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Ting Wei
,
Shoudong Zhao
,
Brice Noël
,
Qing Yan
, and
Wei Qi

Abstract

Greenland experienced multiple extreme weather/climate events in recent decades that led to significant melting of the ice sheet. However, how the intensity of extreme climate events over Greenland varied under recent warming has not been fully examined. Here, we collect 176 in situ observations over Greenland and demonstrate that the observed extreme temperature/precipitation events over Greenland are well captured by the RACMO2.3p2 model, in terms of climatological distribution, interannual variability, and long-term trend. Thus, we then investigate the spatiotemporal features of extreme events over Greenland during 1958–2019, using the daily model outputs at 5.5-km resolution. The simulated annual maximum temperature exhibits a significant increasing trend (∼0.13°C decade−1) during 1958–2019, whereas there is a weakening trend (−0.24°C decade−1) in annual minimum temperature over Greenland, especially after the 1990s (−1.24°C decade−1). For the interannual variability, changes in temperature extremes between warm and cold temperature years share large similarities with the distributions of long-term trends. The extreme precipitation events measured by annual maximum daily precipitation amount show a profound increasing trend (0.52 mm day−1 decade−1) over northeastern Greenland during 1958–2019, with large interannual variability in the ice-free coastal region and southern Greenland. Additionally, the changes in extreme warm and cold events are generally linked with the variation of Greenland blocking in summer and Arctic polar vortex in winter, respectively, in terms of favorable circulation background, and the extreme precipitation events are often associated with the position of the polar jet stream.

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Wei Mei
,
Shang-Ping Xie
, and
Ming Zhao

Abstract

Interannual–decadal variability of tropical cyclone (TC) track density over the North Atlantic (NA) between 1979 and 2008 is studied using observations and simulations with a 25-km-resolution version of the High Resolution Atmospheric Model (HiRAM) forced by observed sea surface temperatures (SSTs). The variability on decadal and interannual time scales is examined separately. On both time scales, a basinwide mode dominates, with the time series being related to variations in seasonal TC counts. On decadal time scales, this mode relates to SST contrasts between the tropical NA and the tropical northeast Pacific as well as the tropical South Atlantic, whereas on interannual time scales it is controlled by SSTs over the central–eastern equatorial Pacific and those over the tropical NA. The temporal evolution of the spatial distribution of track density is further investigated by normalizing the track density with seasonal TC counts. On decadal time scales, two modes emerge: one is an oscillation between track density over the U.S. East Coast and midlatitude ocean and that over the Gulf of Mexico and the Caribbean Sea and the other oscillates between low and middle latitudes. They might be driven by the preceding winter North Atlantic Oscillation and concurrent Atlantic meridional mode, respectively. On interannual time scales, two similar modes are present in observations but are not well separated in HiRAM simulations. Finally, the internal variability and predictability of TC track density are explored and discussed using HiRAM ensemble simulations. The results suggest that basinwide total TC counts/days are much more predictable than local TC occurrence, posing a serious challenge to the prediction and projection of regional TC threats, especially the U.S. landfall hurricanes.

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Hong-Li Ren
,
Yuntao Wei
, and
Shuo Zhao

Abstract

The real-time multivariate Madden–Julian oscillation (MJO) (RMM) index has now been widely applied as a standard in operational subseasonal prediction and monitoring. Its calculation procedures involve the extraction of major intraseasonal variability (ISV) by subtracting the prior 120-day mean. However, this study uncovers that such a real-time strategy artificially creates unwanted low-frequency variability (LFVartificial) that might cause nonnegligible influences on the RMM amplitude and phase. Compared to the real LFV, the LFVartificial explains more (∼70% in boreal summer) of the residual LFV (LFVresidual) in the RMM index. It occupies 33% of all days that the LFVresidual explains more than one-half of total RMM amplitude, 19% that the LFV contribution exceeds ISV, and 10% that the LFVartificial-associated RMM amplitude surpasses 0.8. The RMM-defined “MJO” is obscured by the LFVresidual in such a way that the eastward-propagating mode is stronger and bigger with a slower phase speed, as compared with the “true” MJO derived from the 20–100-day filtered data. The interference effects of LFVresidual on the MJO might be particularly strong when the background state is changing rapidly with time. However, these issues can be well avoided when one chooses to remove the centered 120-day mean, as evidenced by the largely reduced three percentages (17%, 8%, and 1%) mentioned above in the so-derived index. These results give us a reminder that more attention should be paid to monitoring or predicting an MJO using the RMM index in a rapidly changing low-frequency background or in the boreal summer.

Significance Statement

The real-time multivariate MJO (RMM) index has been widely applied in the monitoring and prediction of the MJO, the major tropical intraseasonal variability influencing global weather and climate. Using observational analysis, we reveal that there exist such scenarios (∼16%) when large-amplitude RMM indices do not represent a strong MJO, mainly due to the obscuring effect of residual, while largely artificial, low-frequency variability introduced by the RMM calculation procedures. This finding is of great significance as it informs the research community that serious caution should be given when relating large RMM amplitude to the MJO, especially in a condition when the low-frequency background state is rapidly changing with time or in the boreal summer.

Free access
Li Tao
,
Tim Li
,
Yuan-Hui Ke
, and
Jiu-Wei Zhao

Abstract

A Pacific–Japan (PJ) pattern index is defined based on the singular value decomposition (SVD) analysis of summertime 500-hPa height in East Asia and precipitation in the tropical western North Pacific (WNP). The time series of this PJ index shows clearly the interannual and interdecadal variations since 1948. Idealized atmospheric general circulation model (AGCM) experiments were carried out to understand the remote and local SST forcing in causing the interannual variations of the PJ pattern and interdecadal variations of the PJ-like pattern. It is found that the PJ interannual variation is closely related to El Niño–Southern Oscillation (ENSO). A basinwide warming occurs in the tropical Indian Ocean (TIO) during El Niño mature winter. The TIO warming persists from the El Niño peak winter to the succeeding summer. Meanwhile, a cold SST anomaly (SSTA) appears in the eastern WNP and persists from the El Niño mature winter to the succeeding summer. Idealized AGCM experiments that separate the TIO and WNP SSTA forcing effects show that both the remote eastern TIO forcing and local WNP SSTA forcing are important in affecting atmospheric heating anomaly in the WNP monsoon region, which further impacts the PJ interannual teleconnection pattern over East Asia. In contrast to the interannual variation, the interdecadal change of the PJ-like pattern is primarily affected by the interdecadal change of SST in the TIO rather than by the local SSTA in the WNP.

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Er Lu
,
Wei Zhao
,
Xukai Zou
,
Dianxiu Ye
,
Chunyu Zhao
, and
Qiang Zhang

Abstract

A method is developed in this study to monitor and detect extreme precipitation events. For a rainfall event to be severe, it should last for a long period and affect a wide region while maintaining a strong intensity. However, if the duration is inappropriately taken as too long and the region is inappropriately taken as too wide, then the averaged intensity might be too weak. There should be a balance among the three quantities. Based upon understanding of the issue, the authors proposed a simple mathematical model, which contains two reasonable constraints. The relation of the “extreme” intensity with both duration and region (EIDR) is derived. With the prescribed baseline extreme intensities, the authors calculate the relative intensities with the data. Through comparison among different time periods and spatial sizes, one can identify the event that is most extreme, with its starting time, duration, and geographic region being determined. Procedures for monitoring the extreme event are provided. As an example, the extreme event contained in the 1991 persistent heavy rainfall over east China is detected.

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Shoudong Zhao
,
Minghu Ding
,
Wenqian Zhang
,
Ting Wei
,
Wei Cheng
,
Junming Chen
, and
Cunde Xiao

Abstract

Changes in extreme temperatures have more effects on ecosystems and human society than changes in climate averages. As a hotspot of global warming, the Arctic has experienced unprecedented heatwaves recently, which highlights the importance of identifying long-term variations of extreme temperatures. However, spatial unbalance of observations and artificially chosen investigation periods limit our knowledge of extreme temperatures over the Arctic lands. Here, we build a complete and quality-controlled observation network on surface temperature over the Arctic lands and combine in situ and reanalysis data to evaluate changes of extreme temperatures during the period 1979–2020. Our results indicate that 1) the increase in extreme temperatures has accelerated since the 2000s, especially on the coast of Eurasia; 2) the change magnitude for cold events is larger than for warm events, in terms of intensity, frequency, and duration; and 3) increases in warm events only occur locally, for example, Alaska and central Siberia, while decreases in cold events occur throughout the Arctic lands. The long-term trends of extreme temperatures are synchronous with sea ice loss, and patterns of interannual variations are mainly related to the North Atlantic Oscillation. We suggest further efforts toward improvement over North America, especially for Greenland, through sufficient observations and regional models.

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Yi Yang
,
Hongtao Nie
,
Yongli Zhang
,
Xiaofan Luo
,
Hao Wei
, and
Wei Zhao

Abstract

Open water in ice-covered oceans is an essential condition for shipping and resource exploitation. We investigate the interannual and spatial variations of the open water onset time in the Kara Sea (KS) and the underlying mechanisms through analyzing satellite-based observations and model simulation results. The empirical orthogonal function (EOF) analysis on the satellite sea ice concentration during 1979–2020 reveals two primary spatial distribution patterns of the open water onset time. The first mode EOF1 shows the coherent advance or delay of the open water onset time within the KS, which is consistent with the multiyear-averaged state. The second mode EOF2 exhibits a seesaw pattern between the southwest and middle regions, which represents the regional difference of the open water onset time within the KS. In 1997 with significant anomaly in EOF2, analysis of the model simulation reveals that the strong easterly wind-induced ice transport is the main reason for the earlier opening in the middle region and delayed opening in the southwestern region. When compared with the multiyear-averaged state, this dynamic process causes a noticeable redistribution of local sea ice in the early melting season (May to June), with much more ice in the southwestern region, thence influences the regional onset time of open water. A similar situation also occurred in the years 1985, 2001, and 2004, as these years presented stronger easterly wind energy accumulated over May to June, which cause earlier opening in the middle region and later opening in the southwestern region.

Significance Statement

Variability of the open water in the Arctic Ocean has a significant impact on climate and ecosystem variability and also human activities. This study focuses on understanding why the onset time of open water was asynchronous over the Kara Sea. Generally, the open water first forms in the western region of the Kara Sea under the influences of warm inflow from the Barents Sea and river runoff. However, when strong easterly winds prevail across the whole region at the beginning of the melting season, sea ice is transported from east to west, resulting in the advanced opening in the middle and delayed opening in the southwest regions. This finding points out that wind can combine with surface and lateral heat fluxes to influence the interannual variability in the distribution of the open water onset time in the Kara Sea.

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Wei Mei
,
Shang-Ping Xie
,
Ming Zhao
, and
Yuqing Wang

Abstract

Forced interannual-to-decadal variability of annual tropical cyclone (TC) track density in the western North Pacific between 1979 and 2008 is studied using TC tracks from observations and simulations by a 25-km-resolution version of the GFDL High-Resolution Atmospheric Model (HiRAM) that is forced by observed sea surface temperatures (SSTs). Two modes dominate the decadal variability: a nearly basinwide mode, and a dipole mode between the subtropics and lower latitudes. The former mode links to variations in TC number and is forced by SST variations over the off-equatorial tropical central North Pacific, whereas the latter might be associated with the Atlantic multidecadal oscillation. The interannual variability is also controlled by two modes: a basinwide mode driven by SST anomalies of opposite signs located in the tropical central Pacific and eastern Indian Ocean, and a southeast–northwest dipole mode connected to the conventional eastern Pacific ENSO. The seasonal evolution of the ENSO effect on TC activity is further explored via a joint empirical orthogonal function analysis using TC track density of consecutive seasons, and the analysis reveals that two types of ENSO are at work. Internal variability in TC track density is then examined using ensemble simulations from both HiRAM and a regional atmospheric model. It exhibits prominent spatial and seasonal patterns, and it is particularly strong in the South China Sea and along the coast of East Asia. This makes an accurate prediction and projection of TC landfall extremely challenging in these regions. In contrast, basin-integrated metrics (e.g., total TC counts and TC days) are more predictable.

Full access
Wei Zhao
,
Zhongmin Hu
,
Qun Guo
,
Genan Wu
,
Ruru Chen
, and
Shenggong Li

Abstract

Understanding the atmosphere–land surface interaction is crucial for clarifying the responses and feedbacks of terrestrial ecosystems to climate change. However, quantifying the effects of multiple climatic factors to vegetation activities is challenging. Using the geographical detector model (GDM), this study quantifies the relative contributions of climatic factors including precipitation, relative humidity, solar radiation, and air temperature to the interannual variation (IAV) of the normalized difference vegetation index (NDVI) in the northern grasslands of China during 2000 to 2016. The results show heterogeneous spatial patterns of determinant climatic factors on the IAV of NDVI. Precipitation and relative humidity jointly controlled the IAV of NDVI, illustrating more explanatory power than solar radiation and air temperature, and accounting for higher proportion of area as the determinant factor in the study region. It is noteworthy that relative humidity, a proxy of atmospheric aridity, is as important as precipitation for the IAV of NDVI. The contribution of climatic factors to the IAV of NDVI varied by vegetation type. Owing to the stronger explanatory power of climatic factors on NDVI variability in temperate grasslands, we conclude that climate variability may exert more influence on temperate grasslands than on alpine grasslands. Our study highlights the importance of the role of atmospheric aridity to vegetation activities in grasslands. We suggest focusing more on the differences between vegetation types when addressing the climate–vegetation relationships at a regional scale.

Free access
Meilin Zhu
,
Lonnie G. Thompson
,
Huabiao Zhao
,
Tandong Yao
,
Wei Yang
, and
Shengqiang Jin

Abstract

Glacier changes on the Tibetan Plateau (TP) have been spatially heterogeneous in recent decades. The understanding of glacier mass changes in western Tibet, a transitional area between the monsoon-dominated region and the westerlies-dominated region, is still incomplete. For this study, we used an energy–mass balance model to reconstruct annual mass balances from October 1967 to September 2019 to explore the effects of local climate and large-scale atmospheric circulation on glacier mass changes in western Tibet. The results showed that Xiao Anglong Glacier is close to a balanced condition, with an average value of −53 ± 185 mm water equivalent (w.e.) yr−1 for 1968–2019. The interannual mass balance variability during 1968–2019 was primary driven by ablation-season precipitation, which determined changes in the snow accumulation and strongly influenced melt processes. The interannual mass balance variability during 1968–2019 was less affected by ablation-season air temperature, which only weakly affected snowfall and melt energy. Further analysis suggests that the southward (or northward) shift of the westerlies caused low (or high) ablation-season precipitation, and therefore low (or high) annual mass balance for glaciers in western Tibet. In addition, the average mass balance for Xiao Anglong Glacier was 83 ± 185, −210 ± 185, and −10 ± 185 mm w.e. yr−1 for 1968–90, 1991–2012, and 2013–19, respectively. These mass changes were associated with the variations in precipitation and air temperature during the ablation season on interdecadal time scales.

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