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Shuangwen Sun, Jian Lan, Yue Fang, Tana, and Xiaoqian Gao

Abstract

Although the Indian Ocean dipole (IOD) and ENSO are significantly correlated, there are indeed some IODs independent of ENSO. In this research, the characteristics of independent IOD are investigated and a new triggering mechanism is proposed based on case study and statistical analysis. Results show that the independent IODs peak in an earlier season and have a weaker intensity compared with the IODs associated with ENSO. The wind anomaly associated with the independent IOD is very unique and shows a monsoonlike pattern, in addition to the equatorial easterly wind anomaly (EEWA) common to all IODs. The evolution of the EEWA associated with the independent IOD is well captured by the second EOF mode of the equatorial zonal wind interannual variability, suggesting that the independent IOD is an important climate mode inherent to the tropical Indian Ocean. The EEWA associated with the independent IOD is tightly linked to Indian summer monsoon activities in spring, and the convection anomalies associated with early summer monsoon onset in the Bay of Bengal plays a key role in inducing the EEWA. The EEWA can persist through spring and summer and causes a series of processes similar to those related to the IODs associated with ENSO. The correlation between the independent IOD and Indian summer monsoon activities increases dramatically after the 1980s, which is probably due to the mean state change in the tropical Indian Ocean climate system.

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Fengyun Sun, Alfonso Mejia, Sanjib Sharma, Peng Zeng, and Yue Che

Abstract

Because downscaling tools are needed to support climate change mitigation and adaptation practices, the guarantee of their credibility is of vital importance. To evaluate downscaling results, one needs to select a set of effective and nonoverlapping indices that reflect key system attributes. However, this subject is still insufficiently researched. With this study, we propose a diagnostic framework that evaluates the credibility of precipitation downscaling using five different attributes: spatial, temporal, trend, extreme, and climate event. A daily variant of the bias-corrected spatial downscaling approach is used to downscale daily precipitation from the GFDL-ESM2G climate model at 148 stations in the Yangtze River basin in China. Results prove that this framework is effective in systematically evaluating the performance of downscaling across the Yangtze River basin in the context of climate change and exacerbating climate extremes. Moreover, results also indicate that the downscaling approach adopted in this study yields good performance in correcting spatiotemporal bias, preserving trends, approximating extremes, and characterizing climate events across the Yangtze River basin. The proposed framework can be beneficial to planners and engineers facing issues relevant to climate change assessment.

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Yue Sun, Haishan Chen, Siguang Zhu, Jie Zhang, and Jiangfeng Wei

Abstract

Under the background of global warming, the Eurasian warming features evident spatial heterogeneity, and Northeast Asia (NEA) is one of the regions with the most significant summer warming. Based on reanalysis data and the CESM1.2.2 model, we investigated the possible impacts of spring Eurasian snowmelt on recent NEA summer warming and the relevant mechanisms. Results show that increased (decreased) spring snowmelt over eastern Europe to western Siberia (EEWS) is closely linked to NEA summer warming (cooling). Increased spring snowmelt can wet the soil, weakening surface sensible heating to the atmosphere and cooling the atmosphere. The persistent anomalous soil moisture and surface sensible heat induce geopotential height decrease over EEWS and strengthen the eastward-propagating wave train. Furthermore, positive geopotential height anomalies appear in downstream NEA in summer via the adjustment of the atmospheric circulation. Controlled by the anomalous high pressure system, the west part of NEA is affected by the southerly warm advection, while the east is affected by adiabatic warming induced by the dominant descending motion. Meanwhile, decreased cloud and increased incident solar radiation over NEA favor summer land surface warming. Model results suggest that CESM1.2.2 can basically reproduce the positive correlation between NEA summer land surface temperature and EEWS spring snowmelt. With the positive spring snowmelt forcing, the simulated positive soil moisture and negative sensible heat anomalies persist from spring to summer over EEWS. Consequently, negative geopotential height anomalies appear over the snowmelt region while positive anomalies occur around Lake Baikal, resulting in evident NEA land surface warming.

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Yue Sun, Jing-Wu Liu, and Shang-Ping Xie

Abstract

In winter, the warm water of the Gulf Stream anchors a salient precipitation band. Previous studies suggested a close relationship between the sea surface temperature (SST) front and the precipitation band through sea level pressure (SLP) adjustment. This study uses 17 years of high-resolution precipitation observations to reveal that the variation in wintertime precipitation over the Gulf Stream is related to the North Atlantic Oscillation (NAO) at the interannual time scale. The moisture budget analysis shows that the climatological precipitation band is supported by the large evaporation from the Florida Current, mean flow, and synoptic moisture convergence within the boundary layer, with a negative contribution from mean-flow moisture advection by the prevailing northwesterlies. For interannual variability, by contrast, the negative contribution of mean-flow moisture advection significantly decreases due to anomalous southeasterlies west of the intensified Azores high at the positive NAO phase. The contributions from mean-flow moisture advection and mean and synoptic convergence vary greatly along the Gulf Stream. In addition, mean-flow and synoptic moisture convergences positively contribute to the precipitation band both in climatology and at the interannual time scale, indicative of a positive feedback between precipitation and boundary layer convergence. Our analysis suggests that the SLP adjustment mechanism across the SST front is still at work in interannual variability, and the variation of synoptic activities over the Gulf Stream plays an important role in modulating the frontal precipitation. By relating the frontal precipitation to the NAO, this study bridges small-scale air–sea interaction and large-scale atmospheric circulation.

Open access
Qing Yue, Eric J. Fetzer, Brian H. Kahn, Sun Wong, Gerald Manipon, Alexandre Guillaume, and Brian Wilson

Abstract

The precision, accuracy, and potential sampling biases of temperature T and water vapor q vertical profiles obtained by satellite infrared sounding instruments are highly cloud-state dependent and poorly quantified. The authors describe progress toward a comprehensive T and q climatology derived from the Atmospheric Infrared Sounder (AIRS) suite that is a function of cloud state based on collocated CloudSat observations. The AIRS sampling rates, biases, and center root-mean-square differences (CRMSD) are determined through comparisons of pixel-scale collocated ECMWF model analysis data. The results show that AIRS provides a realistic representation of most meteorological regimes in most geographical regions, including those dominated by high thin cirrus and shallow boundary layer clouds. The mean AIRS observational biases relative to the ECMWF analysis between the surface and 200 hPa are within ±1 K in T and from −1 to +0.5 g kg−1 in q. Biases because of cloud-state-dependent sampling dominate the total biases in the AIRS data and are largest in the presence of deep convective (DC) and nimbostratus (Ns) clouds. Systematic cold and dry biases are found throughout the free troposphere for DC and Ns. Somewhat larger biases are found over land and in the midlatitudes than over the oceans and in the tropics, respectively. Tropical and oceanic regions generally have a smaller CRMSD than the midlatitudes and over land, suggesting agreement of T and q variability between AIRS and ECMWF in these regions. The magnitude of CRMSD is also strongly dependent on cloud type.

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Qing Yue, Brian H. Kahn, Eric J. Fetzer, Sun Wong, Xianglei Huang, and Mathias Schreier

Abstract

Observations from multiple sensors on the NASA Aqua satellite are used to estimate the temporal and spatial variability of short-term cloud responses (CR) and cloud feedbacks λ for different cloud types, with respect to the interannual variability within the A-Train era (July 2002–June 2017). Short-term cloud feedbacks by cloud type are investigated both globally and locally by three different definitions in the literature: 1) the global-mean cloud feedback parameter λ GG from regressing the global-mean cloud-induced TOA radiation anomaly ΔR G with the global-mean surface temperature change ΔT GS; 2) the local feedback parameter λ LL from regressing the local ΔR with the local surface temperature change ΔT S; and 3) the local feedback parameter λ GL from regressing global ΔR G with local ΔT S. Observations show significant temporal variability in the magnitudes and spatial patterns in λ GG and λ GL, whereas λ LL remains essentially time invariant for different cloud types. The global-mean net λ GG exhibits a gradual transition from negative to positive in the A-Train era due to a less negative λ GG from low clouds and an increased positive λ GG from high clouds over the warm pool region associated with the 2015/16 strong El Niño event. Strong temporal variability in λ GL is intrinsically linked to its dependence on global ΔR G, and the scaling of λ GL with surface temperature change patterns to obtain global feedback λ GG does not hold. Despite the shortness of the A-Train record, statistically robust signals can be obtained for different cloud types and regions of interest.

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Bo Sun, Huijun Wang, Aihui Wang, Yue Miao, Botao Zhou, and Huixin Li

Abstract

This study investigated the characteristics of both the regular and irregular seasonal northward march of the East Asian summer wet environment (SNM_EASWE) over the continent during June–July over the past six decades and in the future. During 1961–2015 and in the future, the regular SNM_EASWE is defined mainly by an intensified climatic northward-moving rainband over eastern China, whereas the irregular SNM_EASWE is defined mainly by less clear features of northward-moving rainband. Further analyses indicate that the boreal summer intraseasonal oscillation (BSISO) played a dominant role in affecting the regular/irregular SNM_EASWE during 1961–79, whereas both the BSISO and the seasonally varying western North Pacific (WNP) eddy may exert notable influences on the regular/irregular SNM_EASWE during 1980–2015 and in the future, where the WNP eddy refers to the anomalous anticyclone/cyclone over the WNP associated with the anomalous western Pacific subtropical high. During 1980–2015, a La Niña–like (El Niño–like) condition in the tropical Pacific during June–July may induce a regular (irregular) SNM_EASWE case because of the influence of anomalous convection over the Maritime Continent on the seasonally varying WNP eddy; an anomalous warming (cooling) in the tropical Indian Ocean during June–July may also partly induce a regular (irregular) SNM_EASWE case via influencing the seasonally varying WNP eddy. The increased influence of the seasonally varying WNP eddy on the regular/irregular SNM_EASWE after 1979 is attributed to the increased interannual variability of convective activity over the Maritime Continent and of sea surface temperatures in the Arabian Sea after 1979.

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Shuangwen Sun, Yue Fang, Yongcan Zu, Baochao Liu, Tana, and Azizan Abu Samah

Abstract

The seasonal characteristics of the mesoscale coupling between sea surface temperature (SST) and wind speed in the South China Sea (SCS) are investigated using satellite observations. The correlation between mesoscale SST and wind speed is highest in winter. The region of high correlation is located in the central SCS in the early stage of the winter monsoon. It then gradually shifts northward in the following months and is located in the northern SCS in the late stage of the winter monsoon. In summer, the region of high correlation is located to the east of the Vietnam coast. Two controlling factors are crucial in mesoscale SST–wind speed coupling: the mesoscale SST gradient and the wind speed steadiness. The mesoscale SST gradient is fundamental in mesoscale coupling, but a steady wind speed also plays an important role. The development of significant coupling depends on the relative contribution of these two factors. For regions where the mesoscale SST gradient is relatively weak, a very steady wind field is required for detectable mesoscale coupling to occur, whereas in regions where the wind speed is less steady, a stronger mesoscale SST gradient must exist for coupling to develop. Variations in wind speed steadiness can well explain the inconsistency between the spatial patterns of the mesoscale SST gradient and the intensity of coupling. The wind speed steadiness is a good factor with which to evaluate the constraining effect of the background wind field variability on the development of mesoscale coupling in the SCS.

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Qing Yue, Brian H. Kahn, Eric J. Fetzer, Mathias Schreier, Sun Wong, Xiuhong Chen, and Xianglei Huang

Abstract

The authors present a new method to derive both the broadband and spectral longwave observation-based cloud radiative kernels (CRKs) using cloud radiative forcing (CRF) and cloud fraction (CF) for different cloud types using multisensor A-Train observations and MERRA data collocated on the pixel scale. Both observation-based CRKs and model-based CRKs derived from the Fu–Liou radiative transfer model are shown. Good agreement between observation- and model-derived CRKs is found for optically thick clouds. For optically thin clouds, the observation-based CRKs show a larger radiative sensitivity at TOA to cloud-cover change than model-derived CRKs. Four types of possible uncertainties in the observed CRKs are investigated: 1) uncertainties in Moderate Resolution Imaging Spectroradiometer cloud properties, 2) the contributions of clear-sky changes to the CRF, 3) the assumptions regarding clear-sky thresholds in the observations, and 4) the assumption of a single-layer cloud. The observation-based CRKs show the TOA radiative sensitivity of cloud types to unit cloud fraction change as observed by the A-Train. Therefore, a combination of observation-based CRKs with cloud changes observed by these instruments over time will provide an estimate of the short-term cloud feedback by maintaining consistency between CRKs and cloud responses to climate variability.

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Shuguang Wang, Adam H. Sobel, Fuqing Zhang, Y. Qiang Sun, Ying Yue, and Lei Zhou

Abstract

This study investigates the October and November MJO events observed during the Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year 2011 (CINDY)/Dynamics of the MJO (DYNAMO) field campaign through cloud-permitting numerical simulations. The simulations are compared to multiple observational datasets. The control simulation at 9-km horizontal grid spacing captures the slow eastward progression of both the October and November MJO events in surface precipitation, outgoing longwave radiation, zonal wind, humidity, and large-scale vertical motion. The vertical motion shows weak ascent in the leading edge of the MJO envelope, followed by deep ascent during the peak precipitation stage and trailed by a broad second baroclinic mode structure with ascent in the upper troposphere and descent in the lower troposphere. Both the simulation and the observations also show slow northward propagation components and tropical cyclone–like vortices after the passage of the MJO active phase. Comparison with synthesized observations from the northern sounding array shows that the model simulates the passage of the two MJO events over the sounding array region well. Sensitivity experiments to SST indicate that daily SST plays an important role for the November MJO event, but much less so for the October event.

Analysis of the moist static energy (MSE) budget shows that both advection and diabatic processes (i.e., surface fluxes and radiation) contribute to the development of the positive MSE anomaly in the active phase, but their contributions differ by how much they lead the precipitation peak. In comparison to the observational datasets used here, the model simulation may have a stronger surface flux feedback and a weaker radiative feedback. The normalized gross moist stability in the simulations shows an increase from near-zero values to ~0.8 during the active phase, similar to what is found in the observational datasets.

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