Multivariate Empirical Orthogonal Function Research Articles

ENSO‐Modulated Variability in Winter Shelf Circulation of the Northern South China Sea

AbstractWe combined long‐term observational data from 1999 to 2021 with numerical simulations to study the seasonal changes in the currents along the continental shelf in the Northern South China Sea (NSCS) during winter and how these changes relate to the El Niño‐Southern Oscillation (ENSO). Our results indicate that during El Niño events, the eastward movement of the warm pool in the tropical Pacific Ocean not only leads to colder sea surface temperatures and a stronger Kuroshio current intrusion but also significantly affects the formation of a high‐pressure system in the subtropics over the NSCS. In El Niño years, an anomalous anticyclonic wind stress curl in the South China Sea weakens the northeast winter monsoon, which in turn weakens the cyclonic shelf circulation. The first principal component from the multivariate empirical orthogonal function decomposition, which accounts for 49.02% of the total variance, shows a significant correlation of 0.64 with the Niño 3.4 index, indicating the circulation's sensitivity to tropical climate changes. Our analysis of the winter shelf circulation, based on the along‐isobath depth‐integrated vorticity equation, reveals that the exchange of water across the isobaths over the shelf is mainly controlled by the nonlinear advection of relative vorticity, with wind stress curl and bottom stress curl playing a less significant role in regulating the structure of these exchanges. The combined effect of baroclinic forces and topography likely governs the dynamics over the slope.

Coherent Interannual–Decadal Potential Temperature Variability in the Tropical–North Pacific Ocean and Deep South China Sea

AbstractClimate variability over the Tropical and North Pacific Ocean (TPO and NPO, respectively) modulates marginal sea variability. The South China Sea (SCS), the largest marginal sea in the western NPO, is an outstanding example of a region that responds quickly to climate change. However, there is considerable uncertainty regarding the response of the deep SCS to large‐scale climate variability. Multivariate empirical orthogonal function analysis revealed three prominent modes of interconnected temperature anomaly fluctuations within the TPO and NPO. These coherent modes highlight the interactive dynamics among climate variations and reveal their modulation mechanisms for previously less explored potential temperature variabilities in the deep SCS. On the atmospheric bridge, external forces modify the upper‐layer Luzon Strait Transport (LST) by adjusting the Ekman transport and Kuroshio intrusion. For the oceanic pathway, climate variations disturb the deep‐layer LST by adjusting the barotropic flows in the upper layer.

Climatic characteristics and main weather patterns of extreme precipitation in the middle Yangtze River valley

Abstract Based on the daily precipitation data and ERA5 reanalysis data of 40 years from 1981 to 2018 in the middle Yangtze River Valley (MYRV), the climatic characteristics of extreme precipitation are analyzed using statistical methods. The multivariate empirical orthogonal functions and spectral clustering methods are used to classify and synthesize the extreme precipitation weather. The results show that: (1) The spatial distribution of the extreme precipitation threshold is uneven due to the regional topography. The spatial distribution of the average precipitation and frequency of extreme precipitation days is characterized by the north-south antiphase distribution. (2) According to the main influencing systems, the 215 regional extreme precipitation days in the MYRV in the past 40 years can be classified into three types: southwest vortex type, typhoon type, and cold trough shear line type. (3) The southwest vortex type of extreme precipitation occurs in the deep warm and humid airflow in front of the southwest vortex trough, but the typhoon type has better thermal dynamic conditions, and the cold and warm airflow convergence of the cold trough shear line type is more obvious. The rainfall area of three types of extreme precipitation is the result of the synergistic effect of the system.

Multivariate Sea Surface Prediction in the Bohai Sea Using a Data-Driven Model

Data-driven predictions of marine environmental variables are typically focused on single variables. However, in real marine environments, there are correlations among different oceanic variables. Additionally, sea–air interactions play a significant role in influencing the evolution of the marine environment. Both internal dynamics and external drivers contribute to these changes. In this study, a data-driven model is proposed using sea surface height anomaly (SSHA), sea surface temperature (SST), and sea surface wind (SSW) in the Bohai Sea. This model combines multivariate empirical orthogonal functions (MEOFs) with long and short-term memory (LSTM). MEOF analysis is used on the multivariate dataset of SSHA and SST, considering the correlation among sea surface variables. SSW is introduced as a predictor to enhance the predictability of the multivariate sea surface model. In the case of the Bohai Sea, the comparative tests of the model without wind field effect, the fully coupled model, and the proposed prediction model were carried out. MEOF analysis is employed in comparative experiments for oceanic variables, atmospheric variables, and combined atmospheric and oceanic variables. The results demonstrate that using wind field as a predictor can improve the forecast accuracy of SSHA and SST in the Bohai Sea. The root mean square errors (RMSE) for SSHA and SST in a 7-day forecast are 0.016 m and 0.3200 °C, respectively.

Climate downscaling for regional models with a neural network: A Hawaiian example

Global ocean/atmosphere circulation models (GCMs) allow us to better understand and predict the behavior of the ocean and atmosphere at large spatial and temporal scales; however, they may be unsuited for regional studies due to their low spatial resolution. We have developed a method for downscaling GCMs data using an artificial neural network to reconstruct high spatial resolution regional fields. We use these downscaled fields to force a regional ocean model and examine the efficacy of the method and results. The new downscaling method combines the multivariate empirical orthogonal function (EOF) with a convolutional neural network. Utilizing an EOF decomposition of high-resolution observations and/or regional model output, we train the neural network so that it will produce high-resolution fields based on the low-resolution GCM input. We apply this method to downscale GCM near-surface wind vectors in the region of the Hawaiian Islands and force a regional ocean simulation with the downscaled winds. We compare this to a simulation directly forced by the GCM winds. The results show that the ocean simulation forced by the downscaled GCM winds demonstrates a significant improvement in capturing the ocean dynamics: increasing wind energy input from the shear regions around the islands, while decreasing it in the lee of islands. In addition, the downscaled wind transfers twice as much energy to the deep ocean as the GCM wind.

The role of transient eddies in the intraseasonal reversal of East Asian winter air temperature anomalies

The intraseasonal reversal of wintertime surface air temperature (SAT) anomalies over East Asia (15°-55°N, 80°-130°E) is becoming a matter of concern. Thus, the predominant features of the reversal mode of SAT anomalies and its relevant dynamical mechanism associated with transient eddies (TEs) are studied by using the Multivariate Empirical Orthogonal Function (MV-EOF) analysis method and the geopotential tendency equation. Results show that the third MV-EOF mode well depicts a colder (warmer) DJ with a warmer (colder) February and is closely linked to an out-of-phase variation in both East Asian Polar Front Jet (EAPJ) and East Asian Subtropical Jet (EASJ). It is found that synoptic-scale (2.5-8d) and low-frequency (10-90d) TE activities over Eurasia play important roles in the intraseasonal reversal in SAT anomalies by adjusting time-mean flows. A cold DJ in East Asia dynamically corresponds to a strengthened EASJ and weakened EAPJ, while the TE forcing dominated by low-frequency TE vorticity forcing and synoptic-scale TE heating forcing tends to weaken the EASJ and reinforce the EAPJ, unfavorable to the maintenance of cold anomalies over East Asia. However, the characteristics of both synoptic-scale and low-frequency TE activities in February are significantly different from that in DJ. By comparison, the TE forcing is dominated by synoptic-scale TE vorticity forcing and low-frequency TE heating forcing, which makes great contribution to the weakening of EASJ and the enhancement and maintenance of EAPJ, conducive to a weaker East Asian winter monsoon and eventually to a warmer East Asia.

Region-dependent meteorological conditions for the winter cold hazards with and without precipitation in China

Cold hazard is one of the major meteorological disasters in winter. However, the meteorological conditions for the cold hazard events vary significantly with both the feature of the event and the region of occurrence. This study divides winter cold hazard events in China into three categories based on the daily gridded dataset of cold hazards from November 1980 to March 2020: events without wintry precipitation (hazardous low temperature, abrupt temperature drop, and/or freezing), with wintry precipitation only (hazardous sleet and/or snowstorm), and with both. The region-dependent multivariate meteorological conditions for each category of cold hazards are investigated using ERA5 reanalysis data. Results show that the surface air temperature (T2m) and its anomaly (T2m_anom) are lower than climatology during cold hazards. But the difference in T2m among provinces exceeds 30 °C, and even for the same province, the difference among different categories of cold hazards exceeds 10 °C. The region- and category-dependent differences of T2m_anom and daily temperature drop (∆T24) are also large, about 5 °C and 2 °C d−1, respectively. The Multivariate Empirical Orthogonal Function analysis has further been applied to not only the abovementioned temperature-related variables but also the precipitation-related variables (i.e., daily accumulated total precipitation, daily accumulated snowfall, and daily mean snow depth) in the middle and lower Yangtze River region, which reveals the event-mean state and spatial–temporal coupling evolution during the progression of the event for the selected key meteorological variables. The meteorological conditions for cold hazards put forward by this study could provide region-dependent and category-dependent reference for the prediction and warning of cold hazards.

Analysis and Prediction of Wind Speed Effects in East Asia and the Western Pacific Based on Multi-Source Data

With the increasing problem of global warming caused by the massive use of fossil fuels, biomass energy as a renewable energy source has attracted widespread attention throughout the globe. In this paper, we analyzed the spatial and temporal variation in wind energy in the East Asia and Western Pacific areas using IGRA site data, ERA5, and NCEP/NCAR reanalysis data from 2000 to 2021, and multi-variate empirical orthogonal function (MV-EOF) decomposition with the Pettitt mutation test, and the seasonal autoregression integrated moving average (SARIMA) model was used to predict the trend of wind speed. The spatial and temporal variations in wind energy in East Asia and Western Pacific areas were analyzed, and it was found that the richer wind-energy resources were mainly concentrated in the “Three Norths” (North China, Northwest China, and Northeast China) and Mongolia, followed by the Western Pacific areas. In addition, the T’ai-hang Mountains and the Qinghai-Tibet Plateau in China block the wind resources in the eastern and southern regions of East Asia, resulting in a shortage of wind resources in this region. In addition, the summer wind speed is significantly lower than in the other three seasons. The first-mode contributions of the MV-EOF wind field and geopotential heights, respectively, are 29.47% and 37.75%. The results show that: (1) There are significant seasonal differences in wind-energy resources in the study area, with the lowest wind speed in summer and the highest wind speed in winter. (2) The wind energy in the study area has significant regional characteristics. For example, China’s Qinghai-Tibet Plateau, Inner Mongolia, Xinjiang region, and Mongolia are rich in wind-energy resources. (3) Wind-energy resources in the study area have gradually increased since 2010, mainly due to changes in large-scale oceanic and atmospheric circulation patterns caused by global warming.

Evaluation of the interannual variability in the East Asian summer monsoon in AMIP and historical experiments of CAS FGOALS-f3-L

The evaluation of East Asian summer monsoon (EASM) simulations could improve our understanding of Asian monsoon dynamics and climate simulations. In this study, by using Phase 6 of the Coupled Model Intercomparison Project (CMIP6) experiments of the Atmospheric Model Intercomparison Project (AMIP) and historical runs of the Chinese Academy of Sciences (CAS) Flexible Global Ocean–Atmosphere–Land System (FGOALS-f3-L) model, the model simulation skill for the interannual variability in the EASM was determined. According to multivariate empirical orthogonal function (MV-EOF) analysis, the major mode of the EASM mainly emerged as a Pacific-Japan pattern in the western Pacific accompanied by a local anticyclonic anomaly with a total variance of 24.6%. The historical experiment could suitably reproduce this spatial pattern and attained a closer total variance than that attained by the AMIP experiment. The historical experiment could also better simulate the time frequency of the EASM variability than the AMIP experiment. However, the phase of principal component 1 (PC1) was not suitably reproduced in the historical experiment since no initialization procedure was applied at the beginning of the integration in the historical simulation process, whereas the sea surface temperature (SST) was preset in the AMIP experiment. Further analysis revealed that air–sea interactions in the Indian Ocean and tropical western Pacific were important for the model to provide satisfactory EASM simulations, while El Niño–Southern Oscillation (ENSO) simulation was possibly related to the climate variability in the EASM simulations, which should be further analyzed.摘要对东亚夏季季风(EASM)模拟的评估可以提高我们对亚洲季风动力和气候模拟的理解. 在这项研究中, 通过使用中国科学院(CAS)全球海洋-大气-陆地系统(FGOALS-f3-L)模式参加的第六次耦合模式相互比较计划(CMIP6)中的大气模式相互比较计划(AMIP)和历史(historical)试验, 明确了EASM的年际变率的模拟能力. 通过多变量经验正交函数(MV-EOF)分析发现, 观测的EASM的主导模态为西太平洋上的太平洋-日本模态, 并伴有局部反气旋异常. 主导模态的方差贡献率为24.6%. 历史(historical)试验可以基本再现这种空间模态, 其方差贡献率较AMIP试验更接近于观测. 与AMIP试验相比, 历史(historical)试验还能更好地模拟EASM变率的时间频率. 然而, 由于历史(historical)模拟没有在积分开始时应用初始化过程, 而AMIP试验受到海表面温度(SST)的约束, 因此主成分(PC1)的位相在历史(historical)试验中没有得到较好地再现. 进一步分析发现, 印度洋和西太平洋热带地区的海气相互作用对EASM的模拟非常重要, 而EASM气候变率的模拟可能与厄尔尼诺-南方涛动(ENSO)的模拟能力有关, 这值得进一步分析.

Leading modes of wind field variability over the western Tibet Plateau

Atmospheric circulations bring moisture from above the ocean to the high mountains of the western Tibet Plateau (TP), thus wind variability is of great importance to the water cycle centered on the western TP. This study therefore examines the leading modes of the wind fields over the western TP. We use the multivariate empirical orthogonal function (MV-EOF) analysis method to detect the dominant wind patterns above the western TP. This method extracts the leading modes of combined meridional and zonal wind variability at 200-hPa in the region of 22° N–50° N, 50° E–92° E. We find the first leading mode of the combined zonal and meridional wind field in the annual mean and in most seasons (spring, summer and autumn) over the western TP shows high similarity to the Western Tibetan Vortex (WTV), a large-scale atmospheric vortex-like pattern recently recognized over the western TP. In winter, the WTV, however, is closer to the second leading mode. We estimate the sensitivity of our results by changing the domain of the MV-EOF analysis region surrounding the western. We find the influence of the WTV is less sensitive to analysis location around the western TP. In short, the WTV generally represents the first leading mode of the wind field in most seasons over the western TP. This study augments our knowledge on wind variability over the western TP.

Three leading coupled modes of summer rainfall with atmospheric circulations over northern East Asia

AbstractNorthern East Asia (NEA) is characterized by wet monsoon region in the east and mid‐latitude westerly‐controlled dry inland in the west in summer, where ecosystem and environment are vulnerable to rainfall variability. Previous studies found close relationship between summer rainfall in NEA and local large‐scale atmospheric circulation systems including East Asian upper‐tropospheric westerly jet (EAJ) and middle‐tropospheric trough (EAT), and lower‐tropospheric low over NEA (NEAL). However, major features of rainfall–circulation coupling over NEA are still not fully understood. This study addresses this issue using multivariate empirical orthogonal functions method based on the ERA‐Interim reanalysis dataset and the GPCP precipitation data for 1979–2018. Three leading coupled modes are identified, together accounting for 30–50% of summer rainfall year‐to‐year variance in most of NEA. The first mode features consistent decrease of rainfall in NEA related to the decelerated EAJ, southward shifted EAT, and weakened NEAL, with a significant interdecadal change in late 1990s. The second mode exhibits a meridional dipole rainfall pattern, with less rainfall along the East Asian subtropical rainy belt and more rainfall in southern Russian Far East, coupled with the northward shifted EAJ, weakened EAT, and intensified NEAL. The third mode presents a zonal dipole rainfall pattern, with suppressed rainfall in southern Russia east of northeast China and enhanced rainfall around the Lake Baikal related to the decelerated EAJ, and westward shifted EAT and NEAL. Further investigation shows that the first mode is remotely modulated by summer rainfall anomalies in the Sahel region and Atlantic Multidecadal Oscillation (AMO) on the interdecadal timescales, and by the Polar/Eurasia teleconnection on the interannual timescales. The second and third modes are, respectively, modulated by summer rainfall in the western North Pacific and north central‐eastern India through the East Asia‐Pacific and circumglobal teleconnection patterns.

The Leading Mode and Factors for Coherent Variations among the Subsystems of Tropical Asian Summer Monsoon Onset

AbstractPrevious studies on the Asian summer monsoon (ASM) onset mainly focused on each monsoon subsystem. Mainly based on the monthly mean rainfall and low-level winds in May, this study investigated the dominant onset mode from the perspective of the entire tropical ASM region, which reveals the coherent features among the regional-scale onsets. The results of multivariate empirical orthogonal function (MV-EOF) analysis indicate that the MV-EOF1 presents reduced rainfall and anomalous low-level easterly winds at 850 hPa over the tropical ASM region in May during its positive phase. The corresponding principal component (PC1) is highly correlated with the local monsoon onset dates over the Arabian Sea, the Bay of Bengal, the Indo-China Peninsula, and the South China Sea, where the mean monsoon onsets occur in May. The only exception is the Indian subcontinent, where the mean monsoon onsets occur in June. The results indicate that the leading mode captures the synchronized variation of monsoon onset over most Asian monsoon subsystems, which exhibits remarkable interannual and interdecadal changes. The factors that modulate the coherent variation of the tropical ASM onset are further examined. The simultaneously delayed ASM onset tends to occur during the easterly phase of the 30–80-day oscillation, the decaying phase of El Niño, and the positive phase of Pacific decadal oscillation (PDO). The 30–80-day oscillation serves as a background condition for the synchronized delayed or advanced ASM onset. El Niño–related sea surface temperature anomalies modulate the tropical ASM onset mode by modulating the tropical Walker circulation and inducing an atmospheric Rossby wave response. The PDO affects the tropical ASM onset mode mainly via the equatorial Rossby wave response and the extratropical Rossby wave train.

Dominant physical-biogeochemical drivers for the seasonal variations in the surface chlorophyll-a and subsurface chlorophyll-a maximum in the Bay of Bengal

The seasonal variations and driving mechanisms of the surface and subsurface chlorophyll-a concentrations in the Bay of Bengal are far from resolved, as only a few local, short-term studies have been performed. Hence, this study investigates a comprehensive basin-wide framework of the seasonal variations in the chlorophyll-a concentration, its dominant external forcing, and the internal dynamics of the Bay of Bengal. Multivariate empirical orthogonal function decomposition and heterogeneous correlation analyses are applied to numerous observational, reanalysis, and satellite datasets, including chlorophyll-a, nutrients, temperature, salinity, turbidity, and wind stress curl datasets collected from various sources, including the Copernicus Marine Environment Monitoring Service, World Ocean Atlas, and ERA-Interim. This study suggests that the chlorophyll-a concentrations at both the surface and the subsurface chlorophyll-a maximum (SCM) are higher during summer and early autumn than during the other seasons, especially along the coastal regions and western part of the Bay of Bengal. During summer and early autumn, riverine nutrient inputs, the intrusion of nutritious water from the Arabian Sea, and coastal upwelling are the three dominant drivers controlling the chlorophyll-a concentrations at both the surface and the SCM. The positive wind stress curl-induced uplift of the thermocline increases the nutrient supply and thus significantly enhances the chlorophyll-a concentration at the SCM along the entire western side of the bay during the second half of the year. During spring, the deep euphotic depth plays a vital role in controlling the concentration and depth of the SCM. The depth of the 26 °C isotherm can be used as a proxy of the depth of the SCM. This study provides an improved understanding of the high chlorophyll-a concentrations and their drivers in five potential zones within the Bay of Bengal, which will help to identify the rich marine ecosystems therein.

Analyzing the effects of sea ice melting and atmospheric heat transport on the warming around arctic based on comparable analysis and coupling modes

The Arctic warming has become a key signal with global climate change in recent decades. In this study, sea ice volume and whole layer atmospheric heat flux divergence were used to represent the local factor and external transport, respectively. The random forest algorithm was adopted to study the nonlinear effects and variations in importance between the local factors and external transport on Arctic warming between 1979 and 2018. The multivariate empirical orthogonal function decomposition method was applied to explore the coupling structure among sea ice volume, heat flux divergence, and temperature at different altitudes, locate the main passages of atmospheric heat transport to the Arctic, and explore the physical mechanisms of extreme Arctic climate events in the past two years. The analysis results suggest that sea ice has a significant impact on lower-level warming, and the atmospheric heat transport is essential in regulating temperature changes in the middle and upper troposphere. Additionally, on an interdecadal scale, the average state of Arctic warming was found to be strongly related to the Arctic Ocean Oscillation index, explaining the warming trend in the Atlantic sector. The trend is jointly controlled by the heat transport passages in the Pacific and Atlantic Oceans. The abrupt change in 2017–2018 was caused by the increased heat transport in the Pacific Ocean and weakened heat transport in the Atlantic Ocean, leading to abnormal warming and cooling near the two passages. On a seasonal scale, heat transport increase in the three passages located in 1) the Baffin Bay and the Labrador Sea, 2) the Nordic Peninsula and the Barents Sea, 3) the Bering Sea and the East Siberian Sea likely causes regional differences in Arctic summer warming. The increased heat transport in the Bering Sea and East Siberian Sea passage in winter made the Pacific sector significantly warmer. A positive feedback mechanism was created by the change in the circulation field between the temperature and Pacific heat transport.

Impacts of Large-Scale Soil Moisture Anomalies on the Hydroclimate of Southeastern South America

AbstractThe La Plata basin (LPB), located in southeastern South America (SESA), is a region of significant socioeconomic importance, particularly for agriculture. This area of South America exhibits strong land–atmosphere coupling in the warm season. In this work, we evaluate the impact of large-scale soil moisture (SM) anomalies on regional-scale atmospheric conditions. Multivariate empirical orthogonal function (EOF) analysis is used to extract the dominant modes of joint variability of monthly averaged root-zone SM and 1-month-lagged precipitation from atmospheric reanalyses. We find that the dominant EOF pattern is consistent with a positive correlation between antecedent SM and precipitation, while the second dominant EOF pattern is consistent with a negative correlation between these variables. To evaluate causality, the effects of large-scale SM anomalies on atmospheric variables are examined using the Community Earth System Model (CESM). CESM simulations suggest that anomalously dry SM is initially collocated with decreased precipitation. Subsequent changes in the atmospheric circulation associated with a thermal low draw moisture into the region, eventually promoting increased precipitation. This study investigates the pathways through which SM anomalies modulate precipitation in this region. For this reason, this study has potential atmospheric prediction applications that could benefit the population and the socioeconomic well-being of this important region.

Intensified Impacts of Central Pacific ENSO on the Reversal of December and January Surface Air Temperature Anomaly over China since 1997

AbstractThe reversal of surface air temperature anomalies (SATA) in winter brings a great challenge for short-term climate prediction, and the mechanisms are not well understood. This study found that the reversal of SATA between December and January over China could be demonstrated by the second leading mode of multivariate empirical orthogonal function analysis on the December–January SATA. It further reveals that the central Pacific El Niño–Southern Oscillation (CP ENSO) has contributed more influence on such a reversal of SATA since 1997. CP ENSO shows positive but weak correlations with SATA over China in both December and January during the pre-1996 period, whereas it shows significant negative and positive correlations with the SATA in December and January, respectively, during the post-1997 period. The CP ENSO–related circulations suggest that the change of the Siberian high has played an essential role in the reversal of SATA since 1997. The pattern of sea surface temperature anomalies associated with the CP ENSO leads to a westward-replaced Walker circulation that alters the local meridional circulation and, further, has impacted the Siberian high and SATA over China since 1997. Moreover, the seasonal northward march of the convergence zone from December to January causes a northward-replaced west branch of the Walker circulation in January compared with that in December. The west branch of the Walker circulation in December and January directly modulates local Hadley and Ferrel circulations and then causes contrasting Siberian high anomalies by inducing opposite vertical motion anomalies over Siberia. The reversal of SATA between December and January, therefore, has been more frequently observed over China since 1997. The abovementioned mechanisms are validated by the analysis at pentad time scales and confirmed by numerical simulations.

A Multivariate Balanced Initial Ensemble Generation Approach for an Atmospheric General Circulation Model

Based on the multivariate empirical orthogonal function (MEOF) method, a multivariate balanced initial ensemble generation method was applied to the ensemble data assimilation scheme. The initial ensembles were generated with a reasonable consideration of the physical relationships between different model variables. The spatial distribution derived from the MEOF analysis is combined with the 3-D random perturbation to generate a balanced initial perturbation field. The Local Ensemble Transform Kalman Filter (LETKF) data assimilation scheme was established for an atmospheric general circulation model. Ensemble data assimilation experiments using different initial ensemble generation methods, spatially random and MEOF-based balanced, are performed using realistic atmospheric observations. It is shown that the ensembles integrated from the balanced initial ensembles maintain a much more reasonable spread and a more reliable horizontal correlation compared with the historical model results than those from the randomly perturbed initial ensembles. The model predictions were also improved by adopting the MEOF-based balanced initial ensembles.

Intraseasonal Vertical Cloud Regimes Based on CloudSat Observations over the Tropics

This study identifies the evolution of tropical vertical cloud regimes (CRs) and their associated heating structures on the intraseasonal time scales. Using the cloud classification retrievals of CloudSat during boreal winter between 2006 and 2017, the CR index is defined as the leading pair of the combined multivariate empirical orthogonal functions of the daily mean frequency of deep, high, and low clouds over the tropical Indian Ocean, Maritime Continents, and the Western Pacific. The principal components of the CR index exhibit robust temporal variance in the 30 to 80 day intraseasonal band. Based on the propagation stages of the CRs, the coherent vertical structures of cloud composition and large-scale moisture and vertical motion exhibit a westward-tilted structure. The associated Q1-QR diabatic heating and cloud radiative forcing are consistent with the key characteristics of the Madden Julian Oscillation (MJO) documented in the previous studies. Lastly, an MJO case study showcases that the presented approach characteristically captures the propagation of moisture, cloud vertical structure, and precipitation activity across spatial and temporal scales. The current results suggest that the CR index can potentially serve as an evaluation metric to cloud-associated processes in the simulated tropical intraseasonal variability in global climate models.

How changing cloud water to rain conversion profile impacts on radiation and its linkage to a better Indian summer monsoon rainfall simulation

Effect of modifying cloud water to rain conversion factor above freezing level on radiation flux is studied. The linkage of cloud-radiation interaction with a better Indian summer monsoon (ISM) rainfall simulation has also been investigated. Two simulations were performed with Climate Forecast System version 2 (CFSv2), one with default revised simplified Arakawa-Schubert (RSAS) convection scheme and another with modified RSAS (RSAS-mod) in which the cloud water to precipitation conversion factor is revised. It is observed that both top of the atmosphere (TOA) and surface energy imbalances are improved in the RSAS-mod simulation. The major contribution seems to come from the enhanced reflected shortwave radiation at the TOA. In RSAS-mod, more shortwave radiation is getting reflected at the TOA and thus less shortwave is available to reach at the surface. It has happened as a consequence of enhanced planetary albedo in RSAS-mod. It is also observed that high cloud cover has increased in RSAS-mod and there is a decrease in low cloud cover. As a result of increased high cloud cover, outgoing longwave radiation has decreased significantly in RSAS-mod. It is also found from the multivariate empirical orthogonal function (MV-EOF) analysis that the composite of longwave cloud radiative forcing corresponding to phases 4 and 5 of boreal summer intraseasonal oscillation (BSISO), which signifies the active phase of ISM, is better simulated in RSAS-mod. This has helped to simulate a better seasonal rainfall.

A Dynamical‐Statistical Approach to Retrieve the Ocean Interior Structure From Surface Data: SQG‐mEOF‐R

AbstractCombining the dynamical surface‐trapped mode derived from the Surface Quasi‐Geostrophic (SQG) function with the statistical mode calculated from multivariate empirical orthogonal function (EOF) reconstruction (mEOF‐R) method, this paper proposes a new method, SQG‐mEOF‐R, to estimate the interior density from the sea surface density and sea surface height. This method is applied to the eddy‐resolving Ocean General Circulation Model For the Earth simulator simulation and compared with the conventional SQG, isQG (interior plus SQG), and mEOF‐R methods. Two different dynamical regimes were considered: the NorthWest Pacific, dominated by surface‐intensified eddies, and the Southeast Pacific, characterized by the occurrence of subsurface‐intensified eddies. In both regions, the proposed method proves to be robust in reconstructing mesoscale features, with reduced root‐mean square error and relatively high correlation coefficient. The superiority of SQG‐mEOF‐R is highlighted in those subsurface‐intensified eddies that are little or nothing reconstructed by SQG or isQG method.