Search Results
Abstract
Daily synoptic observations were examined to determine the critical air temperatures and dewpoints that separate solid versus liquid precipitation for the fall and spring seasons at 547 stations over northern Eurasia. The authors found that critical air temperatures are highly geographically dependent, ranging from −1.0° to 2.5°C, with the majority of stations over European Russia ranging from 0.5° to 1.0°C and those over south-central Siberia ranging from 1.5° to 2.5°C. The fall season has a 0.5°–1.0°C lower value than the spring season at 42% stations. Relative humidity, elevation, the station's air pressure, and climate regime were found to have varying degrees of influences on the distribution of critical air temperature, although the relationships are very complex and cannot be formulated into a simple rule that can be applied universally. Although the critical dewpoint temperatures have a spread of −1.5° to 1.5°C, 92% of stations have critical values of 0.5°–1.0°C. The critical dewpoint is less dependent on environmental factors and seasons. A combination of three critical dewpoints and three air temperatures is developed for each station for spring and fall separately that has improved snow event predictability when the dewpoint is in the range of −0.5°–1.5°C and has improved rainfall event predictability when the dewpoint is higher than or equal to 0°C based on the statistics of all 537 stations. Results suggest that application of site-specific critical values of air temperature and dewpoint to discriminate between solid and liquid precipitation is needed to improve snow and hydrological modeling at local and regional scales.
Abstract
Daily synoptic observations were examined to determine the critical air temperatures and dewpoints that separate solid versus liquid precipitation for the fall and spring seasons at 547 stations over northern Eurasia. The authors found that critical air temperatures are highly geographically dependent, ranging from −1.0° to 2.5°C, with the majority of stations over European Russia ranging from 0.5° to 1.0°C and those over south-central Siberia ranging from 1.5° to 2.5°C. The fall season has a 0.5°–1.0°C lower value than the spring season at 42% stations. Relative humidity, elevation, the station's air pressure, and climate regime were found to have varying degrees of influences on the distribution of critical air temperature, although the relationships are very complex and cannot be formulated into a simple rule that can be applied universally. Although the critical dewpoint temperatures have a spread of −1.5° to 1.5°C, 92% of stations have critical values of 0.5°–1.0°C. The critical dewpoint is less dependent on environmental factors and seasons. A combination of three critical dewpoints and three air temperatures is developed for each station for spring and fall separately that has improved snow event predictability when the dewpoint is in the range of −0.5°–1.5°C and has improved rainfall event predictability when the dewpoint is higher than or equal to 0°C based on the statistics of all 537 stations. Results suggest that application of site-specific critical values of air temperature and dewpoint to discriminate between solid and liquid precipitation is needed to improve snow and hydrological modeling at local and regional scales.
Abstract
The influences of surface climate conditions and atmospheric circulation on seasonal river discharges of the Ob, Yenisei, and Lena River basins during 1936–95 have been examined and quantified. Climatic variables include seasonal basin-averaged surface air temperatures, precipitation, maximum snow accumulation depth, and starting and ending dates of the basins' continuous snow cover. Atmospheric circulation is represented by the Northern Hemisphere annular mode (NAM) index. The combinations of these climatic and atmospheric variables explain about 31% to 55% of the variance of the annual total discharges of these rivers. On average, climatic and atmospheric variables explain 35% to 69% variance of spring discharges, 34% to 47% variance of summer discharges, 21% to 50% variance of fall discharges, and 18% to 36% variance of winter discharges. This study reveals that the spring thermal condition is most significant for spring discharge and negatively affects summer discharge. Climatic conditions during the previous winter through fall influence fall discharges, while the atmospheric conditions of the previous summer and fall affect winter discharges. Also, winter snow accumulation influences summer and fall discharges of the Ob and Yenisei Rivers but affects winter and spring discharges of the Lena River, suggesting the importance of topography and permafrost conditions to river discharges over high-latitude regions.
Abstract
The influences of surface climate conditions and atmospheric circulation on seasonal river discharges of the Ob, Yenisei, and Lena River basins during 1936–95 have been examined and quantified. Climatic variables include seasonal basin-averaged surface air temperatures, precipitation, maximum snow accumulation depth, and starting and ending dates of the basins' continuous snow cover. Atmospheric circulation is represented by the Northern Hemisphere annular mode (NAM) index. The combinations of these climatic and atmospheric variables explain about 31% to 55% of the variance of the annual total discharges of these rivers. On average, climatic and atmospheric variables explain 35% to 69% variance of spring discharges, 34% to 47% variance of summer discharges, 21% to 50% variance of fall discharges, and 18% to 36% variance of winter discharges. This study reveals that the spring thermal condition is most significant for spring discharge and negatively affects summer discharge. Climatic conditions during the previous winter through fall influence fall discharges, while the atmospheric conditions of the previous summer and fall affect winter discharges. Also, winter snow accumulation influences summer and fall discharges of the Ob and Yenisei Rivers but affects winter and spring discharges of the Lena River, suggesting the importance of topography and permafrost conditions to river discharges over high-latitude regions.
Abstract
Atmospheric rivers (ARs) are long and narrow regions of strong horizontal water vapor transport. Upon landfall, ARs are typically associated with heavy precipitation and strong surface winds. A quantitative understanding of the atmospheric conditions that favor extreme surface winds during ARs has implications for anticipating and managing various impacts associated with these potentially hazardous events. Here, a global AR database (1999–2014) with relevant information from MERRA-2 reanalysis, QuikSCAT, and AIRS satellite observations is used to better understand and quantify the role of near-surface static stability in modulating surface winds during landfalling ARs. The temperature difference between the surface and 1 km MSL (ΔT; used here as a proxy for near-surface static stability), along with integrated water vapor transport (IVT), is analyzed to quantify their relationships to surface winds using bivariate linear regression. In four regions where AR landfalls are common, the MERRA-2-based results indicate that IVT accounts for 22%–38% of the variance in surface wind speed. Combining ΔT with IVT increases the explained variance to 36%–52%. Substitution of QuikSCAT surface winds and AIRS ΔT in place of the MERRA-2 data largely preserves this relationship (e.g., 44% as compared with 52% explained variance for U.S. West Coast). Use of an alternate static stability measure—the bulk Richardson number—yields a similar explained variance (47%). Last, AR cases within the top and bottom 25% of near-surface static stability indicate that extreme surface winds (gale or higher) are more likely to occur in unstable conditions (5.3% and 14.7% during weak and strong IVT, respectively) than in stable conditions (0.58% and 6.15%).
Abstract
Atmospheric rivers (ARs) are long and narrow regions of strong horizontal water vapor transport. Upon landfall, ARs are typically associated with heavy precipitation and strong surface winds. A quantitative understanding of the atmospheric conditions that favor extreme surface winds during ARs has implications for anticipating and managing various impacts associated with these potentially hazardous events. Here, a global AR database (1999–2014) with relevant information from MERRA-2 reanalysis, QuikSCAT, and AIRS satellite observations is used to better understand and quantify the role of near-surface static stability in modulating surface winds during landfalling ARs. The temperature difference between the surface and 1 km MSL (ΔT; used here as a proxy for near-surface static stability), along with integrated water vapor transport (IVT), is analyzed to quantify their relationships to surface winds using bivariate linear regression. In four regions where AR landfalls are common, the MERRA-2-based results indicate that IVT accounts for 22%–38% of the variance in surface wind speed. Combining ΔT with IVT increases the explained variance to 36%–52%. Substitution of QuikSCAT surface winds and AIRS ΔT in place of the MERRA-2 data largely preserves this relationship (e.g., 44% as compared with 52% explained variance for U.S. West Coast). Use of an alternate static stability measure—the bulk Richardson number—yields a similar explained variance (47%). Last, AR cases within the top and bottom 25% of near-surface static stability indicate that extreme surface winds (gale or higher) are more likely to occur in unstable conditions (5.3% and 14.7% during weak and strong IVT, respectively) than in stable conditions (0.58% and 6.15%).
