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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] 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.
[en] Deciduous shrub abundance is increasing across the Arctic in response to climatic warming. In a recent field manipulation experiment in which shrubs were removed from a plot and compared to a control plot with shrubs, Blok et al (2010 Glob. Change Biol. 16 1296–305) found that shrubs protect the ground through shading, resulting in a ∼ 9% shallower active layer thickness (ALT) under shrubs compared to grassy-tundra, which led them to argue that continued Arctic shrub expansion could mitigate future permafrost thaw. We utilize the Community Land Model (CLM4) coupled to the Community Atmosphere Model (CAM4) to evaluate this hypothesis. CLM4 simulates shallower ALT (∼− 11 cm) under shrubs, consistent with the field manipulation study. However, in an idealized pan-Arctic + 20% shrub area experiment, atmospheric heating, driven mainly by surface albedo changes related to protrusion of shrub stems above the spring snowpack, leads to soil warming and deeper ALT (∼+ 10 cm). Therefore, if climate feedbacks are considered, shrub expansion may actually increase rather than decrease permafrost vulnerability. When we account for blowing-snow redistribution from grassy-tundra to shrubs, shifts in snowpack distribution in low versus high shrub area simulations counter the climate warming impact, resulting in a grid cell mean ALT that is unchanged. These results reinforce the need to consider vegetation dynamics and blowing-snow processes in the permafrost thaw model projections.
[en] Sparse gauge networks in Sub-Saharan Africa (SSA) limit our ability to identify changing precipitation extremes with in situ observations. Given the potential for satellite and satellite-gauge precipitation products to help, we investigate how daily gridded gauge and satellite products compare for seven core climate change precipitation indices. According to a new gauge-only product, the Rainfall Estimates on a Gridded Network (REGEN), there were notable changes in SSA precipitation characteristics between 1950 and 2013 in well-gauged areas. We examine these trends and how these vary for wet, intermediate, and dry areas. For a 31 year period of overlap, we compare REGEN data, other gridded products and three satellite products. Then for 1998–2013, we compare a set of 12 satellite products. Finally, we compare spatial patterns of 1983–2013 trends across all of SSA. Robust 1950–2013 trends indicate that in well-gauged areas extreme events became wetter, particularly in wet areas. Annual totals decreased due to fewer rain days. Between 1983 and 2013 there were positive trends in average precipitation intensity and annual maximum 1 d totals. These trends only represent 15% of SSA, however, and only one tenth of the main wet areas. Unfortunately, gauge and satellite products do not provide consensus for wet area trends. A promising result for identifying regional changes is that numerous satellite products do well at interannual variations in precipitation totals and number of rain days, even as well as some gauge-only products. Products are less accurate for dry spell length and average intensity and least accurate for annual maximum 1 d totals. Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (3B42-V7) and Climate Hazards center Infrared Precipitation with Stations (CHIRPS v2.0) ranked highest for multiple indices. Several products have seemingly unrealistic trends outside of the well-gauged areas that may be due to influence of non-stationary systematic biases. Social media abstract. Sparse data show increasing Africa rainfall extremes and satellite products fill some missing pieces. (letter)
[en] Washington State experienced widespread drought in 2015 and the largest burned area in the observational record, attributable in part to exceptionally low winter snow accumulation and high summer temperatures. We examine 2015 drought severity in the Cascade and Olympic mountains relative to the historical climatology (1950–present) and future climate projections (mid-21st century) for a mid-range global greenhouse gas emissions scenario. Although winter precipitation was near normal, the regional winter temperature anomaly was +2.1 °C (+2.0σ) in 2015, consistent with projections of a +2.3 °C (+2.2σ) temperature change and near normal precipitation in the future, relative to the climatology. April 1 snow water equivalent in 2015, −325 mm (−1.5σ), and the future, −252 mm (−1.1σ), were substantially lower than the climatology. Wildfire potential, as indicated by dead fuel moisture content, was higher in 2015 than mid-21st century mean projections. In contrast to most historical droughts, which have been driven by precipitation deficits, our results suggest that 2015 is a useful analog of typical conditions in the Pacific Northwest by the mid-21st century. (letter)
[en] At present 4 of 10 dedicated rainfall observing satellite systems have exceeded their design life, some by more than a decade. Here, we show operational implications for flood management of a ‘collapse’ of space-based rainfall observing infrastructure as well as the high-value opportunities for a globally coordinated portfolio of satellite missions and data services. Results show that the current portfolio of rainfall missions fails to meet operational data needs for flood management, even when assuming a perfectly coordinated data product from all current rainfall-focused missions (i.e., the full portfolio). In the full portfolio, satellite-based rainfall data deficits vary across the globe and may preclude climate adaptation in locations vulnerable to increasing flood risks. Moreover, removing satellites that are currently beyond their design life (i.e., the reduced portfolio) dramatically increases data deficits globally and could cause entire high intensity flood events to be unobserved. Recovery from the reduced portfolio is possible with internationally coordinated replenishment of as few as 2 of the 4 satellite systems beyond their design life, yielding rainfall data coverages that outperform the current full portfolio (i.e., an optimized portfolio of eight satellites can outperform ten satellites). This work demonstrates the potential for internationally coordinated satellite replenishment and data services to substantially enhance the cost-effectiveness, sustainability and operational value of space-based rainfall observations in managing evolving flood risks. (letter)
[en] Climate models project considerable ranges and uncertainties in future climatic changes. To assess the potential impacts of climatic changes on mountain permafrost within these ranges of uncertainty, this study presents a sensitivity analysis using a permafrost process model combined with climate input based on delta-change approaches. Delta values comprise a multitude of coupled air temperature and precipitation changes to analyse long-term, seasonal and seasonal extreme changes on a typical low-ice content mountain permafrost location in the Swiss Alps. The results show that seasonal changes in autumn (SON) have the largest impact on the near-surface permafrost thermal regime in the model, and lowest impacts in winter (DJF). For most of the variability, snow cover duration and timing are the most important factors, whereas maximum snow height only plays a secondary role unless maximum snow heights are very small. At least for the low-ice content site of this study, extreme events have only short-term effects and have less impact on permafrost than long-term air temperature trends. (letter)
[en] An analysis is made of changes in basal ice crust layer characteristics from snow cover surveys made at 958 Russian stations since 1966. The analysis revealed that substantial changes have occurred in response to two competing processes: an increase in thaws associated with strong regional warming and an increase in the duration of the basal ice layer presence on the ground, and a shortening of the snowmelt period associated with a decrease in basal ice layer event frequency and severity. The latter appears to be the more significant process over the past 40 years. Our findings support the notion that the entire spring snowmelt process has become shorter in duration and more intense when taking into account a concomitant trend toward increasing snow depths over large regions of Russia. A more intense spring melt period has important consequences for spring flood dynamics and deserves further study.