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Abstract
The diurnal variability and the environmental conditions that support the moisture resurgence of MJO events observed during the Cooperative Indian Ocean Experiment on Intraseasonal Variability (CINDY)/DYNAMO campaign in October–December 2011 are investigated using in situ observations and the cloud-resolving fully air–ocean–wave Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS). Spectral density and wavelet analysis of the total precipitable water (TPW) constructed from the DYNAMO soundings and TRMM satellite precipitation reveal a deep layer of vapor resurgence during the observed Wheeler and Hendon real-time multivariate MJO index phases 5–8 (MJO suppressed phase), which include diurnal, quasi-2-, quasi-3–4-, quasi-6–8-, and quasi-16-day oscillations. A similar oscillatory pattern is found in the DYNAMO moorings sea surface temperature analysis, suggesting a tightly coupled atmosphere and ocean system during these periods. COAMPS hindcast focused on the 12–16 November 2011 event suggests that both the diurnal sea surface temperature (SST) pumping and horizontal and vertical moisture transport associated with the westward propagating mixed Rossby–Gravity (MRG) waves play an essential role in the moisture resurgence during this period. Idealized COAMPS simulations of MRG waves are used to estimate the MRG and diurnal SST contributions to the overall moisture increase. These idealized MRG sensitivity experiments showed the TPW increase varies from 9% to 13% with the largest changes occurring in the simulations that included a diurnal SST variation of 2.5°C as observed.
Abstract
The diurnal variability and the environmental conditions that support the moisture resurgence of MJO events observed during the Cooperative Indian Ocean Experiment on Intraseasonal Variability (CINDY)/DYNAMO campaign in October–December 2011 are investigated using in situ observations and the cloud-resolving fully air–ocean–wave Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS). Spectral density and wavelet analysis of the total precipitable water (TPW) constructed from the DYNAMO soundings and TRMM satellite precipitation reveal a deep layer of vapor resurgence during the observed Wheeler and Hendon real-time multivariate MJO index phases 5–8 (MJO suppressed phase), which include diurnal, quasi-2-, quasi-3–4-, quasi-6–8-, and quasi-16-day oscillations. A similar oscillatory pattern is found in the DYNAMO moorings sea surface temperature analysis, suggesting a tightly coupled atmosphere and ocean system during these periods. COAMPS hindcast focused on the 12–16 November 2011 event suggests that both the diurnal sea surface temperature (SST) pumping and horizontal and vertical moisture transport associated with the westward propagating mixed Rossby–Gravity (MRG) waves play an essential role in the moisture resurgence during this period. Idealized COAMPS simulations of MRG waves are used to estimate the MRG and diurnal SST contributions to the overall moisture increase. These idealized MRG sensitivity experiments showed the TPW increase varies from 9% to 13% with the largest changes occurring in the simulations that included a diurnal SST variation of 2.5°C as observed.
Abstract
Cloud-resolving large-eddy simulations (LES) on a 500 km × 500 km periodic domain coupled to a thermodynamic ocean mixed layer are used to study the effect of large-scale moisture convergence M on the convective population and heat and moisture budgets of the tropical atmosphere, for several simulations with M representative of the suppressed, transitional, and active phases of the Madden–Julian oscillation (MJO). For a limited-area model without an imposed vertical velocity, M controls the overall vertical temperature structure. Moisture convergence equivalent to ~200 W m−2 (9 mm day−1) maintains the observed temperature profile above 5 km. Increased convective heating for simulations with higher M is partially offset by greater infrared cooling, suggesting a potential negative feedback that helps maintain the weak temperature gradient conditions observed in the tropics. Surface evaporation decreases as large-scale moisture convergence increases, and is only a minor component of the overall water budget for convective conditions representing the active phase of the MJO. Cold pools generated by evaporation of precipitation under convective conditions are gusty, with roughly double the wind stress of their surroundings. Consistent with observations, enhanced surface evaporation due to cold pool gusts is up to 40% of the mean, but has a small effect on the total moisture budget compared to the imposed large-scale moisture convergence.
Abstract
Cloud-resolving large-eddy simulations (LES) on a 500 km × 500 km periodic domain coupled to a thermodynamic ocean mixed layer are used to study the effect of large-scale moisture convergence M on the convective population and heat and moisture budgets of the tropical atmosphere, for several simulations with M representative of the suppressed, transitional, and active phases of the Madden–Julian oscillation (MJO). For a limited-area model without an imposed vertical velocity, M controls the overall vertical temperature structure. Moisture convergence equivalent to ~200 W m−2 (9 mm day−1) maintains the observed temperature profile above 5 km. Increased convective heating for simulations with higher M is partially offset by greater infrared cooling, suggesting a potential negative feedback that helps maintain the weak temperature gradient conditions observed in the tropics. Surface evaporation decreases as large-scale moisture convergence increases, and is only a minor component of the overall water budget for convective conditions representing the active phase of the MJO. Cold pools generated by evaporation of precipitation under convective conditions are gusty, with roughly double the wind stress of their surroundings. Consistent with observations, enhanced surface evaporation due to cold pool gusts is up to 40% of the mean, but has a small effect on the total moisture budget compared to the imposed large-scale moisture convergence.
Abstract
The local environment during the joint Atmospheric Radiation Measurement Program (ARM) Madden–Julian oscillation (MJO) Investigation Experiment (AMIE)–Cooperative Indian Ocean Experiment on Intraseasonal Variability in Year 2011 (CINDY2011)–Dynamics of the MJO (DYNAMO) field experiments caused frequent occurrences of sidelobe artifacts in the NCAR S-Pol radar dataset. Although generally low in radar reflectivity factor value (less than 5 dBZ), this contamination still proved problematic for Bragg scattering layer (BSL) analysis, generating numerous false BSL edge detections. In this paper, a statistical filtering technique is developed that effectively removes these false BSL edge detections, utilizing a new version of BSL analysis based on range–height indicator (RHI) data instead of plan position indicator data.
Abstract
The local environment during the joint Atmospheric Radiation Measurement Program (ARM) Madden–Julian oscillation (MJO) Investigation Experiment (AMIE)–Cooperative Indian Ocean Experiment on Intraseasonal Variability in Year 2011 (CINDY2011)–Dynamics of the MJO (DYNAMO) field experiments caused frequent occurrences of sidelobe artifacts in the NCAR S-Pol radar dataset. Although generally low in radar reflectivity factor value (less than 5 dBZ), this contamination still proved problematic for Bragg scattering layer (BSL) analysis, generating numerous false BSL edge detections. In this paper, a statistical filtering technique is developed that effectively removes these false BSL edge detections, utilizing a new version of BSL analysis based on range–height indicator (RHI) data instead of plan position indicator data.
Abstract
Using ERA-Interim global atmospheric reanalysis, an original tracking approach is developed to follow tropical low pressure systems from the early tropical depression (TD) stage up to possible intensification into developed tropical cyclones (TCs). The different TC stages are identified using the IBTrACS dataset. This approach detects many more TD initiations compared to IBTrACS alone and thus gives a more comprehensive dataset to study the cyclogenesis by considering separately TD initiations and the probability of intensification.
In the south Indian Ocean (SIO), the MJO modulation of the number of TCs is primarily due to the modulation of the number of TD initiations and secondarily to the probability of their intensification. The TD initiations are more probable at 55°, 75°, and 95°E and can be primarily attributed to the development of an unstable cyclonic meridional shear of the zonal wind at low levels. The reinforcement of this shear results from (i) a heat low, related to a precipitation anomaly, which triggers westerly winds equatorward of the initiation region and (ii) an easterly wind strengthening south of the initiation regions due either to a reinforcement of the subtropical high (for western and central SIO) or to a large-scale depression over the western Maritime Continent (for eastern SIO). Over the western and central SIO, the concomitance of precipitation and subtropical high anomalies at the origin of the shear reinforcement could be partly stochastic, giving a weaker relation with MJO and ENSO. Over the eastern SIO, the large-scale MJO (and ENSO) perturbation pattern alone can reinforce the shear, giving a larger modulation of the number of TD initiations.
Abstract
Using ERA-Interim global atmospheric reanalysis, an original tracking approach is developed to follow tropical low pressure systems from the early tropical depression (TD) stage up to possible intensification into developed tropical cyclones (TCs). The different TC stages are identified using the IBTrACS dataset. This approach detects many more TD initiations compared to IBTrACS alone and thus gives a more comprehensive dataset to study the cyclogenesis by considering separately TD initiations and the probability of intensification.
In the south Indian Ocean (SIO), the MJO modulation of the number of TCs is primarily due to the modulation of the number of TD initiations and secondarily to the probability of their intensification. The TD initiations are more probable at 55°, 75°, and 95°E and can be primarily attributed to the development of an unstable cyclonic meridional shear of the zonal wind at low levels. The reinforcement of this shear results from (i) a heat low, related to a precipitation anomaly, which triggers westerly winds equatorward of the initiation region and (ii) an easterly wind strengthening south of the initiation regions due either to a reinforcement of the subtropical high (for western and central SIO) or to a large-scale depression over the western Maritime Continent (for eastern SIO). Over the western and central SIO, the concomitance of precipitation and subtropical high anomalies at the origin of the shear reinforcement could be partly stochastic, giving a weaker relation with MJO and ENSO. Over the eastern SIO, the large-scale MJO (and ENSO) perturbation pattern alone can reinforce the shear, giving a larger modulation of the number of TD initiations.
Abstract
Lower-tropospheric (1000–700 hPa) moistening processes of the two Madden–Julian oscillations (MJOs) over the Indian Ocean during Dynamics of the MJO (DYNAMO)/Cooperative Indian Ocean Experiment on Intraseasonal Variability in Year 2011 (CINDY) are investigated by using soundings, operational assimilation, and satellite data. A scale-separated moisture budget is calculated at the sounding site by using time-decomposed wind and moisture fields. Each budget term is projected onto the intraseasonal moisture anomaly and its time tendency change. The projections and the corresponding temporal correlations are analyzed together with the temporal evolution of the budget terms to identify the dominant moistening process responsible for the MJO evolution. Results indicate that broad-scale advection by low-frequency and MJO flow and moisture fields are dominant moisture sources, while the residual of the moisture budget (−Q 2) is a dominant sink contributing to the tendency term (propagation) and intraseasonal moisture anomaly (growth and decay). Dividing their life cycles into four phases (suppressed, cloud developing, convective, and decaying phases), the two MJOs exhibit different budget balances in the premoistening stage from the suppressed phase to the cloud-developing phase when low-frequency vertical motion is downward in MJO1 but upward in MJO2. The corresponding drying and moistening are balanced by negative Q 2 (reevaporation in nonraining cloud) in MJO1 and positive Q 2 in MJO2. The result implies that low-frequency flow (>60 days) can affect the initiation of MJOs. The premoistening in the lower troposphere by boundary layer moisture convergence leading the deep convection is observed but only in the cloud-developing phase to convective phase of the MJOs. Nonlinear moisture advection by synoptic disturbances always acts as a diffusive term. It is the dominant moisture source in the suppress phase of the two MJOs.
Abstract
Lower-tropospheric (1000–700 hPa) moistening processes of the two Madden–Julian oscillations (MJOs) over the Indian Ocean during Dynamics of the MJO (DYNAMO)/Cooperative Indian Ocean Experiment on Intraseasonal Variability in Year 2011 (CINDY) are investigated by using soundings, operational assimilation, and satellite data. A scale-separated moisture budget is calculated at the sounding site by using time-decomposed wind and moisture fields. Each budget term is projected onto the intraseasonal moisture anomaly and its time tendency change. The projections and the corresponding temporal correlations are analyzed together with the temporal evolution of the budget terms to identify the dominant moistening process responsible for the MJO evolution. Results indicate that broad-scale advection by low-frequency and MJO flow and moisture fields are dominant moisture sources, while the residual of the moisture budget (−Q 2) is a dominant sink contributing to the tendency term (propagation) and intraseasonal moisture anomaly (growth and decay). Dividing their life cycles into four phases (suppressed, cloud developing, convective, and decaying phases), the two MJOs exhibit different budget balances in the premoistening stage from the suppressed phase to the cloud-developing phase when low-frequency vertical motion is downward in MJO1 but upward in MJO2. The corresponding drying and moistening are balanced by negative Q 2 (reevaporation in nonraining cloud) in MJO1 and positive Q 2 in MJO2. The result implies that low-frequency flow (>60 days) can affect the initiation of MJOs. The premoistening in the lower troposphere by boundary layer moisture convergence leading the deep convection is observed but only in the cloud-developing phase to convective phase of the MJOs. Nonlinear moisture advection by synoptic disturbances always acts as a diffusive term. It is the dominant moisture source in the suppress phase of the two MJOs.
Abstract
Atmospheric soundings, radar, and air–sea flux measurements collected during Dynamics of the Madden–Julian Oscillation (DYNAMO) are employed to study MJO convective onset (i.e., the transition from shallow to deep convection) in the tropical Indian Ocean. The findings indicate that moistening of the low–midtroposphere during the preonset stage of the MJO is achieved by simultaneous changes in the convective cloud population and large-scale circulation. Namely, cumuliform clouds deepen and grow in areal coverage as the drying by large-scale subsidence and horizontal (westerly) advection wane. The reduction of large-scale subsidence is tied to the reduction of column radiative cooling during the preonset stage, which ultimately links back to the evolving cloud population. While net column moistening in the preonset stage is tied to large-scale circulation changes, a new finding of this study is the high degree to which the locally driven diurnal cycle invigorates convective clouds and cumulus moistening each day. This diurnal cycle is manifest in a daytime growth of cumulus clouds (in both depth and areal coverage) in response to oceanic diurnal warm layers, which drive a daytime increase of the air–sea fluxes of heat and moisture. This diurnally modulated convective cloud field exhibits prominent mesoscale organization in the form of open cells and horizontal convective rolls. It is hypothesized that the diurnal cycle and mesoscale cloud organization characteristic of the preonset stage of the MJO represent two manners in which local processes promote more vigorous daily-mean column moistening than would otherwise occur.
Abstract
Atmospheric soundings, radar, and air–sea flux measurements collected during Dynamics of the Madden–Julian Oscillation (DYNAMO) are employed to study MJO convective onset (i.e., the transition from shallow to deep convection) in the tropical Indian Ocean. The findings indicate that moistening of the low–midtroposphere during the preonset stage of the MJO is achieved by simultaneous changes in the convective cloud population and large-scale circulation. Namely, cumuliform clouds deepen and grow in areal coverage as the drying by large-scale subsidence and horizontal (westerly) advection wane. The reduction of large-scale subsidence is tied to the reduction of column radiative cooling during the preonset stage, which ultimately links back to the evolving cloud population. While net column moistening in the preonset stage is tied to large-scale circulation changes, a new finding of this study is the high degree to which the locally driven diurnal cycle invigorates convective clouds and cumulus moistening each day. This diurnal cycle is manifest in a daytime growth of cumulus clouds (in both depth and areal coverage) in response to oceanic diurnal warm layers, which drive a daytime increase of the air–sea fluxes of heat and moisture. This diurnally modulated convective cloud field exhibits prominent mesoscale organization in the form of open cells and horizontal convective rolls. It is hypothesized that the diurnal cycle and mesoscale cloud organization characteristic of the preonset stage of the MJO represent two manners in which local processes promote more vigorous daily-mean column moistening than would otherwise occur.
Abstract
A multination joint field campaign called the Dynamics of MJO/Cooperative Indian Ocean Experiment on Intraseasonal Variability in Year 2011 (DYNAMO/CINDY2011) took place in the equatorial Indian Ocean (IO) in late 2011. During the campaign period, two strong MJO events occurred from the middle of October to the middle of December (referred to as MJO I and MJO II, respectively). Both the events were initiated over the western equatorial Indian Ocean (WIO) around 50°–60°E. Using multiple observational data products (ERA-Interim, the ECMWF final analysis, and NASA MERRA), the authors unveil specific processes that triggered the MJO convection in the WIO. It is found that, 10 days prior to MJO I initiation, a marked large-scale ascending motion anomaly appeared in the lower troposphere over the WIO. The cause of this intraseasonal vertical motion anomaly was attributed to anomalous warm advection by a cyclonic gyre anomaly over the northern IO. The MJO II initiation was preceded by a low-level specific humidity anomaly. This lower-tropospheric moistening was attributed to the advection of mean moisture by anomalous easterlies over the equatorial IO. The contrast of anomalous precursor winds at the equator (westerly versus easterly) implies different triggering mechanisms for the MJO I and II events. It was found that upper-tropospheric circumnavigating signals did not contribute the initiation of both the MJO events. The EOF-based real-time multivariate MJO (RMM) indices should not be used to determine MJO initiation time and location because they are primarily used to capture large zonal scale and eastward-propagating signals, not localized features.
Abstract
A multination joint field campaign called the Dynamics of MJO/Cooperative Indian Ocean Experiment on Intraseasonal Variability in Year 2011 (DYNAMO/CINDY2011) took place in the equatorial Indian Ocean (IO) in late 2011. During the campaign period, two strong MJO events occurred from the middle of October to the middle of December (referred to as MJO I and MJO II, respectively). Both the events were initiated over the western equatorial Indian Ocean (WIO) around 50°–60°E. Using multiple observational data products (ERA-Interim, the ECMWF final analysis, and NASA MERRA), the authors unveil specific processes that triggered the MJO convection in the WIO. It is found that, 10 days prior to MJO I initiation, a marked large-scale ascending motion anomaly appeared in the lower troposphere over the WIO. The cause of this intraseasonal vertical motion anomaly was attributed to anomalous warm advection by a cyclonic gyre anomaly over the northern IO. The MJO II initiation was preceded by a low-level specific humidity anomaly. This lower-tropospheric moistening was attributed to the advection of mean moisture by anomalous easterlies over the equatorial IO. The contrast of anomalous precursor winds at the equator (westerly versus easterly) implies different triggering mechanisms for the MJO I and II events. It was found that upper-tropospheric circumnavigating signals did not contribute the initiation of both the MJO events. The EOF-based real-time multivariate MJO (RMM) indices should not be used to determine MJO initiation time and location because they are primarily used to capture large zonal scale and eastward-propagating signals, not localized features.
Abstract
This study investigates the October and November MJO events observed during the Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year 2011 (CINDY)/Dynamics of the MJO (DYNAMO) field campaign through cloud-permitting numerical simulations. The simulations are compared to multiple observational datasets. The control simulation at 9-km horizontal grid spacing captures the slow eastward progression of both the October and November MJO events in surface precipitation, outgoing longwave radiation, zonal wind, humidity, and large-scale vertical motion. The vertical motion shows weak ascent in the leading edge of the MJO envelope, followed by deep ascent during the peak precipitation stage and trailed by a broad second baroclinic mode structure with ascent in the upper troposphere and descent in the lower troposphere. Both the simulation and the observations also show slow northward propagation components and tropical cyclone–like vortices after the passage of the MJO active phase. Comparison with synthesized observations from the northern sounding array shows that the model simulates the passage of the two MJO events over the sounding array region well. Sensitivity experiments to SST indicate that daily SST plays an important role for the November MJO event, but much less so for the October event.
Analysis of the moist static energy (MSE) budget shows that both advection and diabatic processes (i.e., surface fluxes and radiation) contribute to the development of the positive MSE anomaly in the active phase, but their contributions differ by how much they lead the precipitation peak. In comparison to the observational datasets used here, the model simulation may have a stronger surface flux feedback and a weaker radiative feedback. The normalized gross moist stability in the simulations shows an increase from near-zero values to ~0.8 during the active phase, similar to what is found in the observational datasets.
Abstract
This study investigates the October and November MJO events observed during the Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year 2011 (CINDY)/Dynamics of the MJO (DYNAMO) field campaign through cloud-permitting numerical simulations. The simulations are compared to multiple observational datasets. The control simulation at 9-km horizontal grid spacing captures the slow eastward progression of both the October and November MJO events in surface precipitation, outgoing longwave radiation, zonal wind, humidity, and large-scale vertical motion. The vertical motion shows weak ascent in the leading edge of the MJO envelope, followed by deep ascent during the peak precipitation stage and trailed by a broad second baroclinic mode structure with ascent in the upper troposphere and descent in the lower troposphere. Both the simulation and the observations also show slow northward propagation components and tropical cyclone–like vortices after the passage of the MJO active phase. Comparison with synthesized observations from the northern sounding array shows that the model simulates the passage of the two MJO events over the sounding array region well. Sensitivity experiments to SST indicate that daily SST plays an important role for the November MJO event, but much less so for the October event.
Analysis of the moist static energy (MSE) budget shows that both advection and diabatic processes (i.e., surface fluxes and radiation) contribute to the development of the positive MSE anomaly in the active phase, but their contributions differ by how much they lead the precipitation peak. In comparison to the observational datasets used here, the model simulation may have a stronger surface flux feedback and a weaker radiative feedback. The normalized gross moist stability in the simulations shows an increase from near-zero values to ~0.8 during the active phase, similar to what is found in the observational datasets.
Abstract
Previous observational analysis and modeling studies indicate that air–sea coupling plays an essential role in improving MJO simulations and extending MJO forecasting skills. However, whether the SST feedback plays an indispensable role for the existence of the MJO remains controversial, and the precise physical processes through which the SST feedback may lead to better MJO simulations and forecasts remain elusive.
The DYNAMO/Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year 2011 (CINDY) field campaign recently completed over the Indian Ocean reveals a new perspective and provides better data to improve understanding of the MJO. It is found that among the five MJO events that occurred during the DYNAMO/CINDY field campaign, only two MJO events (the November and March ones) have robust SST anomalies associated with them. For the other three MJO events (the October, December, and January ones), no coherent SST anomalies are observed. This observational scenario suggests that the roles of air–sea coupling on the MJO vary greatly from event to event.
To elucidate the varying roles of air–sea coupling on different MJO events, a suite of hindcast experiments was conducted with a particular focus on the October and November MJO events. The numerical results confirm that the October MJO is largely controlled by atmospheric internal dynamics, while the November MJO is strongly coupled with underlying ocean. For the November MJO event, the positive SST anomalies significantly improve MJO forecasting by enhancing the response of a Kelvin–Rossby wave couplet, which prolongs the feedback between convection and large-scale circulations, and thus favors the development of stratiform rainfall, in turn, facilitating the production of eddy available potential energy and significantly amplifying the intensity of the model November MJO.
Abstract
Previous observational analysis and modeling studies indicate that air–sea coupling plays an essential role in improving MJO simulations and extending MJO forecasting skills. However, whether the SST feedback plays an indispensable role for the existence of the MJO remains controversial, and the precise physical processes through which the SST feedback may lead to better MJO simulations and forecasts remain elusive.
The DYNAMO/Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year 2011 (CINDY) field campaign recently completed over the Indian Ocean reveals a new perspective and provides better data to improve understanding of the MJO. It is found that among the five MJO events that occurred during the DYNAMO/CINDY field campaign, only two MJO events (the November and March ones) have robust SST anomalies associated with them. For the other three MJO events (the October, December, and January ones), no coherent SST anomalies are observed. This observational scenario suggests that the roles of air–sea coupling on the MJO vary greatly from event to event.
To elucidate the varying roles of air–sea coupling on different MJO events, a suite of hindcast experiments was conducted with a particular focus on the October and November MJO events. The numerical results confirm that the October MJO is largely controlled by atmospheric internal dynamics, while the November MJO is strongly coupled with underlying ocean. For the November MJO event, the positive SST anomalies significantly improve MJO forecasting by enhancing the response of a Kelvin–Rossby wave couplet, which prolongs the feedback between convection and large-scale circulations, and thus favors the development of stratiform rainfall, in turn, facilitating the production of eddy available potential energy and significantly amplifying the intensity of the model November MJO.
Abstract
This study examines the DigiCORA and Global Climate Observing System Reference Upper-Air Network (GRUAN) humidity corrections of Vaisala RS92 radiosondes at three sites over the tropical Indian Ocean and surrounding areas during the Dynamics of the Madden–Julian Oscillation (DYNAMO) field campaign in 2011. The proprietary DigiCORA correction algorithm is built into the ground station software provided by Vaisala, whereas the GRUAN correction is an open source algorithm. Included in the GRUAN data product are uncertainty estimates for their corrections. This information is used to examine the statistical consistency of the various corrections.
In general, the algorithms produce a positive relative humidity (RH) correction that increases with altitude related primarily to a solar radiation dry bias adjustment. For example, in daytime soundings the relative RH correction increases from a few percent for temperatures >0°C to 20%–40% between 100 and 200 hPa. Comparison of corrected RH vertical profiles show only small differences (on the order of a few percent or less at any given level) between the DigiCORA and GRUAN algorithms, such that these corrections are considered to be statistically consistent at most levels.
In evaluating corrected humidity data with independent estimates of total precipitable water (TPW), good agreement was found at all sites between corrected sounding and ground-based microwave radiometer (MWR) estimates of TPW with mean differences ≤0.9 mm (or <2%), which is well within the uncertainty of these measurements. Overall, the correction algorithms examined herein perform well over a wide range of tropical moisture conditions.
Abstract
This study examines the DigiCORA and Global Climate Observing System Reference Upper-Air Network (GRUAN) humidity corrections of Vaisala RS92 radiosondes at three sites over the tropical Indian Ocean and surrounding areas during the Dynamics of the Madden–Julian Oscillation (DYNAMO) field campaign in 2011. The proprietary DigiCORA correction algorithm is built into the ground station software provided by Vaisala, whereas the GRUAN correction is an open source algorithm. Included in the GRUAN data product are uncertainty estimates for their corrections. This information is used to examine the statistical consistency of the various corrections.
In general, the algorithms produce a positive relative humidity (RH) correction that increases with altitude related primarily to a solar radiation dry bias adjustment. For example, in daytime soundings the relative RH correction increases from a few percent for temperatures >0°C to 20%–40% between 100 and 200 hPa. Comparison of corrected RH vertical profiles show only small differences (on the order of a few percent or less at any given level) between the DigiCORA and GRUAN algorithms, such that these corrections are considered to be statistically consistent at most levels.
In evaluating corrected humidity data with independent estimates of total precipitable water (TPW), good agreement was found at all sites between corrected sounding and ground-based microwave radiometer (MWR) estimates of TPW with mean differences ≤0.9 mm (or <2%), which is well within the uncertainty of these measurements. Overall, the correction algorithms examined herein perform well over a wide range of tropical moisture conditions.