AS1.10

Extreme precipitation is expected to increase with climate change at the Clausius-Clapeyron rate of approximately 7% per °C of warming; however, tropical cyclone (TC) precipitation may increase at a greater rate due to feedbacks between the storm dynamics and the thermodynamic increase in moisture. Previous modeling studies simulate increasing TC intensities with warming sea surface temperatures (SSTs), which may push the precipitation increase above the Clausius-Clapeyron rate. Recent work by the authors used the Community Atmosphere Model (CAM) in a state of radiative-convective equilibrium (RCE) with globally-uniform SSTs varying between 295 and 305 K to break down the TC precipitation response to warming into thermodynamic and dynamic contributions. Results showed that for 99th percentile TC precipitation, increases in atmospheric moisture (thermodynamics) contributed just over 66% of the precipitation increase while increases in TC intensity (dynamics) contributed about 20%. This work explores if the relationship between TC precipitation, SST, and storm intensities found in the RCE simulations holds for observations and high-resolution climate model simulations. The observations consist of TC tracks and intensities from the IBTrACS database, SSTs from the NOAA OISST dataset, and precipitation from the IMERG satellite product. The high-resolution climate model simulations are from the High Resolution Model Intercomparison Project (HighResMIP), a CMIP6-endorsed MIP that has both historical and future climate runs. The methodology involves extracting TC precipitation using an automated algorithm, binning TCs by relevant characteristics (i.e., their local-environment SSTs, intensities, and outer sizes), extracting various precipitation metrics from their precipitation fields, and calculating relationships between the precipitation metrics, TC characteristics, and SSTs. The goal is to use these relationships to project future TC precipitation changes under different future climate change scenarios using just changes in SST.

How to cite: Stansfield, A. and Reed, K.: Projecting Future Tropical Cyclone Precipitation Increases using a Hierarchical Modeling Framework, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6117, https://doi.org/10.5194/egusphere-egu22-6117, 2022.

In recent years, western Europe has been threatened by anomalous tropical cyclones, developed from tropical transition (TT) processes in which a baroclinic cyclone becomes in a fully barotropic cyclone. Thirty-three tropical transition events were identified in the North Atlantic basin during the period 1979-2019 using ERA5 and HURDAT datasets. The TTs show a favored seasonality covering 70% of total between September and November.

A TT climatology is built and analyzed using large-scale storm-centered composites to study their common features and highlighting their differences respect the long-term climatology. The results reveal that TT synoptic environment is mainly characterized by a trough at 300 hPa and a strong anticyclone located north of the cyclone. In addition, a previous westerlies meridional trough with quasigeostrophic forcing acts as precursor. As the ERA5 does not accurately represent the diabatic processes due to its horizontal resolution, the deepening of mean sea level pressure is not shown in the composites. The average Potential Vorticity 300-200 hPa (PV) shows a decreasing in the upper troposphere around the cyclones as the moment of TT is approaching, while the PV is increasing in the lower troposphere. This PV conjunction promotes low-level wind speed intensification around the cyclone center that is linked with differential diabatic heat source in the low troposphere.

How to cite: Calvo-Sancho, C., González-Alemán, J. J., Bolgiani, P., Santos-Muñoz, D., Farrán, J. I., Sastre, M., and Martín, M. L.: A Climatology of Tropical Transitions in the North Atlantic Ocean, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2395, https://doi.org/10.5194/egusphere-egu22-2395, 2022.

The direct detection — or tracking — of tropical cyclones (TC) in gridded datasets outputs from reanalyses or model simulations is required to assess TC statistics. This issue has been tackled independently by many modeling centers or research groups; hence there is little homogeneity in the existing methods. The trackers – i.e., the algorithms used to perform that tracking -- generally fall into one of two categories: physics-based or dynamics-based. Physics-based trackers use sea-level pressure as their primary tracking variable, with additional warm-core and intensity criteria, whereas dynamics-based trackers use kinematic variables such as vorticity.

We compared four trackers taken from both categories and that we deem very different from one another in terms of their formulation: UZ (sometimes called TempestExtremes, Ullrich et al. 2021), OWZ (Tory et al. 2013), TRACK (Hodges et al. 2017) and CNRM (Chauvin et al. 2016). We assessed their performances by tracking TCs in ERA5 and comparing the outcome to the IBTrACS database – a collection of TC observations from several meteorological centers worldwide.

We find typical detection rates ranging from 70 to 80% and False Alarm (FA) rates ranging from 20 to 50% depending on the trackers. Based on the finding that a large proportion of these FAs are extra-tropical cyclones, we adapted an existing filtering method that relies on the relative positions of the detected tracks and the upper troposphere subtropical jet. When applied identically to the four trackers, it reduces FA rates to figures ranging from 9 to 30% while leaving detection rates unchanged.

Even though we were able to find most of the observed TCs in ERA5, we find, in agreement with several results in the recent literature, that their intensity is largely underestimated. However, and perhaps counterintuitively, there is no simple attenuation relationship between observed and reanalyzed TCs: for example, the strongest observed TCs are found in ERA5 with intensities covering almost the entire TC intensity scale.

We conclude by providing guidelines applicable when faced with the question of which tracker(s) to use depending on the research question. In particular, we show that using several trackers is not necessarily relevant for optimizing detection skills but combining them can be helpful to gain insight into different aspects of TCs in the same dataset.

Finally, we used the expertise gained above to track TCs in a set of HighResMIP simulations performed with the IPSL-CM7A model at different resolutions. In agreement with recent results, we find that the ability to simulate TCs improves significantly with resolution. Even though the intensity of simulated TCs remains too weak on average, the global statistics approach observations for simulations at a few tens of kilometers of horizontal resolution.

How to cite: Bourdin, S., Fromang, S., Dulac, W., Cattiaux, J., and Chauvin, F.: Tracking tropical cyclones in reanalysis and simulations: guidelines from an intercomparison of four algorithms, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1806, https://doi.org/10.5194/egusphere-egu22-1806, 2022.

In this study, we have examined meteorological drivers that led to the genesis of tropical cyclone Seroja. Developing over the Maritime Continent and in April 2021, it brought historic flooding and landslides to southern Indonesia, East Timor and Western Australia’s Mid West region. Seroja was the first tropical cyclone to have a significant impact on Indonesian land.

We have shown that the genesis of tropical cyclone Seroja in the region of Timor and Suvu Seas was associated with enhanced Equatorial Convection on March 27, 2021 which was preceded by warm sea surface anomalies (SSTs) in that region. The Equatorial Convection was related to Madden-Julian Oscillation (MJO) mode: it developed on the leading edge of MJO where SSTs were high. We have also investigated the role of tropical waves in the development of tropical cyclone Seroja. The interaction between convectively coupled equatorial Rossby wave and three convectively coupled Kelvin waves embedded within the larger-scale envelope of the MJO, provided a supportive environment for this extreme event. The Equatorial Convection that eventually became tropical cyclone Seroja moved southwest, boosted by environmental cyclonic vorticity associated with Rossby Wave. Each of the three Kelvin Waves that arrived over the Maritime Continent had a unique contribution in this event; structuring the convection, winds and precipitation patterns.

How to cite: Latos, B., Peyrillé, P., Lefort, T., Flatau, M., Flatau, P., Baranowski, D., Florida, N., Permana, D., and Szkółka, W.: The role of tropical waves in the genesis of tropical cyclone Seroja, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-566, https://doi.org/10.5194/egusphere-egu22-566, 2022.

The vertical structure of precipitation and its evolution during mid-level dry-air intrusion (DAI) for landfalling tropical cyclones (LTCs) over China in the past 10 years were examined using several observed TRMM PR products and a reanalysis dataset. We show that in the outer region where the environmental mid-level dry air intrudes more easily, the process of environmental DAI has an important effect on the vertical structure and precipitation of LTCs through promoting substantially stratiform precipitation while inhibiting infrequent intense convective precipitation. Although the total mean rain rate does not change much during the DAI period, both the mean rain rate and area of stratiform precipitation are almost doubled, while the convective precipitation halves compared to the situation prior to the DAI period. Also, the vertical structure of precipitation relative to the vertical wind shear (VWS) is modulated by the dry air, with a clear stratiform precipitation structure in the DAI region, though the dry-air distribution of LTCs does not depend on the direction of the VWS but rather on the synoptic environmental collocation. Further analysis shows that the mid-level DAI is favorable to the generation of stratiform precipitation through producing moderate mid-level convergence and less intense low-level subsidence, which contribute to the mid-level spin-up without spinning down the low-level circulation. At the same time, it helps maintaining the uniform stratiform precipitation above the melting layer and homogenizing the low-level circulation, and thus boosts the development of stratiform precipitation in intensity and area in the outer region.

How to cite: Shu, S.: How does dry air influence the precipitation of landfalling tropical cyclones, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1492, https://doi.org/10.5194/egusphere-egu22-1492, 2022.

Tropical cyclones (TCs) are some of the most dangerous natural hazards that human civilisation is exposed to. Effective adaptation for coastal regions requires reliable forecasts of risks for the season. Natural Hazard models such as the Synthetic Tropical cyclOne genRation Model (STORM) developed by Bloemendaal et al. (2020) are a common choice to assess risks without the expense of running a full forecast model. STORM has so far only been compared to observations on a basin-wide scale. However, for useful risk assessments in coastal regions, the model is also required to be skilful on much smaller spatial scales. We examine landfall statistics in some key areas such as the Gulf of Mexico.  Numerous indices for TC genesis have been developed over the past decades that aim to derive genesis locations from meteorological variables. None of the currently operational indices however is capable of realistically modelling interannual variability in genesis numbers and locations. Here, we compare the purely statistical Poisson interannual variability to that observed. Using Poisson regression between observations and driving environmental variables such as relative sea surface temperatures and wind shear, we then produce a new index for genesis location that has better predictive skill on interannual time scales.

How to cite: Ermis, S. and Toumi, R.: Modelling interannual variability in a tropical cyclone hazard model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1725, https://doi.org/10.5194/egusphere-egu22-1725, 2022.

The diurnal variation of tropical oceanic convection has been recognized for decades. Recent observational studies have also documented a diurnal cycle associated with the upper-level cirrus canopy of tropical cyclone (TC) measured using the infrared brightness temperature from satellites. However, TC canopy clouds are not always coupled tightly with deep convection. The overshooting top (OT) is an appropriate proxy for deep convection with an intense updraft that can penetrate the tropopause, which has an important influence on typhoon intensification. So far, there are no observational evidences for the relationship between diurnal intensity variation and OT occurrences in TC.

We analyze the diurnal variation of OTs within 45 western North Pacific typhoons, using 9003 Himawari-8 satellite images and a unique OT detection algorithm. We examine the distribution of OTs in different types of typhoons in terms of both intensity and intensity change and the relationship between the OTs and typhoon intensification on a diurnal scale. Our results show that a greater OT density occurs in strong typhoons and rapid intensification (RI) typhoons. Moreover, RI typhoons showed greater diurnal variation than non-RI typhoons. The diurnal cycle of OT density in RI typhoons was in phase with the intensification of the typhoon, with the maximum in the early morning. These observational results are consistent with recently published case study simulations of the diurnal radiation effects on TC in both realistic and idealized scenarios. Therefore, OT density can become a potentially effective indicator to estimate diurnal changes in typhoon intensity.

How to cite: Tang, X., Sun, L., Zhuge, X., Tan, Z.-M., and Fang, J.: Diurnal Variation of Clouds Overshooting Tops Detected by Himawari-8 Satellite and Typhoon Intensity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3862, https://doi.org/10.5194/egusphere-egu22-3862, 2022.

Tropical storms that develop over the North Indian Ocean basin pose a major threat to the extensive peninsular coastlines teeming with overpopulated cities and vast areas of low-lying farmlands. With each year, the economic and property losses due to storm-induced gales, landslides and flash floods over the coastlines are becoming more frequent. Reliable subseasonal prediction of tropical cyclogenesis over the landlocked North Indian Ocean basin has extreme demand and requires accurate rendition of the crucial parameters that influence the storm development. While several genesis potential indices are used for climatological monitoring and prediction of cyclogenesis globally, their skill in subseasonal prediction of individual storm development is limited, especially near coastlines. This study reviews an improved genesis potential parameter, namely IGPP, that can detect cyclogenesis, evolution and storm tracks from post-processed Multi-model ensemble outputs. The IGPP is a revised version of Kotal Genesis Potential Parameter (KGPP) introduced by the India Meteorological Department for short and medium‐range operational cyclogenesis prediction over the North Indian Ocean. We analyzed and compared the cyclogenesis prediction systems when multiple storm systems of different intensities develop simultaneously. Results show that false alarms and overestimation of values present in KGPP are remarkably reduced by using IGPP for all the cases. Moreover, IGPP outperforms KGPP in distinguishing between developing and non-developing storms by accurately representing the cyclogenesis and intensity variations. The mean IGPP shows better correlation with maximum wind speeds of selected storms, with an improvement of almost 34 % compared to KGPP, which we attribute to the changes in thermodynamic and shear terms. The thermodynamic term is modified as the mean equivalent potential temperature of the surface and middle troposphere to include the effect of warm sea surface and tropospheric latent heat release whereas the vertical wind shear between 850 and 200 hPa levels is averaged over an annular region between 100 and 200 km radii from the storm centres and rescaled. IGPP has replaced KGPP operationally and is successfully implemented as one of the indices for the extended range probabilistic prediction of cyclogenesis by the India Meteorological Department. Probabilistic predictions using IGPP has been instrumental in providing early guidance on storm formation and weekly forecasts are available at https://www.tropmet.res.in/erpas/.

How to cite: Sudheesh, S. G., Sahai, A. K., Sukumarapillai, A., Joseph, S., and Beucler, T.: An Improved Genesis and Evolution Parameter for Subseasonal Prediction of the North Indian Ocean Tropical Cyclones, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6009, https://doi.org/10.5194/egusphere-egu22-6009, 2022.

Approximately, 25.6 tropical cyclones (TCs) occur in the western North Pacific (WNP) each year, of which 3.4 TCs affect the Korean Peninsula (KP). In 2019, a record of seven TCs affected the KP. We investigated and elucidated the favorable conditions influencing the TCs approaching the KP using the Weather Research and Forecasting model version 4.0 (WRFv4). The cold Maritime Continent-warm WNP sea surface temperature (SST) was found to be a major factor. The effect of the SST gradient was examined for one representative case using WRFv4 with varying SST anomalies. This study suggests that the SST gradient-induced change in the circulation over the Maritime Continent is a main factor causing the TCs to approach the KP.

How to cite: Moon, M. and Ha, K.-J.: Abnormal Activities of Tropical Cyclones in 2019 Over theKorean Peninsula, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6808, https://doi.org/10.5194/egusphere-egu22-6808, 2022.

Quantifiable assessment of how different physical processes promote tropical cyclone (TC) development is paramount in improving basic understanding of TC genesis and TC intensification forecasts. This assessment can be made via Eulerian budgets or by linearizing the equations of motion. For instance, the Sawyer-Eliassen equation gives the secondary circulation driven by a steady thermodynamic forcing. However, existing diagnostic frameworks often make implicit assumptions such as axisymmetry and temporally-averaged forcing, precluding discussions on how spatially heterogeneous or transient forcing may affect TC intensity. 

In this work, we combine principal component analysis with multiple linear regression to build a linear framework that predicts the evolution of three-dimensional wind fields at different forecast windows, based on current heating and wind conditions. We apply this model to ensembles of WRF simulations on Hurricane Maria (2017) and Typhoon Haiyan (2013). Uniquely, the simulations include cloud radiative feedback denial experiments, which enables us to quantify the extent to which radiative processes drive TC intensification. Given their simplicity, our models are reasonably accurate, with coefficients of determination exceeding 0.8 for forecast windows longer than six hours. The linear nature of our model allows us to cleanly decompose the contributions of different physical processes to three-dimensional TC kinematic changes. Using radiative heating as an example, preliminary results suggest that this heating creates outward-propagating diurnal variability in wind perturbations during critical intensification periods of Hurricane Maria. These wind perturbations resemble a shallow lower-tropospheric secondary circulation; implications of this circulation to TC intensification are explored. 

More generally, our framework can map thermodynamic forcing to kinematic changes without relying on axisymmetric assumptions, which opens the door to data-driven discovery of the leading physical pathways to TC intensification.

How to cite: Tam, F. I.-H., Beucler, T., and Ruppert, J.: A Data-Driven Approach to Isolate the Role of Radiative Heating in Tropical Cyclone Intensification, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6921, https://doi.org/10.5194/egusphere-egu22-6921, 2022.

Process-oriented diagnostics of tropical cyclones (TCs) facilitate a comparison of models to observations with respect to the physical processes relevant to TCs, informing which processes to target for model improvement. Here we use diagnostics based on the column-integrated moist static energy (MSE) variance budget, which focuses on how convection, moisture, clouds, and related processes are coupled. We use five different reanalysis datasets to provide an 'observation'-based reference against which high-resolution global climate models can be evaluated: ERA-Interim, MERRA-2, CFSR, ERA-5, and JRA-55. We calculate the budget in 10 x 10 degree boxes following tracked TCs composites over storm snapshots of the same intensity. The composites are qualitatively similar to prior work, with radiative feedbacks contributing most to MSE variance growth in the early stages of TC development and in weaker storms, and with surface flux feedbacks increasing strongly with intensity. Reanalyses that have a stronger radiative feedback, normalized by the box-mean MSE variance, in a given intensity bin exhibit a higher percentage of storms that intensify to the next bin, which emphasizes the value of the MSE variance budget as a process-oriented diagnostic for understanding model simulation of TCs. However, there is a large spread in MSE variance and the radiative and surface flux feedback contributions to MSE variance growth across reanalyses, even when considering composites over storms of the same intensity. The spread across reanalyses is comparable to the spread across the high-resolution climate models considered by Wing et al. (2019). This suggests that the data assimilation present in reanalyses does little to constrain the TC-MSE variance budget and indicates that caution must be taken when evaluating climate models against reanalysis. Ongoing work continues to evaluate climate model simulations, including those from the HighResMIP ensemble, against the reanalysis-based reference, and examine the large-scale environments associated with TC formation in reanalyses.

How to cite: Wing, A., Dirkes, C., Camargo, S., Kim, D., and Moon, Y.: Process-oriented diagnosis of tropical cyclones based on the moist static energy variance budget in reanalyses and high-resolution climate models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9805, https://doi.org/10.5194/egusphere-egu22-9805, 2022.

Devastating Japan in October 2019, Supertyphoon (STY) Hagibis was an important typhoon in the history of the Pacific. A striking feature of Hagibis was its explosive RI (rapid intensification). In 24 h, Hagibis intensified by 100 kt, making it one of the fastest-intensifying typhoons ever observed. After RI, Hagibis’s intensification stalled. Using the current typhoon intensity record holder, i.e., STY Haiyan (2013), as a benchmark, this work explores the intensity evolution differences of these 2 high-impact STYs.

We found that the extremely high pre-storm sea surface temperature reaching 30.5∘C, deep/warm pre-storm ocean heat content reaching 160 kJ cm^-2, fast forward storm motion of ~8 m s^-1, small during-storm ocean cooling effect of ~ 0.5∘C, significant thunderstorm activity at its center, and rapid eyewall contraction were all important contributors to Hagibis’s impressive intensification. There was 36% more air-sea flux for Hagibis’s RI than for Haiyan’s.

After its spectacular RI, Hagibis’s intensification stopped, despite favorable environments. Haiyan, by contrast, continued to intensify, reaching its record-breaking intensity of 170 kt. A key finding here is the multiple pathways that storm size affected the intensity evolution for both typhoons. After RI, Hagibis experienced a major size expansion, becoming the largest typhoon on record in the Pacific. This size enlargement, combined with a reduction in storm translational speed, induced stronger ocean cooling that reduced ocean flux and hindered intensification. The large storm size also contributed to slower eyewall replacement cycles (ERCs), which prolonged the negative impact of the ERC on intensification.

How to cite: Lin, I., Rogers, R. F., Huang, H.-C., Liao, Y.-C., Herndon, D., Yu, J.-Y., Chang, Y.-T., Zhang, J. A., Patricola, C. M., Pun, I.-F., and Lien, C.-C.: Ocean Interaction and the Intensity Evolution of Two High-Impact Super Typhoons: Hagibis (2019) and Haiyan (2013), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1254, https://doi.org/10.5194/egusphere-egu22-1254, 2022.

The Madden-Julian Oscillation (MJO) can create favorable conditions for tropical cyclone (TC) genesis in the Indian Ocean, but past work has not thoroughly investigated how TCs after genesis may influence MJO convection development. This work utilizes long-term composite analysis to broadly establish the relationship between Indian Ocean TCs and each MJO phase over the Indian basin, and then seeks to isolate direct impacts of the TCs on MJO convection coverage and intensity.

We first examine Indian Ocean TC interactions with MJO convection using daily-mean ERA5 reanalysis and TRMM precipitation products from 1998-2018 for TC and non-TC days per MJO phase, excluding 3 days before and after Best-Track TC lifespans to reduce contamination of non-TC composites. Preliminary analysis suggests that TC periods are associated with stronger MJOs, with an anomalously stronger MJO large-scale circulation and associated subsidence over the equatorial Indian Ocean. We find higher CAPE and increased TRMM rainfall during convectively-active MJO phases over the eastern Indian Ocean when TCs are present, but increased dry-air advection, greater CIN, and decreased TRMM rainfall over the western Indian Ocean during the same phases. These findings allude to suppression of MJO convection development during TC periods in the western MJO convective envelope, with coincident enhancement of MJO convection in the eastern MJO convective envelope. While these broad conclusions are consistent during non-convectively-active MJO phases, changing MJO strength during TC periods for convectively-active MJO phases limit our ability to quantify TC impacts on MJO convection using only composite analysis.

To better quantify TC influences, we next isolate direct TC impacts on MJO convection using metrics for the TC range of influence, likelihood of interaction with MJO convection, and strength of TC-MJO convection interactions. Since a TC’s influence likely extends beyond the 34-kt wind radii provided by Best-Track, we determine an “outer wind radius” by integrating a radial wind model outward from each TC eye to ~5 m/s. We next quantify the overlapping area between each TC outer wind radius and the coincident MJO convection by using the MJO precipitation boundary determined from a large-scale precipitation tracking dataset, with the size of the overlapping area providing the likelihood of interaction. For time periods when TC outer wind radii and MJO convection overlap, we compare the convection coverage and intensity observed by TRMM between MJO convection sectors with and without TC wind overlap. The strength of a TC-MJO convection interaction is finally quantified by comparing the convection coverage and intensity between these sectors. With climatological statistics on the likelihood and strength of TC-MJO interactions, future MJO prediction and Maritime Continent rainfall forecasts could be adjusted according to the presence or absence of Indian Ocean TCs.

How to cite: Thayer, J. and Hence, D.: Tropical Cyclone Interactions with Madden-Julian Oscillation Convection in the Indian Ocean, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2080, https://doi.org/10.5194/egusphere-egu22-2080, 2022.

Forecasting the Madden-Julian Oscillation (MJO) is challenging for many numerical weather prediction (NWP) systems and climate models. Models tend to simulate slower MJO propagation than in observations, impacting other weather and climate patterns across the world through its teleconnections. Observations show that sea surface temperatures (SST), and subsequently sea surface fluxes influence MJO convection in the tropics. Coupled ocean-atmosphere models, which dynamically predict SST, tend to perform better in forecasting the MJO than atmosphere-only models that use persisted SST. Lower resolution coupled climate models are routinely used by forecasting centres, however, there are only a few operational weather forecasts utilising high resolution coupled NWP systems. The Met Office has developed a coupled NWP system running in near real-time since May 2016, alongside their operational, atmosphere-only NWP system. Comparison between the models using the Real-time Multivariate MJO index reveals that both are similarly skillful within 7 and 10 forecast days for operational and coupled models, respectively. The coupled model produces faster MJO propagation than the operational model. Consistent with this faster propagation, coupled model forecasts initiated during active MJO convection over the Indian Ocean (RMM phase 1), show enhanced convection by lead day 7 in the Sulawesi-Banda Sea region located ahead (to the east) of the convective envelope. Warm SST anomalies of order 0.1°C in that region are simulated in the coupled model composites from lead day 1, consistent with observations. When the coupled model is initialised with active MJO convection over the Maritime Continent (RMM phase 4), the model suppresses convection faster in the equatorial Indian Ocean region, which is behind (to the west) of the MJO convection. Cold SST anomalies are created in the coupled model from lead day 1 in that region, stronger than observations suggest and leading to excessive suppression of convection in the coupled model here. We explain the differences between the coupled and atmosphere-only simulations through a combination of upwelling diagnostics, analysis of moisture budget terms and targeted numerical experiments for SST-convection feedback.

How to cite: Karlowska, E., Matthews, A., Webber, B., Graham, T., and Xavier, P.: Sea surface temperature impact on Madden-Julian Oscillation convection in the Met Office coupled and atmosphere-only forecast models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-271, https://doi.org/10.5194/egusphere-egu22-271, 2022.

The Madden-Julian oscillation (MJO) events can be categorized into four types based on their propagation characteristics: standing, jumping, slow-propagating, and fast-propagating types. While the characteristics of each MJO type have been documented in the literature, it remains unknown whether such diversity is realistically represented in the state-of-art climate models. This study evaluates the MJO diversity in 28 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. We find that many CMIP6 models reasonably reproduce the MJO diversity although the relative frequency of propagating types tends to be underestimated. When individual models are grouped into the GOOD and POOR models by considering the performance in capturing propagation pattern of the four MJO types, the GOOD models show a much stronger relationship between MJO type and underlying sea surface temperature (SST) anomalies, especially for standing and fast-propagating types. We find a systematic difference in the model biases in the climatological mean SST and column water vapor between the GOOD and POOR models, with the POOR models exhibiting much stronger cold and dry biases over the equatorial western Pacific. Our results suggest that the MJO diversity can be improved by reducing model mean bias.

How to cite: Back, S.-Y., Kim, D., and Son, S.-W.: MJO diversity in CMIP6 models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11037, https://doi.org/10.5194/egusphere-egu22-11037, 2022.

The diurnal cycle in tropical islands is critical for water supplies and agriculture, and potentially has important feedbacks onto longer timescale tropical disturbances. However, the conditions that regulate the diurnal cycle of rainfall on such islands remain poorly understood.  Here, we use observations and a cloud resolving model to understand intraseasonal variability of the diurnal cycle in and near Luzon during boreal summer. 

The boreal summer intraseasonal oscillation (BSISO) and quasi biweekly oscillation (QBWO) modulate the Luzon diurnal cycle in a similar manner during their lifecycles. In particular, the diurnal cycle of rainfall and offshore propagation of rainfall into the South China Sea are maximized during phases of the BSISO and QBWO characterized by increasing tropospheric moisture, sufficient insolation, and weak offshore easterly flow. These conditions occur in advance of the large-scale convective envelope of the BSISO and QBWO. Such a phase relationship suggests that enhanced diurnal rainfall may aid northward propagation of intraseasonal disturbances in the South China Sea.

The Cloud Model 1 (CM1) integrated at 1 km horizontal grid spacing is used to isolate the relative importance of background wind, humidity, and insolation for the diurnal cycle in and near an idealized tropical island resembling Luzon. By prescribing daily mean BSISO background wind variations through nudging, it is shown that the wind direction and speed are major regulators of offshore propagation of diurnal disturbances on the west side of the island. In particular, offshore propagation is maximized during periods of offshore easterly flow at low levels. Other experiments that test sensitivity to the vertical profile of wind are discussed. We also show that BSISO humidity and surface shortwave radiation variations are major contributors to diurnal cycle variability.  These results not only have implications for the diurnal cycle in the Philippines, but also other tropical islands such as Sumatra with prominent diurnal cycles modulated by intraseasonal variability.

How to cite: Maloney, E. and Natoli, M.: Intraseasonal Variability of the Philippines Diurnal Cycle, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9672, https://doi.org/10.5194/egusphere-egu22-9672, 2022.

The simulation of the Madden-Julian Oscillation (MJO) and convectively coupled equatorial waves (CCEWs) is considered in 13 state-of-the-art models from phase 6 of the Coupled Model Intercomparison Project (CMIP6). We use frequency-wavenumber power spectra of the models and observations for Outgoing Longwave Radiation (OLR) and zonal velocity at 250 hPa (U250), and consider the historical and end-of-century projections for the SSP245 and SSP585 scenarios. The models simulate a spectrum quantitatively resembling that observed, though systematic biases exist. MJO and Kelvin waves (KW) are mostly underestimated, while equatorial Rossby waves (ER) are overestimated. The models project a moderate future increase in power for the MJO, a robust increase for Kelvin waves (KW) and weaker power values for most other wavenumber-frequency combinations, including higher wavenumber ER. In addition to strengthening, KW also shift toward higher phase speeds (or equivalent depths). Models with a more realistic MJO in their control climate tend to simulate a stronger intensification, and models with a more realistic KW in their control climate tend to simulate a weaker intensification. 

How to cite: Bartana, H., Garfinkel, C., Shamir, O., and Rao, J.: Projected Future Changes in Equatorial Wave Spectrum in CMIP6, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1083, https://doi.org/10.5194/egusphere-egu22-1083, 2022.

The dominant modes of variability at the sub-seasonal to seasonal (S2S) time scales in the tropical atmosphere, with particular emphasis on the Madden-Julian oscillation (MJO), is investigated using the observed NOAA outgoing longwave radiation (OLR). This study focuses on the boreal winter season (November to April) of the period 1993-2016. The multi-channel singular spectral analysis (MSSA) method is introduced and used to isolate the dominant modes associated with the tropical boreal winter daily OLR anomalies. The results show that the dominant MSSA mode consists of an intraseasonal oscillation with a period of around 35-day and two seasonally persistent modes. The 35-day oscillation is related to the intraseasonal convective activity of the tropics with little contribution to the seasonal mean value, and the phase composites and propagation characteristics of the 35-day mode are almost identical to the MJO (referred to as the MJO mode). The seasonally persistent modes are characterized by large-scale patterns that prevail over most of the tropics with the same sign anomalies throughout the boreal winter season, which represent inter-annual variations and are related to the El Niño-Southern Oscillation (ENSO) pattern. In this work, the MSSA based analysis is applied to the fully coupled (atmosphere-ocean-land-cryosphere) Euro-Mediterranean Center on Climate Change (CMCC) seasonal prediction system to evaluate the model's performance in simulating observed dominant modes of the boreal winter tropical variability.

How to cite: Shahi, N. K., Scoccimarro, E., Gualdi, S., Peano, D., and Navarra, A.: Fidelity of the CMCC SPS model in simulating the dominant mode of tropical variability in boreal winter, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1500, https://doi.org/10.5194/egusphere-egu22-1500, 2022.

Convectively coupled equatorial Kelvin waves (CCKWs) are tropical weather systems that can lead to extreme precipitation. A vorticity budget for CCKWs over the Indian Ocean is presented, to identify the basic mechanisms of eastward propagation and growth. The budget is well closed, with a small residual. In the lower troposphere, CCKWs behave like strongly modified theoretical equatorial Kelvin waves. Vortex stretching, from the divergence of the Kelvin wave acting on planetary vorticity (the −f D term), is the sole mechanism by which the vorticity structure of a theoretical Kelvin wave propagates eastward. In the lower and middle troposphere, this term is also the key mechanism for the eastward propagation of CCKWs but, due to subtleties in its structure and phasing linked to a combination of modal structures, it also contributes to growth. Unlike in the theoretical Kelvin wave, other vorticity source terms also play a role in the propagation and growth of CCKWs. In particular, vortex stretching from relative vorticity (the - zeta D term) is the largest source term, and this leads strongly to growth, through interactions between the background and perturbation vorticity and divergence. Horizontal vorticity advection by the background flow contributes to propagation, and also acts to retard the growth of the CCKW. The sum of the source terms in this complex vorticity budget leads to eastward propagation and growth of CCKWs. The structure and vorticity budget of CCKWs in the upper troposphere is quite unlike that of a Kelvin wave, and appears to arise as a forced response to the lower-tropospheric structure.

How to cite: Matthews, A.: Dynamical propagation and growth mechanisms for convectively coupled equatorial Kelvin waves over the Indian Ocean, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2538, https://doi.org/10.5194/egusphere-egu22-2538, 2022.

Two separate dynamics have been used to understand the vertical structure of the Kelvin waves. Stratospheric Kelvin waves have been interpreted in terms of plane gravity waves, where the waves pump their energy upward. On the other hand, the characteristics of the tropospheric Kelvin waves have been interpreted as a superposition between low orders (mostly the first and second) baroclinic modes, which are expected under the hypothesis that the tropopause acts as a rigid lid. We used Fourier transformation to isolate the dynamical fields of the ERA-I reanalysis field into upward and downward phase components. Then, wavelet-based indices have been used to target wavenumber four Kelvin waves centered over the Indian ocean at different phase speeds. We found that the upward-energy waves are settled in the stratosphere, while the downward-energy waves are in the troposphere indicating that the tropospheric Kelvin waves at a single wavenumber behave as plane gravity wave-like their counterpart in the stratosphere. The upward-energy waves in the troposphere were found to follow the structure of the plane Kelvin waves with the zonal wind is in phase with the geopotential height, out of phase with upward wind, and in quadrature with the temperature field.

How to cite: Shaaban, A. and Roundy, P.: On the plane wave perspective of the tropospheric Kelvin waves, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3081, https://doi.org/10.5194/egusphere-egu22-3081, 2022.

The strong cross-equatorial Low Level Jet (LLJ) exists over the Indian Ocean and the South Asia is an important component in modulating the Indian Summer Monsoon Rainfall (ISMR). The interannual variation of the Monsoon LLJ (MLLJ) is examined using the interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim), Indian Monsoon Data Assimilation and Analysis (IMDAA), and Modern-Era Retrospective Analysis for Research and Application (MERRA) reanalyses data at different pressure levels during the 40 years period (1979-2018) and its implications on ISMR is studied using 0.25°× 0.25° gridded rainfall data for same period from IMD (Indian Meteorological Department). In June, July, August and September, the analysis of MLLJ strength at different level shows that the maximum wind speed in MLLJ core region is fluctuated between the levels 850hpa to 950hpa.The maximum MLLJ strength is calculated by taking maximum of wind speed over the core region (0°N- 20°N, 40°E- 80°E) of MLLJ and for the pressure levels (1000hpa to 700hpa) for each year and the MLLJ height is defined as the vertical pressure level at which the MLLJ strength is maximum. The trend analysis of maximum MLLJ strength and MLLJ height is carried out using reanalyses data and results suggest that there is an increasing trend in maximum wind speed during ISM months for ERA and MERRAdata while decreasing trend is seen with IMDAA. Also, the MLLJ height is showing negative trend for July and September months in MERRA data. The spatial correlation analysis of MLLJ strength and height with ISMR over India is computed to analyze the impact of inter annual variations of MLLJ in ISMR.It is noted thatthe MLLJ strength for June and September months has strong positive correlation with the rainfall of these months comparedto the months of July andAugust. Results show that MLLJ (strength and height) plays an important role in modulating rainfall particularly during the onset andwithdrawal phases of Indian summer monsoon.

How to cite: Purwar, S., Vasudevan, R., and Mohapatra, G.: Interannual variability in Monsoon Low Level Jet and Indian summermonsoon rainfall (ISMR), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-171, https://doi.org/10.5194/egusphere-egu22-171, 2022.

The diurnal cycle is one of the major modes of weather variability over the islands and coastal seas of the Maritime Continent. As observed in gridded data from the GPM satellite, the mean diurnal cycle of precipitation over land comprises a relatively rapid increase in rainfall rate through the afternoon followed by a more gradual decrease in intensity through the evening and night. Characterisation of this cycle using a small number of independently intuitive parameters helps in the assessment of model performance, and a best-fit waveform approach is often favoured for its conversion from discrete data to a continuous approximation. The phase of the peak of the best-fit first diurnal harmonic (a pure sine wave of 24-hour period) is systematically later over land than the observed time of peak precipitation by the order of one to three hours. Fitting of the mean diurnal cycle of precipitation using a skew-permitting waveform is trialled to capture its characteristics more accurately. A positive skewness, indicating a sharp rise and gradual decrease, is observed across most land area while skewness over the coastal seas is regionally dependent. Positive skewness over land displaces the best-fit peak to earlier time than the first diurnal harmonic peak, resulting in improved alignment between the observed peak and the best-fit peak, generally within one hour.

The skew-permitting approach to characterisation is further applied to data from regional hindcast model runs to assess model skill at capturing the diurnal cycle. It suggests reasonable skill over mountainous land area where diurnal deep convection tends to initiate, but poor skill over land away from such convection centres. The skewness parameter exposes poor skill over the coastal seas; immediately offshore southwest of Sumatra the amplitude and phase parameters from the model align well with observed values, however model skewness infers a gradual intensification of mean precipitation up to the peak while observations indicate a rapid intensification in this area. These findings will contribute to our understanding of the deficiencies of rainfall propagation mechanisms in models.

How to cite: Mustafa, J., Matthews, A., Hall, R., Heywood, K., and do Valle Chagas Azaneu, M.: Characterisation and model representation of the diurnal cycle of precipitation over the Maritime Continent, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-231, https://doi.org/10.5194/egusphere-egu22-231, 2022.

The Madden Julian Oscillation (MJO) and the Boreal Summer Intraseasonal Oscillation (BSISO) are fundamental modes of variability in the tropical atmosphere on the intraseasonal time scale. A linear model, using a moist shallow water equation set on an equatorial beta plane, is developed to provide a unified treatment of the two modes and to understand their growth and propagation over the Indian Ocean. Moisture is assumed to increase linearly with longitude and to decrease quadratically with latitude. Solutions are obtained through linear stability analysis, considering the gravest (n=1) meridional mode with nonzero meridional velocity.

Anomalies in zonal moisture advection and surface fluxes are both proportional to those in zonal wind, but of opposite sign. With observation-based estimates for both effects, the zonal advection dominates, and drives the planetary-scale instability. With a sufficiently small meridional moisture gradient, the horizontal structure exhibits oscillations with latitude and a northwestsoutheast horizontal tilt in the northern hemisphere, qualitatively resembling the observed BSISO. As the meridional moisture gradient increases, the horizontal tilt decreases and the spatial pattern transforms toward the "swallowtail" structure associated with the MJO, with cyclonic gyres in both hemispheres straddling the equatorial precipitation maximum. These results suggest that the magnitude of the meridional moisture gradient shapes the horizontal structures, leading to the transformation from the BSISO-like tilted horizontal structure to the MJO-like neutral wave structure as the meridional moisture gradient changes with the seasons. The existence and behavior of these intraseasonal modes can be understood as a consequence of phase speed matching between the equatorial mode with zero meridional velocity (analogous to the dry Kelvin wave) and a local off-equatorial component that is characterized by considering an otherwise similar system on an f-plane.

How to cite: Wang, S. and Sobel, A.: A unified moisture mode theory for the Madden Julian Oscillation and the Boreal Summer Intraseasonal Oscillation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1308, https://doi.org/10.5194/egusphere-egu22-1308, 2022.

To explore the characteristics of Northerly Cold Surge during Years of the Maritime Continent Campaign 2021, intensive observation was used to detect the modification processes of the air mass at the head of cold surge, convection development, and severe weather including torrential rainfall using several methods such as the intensive upper-air observation at Jakarta and Pangkal Pinang, vapor variation observation with GNSS network, and precipitation radar network. During this campaign, 7 CENS (Cross-Equatorial Northerly Surge) events were observed according to Hattori’s criteria. The results of the intensive observation show that all of 7 CENS events occurred in association with the negative SST anomaly over the Java Sea with CENS6 (18 – 21 February 2021) induced extreme rainfall (over 150 mm/day) in the southern part of Jakarta. The significant negative SST anomaly was continued over the inland & marginal seas of Indonesia under the strong northerly surge condition during this campaign.

How to cite: Makmur, E., Moteki, Q., Fitria, W., Nurrahmat, M. H., Riama, N., Sasmito, A., Suharmanto, E., Soebroto, E., Kurniawan, R., Swarinoto, Y., Rahayu, S., Harsa, H., Hanggoro, W., Fatkhuroyan, F., Habibie, N., Praja, A., Hutapea, D., Sapta, R., Noviati, S., Paski, J., and Karnawati, D.: Characteristics of 7 Northerly Cold Surge Events During Years of the Maritime Continent Campaign 2021, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2111, https://doi.org/10.5194/egusphere-egu22-2111, 2022.

Rainfall forecasts over northern tropical Africa are potentially beneficial for a wide range of applications from agriculture to health, but current numerical weather prediction models have very limited skill over this region, even in a probabilistic sense. A recent study by Vogel et al. (2021, DOI: 10.1029/2020GL091022) has demonstrated for the summer monsoon season July-September that even a relatively simple statistical forecast model based on past time-space rank correlations in rainfall estimates from Tropical Rainfall Measuring Mission can outperform numerical models.

Here we extend the correlation part of the Vogel et al. study in various ways: (a) we use time lags up to the previous three days, (b) we use a larger geographic area spanning several thousand kilometers over northern tropical Africa and the Atlantic Ocean, (c) we consider five different seasons per year, (d) we use the more recent satellite-based globally gridded Integrated Multi-satellitE Retrievals for Global Precipitation Measurement final-version product from 2001–2019, and (e) we link the detected correlation patterns to known meteorological features such as African Easterly waves.

Our results show that significant correlations can be found for all lags from one to three days in all seasons along the fringes of the climatological rainbelt over tropical Africa. We attribute this to the large-scale drivers that trigger and organize rainfall, which in turn causes coherent spatio-temporal anomalies. On the contrary, low correlations are observed within the rainbelt at all time lags, indicating the lack of a single dominant forcing, high stochasticity, or both. To quantify the coherence of the forcings identified in each season, we introduce a new metric called coherence-factor. It is computed at every grid-point and summarizes the extent to which the lagged correlations reflect a propagation with a constant phase speed and direction. High values of the coherence-factor combined with healthy levels of correlations over the three days considered indicate physically interpretable, stable relationships that potentially translate into high potential predictability. For example, high coherence over the Sahel region in the July-September season shows the dominance of AEWs to trigger and organize rainfall. In contrast, the December-February season shows a very different picture with high coherence only over the equatorial oceanic region. The May–June season closely resembles July–September, indicating the early stages of AEWs activity. March–April and October–November seasons show features characteristic of those they are transitioning between.

In the future, the coherent features identified in this study will be used as predictors for testing several statistical and hybrid (i.e., additionally including predictors from numerical weather prediction) models in every season to forecast rainfall over northern tropical Africa.

How to cite: Rasheeda Satheesh, A., Knippertz, P., and Fink, A.: How coherent is rainfall in northern tropical Africa in time and space – and why?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2427, https://doi.org/10.5194/egusphere-egu22-2427, 2022.

The Upper-Tropospheric Cyclonic Vortexes (UTCV) are one of the main synoptic systems responsible for rainfall production in the pre-rainy season over Northeastern Brazil (BNE). This study aims to analyze the UTCV contribution with precipitation and moisture transport convergence in the BNE, comparing it to the most important moisture recycling region in South America from 2015 to 2017 - The Amazon region (AMZ), which has the largest hydrographic basin in the world; in addition to the high importance for the moisture transport to extratropical latitudes of the continent. Furthermore, the El Niño Southern Oscillation influence on the frequency and intensity of the UTCV was also investigated. The method proposed by this study sought to calculate the average moisture convergence and precipitation through pre-established areas using virtual boxes. This comparison concerns the average intensity and total amount of moisture convergence and precipitation for the defined regions. 22 UTCV were identified during the three years of analysis, with the highest frequency in 2016, the transition year between El Niño and La Niña. Through the two boxes fixed in both study regions, it was possible to observe, on certain dates, higher concentrations of moisture convergence and precipitation in the BNE concerning AMZ. This occurred during the presence of some vortexes over the BNE, mainly in 2016, highlighting a case in January of that same year when the moisture convergence values in the BNE were more intense than the first three months in the AMZ.

How to cite: Lyra, M., Arraut, J., and Braga, H.: The Upper Tropospheric Cyclonic Vortex Influence over Moisture Convergence and Precipitation on Brazilian Northeastern, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2851, https://doi.org/10.5194/egusphere-egu22-2851, 2022.

Tropical deep convection is both driven by the large-scale circulation, such as the Hadley Cell, as well as by periodic heating, namely the diurnal cycle. In a suite of idealized cloud-resolving simulations we allow for an idealized Hadley Cell to evolve by imposing a spatial surface temperature gradient. In line with recent studies (O’Neill et al., 2017, Patrizio & Randall, 2019), we find that a large-scale oscillation of period T_L self-organizes, visible in many quantities, especially precipitation. The period T_L is found to depend approximately linearly on L, the meridional domain size. When we now impose a diurnal cycle at T_D=1day, the timeseries of precipitation is modified. For small L, the power spectrum shows that T_D dominates, whereas for large L the intrinsic mode T_L prevails. At intermediate T_L⋍T_D a resonance occurs, which causes the amplitude to nearly double, leading to more extreme rainfall. To gain insight, we propose a simple damped harmonic oscillator model with a spatial energy source, mimicking convective latent heat release. We associate the “spring constant” with the meridional domain size L. The coupling to the diurnal cycle is then incorporated by a periodic drive. Results show that the model can mimic the resonance at intermediate periods and the dominance of large-scale modes at large system sizes. We further find an envelope period which may give insight into the observed meandering of the ITCZ (Mapes et al., 2018). Our results could help understanding of tropical extreme events, e.g. MCS, and how they could be invigorated by the large scale circulation.

How to cite: Haerter, J. O. and Fiévet, R.: The diurnal cycle resonates with the large-scale circulation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5331, https://doi.org/10.5194/egusphere-egu22-5331, 2022.

During the long dry season (June-September) Western Central Africa (WCA) is a region with an extensive and persistent stratocumulus or stratus deck. Previous studies have shown that this extensive cloud cover is crucial for the existence of a biodiverse, light-deficient tropical rainforest ecosystem in Gabon. Yet, its climatological behaviour, the cloud genesis and lysis mechanisms, and thus its persistence under the ongoing climate change has not been intensively studied yet.

In the present study, we created various climatologies of Low Cloud Cover (LCC) in the region based on (a) 3-hourly data from in-situ eye observations by synoptic stations, (b) on 15-minute data from the SEVIRI instrument aboard the METEOSAT Second Generation geostationary satellite, and (c) twice daily data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat’s Cloud Profiling Radar (CPR). To validate the satellite products against eye observations of cloudiness at synoptic stations, the latter are spatially weighted in the observer’s field of view and compared against co-located pixel averages of the satellites. To obtain an as accurate depiction of the diurnal cycle of LCC as possible, we combined the SAFNWC cloud type product during the day with the Night Microphysical Scheme during the night. Both product use various SEVIRI spectral channels. Vertical profiles of cloudiness at 250 m resolution are derived from the Calipso-CloudSat 2B-GEOPROF-LIDAR product.

The mean climatology shows more clouds at the coast and the coastal plains, decreasing cloud occurrence frequency landward. The closer to the Congo basin, the less persistence is the LCC deck. The diurnal cycle of the LCC has a smaller amplitude on the coastal plains of Gabon, while at the leeward site of the Chaillu Mountains, an up to 1000 m high low mountain range in southern Gabon, a higher amplitude with substantial clearing in the afternoon and cloud formation in the night prevails. The persistence of the LCC on the windward side of the Chaillu Mountains might be related to upslope winds. Further, a change in the cloud genus from stratocumulus to cumulus is observed on the plateau during the afternoon in association with the clearing. It is speculated that this is associated with an increased boundary layer height. Another cause might be a Foehn-effect, dissipating the Low Cloud Cover behind the Chaillu Mountains and being responsible for the higher amplitude in the diurnal cycle above the plateau. On the windward side of the Chaillu Mountains, there is no transition observed from stratocumulus to cumulus clouds, presented with its persistence cloud deck.

In summary, the present study constitutes the hitherto most comprehensive sub-daily station- and satellite-based, dry-season climatology of LCC over western equatorial Africa.

How to cite: Aellig, R., Champagne, O., Camberlin, P., Fink, A., Knippertz, P., Moron, V., Philippon, N., and Seze, G.: Climatology of low-level clouds during the main dry season over Western Equatorial Africa: Comparison between ground observations and satellites, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5881, https://doi.org/10.5194/egusphere-egu22-5881, 2022.

Mesoscale convective systems (MCSs), long-lived convective clusters spanning more than 100 km horizontally, are known to be the dominant source of rainfall in the tropics, and the longest-lived MCSs are shown to be largely responsible for tropical extreme precipitation [Roca and Fiolleau, 2020]. Globally, the most extreme storms tend to be located over land, and the most intense storms over oceans tend to be adjacent to land, where motion is favored from land to ocean, e.g. tropical West Africa and the adjacent Eastern Atlantic Ocean [Zipser et al., 2006]. These systems are organized and maintained by the atmospheric characteristics needed for deep convection (moisture, instability, and lift), and the presence of vertical wind shear [Schumacher and Rasmussen, 2020]. Dry soils seem to have a large influence on strengthening organized convection [Klein and Taylor, 2020]. However, the mechanisms behind the intensification or dissipation of MCSs advected from land to sea are not well established yet.
To address this shortcoming, we investigate the evolution of MCSs emerging from satellite data over tropical Africa and the Eastern Atlantic Ocean. We use a database of tracked MCSs from infrared satellite data, TOOCAN [Fioellau and Roca, 2013]. Using these data we built a lagrangian tracker by which groups of MCSs - occurring in spatial proximity of each other with a 15 deg x 15 deg patch - are followed. We study the evolution of the cloud field within the patch, initiated at the time and latitude of maximum convective activity in the season. We superimpose a collocated satellite precipitation dataset, IMERG, to gain insight into the precipitation field related to the tracked MCSs, and study the environmental properties (temperature, wind profiles) using ERA5 reanalysis datasets. Over land, we find (i) that the MCS cover exhibits a clear diurnal cycle with peaks in the late afternoon and (ii) the lagrangian patch moves with a near constant velocity. Over ocean, we find a (i) decrease of the MCS cover which does not correspond to a decrease in precipitation and that (ii) at times the MCS evolution becomes stationary, corresponding to near-zero wind profiles. By generalizing these results to five years of tracked MCSs, we aim to gain insight into what environmental conditions are necessary for the development of strongly organized MCS fields over the coastal regions and the ocean, which, if persistent in time, could eventually evolve into tropical cyclones.

How to cite: Kruse, I. L. and Haerter, J. O.: Land-Ocean Transitions in the Tropics: What Makes MCSs Persist?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8614, https://doi.org/10.5194/egusphere-egu22-8614, 2022.