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Quanhua Liu
,
Xingming Liang
,
Yong Han
,
Paul van Delst
,
Yong Chen
,
Alexander Ignatov
, and
Fuzhong Weng

Abstract

The Community Radiative Transfer Model (CRTM) developed at the Joint Center for Satellite Data Assimilation (JCSDA) is used in conjunction with a daily sea surface temperature (SST) and the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) atmospheric data and surface wind to calculate clear-sky top-of-atmosphere (TOA) brightness temperatures (BTs) in three Advanced Very High Resolution Radiometer (AVHRR) thermal infrared channels over global oceans. CRTM calculations are routinely performed by the sea surface temperature team for four AVHRR instruments on board the National Oceanic and Atmospheric Administration (NOAA) satellites NOAA-16, NOAA-17, and NOAA-18 and the Meteorological Operation (MetOp) satellite MetOp-A, and they are compared with clear-sky TOA BTs produced by the operational AVHRR Clear-Sky Processor for Oceans (ACSPO). It was observed that the model minus observation (M−O) bias in the NOAA-16 AVHRR channel 3b (Ch3b) centered at 3.7 μm experienced a discontinuity of ∼0.3 K when a new CRTM version 1.1 (v.1.1) was implemented in ACSPO processing in September 2008. No anomalies occurred in any other AVHRR channel or for any other platform. This study shows that this discontinuity is caused by the out-of-band response in NOAA-16 AVHRR Ch3b and by using a single layer to the NCEP GFS temperature profiles above 10 hPa for the alpha version of CRTM. The problem has been solved in CRTM v.1.1, which uses one of the six standard atmospheres to fill in the missing data above the top pressure level in the input NCEP GFS data. It is found that, because of the out-of-band response, the NOAA-16 AVHRR Ch3b has sensitivity to atmospheric temperature at high altitudes. This analysis also helped to resolve another anomaly in the absorption bands of the High Resolution Infrared Radiation Sounder (HIRS) sensor, whose radiances and Jacobians were affected to a much greater extent by this CRTM inconsistency.

Full access
Xiaodong Shang
,
Yongfeng Qi
,
Guiying Chen
,
Changrong Liang
,
Rolf G. Lueck
,
Brett Prairie
, and
Hua Li

Abstract

Measurements of turbulence in the deep ocean, particularly close to the bottom, are extremely sparse because of the difficulty and operational risk of obtaining deep profiles near the seafloor. A newly developed expendable instrument—the VMP-X (Vertical Microstructure Profiler–Expendable)—carries two microstructure shear probes to measure the fluctuations of vertical shear into the dissipation range and can profile down to a depth of 6000 m. Data from nine VMP-X profiles in the western Pacific Ocean near 11.6°N over rough topography display bottom-intensified turbulence with dissipation rates increasing by two factors of 10 to 4 W kg−1 within 200 m above the bottom. In contrast, over smooth topography in the southern South China Sea near 11°N, three profiles show that turbulence in the bottom boundary layer increases only slightly, with dissipation rates reaching 1 W kg−1. The eddy diffusivity over rough topography reached to 5 m2 s−1. The average diffusivity over all depths was 0.3 and 0.9 m2 s−1 for the tests in the southern South China Sea and in the western Pacific Ocean, respectively, and these values are much larger than previous estimates of less than ≈0.1 m2 s−1 for the main thermocline.

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Lei Zheng
,
Xiao Cheng
,
Zhuoqi Chen
,
Shaoyin Wang
,
Qi Liang
, and
Kang Wang

Abstract

Snowmelt is a critical component in the cryosphere and has a direct impact on Earth’s energy and water budget. Here, a 40-yr integrated melt onset (MO) dataset over sea ice, ice sheets, and terrestrial snow is compiled from spaceborne microwave radiometers and ERA5, allowing an overall assessment of the cryosphere. Results suggest that MO in both hemispheres shows latitudinal and vertical zonalities. The global cryosphere presented a trend toward earlier MO (−2 days decade−1) with hotpots distributed at the Northern Hemisphere high latitudes where the warming rate is much higher than that at lower latitudes. Overall, variations in MO showed a similar pattern to that in near-surface temperature. The advance of MO has been slowing down since the 1990s and no significant trend was observed during the so-called warming hiatus period (1998–2012). Regionally, climatic linkage analyses suggest the local MO variations were associated with different climate indices. MO in the pan-Arctic region is related with the Arctic Oscillation and North Atlantic Oscillation, while that in the pan-Antarctic region is associated with El Niño–Southern Oscillation and the southern annular mode. Occasionally, abnormal MO occurs as a result of extreme weather conditions. In February 2018, abnormal early melt events that occurred in the Arctic Ocean are found to be linked with the warm southerly flow due to sudden stratospheric warming. These findings suggest the satellite-based MO allows examining the dynamics and extremes in the climate system, both regionally and globally.

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Yanping Li
,
Kit Szeto
,
Ronald E. Stewart
,
Julie M. Thériault
,
Liang Chen
,
Bohdan Kochtubajda
,
Anthony Liu
,
Sudesh Boodoo
,
Ron Goodson
,
Curtis Mooney
, and
Sopan Kurkute

Abstract

A devastating, flood-producing rainstorm occurred over southern Alberta, Canada, from 19 to 22 June 2013. The long-lived, heavy rainfall event was a result of complex interplays between topographic, synoptic, and convective processes that rendered an accurate simulation of this event a challenging task. In this study, the Weather Research and Forecasting (WRF) Model was used to simulate this event and was validated against several observation datasets. Both the timing and location of the model precipitation agree closely with the observations, indicating that the WRF Model is capable of reproducing this type of severe event. Sensitivity tests with different microphysics schemes were conducted and evaluated using equitable threat and bias frequency scores. The WRF double-moment 6-class microphysics scheme (WDM6) generally performed better when compared with other schemes. The application of a conventional convective/stratiform separation algorithm shows that convective activity was dominant during the early stages, then evolved into predominantly stratiform precipitation later in the event. The HYSPLIT back-trajectory analysis and regional water budget assessments using WRF simulation output suggest that the moisture for the precipitation was mainly from recycling antecedent soil moisture through evaporation and evapotranspiration over the Canadian Prairies and the U.S. Great Plains. This analysis also shows that a small fraction of the moisture can be traced back to the northeastern Pacific, and direct uptake from the Gulf of Mexico was not a significant source in this event.

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Jianping Duan
,
Liang Chen
,
Lun Li
,
Peili Wu
,
Nikolaos Christidis
,
Zhuguo Ma
,
Fraser C. Lott
,
Andrew Ciavarella
, and
Peter A. Stott
Full access
I-Han Chen
,
Yi-Jui Su
,
Hsiao-Wei Lai
,
Jing-Shan Hong
,
Chih-Hsin Li
,
Pao-Liang Chang
, and
Ying-Jhang Wu

Abstract

A 16-member convective-scale ensemble prediction system (CEPS) developed at the Central Weather Bureau (CWB) of Taiwan is evaluated for probability forecasts of convective precipitation. To address the issues of limited predictability of convective systems, the CEPS provides short-range forecasts using initial conditions from a rapid-updated ensemble data assimilation system. This study aims to identify the behavior of the CEPS forecasts, especially the impact of different ensemble configurations and forecast lead times. Warm-season afternoon thunderstorms (ATs) from 30 June to 4 July 2017 are selected. Since ATs usually occur between 1300 and 2000 LST, this study compares deterministic and probabilistic quantitative precipitation forecasts (QPFs) launched at 0500, 0800, and 1100 LST. This study demonstrates that initial and boundary perturbations (IBP) are crucial to ensure good spread–skill consistency over the 18-h forecasts. On top of IBP, additional model perturbations have insignificant impacts on upper-air and precipitation forecasts. The deterministic QPFs launched at 1100 LST outperform those launched at 0500 and 0800 LST, likely because the most-recent data assimilation analyses enhance the practical predictability. However, it cannot improve the probabilistic QPFs launched at 1100 LST due to inadequate ensemble spreads resulting from limited error growth time. This study points out the importance of sufficient initial condition uncertainty on short-range probabilistic forecasts to exploit the benefits of rapid-update data assimilation analyses.

Significance Statement

This study aims to understand the behavior of convective-scale short-range probabilistic forecasts in Taiwan and the surrounding area. Taiwan is influenced by diverse weather systems, including typhoons, mei-yu fronts, and local thunderstorms. During the past decade, there has been promising improvement in predicting mesoscale weather systems (e.g., typhoons and mei-yu fronts). However, it is still challenging to provide timely and accurate forecasts for rapid-evolving high-impact convection. This study provides a reference for the designation of convective-scale ensemble prediction systems; in particular, those with a goal to provide short-range probabilistic forecasts. While the findings cannot be extrapolated to all ensemble prediction systems, this study demonstrates that initial and boundary perturbations are the most important factors, while the model perturbation has an insignificant effect. This study suggests that in-depth studies are required to improve the convective-scale initial condition accuracy and uncertainty to provide reliable probabilistic forecasts within short lead times.

Restricted access
Zhangqi Dai
,
Bin Wang
,
Ling Zhu
,
Jian Liu
,
Weiyi Sun
,
Longhui Li
,
Guonian Lü
,
Liang Ning
,
Mi Yan
, and
Kefan Chen

Abstract

Atlantic multidecadal variability (AMV) is a cornerstone for decadal prediction and profoundly influences regional and global climate variability, yet its fundamental drivers remain an issue for debate. Studies suggest that external forcing may have affected AMV during the Little Ice Age (AD 1400–1860). However, the detailed mechanism remains elusive, and the AMV’s centennial to millennial variations over the past 2000 years have not yet been explored. We first show that proxy-data reconstructions and paleo-data assimilations suggest a significant 60-yr AMV during AD 1250–1860 but not during AD 1–1249. We then conducted a suite of experiments with the Community Earth System Model (CESM) to unravel the causes of the changing AMV property. The simulation results under all external forcings match the reconstructions reasonably well. We find that the significant 60-yr AMV during 1250–1860 arises predominantly from the volcano forcing variability. During the period 1–1249, the average volcanic eruption intensity is about half of the 1250–1860 intensity, and a 20–40-yr internal variability dominates the AMV. The volcanic radiative forcing during 1250–1860 amplifies AMV and shifts the internal variability peak from 20–40 years to 60 years. The volcano forcing prolongs AMV periodicity by sustaining Arctic cooling, delaying subpolar sea ice melting and atmospheric feedback to reduce surface evaporation. These slow-response processes over the subpolar North Atlantic results in a persisting reduction of sea surface salinity, weakening the Atlantic overturning circulation, and warm water transport from the subtropical North Atlantic. The results reveal the cause of the nonstationary AMV over the past two millennia and shed light on the AMV’s response to external forcing.

Significance Statement

AMV plays an important role in the regional and global climate variability. The purpose of this study is to better understand the secular change of AMV during the past 2000 years and its response to the external forcing. Proxy data and model simulation consistently show a significant 60-yr AMV during AD 1250–1860 that is absent during AD 1–1249. Active volcanic eruptions during 1250–1860 amplify the AMV and shift its intrinsic 20–40-yr to a prominent 60-yr variance peak. Volcanoes prolong AMV periodicity by sustaining Arctic cooling, delaying subpolar sea ice melting, reducing evaporation, and increasing surface salinity. These results help us better understand nonstationary AMV and highlight the role of external forcing over the past two millennia.

Open access
Pao-Liang Chang
,
Jian Zhang
,
Yu-Shuang Tang
,
Lin Tang
,
Pin-Fang Lin
,
Carrie Langston
,
Brian Kaney
,
Chia-Rong Chen
, and
Kenneth Howard

Abstract

Over the last two decades, the Central Weather Bureau of Taiwan and the U.S. National Severe Storms Laboratory have been involved in a research and development collaboration to improve the monitoring and prediction of river flooding, flash floods, debris flows, and severe storms for Taiwan. The collaboration resulted in the Quantitative Precipitation Estimation and Segregation Using Multiple Sensors (QPESUMS) system. The QPESUMS system integrates observations from multiple mixed-band weather radars, rain gauges, and numerical weather prediction model fields to produce high-resolution (1 km) and rapid-update (10 min) rainfall and severe storm monitoring and prediction products. The rainfall products are widely used by government agencies and emergency managers in Taiwan for flood and mudslide warnings as well as for water resource management. The 3D reflectivity mosaic and QPE products are also used in high-resolution radar data assimilation and for the verification of numerical weather prediction model forecasts. The system facilitated collaborations with academic communities for research and development of radar applications, including quantitative precipitation estimation and nowcasting. This paper provides an overview of the operational QPE capabilities in the Taiwan QPESUMS system.

Full access
Chu-Chun Chen
,
Min-Hui Lo
,
Eun-Soon Im
,
Jin-Yi Yu
,
Yu-Chiao Liang
,
Wei-Ting Chen
,
Iping Tang
,
Chia-Wei Lan
,
Ren-Jie Wu
, and
Rong-You Chien

Abstract

Tropical deforestation can result in substantial changes in local surface energy and water budgets, and thus in atmospheric stability. These effects may in turn yield changes in precipitation. The Maritime Continent (MC) has undergone severe deforestation during the past few decades but it has received less attention than the deforestation in the Amazon and Congo rain forests. In this study, numerical deforestation experiments are conducted with global (i.e., Community Earth System Model) and regional climate models (i.e., Regional Climate Model version 4.6) to investigate precipitation responses to MC deforestation. The results show that the deforestation in the MC region leads to increases in both surface temperature and local precipitation. Atmospheric moisture budget analysis reveals that the enhanced precipitation is associated more with the dynamic component than with the thermodynamic component of the vertical moisture advection term. Further analyses on the vertical profile of moist static energy indicate that the atmospheric instability over the deforested areas is increased as a result of anomalous moistening at approximately 800–850 hPa and anomalous warming extending from the surface to 750 hPa. This instability favors ascending air motions, which enhance low-level moisture convergence. Moreover, the vertical motion increases associated with the MC deforestation are comparable to those generated by La Niña events. These findings offer not only mechanisms to explain the local climatic responses to MC deforestation but also insights into the possible reasons for disagreements among climate models in simulating the precipitation responses.

Open access
Gengxin Chen
,
Weiqing Han
,
Xiaolin Zhang
,
Linlin Liang
,
Huijie Xue
,
Ke Huang
,
Yunkai He
,
Jian Li
, and
Dongxiao Wang

Abstract

Using 4-yr mooring observations and ocean circulation model experiments, this study characterizes the spatial and temporal variability of the Equatorial Intermediate Current (EIC; 200–1200 m) in the Indian Ocean and investigates the causes. The EIC is dominated by seasonal and intraseasonal variability, with interannual variability being weak. The seasonal component dominates the midbasin with a predominant semiannual period of ~166 days but weakens toward east and west where the EIC generally exhibits large intraseasonal variations. The resonant second and fourth baroclinic modes at the semiannual period make the largest contribution to the EIC, determining the overall EIC structures. The higher baroclinic modes, however, modify the EIC’s vertical structures, forming multiple cores during some time periods. The EIC intensity has an abrupt change near 73°E, which is strong to the east and weak to the west. Model simulation suggests that the abrupt change is caused primarily by the Maldives, which block the propagation of equatorial waves. The Maldives impede the equatorial Rossby waves, reducing the EIC’s standard deviation associated with reflected Rossby waves by ~48% and directly forced waves by 20%. Mode decomposition further demonstrates that the semiannual resonance amplitude of the second baroclinic mode reduces by 39% because of the Maldives. However, resonance amplitude of the four baroclinic mode is less affected, because the Maldives fall in the node region of mode 4’s resonance. The research reveals the spatiotemporal variability of the poorly understood EIC, contributing to our understanding of equatorial wave–current dynamics.

Free access