctic sea ice becomes a seasonal ice cover. 相似文献
We analyzed the spatial local accuracy of land cover (LC) datasets for the Qiangtang Plateau, High Asia, incorporating 923 field sampling points and seven LC compilations including the International Geosphere Biosphere Programme Data and Information System (IGBPDIS), Global Land cover mapping at 30 m resolution (GlobeLand30), MODIS Land Cover Type product (MCD12Q1), Climate Change Initiative Land Cover (CCI-LC), Global Land Cover 2000 (GLC2000), University of Maryland (UMD), and GlobCover 2009 (Glob-Cover). We initially compared resultant similarities and differences in both area and spatial patterns and analyzed inherent relationships with data sources. We then applied a geographically weighted regression (GWR) approach to predict local accuracy variation. The results of this study reveal that distinct differences, even inverse time series trends, in LC data between CCI-LC and MCD12Q1 were present between 2001 and 2015, with the exception of category areal discordance between the seven datasets. We also show a series of evident discrepancies amongst the LC datasets sampled here in terms of spatial patterns, that is, high spatial congruence is mainly seen in the homogeneous southeastern region of the study area while a low degree of spatial congruence is widely distributed across heterogeneous northwestern and northeastern regions. The overall combined spatial accuracy of the seven LC datasets considered here is less than 70%, and the GlobeLand30 and CCI-LC datasets exhibit higher local accuracy than their counterparts, yielding maximum overall accuracy (OA) values of 77.39% and 61.43%, respectively. Finally, 5.63% of this area is characterized by both high assessment and accuracy (HH) values, mainly located in central and eastern regions of the Qiangtang Plateau, while most low accuracy regions are found in northern, northeastern, and western regions.
Analysis of the nexus between vegetation dynamics and climatic parameters like surface temperature is essential in environmental and ecological studies and for monitoring of the natural resources. This study explored the spatio-temporal distribution of land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) and the relationship between them in the Andassa watershed from 1986 to 2016 periods using Landsat data. Monthly average air temperature data of three meteorological sites were used for validating the results. The findings of the study showed that the LST of the Andassa watershed has increased during the study periods. Overall, average LST has been rising with an increasing rate of 0.081°C per year. Other results of this study also showed that there has been a dynamic change in vegetation cover of the watershed in all seasons. There was also a negative correlation between LST and NDVI in all the studied years. From this study we can understand that there has been degradation of vegetation and intensification of LST from 1986 to 2016. 相似文献