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- Author or Editor: Qing Wang x
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Abstract
The possible impacts of different sea surface temperature (SST) configurations on the predictability of the boreal summer tropical intraseasonal oscillation (TISO) are assessed with a series of ensemble forecasts. The five different lower boundary conditions examined in this study are, respectively, (i) the fully interactive ocean–atmosphere coupling, (ii) “smoothed” SST, which excludes the intraseasonal signal from sea surface forcing, (iii) damped persistent SST, (iv) coupling to a slab mixed-layer ocean, and (v) daily SST from the coupled forecast. The full atmosphere–ocean coupling generates an interactive SST that results in the highest TISO predictability of about 30 days over Southeast Asia. The atmosphere-only model is capable of reaching this predictability if the ensemble mean daily SST forecast by the coupled model is used as the lower boundary condition, which suggests that, in principle, the so-called tier-one and tier-two systems have the same predictability for the boreal summer TISO. The atmosphere-only model driven by either smoothed or damped persistent SSTs, however, has the lowest predictability (∼20 days). The atmospheric model coupled to a slab mixed-layer ocean achieves a predictability of 25 days. The positive SST anomalies in the northern Indo–western Pacific Oceans trigger convective disturbances by moistening and warming up the atmospheric boundary layer. The seasonal mean easterly shear intensifies the anomalous convection by enhancing the surface convergence. An overturning meridional circulation driven by the off-equatorial anomalous convection suppresses the near-equatorial convection and enhances the northward flows, which further intensify the off-equatorial surface convergence and the TISO-related convection. Thus, the boreal summer mean easterly shear and the overturning meridional circulation in the northern Indo–western Pacific sector act as “amplifiers” for the SST feedback to the convection of the TISO.
Abstract
The possible impacts of different sea surface temperature (SST) configurations on the predictability of the boreal summer tropical intraseasonal oscillation (TISO) are assessed with a series of ensemble forecasts. The five different lower boundary conditions examined in this study are, respectively, (i) the fully interactive ocean–atmosphere coupling, (ii) “smoothed” SST, which excludes the intraseasonal signal from sea surface forcing, (iii) damped persistent SST, (iv) coupling to a slab mixed-layer ocean, and (v) daily SST from the coupled forecast. The full atmosphere–ocean coupling generates an interactive SST that results in the highest TISO predictability of about 30 days over Southeast Asia. The atmosphere-only model is capable of reaching this predictability if the ensemble mean daily SST forecast by the coupled model is used as the lower boundary condition, which suggests that, in principle, the so-called tier-one and tier-two systems have the same predictability for the boreal summer TISO. The atmosphere-only model driven by either smoothed or damped persistent SSTs, however, has the lowest predictability (∼20 days). The atmospheric model coupled to a slab mixed-layer ocean achieves a predictability of 25 days. The positive SST anomalies in the northern Indo–western Pacific Oceans trigger convective disturbances by moistening and warming up the atmospheric boundary layer. The seasonal mean easterly shear intensifies the anomalous convection by enhancing the surface convergence. An overturning meridional circulation driven by the off-equatorial anomalous convection suppresses the near-equatorial convection and enhances the northward flows, which further intensify the off-equatorial surface convergence and the TISO-related convection. Thus, the boreal summer mean easterly shear and the overturning meridional circulation in the northern Indo–western Pacific sector act as “amplifiers” for the SST feedback to the convection of the TISO.
Abstract
Anomalous warming occurred over the Tibetan Plateau (TP) before and during the disastrous freezing rain and heavy snow hitting central and southern China in January 2008. The relationship between the TP warming and this extreme event is investigated with an atmospheric general circulation model. Two perpetual runs were performed. One is forced by the climatological mean sea surface temperatures in January as a control run; and the other has the same model setting as the control run except with an anomalous warming over the TP that mimics the observed temperature anomaly. The numerical results demonstrate that the TP warming induces favorable circulation conditions for the occurrence of this extreme event, which include the deepened lower-level South Asian trough, the enhanced lower-level southwesterly moisture transport in central-southern China, the lower-level cyclonic shear in the southerly flow over southeastern China, and the intensified Middle East jet stream in the middle and upper troposphere. Moreover, the anomalous TP warming results in a remarkable cold anomaly near the surface and a warm anomaly aloft over central China, forming a stable stratified inversion layer that favors the formation of the persistent freezing rain. The possible physical linkages between the TP warming and the relevant resultant circulation anomalies are proposed. The potential reason of the anomalous TP warming during the 2007–08 winter is also discussed.
Abstract
Anomalous warming occurred over the Tibetan Plateau (TP) before and during the disastrous freezing rain and heavy snow hitting central and southern China in January 2008. The relationship between the TP warming and this extreme event is investigated with an atmospheric general circulation model. Two perpetual runs were performed. One is forced by the climatological mean sea surface temperatures in January as a control run; and the other has the same model setting as the control run except with an anomalous warming over the TP that mimics the observed temperature anomaly. The numerical results demonstrate that the TP warming induces favorable circulation conditions for the occurrence of this extreme event, which include the deepened lower-level South Asian trough, the enhanced lower-level southwesterly moisture transport in central-southern China, the lower-level cyclonic shear in the southerly flow over southeastern China, and the intensified Middle East jet stream in the middle and upper troposphere. Moreover, the anomalous TP warming results in a remarkable cold anomaly near the surface and a warm anomaly aloft over central China, forming a stable stratified inversion layer that favors the formation of the persistent freezing rain. The possible physical linkages between the TP warming and the relevant resultant circulation anomalies are proposed. The potential reason of the anomalous TP warming during the 2007–08 winter is also discussed.
Abstract
A new bulk transfer formulation for the surface turbulent fluxes of momentum, heat, and moisture has been developed by using the square root of the vertically averaged turbulent kinetic energy (TKE) in the atmospheric boundary layer as a velocity scale, in place of the mean wind speed. The new parameterization utilizes the surface radiative (skin) temperature instead of the temperature at a “roughness height.” Field observations and large-eddy simulation (LES) results were used to develop the parameterization. It has been tested using an independent dataset from the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE). The predicted surface momentum flux compares very well with the observations, despite the fact that the data used for developing the new parameterization have a very different roughness length from the independent FIFE data. This shows that the parameterization can represent a wide range of surface roughness boundary conditions. The predicted sensible and latent heat fluxes also agree well with the FIFE observations, although the predicted surface sensible heat flux is somewhat less than observed at the FIFE site. The diurnal cycles of the predicted surface sensible heat and latent heat fluxes correspond very well with the observations in both magnitude and phase.
Abstract
A new bulk transfer formulation for the surface turbulent fluxes of momentum, heat, and moisture has been developed by using the square root of the vertically averaged turbulent kinetic energy (TKE) in the atmospheric boundary layer as a velocity scale, in place of the mean wind speed. The new parameterization utilizes the surface radiative (skin) temperature instead of the temperature at a “roughness height.” Field observations and large-eddy simulation (LES) results were used to develop the parameterization. It has been tested using an independent dataset from the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE). The predicted surface momentum flux compares very well with the observations, despite the fact that the data used for developing the new parameterization have a very different roughness length from the independent FIFE data. This shows that the parameterization can represent a wide range of surface roughness boundary conditions. The predicted sensible and latent heat fluxes also agree well with the FIFE observations, although the predicted surface sensible heat flux is somewhat less than observed at the FIFE site. The diurnal cycles of the predicted surface sensible heat and latent heat fluxes correspond very well with the observations in both magnitude and phase.
Abstract
Traditional atmospheric surface layer theory assumes homogeneous surface conditions. Regardless, nearly all surface layer parameterization schemes employed within numerical weather prediction models utilize the same techniques within highly heterogeneous coastal regimes as for homogeneous environments. We compare predicted surface weather and fluxes of momentum, heat, and moisture—focusing mainly on momentum—from regional simulations using the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) atmospheric model to observations collected from offshore buoys, inland flux towers, and radiosonde profiles during the Coastal Land-Air-Sea Interaction (CLASI) project throughout the summer of 2021 around Monterey Bay, California. Results reveal that modeled cross-coastal surface flux gradients are spuriously discontinuous, leading to systematically overestimated fluxes and weak winds inland of the coastline during onshore flow periods. Additionally, contrary to observations, modeled surface exchange coefficients are insensitive to wind direction on both sides of the coast, which degrades predictive skill downstream from the coastline. Over the central bay, prediction degrades when near-surface wind directions deviate from the prevailing flow direction as the parameterized stress–wind relationship fails during these cases. Predictive skill over the bay is therefore linked to variations in wind direction. Offshore of the geographically complex peninsula, systematic biases are less clear; however, bifurcations in drag coefficients based on wind direction were measured here as well. Last, increasing the horizontal grid spacing from 333 m to 3 km does not significantly affect surface layer prediction. This work highlights the need to reevaluate surface layer parameterization methods for modeling within coastal regions.
Significance Statement
Understanding surface layer weather is critical for many purposes, such as infrastructure design and weather forecasting. Within the context of numerical modeling and weather prediction, skillful forecasts of surface winds and temperature rely on accurate portrayal of the surface layer. By comparing observations collected during the Coastal Land-Air-Sea Interaction field program to numerical model solutions, we show that prediction of the surface layer fluxes of momentum, heat, and moisture break down near the coastline, which leads to biases in the predicted surface layer weather both inland and over the water. As surface layer parameterization methods across nearly all numerical models are rooted in the same practices, our results call into question the use of traditional methods near the coastline.
Abstract
Traditional atmospheric surface layer theory assumes homogeneous surface conditions. Regardless, nearly all surface layer parameterization schemes employed within numerical weather prediction models utilize the same techniques within highly heterogeneous coastal regimes as for homogeneous environments. We compare predicted surface weather and fluxes of momentum, heat, and moisture—focusing mainly on momentum—from regional simulations using the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) atmospheric model to observations collected from offshore buoys, inland flux towers, and radiosonde profiles during the Coastal Land-Air-Sea Interaction (CLASI) project throughout the summer of 2021 around Monterey Bay, California. Results reveal that modeled cross-coastal surface flux gradients are spuriously discontinuous, leading to systematically overestimated fluxes and weak winds inland of the coastline during onshore flow periods. Additionally, contrary to observations, modeled surface exchange coefficients are insensitive to wind direction on both sides of the coast, which degrades predictive skill downstream from the coastline. Over the central bay, prediction degrades when near-surface wind directions deviate from the prevailing flow direction as the parameterized stress–wind relationship fails during these cases. Predictive skill over the bay is therefore linked to variations in wind direction. Offshore of the geographically complex peninsula, systematic biases are less clear; however, bifurcations in drag coefficients based on wind direction were measured here as well. Last, increasing the horizontal grid spacing from 333 m to 3 km does not significantly affect surface layer prediction. This work highlights the need to reevaluate surface layer parameterization methods for modeling within coastal regions.
Significance Statement
Understanding surface layer weather is critical for many purposes, such as infrastructure design and weather forecasting. Within the context of numerical modeling and weather prediction, skillful forecasts of surface winds and temperature rely on accurate portrayal of the surface layer. By comparing observations collected during the Coastal Land-Air-Sea Interaction field program to numerical model solutions, we show that prediction of the surface layer fluxes of momentum, heat, and moisture break down near the coastline, which leads to biases in the predicted surface layer weather both inland and over the water. As surface layer parameterization methods across nearly all numerical models are rooted in the same practices, our results call into question the use of traditional methods near the coastline.
