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- Author or Editor: Wei-Ting Chen x
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Abstract
The present study aims to identify the precipitation bias associated with the interactions among fast physical processes in the Community Atmospheric Model, version 5 (CAM5), during the abrupt onset of the South China Sea (SCS) summer monsoon, a key precursor of the overall East Asia summer monsoon (EASM). The multiyear hindcast approach is utilized to obtain the well-constrained synoptic-scale horizontal circulation each year during the onset period from the years 1998 to 2012. In the pre-onset period, the ocean precipitation over the SCS is insufficiently suppressed in CAM5 hindcasts and thus weaker land–ocean precipitation contrasts. This is associated with the weaker and shallower convection simulated over the surrounding land, producing weaker local circulation within the SCS basin. In the post-onset period, rainfall of the organized convection over the Philippine coastal ocean is underestimated in the hindcasts, with overestimated upper-level heating. These biases are further elaborated as the underrepresentation of the convection diurnal cycle and coastal convection systems, as well as the issue of precipitation sensitivity to environmental moisture during the SCS onset period. The biases identified in hindcasts are consistent with the general bias of the EASM in the climate simulation of CAM5. The current results highlight that the appropriate representation of land–ocean–convection interactions over coastal areas can potentially improve the simulation of seasonal transition over the monsoon regions.
Abstract
The present study aims to identify the precipitation bias associated with the interactions among fast physical processes in the Community Atmospheric Model, version 5 (CAM5), during the abrupt onset of the South China Sea (SCS) summer monsoon, a key precursor of the overall East Asia summer monsoon (EASM). The multiyear hindcast approach is utilized to obtain the well-constrained synoptic-scale horizontal circulation each year during the onset period from the years 1998 to 2012. In the pre-onset period, the ocean precipitation over the SCS is insufficiently suppressed in CAM5 hindcasts and thus weaker land–ocean precipitation contrasts. This is associated with the weaker and shallower convection simulated over the surrounding land, producing weaker local circulation within the SCS basin. In the post-onset period, rainfall of the organized convection over the Philippine coastal ocean is underestimated in the hindcasts, with overestimated upper-level heating. These biases are further elaborated as the underrepresentation of the convection diurnal cycle and coastal convection systems, as well as the issue of precipitation sensitivity to environmental moisture during the SCS onset period. The biases identified in hindcasts are consistent with the general bias of the EASM in the climate simulation of CAM5. The current results highlight that the appropriate representation of land–ocean–convection interactions over coastal areas can potentially improve the simulation of seasonal transition over the monsoon regions.
Abstract
Changes in extreme temperatures have more effects on ecosystems and human society than changes in climate averages. As a hotspot of global warming, the Arctic has experienced unprecedented heatwaves recently, which highlights the importance of identifying long-term variations of extreme temperatures. However, spatial unbalance of observations and artificially chosen investigation periods limit our knowledge of extreme temperatures over the Arctic lands. Here, we build a complete and quality-controlled observation network on surface temperature over the Arctic lands and combine in situ and reanalysis data to evaluate changes of extreme temperatures during the period 1979–2020. Our results indicate that 1) the increase in extreme temperatures has accelerated since the 2000s, especially on the coast of Eurasia; 2) the change magnitude for cold events is larger than for warm events, in terms of intensity, frequency, and duration; and 3) increases in warm events only occur locally, for example, Alaska and central Siberia, while decreases in cold events occur throughout the Arctic lands. The long-term trends of extreme temperatures are synchronous with sea ice loss, and patterns of interannual variations are mainly related to the North Atlantic Oscillation. We suggest further efforts toward improvement over North America, especially for Greenland, through sufficient observations and regional models.
Abstract
Changes in extreme temperatures have more effects on ecosystems and human society than changes in climate averages. As a hotspot of global warming, the Arctic has experienced unprecedented heatwaves recently, which highlights the importance of identifying long-term variations of extreme temperatures. However, spatial unbalance of observations and artificially chosen investigation periods limit our knowledge of extreme temperatures over the Arctic lands. Here, we build a complete and quality-controlled observation network on surface temperature over the Arctic lands and combine in situ and reanalysis data to evaluate changes of extreme temperatures during the period 1979–2020. Our results indicate that 1) the increase in extreme temperatures has accelerated since the 2000s, especially on the coast of Eurasia; 2) the change magnitude for cold events is larger than for warm events, in terms of intensity, frequency, and duration; and 3) increases in warm events only occur locally, for example, Alaska and central Siberia, while decreases in cold events occur throughout the Arctic lands. The long-term trends of extreme temperatures are synchronous with sea ice loss, and patterns of interannual variations are mainly related to the North Atlantic Oscillation. We suggest further efforts toward improvement over North America, especially for Greenland, through sufficient observations and regional models.
Abstract
This study implements the unified parameterization (UP) in the Central Weather Bureau Global Forecast System (CWBGFS) based on the relaxed Arakawa–Schubert scheme (RAS) at a horizontal resolution of 15 km. The new cumulus parameterization that incorporates the UP framework is called URAS. The UP generalizes the representation of moist convection between the parameterized and the explicitly resolved processes according to the process-dependent convective updraft fraction (σ). Short-term hindcasts are performed to investigate the impacts of the UP on the simulated precipitation variability and organized convective systems over the Maritime Continent when multiple scales of convection occurred. The result shows that σ is generally larger when convective systems develop, which adaptively reduces the parameterized convection and increases the spatial variation of moisture. In the URAS experiment, the moisture hotspots within organized convective systems contribute to the enhanced local circulation and the more significant variability of precipitation. Consequently, the URAS has a more realistic precipitation spectrum, an improved relationship between the maximum precipitation and the horizontal scale of the convective systems, and an improved column water vapor–precipitation relationship.
Abstract
This study implements the unified parameterization (UP) in the Central Weather Bureau Global Forecast System (CWBGFS) based on the relaxed Arakawa–Schubert scheme (RAS) at a horizontal resolution of 15 km. The new cumulus parameterization that incorporates the UP framework is called URAS. The UP generalizes the representation of moist convection between the parameterized and the explicitly resolved processes according to the process-dependent convective updraft fraction (σ). Short-term hindcasts are performed to investigate the impacts of the UP on the simulated precipitation variability and organized convective systems over the Maritime Continent when multiple scales of convection occurred. The result shows that σ is generally larger when convective systems develop, which adaptively reduces the parameterized convection and increases the spatial variation of moisture. In the URAS experiment, the moisture hotspots within organized convective systems contribute to the enhanced local circulation and the more significant variability of precipitation. Consequently, the URAS has a more realistic precipitation spectrum, an improved relationship between the maximum precipitation and the horizontal scale of the convective systems, and an improved column water vapor–precipitation relationship.
Abstract
This study quantifies the potential effect of the lee vortex on the fine particulate matter (PM2.5) pollution deterioration under the complex topography in Taiwan using observational data. We select the lee-vortex days that favor the development of the lee vortices in northwestern Taiwan under the southeasterly synoptic winds. We then define the enhancement index that discerns the areas with the high occurrence frequencies of the PM2.5 enhancement under the flow regime relative to the seasonal background concentrations. Under the lee-vortex days, the center of western Taiwan exhibits enhancement indices higher than 0.65. In addition, during the consecutive lee-vortex days, the index characterizes a northward shift in the PM2.5-enhanced areas under the subtle transition of the background wind directions. The areas with indices higher than 0.65 expand on the second day in northwestern Taiwan; the number of stations exhibiting indices higher than 0.8 increases by threefold from the first to the second day. The idealized numerical simulations using the Taiwan vector vorticity equation cloud-resolving model (TaiwanVVM) explicitly resolve the structures of leeside circulations and the associated pollutant transport, and their evolutions are highly sensitive to the background winds.
Significance Statement
Our study investigates the challenging question of local circulation patterns affected by mountain orography and the associated pollutant transport. We analyzed long-term balloon sounding and ground station observations to select the weather regime favoring the formation of lee vortices on Taiwan island. We then quantified the areas with a frequent enhancement of particulate pollutants. The long-term trend of the lee-vortex days exhibited a significant increase in the past decades. The pollution enhancement areas are highly consistent with the regions dominated by leeside local circulation. Together with the idealized high-resolution simulations, we identified that the detailed evolution of the lee vortices is highly sensitive to the subtle changes in background wind direction and hence the redistribution of local pollution.
Abstract
This study quantifies the potential effect of the lee vortex on the fine particulate matter (PM2.5) pollution deterioration under the complex topography in Taiwan using observational data. We select the lee-vortex days that favor the development of the lee vortices in northwestern Taiwan under the southeasterly synoptic winds. We then define the enhancement index that discerns the areas with the high occurrence frequencies of the PM2.5 enhancement under the flow regime relative to the seasonal background concentrations. Under the lee-vortex days, the center of western Taiwan exhibits enhancement indices higher than 0.65. In addition, during the consecutive lee-vortex days, the index characterizes a northward shift in the PM2.5-enhanced areas under the subtle transition of the background wind directions. The areas with indices higher than 0.65 expand on the second day in northwestern Taiwan; the number of stations exhibiting indices higher than 0.8 increases by threefold from the first to the second day. The idealized numerical simulations using the Taiwan vector vorticity equation cloud-resolving model (TaiwanVVM) explicitly resolve the structures of leeside circulations and the associated pollutant transport, and their evolutions are highly sensitive to the background winds.
Significance Statement
Our study investigates the challenging question of local circulation patterns affected by mountain orography and the associated pollutant transport. We analyzed long-term balloon sounding and ground station observations to select the weather regime favoring the formation of lee vortices on Taiwan island. We then quantified the areas with a frequent enhancement of particulate pollutants. The long-term trend of the lee-vortex days exhibited a significant increase in the past decades. The pollution enhancement areas are highly consistent with the regions dominated by leeside local circulation. Together with the idealized high-resolution simulations, we identified that the detailed evolution of the lee vortices is highly sensitive to the subtle changes in background wind direction and hence the redistribution of local pollution.
ABSTRACT
We studied the scale interactions of the convectively coupled Kelvin waves (KWs) over the South China Sea (SCS) and Maritime Continent (MC) during December 2016. Three KWs were observed near the equator in this month while the Madden–Julian oscillation (MJO) was inactive. The impacts of these KWs on the rainfall variability of various time scales are diagnosed, including synoptic disturbances, diurnal cycle (DC), and the onset of the Australian monsoon. Four interaction events between the KWs and the westward-propagating waves over the off-equatorial regions were examined; two events led to KW enhancements and the other two contributed to the formation of a tropical depression/tropical cyclone. Over the KW convectively active region of the MC, the DC of precipitation was enhanced in major islands and neighboring oceans. Over the land, the DC hot spots were modulated depending on the background winds and the terrain effects. Over the ocean, the “coastal regime” of the DC appeared at specific coastal areas. Last, the Australian summer monsoon onset occurred with the passage of a KW, which provided favorable conditions of low-level westerlies and initial convection over southern MC and the Arafura Sea. This effect may be helped by the warm sea surface temperature anomalies associated with the La Niña condition of this month. The current results showcase that KWs and their associated scale interactions can provide useful references for weather monitoring and forecast of this region when the MJO is absent.
ABSTRACT
We studied the scale interactions of the convectively coupled Kelvin waves (KWs) over the South China Sea (SCS) and Maritime Continent (MC) during December 2016. Three KWs were observed near the equator in this month while the Madden–Julian oscillation (MJO) was inactive. The impacts of these KWs on the rainfall variability of various time scales are diagnosed, including synoptic disturbances, diurnal cycle (DC), and the onset of the Australian monsoon. Four interaction events between the KWs and the westward-propagating waves over the off-equatorial regions were examined; two events led to KW enhancements and the other two contributed to the formation of a tropical depression/tropical cyclone. Over the KW convectively active region of the MC, the DC of precipitation was enhanced in major islands and neighboring oceans. Over the land, the DC hot spots were modulated depending on the background winds and the terrain effects. Over the ocean, the “coastal regime” of the DC appeared at specific coastal areas. Last, the Australian summer monsoon onset occurred with the passage of a KW, which provided favorable conditions of low-level westerlies and initial convection over southern MC and the Arafura Sea. This effect may be helped by the warm sea surface temperature anomalies associated with the La Niña condition of this month. The current results showcase that KWs and their associated scale interactions can provide useful references for weather monitoring and forecast of this region when the MJO is absent.
Abstract
Tropical deforestation can result in substantial changes in local surface energy and water budgets, and thus in atmospheric stability. These effects may in turn yield changes in precipitation. The Maritime Continent (MC) has undergone severe deforestation during the past few decades but it has received less attention than the deforestation in the Amazon and Congo rain forests. In this study, numerical deforestation experiments are conducted with global (i.e., Community Earth System Model) and regional climate models (i.e., Regional Climate Model version 4.6) to investigate precipitation responses to MC deforestation. The results show that the deforestation in the MC region leads to increases in both surface temperature and local precipitation. Atmospheric moisture budget analysis reveals that the enhanced precipitation is associated more with the dynamic component than with the thermodynamic component of the vertical moisture advection term. Further analyses on the vertical profile of moist static energy indicate that the atmospheric instability over the deforested areas is increased as a result of anomalous moistening at approximately 800–850 hPa and anomalous warming extending from the surface to 750 hPa. This instability favors ascending air motions, which enhance low-level moisture convergence. Moreover, the vertical motion increases associated with the MC deforestation are comparable to those generated by La Niña events. These findings offer not only mechanisms to explain the local climatic responses to MC deforestation but also insights into the possible reasons for disagreements among climate models in simulating the precipitation responses.
Abstract
Tropical deforestation can result in substantial changes in local surface energy and water budgets, and thus in atmospheric stability. These effects may in turn yield changes in precipitation. The Maritime Continent (MC) has undergone severe deforestation during the past few decades but it has received less attention than the deforestation in the Amazon and Congo rain forests. In this study, numerical deforestation experiments are conducted with global (i.e., Community Earth System Model) and regional climate models (i.e., Regional Climate Model version 4.6) to investigate precipitation responses to MC deforestation. The results show that the deforestation in the MC region leads to increases in both surface temperature and local precipitation. Atmospheric moisture budget analysis reveals that the enhanced precipitation is associated more with the dynamic component than with the thermodynamic component of the vertical moisture advection term. Further analyses on the vertical profile of moist static energy indicate that the atmospheric instability over the deforested areas is increased as a result of anomalous moistening at approximately 800–850 hPa and anomalous warming extending from the surface to 750 hPa. This instability favors ascending air motions, which enhance low-level moisture convergence. Moreover, the vertical motion increases associated with the MC deforestation are comparable to those generated by La Niña events. These findings offer not only mechanisms to explain the local climatic responses to MC deforestation but also insights into the possible reasons for disagreements among climate models in simulating the precipitation responses.
Abstract
To assess deep convective parameterizations in a variety of GCMs and examine the fast-time-scale convective transition, a set of statistics characterizing the pickup of precipitation as a function of column water vapor (CWV), PDFs and joint PDFs of CWV and precipitation, and the dependence of the moisture–precipitation relation on tropospheric temperature is evaluated using the hourly output of two versions of the GFDL Atmospheric Model, version 4 (AM4), NCAR CAM5 and superparameterized CAM (SPCAM). The 6-hourly output from the MJO Task Force (MJOTF)/GEWEX Atmospheric System Study (GASS) project is also analyzed. Contrasting statistics produced from individual models that primarily differ in representations of moist convection suggest that convective transition statistics can substantially distinguish differences in convective representation and its interaction with the large-scale flow, while models that differ only in spatial–temporal resolution, microphysics, or ocean–atmosphere coupling result in similar statistics. Most of the models simulate some version of the observed sharp increase in precipitation as CWV exceeds a critical value, as well as that convective onset occurs at higher CWV but at lower column RH as temperature increases. While some models quantitatively capture these observed features and associated probability distributions, considerable intermodel spread and departures from observations in various aspects of the precipitation–CWV relationship are noted. For instance, in many of the models, the transition from the low-CWV, nonprecipitating regime to the moist regime for CWV around and above critical is less abrupt than in observations. Additionally, some models overproduce drizzle at low CWV, and some require CWV higher than observed for strong precipitation. For many of the models, it is particularly challenging to simulate the probability distributions of CWV at high temperature.
Abstract
To assess deep convective parameterizations in a variety of GCMs and examine the fast-time-scale convective transition, a set of statistics characterizing the pickup of precipitation as a function of column water vapor (CWV), PDFs and joint PDFs of CWV and precipitation, and the dependence of the moisture–precipitation relation on tropospheric temperature is evaluated using the hourly output of two versions of the GFDL Atmospheric Model, version 4 (AM4), NCAR CAM5 and superparameterized CAM (SPCAM). The 6-hourly output from the MJO Task Force (MJOTF)/GEWEX Atmospheric System Study (GASS) project is also analyzed. Contrasting statistics produced from individual models that primarily differ in representations of moist convection suggest that convective transition statistics can substantially distinguish differences in convective representation and its interaction with the large-scale flow, while models that differ only in spatial–temporal resolution, microphysics, or ocean–atmosphere coupling result in similar statistics. Most of the models simulate some version of the observed sharp increase in precipitation as CWV exceeds a critical value, as well as that convective onset occurs at higher CWV but at lower column RH as temperature increases. While some models quantitatively capture these observed features and associated probability distributions, considerable intermodel spread and departures from observations in various aspects of the precipitation–CWV relationship are noted. For instance, in many of the models, the transition from the low-CWV, nonprecipitating regime to the moist regime for CWV around and above critical is less abrupt than in observations. Additionally, some models overproduce drizzle at low CWV, and some require CWV higher than observed for strong precipitation. For many of the models, it is particularly challenging to simulate the probability distributions of CWV at high temperature.
