Diagnosing Seasonal Forecast Skill of the Indian Ocean Dipole Mode Using Model AnalogsAbstract
A retrospective tropical Indian Ocean dipole mode (IOD) hindcast for 1958–2014 was conducted using 20 models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), with a model-based analog forecast (MAF) method. In the MAF approach, forecast ensembles are extracted from preexisting model simulations by finding the states that initially best match an observed anomaly and tracking their subsequent evolution, with no additional model integrations. By optimizing the key factors in the MAF method, we suggest that the optimal domain for the analog criteria should be concentrated in the tropical Indian Ocean region for IOD predictions. Including external forcing trends improves the skills of the east and west poles of the IOD, but not the IOD prediction itself. The MAF IOD prediction showed comparable skills to the assimilation-initialized hindcast, with skillful predictions corresponding to a 4- and 3-month lead, respectively. The IOD forecast skill had significant decadal variations during the 55-yr period, with low skill after the early 2000s and before 1985 and high skill during 1985–2000. This work offers a computational efficient and practical approach for seasonal prediction of the tropical Indian Ocean sea surface temperature.
Abstract
A retrospective tropical Indian Ocean dipole mode (IOD) hindcast for 1958–2014 was conducted using 20 models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), with a model-based analog forecast (MAF) method. In the MAF approach, forecast ensembles are extracted from preexisting model simulations by finding the states that initially best match an observed anomaly and tracking their subsequent evolution, with no additional model integrations. By optimizing the key factors in the MAF method, we suggest that the optimal domain for the analog criteria should be concentrated in the tropical Indian Ocean region for IOD predictions. Including external forcing trends improves the skills of the east and west poles of the IOD, but not the IOD prediction itself. The MAF IOD prediction showed comparable skills to the assimilation-initialized hindcast, with skillful predictions corresponding to a 4- and 3-month lead, respectively. The IOD forecast skill had significant decadal variations during the 55-yr period, with low skill after the early 2000s and before 1985 and high skill during 1985–2000. This work offers a computational efficient and practical approach for seasonal prediction of the tropical Indian Ocean sea surface temperature.
Abstract
The effect of tropical cyclone (TC) size on TC-induced sea surface temperature (SST) cooling and subsequent TC intensification is an intriguing issue without much exploration. Via compositing satellite-observed SST over the western North Pacific during 2004–19, this study systematically examined the effect of storm size on the magnitude, spatial extension, and temporal evolution of TC-induced SST anomalies (SSTA). Consequential influence on TC intensification is also explored. Among the various TC wind radii, SSTA are found to be most sensitive to the 34-kt wind radius (R34) (1 kt ≈ 0.51 m s−1). Generally, large TCs generate stronger and more widespread SSTA than small TCs (for category 1–2 TCs, R34: ∼270 vs 160 km; SSTA: −1.7° vs −0.9°C). Despite the same effect on prolonging residence time of TC winds, the effect of doubling R34 on SSTA is more profound than halving translation speed, due to more wind energy input into the upper ocean. Also differing from translation speed, storm size has a rather modest effect on the rightward shift and timing of maximum cooling. This study further demonstrates that storm size regulates TC intensification through an oceanic pathway: large TCs tend to induce stronger SST cooling and are exposed to the cooling for a longer time, both of which reduce the ocean’s enthalpy supply and thereby diminish TC intensification. For larger TCs experiencing stronger SST cooling, the probability of rapid intensification is half of smaller TCs. The presented results suggest that accurately specifying storm size should lead to improved cooling effect estimation and TC intensity prediction.
Significance Statement
Storm size has long been speculated to play a crucial role in modulating the TC self-induced sea surface temperature (SST) cooling and thus potentially influence TC intensification through ocean negative feedback. Nevertheless, systematic analysis is lacking. Here we show that larger TCs tend to generate stronger SST cooling and have longer exposure to the cooling effect, both of which enhance the strength of the negative feedback. Consequently, larger TCs undergo weaker intensification and are less likely to experience rapid intensification than smaller TCs. These results demonstrate that storm size can influence TC intensification not only from the atmospheric pathway, but also via the oceanic pathway. Accurate characterization of this oceanic pathway in coupled models is important to accurately forecast TC intensity.
Abstract
The effect of tropical cyclone (TC) size on TC-induced sea surface temperature (SST) cooling and subsequent TC intensification is an intriguing issue without much exploration. Via compositing satellite-observed SST over the western North Pacific during 2004–19, this study systematically examined the effect of storm size on the magnitude, spatial extension, and temporal evolution of TC-induced SST anomalies (SSTA). Consequential influence on TC intensification is also explored. Among the various TC wind radii, SSTA are found to be most sensitive to the 34-kt wind radius (R34) (1 kt ≈ 0.51 m s−1). Generally, large TCs generate stronger and more widespread SSTA than small TCs (for category 1–2 TCs, R34: ∼270 vs 160 km; SSTA: −1.7° vs −0.9°C). Despite the same effect on prolonging residence time of TC winds, the effect of doubling R34 on SSTA is more profound than halving translation speed, due to more wind energy input into the upper ocean. Also differing from translation speed, storm size has a rather modest effect on the rightward shift and timing of maximum cooling. This study further demonstrates that storm size regulates TC intensification through an oceanic pathway: large TCs tend to induce stronger SST cooling and are exposed to the cooling for a longer time, both of which reduce the ocean’s enthalpy supply and thereby diminish TC intensification. For larger TCs experiencing stronger SST cooling, the probability of rapid intensification is half of smaller TCs. The presented results suggest that accurately specifying storm size should lead to improved cooling effect estimation and TC intensity prediction.
Significance Statement
Storm size has long been speculated to play a crucial role in modulating the TC self-induced sea surface temperature (SST) cooling and thus potentially influence TC intensification through ocean negative feedback. Nevertheless, systematic analysis is lacking. Here we show that larger TCs tend to generate stronger SST cooling and have longer exposure to the cooling effect, both of which enhance the strength of the negative feedback. Consequently, larger TCs undergo weaker intensification and are less likely to experience rapid intensification than smaller TCs. These results demonstrate that storm size can influence TC intensification not only from the atmospheric pathway, but also via the oceanic pathway. Accurate characterization of this oceanic pathway in coupled models is important to accurately forecast TC intensity.
Abstract
The generation of multiple wave couplets with deep tropospheric downdrafts/updrafts by convection is explored through idealized 2D moist numerical simulations as well as dry experiments with prescribed artificial latent heating. These wave couplets are capable of horizontally propagating over a long distance at a fast speed with vertical motions spanning the entire troposphere. The timing of wave generation is determined by the variation in the local heating rate, which arose from the imbalances among latent heating, nonlinear advection, and adiabatic heating/cooling. The amplitudes of wave couplets also correspond well with the strength of the local heating rate. The heat budget analysis highlights the crucial roles of both latent heating and nonlinear advection in the generation of the tropospheric wave couplets. Strong latent heating induces the thermodynamic imbalance and thus triggers waves. Meanwhile, latent heating also increases vertical motion in the source region and thus enhances nonlinear advection through transferring heat upward. Nonlinear advection, which has a comparable magnitude to latent heating in the upper troposphere, partially offsets the balancing effect of adiabatic heating/cooling, and results in a more persistent imbalance at high levels, allowing for the emission of consecutive waves even when latent heating becomes weak. In the simulation with weak nonlinear advection, fewer wave couplets are found, as the effect of latent heating is more easily offset by adiabatic cooling before it weakens.
Significance Statement
The generation of gravity waves in the troposphere by convection is of significant importance in the fields of atmospheric science and meteorology. The waves play a crucial role in the initiation and organization of convection, and the parameterization of wave momentum flux in global numerical models. This study aimed to investigate the generation of wave couplets in the troposphere through idealized numerical simulations with varying prescribed latent heating. The results showed that gravity wave couplets were generated in succession as a result of the imbalances among latent heating, nonlinear advection, and adiabatic heating/cooling. This study highlighted an important but yet complex issue of gravity waves being generated within convection by nonlinear sources other than latent heating, which had been neglected in many recent studies on the topic. These findings deepened our understanding of convectively generated gravity waves and paved the way for coupled wave–convection relationship studies.
Abstract
The generation of multiple wave couplets with deep tropospheric downdrafts/updrafts by convection is explored through idealized 2D moist numerical simulations as well as dry experiments with prescribed artificial latent heating. These wave couplets are capable of horizontally propagating over a long distance at a fast speed with vertical motions spanning the entire troposphere. The timing of wave generation is determined by the variation in the local heating rate, which arose from the imbalances among latent heating, nonlinear advection, and adiabatic heating/cooling. The amplitudes of wave couplets also correspond well with the strength of the local heating rate. The heat budget analysis highlights the crucial roles of both latent heating and nonlinear advection in the generation of the tropospheric wave couplets. Strong latent heating induces the thermodynamic imbalance and thus triggers waves. Meanwhile, latent heating also increases vertical motion in the source region and thus enhances nonlinear advection through transferring heat upward. Nonlinear advection, which has a comparable magnitude to latent heating in the upper troposphere, partially offsets the balancing effect of adiabatic heating/cooling, and results in a more persistent imbalance at high levels, allowing for the emission of consecutive waves even when latent heating becomes weak. In the simulation with weak nonlinear advection, fewer wave couplets are found, as the effect of latent heating is more easily offset by adiabatic cooling before it weakens.
Significance Statement
The generation of gravity waves in the troposphere by convection is of significant importance in the fields of atmospheric science and meteorology. The waves play a crucial role in the initiation and organization of convection, and the parameterization of wave momentum flux in global numerical models. This study aimed to investigate the generation of wave couplets in the troposphere through idealized numerical simulations with varying prescribed latent heating. The results showed that gravity wave couplets were generated in succession as a result of the imbalances among latent heating, nonlinear advection, and adiabatic heating/cooling. This study highlighted an important but yet complex issue of gravity waves being generated within convection by nonlinear sources other than latent heating, which had been neglected in many recent studies on the topic. These findings deepened our understanding of convectively generated gravity waves and paved the way for coupled wave–convection relationship studies.
Abstract
In the absence of scattering, thermal contrast in the atmosphere is the key to infrared remote sensing. Without the thermal contrast, the amount of absorption will be identical to the amount of emission, making the atmospheric vertical structure undetectable using remote sensing techniques. Here we show that, even in such an isothermal atmosphere, the scattering of clouds can cause a distinguishable change in upwelling radiance at the top of the atmosphere. A two-stream analytical solution, as well as a budget analysis based on Monte-Carlo simulations, are used to offer a physical explanation of such influence on an idealized isothermal atmosphere by cloud scattering: it increases the chance of photons being absorbed by the atmosphere before they can reach the boundaries (both top and bottom), which leads to a reduction of TOA upwelling radiance. Actual sounding profiles and cloud properties inferred from satellite observations within six-hour timeframes are fed into a more realistic and comprehensive radiative transfer model to show such cloud scattering effect, under nearly isothermal circumstances in the lower troposphere, can lead to ~1 to 1.5 K decrease in brightness temperature for the nadir-view MODIS 8.5-μm channel. The study suggests that cloud scattering can provide signals useful for remote sensing applications even for such an isothermal environment.
Abstract
In the absence of scattering, thermal contrast in the atmosphere is the key to infrared remote sensing. Without the thermal contrast, the amount of absorption will be identical to the amount of emission, making the atmospheric vertical structure undetectable using remote sensing techniques. Here we show that, even in such an isothermal atmosphere, the scattering of clouds can cause a distinguishable change in upwelling radiance at the top of the atmosphere. A two-stream analytical solution, as well as a budget analysis based on Monte-Carlo simulations, are used to offer a physical explanation of such influence on an idealized isothermal atmosphere by cloud scattering: it increases the chance of photons being absorbed by the atmosphere before they can reach the boundaries (both top and bottom), which leads to a reduction of TOA upwelling radiance. Actual sounding profiles and cloud properties inferred from satellite observations within six-hour timeframes are fed into a more realistic and comprehensive radiative transfer model to show such cloud scattering effect, under nearly isothermal circumstances in the lower troposphere, can lead to ~1 to 1.5 K decrease in brightness temperature for the nadir-view MODIS 8.5-μm channel. The study suggests that cloud scattering can provide signals useful for remote sensing applications even for such an isothermal environment.
Abstract
Climate model projections of atmospheric circulation patterns, their frequency, and associated temperature and precipitation anomalies under a high-end global warming scenario are assessed over the Pacific Northwest of North America for the final three decades of the twenty-first century. Model simulations are from phase 6 of the Coupled Model Intercomparison Project (CMIP6) and circulation patterns are identified using the self-organizing maps (SOMs) approach, applied to 500-hPa geopotential height (Z500) anomalies. Overall, the range of projected circulation patterns is similar to that in the current climate, especially in winter, whereas in summer the models project a general reduction in the magnitude of Z500 anomalies. Significant changes in pattern frequencies are also projected in summer, with an overall decrease in the frequency of patterns with large Z500 anomalies. In winter, patterns historically associated with anomalously cold weather in northern latitudes are projected to warm the most, and in summer the largest temperature increases are projected over inland areas. Precipitation is found to increase across all seasons and most SOM patterns. However, some summer patterns that are associated with above-average precipitation in the current climate are projected to become significantly drier by the end of the century.
Significance Statement
This paper uses a novel method to analyze projections of large-scale atmospheric circulation over the Pacific Northwest of North America, reducing the uncertainty of changes to the circulation patterns over the region under a high-emissions scenario of global warming.
Abstract
Climate model projections of atmospheric circulation patterns, their frequency, and associated temperature and precipitation anomalies under a high-end global warming scenario are assessed over the Pacific Northwest of North America for the final three decades of the twenty-first century. Model simulations are from phase 6 of the Coupled Model Intercomparison Project (CMIP6) and circulation patterns are identified using the self-organizing maps (SOMs) approach, applied to 500-hPa geopotential height (Z500) anomalies. Overall, the range of projected circulation patterns is similar to that in the current climate, especially in winter, whereas in summer the models project a general reduction in the magnitude of Z500 anomalies. Significant changes in pattern frequencies are also projected in summer, with an overall decrease in the frequency of patterns with large Z500 anomalies. In winter, patterns historically associated with anomalously cold weather in northern latitudes are projected to warm the most, and in summer the largest temperature increases are projected over inland areas. Precipitation is found to increase across all seasons and most SOM patterns. However, some summer patterns that are associated with above-average precipitation in the current climate are projected to become significantly drier by the end of the century.
Significance Statement
This paper uses a novel method to analyze projections of large-scale atmospheric circulation over the Pacific Northwest of North America, reducing the uncertainty of changes to the circulation patterns over the region under a high-emissions scenario of global warming.
Abstract
The thermodynamic processes associated with convection in tropical African and northeastern Pacific easterly waves (AEWs and PEWs, respectively) are examined on the basis of empirical orthogonal functions (EOFs) and a plume buoyancy framework. Linear regression analysis reveals the relationship between temperature, moisture, buoyancy, and precipitation in EWs. Plume buoyancy is found to be highly correlated with rainfall in both AEWs and PEWs, and a near 1:1 relationship is found between a buoyancy-based diagnostic of rainfall and rainfall rates from ERA5. Close inspection of the contribution of moisture and temperature to plume buoyancy reveals that temperature and moisture contribute roughly equally to the buoyancy in AEWs, while moisture dominates the distribution of buoyancy in PEWs. A scale analysis is performed in order to understand the relative amplitudes of temperature and moisture in easterly waves. It is found that the smaller contribution of temperature to the thermodynamics of PEWs relative to AEWs is related to their slower propagation speed, which allows PEWs to more robustly adjust to weak temperature gradient (WTG) balance. The consistency of the buoyancy analysis and the scale analysis indicates that PEWs are moisture modes: waves in which water vapor plays a dominant role in their thermodynamics. AEWs, on the other hand, are mixed waves in which temperature and moisture play similar roles in their thermodynamics.
Abstract
The thermodynamic processes associated with convection in tropical African and northeastern Pacific easterly waves (AEWs and PEWs, respectively) are examined on the basis of empirical orthogonal functions (EOFs) and a plume buoyancy framework. Linear regression analysis reveals the relationship between temperature, moisture, buoyancy, and precipitation in EWs. Plume buoyancy is found to be highly correlated with rainfall in both AEWs and PEWs, and a near 1:1 relationship is found between a buoyancy-based diagnostic of rainfall and rainfall rates from ERA5. Close inspection of the contribution of moisture and temperature to plume buoyancy reveals that temperature and moisture contribute roughly equally to the buoyancy in AEWs, while moisture dominates the distribution of buoyancy in PEWs. A scale analysis is performed in order to understand the relative amplitudes of temperature and moisture in easterly waves. It is found that the smaller contribution of temperature to the thermodynamics of PEWs relative to AEWs is related to their slower propagation speed, which allows PEWs to more robustly adjust to weak temperature gradient (WTG) balance. The consistency of the buoyancy analysis and the scale analysis indicates that PEWs are moisture modes: waves in which water vapor plays a dominant role in their thermodynamics. AEWs, on the other hand, are mixed waves in which temperature and moisture play similar roles in their thermodynamics.
Abstract
For the tropical country of Sri Lanka, subseasonal variability in precipitation is both ecologically and societally relevant, influencing agricultural yields, natural hazard risk, energy production, and disease incidence. The primary driver of this subseasonal precipitation variability is the Madden–Julian oscillation (MJO). Here we investigate this influence on Sri Lankan precipitation across seasons, describing MJO-associated precipitation patterns and exploring the potential for MJO-informed subseasonal forecasts. We do so using 40-yr satellite-derived records of precipitation with high spatial resolution (from CHIRPS v2.0) and related meteorological and atmospheric fields (from ERA5 and MERRA-2). We find a direct MJO influence on precipitation corresponding to propagation of the MJO’s convectively active region and suppressed region near Sri Lanka, with the strength and spatial patterns of this influence differing across seasons. There are particularly strong impacts in the second intermonsoon (SIM; October–November) and southwest monsoon (SWM; May–September) seasons. During SIM the impacts are island-wide, but strongest in the northeast. During the SWM the absolute impacts are localized to the southwest, but the relative impacts (i.e., relative to precipitation climatology) are fairly uniform across the island. Moreover, we find significant associations between MJO phase and Sri Lankan precipitation at time scales of up to several weeks. Notably, these associations are stronger when using the OLR-based MJO index (OMI) rather than the more commonly used real-time multivariate MJO index (RMM). While the MJO associations we describe here arise from a highly simplified forecasting scheme, they provide a foundation and impetus for developing a more complete, MJO-informed precipitation forecast method.
Significance Statement
Rainfall variability at the subseasonal (weeks–months) time scale is critical to societal well-being, given its fundamental importance for agriculture, flood risk, hydropower generation, and disease incidence. Our work describes how such rainfall variability in Sri Lanka is impacted by the Madden–Julian oscillation, in which a region of enhanced rainfall and cloudiness, paired with a region of decreased rainfall and cloudiness, circles the globe every 30–60 days. Our results suggest that its influence on Sri Lankan rainfall may be strong enough that incorporating knowledge of the Madden–Julian oscillation into forecasts can improve the accuracy of rainfall prediction for Sri Lanka. Future work should develop a more comprehensive forecast method to assess viability in real-world forecasting scenarios.
Abstract
For the tropical country of Sri Lanka, subseasonal variability in precipitation is both ecologically and societally relevant, influencing agricultural yields, natural hazard risk, energy production, and disease incidence. The primary driver of this subseasonal precipitation variability is the Madden–Julian oscillation (MJO). Here we investigate this influence on Sri Lankan precipitation across seasons, describing MJO-associated precipitation patterns and exploring the potential for MJO-informed subseasonal forecasts. We do so using 40-yr satellite-derived records of precipitation with high spatial resolution (from CHIRPS v2.0) and related meteorological and atmospheric fields (from ERA5 and MERRA-2). We find a direct MJO influence on precipitation corresponding to propagation of the MJO’s convectively active region and suppressed region near Sri Lanka, with the strength and spatial patterns of this influence differing across seasons. There are particularly strong impacts in the second intermonsoon (SIM; October–November) and southwest monsoon (SWM; May–September) seasons. During SIM the impacts are island-wide, but strongest in the northeast. During the SWM the absolute impacts are localized to the southwest, but the relative impacts (i.e., relative to precipitation climatology) are fairly uniform across the island. Moreover, we find significant associations between MJO phase and Sri Lankan precipitation at time scales of up to several weeks. Notably, these associations are stronger when using the OLR-based MJO index (OMI) rather than the more commonly used real-time multivariate MJO index (RMM). While the MJO associations we describe here arise from a highly simplified forecasting scheme, they provide a foundation and impetus for developing a more complete, MJO-informed precipitation forecast method.
Significance Statement
Rainfall variability at the subseasonal (weeks–months) time scale is critical to societal well-being, given its fundamental importance for agriculture, flood risk, hydropower generation, and disease incidence. Our work describes how such rainfall variability in Sri Lanka is impacted by the Madden–Julian oscillation, in which a region of enhanced rainfall and cloudiness, paired with a region of decreased rainfall and cloudiness, circles the globe every 30–60 days. Our results suggest that its influence on Sri Lankan rainfall may be strong enough that incorporating knowledge of the Madden–Julian oscillation into forecasts can improve the accuracy of rainfall prediction for Sri Lanka. Future work should develop a more comprehensive forecast method to assess viability in real-world forecasting scenarios.
