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- Author or Editor: Wenkai Li x
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Abstract
Accurate subseasonal forecasts for snow cover have significant socioeconomic value. This paper evaluates subseasonal forecasts for winter snow cover in the Northern Hemisphere as predicted by three numerical models: the Model for Prediction Across Scales – Atmosphere (MPAS), the China Meteorological Administration (CMA) model, and the European Centre for Medium-Range Weather Forecasts (ECMWF) model. While these models can generally simulate the spatial distribution of winter snow cover climatology and subseasonal variability, they tend to underestimate both the climatology and the intensity of subseasonal variability. Compared to persistence forecasts, these models demonstrate skill in subseasonal snow cover forecasting. Notably, the ECMWF model outperforms the MPAS and CMA models. The sensitivity of the surface air temperature subseasonal forecast skill to the predicted snow cover was also investigated using the MPAS. The results show that for forecasts with lead times of 1 to 2 weeks, the predicted snow cover contributes to the temperature forecasting skill. However, for forecasts with lead times of 3 to 4 weeks, the predicted snow cover does not enhance the temperature forecasting skill. Furthermore, part of the errors in temperature forecasts can be attributed to inaccuracies in snow cover forecasts with lead times of 2 weeks or more. These findings suggest that refining snow cover parameterization schemes and effectively exploiting predictability from snow cover can enhance the skill of subseasonal atmospheric forecasts.
Abstract
Accurate subseasonal forecasts for snow cover have significant socioeconomic value. This paper evaluates subseasonal forecasts for winter snow cover in the Northern Hemisphere as predicted by three numerical models: the Model for Prediction Across Scales – Atmosphere (MPAS), the China Meteorological Administration (CMA) model, and the European Centre for Medium-Range Weather Forecasts (ECMWF) model. While these models can generally simulate the spatial distribution of winter snow cover climatology and subseasonal variability, they tend to underestimate both the climatology and the intensity of subseasonal variability. Compared to persistence forecasts, these models demonstrate skill in subseasonal snow cover forecasting. Notably, the ECMWF model outperforms the MPAS and CMA models. The sensitivity of the surface air temperature subseasonal forecast skill to the predicted snow cover was also investigated using the MPAS. The results show that for forecasts with lead times of 1 to 2 weeks, the predicted snow cover contributes to the temperature forecasting skill. However, for forecasts with lead times of 3 to 4 weeks, the predicted snow cover does not enhance the temperature forecasting skill. Furthermore, part of the errors in temperature forecasts can be attributed to inaccuracies in snow cover forecasts with lead times of 2 weeks or more. These findings suggest that refining snow cover parameterization schemes and effectively exploiting predictability from snow cover can enhance the skill of subseasonal atmospheric forecasts.
Abstract
The Tibetan Plateau snow cover exhibits notable subseasonal variability and plays a crucial role in influencing the atmosphere. This study employs numerical experiments to investigate the atmospheric feedback resulting from extreme anomalous snow cover events on the Tibetan Plateau, with a focus on both local and nonlocal atmospheric temperatures. The findings reveal that diabatic heating, directly induced by these events, leads to a local surface energy cooling response over the Tibetan Plateau, contributing to a reduction in local temperatures. This cooling effect amplifies local atmospheric temperature anomalies associated with extreme anomalous Tibetan Plateau snow cover events, constituting approximately 50% of the total final local surface air temperature anomalies. Furthermore, the Tibetan Plateau snow cover, through adiabatic processes, exerts a nonlocal influence on atmospheric temperature and circulation. The atmospheric temperature responses downstream of the Tibetan Plateau vary at different heights and regions, featuring both cold and warm anomaly responses. These variations depend on the relative contributions of horizontal advection and vertical advection in adiabatic heating.
Significance Statement
Snow cover is influenced by the atmosphere, and in turn, it affects the atmosphere. This study examines the feedback of extreme anomalous Tibetan Plateau snow cover events on the atmosphere at the subseasonal time scale, with a focus on atmospheric temperature. Our findings indicate that Tibetan Plateau snow cover has both local and nonlocal feedback effects on the atmosphere. In particular, extreme anomalous Tibetan Plateau snow cover amplifies local surface air temperature anomalies. The feedback contributes to approximately 50% of the total final local surface air temperature anomalies.
Abstract
The Tibetan Plateau snow cover exhibits notable subseasonal variability and plays a crucial role in influencing the atmosphere. This study employs numerical experiments to investigate the atmospheric feedback resulting from extreme anomalous snow cover events on the Tibetan Plateau, with a focus on both local and nonlocal atmospheric temperatures. The findings reveal that diabatic heating, directly induced by these events, leads to a local surface energy cooling response over the Tibetan Plateau, contributing to a reduction in local temperatures. This cooling effect amplifies local atmospheric temperature anomalies associated with extreme anomalous Tibetan Plateau snow cover events, constituting approximately 50% of the total final local surface air temperature anomalies. Furthermore, the Tibetan Plateau snow cover, through adiabatic processes, exerts a nonlocal influence on atmospheric temperature and circulation. The atmospheric temperature responses downstream of the Tibetan Plateau vary at different heights and regions, featuring both cold and warm anomaly responses. These variations depend on the relative contributions of horizontal advection and vertical advection in adiabatic heating.
Significance Statement
Snow cover is influenced by the atmosphere, and in turn, it affects the atmosphere. This study examines the feedback of extreme anomalous Tibetan Plateau snow cover events on the atmosphere at the subseasonal time scale, with a focus on atmospheric temperature. Our findings indicate that Tibetan Plateau snow cover has both local and nonlocal feedback effects on the atmosphere. In particular, extreme anomalous Tibetan Plateau snow cover amplifies local surface air temperature anomalies. The feedback contributes to approximately 50% of the total final local surface air temperature anomalies.
Abstract
Superimposed on a warming trend, Arctic winter surface air temperature (SAT) exhibits substantial interannual variability, the underlying mechanisms of which are unclear, especially with regard to the role of sea ice variations and atmospheric processes. Here, atmospheric reanalysis data and idealized atmospheric model simulations are used to reveal the mechanisms by which sea ice variations and atmospheric anomalous conditions affect interannual variations in wintertime Arctic SAT. Results show that near-surface interannual warming in the Arctic is accompanied by comparable warming throughout large parts of the Arctic troposphere and large-scale anomalous atmospheric circulation patterns. Within the Arctic, changes in large-scale atmospheric circulations due to internal atmospheric variability explain a substantial fraction of interannual variation in SAT and tropospheric temperatures, which lead to an increase in moisture and downward longwave radiation, with the rest likely coming from sea ice–related and other surface processes. Arctic winter sea ice loss allows the ocean to release more heat and moisture, which enhances Arctic warming; however, this effect on SAT is confined to the ice-retreat area and has a limited influence on large-scale atmospheric circulations.
Abstract
Superimposed on a warming trend, Arctic winter surface air temperature (SAT) exhibits substantial interannual variability, the underlying mechanisms of which are unclear, especially with regard to the role of sea ice variations and atmospheric processes. Here, atmospheric reanalysis data and idealized atmospheric model simulations are used to reveal the mechanisms by which sea ice variations and atmospheric anomalous conditions affect interannual variations in wintertime Arctic SAT. Results show that near-surface interannual warming in the Arctic is accompanied by comparable warming throughout large parts of the Arctic troposphere and large-scale anomalous atmospheric circulation patterns. Within the Arctic, changes in large-scale atmospheric circulations due to internal atmospheric variability explain a substantial fraction of interannual variation in SAT and tropospheric temperatures, which lead to an increase in moisture and downward longwave radiation, with the rest likely coming from sea ice–related and other surface processes. Arctic winter sea ice loss allows the ocean to release more heat and moisture, which enhances Arctic warming; however, this effect on SAT is confined to the ice-retreat area and has a limited influence on large-scale atmospheric circulations.
Abstract
The forecast skill for week-2 wintertime surface air temperature (SAT) over the Northern Hemisphere by the Model for Prediction Across Scales–Atmosphere (MPAS-A) is evaluated and compared with operational forecast systems that participate in the Subseasonal to Seasonal Prediction project (S2S). An intercomparison of the MPAS against the China Meteorological Administration (CMA) model and the European Centre for Medium-Range Weather Forecasts (ECMWF) model was performed using 10-yr reforecasts. Comparing the forecast skill for SAT and atmospheric circulation anomalies at a lead of 2 weeks among the three models, the MPAS shows skill lower than the ECMWF model but higher than the CMA model. The gap in skills between the MPAS model and CMA model is not as large as that between the ECMWF model and MPAS model. Additionally, an intercomparison of the MPAS model against 10 S2S models is presented by using real-time forecasts since 2016 stored in the S2S database. The results show that the MPAS model has forecast skill for week-2 to week-4 wintertime SAT comparable to that in most S2S models. The MPAS model tends to be at an intermediate level compared to current operational forecast models.
Abstract
The forecast skill for week-2 wintertime surface air temperature (SAT) over the Northern Hemisphere by the Model for Prediction Across Scales–Atmosphere (MPAS-A) is evaluated and compared with operational forecast systems that participate in the Subseasonal to Seasonal Prediction project (S2S). An intercomparison of the MPAS against the China Meteorological Administration (CMA) model and the European Centre for Medium-Range Weather Forecasts (ECMWF) model was performed using 10-yr reforecasts. Comparing the forecast skill for SAT and atmospheric circulation anomalies at a lead of 2 weeks among the three models, the MPAS shows skill lower than the ECMWF model but higher than the CMA model. The gap in skills between the MPAS model and CMA model is not as large as that between the ECMWF model and MPAS model. Additionally, an intercomparison of the MPAS model against 10 S2S models is presented by using real-time forecasts since 2016 stored in the S2S database. The results show that the MPAS model has forecast skill for week-2 to week-4 wintertime SAT comparable to that in most S2S models. The MPAS model tends to be at an intermediate level compared to current operational forecast models.
Abstract
The dynamic origin of the interannual variability of West China autumn rainfall (WCAR), a special weather/climate phenomenon over western-central China in September and October, was investigated via observational diagnosis and numerical simulations. Here we found that the interannual variability of WCAR is closely related to the local horizontal trough, which is passively induced by two lower-level anticyclonic (high pressure) anomalies over East Asia. The anticyclonic anomaly over the south is a Gill-type response to the central and eastern Pacific diabatic cooling, while that over the north is part of the mid- to high-latitude barotropic Rossby wave train, which could be induced by either the thermal forcing of the central and eastern Pacific Ocean sea surface temperature (SST) cooling or that of the subtropical northern Atlantic Ocean SST warming. The quasi-barotropic high pressure anomaly over East Asia acts as an “invisible mountain” that steers the low-level anomalous southwesterly into a southeasterly and hinders the water vapor going farther to the north, leading to enhanced WCAR. However, the real mountain ranges in the region (the Qinglin and Ba Mountains) have no essential impact on the formation and interannual variability of WCAR.
Abstract
The dynamic origin of the interannual variability of West China autumn rainfall (WCAR), a special weather/climate phenomenon over western-central China in September and October, was investigated via observational diagnosis and numerical simulations. Here we found that the interannual variability of WCAR is closely related to the local horizontal trough, which is passively induced by two lower-level anticyclonic (high pressure) anomalies over East Asia. The anticyclonic anomaly over the south is a Gill-type response to the central and eastern Pacific diabatic cooling, while that over the north is part of the mid- to high-latitude barotropic Rossby wave train, which could be induced by either the thermal forcing of the central and eastern Pacific Ocean sea surface temperature (SST) cooling or that of the subtropical northern Atlantic Ocean SST warming. The quasi-barotropic high pressure anomaly over East Asia acts as an “invisible mountain” that steers the low-level anomalous southwesterly into a southeasterly and hinders the water vapor going farther to the north, leading to enhanced WCAR. However, the real mountain ranges in the region (the Qinglin and Ba Mountains) have no essential impact on the formation and interannual variability of WCAR.
Abstract
Earth’s surface warming by external forcing depends on location. Warming amplification, or greater surface warming than the global average, occurs in the Arctic and high-elevation regions, including the Tibetan Plateau (TP). We examined the major drivers of TP warming amplification in recent decades (1979–2020) and under future climate scenarios (2061–2100) by applying local energy budget diagnosis of multiple radiative kernels based on state-of-the-art reanalysis datasets and coupled model simulations. From 1979 to 2020, both the snow–albedo feedback and cloud–radiation feedback strongly affected the seasonality of TP warming (summer vs winter). Snow cover and albedo decreased significantly in winter but showed only small changes in summer. TP total and low-level cloud cover increased in summer, causing cooling, and decreased in winter, causing warming. During winter, TP warming amplification (1.84 from 1979 to 2020) is weaker than Arctic amplification (3.64) because the positive contribution of the surface albedo feedback to TP warming is not as strong as the dual warming effects of the lapse rate feedback and surface heat flux observed in the Arctic. Our attribution analyses based on the preindustrial control (piControl) and Historical simulations of phase 6 of the Coupled Model Intercomparison Project confirmed that TP warming is caused by external forcing. Because the external forcing associated with anthropogenic activity is increasing, TP warming will continue to the end of the twenty-first century. Under likely future warming scenarios, winter TP warming amplification is still less than in the Arctic due to the effects of the lapse rate feedback and surface heat flux.
Significance Statement
Over the Tibetan Plateau, warming amplification, which refers to greater surface warming than the global average (∼75% more warming than the global average from 1979 to 2020), has resulted in melting permafrost, retreating glaciers, and decreasing biodiversity. This study quantified the relative effects of eight physical processes on the warming amplification over the Tibetan Plateau. In the boreal winter, the reduction in snow cover and albedo are the leading contributors (about 49%) to Tibetan Plateau warming, meaning that melting snow exposes darker ground that absorbs more sunlight than snow does. In a warmer future climate, continued melting snow cover is projected to further enhance Tibetan Plateau warming amplification.
Abstract
Earth’s surface warming by external forcing depends on location. Warming amplification, or greater surface warming than the global average, occurs in the Arctic and high-elevation regions, including the Tibetan Plateau (TP). We examined the major drivers of TP warming amplification in recent decades (1979–2020) and under future climate scenarios (2061–2100) by applying local energy budget diagnosis of multiple radiative kernels based on state-of-the-art reanalysis datasets and coupled model simulations. From 1979 to 2020, both the snow–albedo feedback and cloud–radiation feedback strongly affected the seasonality of TP warming (summer vs winter). Snow cover and albedo decreased significantly in winter but showed only small changes in summer. TP total and low-level cloud cover increased in summer, causing cooling, and decreased in winter, causing warming. During winter, TP warming amplification (1.84 from 1979 to 2020) is weaker than Arctic amplification (3.64) because the positive contribution of the surface albedo feedback to TP warming is not as strong as the dual warming effects of the lapse rate feedback and surface heat flux observed in the Arctic. Our attribution analyses based on the preindustrial control (piControl) and Historical simulations of phase 6 of the Coupled Model Intercomparison Project confirmed that TP warming is caused by external forcing. Because the external forcing associated with anthropogenic activity is increasing, TP warming will continue to the end of the twenty-first century. Under likely future warming scenarios, winter TP warming amplification is still less than in the Arctic due to the effects of the lapse rate feedback and surface heat flux.
Significance Statement
Over the Tibetan Plateau, warming amplification, which refers to greater surface warming than the global average (∼75% more warming than the global average from 1979 to 2020), has resulted in melting permafrost, retreating glaciers, and decreasing biodiversity. This study quantified the relative effects of eight physical processes on the warming amplification over the Tibetan Plateau. In the boreal winter, the reduction in snow cover and albedo are the leading contributors (about 49%) to Tibetan Plateau warming, meaning that melting snow exposes darker ground that absorbs more sunlight than snow does. In a warmer future climate, continued melting snow cover is projected to further enhance Tibetan Plateau warming amplification.
