Search Results
Abstract
Subseasonal heatwave-driven concurrent hot and dry extreme events (HDEs) can cause substantial damage to crops, and hence to lives and livelihoods. However, the physical processes that lead to these devastating events are not well understood. Based on observations and reanalysis data for 1979–2016 over China, we show that HDEs occur preferentially over central and eastern China (CEC) and southern China (SC), with a maximum of three events per year along the Yangtze Valley. The probability of longer-lived and potentially more damaging HDEs is larger in SC than in CEC. Over SC the key factors of HDEs—positive anomalies of surface air temperature and evapotranspiration, and negative anomalies of soil moisture—begin two pentads before maximizing at the peak of the HDEs. These anomalies occur south of a positive height anomaly at 200 hPa, associated with a large-scale subsidence anomaly. The processes over CEC are similar to those for SC, but the anomalies begin one pentad before the peak. HDE frequency is strongly related to the Silk Road pattern and the boreal summer intraseasonal oscillation. Positive phases of the Silk Road pattern and suppressed phases of the boreal summer intraseasonal oscillation are associated with positive height anomalies over CEC and SC, increasing HDE frequency by about 35%–54% relative to the climatological mean. Understanding the effects of subseasonal and seasonal atmospheric circulation variability, such as the Silk Road pattern and boreal summer intraseasonal oscillation, on HDEs is important to improve HDE predictions over China.
Abstract
Subseasonal heatwave-driven concurrent hot and dry extreme events (HDEs) can cause substantial damage to crops, and hence to lives and livelihoods. However, the physical processes that lead to these devastating events are not well understood. Based on observations and reanalysis data for 1979–2016 over China, we show that HDEs occur preferentially over central and eastern China (CEC) and southern China (SC), with a maximum of three events per year along the Yangtze Valley. The probability of longer-lived and potentially more damaging HDEs is larger in SC than in CEC. Over SC the key factors of HDEs—positive anomalies of surface air temperature and evapotranspiration, and negative anomalies of soil moisture—begin two pentads before maximizing at the peak of the HDEs. These anomalies occur south of a positive height anomaly at 200 hPa, associated with a large-scale subsidence anomaly. The processes over CEC are similar to those for SC, but the anomalies begin one pentad before the peak. HDE frequency is strongly related to the Silk Road pattern and the boreal summer intraseasonal oscillation. Positive phases of the Silk Road pattern and suppressed phases of the boreal summer intraseasonal oscillation are associated with positive height anomalies over CEC and SC, increasing HDE frequency by about 35%–54% relative to the climatological mean. Understanding the effects of subseasonal and seasonal atmospheric circulation variability, such as the Silk Road pattern and boreal summer intraseasonal oscillation, on HDEs is important to improve HDE predictions over China.
Abstract
There is still no consensus about the best methodology for attributing observed changes in climate or climate events. One widely used approach relies on experiments in which the time periods of interest are simulated using an atmospheric general circulation model (AGCM) forced by prescribed sea surface temperatures (SSTs), with and without estimated anthropogenic influences. A potential limitation of such experiments is the lack of explicit atmosphere–ocean coupling; therefore a key question is whether the attribution statements derived from such studies are in fact robust. In this research the authors have carried out climate model experiments to test attribution conclusions in a situation where the answer is known—a so-called perfect model approach. The study involves comparing attribution conclusions for decadal changes derived from experiments with a coupled climate model (specifically an AGCM coupled to an ocean mixed-layer model) with conclusions derived from parallel experiments with the same AGCM forced by SSTs derived from the coupled model simulations. Results indicate that attribution conclusions for surface air temperature changes derived from AGCM experiments are generally robust and not sensitive to air–sea coupling. However, changes in seasonal mean and extreme precipitations, and circulation in some regions, show large sensitivity to air–sea coupling, notably in the summer monsoons over East Asia and Australia. Comparison with observed changes indicates that the coupled simulations generally agree better with observations. These results demonstrate that the AGCM-based attribution method has limitations and may lead to erroneous attribution conclusions in some regions for local circulation and mean and extreme precipitation. The coupled mixed-layer model used in this study offers an alternative and, in some respects, superior tool for attribution studies.
Abstract
There is still no consensus about the best methodology for attributing observed changes in climate or climate events. One widely used approach relies on experiments in which the time periods of interest are simulated using an atmospheric general circulation model (AGCM) forced by prescribed sea surface temperatures (SSTs), with and without estimated anthropogenic influences. A potential limitation of such experiments is the lack of explicit atmosphere–ocean coupling; therefore a key question is whether the attribution statements derived from such studies are in fact robust. In this research the authors have carried out climate model experiments to test attribution conclusions in a situation where the answer is known—a so-called perfect model approach. The study involves comparing attribution conclusions for decadal changes derived from experiments with a coupled climate model (specifically an AGCM coupled to an ocean mixed-layer model) with conclusions derived from parallel experiments with the same AGCM forced by SSTs derived from the coupled model simulations. Results indicate that attribution conclusions for surface air temperature changes derived from AGCM experiments are generally robust and not sensitive to air–sea coupling. However, changes in seasonal mean and extreme precipitations, and circulation in some regions, show large sensitivity to air–sea coupling, notably in the summer monsoons over East Asia and Australia. Comparison with observed changes indicates that the coupled simulations generally agree better with observations. These results demonstrate that the AGCM-based attribution method has limitations and may lead to erroneous attribution conclusions in some regions for local circulation and mean and extreme precipitation. The coupled mixed-layer model used in this study offers an alternative and, in some respects, superior tool for attribution studies.
Abstract
The Silk Road pattern (SRP) teleconnection manifests in summer over Eurasia, where it is associated with substantial temperature and precipitation anomalies. The SRP varies on interannual and decadal scales; reanalyses show an increase in its decadal variability around the mid-1970s. Understanding what drives this decadal variability is particularly important, because contemporary seasonal prediction models struggle to predict the phase of the SRP. Based on analysis of observations and multiple targeted numerical experiments, this study proposes a mechanism for decadal SRP variability. Causal effect network analysis confirms a positive feedback loop between the eastern portion of the SRP pattern and vertical motion over India on synoptic time scales. Anomalies over a larger region of subtropical South Asia can reinforce a background state that projects onto the positive or negative SRP through this mechanism. This effect is isolated and confirmed in targeted numerical simulations. The transition from weak to strong decadal variability in the mid-1970s is consistent with more spatially coherent interannual precipitation variability over subtropical South Asia. Furthermore, results suggest that oceanic variability does not directly force the SRP. Nevertheless, sea surface temperatures in the North Atlantic and the North Pacific may indirectly affect the SRP by modulating South Asian rainfall on decadal time scales.
Abstract
The Silk Road pattern (SRP) teleconnection manifests in summer over Eurasia, where it is associated with substantial temperature and precipitation anomalies. The SRP varies on interannual and decadal scales; reanalyses show an increase in its decadal variability around the mid-1970s. Understanding what drives this decadal variability is particularly important, because contemporary seasonal prediction models struggle to predict the phase of the SRP. Based on analysis of observations and multiple targeted numerical experiments, this study proposes a mechanism for decadal SRP variability. Causal effect network analysis confirms a positive feedback loop between the eastern portion of the SRP pattern and vertical motion over India on synoptic time scales. Anomalies over a larger region of subtropical South Asia can reinforce a background state that projects onto the positive or negative SRP through this mechanism. This effect is isolated and confirmed in targeted numerical simulations. The transition from weak to strong decadal variability in the mid-1970s is consistent with more spatially coherent interannual precipitation variability over subtropical South Asia. Furthermore, results suggest that oceanic variability does not directly force the SRP. Nevertheless, sea surface temperatures in the North Atlantic and the North Pacific may indirectly affect the SRP by modulating South Asian rainfall on decadal time scales.
Abstract
This paper reports a consistent seesaw relationship between interdecadal precipitation variability over North China and the Southwest United States, which can be found in observations and simulations with several models. Idealized model simulations suggest the seesaw could be mainly driven by the interdecadal Pacific oscillation (IPO), through a large-scale circulation anomaly occupying the entire northern North Pacific, while the Atlantic multidecadal oscillation (AMO) contributes oppositely and less. Modulation of precipitation by the IPO tends to be intensified when the AMO is in the opposite phase, but weakened when the AMO is in the same phase. The warm IPO phase is associated with an anomalous cyclone over the northern North Pacific; consequently, anomalous southwesterly winds bring more moisture and rainfall to the Southwest United States, while northwesterly wind anomalies prevail over North China with negative rainfall anomalies. The east–west seesaw of rainfall anomalies reverses sign when the circulation anomaly becomes anticyclonic during the cold IPO phase. The IPO-related tropical SST anomalies affect the meridional temperature gradient over the North Pacific and adjacent regions and the mean meridional circulation. In the northern North Pacific, the atmospheric response to IPO forcing imposes an equivalent barotropic structure throughout the troposphere. An important implication from this study is the potential predictability of drought-related water stresses over these arid and semiarid regions, with the progress of our understanding and prediction of the IPO and AMO.
Abstract
This paper reports a consistent seesaw relationship between interdecadal precipitation variability over North China and the Southwest United States, which can be found in observations and simulations with several models. Idealized model simulations suggest the seesaw could be mainly driven by the interdecadal Pacific oscillation (IPO), through a large-scale circulation anomaly occupying the entire northern North Pacific, while the Atlantic multidecadal oscillation (AMO) contributes oppositely and less. Modulation of precipitation by the IPO tends to be intensified when the AMO is in the opposite phase, but weakened when the AMO is in the same phase. The warm IPO phase is associated with an anomalous cyclone over the northern North Pacific; consequently, anomalous southwesterly winds bring more moisture and rainfall to the Southwest United States, while northwesterly wind anomalies prevail over North China with negative rainfall anomalies. The east–west seesaw of rainfall anomalies reverses sign when the circulation anomaly becomes anticyclonic during the cold IPO phase. The IPO-related tropical SST anomalies affect the meridional temperature gradient over the North Pacific and adjacent regions and the mean meridional circulation. In the northern North Pacific, the atmospheric response to IPO forcing imposes an equivalent barotropic structure throughout the troposphere. An important implication from this study is the potential predictability of drought-related water stresses over these arid and semiarid regions, with the progress of our understanding and prediction of the IPO and AMO.
Abstract
Anomalies in Siberian snow cover have been shown to affect Eurasian winter climate through the North Atlantic Oscillation (NAO). The existence of a teleconnection between North American snow cover and the NAO is far less certain, particularly for limited, regional snow cover anomalies. Using three ensembles of the Community Atmosphere Model, version 2 (CAM2), the authors examined teleconnections between persistent, forced snow cover in the northern Great Plains of the United States and western Eurasian winters. One ensemble allowed the model to freely determine global snow cover, while the other two forced a 72-cm snowpack centered over Nebraska. Of the forced ensembles, the “early-season” (“late season”) simulations initiated the snowpack on 1 November (1 January). The additional snow cover generated lower (higher) sea level pressures and geopotential heights over Iceland (the Azores) and warmer (cooler) temperatures over northern and western (eastern and southeastern) Europe, which suggests the positive NAO phase.
Differences between the free-snow-cover and early-season ensembles were never significant until January, which implied either that the atmospheric response required a long lag or that the late-winter atmosphere was particularly sensitive to Great Plains snow. The authors rejected the former hypothesis and supported the latter by noting similarities between the early- and late-season ensembles in late winter for European 2-m temperatures, transatlantic circulation, and an NAO index. Therefore, a regional North American snow cover anomaly in an area of high inter- and intra-annual snow cover variability can show a stronger teleconnection to European winter climate than previously reported for broader snow cover anomalies. In particular, anomalous late-season snow in the Great Plains may shift the NAO toward the positive phase.
Abstract
Anomalies in Siberian snow cover have been shown to affect Eurasian winter climate through the North Atlantic Oscillation (NAO). The existence of a teleconnection between North American snow cover and the NAO is far less certain, particularly for limited, regional snow cover anomalies. Using three ensembles of the Community Atmosphere Model, version 2 (CAM2), the authors examined teleconnections between persistent, forced snow cover in the northern Great Plains of the United States and western Eurasian winters. One ensemble allowed the model to freely determine global snow cover, while the other two forced a 72-cm snowpack centered over Nebraska. Of the forced ensembles, the “early-season” (“late season”) simulations initiated the snowpack on 1 November (1 January). The additional snow cover generated lower (higher) sea level pressures and geopotential heights over Iceland (the Azores) and warmer (cooler) temperatures over northern and western (eastern and southeastern) Europe, which suggests the positive NAO phase.
Differences between the free-snow-cover and early-season ensembles were never significant until January, which implied either that the atmospheric response required a long lag or that the late-winter atmosphere was particularly sensitive to Great Plains snow. The authors rejected the former hypothesis and supported the latter by noting similarities between the early- and late-season ensembles in late winter for European 2-m temperatures, transatlantic circulation, and an NAO index. Therefore, a regional North American snow cover anomaly in an area of high inter- and intra-annual snow cover variability can show a stronger teleconnection to European winter climate than previously reported for broader snow cover anomalies. In particular, anomalous late-season snow in the Great Plains may shift the NAO toward the positive phase.
Abstract
Studies have shown that the location and structure of the simulated intertropical convergence zone (ITCZ) is sensitive to the treatment of sub-gridscale convection and cloud–radiation interactions. This sensitivity remains in idealized aquaplanet experiments with fixed surface temperatures. However, studies have not considered the role of cloud-radiative effects (CRE; atmospheric heating due to cloud–radiation interactions) in the sensitivity of the ITCZ to the treatment of convection. We use an atmospheric energy input (AEI) framework to explore how the CRE modulates the sensitivity of the ITCZ to convective mixing in aquaplanet simulations. Simulations show a sensitivity of the ITCZ to convective mixing, with stronger convective mixing favoring a single ITCZ. For simulations with a single ITCZ, the CRE maintains the positive equatorial AEI. To explore the role of the CRE further, we prescribe the CRE as either zero or a meridionally and diurnally varying climatology. Removing the CRE is associated with a reduced equatorial AEI and an increase in the range of convective mixing rates that produce a double ITCZ. Prescribing the CRE reduces the sensitivity of the ITCZ to convective mixing by 50%. In prescribed-CRE simulations, other AEI components, in particular the surface latent heat flux, modulate the sensitivity of the AEI to convective mixing. Analysis of the meridional moist static energy transport shows that a shallower Hadley circulation can produce an equatorward energy transport at low latitudes even with equatorial ascent.
Abstract
Studies have shown that the location and structure of the simulated intertropical convergence zone (ITCZ) is sensitive to the treatment of sub-gridscale convection and cloud–radiation interactions. This sensitivity remains in idealized aquaplanet experiments with fixed surface temperatures. However, studies have not considered the role of cloud-radiative effects (CRE; atmospheric heating due to cloud–radiation interactions) in the sensitivity of the ITCZ to the treatment of convection. We use an atmospheric energy input (AEI) framework to explore how the CRE modulates the sensitivity of the ITCZ to convective mixing in aquaplanet simulations. Simulations show a sensitivity of the ITCZ to convective mixing, with stronger convective mixing favoring a single ITCZ. For simulations with a single ITCZ, the CRE maintains the positive equatorial AEI. To explore the role of the CRE further, we prescribe the CRE as either zero or a meridionally and diurnally varying climatology. Removing the CRE is associated with a reduced equatorial AEI and an increase in the range of convective mixing rates that produce a double ITCZ. Prescribing the CRE reduces the sensitivity of the ITCZ to convective mixing by 50%. In prescribed-CRE simulations, other AEI components, in particular the surface latent heat flux, modulate the sensitivity of the AEI to convective mixing. Analysis of the meridional moist static energy transport shows that a shallower Hadley circulation can produce an equatorward energy transport at low latitudes even with equatorial ascent.
Abstract
A newly assembled atmosphere–ocean coupled model, called HadKPP, is described and then used to determine the effects of subdaily air–sea coupling and fine near-surface ocean vertical resolution on the representation of the Northern Hemisphere summer intraseasonal oscillation. HadKPP comprises the Hadley Centre atmospheric model coupled to the K-Profile Parameterization ocean boundary layer model.
Four 30-member ensembles were performed that vary in ocean vertical resolution between 1 and 10 m and in coupling frequency between 3 and 24 h. The 10-m, 24-h ensemble exhibited roughly 60% of the observed 30–50-day variability in sea surface temperatures and rainfall and very weak northward propagation. Enhancing only the vertical resolution or only the coupling frequency produced modest improvements in variability and just a standing intraseasonal oscillation. Only the 1-m, 3-h configuration generated organized, northward-propagating convection similar to observations. Subdaily surface forcing produced stronger upper-ocean temperature anomalies in quadrature with anomalous convection, which likely affected lower-atmospheric stability ahead of the convection, causing propagation. Well-resolved air–sea coupling did not improve the eastward propagation of the boreal summer intraseasonal oscillation in this model.
Upper-ocean vertical mixing and diurnal variability in coupled models must be improved to accurately resolve and simulate tropical subseasonal variability. In HadKPP, the mere presence of air–sea coupling was not sufficient to generate an intraseasonal oscillation resembling observations.
Abstract
A newly assembled atmosphere–ocean coupled model, called HadKPP, is described and then used to determine the effects of subdaily air–sea coupling and fine near-surface ocean vertical resolution on the representation of the Northern Hemisphere summer intraseasonal oscillation. HadKPP comprises the Hadley Centre atmospheric model coupled to the K-Profile Parameterization ocean boundary layer model.
Four 30-member ensembles were performed that vary in ocean vertical resolution between 1 and 10 m and in coupling frequency between 3 and 24 h. The 10-m, 24-h ensemble exhibited roughly 60% of the observed 30–50-day variability in sea surface temperatures and rainfall and very weak northward propagation. Enhancing only the vertical resolution or only the coupling frequency produced modest improvements in variability and just a standing intraseasonal oscillation. Only the 1-m, 3-h configuration generated organized, northward-propagating convection similar to observations. Subdaily surface forcing produced stronger upper-ocean temperature anomalies in quadrature with anomalous convection, which likely affected lower-atmospheric stability ahead of the convection, causing propagation. Well-resolved air–sea coupling did not improve the eastward propagation of the boreal summer intraseasonal oscillation in this model.
Upper-ocean vertical mixing and diurnal variability in coupled models must be improved to accurately resolve and simulate tropical subseasonal variability. In HadKPP, the mere presence of air–sea coupling was not sufficient to generate an intraseasonal oscillation resembling observations.
Abstract
The northward-propagating intraseasonal (30–40 day) oscillation (NPISO) between active and break monsoon phases exerts a critical control on summer-season rainfall totals over India. Advances in diagnosing these events and comprehending the physical mechanisms behind them may hold the potential for improving their predictability. While previous studies have attempted to extract active and break events from reanalysis data to elucidate a composite life cycle, those studies have relied on first isolating the intraseasonal variability in the record (e.g., through bandpass filtering, removing harmonics, or empirical orthogonal function analysis). Additionally, the underlying physical processes that previous studies have proposed have varied, both among themselves and with studies using general circulation models.
A simple index is defined for diagnosing NPISO events in observations and reanalysis, based on lag correlations between outgoing longwave radiation (OLR) over India and over the equatorial Indian Ocean. This index is the first to use unfiltered OLR observations and so does not specifically isolate intraseasonal periods. A composite NPISO life cycle based on this index is similar to previous composites in OLR and surface winds, demonstrating that the dominance of the intraseasonal variability in the monsoon climate system eliminates the need for more complex methods (e.g., time filtering or EOF analysis) to identify the NPISO. This study is also among the first to examine the NPISO using a long-period record of high-resolution sea surface temperatures (SSTs) from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager. Application of this index to those SSTs demonstrates that SST anomalies exist in near quadrature with convection, as suggested by recent coupled model studies. Analysis of the phase relationships between atmospheric fields and SSTs indicates that the atmosphere likely forced the SST anomalies. The results of this lag-correlation analysis suggest that the oscillation serves as its own most reliable—and perhaps only—predictor, and that signals preceding an NPISO event appear first over the Indian subcontinent, not the equatorial Indian Ocean where the events originate.
Abstract
The northward-propagating intraseasonal (30–40 day) oscillation (NPISO) between active and break monsoon phases exerts a critical control on summer-season rainfall totals over India. Advances in diagnosing these events and comprehending the physical mechanisms behind them may hold the potential for improving their predictability. While previous studies have attempted to extract active and break events from reanalysis data to elucidate a composite life cycle, those studies have relied on first isolating the intraseasonal variability in the record (e.g., through bandpass filtering, removing harmonics, or empirical orthogonal function analysis). Additionally, the underlying physical processes that previous studies have proposed have varied, both among themselves and with studies using general circulation models.
A simple index is defined for diagnosing NPISO events in observations and reanalysis, based on lag correlations between outgoing longwave radiation (OLR) over India and over the equatorial Indian Ocean. This index is the first to use unfiltered OLR observations and so does not specifically isolate intraseasonal periods. A composite NPISO life cycle based on this index is similar to previous composites in OLR and surface winds, demonstrating that the dominance of the intraseasonal variability in the monsoon climate system eliminates the need for more complex methods (e.g., time filtering or EOF analysis) to identify the NPISO. This study is also among the first to examine the NPISO using a long-period record of high-resolution sea surface temperatures (SSTs) from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager. Application of this index to those SSTs demonstrates that SST anomalies exist in near quadrature with convection, as suggested by recent coupled model studies. Analysis of the phase relationships between atmospheric fields and SSTs indicates that the atmosphere likely forced the SST anomalies. The results of this lag-correlation analysis suggest that the oscillation serves as its own most reliable—and perhaps only—predictor, and that signals preceding an NPISO event appear first over the Indian subcontinent, not the equatorial Indian Ocean where the events originate.
Abstract
While the Indian monsoon exhibits substantial variability on interannual time scales, its intraseasonal variability (ISV) is of greater magnitude and hence of critical importance for monsoon predictability. This ISV comprises a 30–50-day northward-propagating oscillation (NPISO) between active and break events of enhanced and reduced rainfall, respectively, over the subcontinent. Recent studies have implied that coupled general circulation models (CGCMs) were better able to simulate the NPISO than their atmosphere-only counterparts (AGCMs). These studies have forced their AGCMs with SSTs from coupled integrations or observations from satellite-based infrared sounders, both of which underestimate the ISV of tropical SSTs.
The authors have forced the 1.25° × 0.83° Hadley Centre Atmospheric Model (HadAM3) with a daily, high-resolution, observed SST analysis from the United Kingdom National Center for Ocean Forecasting that contains greater ISV in the Indian Ocean than past products. One ensemble of simulations was forced by daily SSTs, a second with monthly means, and a third with 5-day means. The ensemble with daily SSTs displayed significantly greater variability in 30–50-day rainfall across the monsoon domain than the ensemble with monthly mean SSTs, variability similar to satellite-derived precipitation analyses. Individual ensemble members with daily SSTs contained intraseasonal events with a strength, a propagation speed, and an organization that closely matched observed events. When ensemble members with monthly mean SSTs displayed power in intraseasonal rainfall, the events were weak and disorganized, and they propagated too quickly. The ensemble with 5-day means had less intraseasonal rainfall variability than the ensemble with daily SSTs but still produced coherent NPISO-like events, indicating that SST variability at frequencies higher than 5 days contributes to but is not critical for simulations of the NPISO.
It is concluded that high-frequency SST anomalies not only increased variance in intraseasonal rainfall but helped to organize and maintain coherent NPISO-like convective events. Further, the results indicate that an AGCM can respond to realistic and frequent SST forcing to generate an NPISO that closely resembles observations. These results have important implications for simulating the NPISO in AGCMs and coupled climate models, as well as for predicting tropical ISV in short- and medium-range weather forecasts.
Abstract
While the Indian monsoon exhibits substantial variability on interannual time scales, its intraseasonal variability (ISV) is of greater magnitude and hence of critical importance for monsoon predictability. This ISV comprises a 30–50-day northward-propagating oscillation (NPISO) between active and break events of enhanced and reduced rainfall, respectively, over the subcontinent. Recent studies have implied that coupled general circulation models (CGCMs) were better able to simulate the NPISO than their atmosphere-only counterparts (AGCMs). These studies have forced their AGCMs with SSTs from coupled integrations or observations from satellite-based infrared sounders, both of which underestimate the ISV of tropical SSTs.
The authors have forced the 1.25° × 0.83° Hadley Centre Atmospheric Model (HadAM3) with a daily, high-resolution, observed SST analysis from the United Kingdom National Center for Ocean Forecasting that contains greater ISV in the Indian Ocean than past products. One ensemble of simulations was forced by daily SSTs, a second with monthly means, and a third with 5-day means. The ensemble with daily SSTs displayed significantly greater variability in 30–50-day rainfall across the monsoon domain than the ensemble with monthly mean SSTs, variability similar to satellite-derived precipitation analyses. Individual ensemble members with daily SSTs contained intraseasonal events with a strength, a propagation speed, and an organization that closely matched observed events. When ensemble members with monthly mean SSTs displayed power in intraseasonal rainfall, the events were weak and disorganized, and they propagated too quickly. The ensemble with 5-day means had less intraseasonal rainfall variability than the ensemble with daily SSTs but still produced coherent NPISO-like events, indicating that SST variability at frequencies higher than 5 days contributes to but is not critical for simulations of the NPISO.
It is concluded that high-frequency SST anomalies not only increased variance in intraseasonal rainfall but helped to organize and maintain coherent NPISO-like convective events. Further, the results indicate that an AGCM can respond to realistic and frequent SST forcing to generate an NPISO that closely resembles observations. These results have important implications for simulating the NPISO in AGCMs and coupled climate models, as well as for predicting tropical ISV in short- and medium-range weather forecasts.
Abstract
The southwest monsoon delivers over 70% of India’s annual rainfall and is crucial to the success of agriculture across much of South Asia. Monsoon precipitation is known to be sensitive to sea surface temperature (SST) in the Bay of Bengal (BoB). Here, we use a configuration of the Unified Model of the Met Office coupled to an ocean mixed layer model to investigate the role of upper-ocean features in the BoB on southwest monsoon precipitation. We focus on the pronounced zonal and meridional SST gradients characteristic of the BoB; the zonal gradient in particular has an as-yet unknown effect on monsoon rainfall. We find that the zonal SST gradient is responsible for a 50% decrease in rainfall over the southern BoB (approximately 5 mm day−1), and a 50% increase in rainfall over Bangladesh and northern India (approximately 1 mm day−1). This increase is remotely forced by a strengthening of the monsoon Hadley circulation. The meridional SST gradient acts to decrease precipitation over the BoB itself, similarly to the zonal SST gradient, but does not have comparable effects over land. The impacts of barrier layers and high-salinity subsurface water are also investigated, but neither has significant effects on monsoon precipitation in this model; the influence of barrier layers on precipitation is felt in the months after the southwest monsoon. Models should accurately represent oceanic processes that directly influence BoB SST, such as the BoB cold pool, in order to faithfully represent monsoon rainfall.
Abstract
The southwest monsoon delivers over 70% of India’s annual rainfall and is crucial to the success of agriculture across much of South Asia. Monsoon precipitation is known to be sensitive to sea surface temperature (SST) in the Bay of Bengal (BoB). Here, we use a configuration of the Unified Model of the Met Office coupled to an ocean mixed layer model to investigate the role of upper-ocean features in the BoB on southwest monsoon precipitation. We focus on the pronounced zonal and meridional SST gradients characteristic of the BoB; the zonal gradient in particular has an as-yet unknown effect on monsoon rainfall. We find that the zonal SST gradient is responsible for a 50% decrease in rainfall over the southern BoB (approximately 5 mm day−1), and a 50% increase in rainfall over Bangladesh and northern India (approximately 1 mm day−1). This increase is remotely forced by a strengthening of the monsoon Hadley circulation. The meridional SST gradient acts to decrease precipitation over the BoB itself, similarly to the zonal SST gradient, but does not have comparable effects over land. The impacts of barrier layers and high-salinity subsurface water are also investigated, but neither has significant effects on monsoon precipitation in this model; the influence of barrier layers on precipitation is felt in the months after the southwest monsoon. Models should accurately represent oceanic processes that directly influence BoB SST, such as the BoB cold pool, in order to faithfully represent monsoon rainfall.
