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Dongqian Wang
,
Ying Sun
,
Ting Hu
, and
Hong Yin

Abstract

The anthropogenic forcing and anomalous atmospheric circulation have increased the occurrence probability of 2022-like extreme heat by approximately 62.0 and 2.6 times, respectively.

Open access
Yuntao Wei
,
Hong-Li Ren
,
Baoqiang Xiang
,
Yan Wang
,
Jie Wu
, and
Shuguang Wang

Abstract

The Madden–Julian oscillation (MJO) is the dominant intraseasonal wave phenomenon influencing extreme weather and climate worldwide. Realistic simulations and accurate predictions of MJO genesis are the cornerstones for successfully monitoring, forecasting, and managing meteorological disasters 3–4 weeks in advance. Nevertheless, the genesis processes and emerging precursor signals of an eastward-propagating MJO event remain largely uncertain. Here, we find that the MJO genesis processes observed in the past four decades exhibit remarkable diversity with different seasonality and can be classified objectively into four types, namely, a novel downstream origin from the westward-propagating intraseasonal oscillation (WPISO; 20.4%), localized breeding from the Indian Ocean suppressed convection (IOSC; 15.4%), an upstream succession of the preceding weakly dispersive (WD; 25.9%), and strongly dispersive (SD; 38.3%) MJO. These four types are associated with different oceanic background states, characterized by central Pacific cooling, southern Maritime Continent warming, eastern Pacific cooling, and central Pacific warming for the WPISO, IOSC, WD, and SD types, respectively. The SD type is also favored during the easterly phase of the stratospheric quasi-biennial oscillation. Diverse convective initiations possibly imply various kinds of propagations of MJO. The subseasonal reforecasts indicate robustly distinct prediction skills for the diverse MJO genesis. A window of opportunity for skillful week 3–4 prediction probably opens with the aid of the WPISO-type MJO precursor, which has increased the predictability of primary MJO onset by 1 week. These findings suggest that the diversified MJO genesis can be skillfully foreseen by monitoring unique precursor signals and can also serve as benchmarks for evaluating contemporary models’ modeling and predicting capabilities.

Open access
Cheng Qian
,
Jun Wang
,
Siyan Dong
,
Hong Yin
,
Claire Burke
,
Andrew Ciavarella
,
Buwen Dong
,
Nicolas Freychet
,
Fraser C. Lott
, and
Simon F. B. Tett
Full access
Ming Feng
,
Yongliang Duan
,
Susan Wijffels
,
Je-Yuan Hsu
,
Chao Li
,
Huiwu Wang
,
Yang Yang
,
Hong Shen
,
Jianjun Liu
,
Chunlin Ning
, and
Weidong Yu
Full access
Yaohui Li
,
Xing Yuan
,
Hongsheng Zhang
,
Runyuan Wang
,
Chenghai Wang
,
Xianhong Meng
,
Zhiqiang Zhang
,
Shanshan Wang
,
Yang Yang
,
Bo Han
,
Kai Zhang
,
Xiaoping Wang
,
Hong Zhao
,
Guangsheng Zhou
,
Qiang Zhang
,
Qing He
,
Ni Guo
,
Wei Hou
,
Cunjie Zhang
,
Guoju Xiao
,
Xuying Sun
,
Ping Yue
,
Sha Sha
,
Heling Wang
,
Tiejun Zhang
,
Jinsong Wang
, and
Yubi Yao

Abstract

A major experimental drought research project entitled “Mechanisms and Early Warning of Drought Disasters over Northern China” (DroughtEX_China) was launched by the Ministry of Science and Technology of China in 2015. The objective of DroughtEX_China is to investigate drought disaster mechanisms and provide early-warning information via multisource observations and multiscale modeling. Since the implementation of DroughtEX_China, a comprehensive V-shape in situ observation network has been established to integrate different observational experiment systems for different landscapes, including crops in northern China. In this article, we introduce the experimental area, observational network configuration, ground- and air-based observing/testing facilities, implementation scheme, and data management procedures and sharing policy. The preliminary observational and numerical experimental results show that the following are important processes for understanding and modeling drought disasters over arid and semiarid regions: 1) the soil water vapor–heat interactions that affect surface soil moisture variability, 2) the effect of intermittent turbulence on boundary layer energy exchange, 3) the drought–albedo feedback, and 4) the transition from stomatal to nonstomatal control of plant photosynthesis with increasing drought severity. A prototype of a drought monitoring and forecasting system developed from coupled hydroclimate prediction models and an integrated multisource drought information platform is also briefly introduced. DroughtEX_China lasted for four years (i.e., 2015–18) and its implementation now provides regional drought monitoring and forecasting, risk assessment information, and a multisource data-sharing platform for drought adaptation over northern China, contributing to the global drought information system (GDIS).

Full access
Ming Feng
,
Yongliang Duan
,
Susan Wijffels
,
Je-Yuan Hsu
,
Chao Li
,
Huiwu Wang
,
Yang Yang
,
Hong Shen
,
Jianjun Liu
,
Chunlin Ning
, and
Weidong Yu

Abstract

Sea surface temperatures (SSTs) north of Australia in the Indonesian–Australian Basin are significantly influenced by Madden–Julian oscillation (MJO), an eastward-moving atmospheric disturbance that traverses the globe in the tropics. The region also has large-amplitude diurnal SST variations, which may influence the air–sea heat and moisture fluxes, that provide feedback to the MJO evolution. During the 2018/19 austral summer, a field campaign aiming to better understand the influences of air–sea coupling on the MJO was conducted north of Australia in the Indonesian–Australian Basin. Surface meteorology from buoy observations and upper-ocean data from autonomous fast-profiling float observations were collected. Two MJO convective phases propagated eastward across the region in mid-December 2018 and late January 2019 and the second MJO was in conjunction with a tropical cyclone development. Observations showed that SST in the region was rather sensitive to the MJO forcing. Air–sea heat fluxes warmed the SST throughout the 2018/19 austral summer, punctuated by the MJO activities, with a 2°–3°C drop in SST during the two MJO events. Substantial diurnal SST variations during the suppressed phases of the MJOs were observed, and the near-surface thermal stratifications provided positive feedback for the peak diurnal SST amplitude, which may be a mechanism to influence the MJO evolution. Compared to traditionally vessel-based observation programs, we have relied on fast-profiling floats as the main vehicle in measuring the upper-ocean variability from diurnal to the MJO time scales, which may pave the way for using cost-effective technology in similar process studies.

Free access
David M. L. Sills
,
Gregory A. Kopp
,
Lesley Elliott
,
Aaron Jaffe
,
Elizabeth Sutherland
,
Connell Miller
,
Joanne Kunkel
,
Emilio Hong
,
Sarah Stevenson
, and
William Wang
Full access
David M. L. Sills
,
Gregory A. Kopp
,
Lesley Elliott
,
Aaron L. Jaffe
,
Liz Sutherland
,
Connell S. Miller
,
Joanne M. Kunkel
,
Emilio Hong
,
Sarah A. Stevenson
, and
William Wang

Abstract

Canada is a vast country with most of its population located along its southern border. Large areas are sparsely populated and/or heavily forested, and severe weather reports are rare when thunderstorms occur there. Thus, it has been difficult to accurately assess the true tornado climatology and risk. It is also important to establish a reliable baseline for tornado-related climate change studies. The Northern Tornadoes Project (NTP), led by Western University, is an ambitious multidisciplinary initiative aimed at detecting and documenting every tornado that occurs across Canada. A team of meteorologists and wind engineers collects research-quality data during each damage investigation via thorough ground surveys and high-resolution satellite, aircraft, and drone imaging. Crowdsourcing through social media is also key to tracking down events. In addition, NTP conducts research to improve our ability to detect and accurately assess tornadoes that affect forests, cropland, and grassland. An open data website allows sharing of resulting datasets and analyses. Pilot investigations were carried out during the warm seasons of 2017 and 2018, with the scope expanding from the detection of any tornadoes in heavily forested regions of central Canada in 2017 to the detection of all EF1+ tornadoes in Ontario plus all significant events outside of Ontario in 2018. The 2019 season was the first full campaign, systematically collecting research-quality tornado data across the entire country. To date, the project has found 89 tornadoes that otherwise would not have been identified, and increased the national tornado count in 2019 by 78%.

Full access
Masao Kanamitsu
,
Arun Kumar
,
Hann-Ming Henry Juang
,
Jae-Kyung Schemm
,
Wanqui Wang
,
Fanglin Yang
,
Song-You Hong
,
Peitao Peng
,
Wilber Chen
,
Shrinivas Moorthi
, and
Ming Ji

The new National Centers for Environmental Prediction (NCEP) numerical seasonal forecast system is described in detail. The new system is aimed at a next-generation numerical seasonal prediction in which focus is placed on land processes, initial conditions, and ensemble methods, in addition to the tropical SST forcing. The atmospheric model physics is taken from the NCEP–National Center for Atmospheric Research (NCAR) reanalysis model, which has more comprehensive land hydrology and improved physical processes. The model was further upgraded by introducing three new parameterization schemes: 1) the relaxed Arakawa–Schubert (RAS) convective parameterization, which improved middle latitude response to tropical heating; 2) Chou's shortwave radiation, which corrected surface radiation fluxes; and 3) Chou's longwave radiation scheme together with smoothed mean orography that reduced model warm bias. Atmospheric initial conditions were taken from the operational NCEP Global Data Assimilation System, allowing the seasonal forecast to start from realistic initial conditions and to seamlessly connect with the short- and medium-range forecasts. The Pacific basin ocean model is the same as that in the old NCEP seasonal system and is coupled to the new atmospheric model with a two-tier approach. The operational atmospheric forecast is performed once a month with a 20-member ensemble. Prior to the forecast, 10-member ensemble hindcasts of the same month from 1979 to the present are performed to define model climatology and model forecast skill. The system has been running routinely since April 2000, and the products are available online at NWS's ftp site.

Full access
Haibo Du
,
Markus G. Donat
,
Shengwei Zong
,
Lisa V. Alexander
,
Rodrigo Manzanas
,
Andries Kruger
,
Gwangyong Choi
,
Jim Salinger
,
Hong S. He
,
Mai-He Li
,
Fumiaki Fujibe
,
Banzragch Nandintsetseg
,
Shafiqur Rehman
,
Farhat Abbas
,
Matilde Rusticucci
,
Arvind Srivastava
,
Panmao Zhai
,
Tanya Lippmann
,
Ibouraïma Yabi
,
Michael C. Stambaugh
,
Shengzhong Wang
,
Altangerel Batbold
,
Priscilla Teles de Oliveira
,
Muhammad Adrees
,
Wei Hou
,
Claudio Moises Santos e Silva
,
Paulo Sergio Lucio
, and
Zhengfang Wu

Abstract

Extreme precipitation occurring on consecutive days may substantially increase the risk of related impacts, but changes in such events have not been studied at a global scale. Here we use a unique global dataset based on in situ observations and multimodel historical and future simulations to analyze the changes in the frequency of extreme precipitation on consecutive days (EPCD). We further disentangle the relative contributions of variations in precipitation intensity and temporal correlation of extreme precipitation to understand the processes that drive the changes in EPCD. Observations and climate model simulations show that the frequency of EPCD is increasing in most land regions, in particular, in North America, Europe, and the Northern Hemisphere high latitudes. These increases are primarily a consequence of increasing precipitation intensity, but changes in the temporal correlation of extreme precipitation regionally amplify or reduce the effects of intensity changes. Changes are larger in simulations with a stronger warming signal, suggesting that further increases in EPCD are expected for the future under continued climate warming.

Full access