Using more than 14 years of GRACE(Gravity Recovery and Climate Experiment) satellite gravimetry observations, we estimate the ice loss rate for the Patagonia Ice Field(PIF) of South America. After correcting the effec...Using more than 14 years of GRACE(Gravity Recovery and Climate Experiment) satellite gravimetry observations, we estimate the ice loss rate for the Patagonia Ice Field(PIF) of South America. After correcting the effects of glacier isostatic adjustment(GIA) and hydrological variations, the ice loss rate is -23.5 ± 8.1 Giga ton per year(Gt/yr) during the period April 2002 through December 2016, equivalent to an average ice thickness change of-1.3 m/yr if evenly distributed over PIF. The PIF ice mass change series also show obvious inter-annual variations during the entire period. For the time spans April 2002 to December 2007, January 2008 to December 2012 and January 2013 to December 2016, the ice loss rates are -26.4,-9.0 and -25.0 Gt/yr, respectively, indicating that the ice melting experienced significant slowing down and accelerating again in the past decade. Comparison with time series from temperature and precipitation data over PIF suggests that the inter-annual ice losses might not be directly correlated with the temperature changes and precipitation anomalies, and thus their interrelation is intricate. However, the dramatic ice loss acceleration in 2016(with more than 100 Gt within the first half of the year) appears closely related with the evident temperature increase and severe precipitation shortage over 2016, which are likely correlated with the strong E1 Nino event around 2016. Moreover, we compare the GRACE spherical harmonic(SH) and mass concentration(Mascon) solutions in estimating the PIF ice loss rate, and find that the Mascon result has larger uncertainty in leakage error correction,while the SH solutions can better correct leakage errors based on a constrained forward modeling iterative method. Thus the GRACE SH solutions with constrained forward modeling recovery are recommended to evaluating the ice mass change of PIF or other glacier regions with relatively smaller spatial scales.展开更多
The regional Weather and Research Forecast (WRF) Model was run for the 2000-2010 period over the Northern Patagonia Icefield (NPI) with an horizontal resolution of 5 km. The regional model was initialized using the NC...The regional Weather and Research Forecast (WRF) Model was run for the 2000-2010 period over the Northern Patagonia Icefield (NPI) with an horizontal resolution of 5 km. The regional model was initialized using the NCEP/NCAR atmospheric Reanalysis database. The simulation results, centered over the NPI, were validated against the observed data from the local surface stations in order to evaluate the improvement of the model results due to its increased horizontal resolution with respect to the lower resolution from Global Climate Model simulations. Interest in the NPI is due to 1) the large body of frozen water exposed to the impact of the warming planet, 2) the scarce availability of observed meteorological and glaciological information in this large and remote icefield, and 3) the need to validate the model behavior in simulating the current climate and its variability in complex terrain. The results will shed light on the degree of confidence in simulating future climate scenarios in the region and also in similar geographical settings. Based on this study subsequent model runs will allow to model future climate changes in Patagonia, which is basic information for estimating glacier variations to be expected during this century.展开更多
Atmospheric and oceanic drag are the main environmental forces controlling sea ice drift. Oceanic drag includes the form drag generated by water pressure gradients on the side of ice floes or on ice ridges, and the sk...Atmospheric and oceanic drag are the main environmental forces controlling sea ice drift. Oceanic drag includes the form drag generated by water pressure gradients on the side of ice floes or on ice ridges, and the skin friction generated by viscous flow on the bottom of ice floes. In this study, we carried out a two-dimensional numerical simulation using FLUENT software to investigate the characteristics of dynamic flow under ice with a smooth undersurface. We studied water drag and flow field distribution below the ice under different conditions of ice draft and flow velocity, and the results agreed well with data from laboratory-based physical modeling tests, demonstrating the ability of the numerical model to reproduce the dynamic interactions between sea ice and the flow field. The degree of distortion in the flow field caused by ice increased as the ice draft increased. Vortexes occurred in the wake field of the floe, and the centers of the vortexes moved away from the ice with increasing ice draft. The simulated drag of water on ice showed a clear linear relationship with the square of the flow velocity.展开更多
基金supported by the Natural Science Foundation of Shanghai (17ZR1435600)the Open Fund of Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University (16-01-05)the National Key Research and Development Program of China (2016YFB0501405)
文摘Using more than 14 years of GRACE(Gravity Recovery and Climate Experiment) satellite gravimetry observations, we estimate the ice loss rate for the Patagonia Ice Field(PIF) of South America. After correcting the effects of glacier isostatic adjustment(GIA) and hydrological variations, the ice loss rate is -23.5 ± 8.1 Giga ton per year(Gt/yr) during the period April 2002 through December 2016, equivalent to an average ice thickness change of-1.3 m/yr if evenly distributed over PIF. The PIF ice mass change series also show obvious inter-annual variations during the entire period. For the time spans April 2002 to December 2007, January 2008 to December 2012 and January 2013 to December 2016, the ice loss rates are -26.4,-9.0 and -25.0 Gt/yr, respectively, indicating that the ice melting experienced significant slowing down and accelerating again in the past decade. Comparison with time series from temperature and precipitation data over PIF suggests that the inter-annual ice losses might not be directly correlated with the temperature changes and precipitation anomalies, and thus their interrelation is intricate. However, the dramatic ice loss acceleration in 2016(with more than 100 Gt within the first half of the year) appears closely related with the evident temperature increase and severe precipitation shortage over 2016, which are likely correlated with the strong E1 Nino event around 2016. Moreover, we compare the GRACE spherical harmonic(SH) and mass concentration(Mascon) solutions in estimating the PIF ice loss rate, and find that the Mascon result has larger uncertainty in leakage error correction,while the SH solutions can better correct leakage errors based on a constrained forward modeling iterative method. Thus the GRACE SH solutions with constrained forward modeling recovery are recommended to evaluating the ice mass change of PIF or other glacier regions with relatively smaller spatial scales.
文摘The regional Weather and Research Forecast (WRF) Model was run for the 2000-2010 period over the Northern Patagonia Icefield (NPI) with an horizontal resolution of 5 km. The regional model was initialized using the NCEP/NCAR atmospheric Reanalysis database. The simulation results, centered over the NPI, were validated against the observed data from the local surface stations in order to evaluate the improvement of the model results due to its increased horizontal resolution with respect to the lower resolution from Global Climate Model simulations. Interest in the NPI is due to 1) the large body of frozen water exposed to the impact of the warming planet, 2) the scarce availability of observed meteorological and glaciological information in this large and remote icefield, and 3) the need to validate the model behavior in simulating the current climate and its variability in complex terrain. The results will shed light on the degree of confidence in simulating future climate scenarios in the region and also in similar geographical settings. Based on this study subsequent model runs will allow to model future climate changes in Patagonia, which is basic information for estimating glacier variations to be expected during this century.
基金supported by the National Natural Science Foundation of China(Grant nos.41276191 and 40930848)
文摘Atmospheric and oceanic drag are the main environmental forces controlling sea ice drift. Oceanic drag includes the form drag generated by water pressure gradients on the side of ice floes or on ice ridges, and the skin friction generated by viscous flow on the bottom of ice floes. In this study, we carried out a two-dimensional numerical simulation using FLUENT software to investigate the characteristics of dynamic flow under ice with a smooth undersurface. We studied water drag and flow field distribution below the ice under different conditions of ice draft and flow velocity, and the results agreed well with data from laboratory-based physical modeling tests, demonstrating the ability of the numerical model to reproduce the dynamic interactions between sea ice and the flow field. The degree of distortion in the flow field caused by ice increased as the ice draft increased. Vortexes occurred in the wake field of the floe, and the centers of the vortexes moved away from the ice with increasing ice draft. The simulated drag of water on ice showed a clear linear relationship with the square of the flow velocity.