Outgoing Longwave Radiation Data Research Articles

Lagged Response of MJO Convection and Precipitation to Solar Ultraviolet Variations on Intraseasonal Time Scales

AbstractComposite analyses of NOAA satellite‐based outgoing longwave radiation data and ERA5 reanalysis data for nearly six solar maximum periods support the existence of a response of tropical convection and precipitation to short‐term (∼27‐day) solar ultraviolet variations. Following solar UV peaks, the response consists of an increase in average convection and precipitation in the equatorial Indian Ocean and a decrease in the western and central tropical Pacific, with maximum amplitude at a lag of 4 to 8 days. The opposite occurs following short‐term solar UV minima. The observed responses are most detectable when the Madden‐Julian oscillation (MJO) is active and appear to be related to a reduced ability of the MJO to propagate across the Maritime Continent barrier following solar UV peaks relative to UV minima. A similar behavior has previously been found when the stratospheric quasi‐biennial oscillation is in its westerly phase relative to its easterly phase.

Anomalies in Infrared Outgoing Longwave Radiation Data before the Yangbi Ms6.4 and Luding Ms6.8 Earthquakes Based on Time Series Forecasting Models

Numerous scholars have used traditional thermal anomaly extraction methods and time series prediction models to study seismic anomalies based on longwave infrared radiation data. This paper selected bidirectional long short-term memory (BILSTM) as the research algorithm after analyzing and comparing the prediction performance of five time series prediction models. Based on the outgoing longwave radiation (OLR) data, the time series prediction model was used to predict the infrared longwave radiation values in the spatial area of 5° × 5° at the epicenter for 30 days before the earthquake. The confidence interval was used as the evaluation criterion to extract anomalies. The examples of earthquakes selected for study were the Yangbi Ms6.4-magnitude earthquake in Yunnan on 21 May 2021 and the Luding Ms6.8-magnitude earthquake in Sichuan on 5 September 2022. The results showed that the observed values of the Yangbi earthquake 15 to 16 days before the earthquake (5 May to 6 May) exceeded the prediction confidence interval over a wide area and to a large extent. This indicates a strong and concentrated OLR anomaly before the Yangbi earthquake. The observations at 27 days (9 August), 18 days (18 August), and 8 days (28 August) before the Luding earthquake exceeded the prediction confidence interval in a local area and by a large extent, indicating a strong and scattered OLR anomaly before the Luding earthquake. Overall, the method used in this paper extracts anomalies in both spatial and temporal dimensions and is an effective method for extracting infrared longwave radiation anomalies.

Generation of global 1-km daily top-of-atmosphere outgoing longwave radiation product from 2000 to 2021 using machine learning

ABSTRACT Top-of-atmosphere (TOA) outgoing longwave radiation (OLR), a key component of the Earth’s energy budget, serves as a diagnostic of the Earth’s climate system response to incoming solar radiation. However, existing products are typically estimated using broadband sensors with coarse spatial resolutions. This paper presents a machine learning method to estimate TOA OLR by directly linking Moderate Resolution Imaging Spectroradiometer (MODIS) TOA radiances with TOA OLR determined by Clouds and the Earth’s Radiant Energy System (CERES) and other information, such as the viewing geometry, land surface temperature and cloud top temperature determined by Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2). Models are built separately under clear- and cloudy-sky conditions using a gradient boosting regression tree. Independent test results show that the root mean square errors (RMSEs) of the clear-sky and cloudy-sky models for estimating instantaneous values are 4.1 and 7.8 W/m2, respectively. Real-time conversion ratios derived from CERES daily and hourly OLR data are used to convert the instantaneous MODIS OLR to daily results. Inter-comparisons of the daily results show that the RMSE of the estimated MODIS OLR is 8.9 W/m2 in East Asia. The developed high resolution dataset will be beneficial in analyzing the regional energy budget.

The Variations of Outgoing Longwave Radiation in East Asia and Its Influencing Factors

Outgoing longwave radiation (OLR) data are one of the key factors in studying the radiation balance of the earth–atmosphere system in East Asia. It is of great significance to explore the influence factors on OLR. This paper processes the data of nearly 19 years, from September 2002 to February 2022, and conducts in-depth research using the exponential smoothing method, empirical orthogonal decomposition (EOF), correlation analysis, and other methods. We found that the spatial distribution of OLR is zonal symmetry and gradually decreases with the increase of latitude. Using EOF analysis, it is found that the total variance contribution of the first four decomposed spatial features exceeds 70%, and the overall change trend of the four-time coefficients in the past 19 years all show a downward trend. OLR is positively correlated with total column water vapor (TCWV), air temperature (AT), and cloud top temperature (CTT), but negatively correlated with cloud top pressure (CTP). OLR has a similar spatial correlation distribution with TCWV and AT, while the spatial correlation between OLR and CTP is opposite to the first two parameters. In most parts of East Asia, the spatial correlation with CTT exceeds 0.8. The change in OLR value is affected by various meteorological parameters. In East Asia, the positive correlation between 30° N and 60° N is significantly affected by TCWV, AT, and CTT; and the negative correlation is more significantly affected by CTP. At 0–25° N, the positive correlation is significantly affected by CTP and CTT, while the negative correlation is significantly affected by TCWV and AT.

A Direct Method for the Estimation of Top-of-Atmosphere Outgoing Longwave Radiation from Himawari-8/AHI Data

Top-of-atmosphere (TOA) outgoing longwave radiation (OLR), a key component of the Earth’s energy budget, serves as a diagnostic of the Earth’s climate system response to incoming solar radiation. However, existing products are typically estimated using the traditional two-step method, which may bring extra uncertainties. This paper presents a direct machine learning method to estimate TOA OLR by directly linking Himawari-8/Advanced Himawari Imager (AHI) TOA radiances with TOA OLR determined by Clouds and the Earth’s Radiant Energy System (CERES) and other information, such as the viewing geometry. Models are built separately under clear- and cloudy-sky conditions using a gradient-boosting regression tree. Independent test results show that the root mean square errors (RMSEs) of the clear-sky and cloudy-sky models for estimating instantaneous values are 7.46 W/m2 (3.0%) and 11.61 W/m2 (5.8%), respectively. Daily results are obtained by averaging all the instantaneous results in one day. Intercomparisons of the daily results with CERES TOA OLR data show that the RMSE of the estimated AHI OLR is ~6 W/m2 (3%). The developed high-resolution AHI TOA OLR dataset will be beneficial in analyzing the regional energy budget.

Integration of multiple earthquakes precursors before large earthquakes: A case study of 25 April 2015 in Nepal

In this work, we analyze magnetic data, Land Surface Temperature (LST), Outgoing Longwave Radiation (OLR), Air Temperature (AT) and Relative Humidity (RH) around the epicenter before and after the large EQs occurred on April 25, 2015 in Nepal. Daytime and nighttime LST values were retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite. We used the magnetic data acquired by Swarm satellites in the top side ionosphere, and daily OLR data was obtained from the United States National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellites. Moreover, AT and RH values were provided from the nearest meteorological ground station to the epicenter located at Katmandu airport. As data analysis, short-term (15 days before and 5 days after the earthquakes) and medium-term (2 months before and 1 month after the earthquakes) evaluations were carried out. For short-term analysis, the results of the magnetic field in the topside ionosphere detected an interesting anomaly on April 12, 2015. Besides, nighttime LST anomaly was observed on April 13, 2015, 14 days before the earthquakes, which was also an anomalous day for AT and RH analysis. Moreover, in the OLR analysis, April 12, 2015 was anomalous day based on the time series of the epicentral pixel that coincides with the magnetic field anomaly. Concerning the medium-term nighttime LST analysis, 13th April was the day, which may be associated with the earthquakes. For the medium-term OLR analysis, April 12, 2015 was found to be related to the seismic activity based on the epicentral pixel. Besides, the RH anomaly on 13 April was the only mutual day with the anomalies of LST and OLR for the medium-term analysis. Based on the short-term and medium-term results, these two days, 12 and April 13, 2015, may be associated with the preparation for the earthquake occurrence. Overall, it is concluded that these methods could be effective and reliable in detecting anomalies that precede upcoming EQs with further investigations.

Identification of Summer Monsoon Onset over Nepal by using Satellite-Derived OLR Data

Summer monsoon onset is considered as the beginning of the rainy season in South Asia. In Nepal, summer monsoon onsets from eastern part and ~80% of the annual rainfall occurs during summer monsoon season (i.e., June to September). The monsoon onset is one of the crucial elements for the socio-economic development as the majority of the population depends primarily on rain fed agriculture systems for their livelihood. For identification of the monsoon onset date over eastern Nepal, daily mean satellite-derived Outgoing Long-wave Radiation (OLR) data (10 × 10 spatial resolution) obtained from National Environmental Satellite Data and Information Service (NESDIS), NOAA is used. Long term OLR data from 1979 to 2019 for March to June is analyzed to study monsoon progression towards eastern Nepal. The rainfall amount obtained from rain gauge stations is compared with the OLR data, which depicts a higher correlation in the southern part of Eastern and Central Nepal than in the northern regions. A convective episode signifies the drop in OLR by about 45 Wm-2 from 10 May to 10 June. Further, the relation between the date of characteristic fall of OLR below 250Wm-2 and monsoon onset date announced by MFD (Meteorological Forecasting Division) for the study period is evaluated to predict new onset dates over the region. The predicted onset date is found as 13th of June on average and its correlation with the MFD onset date is 0.6 (p<0.01). The study highlights the potential application of the satellite-derived OLR based method for the early prediction of onset of summer monsoon over eastern Nepal.

Evaluation of Reprocessed Fengyun-3B Global Outgoing Longwave Radiation Data: Comparison with CERES OLR

Evaluation of Reprocessed Fengyun-3B Global Outgoing Longwave Radiation Data: Comparison with CERES OLR

High-resolution outgoing long wave radiation data (2014–2020) of INSAT-3D Imager and its comparison with Clouds and Earth’s Radiant Energy System (CERES) data

As a proxy of convection INSAT-3D satellite-derived product Outgoing Long Wave Radiation (OLR) data is available in both high temporal and spatial ranges over 40°N–40°S & 35°E–135°E. Daily gridded data set of 7 years of data (2014–2020) has been generated at 10 km × 10 km resolution and the same is compared with Clouds and Earth’s Radiant Energy System (CERES) instrument data taken from CERES as reference. Almost all the INSAT-3D data set generated is Global Space-based Inter-Calibration System (GSICS) corrected. The spatiotemporal consistency of the data set was statistically analyzed and found to be reasonably good agreement having a bias of ∼±5–6 W/m2 over above said domain.This inter-comparison is essential to get confidence in the data sets and release it further in the public domain for any scientific study. Again, this data set will be very useful in diagnosing the variations of convection at different scales (daily, weekly, monthly, annual, seasonal, intra-seasonal, etc.) & an important repository of Daily Climate Data Records (DCDR) for future studies. The specified domain of the present study is affected throughout the year with variable (weak, moderate, intense, or severe) spatiotemporal Inter-Tropical Convergence Zone (ITCZ) convection streams due to different types of weather activities (winter, pre-monsoon, monsoon, and post-monsoon) throughout the year. To visualize the importance of this high-resolution OLR data set a case study of Cyclone Amphan and Vayu is presented. The extremely severe intense convection (OLR departure −112 W/m2 with INSAT-3D new data set whereas −104 W/m2 in CERES data) was observed in both the data sets on 18th May-2020 at 13.7–16°N & 86.2–86.8°E during the super cyclonic stage of Amphan. A similar type of variation in the OLR has been noticed for Vayu Cyclone (OLR departure −94 W/m2 with INSAT-3D new data set whereas −86 W/m2 in CERES data). This information is very useful in impact-based forecasting and further future actions for disaster managers/decision-makers. The localized convective features during cyclone activity over the Indian Ocean region both in the Arabian Sea and the Bay of Bengal are well captured with this new data set and the difference in OLR of INSAT -3D and CERES -9 W/m2 and -12 W/m2 respectively.

Spatial-Temporal Mode Analysis and Prediction of Outgoing Longwave Radiation over China in 2002–2021 Based on Atmospheric Infrared Sounder Data

Outgoing longwave radiation (OLR) is a key factor to study the radiation balance of the earth–atmosphere system. It is of great significance to explore the temporal and spatial variation characteristics over the OLR value in China region and to predict its future variation trend. We investigate the characteristic distribution of OLR value over China and predict its results in time series using the seasonal autoregressive integrated moving average (SARIMA) and long short-term memory (LSTM) methods based on the OLR data by the Atmospheric Infrared Sounder (AIRS). The Mann–Kendall (MK) mutation test was used to analyze the annual average of OLR values in China and the mutation points in the four seasons. The empirical orthogonal function (EOF) is used to decompose the spatial characteristics and temporal variation of OLR values in China. The MK mutation test is used to obtain the mutation points in the three seasons of spring, summer and autumn. The cumulative variance contribution of the four modes obtained by EOF decomposition exceeds 70%, and the variance contribution of the first mode exceeds 50%. The prediction accuracy with SARIMA model is 99% and LSTM algorithm is 97%. The results of spatiotemporal analysis show that the OLR value near the equator is significantly higher than that of the north and south poles and decreases with the increase of latitude; the OLR value in spring, summer and autumn is higher than that in winter. The results of the MK test show that there are many mutation points in autumn, and the location of the mutation points cannot be determined. The mutation points in spring and summer meet the confidence interval; the first mode of EOF decomposition has a meridional structure, and the OLR value is dropped within 18 years as a whole. The spatial characteristics of modes 1 and 3 have obvious changes in the Qinghai-Tibet Plateau and Northeast China. The prediction results show that the prediction accuracy of SARIMA is higher than that of LSTM. Therefore, the results predicted by SARIMA may provide a reference for the study of the radiation balance of the earth–atmosphere system in China.

EOS: Atmospheric Radiative Transfer in Habitable Worlds with HELIOS

Abstract We present EOS, a procedure for determining the outgoing longwave radiation (OLR) and top-of-atmosphere (TOA) albedo for a wide range of conditions expected to be present in the atmospheres of rocky planets with temperate conditions. EOS is based on HELIOS and HELIOS-K, which are novel and publicly available atmospheric radiative transfer (RT) codes optimized for fast calculations with GPU processors. These codes were originally developed for the study of giant planets. In this paper we present an adaptation for applications to terrestrial-type, habitable planets, adding specific physical recipes for the gas opacity and vertical structure of the atmosphere. To test the reliability of the procedure, we assessed the impact of changing line opacity profile, continuum opacity model, atmospheric lapse rate, and tropopause position prescriptions on the OLR and the TOA albedo. The results obtained with EOS are in line with those of other RT codes running on traditional CPU processors, while being at least one order of magnitude faster. The adoption of OLR and TOA albedo data generated with EOS in a zonal and seasonal climate model correctly reproduces the fluxes of the present-day Earth measured by the CERES spacecraft. The results of this study disclose the possibility to incorporate fast RT calculations in climate models aimed at characterizing the atmospheres of habitable exoplanets.

Linkages of Active and Weakening MJO events to Seasonal Variations over the Maritime Continent

The Madden-Julian Oscillation (MJO) is a large-scale phenomenon of air-sea intra-seasonal variability in the equatorial area, particularly in the Maritime Continent (MC). This research focused on the analysis of the MJO propagation process in association with rainfall events and sea surface temperature anomaly (SSTA) during seasonal variations, i.e., November, December, January February, and March (NDJFM), and May, June, July, August September (MJJAS). MJO events from 2010 to 2019 were classified as MJO active or MJO weakening according to propagation characteristics and amplitude changes in the RMM index. This research uses a dataset of 10-year series of daily Tropical Rainfall Measuring Mission (TRMM) (3B42 V7 derived) measurements for detecting rain rates. Daily OLR data from the NOAA Physical Sciences Laboratory and SSTA daily data from Physical Oceanography Distributed Active Archive Centre (PODAAC) NOAA are considered for analysing MJO propagation. Composites of outgoing longwave radiation (OLR) were also identified differences between the two events; active MJO events had consistently higher negative OLR anomalies than weakening MJO events. Active MJO events during NDJFM had a higher rain rate and positive SSTA than weakening MJO events. Furthermore, composite rain rates distribution over MC during NDJFM are mainly located in the south of the equator, contrarily when MJJAS are north of the equator.

Dynamic Characteristics of the Circulation and Diurnal Spatial Cycle of Outgoing Longwave Radiation in the Different Phases of the Madden–Julian Oscillation during the Formation of the South Atlantic Convergence Zone

In this work, we verified the formation of the South Atlantic Convergence Zone (SACZ) during the active, unfavorable, and transition phases of the Madden–Julian Oscillation (MJO), as well as the diurnal spatial variability in the estimated Outgoing Longwave Radiation (OLR) data. The real-time multivariate index (RMM) and the composites of meteorological variables were used, along with the temporal average of the estimated OLR data. All the different patterns for the average period of SACZ showed classic behavior: well-organized and with meteorological variables in phases throughout the troposphere. However, some differences were evident in the organization of each phase of the MJO: at 200 hPa, the Bolivian High (BH) was more flattened during the active phase pattern than in the unfavorable and transition phases, being wider and with a wavier trough embedded in the western flow; at medium levels, the subtropical highs appeared more defined and with a very wide trough; the trough supported the frontal systems on the surface and, together with the subtropical highs, concentrated all the moisture in this layer. In the OLR dataset, the formation of the Coast Squall Line (CSL) occurred during SACZ events in the active phase and MJO transition, whereas in the unfavorable phase, this system was not observed.

Retrieval of Outgoing Longwave Radiation from the Fengyun-3D Satellite and Its Climate Applications

The Fengyun-3D (FY-3D) satellite is a Chinese Earth observation satellite with high spectral resolution that can provide multi-spectral observations under all weather conditions. Outgoing longwave radiation (OLR) is an important parameter in the earth radiation energy balance and can reflect changes in atmospheric circulation and convective activity in response to incoming solar radiation. To apply the OLR data of the FY-3D satellite (F_OLR) to weather and climate analyses, the traditional single-channel OLR inversion algorithm for the NOAA (National Oceanic and Atmospheric Administration) satellite was used to calculate F_OLR, and the difference between F_OLR and the OLR data of the NOAA 18 satellite (N_OLR) was analyzed. A correction algorithm was proposed to correct F_OLR to match N_OLR; the spatiotemporal consistency of the corrected F_OLR and N_OLR was evaluated, and the two types of OLR data were used to analyze the onset of the South China Sea Summer Monsoon (SCSSM) and typhoon precipitation in China. The results showed that the corrected F_OLR and N_OLR were consistent in both temporal variation and spatial distribution and that the monitoring of the SCSSM and typhoon precipitation by the two types of OLR data was also in agreement, showing their equivalent quality. Finally, the N_OLR (2006–2019) and the corrected F_OLR (2020-present) were combined to form a long time series OLR dataset that was used in the Beijing Climate Center climate monitoring system in China to monitor abnormal changes in the global convective activity. This study can provide a reference method for future weather and climate applications of Chinese satellites.

Atmospheric and ionospheric coupling phenomena associated with large earthquakes

This paper explores multi-instrument space-borne observations in order to validate physical concepts of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) in relation to a selection of major seismic events. In this study we apply some validated techniques to observations in order to identify atmospheric and ionospheric precursors associated with some of recent most destructive earthquakes: M8.6 of March 28, 2005 and M8.5 of Sept. 12, 2007 in Sumatra, and M7.9 of May 12, 2008 in Wenchuan, China. New investigations are also presented concerning these three earthquakes and for the M7.2 of March 2008 in the Xinjiang-Xizang border region, China (the Yutian earthquake). It concerns the ionospheric density, the Global Ionospheric Maps (GIM) of the Total Electron Content (TEC), the Thermal Infra-Red (TIR) anomalies, and the Outgoing Longwave Radiation (OLR) data. It is shown that all these anomalies are identified as short-term precursors, which can be explained by the LAIC concept proposed in [S. Pulinets, D. Ouzounov, J. Asian Earth Sci. 41, 371 (2011)].

The Outgoing Longwave Radiation Analysis of Medium and Strong Earthquakes

Two approaches are applied to outgoing longwave radiation (OLR) data to obtain abnormal changes before and after six earthquakes: the background field analysis (BFA) method, which focuses on statistically processing the increment of a radiation value to the multiyear average of the data; and the tidal force fluctuant analysis method, which abandons background data for many years by using the influence of tidal fluctuations to obtain incremental changes in radiation. The results demonstrate that the increase in OLR data identified via the BFA method was uncertain. In the time distribution, the occurrence time of anomalies is isolated and not continuous. In the spatial distribution, many OLR enhancement areas occurred multiple times in the nonseismic and remote seismic-related fault structure areas. In contrast, through the tidal force fluctuant analysis method a clear and consecutive OLR anomaly emerged in the seismogenic cycle of the tidal force. It corresponded with the tidal force through a unique evolution: increased-earthquake-shrink around the epicentre, consistent with the change in the law of thermal radiation during the rock-breaking process under stress, and clearly related to the earthquake's seismic tectonic stress change. It is proven that the tidal force of a celestial body may trigger an earthquake when the tectonic stress reaches its critical breaking point, and when the triggering action is a continuous rather than brief one-shot process. The in situ stress state is key. The OLR anomaly was the physical performance of underlying surface radiation from the change in seismic tectonic stress.

Exploring the Factors Influencing the Strength and Variability of Convectively Coupled Mixed Rossby–Gravity Waves

AbstractThe three-dimensional structure, horizontal and vertical propagation characteristics, and convection–circulation coupling of the convectively coupled westward-propagating mixed Rossby–gravity (MRG) waves are examined by classifying the waves based on their amplitude. Convective signals of the MRG waves were identified and isolated using empirical orthogonal function analysis of wavenumber–frequency-filtered outgoing longwave radiation (OLR) data. It was found that about 50% of the MRG waves occur during the August–November months, and this strong seasonality was considered while characterizing the MRG waves. Five strong and five weak MRG wave seasons were identified during 1979–2019, based on seasonal wave amplitude, and through this classification, significant differences in the strength of convection–circulation coupling, zonal scale of circulation, vertical structure, and propagation characteristics of MRG waves were brought out. It was also found that the seasonal mean background state is significantly different during strong and weak MRG wave seasons. While a La Niña–like background state was found to favor enhanced MRG wave activity, the MRG wave activity is mostly suppressed during an El Niño–like background state. The presence of extratropical wave intrusions is another factor that distinguishes the strong MRG wave seasons from the weak ones. Eastward- and northeastward-propagating extratropical wave trains from the South Atlantic to the east Indian Ocean were observed during strong MRG wave seasons.

Observational evidence of equatorial ionospheric response to severe cyclonic storms ‘AILA’ and ‘WARD’ observed over the North Indian Ocean

This work addresses the vertical atmosphere –ionosphere coupling through two cyclonic events AILA (23–26 May 2009) and ‘WARD’ (10–16 December 2009) observed over the North Indian Ocean. Combined ground Digisonde Tirunelveli (8.7oN, 77.8oE) observation, ECMWF reanalysis, and NOAA Outgoing Longwave Radiation data used to reveal the connection between atmosphere –ionosphere system. At the time of tropical cyclone, we observed a decrease in surface pressure and an increase of sustained oceanic winds. Thereby increases the tropical convection observed from the lowered OLR (Outgoing Longwave Radiation). The existence of Gravity wave oscillations of period ~4 h at the stratosphere and ionosphere regions indicate the propagation of low-frequency GWs (Gravity Waves) from the lower atmosphere. Weak eastward stratospheric winds observed at the time of onset of the cyclonic storm in both AILA and WARD events. The Ionospheric parameter foF2 and h’F2 show strong modulation at the time of cyclones AILA and WARD.

Dynamical Roles of Mixed Rossby–Gravity Waves in Driving Convective Initiation and Propagation of the Madden–Julian Oscillation: General Views

AbstractMotivated by the previous case study, this work shows that dynamical variations of mixed Rossby–gravity waves with tropical depression–type circulations (MRGTDs) are possible drivers of convective initiation and propagation of the Madden–Julian oscillation (MJO) by performing statistical analysis. MJO events initiated in the Indian Ocean (IO) in boreal winter are objectively identified solely using outgoing longwave radiation data. The lagged-composite analysis of detected MJO events demonstrates that MJO convection is initiated in the southwestern IO (SWIO), where strong MRGTD–convection coupling is statistically found. Further classification of MJO cases in terms of intraseasonal convection and MRGTD activities in the SWIO suggests that 26 of 47 cases are related to more enhanced MRGTDs, although they can also be secondarily affected by Kelvin waves. For those MRGTD-enhanced MJO events, MJO convective initiation is primarily triggered by low-level MRGTD circulations that develop via the enhancement of downward energy dispersion in accordance with upper-tropospheric baroclinic conversion. This is supported by the modulation of MRGTD structure associated with zonal wave contraction due to upper-tropospheric zonal convergence, and plentiful moisture advected into the western IO. Following this MRGTD-induced MJO triggering and midtropospheric premoistening in the IO contributed by MRGTD shallow circulations as well as intraseasonal winds during the MJO-suppressed phase, low-level MRGTD winds with eastward group velocity successively trigger convection to the east, which helps MJO convective propagation over the IO. The interannual atmospheric variability may affect whether the presented MRGTD-related processes are effective or not.

Analysis of Synoptic Disturbance in Maritim Continent Using Spherical Harmonics Transformation Method

This study aims to modify the idea of ​​WK99-analyzing the existence of signature in wave-number and frequency spectrum when the analyzed Outgoing Longwave Radiation (OLR) data is associated with a unique phenomenon in Maritime Continent (MC), Borneo vortex (BV). Although BV is often related to easterly equatorial wave disturbances, there was no specific study to examine its behavior in the spectral domain. The purpose of this study is to develop a method to diagnose certain signatures of BV through spectrum analysis of OLR data when BV occurs.
 In contrast to previous studies, to present the unique phenomenon in MC as a target for diagnostics, spectrum analysis is performed by Spherical Harmonics (SH). The results of the OLR data spectrum comparison when BV occurs with the OLR data spectrum when BV does not occur that in the anti-symmetrical component when BV occurs, the tropical depression-mixed Rossby gravity (TD-MRG) wave spectrum is stronger, especially in zonal wave-numbers 5 to 10 and frequencies 0.12 to 0.2. Similar to the anti-symmetrical component, the TD-MRG spectrum of the symmetrical component is also stronger at zonal wave-numbers 5 to 10 and frequencies 0.12 to 0.2. Moreover, the westward-propagating inertio-gravity (WIG) wave spectrum in the symmetrical component is also stronger at the time of BV than when there is no BV, especially at zonal wave-numbers 7 to 13 and frequencies 0.38 to 0.5. It can be concluded that when BV occurs, equatorial waves that propagate to the west, especially the types of TD-MRG and WIG waves are stronger than when BV did not occur. The results of durational grouped spectrum analysis of OLR data when BV occurs indicate that the longer the duration of BV occurs, the stronger the spectrum of TD-MRG and WIG wave types gets.