Madden–Julian Oscillation Research Articles

Using Simple, Explainable Neural Networks to Predict the Madden‐Julian Oscillation

AbstractFew studies have utilized machine learning techniques to predict or understand the Madden‐Julian oscillation (MJO), a key source of subseasonal variability and predictability. Here, we present a simple framework for real‐time MJO prediction using shallow artificial neural networks (ANNs). We construct two ANN architectures, one deterministic and one probabilistic, that predict a real‐time MJO index using maps of tropical variables. These ANNs make skillful MJO predictions out to ∼18 days in October‐March and ∼11 days in April‐September, outperforming conventional linear models and efficiently capturing aspects of MJO predictability found in more complex, dynamical models. The flexibility and explainability of simple ANN frameworks are highlighted through varying model input and applying ANN explainability techniques that reveal sources and regions important for ANN prediction skill. The accessibility, performance, and efficiency of this simple machine learning framework is more broadly applicable to predict and understand other Earth system phenomena.

Tropical, Subtropical, and Extratropical Atmospheric Rivers in the Australian Region

AbstractStudies of atmospheric rivers (ARs) over Australia have, so far, only focused on northwest cloudband–type weather systems. Here we perform a comprehensive analysis of AR climatology and impacts over Australia that includes not only northwesterly systems, but easterly and extratropical ARs also. We quantify the impact of ARs on mean and extreme rainfall including assessing how the origin location of ARs can alter their precipitation outcomes. We found a strong relationship between ARs and extreme rainfall in the agriculturally significant Murray–Daring basin region. We test the hypothesis that the tropical and subtropical originating ARs we observe in Australasia differ from canonical extratropical ARs by examining the vertical structure of ARs grouped by origin location. We found that in the moisture abundant tropics and subtropics, wind speed drives the intensity of ARs, while in the extratropics, the strength of an AR is largely determined by moisture availability. Finally, we examine the modulation of AR frequency by different climate modes. We find weak (but occasionally significant) correlations between ARs frequency and El Niño–Southern Oscillation, the Indian Ocean dipole, and the southern annular mode. However, there is a stronger relationship between the phases of the Madden–Julian oscillation and tropical AR frequency, which is an avenue for potential skill in forecasting ARs on subseasonal time scales.

Assimilating Retrieved Water Vapor and Radar Data from NCAR S-PolKa: Performance and Validation Using Real Cases

Abstract This study investigated the effect of the assimilation of the S- and Ka-band dual‐wavelength-retrieved water vapor data with radial wind and reflectivity data. The vertical profile of humidity, which provides environmental information before precipitation occurs, was obtained at low levels and thinned into averaged and four-quadrant profiles. Additionally, the following two strategies were examined: 1) assimilation of water vapor data with radar data for the entire 2 h and 2) assimilation of water vapor data in the first hour, and radial velocity and reflectivity data in the second hour. By using the WRF local ensemble transform Kalman filter data assimilation system, three real cases of the Dynamics of the Madden–Julian Oscillation experiment were examined through a series of experiments. The analysis results revealed that assimilating additional water vapor data more markedly improved the analysis at the convective scale than assimilating radial wind and reflectivity data alone. In addition, the strategy of assimilating only retrieved water vapor data in the first hour and radial wind and reflectivity data in the second hour achieved the optimal analysis and subsequent very short-term forecast. The evaluation of quantitative precipitation forecasting demonstrated that assimilating additional retrieved water vapor data distinctly improved the rain forecast compared with assimilating radar data only. When moisture data were assimilated, improved nowcasting could be extended up to 4 h. Furthermore, assimilating moisture profiles into four quadrants achieved more accurate analysis and forecast. Overall, our study demonstrated that the humidify information in nonprecipitation areas is critical for further improving the analysis and forecast of convective weather systems.

How Long Can the MJO be Predicted During the Combined Phases of ENSO and QBO?

AbstractThe predictability limit of the Madden‐Julian Oscillation (MJO) in the El Niño and La Niña boreal winters (November‐February) is investigated using observational data and historical run outputs of CMIP models. The MJO predictability is computed by the nonlinear local Lyapunov exponents approach for various MJO indices obtained from bandpass‐filtered (30–80 days) outgoing longwave radiation, 850‐hPa zonal wind, and 200‐hPa zonal wind data. The result shows that the MJO predictability during La Niña winters is enhanced by up to 8 days compared to El Niño winters. Enhanced convection of the MJO phases 2–4 with persistence propagation during La Niña winters leads to higher predictability, as compared with those for El Niño winters. The highest (lowest) predictability of the MJO shows 39 (31) days during La Niña/EQBO (El Niño/EQBO) winters. The longer persistence of the MJO during La Niña/EQBO winters leads to higher predictability.

Forecasts of MJO during DYNAMO in a Coupled Tropical Channel Model: Impact of Planetary Boundary Layer Schemes

It is challenging to predict the eastward-propagating Madden–Julian Oscillation (MJO) events across the Maritime Continent (MC) in models. We constructed an air–sea coupled numerical weather prediction model—a tropical channel model—to investigate the role of the planetary boundary layer (PBL) scheme on eastward-propagating and non-propagating MJO precipitation events during the Dynamics of the MJO (DYNAMO) campaign period. Analysis of three hindcast experiments with different PBL schemes illustrates that the PBL scheme is crucial to simulating the eastward-propagating MJO events. The experiment with the University of Washington (UW) PBL scheme can predict the convection activity over the MC due to a good representation of moist static energy (MSE) tendency relatively well. The horizontal advection and the upward transport of moisture from the PBL to the free atmosphere play a major role in the MSE tendency ahead of MJO convection. The difference in the meridional component of MSE advection accounts for the different MSE budgets in the three hindcast experiments. A well-simulated meridional advection can transport the meridional water vapor to moisten the MC. Our results suggest that a proper PBL scheme with better simulated meridional water vapor distribution is crucial to predicting the eastward propagation of MJO events across the MC in the tropical channel model.

Forecasts of MJO during DYNAMO in a coupled tropical channel model, Part I: Impact of parameterization schemes

AbstractA coupled tropical channel model is developed to forecast the Madden–Julian Oscillation (MJO) event during the Dynamics of the MJO (DYNAMO) campaign period. Eight sets of 30‐day hindcast experiments are performed using different combinations of cumulus parameterization and planetary boundary layer (PBL) schemes. The results indicate that a well‐simulated mean state is a prerequisite for MJO forecast, and the model's ability to reproduce the mean state is sensitive to the parameterization schemes. The experiment with Tiedtke (TDK) cumulus parameterization and University of Washington (UW) PBL schemes can successfully predict the MJO event. Over the equatorial Indian Ocean, this experiment has a good representation of zonal sea surface temperature (SST) gradient and low‐level westerly wind, favouring a reasonable atmospheric circulation. As a result of boundary‐layer convergence in the eastern Indian Ocean, more water vapour is gathered in the low‐middle troposphere by updrafts, contributing to the PBL moistening ahead of the MJO convection and the eastward‐propagation of MJO precipitation. Further analysis reveals that the high cloud is accompanied by strong convection. A better simulation in tropical high cloud fraction helps trap the cloud radiation heating to warm middle‐upper troposphere, which promotes the MJO propagation. Our results suggest that the selection of proper parameterization schemes with a better‐simulated mean state is crucial to predicting the MJO event in the tropical channel model.

Intraseasonal variability of global land monsoon precipitation and its recent trend

Accurate prediction of global land monsoon rainfall on a sub-seasonal (2–8 weeks) time scale has become a worldwide demand. Current forecasts of weekly-mean rainfall in most monsoon regions, however, have limited skills beyond two weeks, calling for a more profound understanding of monsoon intraseasonal variability (ISV). We show that the high-frequency (HF; 8–20 days) ISV, crucial for the Week 2 and Week 3 predictions, accounts for about 53–70% of the total (8–70 days) ISV, generally dominating the sub-seasonal predictability of various land monsoons, while the low-frequency (LF; 20–70 days)’s contribution is comparable to HF only over Australia (AU; 47%), South Asia (SA; 43%), and South America (SAM; 40%). The leading modes of HFISVs in Northern Hemisphere (NH) monsoons primarily originate from different convectively coupled equatorial waves, while from mid-latitude wave trains for Southern Hemisphere (SH) monsoons and East Asian (EA) monsoon. The Madden-Julian Oscillation (MJO) directly regulates LFISVs in Asian-Australian monsoon and affects American and African monsoons by exciting Kelvin waves and mid-latitude teleconnections. During the past four decades, the HF (LF) ISVs have considerably intensified over Asian (Asian-Australian) monsoon but weakened over American (SAM) monsoon. Sub-seasonal to seasonal (S2S) prediction models exhibit higher sub-seasonal prediction skills over AU, SA, and SAM monsoons that have larger LFISV contributions than other monsoons. These results suggest an urgent need to improve the simulation of convectively coupled equatorial waves and two-way interactions between regional monsoon ISVs and mid-latitude processes and between MJO and regional monsoons, especially under the global warming scenarios.

A Statistical Intraseasonal Prediction Model of Extended Boreal Summer Western North Pacific Tropical Cyclone Genesis

Abstract An L2 regularized logistic regression model is developed in this study to predict weekly tropical cyclone (TC) genesis over the western North Pacific (WNP) Ocean and subregions of the WNP including the South China Sea (SCS), the western WNP (WWNP), and the eastern WNP (EWNP). The potential predictors for the TC genesis model include a time-varying TC genesis climatology, the Madden–Julian oscillation (MJO), the quasi-biweekly oscillation (QBWO), and ENSO. The relative importance of the predictors in a constructed L2 regression model is justified by a forward stepwise selection procedure for each region from a 0-week to a 7-week lead. Cross-validated hindcasts are then generated for the corresponding prediction schemes out to a 7-week lead. The TC genesis climatology generally improves the regional model skill, and the importance of intraseasonal oscillations and ENSO is regionally dependent. Over the WNP, there is increased model skill over the time-varying climatology in predicting weekly TC genesis out to a 4-week lead by including the MJO and QBWO, whereas ENSO has a limited impact. On a regional scale, ENSO and then either the MJO or QBWO are the two most important predictors over the EWNP and WWNP after the TC genesis climatology. The MJO is found to be the most important predictor over the SCS. The logistic regression model is shown to have comparable reliability and forecast skill scores to the ECMWF dynamical model on intraseasonal time scales. Significance Statement Skillful forecasts of tropical cyclone activity on time scales from short-range to seasonal are now issued operationally. Although there has been great progress in the understanding of physical mechanisms driving tropical cyclone (TC) activity, intraseasonal prediction of TCs remains a significant scientific challenge. This study develops a statistically based intraseasonal model to predict weekly TC genesis over the western North Pacific Ocean basin. The intraseasonal prediction model developed here for TC genesis over the western North Pacific basin shows skill extending out to four weeks. We discuss the regional dependence of the model skill on ENSO and other subseasonal climate oscillations. This approach provides skillful intraseasonal forecasting of TCs over the western North Pacific basin.

Ocean Surface Flux Algorithm Effects on Tropical Indo-Pacific Intraseasonal Precipitation.

Surface latent heat fluxes help maintain tropical intraseasonal precipitation. We develop a latent heat flux diagnostic that depicts how latent heat fluxes vary with the near‐surface specific humidity vertical gradient (Δq) and surface wind speed (|V|). Compared to fluxes estimated from |V| and Δq measured at tropical moorings and the Coupled Ocean Atmosphere Response Experiment 3.0 (COARE3.0) algorithm, tropical latent heat fluxes in the National Center for Atmospheric Research CEMS2 and Department of Energy E3SMv1 models are significantly overestimated at |V| and Δq extrema. Madden–Julian oscillation (MJO) sensitivity to surface flux algorithm is tested with offline and inline flux corrections. The offline correction adjusts model output fluxes toward mooring‐estimated fluxes; the inline correction replaces the original bulk flux algorithm with the COARE3.0 algorithm in atmosphere‐only simulations of each model. Both corrections indicate reduced latent heat flux feedback to intraseasonal precipitation, in better agreement with observations, suggesting that model‐simulated fluxes are overly supportive for maintaining MJO convection.

The Behaviors of Intraseasonal Cloud Organization During DYNAMO/AMIE

AbstractThis study investigates the organization of tropical convection associated with the Madden‐Julian Oscillation (MJO) during the Dynamics of the MJO/Atmospheric Radiation Measurement MJO Investigation Experiment field campaign. While it is known that tropical clouds can organize and impact the large‐scale environment, how this occurs, and its underlying mechanism are not fully understood. Application of several existing cloud organization indices showed inconsistent evolutions in the measured degree of organization with the MJO. The inconsistency arises from the varying definitions and assumptions of cloud organization behaviors that are applied to each index. While these indices often combine different properties of clouds, such as their number density, size, and distance between them, the analysis of these properties separately provided further understanding of how clouds organize with the MJO. Using the rainfall clusters identified from the S‐Polka radar, we find that deep convective rainfall clusters begin to increase their number density before the arrival of MJO enhanced convective center, which is accompanied by increased proximity (shorter distance to each other) and followed by growth in their size. However, the nonrandomness in the spatial distribution of rainfall clusters maximizes as MJO convection decays. Deep convective clusters become the least randomly distributed as the clusters decay because of the suppression and decay of isolated deep convective cells, while clustered deep convective cells exist longer. This evolution of cloud organization is analogous to mesoscale convective systems, indicating that the duration and frequency of their organization stages are altered by the large‐scale environmental perturbations associated with the MJO.

Importance of integration of subseasonal predictions to improve climate services in Sri Lanka case study: Southwest monsoon 2019

The climate outlook for the 2019 southwest monsoon (SWM) season was prepared through an expert assessment of the prevailing global climate conditions and forecasts from different climate models from around the world during the fourteenth session of the South Asian Climate Outlook Forum (SASCOF14). Above-normal rainfall was predicted over Sri Lanka for SWM 2019, and information was shared at the monsoon forum. Even though SWM 2019 seasonal rainfall wasslightly above average, highly uneven rainfall distribution with a deficit of rainfall at the beginning and a surplus of rainfall during the latter part of the season was observed. Unusual dry conditioned prevailed during the month of May 2019, which led to delay the onset of SWM by 2 weeks. Due to the delay of onset and rainfall deficit during the early part of2019 SWM, late cultivation of paddy was observed.Hydro-catchment areas recorded large shortfalls in early part Southwest Monsoon rainfall reducing hydropower generation to 15–18%, from May to July.The suppressed phase of Madden Julian Oscillation (MJO) (phase 6 to 8) with anomalous easterly winds over Sri Lanka was evident from 04th May to 25th May. As MJO being a major predictive source in subseasonal timescale and Sri Lanka being a country located in the heart of the MJO envelope, integration of subseasonal information into seasonal outlook provide much greater value to decision-makers in Agriculture and Energy sector.

Why Does Convection Weaken over Sumatra Island in an Active Phase of the MJO?

Abstract This study investigated the diurnal cycle of convection over Sumatra Island in an active phase of the Madden–Julian oscillation (MJO) during the Pre-Years of the Maritime Continent (YMC) observation campaign in December 2015 based on in situ and satellite observations and a convection-permitting numerical model. Observations suggest that before the active phase of the MJO in early December, convection occurred frequently over the island during the afternoon and at midnight. By contrast, during the active phase of the MJO in mid-December, afternoon convection over the island was delayed and suppressed, and midnight convection was suppressed. Numerical experiments also successfully replicated the main features of the observed modulations. In general, during the active phase of the MJO, the troposphere became drier in the Sumatra region. While the clouds reduced the solar radiation over the land, the sea breeze was also found to be delayed and weakened. As a result, the afternoon convection initiation was delayed and weakened. Further analyses suggested that the sea breeze was weakened mainly due to the orographic stagnation effect rather than the slightly reduced land–sea temperature contrast. On the other hand, the increased stratiform-anvil clouds induced the anomalous evaporative cooling in the midtroposphere and generated island-scale subsidence during the nighttime, which finally led to the suppression of inland convection. Overall, our study reveals the modulation of diurnal convection over Sumatra Island by an active phase of the MJO and also shows the potential role of land–sea interaction in convection initiation and maintenance.

Joint Distribution Analysis of Forest Fires and Precipitation in Response to ENSO, IOD, and MJO (Study Case: Sumatra, Indonesia)

To evaluate the impact of the El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Madden Julian Oscillation (MJO) on the occurrence of land and forest fire in Sumatra, copula-based joint distribution analysis and quadrant analysis (for extreme events) were carried out in this research. This research used dry spells (number of days without rain) and precipitation anomalies as climate indicators and hotspots as land and forest fire indicators. Using data spanning from 2001 to 2020, this research shows that ENSO and IOD strongly influence hotspots in Sumatra with monsoonal-type precipitation. Even though the impact is not linear, the probability of a higher number of hotspots occurring increases significantly, especially during strong El Niño and weak El Niño combined with positive IOD. Furthermore, the results show that moderate El Niño has a similar impact to weak El Niño on the affected area, while weak El Niño combined with positive IOD can result in effects similar to robust El Niño impact. Meanwhile, this research has shown that the MJO affects hotspots in the first dry season of Sumatran areas that have equatorial-type precipitation. Although its impact on dry spell–precipitation anomaly dependency is unclear, phases 6,7, and 8 of MJO significantly increase dry spell–hotspot dependency during dry conditions.

Effect of the Quasi‐Biennial Oscillation on the Madden Julian Oscillation Teleconnections in the Southern Hemisphere

AbstractThe Madden Julian Oscillation (MJO) is the main source of intraseasonal variability in the tropics. MJO modulates rainfall in remote areas in the Southern Hemisphere by exciting tropical and extratropical wave trains. We use newly released reanalysis data to analyze how the Quasi‐Biennial Oscillation (QBO) can influence the MJO's effects over the Southern Hemisphere, focusing on precipitation anomalies over South America. The anomalies in the intensity of the South Atlantic Convergence Zone (SACZ) and precipitation over Southeastern South America during MJO phases 1 and 4 are intensified during the easterly QBO. The extratropical wave train excited by the anomalous convection over the maritime continent during MJO phase 4 is affected by the QBO, with a stronger, better‐defined pattern during westerly QBO. The conclusions are supported by a perturbation experiment of a case study, conducted using a high‐top atmospheric global climate model where the QBO and MJO are controlled.

MJO Phase Swings Modulate the Recurring Latitudinal Shifts of the 2020 Extreme Summer‐Monsoon Rainfall Around Yangtse

AbstractConsidering the unprecedented extremity of the Meiyu episodes in early summer of 2020, here the authors perform a comprehensive study of the intraseasonal evolution characteristics of the observed rainfall round Yangtse as well as the potential modulating effect of Madden‐Julian Oscillation (MJO). Results suggest that the Meiyu rainfall manifests as recurring latitudinal shifts around Yangtse during June–July of 2020, corresponding well to the continued swings of MJO circulation and convection between Phase 1 and Phase 2. The MJO affects the meridional migration of the 2020 Meiyu rainfall mainly through regulating the westward extended ridge line and southwesterly of the anomalous anticyclone over the western North Pacific (WNP). Specifically, the northeastward propagation of boreal summer MJO from Phase 1 to 2 shifts the ridge line of the anomalous WNP anticyclone northeastward. Consequently, the associated southwesterly anomaly over the southeastern China penetrates to the north of Yangtse and enhances the lower‐tropospheric moisture flux convergence, supporting heavy precipitation there. However, when the MJO swings back to Phase 1, the anomalous southwesterly and moisture flux convergence retreat southward, so does the Meiyu rain band. The present results advanced our understanding of the interactions between the latitudinal shifts of extreme Meiyu rainfall episodes and MJO Phase swings.

Wet season rainfall onset and flash drought: The case of the northern Australian wet season

AbstractIn this paper, we report on the frequency of false onsets of wet season rainfall in the case of the Northern Australian wet season and investigate the role of large‐scale tropical climate processes such as the El Niño–Southern Oscillation, Indian Ocean Dipole (IOD) and Madden–Julian Oscillation. A false onset occurs when a wet season rainfall onset criterion is met, but follow‐up rainfall is not received for weeks or months later. Our analysis of wet season rainfall data from 1950 through 2020 shows a false onset occurs, on average, between 20 and 30% of wet seasons across all of northern Australia. This increases at a regional and local level such as at Darwin, the Northern Territory (NT), and parts of Queensland's north coast to over 50%. Seasonal climate influences, such as a La Niña pattern and a negative IOD that typically expedite the wet season rainfall onset, also increase the likelihood of a false onset over northern Australia. Our analysis also finds that periods of false onsets can sometimes, but not always, coincide with periods of rapid soil moisture depletion. The false rainfall onsets that develop into flash drought can be potentially disruptive and costly and are of potential significance for agriculture and fire management in northern Australia, and in other monsoonal climates that also typically experience a slow build‐up to the seasonal monsoon. In conclusion, effective rainfall indicates that many seasons experience ‘false onsets’ with dry conditions after early rainfall. We propose that false onsets are a physical characteristic of the climate of northern Australia which occurs with relatively high frequency. In addition, these false onsets may sometimes co‐occur with a flash drought.

Evaluating the Eastward Propagation of the MJO in CMIP5 and CMIP6 Models Based on a Variety of Diagnostics

Abstract Given the climatic importance of the Madden–Julian oscillation (MJO), this study evaluates the capability of CMIP6 models in simulating MJO eastward propagation in comparison with their CMIP5 counterparts. To understand the representation of MJO simulation in models, a set of diagnostics with respect to MJO-associated dynamic and thermodynamic structures is applied, including large-scale zonal circulation, vertical structures of diabatic heating and equivalent potential temperature, moisture convergence at the planetary boundary layer (PBL), and the east–west asymmetry of moisture tendency relative to the MJO convection. The simulated propagation of the MJO in CMIP6 models shows an overall improvement in realistic speed and longer distance, which displays a robust linear regression relationship against the above-mentioned dynamic and thermodynamic structures. The improved MJO propagation in CMIP6 largely benefits from better representation of premoistening processes that is primarily contributed by improved PBL moisture convergence. In addition, the convergence of moisture and meridional advection of moisture prior to the MJO convection are enhanced in CMIP6, while the zonal advection of moisture is as weak as that in CMIP5. The increased convergence of moisture is a result of enhanced lower-tropospheric moisture and divergence, and the enhanced meridional advection of moisture can be caused by sharpened meridional gradient of mean lower-tropospheric moisture in the western Pacific. Further examination of the lower-tropospheric moisture budget reveals that the enhanced zonal asymmetry of the moisture tendency in CMIP6 is driven by the drying process to the west of the MJO convection, which is attributed to the negative vertical and zonal advections of moisture.

Modulation of East African Boreal Fall Rainfall: Combined Effects of the Madden–Julian Oscillation (MJO) and El Niño–Southern Oscillation (ENSO)

Abstract Climate variabilities can have significant impacts on rainfall in East Africa, leading to disruption in natural and human systems and affecting the lives of tens of millions of people. Subseasonal and interannual variabilities are critical components of total rainfall variability in the region. The goal of this study is to examine the combined effects of the Madden–Julian oscillation (MJO), operating at a subseasonal time scale, and El Niño–Southern Oscillation (ENSO), operating at an interannual scale, on the modulation of East African boreal fall [October–December (OND)] rainfall, commonly called the short rains. Composite analysis shows that daily rainfall responses depend on MJO phase and its interaction with ENSO state. In particular, MJO modulation of rainfall is generally stronger under El Niño conditions relative to ENSO neutral and La Niña conditions, leading to increased potential for daily precipitation excesses during wet MJO phases under El Niño. There is evidence for both dynamic and thermodynamic mechanisms associated with these impacts, including an increase in westerly moisture transport and easterly advection of temperature and moist static energy. Seasonal analysis shows that the frequency and intensity of wet MJO phases during an El Niño contribute notably to the seasonal total precipitation anomaly. This suggests that the MJO can mediate El Niño’s impact on OND rainfall in East Africa.

Potential Predictability of Southwest U.S. Rainfall: Role of Tropical and High-Latitude Variability

Abstract This study explores the potential predictability of Southwest U.S. (SWUS) precipitation for the November–March season in a set of numerical experiments performed with the Whole Atmospheric Community Climate Model. In addition to the prescription of observed sea surface temperature and sea ice concentration, observed variability from the MERRA-2 reanalysis is prescribed in the tropics and/or the Arctic through nudging of wind and temperature. These experiments reveal how a perfect prediction of tropical and/or Arctic variability in the model would impact the prediction of seasonal rainfall over the SWUS, at various time scales. Imposing tropical variability improves the representation of the observed North Pacific atmospheric circulation, and the associated SWUS seasonal precipitation. This is also the case at the subseasonal time scale due to the inclusion of the Madden–Julian oscillation (MJO) in the model. When additional nudging is applied in the Arctic, the model skill improves even further, suggesting that improving seasonal predictions in high latitudes may also benefit prediction of SWUS precipitation. An interesting finding of our study is that subseasonal variability represents a source of noise (i.e., limited predictability) for the seasonal time scale. This is because when prescribed in the model, subseasonal variability, mostly the MJO, weakens the El Niño–Southern Oscillation (ENSO) teleconnection with SWUS precipitation. Such knowledge may benefit S2S and seasonal prediction as it shows that depending on the amount of subseasonal activity in the tropics on a given year, better skill may be achieved in predicting subseasonal rather than seasonal rainfall anomalies, and conversely. Significance Statement Subseasonal and seasonal predictability of precipitation over the Southwest United States (SWUS) during the wet season is challenging, and long-range forecasts from climate models still exhibit poor skill over this region. In this study we use numerical experiments with constrained tropical and/or Arctic atmospheric variability to explore how climate processes in these two regions impact the SWUS precipitation. Our results highlight how much forecast skill in SWUS precipitation may be gained from better predictions in tropical and high latitudes, from subseasonal to multiyear time scales.

Topographic Influences on Diurnally Driven MJO Rainfall Over the Maritime Continent

AbstractThis work investigates impacts of the Madden‐Julian Oscillation (MJO) on the daily and diurnal rainfall over the Maritime Continent, with emphasis on the influences of topography over Sumatra, Borneo and New Guinea. Eighty‐nine MJO events were identified during 2001–2019 using IMERG satellite data. Daily and diurnal rainfall maxima on the east side of topography lag the west side as the MJO passes. In addition, the island vanguard (pre‐MJO) rain is more convective, while the island rearguard (behind the main MJO body) rain is more stratiform. The timing and magnitude of diurnal rainfall is defined using the maximum hourly rain rate instead of the first diurnal harmonic to avoid smoothing. While a single sharp peak is observed over the mountains around 19 LT, a much broader delayed peak occurs over land to the west of topography and two peaks are observed over land to the east of topography at 15 and 2 LT. Rain peaks offshore from 3 to 7 LT. Cluster analysis shows that the afternoon and nighttime rainfall peaks are highest before the MJO arrives, then gradually decrease and become earlier on the west side of the topography, whereas the afternoon (nighttime) peak east of the topography is enhanced before (after) the MJO arrives. The contrasting east‐west features can be attributed to topographic influences on the moisture flux convergence of the mean column moisture by MJO‐induced winds. The MJO wind modulation of diurnal rainfall over most of the open ocean areas is insignificant.