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- Author or Editor: Wei Li x
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Abstract
This study investigates anvils from thick, nonprecipitating clouds associated with deep convection as observed in the tropics by the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) during the 10-yr period, 1998–2007. Anvils observable by the PR occur, on average, 5 out of every 100 days within grid boxes with 2.5° resolution and with a conditional areal coverage of 1.5%. Unconditional areal coverage is only a few tenths of a percent. Anvils also had an average 17-dBZ echo top of ∼8.5 km and an average thickness of ∼2.7 km. Anvils were usually higher and thicker over land compared to ocean, and occurred most frequently over Africa, the Maritime Continent, and Panama. Anvil properties were intimately tied to the properties of the parent convection. In particular, anvil area and echo-top heights were highly correlated to convective rain area. The next best predictor for anvil areal coverage and echo tops was convective echo tops, while convective reflectivities had the weakest correlation. Strong upper-level wind shear also may be associated with anvil occurrence over land, especially when convection regularly attains echo-top heights greater than 7 km. Some tropical land regions, especially those affected by monsoon circulations, experience significant seasonal variability in anvil properties—strong interannual anvil variability occurs over the central Pacific because of the El Niño–Southern Oscillation. Compared to the CloudSat Cloud Profiling Radar, the TRMM PR underestimates anvil-top height by an average of ∼5 km and underestimates their horizontal extent by an average factor of 4.
Abstract
This study investigates anvils from thick, nonprecipitating clouds associated with deep convection as observed in the tropics by the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) during the 10-yr period, 1998–2007. Anvils observable by the PR occur, on average, 5 out of every 100 days within grid boxes with 2.5° resolution and with a conditional areal coverage of 1.5%. Unconditional areal coverage is only a few tenths of a percent. Anvils also had an average 17-dBZ echo top of ∼8.5 km and an average thickness of ∼2.7 km. Anvils were usually higher and thicker over land compared to ocean, and occurred most frequently over Africa, the Maritime Continent, and Panama. Anvil properties were intimately tied to the properties of the parent convection. In particular, anvil area and echo-top heights were highly correlated to convective rain area. The next best predictor for anvil areal coverage and echo tops was convective echo tops, while convective reflectivities had the weakest correlation. Strong upper-level wind shear also may be associated with anvil occurrence over land, especially when convection regularly attains echo-top heights greater than 7 km. Some tropical land regions, especially those affected by monsoon circulations, experience significant seasonal variability in anvil properties—strong interannual anvil variability occurs over the central Pacific because of the El Niño–Southern Oscillation. Compared to the CloudSat Cloud Profiling Radar, the TRMM PR underestimates anvil-top height by an average of ∼5 km and underestimates their horizontal extent by an average factor of 4.
Abstract
The variability and predictability of tropical cyclone genesis frequency (TCGF) during 1973–2010 at both basinwide and sub-basin scales in the northwest Pacific are investigated using a 100-member ensemble of 60-km-resolution atmospheric simulations that are forced with observed sea surface temperatures (SSTs). The sub-basin regions include the South China Sea (SCS) and the four quadrants of the open ocean. The ensemble-mean results well reproduce the observed interannual-to-decadal variability of TCGF in the southeast (SE), northeast (NE), and northwest (NW) quadrants, but show limited skill in the SCS and the southwest (SW) quadrant. The skill in the SE and NE quadrants is responsible for the model’s ability to replicate the observed variability in basinwide TCGF. Above-normal TCGF is tied to enhanced relative SST (i.e., local SST minus tropical-mean SST) either locally or to the southeast of the corresponding regions in both the observations and ensemble mean for the SE, NE, and NW quadrants, but only in the ensemble mean for the SCS and the SW quadrant. These results demonstrate the strong SST control of TCGF in the SE, NE, and NW quadrants; both empirical and theoretical analyses suggest that ensembles of ∼10, 20, 35, and 15 members can capture the SST-forced TCGF variability in these three sub-basin regions and the entire basin, respectively. In the SW quadrant and the SCS, TCGF contains excessive noise, particularly in the observations, and thus shows low predictability. The variability and predictability of the large-scale atmospheric environment and synoptic-scale disturbances and their contributions to those of TCGF are also discussed.
Abstract
The variability and predictability of tropical cyclone genesis frequency (TCGF) during 1973–2010 at both basinwide and sub-basin scales in the northwest Pacific are investigated using a 100-member ensemble of 60-km-resolution atmospheric simulations that are forced with observed sea surface temperatures (SSTs). The sub-basin regions include the South China Sea (SCS) and the four quadrants of the open ocean. The ensemble-mean results well reproduce the observed interannual-to-decadal variability of TCGF in the southeast (SE), northeast (NE), and northwest (NW) quadrants, but show limited skill in the SCS and the southwest (SW) quadrant. The skill in the SE and NE quadrants is responsible for the model’s ability to replicate the observed variability in basinwide TCGF. Above-normal TCGF is tied to enhanced relative SST (i.e., local SST minus tropical-mean SST) either locally or to the southeast of the corresponding regions in both the observations and ensemble mean for the SE, NE, and NW quadrants, but only in the ensemble mean for the SCS and the SW quadrant. These results demonstrate the strong SST control of TCGF in the SE, NE, and NW quadrants; both empirical and theoretical analyses suggest that ensembles of ∼10, 20, 35, and 15 members can capture the SST-forced TCGF variability in these three sub-basin regions and the entire basin, respectively. In the SW quadrant and the SCS, TCGF contains excessive noise, particularly in the observations, and thus shows low predictability. The variability and predictability of the large-scale atmospheric environment and synoptic-scale disturbances and their contributions to those of TCGF are also discussed.
Abstract
This study evaluates the performance of models from phase 5 and phase 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6) by comparing feedbacks in models with those inferred from observations. Overall, we find no systematic disagreements between the feedbacks in the model ensembles and feedbacks inferred from observations, although there is a wide range in the ability of individual models to reproduce the observations. In particular, 40 of 52 models have best estimates that fall within the uncertainty of the observed total feedback. We quantify two sources of uncertainty in the model ensembles: 1) the structural difference, due to the differences in model parameterizations, and 2) the unforced pattern effect, due to unforced variability, and find that both are important when comparing with an 18-yr observational dataset. We perform the comparison using two energy balance frameworks: the traditional energy balance framework, in which it is assumed that changes in energy balance are controlled by changes in global average surface temperatures, and an alternative framework that assumes the changes in energy balance are controlled by tropical atmospheric temperatures. We find that the alternative framework provides a more robust way of comparing the models with observations, with both smaller structural differences and smaller unforced pattern effect. However, when considering the relation of feedbacks in response to interannual variability and long-term warming, the traditional framework has advantages. There are no great differences between the CMIP5 and CMIP6 ensembles’ ability to reproduce the observed feedbacks.
Abstract
This study evaluates the performance of models from phase 5 and phase 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6) by comparing feedbacks in models with those inferred from observations. Overall, we find no systematic disagreements between the feedbacks in the model ensembles and feedbacks inferred from observations, although there is a wide range in the ability of individual models to reproduce the observations. In particular, 40 of 52 models have best estimates that fall within the uncertainty of the observed total feedback. We quantify two sources of uncertainty in the model ensembles: 1) the structural difference, due to the differences in model parameterizations, and 2) the unforced pattern effect, due to unforced variability, and find that both are important when comparing with an 18-yr observational dataset. We perform the comparison using two energy balance frameworks: the traditional energy balance framework, in which it is assumed that changes in energy balance are controlled by changes in global average surface temperatures, and an alternative framework that assumes the changes in energy balance are controlled by tropical atmospheric temperatures. We find that the alternative framework provides a more robust way of comparing the models with observations, with both smaller structural differences and smaller unforced pattern effect. However, when considering the relation of feedbacks in response to interannual variability and long-term warming, the traditional framework has advantages. There are no great differences between the CMIP5 and CMIP6 ensembles’ ability to reproduce the observed feedbacks.
Abstract
Compared to precipitation extremes calculated from a high-resolution daily observational dataset in China during 1960–2005, simulations in 31 climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) have been quantitatively assessed using skill-score metrics. Four extreme precipitation indices, including the total precipitation (PRCPTOT), maximum consecutive dry days (CDD), precipitation intensity (SDII), and fraction of total rainfall from heavy events (R95T) are analyzed. Results show that CMIP5 models still have wet biases in western and northern China. Especially in western China, the models’ median relative error is about 120% for PRCPTOT; the 25th and 75th percentile errors are of 70% and 220%, respectively. However, there are dry biases in southeastern China, where the underestimation of PRCPTOT reach 200 mm. The performance of CMIP5 models is quite different between western and eastern China. The simulations are more reliable in the east than in the west in terms of spatial pattern and interannual variability. In the east, precipitation indices are more consistent with observations, and the spread among models is smaller. The multimodel ensemble constructed from a selection of the most skillful models shows improved behavior compared to the all-model ensemble. The wet bias in western and northern China and dry bias over southeastern China are all decreased. The median of errors for PRCPTOT has a decrease of 69% and 17% in the west and east, respectively. The good reproduction of the southwesterlies along the east coast of the Arabian Peninsula is revealed to be the main factor explaining the improvement of precipitation patterns and extreme events.
Abstract
Compared to precipitation extremes calculated from a high-resolution daily observational dataset in China during 1960–2005, simulations in 31 climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) have been quantitatively assessed using skill-score metrics. Four extreme precipitation indices, including the total precipitation (PRCPTOT), maximum consecutive dry days (CDD), precipitation intensity (SDII), and fraction of total rainfall from heavy events (R95T) are analyzed. Results show that CMIP5 models still have wet biases in western and northern China. Especially in western China, the models’ median relative error is about 120% for PRCPTOT; the 25th and 75th percentile errors are of 70% and 220%, respectively. However, there are dry biases in southeastern China, where the underestimation of PRCPTOT reach 200 mm. The performance of CMIP5 models is quite different between western and eastern China. The simulations are more reliable in the east than in the west in terms of spatial pattern and interannual variability. In the east, precipitation indices are more consistent with observations, and the spread among models is smaller. The multimodel ensemble constructed from a selection of the most skillful models shows improved behavior compared to the all-model ensemble. The wet bias in western and northern China and dry bias over southeastern China are all decreased. The median of errors for PRCPTOT has a decrease of 69% and 17% in the west and east, respectively. The good reproduction of the southwesterlies along the east coast of the Arabian Peninsula is revealed to be the main factor explaining the improvement of precipitation patterns and extreme events.
Abstract
Superimposed on a warming trend, Arctic winter surface air temperature (SAT) exhibits substantial interannual variability, the underlying mechanisms of which are unclear, especially with regard to the role of sea ice variations and atmospheric processes. Here, atmospheric reanalysis data and idealized atmospheric model simulations are used to reveal the mechanisms by which sea ice variations and atmospheric anomalous conditions affect interannual variations in wintertime Arctic SAT. Results show that near-surface interannual warming in the Arctic is accompanied by comparable warming throughout large parts of the Arctic troposphere and large-scale anomalous atmospheric circulation patterns. Within the Arctic, changes in large-scale atmospheric circulations due to internal atmospheric variability explain a substantial fraction of interannual variation in SAT and tropospheric temperatures, which lead to an increase in moisture and downward longwave radiation, with the rest likely coming from sea ice–related and other surface processes. Arctic winter sea ice loss allows the ocean to release more heat and moisture, which enhances Arctic warming; however, this effect on SAT is confined to the ice-retreat area and has a limited influence on large-scale atmospheric circulations.
Abstract
Superimposed on a warming trend, Arctic winter surface air temperature (SAT) exhibits substantial interannual variability, the underlying mechanisms of which are unclear, especially with regard to the role of sea ice variations and atmospheric processes. Here, atmospheric reanalysis data and idealized atmospheric model simulations are used to reveal the mechanisms by which sea ice variations and atmospheric anomalous conditions affect interannual variations in wintertime Arctic SAT. Results show that near-surface interannual warming in the Arctic is accompanied by comparable warming throughout large parts of the Arctic troposphere and large-scale anomalous atmospheric circulation patterns. Within the Arctic, changes in large-scale atmospheric circulations due to internal atmospheric variability explain a substantial fraction of interannual variation in SAT and tropospheric temperatures, which lead to an increase in moisture and downward longwave radiation, with the rest likely coming from sea ice–related and other surface processes. Arctic winter sea ice loss allows the ocean to release more heat and moisture, which enhances Arctic warming; however, this effect on SAT is confined to the ice-retreat area and has a limited influence on large-scale atmospheric circulations.
Abstract
The present article is the second part of a study on the extreme precipitation indices over China in CMIP5 models that perform a probabilistic projection of future precipitation indices with reference to the period 1986–2005. This is realized with a rank-based weighting method. The ranking of the 25 models is done according to their performance in simulating rainfall indices in present-day climate. Such weights are used to form a weighted ensemble for future climate projection. Results show that, compared to the unweighted raw ensemble, the projection with the weighted scheme is more credible, as the signal-to-noise ratio (SNR) of indices is larger from the weighted ensemble. From the beginning of the mid-twenty-first century, changes of wet indices with probability >0.5 increase significantly, especially over western China and the Yellow–Huai River basin, where the changes of all wet indices are in excess of 10%, the increase of total precipitation (PRCPTOT) can reach up to 20% over western China at the end of twenty-first century, and the SNR of PRCPTOT and precipitation intensity (SDII) is the highest at those two regions. This indicates that the precipitation in those regions has a high reliability to become more extreme. The maximum consecutive dry days (CDD) decreases throughout the north of 30°N, which shows that drought conditions in northern China would be reduced, and they are more likely to increase in southern China. However, the SNR for projection of CDD is less than 1.0 almost everywhere. Such a situation seems related to a strengthening of the East Asian summer monsoon and the associated northward shift of the monsoon front.
Abstract
The present article is the second part of a study on the extreme precipitation indices over China in CMIP5 models that perform a probabilistic projection of future precipitation indices with reference to the period 1986–2005. This is realized with a rank-based weighting method. The ranking of the 25 models is done according to their performance in simulating rainfall indices in present-day climate. Such weights are used to form a weighted ensemble for future climate projection. Results show that, compared to the unweighted raw ensemble, the projection with the weighted scheme is more credible, as the signal-to-noise ratio (SNR) of indices is larger from the weighted ensemble. From the beginning of the mid-twenty-first century, changes of wet indices with probability >0.5 increase significantly, especially over western China and the Yellow–Huai River basin, where the changes of all wet indices are in excess of 10%, the increase of total precipitation (PRCPTOT) can reach up to 20% over western China at the end of twenty-first century, and the SNR of PRCPTOT and precipitation intensity (SDII) is the highest at those two regions. This indicates that the precipitation in those regions has a high reliability to become more extreme. The maximum consecutive dry days (CDD) decreases throughout the north of 30°N, which shows that drought conditions in northern China would be reduced, and they are more likely to increase in southern China. However, the SNR for projection of CDD is less than 1.0 almost everywhere. Such a situation seems related to a strengthening of the East Asian summer monsoon and the associated northward shift of the monsoon front.
Abstract
The Pacific–North American (PNA) pattern and the North Atlantic Oscillation (NAO) are known to contain a tropical sea surface temperature (SST)-forced component. This study examines the sensitivity of the wintertime NAO and PNA to patterns of tropical SST anomalies using a linear statistical–dynamic method. The NAO index is sensitive to SST anomalies over the tropical Indian Ocean, the central Pacific Ocean, and the Caribbean Sea, and the PNA index is sensitive to SST anomalies over the tropical Pacific and Indian Oceans. The NAO and PNA patterns can be reproduced well by combining the linear operator with the consistent SST anomaly over the Indian Ocean and the Niño-4 regions, respectively, suggesting that these are the most efficient ocean basins that force the teleconnection patterns. During the period of 1950–2000, the NAO time series reconstructed by using SST anomalies over the Indian Ocean + Niño-4 region + Caribbean Sea or the Indian Ocean + Niño-4 region is significantly correlated with the observation. Using a cross-spectral analysis, the NAO index is coherent with the SST forcing over the Indian Ocean at a significant 3-yr period and a less significant 10-yr period, with the Indian Ocean SST leading by about a quarter phase. Unsurprisingly, the PNA index is most coherent with the Niño-4 SST at 4–5-yr periods. When compared with the observation, the NAO variability from the linear reconstruction is better reproduced than that of the coupled model, which is better than the Atmospheric Model Intercomparison Project (AMIP) run, while the PNA variability from the AMIP simulations is better than that of the reconstruction, which is better than the coupled model run.
Abstract
The Pacific–North American (PNA) pattern and the North Atlantic Oscillation (NAO) are known to contain a tropical sea surface temperature (SST)-forced component. This study examines the sensitivity of the wintertime NAO and PNA to patterns of tropical SST anomalies using a linear statistical–dynamic method. The NAO index is sensitive to SST anomalies over the tropical Indian Ocean, the central Pacific Ocean, and the Caribbean Sea, and the PNA index is sensitive to SST anomalies over the tropical Pacific and Indian Oceans. The NAO and PNA patterns can be reproduced well by combining the linear operator with the consistent SST anomaly over the Indian Ocean and the Niño-4 regions, respectively, suggesting that these are the most efficient ocean basins that force the teleconnection patterns. During the period of 1950–2000, the NAO time series reconstructed by using SST anomalies over the Indian Ocean + Niño-4 region + Caribbean Sea or the Indian Ocean + Niño-4 region is significantly correlated with the observation. Using a cross-spectral analysis, the NAO index is coherent with the SST forcing over the Indian Ocean at a significant 3-yr period and a less significant 10-yr period, with the Indian Ocean SST leading by about a quarter phase. Unsurprisingly, the PNA index is most coherent with the Niño-4 SST at 4–5-yr periods. When compared with the observation, the NAO variability from the linear reconstruction is better reproduced than that of the coupled model, which is better than the Atmospheric Model Intercomparison Project (AMIP) run, while the PNA variability from the AMIP simulations is better than that of the reconstruction, which is better than the coupled model run.
Abstract
This study compares the impacts of Arctic sea ice decline on the Atlantic meridional overturning circulation (AMOC) in two configurations of the Community Earth System Model with different horizontal resolution. In a suite of model experiments, we impose radiative imbalance at the ice surface, replicating a loss of sea ice cover comparable to that observed during 1979–2014, and we find dramatic differences in the AMOC response between the two models. In the lower-resolution configuration, the AMOC weakens by about one-third over the first 100 years, approaching a new quasi-equilibrium. By contrast, in the higher-resolution configuration, the AMOC weakens by ~10% during the first 20–30 years followed by a full recovery driven by invigorated deep water formation in the Labrador Sea and adjacent regions. We investigate these differences using a diagnostic AMOC stability indicator, which reflects the AMOC freshwater transport in and out of the basin and hence the strength of the basin-scale salt-advection feedback. This indicator suggests that the AMOC in the lower-resolution model is less stable and more sensitive to surface perturbations, as confirmed by hosing experiments mimicking Arctic freshening due to sea ice decline. Differences between the models’ mean states, including the Atlantic Ocean mean surface freshwater fluxes, control the differences in AMOC stability. Our results demonstrate that the AMOC stability indicator is indeed useful for evaluating AMOC sensitivity to perturbations. We emphasize that, despite the differences in the long-term adjustment, both models simulate a multidecadal AMOC weakening caused by Arctic sea ice decline, relevant to climate change.
Abstract
This study compares the impacts of Arctic sea ice decline on the Atlantic meridional overturning circulation (AMOC) in two configurations of the Community Earth System Model with different horizontal resolution. In a suite of model experiments, we impose radiative imbalance at the ice surface, replicating a loss of sea ice cover comparable to that observed during 1979–2014, and we find dramatic differences in the AMOC response between the two models. In the lower-resolution configuration, the AMOC weakens by about one-third over the first 100 years, approaching a new quasi-equilibrium. By contrast, in the higher-resolution configuration, the AMOC weakens by ~10% during the first 20–30 years followed by a full recovery driven by invigorated deep water formation in the Labrador Sea and adjacent regions. We investigate these differences using a diagnostic AMOC stability indicator, which reflects the AMOC freshwater transport in and out of the basin and hence the strength of the basin-scale salt-advection feedback. This indicator suggests that the AMOC in the lower-resolution model is less stable and more sensitive to surface perturbations, as confirmed by hosing experiments mimicking Arctic freshening due to sea ice decline. Differences between the models’ mean states, including the Atlantic Ocean mean surface freshwater fluxes, control the differences in AMOC stability. Our results demonstrate that the AMOC stability indicator is indeed useful for evaluating AMOC sensitivity to perturbations. We emphasize that, despite the differences in the long-term adjustment, both models simulate a multidecadal AMOC weakening caused by Arctic sea ice decline, relevant to climate change.
Abstract
In recent years the semiarid region of northern China, which has total annual precipitation between 200 and 500 mm, has shown signs of severe desertification. Intensive theoretical and observational studies are currently underway to examine the climate changes and other contributing factors. In this study, we used the 1951–86 monthly precipitation measurements in this region to study their fluctuations and relationship with the El Niño/Southern Oscillation. Three main features are identified: 1) a 2–3 year quasi-periodic fluctuation, 2) a tendency for rainfall deficiency for the whole region during ENSO years, and 3) a significant correlation between the precipitation fluctuation in the southern part of this region and Southern Oscillation index, with the former lagging the latter by 2–5 months. These features are also evident from analysis of the proxy data during the last hundred years. Discussions on the possible link between the precipitation fluctuation, the summer monsoon, the western Pacific subtropical high, and ENSO are also presented.
Abstract
In recent years the semiarid region of northern China, which has total annual precipitation between 200 and 500 mm, has shown signs of severe desertification. Intensive theoretical and observational studies are currently underway to examine the climate changes and other contributing factors. In this study, we used the 1951–86 monthly precipitation measurements in this region to study their fluctuations and relationship with the El Niño/Southern Oscillation. Three main features are identified: 1) a 2–3 year quasi-periodic fluctuation, 2) a tendency for rainfall deficiency for the whole region during ENSO years, and 3) a significant correlation between the precipitation fluctuation in the southern part of this region and Southern Oscillation index, with the former lagging the latter by 2–5 months. These features are also evident from analysis of the proxy data during the last hundred years. Discussions on the possible link between the precipitation fluctuation, the summer monsoon, the western Pacific subtropical high, and ENSO are also presented.
Abstract
This study investigates modulation of El Niño–Southern Oscillation (ENSO) on the Madden–Julian oscillation (MJO) propagation during boreal winter. Results show that the spatiotemporal evolution of MJO manifests as a fast equatorially symmetric propagation from the Indian Ocean to the equatorial western Pacific (EWP) during El Niño, whereas the MJO during La Niña is very slow and tends to frequently “detour” via the southern Maritime Continent (MC). The westward group velocity of the MJO is also more significant during El Niño. Based on the dynamics-oriented diagnostics, it is found that, during El Niño, the much stronger leading suppressed convection over the EWP excites a significant front Walker cell, which further triggers a larger Kelvin wave easterly wind anomaly and premoistening and heating effects to the east. However, the equatorial Rossby wave to the west tends to decouple with the MJO convection. Both effects can result in fast MJO propagation. The opposite holds during La Niña. A column-integrated moisture budget analysis reveals that the sea surface temperature anomaly driving both the eastward and equatorward gradients of the low-frequency moisture anomaly during El Niño, as opposed to the westward and poleward gradients during La Niña, induces moist advection over the equatorial eastern MC–EWP region due to the intraseasonal wind anomaly and therefore enhances the zonal asymmetry of the moisture tendency, supporting fast propagation. The role of nonlinear advection by synoptic-scale Kelvin waves is also nonnegligible in distinguishing fast and slow MJO modes. This study emphasizes the crucial roles of dynamical wave feedback and moisture–convection feedback in modulating the MJO propagation by ENSO.
Abstract
This study investigates modulation of El Niño–Southern Oscillation (ENSO) on the Madden–Julian oscillation (MJO) propagation during boreal winter. Results show that the spatiotemporal evolution of MJO manifests as a fast equatorially symmetric propagation from the Indian Ocean to the equatorial western Pacific (EWP) during El Niño, whereas the MJO during La Niña is very slow and tends to frequently “detour” via the southern Maritime Continent (MC). The westward group velocity of the MJO is also more significant during El Niño. Based on the dynamics-oriented diagnostics, it is found that, during El Niño, the much stronger leading suppressed convection over the EWP excites a significant front Walker cell, which further triggers a larger Kelvin wave easterly wind anomaly and premoistening and heating effects to the east. However, the equatorial Rossby wave to the west tends to decouple with the MJO convection. Both effects can result in fast MJO propagation. The opposite holds during La Niña. A column-integrated moisture budget analysis reveals that the sea surface temperature anomaly driving both the eastward and equatorward gradients of the low-frequency moisture anomaly during El Niño, as opposed to the westward and poleward gradients during La Niña, induces moist advection over the equatorial eastern MC–EWP region due to the intraseasonal wind anomaly and therefore enhances the zonal asymmetry of the moisture tendency, supporting fast propagation. The role of nonlinear advection by synoptic-scale Kelvin waves is also nonnegligible in distinguishing fast and slow MJO modes. This study emphasizes the crucial roles of dynamical wave feedback and moisture–convection feedback in modulating the MJO propagation by ENSO.
