Outgoing Longwave Radiation Anomalies Research Articles

A statistical–dynamical approach for probabilistic prediction of sub-seasonal precipitation anomalies over 17 hydroclimatic regions in China

Abstract. In this study, we develop a spatial–temporal projection-based calibration, bridging, and merging (STP-CBaM) method to improve probabilistic sub-seasonal precipitation forecast skill over 17 hydroclimatic regions in China. The calibration model is established by post-processing ECMWF raw forecasts using the Bayesian joint probability (BJP) approach. The bridging models are built using large-scale atmospheric intraseasonal predictors, including zonal wind at 200 hPa (U200) and 850 hPa (U850); an outgoing longwave radiation anomaly (OLRA); and geopotential height at 200 hPa (H200), 500 hPa (H500), and 850 hPa (H850) defined by the STP method. The calibration model and the bridging models are then merged through the Bayesian modelling averaging (BMA) method. Our results indicate that the forecast skill of the calibration model is higher compared to bridging models when the lead time is within 5–10 d. The U200- and OLRA-based bridging models outperform the calibration model in certain months and certain regions. The BMA-merged forecasts take advantage of both calibration models and bridging models. Meanwhile, the BMA-merged forecasts also show high reliability at longer lead times. However, some improvements to reliability are still needed at shorter lead times. These findings demonstrate the great potential to combine dynamical models and statistical models in improving sub-seasonal precipitation forecasts.

A comprehensive study on the synchronized outgoing longwave radiation and relative humidity anomalies related to global Mw ≥ 6.5 earthquakes

A comprehensive study on the synchronized outgoing longwave radiation and relative humidity anomalies related to global Mw ≥ 6.5 earthquakes

Study of The Impact of Convectively Coupled Equatorial Kelvin and Rossby Waves on Rainfall Extremes in Sulawesi, Indonesia

This study examined the impact of Equatorial Kelvin and Equatorial Rossby (ER) waves on rainfall extremes over Sulawesi Island, Indonesia. Impacts are assessed by changes in the probability of rainfall events that exceeded extreme value and changes in the fraction of wet days. Using Asian Precipitation – Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE) rainfall data and Outgoing Longwave Radiation (OLR) from NOAA, impacts are quantified with the respect to wave’s local phase grouping. The local wave phase is based on the standardized OLR anomalies and their temporal tendency. Results showed that Kelvin and ER wave can modulate daily rainfall extremes over Sulawesi Island. Kelvin wave has the strongest impact with changes in the probability of extreme rainfall by up to +100% (-70%) in phases 5 and 6 (1 and 2) and increases the value of wet day fraction by up to > 0.04. Followed by the ER wave with changes in the probability of extreme rainfall by up to +50% (-50%) in phase 4 (1 and 2) and increases the value of the wet day fraction by up to 0.05. The superposition between ER and Kelvin wave occurrence increases the possibility of extreme rainfall occurrence by up to 100 % in almost every part of Sulawesi island in phases 4,5 and 6. The results suggest that Kelvin and ER waves can be another important source of predictability for extreme rainfall on Sulawesi Island.

Tropical‐wave activity and Madden–Julian oscillation termination

AbstractThe Madden–Julian oscillation (MJO) is the dominant mode of intraseasonal variability in the tropics and generates large‐scale precipitation, cloud, and circulation anomalies. Interactions between the MJO and dry and convectively coupled equatorial waves (CCEWs) have been identified in previous works; however, these studies have not focused on MJO events that maintain themselves versus those that decay. Knowledge on how pre‐existing MJO events interact with CCEWs is important for producing more realistic and reliable representations of MJO events in weather forecast and global climate models. This study presents an analysis of intraseasonally varying outgoing longwave radiation (OLR) and zonal wind anomalies at 200 and 850 hPa from National Oceanic and Atmospheric Administration (NOAA) observations and ERA‐Interim reanalysis data respectively, throughout the lifetime of observed MJO events. A climatology of continuing and terminating MJO events is created from an event identification algorithm using common tracking indices including the OLR‐based MJO Index (OMI), filtered OMI (FMO), real‐time multivariate MJO (RMM), and velocity potential MJO (VPM) index. Wheeler–Kiladis power spectra are calculated for each event type to identify predominant wave modes. Symmetric and anti‐symmetric wave spectra are composited and results include the sensitivity of the variables used to define the waves and index choice for identifying the MJO. Our results show fractional differences between continuing and terminating MJO events that are statistically significant at the 95% level. Statistical significance is most prominent within the MJO band where continuing events have higher power, as well as global mixed Rossby–gravity (MRG) waves and tropical depression (TD) waves where terminating events have higher power. These results are mostly robust to meteorological variable and index although the importance of Kelvin waves is amplified in the VPM. A regional analysis including phase separation contains results that are sensitive to variable and domain although westward traveling waves are commonly associated with MJO termination regardless of location.

Probabilistic subseasonal precipitation forecasts using preceding atmospheric intraseasonal signals in a Bayesian perspective

Abstract. Accurate and reliable subseasonal precipitation forecasts are of great socioeconomic value for various aspects. The atmospheric intraseasonal oscillation (ISO), which is one of the leading sources of subseasonal predictability, can potentially be used as predictor for subseasonal precipitation forecasts. However, the relationship between atmospheric intraseasonal signals and subseasonal precipitation is of high uncertainty. In this study, we develop a spatiotemporal-projection-based Bayesian hierarchical model (STP-BHM) for subseasonal precipitation forecasts. The coupled covariance patterns between the preceding atmospheric intraseasonal signals and precipitation are extracted, and the corresponding projection coefficients are defined as predictors. A Bayesian hierarchical model (BHM) is then built to address the uncertainty in the relationship between atmospheric intraseasonal signals and precipitation. The STP-BHM model is applied to predict both the pentad mean precipitation amount and pentad mean precipitation anomalies for each hydroclimatic region over China during the boreal summer monsoon season. The model performance is evaluated through a leave-1-year-out cross-validation strategy. Our results suggest that the STP-BHM model can provide skillful and reliable probabilistic forecasts for both the pentad mean precipitation amount and pentad mean precipitation anomalies at leads of 20–25 d over most hydroclimatic regions in China. The results also indicate that the STP-BHM model outperforms the National Centers for Environmental Prediction (NCEP) subseasonal to seasonal (S2S) model when the lead time is beyond 5 d for pentad mean precipitation amount forecasts. The intraseasonal signals of 850 and 200 hPa zonal wind (U850 and U200) and 850 and 500 hPa geopotential height (H850 and H500) contribute more to the overall forecast skill of the pentad mean precipitation amount predictions. In comparison, the outgoing longwave radiation anomalies (OLRAs) contribute most to the forecast skill of the pentad mean precipitation anomaly predictions. Other sources of subseasonal predictability, such as soil moisture, snow cover, and stratosphere–troposphere interaction, will be included in the future to further improve the subseasonal precipitation forecast skill.

Effect of Advection by Upper-Tropospheric Background Zonal Wind on MJO Phase Speed

Abstract A robust linear regression algorithm is applied to estimate 95% confidence intervals on the background wind associated with Madden–Julian oscillation (MJO) upper-tropospheric atmospheric circulation signals characterized by different phase speeds. Data reconstructed from the ERA5 to represent advection by the upper-tropospheric background flow and MJO-associated zonal wind anomalies, together with satellite outgoing longwave radiation anomalies, all in the equatorial plane, are regressed against advection data filtered for zonal wavenumber 2 and phase speeds of 3, 4, 5, and 7 m s−1. The regressed advection by the background flow is then divided by the negative of the zonal gradient of regressed zonal wind across the central Indian Ocean base longitude at 80°E to estimate the associated background wind that leads to the given advection. The median estimates of background wind associated with these phase speeds are 13.4, 11.2, 10.5, and 10.3 m s−1 easterly. The differences between estimated values at neighboring speeds suggests that advection acts most strongly in slow MJO events, indicating that the slowest events happen to be slow because they experience stronger easterly advection by the upper-tropospheric background wind. Significance Statement The Madden–Julian oscillation (MJO) is the dominant subseasonal rainfall signal of the tropical atmosphere. This project shows that the background wind of the tropical atmosphere most especially slows down the slowest MJO events. Understanding what controls its speed might help scientists better predict events.

A Survey of Statistical Relationships between Tropical Cyclone Genesis and Convectively Coupled Equatorial Rossby Waves

Convectively coupled equatorial Rossby waves (ERW) modulate tropical cyclone activities over tropical oceans. This study presents a survey of the statistical relationship between intraseasonal ERWs and tropical cyclone genesis (TCG) over major global TC basins using four-decade-long outgoing longwave radiation (OLR) and TC best-track datasets. Intraseasonal ERWs are identified from the OLR anomalies using an empirical orthogonal function (EOF) analysis method without imposing equatorial symmetry. We find that westward-propagating ERWs are most significant in four tropical ocean basins over the summer hemisphere and that ERWs exhibit similar northeast-southwest (southeast-northwest) tilted phase lines in the northern (southern) hemisphere, with an appreciable poleward advance of wave energy in most TC basins. The EOF-based ERW indices quantitatively show that ERWs significantly modulate TC genesis. The convectively active (suppressed) phases of ERWs coincide with increased (reduced) TCG occurrences. The TCG modulation by ERWs achieves the maximum where the ERWs propagate through the climatological TCG hotspots. As a result, the total number of TCG occurrences in the TC basins varies significantly according to the ERW phase. The ERW-TCG relationship is significant over the northwestern Pacific Ocean, northeastern Pacific Ocean, and the northern Indian Ocean during the northern summer seasons. In the southern summer season, the ERW-TCG relationship is significant over the southern Indian Ocean, Indonesian-Australia basin, and the southwestern Pacific Ocean. However, ERW activities are weak in the main TC development region of the Atlantic Ocean; and the impact on Atlantic TCG appears to be insignificant.

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.

Roles of synoptic‐scale waves and intraseasonal oscillations in the onset of the South China Sea summer monsoon

AbstractThe maintenance period (20 days after the onset day) of the South China Sea (SCS) summer monsoon (SCSSM) onset is investigated in this paper, the main focus of which is the roles of synoptic‐scale (2–10‐day period) waves (SSWs) relative to those of 10–20‐day and 30–60‐day intraseasonal oscillations (ISOs). The results reveal that the eddy kinetic energy (EKE)‐based SSW intensity displays a greater amplitude and closer relationship with the SCSSM onset date (correlation coefficient: −0.50) than either ISO during the SCSSM onset maintenance period, indicating that frequent synoptic‐scale processes play an important role in the SCSSM onset. Regression analyses based on the original EKE‐based wave intensity further reveal that SSW‐related horizontal wind anomalies show significant cyclonic anomalies over the SCS, with westerlies occupying the central and southern SCS. Moreover, SSW‐induced low‐pressure systems, including negative outgoing longwave radiation (OLR) anomalies, low‐level convergence and weakening of the 500 hPa height field, are observed over the SCS and maintain the SCSSM onset. A three‐dimensional EKE diagnosis is conducted to investigate the relative contributions of SSWs and both ISOs. The results demonstrate that the SSW‐related horizontal barotropic EKE conversion and EKE conversion from eddy available potential energy cooperate to contribute more than the two ISOs to the dynamic processes during the maintenance stage of the SCSSM onset.

Cumulative positive contributions of propagating ISO to the quick low-level atmospheric response during El Niño developing years

Based on the Australian Bureau of Meteorology (BoM) El Niño alert system, this study investigates the atmospheric and oceanic conditions during El Niño developing years between 1982 and 2016. It is found that there is a 2–5-month (subseasonal-to-seasonal) lag to establish the steady low-level atmospheric (or the Southern Oscillation Index, SOI) response than the steady El Niño-pattern Sea Surface Temperature Anomaly (SSTA), which is defined as the critical period in this research. According to the duration of this critical period, the quick and slow steady atmospheric response years can be identified among all El Niño–Southern Oscillation (ENSO) developing events. The quick establishments of the Sea Level Pressure Anomaly (SLPA) in the tropical atmosphere are proved to be closely related to the tropical atmospheric Intra-seasonal Oscillation (ISO) events. In the quick response years, the ISO events can even propagate to the eastern tropical Pacific, which lead to the cumulative negative Outgoing Longwave Radiation (OLR) and SLP anomalies there, and make a positive contribution to the quick atmospheric response at the end of the critical period. However, the eastward-propagation of ISO events is mainly restricted in the tropical Western Pacific in the slow response years, causing slow steady atmospheric response with almost no contributions from ISO. Furthermore, observations and several simulations are used to understand this propagation differences of the ISO between quick and slow response years.

Convective forcing of the North American Monsoon anticyclone at intraseasonal and interannual time scales.

In the upper troposphere and lower stratosphere (UTLS), large-scale anticyclones associated with monsoons play major roles in tropospheric and stratospheric transport and mixing. To understand the forcing of the North American monsoon anticyclone (NAMA), this study examines the connection between precipitation over the tropics and subtropics of the North American longitude sector and the variability of the troposphere and lower stratosphere. Using ERA5 reanalysis and outgoing longwave radiation (OLR) data from 1979âĂŞ2019, we assess the relationship at the intraseasonal time scale using pentad-mean time series. We show that OLR anomalies are correlated with circulation anomalies northwest and northeast of the region of precipitation. Decreased OLR (increased precipitation) corresponds to increased geopotential heights and anticyclonic circulation anomalies in the 300 - 100 hPa layer and an opposite response in the lower tropospheric 850 - 600 hPa layer. The results are consistent with the established theory of the Rossby wave response to latent heating. The increase in height, which is strongest near 150 hPa, indicates that increased precipitation is associated with a strengthened NAMA. UTLS temperatures also have significant correlations with OLR, with cold (warm) anomalies occurring above (below) the core of the anticyclonic anomaly consistent with large-scale balance. The vertical structure of geopotential and temperature anomalies is compared to simulations using an idealized general circulation model, which shows that such a vertical structure is a consistent response to diabatic heating. Correlations at the interannual time scale resemble those at the intraseasonal time scale, demonstrating that precipitation is related to the NAMA at both time scales.

Active and weakening MJO events in the Maritime Continent

To better understand the Madden–Julian Oscillation (MJO) in the Maritime Continent (MC), events from 1980 to 2019 were classified as active or weakening according to propagation characteristics and amplitude changes in two leading indices, the Real-time Multivariate MJO (RMM) index and Outgoing Longwave Radiation (OLR) MJO Index (OMI). Active MJO events had larger index amplitudes than weakening events, and those amplitude differences appeared at day − 3 in the RMM and day − 8 in the OMI and remained through day + 15 in both indices (day 0 marked the day an event entered the MC). Thus, active events were stronger than weakening events as they approached and crossed the MC. To understand differences in environments between these events, composites of OLR and specific humidity were compared for each. Active MJO events had consistently more negative OLR anomalies and greater specific humidity in both the boundary layer and free troposphere than weakening MJO events. Those differences persisted during both easterly and westerly phases of the Quasi-biennial Oscillation (QBO) and during La Niña and El Niño. Active MJO events during QBO westerly winds had more specific humidity than active events did during QBO easterly winds. Finally, both active and weakening MJO events featured a diurnal cycle of lower-tropospheric specific humidity over land areas of the MC, and the amount of atmospheric moisture available to active events was consistently greater than weakening ones. These results indicate that index amplitude, OLR, and tropospheric specific humidity can all be important tools in identifying active and weakening MJO events in the MC, including for different phases of the QBO and the El Niño-Southern Oscillation (ENSO).

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.

Detecting Thermal Anomalies of Earthquake Process Within Outgoing Longwave Radiation Using Time Series Forecasting Models

The catastrophic damages caused by the Jiuzhaigou earthquake in China of August 8, 2017 and the Mexico earthquake of September 20, 2017 have revealed some important weaknesses of currently operational earthquake-monitoring and forecasting systems. In this work, six time series forecasting models were applied to detect pre-earthquake anomalies within infrared outgoing longwave radiation. After comparing their prediction results using non-seismic time series data, the autoregressive integrated moving average (ARIMA) model was selected as the optimal model, and then a new prediction method based on this ARIMA model was proposed. The results show that the values observed on July 27 and August 5 before the Jiuzhaigou earthquake in China exceed the confidence interval for prediction and reaches the maximum on August 5, 2017. This indicates the infrared outgoing longwave radiation (IR-OLR) anomalies before the Jiuzhaigou earthquake in China. For the Mexico earthquake, pre-earthquake IR-OLR anomalies are detected on September 14, 18, and 19, and reaches the maximum on September 14, 2017. This demonstrates that the proposed time series forecasting model based on ARIMA could be an effective method for earthquake anomalies detection within infrared outgoing longwave radiation.

Recent weakening in MJO-related convective activity over the equatorial Indian Ocean and Maritime Continent

We document the observed changes in the intraseasonal variability of precipitation and outgoing longwave radiation (OLR) associated with the Madden-Julian Oscillation (MJO) from 1998 to 2015 when reliable and simultaneous satellite-derived daily precipitation and OLR are available. Tropical Rainfall Measuring Mission (TRMM) observations show a statistically significant weakening trend in variance of convective activity associated with the MJO across the equatorial Indian Ocean (EQIO) and Maritime Continent (MC) in boreal summer and winter seasons. During northern summer, the MJO variability in the POST period (2007–2015) displays a remarkable reduction in convection at all wavenumbers compared with that in the PRE period (1998–2006). During northern winter, along with a reduction in variance, the MJO-related activity is shifted from lower to higher wavenumbers by breaking down the associated convection into smaller scales. EQIO and MC experience a shift from a higher probability of stronger events to weaker events during both seasons in the multivariate Wheeler-Hendon Index. Moreover, there is a southward shift in the location of maximum variance, increasing (reducing) meridional symmetry in MJO variance during boreal summer (winter). This is manifested by a significant increase in boreal winter MJO variance over northern Australia. We also observed that over western EQIO, OLR anomalies associated with dry (wet) phase of MJO are higher (lower) in POST as compared with the PRE period indicating warmer surface temperatures and taller clouds during dry and wet phases of MJO respectively, which is consistent with observation. The exact opposite behavior is seen over the MC and Western Pacific Oceans. These variations in MJO can have important implications for the local and remote climate systems across the globe.

Relationship between Rainfall Pattern in North Central and Southern Nigeria and Some Tropical Climate Systems

Monthly rainfall data from meteorological stations in Nigeria are analyzed from 1951 to 1992, to establish their relationship with some Tropical climate systems. The climate systems include Tropical South Atlantic (TSA) sea surface temperature index, North Atlantic Ocean (NAO) atmospheric index, Tropical North Atlantic (TNA) sea surface temperature index, Central India Precipitation (CIP) and and Outgoing Longwave Radiation Anomaly (OLRA)). The rainfall pattern was given in terms of the August break (quantified in terms of the monsoon break intensity (MBI) and annual rainfall anomaly index (RAI). Partial correlation analysis was carried out to determine the effect of the tropical climate systems on the linear association between them and the stations in Nigeria. Our results show that the rainfall anomalies although sometimes intense do not have predictable patterns. The tele connection between CIP and total rainfall in Nigeria suggests that the rainfall patterns in Nigeria is likely to be modulated by the Tropical Easterly Jet (TEJ) connecting rainfall pattern in Central India to that in Nigeria. The August break is observed to be highly variable and does not show a clear discernable pattern of variability. Its variability may be connected with multiple forcings from ocean and mesoscale circulations.

Tracking of Tropical Intraseasonal Convective Anomalies: 1. Seasonality of the Tropical Intraseasonal Oscillations.

A tracking algorithm based upon a multiple object tracking method is developed to identify, track, and classify Tropical Intraseasonal Oscillations (TISO) on the basis of their direction of propagation. Daily National Oceanic and Atmospheric Administration Outgoing Longwave Radiation anomalies from 1979–2017 are Lanczos band‐pass filtered for the intraseasonal time scale (20–100 days) and spatially averaged with nine neighboring points to get spatially smoothed anomalies over large spatial scales (~105 km2). TISO events are tracked by using a two‐stage Kalman filter predictor‐corrector method. Two dominant components of the TISO (Eastward propagating and Northward propagating) are classified, and it is found that TISO remains active throughout the year. Eastward‐propagating TISO events occur from November to April with a phase speed of ~4 m/s and northward‐propagating TISO events occur from May to October with a phase speed of ~2.5 m/s in both the Indian and Pacific Ocean basins. Composites of the mean background states (wind; sea surface temperature, SST; and moisture) reveal that the co‐occurrence of warm SST and mean westerly zonal wind plays an important role in the direction of propagation and the geographical location of TISO events. In mean state sensitivity experiments with Sp‐CAM4, we have found that the seasonality of TISO in terms of the geographical location of occurrences and direction of propagation is primarily associated with the annual march of the maximum SST and low level zonal wind which tends to follow the SST.

Southern Hemisphere Sensitivity to ENSO Patterns and Intensities: Impacts over Subtropical South America

El Niño flavors influence Subtropical South American (SSA) rainfall through the generation of one or two quasi-stationary Rossby waves. However, it is not yet clear whether the induced wave trains depend on the El Niño pattern and/or its intensity. To investigate this, we performed different sensitivity experiments using an Atmospheric General Circulation Model (AGCM) which was forced considering separately the Canonical and the El Niño Modoki patterns with sea surface temperature (SST) maximum anomalies of 1 and 3 °C. Experiments with 3 °C show that the Canonical El Niño induces two Rossby wave trains, a large one emanating from the western subtropical Pacific and a shorter one initiated over the central-eastern subtropical South Pacific. Only the shorter wave plays a role in generating negative outgoing longwave radiation (OLR) anomalies over SSA. On the other hand, 3 °C El Niño Modoki experiments show the generation of a large Rossby wave train that emanates from the subtropical western south Pacific and reaches South America (SA), promoting the development of negative OLR anomalies over SSA. Experiments with 1 °C show no impacts on OLR anomalies over SSA associated with El Niño Modoki. However, for the Canonical El Niño case there is a statistically significant reduction of the OLR anomalies over SSA related to the intensification of the upper level jet stream over the region. Finally, our model results suggest that SSA is more sensitive to the Canonical El Niño, although this result may be model dependent.

Re‐examining the decadal change of tropical cyclogenesis over the South China Sea around the mid‐1990s

A distinct inter‐decadal increase of tropical cyclone (TC) frequency occurred over the South China Sea (SCS) around the mid‐1990s. Previous studies linked this TC frequency increase to changes in seasonal mean background fields and in the intensity of intra‐seasonal oscillations according to regional and seasonal mean fields. The present study compares the contributions of environmental factors on different timescales to inter‐decadal change of the SCS TC frequency from a local and instantaneous perspective. It is shown that the intra‐seasonal variations of lower‐level vorticity, mid‐level specific humidity, and vertical motion have a dominant contribution to the SCS TC genesis during both 1979–1993 and 1994–2002. The inter‐annual anomalies of sea surface temperature (SST), outgoing longwave radiation (OLR), and vertical motion display an increase of favourable state near TC genesis regions at the mid‐1990s. The intra‐seasonal components of favourable OLR and vertical motion anomalies are larger in the latter period than in the former period. The synoptic components of favourable lower‐level vorticity, vertical wind shear, and mid‐level specific humidity anomalies increase from the former period to the latter period. The present study shows that the contributions of environmental factors to the SCS TC frequency have increased on different timescales around the mid‐1990s. The results suggest that this inter‐decadal increase of TC frequency may include both effects of dynamical‐driven changes and stochastic processes.

New real-time indices for the quasi-biweekly oscillation over the Asian summer monsoon region

The quasi-biweekly oscillation (QBWO), with a periodicity of 10–30 days, is one of the most important modes of intraseasonal variability over the Asian summer monsoon region. Unlike the lower frequency (30–60 days) Madden–Julian Oscillation, which has had several real-time indices proposed for monitoring and predicting its state, there are very few equivalents for the QBWO. Given that extended empirical orthogonal function (EEOF) analysis is arguably more suitable than empirical orthogonal function analysis for capturing the canonical spatial and temporal structure of a propagating wave system, we introduce two new indices for real-time monitoring of the QBWO over the tropical western North Pacific (WNP) and Indian Ocean (IO), separately, by projecting outgoing longwave radiation (OLR) anomalies onto the two leading modes of EEOF analysis for the 10–30-day-filtered OLR anomalies over the two basins during 1980–2012. The newly proposed QBWO indices faithfully represent the vigorous QBWO activities over the WNP and IO, which are underestimated and/or not necessarily well represented by existing indices. It is also shown that the indices are able to reveal the connections between the QBWO and other pronounced phenomena, such as the onset of the South China Sea and Indian monsoons, the occurrence of extreme rainfall events, and tropical cyclone genesis. Thus, monitoring and predicting the evolution of the QBWO in these two basins based on the new QBWO indices should help in the quest to mitigate future damage caused by weather-related disasters at an extended lead time.