Browse
Abstract
Reforecasts produced by the ECMWF Integrated Forecast System (IFS) were used to study heating and moistening processes associated with three MJO events over the equatorial Indian Ocean during the Dynamics of the Madden–Julian Oscillation (DYNAMO) field campaign. Variables produced by and derived from the IFS reforecast (IFS-RF) agree reasonably well with observations over the DYNAMO sounding arrays, and they vary smoothly from the western to eastern equatorial Indian Ocean. This lends confidence toward using IFS-RF as a surrogate of observations over the equatorial Indian Ocean outside the DYNAMO arrays. The apparent heat source Q 1 and apparent moisture sink Q 2 produced by IFS are primarily generated by parameterized cumulus convection, followed by microphysics and radiation. The vertical growth of positive Q 1 and Q 2 associated with the progression of MJO convection can be gradual, stepwise, or rapid depending on the event and its location over the broader equatorial Indian Ocean. The time for convective heating and drying to progress from shallow (800 hPa) to deep (400 hPa) can be <1 to 6 days. This growth time of heating and drying is usually short for convective processes alone but becomes longer when additional microphysical processes, such as evaporative moistening below convective and stratiform clouds, are in play. Three ratios are calculated to measure the possible role of radiative feedback in the MJO events: amplitudes of radiative versus convective heating rates, changes in radiative versus convective heating rates, and diabatic (with and without the radiative component) versus adiabatic heating rates. None of them unambiguously distinguishes the MJO from non-MJO convective events.
Abstract
Reforecasts produced by the ECMWF Integrated Forecast System (IFS) were used to study heating and moistening processes associated with three MJO events over the equatorial Indian Ocean during the Dynamics of the Madden–Julian Oscillation (DYNAMO) field campaign. Variables produced by and derived from the IFS reforecast (IFS-RF) agree reasonably well with observations over the DYNAMO sounding arrays, and they vary smoothly from the western to eastern equatorial Indian Ocean. This lends confidence toward using IFS-RF as a surrogate of observations over the equatorial Indian Ocean outside the DYNAMO arrays. The apparent heat source Q 1 and apparent moisture sink Q 2 produced by IFS are primarily generated by parameterized cumulus convection, followed by microphysics and radiation. The vertical growth of positive Q 1 and Q 2 associated with the progression of MJO convection can be gradual, stepwise, or rapid depending on the event and its location over the broader equatorial Indian Ocean. The time for convective heating and drying to progress from shallow (800 hPa) to deep (400 hPa) can be <1 to 6 days. This growth time of heating and drying is usually short for convective processes alone but becomes longer when additional microphysical processes, such as evaporative moistening below convective and stratiform clouds, are in play. Three ratios are calculated to measure the possible role of radiative feedback in the MJO events: amplitudes of radiative versus convective heating rates, changes in radiative versus convective heating rates, and diabatic (with and without the radiative component) versus adiabatic heating rates. None of them unambiguously distinguishes the MJO from non-MJO convective events.
Abstract
The atmospheric circulation depends on poorly understood interactions between the tropical atmospheric boundary layer (BL) and convection. The surface moist static energy (MSE) source (130 W m−2, of which 120 W m−2 is evaporation) to the tropical marine BL is balanced by upward MSE flux at the BL top that is the source for deep convection. Important for modeling tropical convection and circulation is whether MSE enters the free troposphere by dry turbulent processes originating within the boundary layer or by motions generated by moist deep convection in the free troposphere. Here, highly resolved observations of the BL quantify the MSE fluxes in approximate agreement with recent cloud-resolving models, but the fluxes depend on convective conditions. In convectively suppressed (weak precipitation) conditions, entrainment and downdraft fluxes export equal shares (60 W m−2) of MSE from the BL. Downdraft fluxes are found to increase 50%, and entrainment to decrease, under strongly convective conditions. Variable entrainment and downdraft MSE fluxes between the BL and convective clouds must both be considered for modeling the climate.
Abstract
The atmospheric circulation depends on poorly understood interactions between the tropical atmospheric boundary layer (BL) and convection. The surface moist static energy (MSE) source (130 W m−2, of which 120 W m−2 is evaporation) to the tropical marine BL is balanced by upward MSE flux at the BL top that is the source for deep convection. Important for modeling tropical convection and circulation is whether MSE enters the free troposphere by dry turbulent processes originating within the boundary layer or by motions generated by moist deep convection in the free troposphere. Here, highly resolved observations of the BL quantify the MSE fluxes in approximate agreement with recent cloud-resolving models, but the fluxes depend on convective conditions. In convectively suppressed (weak precipitation) conditions, entrainment and downdraft fluxes export equal shares (60 W m−2) of MSE from the BL. Downdraft fluxes are found to increase 50%, and entrainment to decrease, under strongly convective conditions. Variable entrainment and downdraft MSE fluxes between the BL and convective clouds must both be considered for modeling the climate.
Abstract
This study uses high-resolution rainfall estimates from the S-Polka radar during the DYNAMO field campaign to examine variability of the diurnal cycle of rainfall associated with MJO convection over the Indian Ocean. Two types of diurnal rainfall peaks were found: 1) a late afternoon rainfall peak associated with the diurnal peak in sea surface temperatures (SSTs) and surface fluxes and 2) an early to late morning rainfall peak associated with increased low-tropospheric moisture. Both peaks appear during the MJO suppressed phase, which tends to have stronger SST warming in the afternoon, while the morning peak is dominant during the MJO enhanced phase. The morning peak occurs on average at 0000–0300 LST during the MJO suppressed phase, while it is delayed until 0400–0800 LST during the MJO enhanced phase. This delay partly results from an increased upscale growth of deep convection to broader stratiform rain regions during the MJO enhanced phase. During the MJO suppressed phase, rainfall is dominated by deep and isolated convective cells that are short-lived and peak in association with either the afternoon SST warming or nocturnal moisture increase. This study demonstrates that knowledge of the evolution of cloud and rain types is critical to explaining the diurnal cycle of rainfall and its variability. Some insights into the role of the complex interactions between radiation, moisture, and clouds in driving the diurnal cycle of rainfall are also discussed.
Abstract
This study uses high-resolution rainfall estimates from the S-Polka radar during the DYNAMO field campaign to examine variability of the diurnal cycle of rainfall associated with MJO convection over the Indian Ocean. Two types of diurnal rainfall peaks were found: 1) a late afternoon rainfall peak associated with the diurnal peak in sea surface temperatures (SSTs) and surface fluxes and 2) an early to late morning rainfall peak associated with increased low-tropospheric moisture. Both peaks appear during the MJO suppressed phase, which tends to have stronger SST warming in the afternoon, while the morning peak is dominant during the MJO enhanced phase. The morning peak occurs on average at 0000–0300 LST during the MJO suppressed phase, while it is delayed until 0400–0800 LST during the MJO enhanced phase. This delay partly results from an increased upscale growth of deep convection to broader stratiform rain regions during the MJO enhanced phase. During the MJO suppressed phase, rainfall is dominated by deep and isolated convective cells that are short-lived and peak in association with either the afternoon SST warming or nocturnal moisture increase. This study demonstrates that knowledge of the evolution of cloud and rain types is critical to explaining the diurnal cycle of rainfall and its variability. Some insights into the role of the complex interactions between radiation, moisture, and clouds in driving the diurnal cycle of rainfall are also discussed.
Abstract
Dual-polarization radar rainfall estimation relationships have been extensively tested in continental and subtropical coastal rain regimes, with little testing over tropical oceans where the majority of rain on Earth occurs. A 1.5-yr Indo-Pacific warm pool disdrometer dataset was used to quantify the impacts of tropical oceanic drop-size distribution (DSD) variability on dual-polarization radar variables and their resulting utility for rainfall estimation. Variables that were analyzed include differential reflectivity Z dr; specific differential phase K dp; reflectivity Z h ; and specific attenuation A h . When compared with continental or coastal convection, tropical oceanic Z dr and K dp values were more often of low magnitude (<0.5 dB, <0.3° km−1) and Z dr was lower for a given K dp or Z h , consistent with observations of tropical oceanic DSDs being dominated by numerous, small, less-oblate drops. New X-, C-, and S-band R estimators were derived: R(K dp), R(A h ), R(K dp, ζ dr), R(z, ζ dr), and R(A h , ζ dr), which use linear versions of Z dr and Z h , namely ζ dr and z. Except for R(K dp), convective/stratiform partitioning was unnecessary for these estimators. All dual-polarization estimators outperformed updated R(z) estimators derived from the same dataset. The best-performing estimator was R(K dp, ζ dr), followed by R(A h , ζ dr) and R(z, ζ dr). The R error was further reduced in an updated blended algorithm choosing between R(z), R(z, ζ dr), R(K dp), and R(K dp, ζ dr) depending on Z dr > 0.25 dB and K dp > 0.3° km−1 thresholds. Because of these thresholds and the lack of hail, R(K dp) was never used. At all wavelengths, R(z) was still needed 43% of the time during light rain (R < 5 mm h−1, Z dr < 0.25 dB), composing 7% of the total rain volume. As wavelength decreased, R(K dp, ζ dr) was used more often, R(z, ζ dr) was used less often, and the blended algorithm became increasingly more accurate than R(z).
Abstract
Dual-polarization radar rainfall estimation relationships have been extensively tested in continental and subtropical coastal rain regimes, with little testing over tropical oceans where the majority of rain on Earth occurs. A 1.5-yr Indo-Pacific warm pool disdrometer dataset was used to quantify the impacts of tropical oceanic drop-size distribution (DSD) variability on dual-polarization radar variables and their resulting utility for rainfall estimation. Variables that were analyzed include differential reflectivity Z dr; specific differential phase K dp; reflectivity Z h ; and specific attenuation A h . When compared with continental or coastal convection, tropical oceanic Z dr and K dp values were more often of low magnitude (<0.5 dB, <0.3° km−1) and Z dr was lower for a given K dp or Z h , consistent with observations of tropical oceanic DSDs being dominated by numerous, small, less-oblate drops. New X-, C-, and S-band R estimators were derived: R(K dp), R(A h ), R(K dp, ζ dr), R(z, ζ dr), and R(A h , ζ dr), which use linear versions of Z dr and Z h , namely ζ dr and z. Except for R(K dp), convective/stratiform partitioning was unnecessary for these estimators. All dual-polarization estimators outperformed updated R(z) estimators derived from the same dataset. The best-performing estimator was R(K dp, ζ dr), followed by R(A h , ζ dr) and R(z, ζ dr). The R error was further reduced in an updated blended algorithm choosing between R(z), R(z, ζ dr), R(K dp), and R(K dp, ζ dr) depending on Z dr > 0.25 dB and K dp > 0.3° km−1 thresholds. Because of these thresholds and the lack of hail, R(K dp) was never used. At all wavelengths, R(z) was still needed 43% of the time during light rain (R < 5 mm h−1, Z dr < 0.25 dB), composing 7% of the total rain volume. As wavelength decreased, R(K dp, ζ dr) was used more often, R(z, ζ dr) was used less often, and the blended algorithm became increasingly more accurate than R(z).
Abstract
The daily evolution of temperature, stratification, and turbulence in the diurnal warm layer is described from time series measurements at low to moderate winds and strong insolation in the equatorial Indian Ocean. At 2.0-m depth, turbulence dissipation rates (ε) decreased by two orders of magnitude over 1–2 h immediately after sunrise, initiated by stratification caused by penetrating solar radiation prior to the change in sign of net surface heat flux from cooling to warming. Decaying turbulence preceded a period of rapid growth, in which ε increased by two orders of magnitude over a few hours, and following which ε approached a daytime period of near-steady state. Decay and growth rates predicted by a simplified turbulence model are consistent with those observed. During the daytime period of near-steady state, asymmetric temperature ramps were associated with enhanced ε, supporting the interpretation that this period represents a balance between buoyancy and shear production associated with a shear-driven response to trapping of momentum within the diurnal warm layer.
Abstract
The daily evolution of temperature, stratification, and turbulence in the diurnal warm layer is described from time series measurements at low to moderate winds and strong insolation in the equatorial Indian Ocean. At 2.0-m depth, turbulence dissipation rates (ε) decreased by two orders of magnitude over 1–2 h immediately after sunrise, initiated by stratification caused by penetrating solar radiation prior to the change in sign of net surface heat flux from cooling to warming. Decaying turbulence preceded a period of rapid growth, in which ε increased by two orders of magnitude over a few hours, and following which ε approached a daytime period of near-steady state. Decay and growth rates predicted by a simplified turbulence model are consistent with those observed. During the daytime period of near-steady state, asymmetric temperature ramps were associated with enhanced ε, supporting the interpretation that this period represents a balance between buoyancy and shear production associated with a shear-driven response to trapping of momentum within the diurnal warm layer.
Use of an End-to-End-Simulator to Analyze CYGNSSAbstract
Tropical convection during the onset of two Madden–Julian oscillation (MJO) events, in October and December of 2011, was simulated using the Weather Research and Forecasting (WRF) Model. Observations from the Dynamics of the MJO (DYNAMO) field campaign were assimilated into the WRF Model for an improved simulation of the mesoscale features of tropical convection. The WRF simulations with the assimilation of DYNAMO data produced realistic representations of mesoscale convection related to westerly wind bursts (WWBs) as well as downdraft-induced gust fronts. An end-to-end simulator (E2ES) for the Cyclone Global Navigation Satellite System (CYGNSS) mission was then applied to the WRF dataset, producing simulated CYGNSS near-surface wind speed data. The results indicated that CYGNSS could detect mesoscale wind features such as WWBs and gust fronts even in the presence of simulated heavy precipitation. This study has two primary conclusions as a consequence: 1) satellite simulators could be used to examine a mission’s capabilities for accomplishing secondary tasks and 2) CYGNSS likely will provide benefits to future tropical oceanic field campaigns that should be considered during their planning processes.
Abstract
Tropical convection during the onset of two Madden–Julian oscillation (MJO) events, in October and December of 2011, was simulated using the Weather Research and Forecasting (WRF) Model. Observations from the Dynamics of the MJO (DYNAMO) field campaign were assimilated into the WRF Model for an improved simulation of the mesoscale features of tropical convection. The WRF simulations with the assimilation of DYNAMO data produced realistic representations of mesoscale convection related to westerly wind bursts (WWBs) as well as downdraft-induced gust fronts. An end-to-end simulator (E2ES) for the Cyclone Global Navigation Satellite System (CYGNSS) mission was then applied to the WRF dataset, producing simulated CYGNSS near-surface wind speed data. The results indicated that CYGNSS could detect mesoscale wind features such as WWBs and gust fronts even in the presence of simulated heavy precipitation. This study has two primary conclusions as a consequence: 1) satellite simulators could be used to examine a mission’s capabilities for accomplishing secondary tasks and 2) CYGNSS likely will provide benefits to future tropical oceanic field campaigns that should be considered during their planning processes.
Abstract
The November 2011 Madden–Julian oscillation (MJO) event during the Dynamics of the MJO (DYNAMO) field campaign is simulated with the Regional Atmospheric Modeling System (RAMS) cloud-resolving model to examine the relationship between precipitation and surface latent heat flux (LHFLX) for deep convective clusters within the MJO and to discern the importance of surface LHFLX for organizing MJO convection. First, a simulation similar in size to the DYNAMO northern sounding array was run with interactive surface fluxes. Composites for precipitation, surface LHFLX, wind speed, wind vectors, and near-surface specific humidity are described for various-sized convective clusters during different MJO regimes. The precipitation–LHFLX relationship generally evolves as follows for an individual cluster. About 2 h before cluster identification, the maximum LHFLX occurs upwind of maximum precipitation. As cluster identification time is approached, LHFLX and precipitation maxima become coincident. At and after the cluster is identified, maximum LHFLXs move downwind of the precipitation maximum with a local minimum in LHFLXs behind the precipitation maximum.
Sensitivity simulations with spatially homogenized LHFLXs were then run to determine the impacts of local LHFLX feedbacks on convective organization. Using area-averaged convective versus stratiform precipitation fraction and a simple convective aggregation index to quantify organization, no systematic difference in convective organization was detected between the control and sensitivity simulations, suggesting that local LHFLX variability is not important to convective organization in this model. Implications of these results are discussed.
Abstract
The November 2011 Madden–Julian oscillation (MJO) event during the Dynamics of the MJO (DYNAMO) field campaign is simulated with the Regional Atmospheric Modeling System (RAMS) cloud-resolving model to examine the relationship between precipitation and surface latent heat flux (LHFLX) for deep convective clusters within the MJO and to discern the importance of surface LHFLX for organizing MJO convection. First, a simulation similar in size to the DYNAMO northern sounding array was run with interactive surface fluxes. Composites for precipitation, surface LHFLX, wind speed, wind vectors, and near-surface specific humidity are described for various-sized convective clusters during different MJO regimes. The precipitation–LHFLX relationship generally evolves as follows for an individual cluster. About 2 h before cluster identification, the maximum LHFLX occurs upwind of maximum precipitation. As cluster identification time is approached, LHFLX and precipitation maxima become coincident. At and after the cluster is identified, maximum LHFLXs move downwind of the precipitation maximum with a local minimum in LHFLXs behind the precipitation maximum.
Sensitivity simulations with spatially homogenized LHFLXs were then run to determine the impacts of local LHFLX feedbacks on convective organization. Using area-averaged convective versus stratiform precipitation fraction and a simple convective aggregation index to quantify organization, no systematic difference in convective organization was detected between the control and sensitivity simulations, suggesting that local LHFLX variability is not important to convective organization in this model. Implications of these results are discussed.
Abstract
Properties of the atmospheric boundary layer (ABL) over the central Indian Ocean are investigated using sounding data obtained during the Dynamics of the MJO (DYNAMO) field campaign in 2011/12. Observations from Gan Island on Addu Atoll, the R/V Revelle, and Malé in the Maldives are used to determine the frequency of well-mixed layers and their mean thermodynamic and wind profiles. Well-mixed boundary layers or mixed layers were observed 68% of the time from the three sites, ranging from ~100-m depth in recovering convective downdraft wakes to ~925 m in undisturbed conditions, with a mean depth of 508 m. At Revelle, the site most representative of the open ocean, the ABL displayed a distinct signal of modulation by the October and November MJOs, with mixed-layer depths gradually increasing through the suppressed phases as the sea surface temperature (SST) increased leading up to the active phases, followed by frequent ABL stabilization and shallow mixed layers in recovering wakes. A distinct diurnal cycle of mixed-layer depths and properties was observed during the MJO suppressed phases in response to a diurnal cycle of the SST under the mostly light-wind, clear-sky conditions. The daytime growth of the mixed layer contributed to an afternoon maximum in cumulus cloud development and rainfall during the suppressed periods by allowing more boundary layer thermals to reach their condensation levels. The variability of the ABL on time scales ranging from convective to diurnal to monthly poses significant challenges for numerical simulations of the MJO and the tropical circulation in general.
Abstract
Properties of the atmospheric boundary layer (ABL) over the central Indian Ocean are investigated using sounding data obtained during the Dynamics of the MJO (DYNAMO) field campaign in 2011/12. Observations from Gan Island on Addu Atoll, the R/V Revelle, and Malé in the Maldives are used to determine the frequency of well-mixed layers and their mean thermodynamic and wind profiles. Well-mixed boundary layers or mixed layers were observed 68% of the time from the three sites, ranging from ~100-m depth in recovering convective downdraft wakes to ~925 m in undisturbed conditions, with a mean depth of 508 m. At Revelle, the site most representative of the open ocean, the ABL displayed a distinct signal of modulation by the October and November MJOs, with mixed-layer depths gradually increasing through the suppressed phases as the sea surface temperature (SST) increased leading up to the active phases, followed by frequent ABL stabilization and shallow mixed layers in recovering wakes. A distinct diurnal cycle of mixed-layer depths and properties was observed during the MJO suppressed phases in response to a diurnal cycle of the SST under the mostly light-wind, clear-sky conditions. The daytime growth of the mixed layer contributed to an afternoon maximum in cumulus cloud development and rainfall during the suppressed periods by allowing more boundary layer thermals to reach their condensation levels. The variability of the ABL on time scales ranging from convective to diurnal to monthly poses significant challenges for numerical simulations of the MJO and the tropical circulation in general.
Abstract
Through a series of convection-permitting regional-scale ensembles based on the Weather Research and Forecasting (WRF) Model, this study investigates the predictability of multiscale weather and convectively coupled equatorial waves during the active phase of a Madden–Julian oscillation (MJO) event over the Indian Ocean from 12 October to 12 November 2011. It is found that the practical predictability limit, estimated by the spread of the ensemble perturbed with realistic initial and boundary uncertainties, is as much as 8 days for horizontal winds, temperature, and humidity for scales larger than 2000 km that include equatorial Rossby, Kelvin, inertia–gravity, and mixed Rossby–gravity waves. The practical predictability limit decreases rapidly as scale decreases, resulting in a predictable time scale less than 1 day for scales smaller than 200 km. Through further experiments using minute initial and boundary perturbations an order of magnitude smaller than the current realistic uncertainties, the intrinsic predictability limit for tropical weather at larger scales (>2000 km) is estimated to be achievable beyond 2 weeks, but the limit is likely still less than 3 days for the small scales (<200 km).
Abstract
Through a series of convection-permitting regional-scale ensembles based on the Weather Research and Forecasting (WRF) Model, this study investigates the predictability of multiscale weather and convectively coupled equatorial waves during the active phase of a Madden–Julian oscillation (MJO) event over the Indian Ocean from 12 October to 12 November 2011. It is found that the practical predictability limit, estimated by the spread of the ensemble perturbed with realistic initial and boundary uncertainties, is as much as 8 days for horizontal winds, temperature, and humidity for scales larger than 2000 km that include equatorial Rossby, Kelvin, inertia–gravity, and mixed Rossby–gravity waves. The practical predictability limit decreases rapidly as scale decreases, resulting in a predictable time scale less than 1 day for scales smaller than 200 km. Through further experiments using minute initial and boundary perturbations an order of magnitude smaller than the current realistic uncertainties, the intrinsic predictability limit for tropical weather at larger scales (>2000 km) is estimated to be achievable beyond 2 weeks, but the limit is likely still less than 3 days for the small scales (<200 km).
Abstract
The Madden–Julian oscillation (MJO), a planetary-scale eastward-propagating coherent structure with periods of 30–60 days, is a prominent manifestation of intraseasonal variability in the tropical atmosphere. It is widely presumed that small-scale moist cumulus convection is a critical part of its dynamics. However, the recent results from high-resolution modeling as well as data analysis suggest that the MJO may be understood by dry dynamics to a leading-order approximation. Simple, further theoretical considerations presented herein suggest that if it is to be understood by dry dynamics, the MJO is most likely a strongly nonlinear solitary Rossby wave. Under a global quasigeostrophic equivalent-barotropic formulation, modon theory provides such analytic solutions. Stability and the longevity of the modon solutions are investigated with a global shallow-water model. The preferred modon solutions with the greatest longevities compare well overall with the observed MJO in scale and phase velocity within the factors.
Abstract
The Madden–Julian oscillation (MJO), a planetary-scale eastward-propagating coherent structure with periods of 30–60 days, is a prominent manifestation of intraseasonal variability in the tropical atmosphere. It is widely presumed that small-scale moist cumulus convection is a critical part of its dynamics. However, the recent results from high-resolution modeling as well as data analysis suggest that the MJO may be understood by dry dynamics to a leading-order approximation. Simple, further theoretical considerations presented herein suggest that if it is to be understood by dry dynamics, the MJO is most likely a strongly nonlinear solitary Rossby wave. Under a global quasigeostrophic equivalent-barotropic formulation, modon theory provides such analytic solutions. Stability and the longevity of the modon solutions are investigated with a global shallow-water model. The preferred modon solutions with the greatest longevities compare well overall with the observed MJO in scale and phase velocity within the factors.
