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Nicholas M. Leonardo and Brian A. Colle

Abstract

The largest medium-range (72–120 h) cross-track errors (CTE) of tropical cyclone (TC) forecasts from the Global Ensemble Forecast System (GEFS) over the northern Atlantic Ocean are examined for the 2008–16 seasons. The 38 unique forecasts within the upper quartile of most negative CTEs (i.e., left-of-track bias larger than 250 km by 72 h) do not have a clear common source of steering error, although 12 of the forecasts involve the underprediction of a weak upper-level trough to the west of the TC by 36 h. Meanwhile, at least 18 of the 36 most positive CTEs (right-of-track bias) are associated with TCs embedded in the southwest extent of a subtropical ridge, the strength of which is increasingly underpredicted during the first 24 h of the forecast. Excessive height falls north of the TC are driven by overpredicted divergence aloft, which corresponds to overpredicted TC outer-core convection. The convection is triggered by a 5%–20% overprediction of near-TC moisture and instability in the initial conditions. Weather Research and Forecasting (WRF) Model simulations are run at 36-, 12-, and 4-km grid spacing for select right-of-track cases, using the GEFS for initial and lateral boundary conditions. The 36-km WRF reproduces the same growth of errors as the GEFS because of, in part, sharing the same stability and moisture errors in the initial conditions. Changes in the convective parameterization affect how quickly these errors grow by affecting how much convection spins up. The addition of a 4-km nest with no convective parameterization causes the errors to grow ~20% faster, resulting in an even larger right-of-track error.

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Omar V. Müller, Pier Luigi Vidale, Benoît Vannière, Reinhard Schiemann, Retish Senan, Reindert J. Haarsma, and Johann H. Jungclaus

Abstract

Land–atmosphere interactions are often interpreted as local effects, whereby the soil state drives local atmospheric conditions and feedbacks originate. However, nonlocal mechanisms can significantly modulate land–atmosphere exchanges and coupling. We make use of GCMs at different resolutions (low ~1° and high ~0.25°) to separate the two contributions to coupling: better represented local processes versus the influence of improved large-scale circulation. We use a two-legged metric, complemented by a process-based assessment of four CMIP6 GCMs. Our results show that weakening, strengthening, and relocation of coupling hot spots occur at high resolution globally. The northward expansion of the Sahel hot spot, driven by nonlocal mechanisms, is the most notable change. The African easterly jet’s horizontal wind shear is enhanced in JJA due to better resolved orography at high resolution. This effect, combined with enhanced easterly moisture flux, favors the development of African easterly waves over the Sahel. More precipitation and soil moisture recharge produce strengthening of the coupling, where evapotranspiration remains controlled by soil moisture, and weakening where evapotranspiration depends on atmospheric demand. In SON, the atmospheric influence is weaker, but soil memory helps to maintain the coupling between soil moisture and evapotranspiration and the relocation of the hot spot at high resolution. The multimodel agreement provides robust evidence that atmospheric dynamics determines the onset of land–atmosphere interactions, while the soil state modulates their duration. Comparison of precipitation, soil moisture, and evapotranspiration against satellite data reveals that the enhanced moistening at high resolution significantly reduces model biases, supporting the realism of the hot-spot relocation.

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Xian Xiao, Juanzhen Sun, Xiushu Qie, Zhuming Ying, Lei Ji, Mingxuan Chen, and Lina Zhang

Abstract

A proof-of-concept method for the assimilation of total lightning observations in the 4DVAR framework is proposed and implemented into the Variational Doppler Radar Analysis System (VDRAS). Its performance is evaluated for the very short-term precipitation forecasts of a localized convective event over northeastern China. The lightning DA scheme assimilated pseudo-observations for vertical velocity fields derived from observed total lightning rates and statistically computed vertical velocity profile from VDRAS analysis data. To reduce representative errors of the derived vertical velocity, a distance-weighted horizontal interpolation is applied to the input data prior to the DA. The case study reveals that although 0–2-h precipitation nowcasts are improved by assimilating lightning data alone compared to CTRL (no radar or lightning) and RAD (radar only), better results are obtained when the lightning data are assimilated with radar data simultaneously. The assimilation of both data sources results in improved dynamical consistency with enhanced updraft and latent heat as well as improved moisture distributions. Additional experiments are conducted to evaluate the sensitivity of the combined DA scheme to varied vertical velocity profiles, radii of horizontal interpolation, binning time intervals, and relationships used to estimate the maximum vertical velocity from lightning flash rates. It is shown that the scheme is robust to these variations with both radar and lightning assimilated data.

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Danielle G. Udy, Tessa R. Vance, Anthony S. Kiem, Neil J. Holbrook, and Mark A. J. Curran

Abstract

Weather systems in the southern Indian Ocean (SIO) drive synoptic-scale precipitation variability in East Antarctica and southern Australia. Improved understanding of these dynamical linkages is beneficial to diagnose long-term climate changes from climate proxy records as well as informing regional weather and climate forecasts. Self-organizing maps (SOMs) are used to group daily 500-hPa geopotential height (z500; ERA-Interim) anomalies into nine regional synoptic types based on their dominant patterns over the SIO (30°–75°S, 40°–180°E) from January 1979 to October 2018. The pattern anomalies represented include four meridional, three mixed meridional–zonal, one zonal, and one transitional node. The frequency of the meridional nodes shows limited association with the phase of the southern annular mode (SAM), especially during September–November. The zonal and mixed patterns were nevertheless strongly and significantly correlated with SAM, although the regional synoptic representation of SAM+ conditions was not zonally symmetric and was represented by three separate nodes. We recommend consideration of how different synoptic conditions vary the atmospheric representation of SAM+ in any given season in the SIO. These different types of SAM+ mean a hemispheric index fails to capture the regional variability in surface weather conditions that is primarily driven by the synoptic variability rather than the absolute polarity of the SAM.

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Yujia You and Mingfang Ting

Abstract

Understanding the physical mechanisms behind the secular trends of summer rainfall extremes over the heavily populated Southeast and East Asian monsoon regions is not only of scientific importance but also of considerable socioeconomic implications. In this study, the relevance of the excessive-rain-producing low pressure systems (LPSs) to extreme rainfall is quantified. Using an objective feature-tracking algorithm, the synoptic-scale LPSs are identified and tracked in the 40-yr ECMWF interim reanalysis. The region experiences approximately 16 terrestrial and 18 marine LPSs each summer. The terrestrial LPSs form near the downwind side of the Tibetan Plateau and travel northeastward toward jet latitudes. The marine LPSs form over the western North Pacific Ocean and migrate along the western periphery of the subtropical high. While both types of LPSs account for a large portion of upper-tail rainfall, the terrestrial LPSs predominantly impact the extreme rainfall over inland areas, and the marine LPSs primarily affect the coastal regions where they frequently make landfall. The historical extreme rainfall trend during 1979–2018 aligns with the changes in LPS tracks. The decreasing number of northeastward-moving terrestrial LPSs leads to an extreme rainfall dipole with negative trends in north-central China and positive trends in southern China, while the increasing number of northward-recurving marine LPSs enhances the extreme rainfall in the eastern China coast but suppresses it over the South China Sea. These trends are driven dynamically by the weakening of the monsoonal southwesterlies and the eastward retreat of the subtropical high, which might be attributable to anthropogenic forcings.

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Peter Uhe, Dann Mitchell, Paul D. Bates, Myles R. Allen, Richard A. Betts, Chris Huntingford, Andrew D. King, Benjamin M. Sanderson, and Hideo Shiogama

Abstract

Precipitation events cause disruption around the world and will be altered by climate change. However, different climate modeling approaches can result in different future precipitation projections. The corresponding “method uncertainty” is rarely explicitly calculated in climate impact studies and major reports but can substantially change estimated precipitation changes. A comparison across five commonly used modeling activities shows that, for changes in mean precipitation, less than half of the regions analyzed had significant changes between the present climate and 1.5°C global warming for the majority of modeling activities. This increases to just over half of the regions for changes between present climate and 2°C global warming. There is much higher confidence in changes in maximum 1-day precipitation than in mean precipitation, indicating the robust influence of thermodynamics in the climate change effect on extremes. We also find that none of the modeling activities captures the full range of estimates from the other methods in all regions. Our results serve as an uncertainty map to help interpret which regions require a multimethod approach. Our analysis highlights the risk of overreliance on any single modeling activity and the need for confidence statements in major synthesis reports to reflect this method uncertainty. Considering multiple sources of climate projections should reduce the risks of policymakers being unprepared for impacts of warmer climates relative to using single-method projections to make decisions.

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Andrew Hoell, Andrea E. Gaughan, Tamuka Magadzire, and Laura Harrison

Abstract

The spatiotemporal evolution of daily southern Africa precipitation characteristics, and associated atmospheric circulation, related to El Niño and La Niña is examined across the region’s November–April wet season. Precipitation characteristics are examined in terms of monthly changes in daily average precipitation, the number of precipitation days, and the number of heavy precipitation days in three independently constructed estimates of observed precipitation during 1983–2018. Mechanisms related to precipitation changes, including contributions from mass divergence, water vapor transports, and transient eddies, are diagnosed using the atmospheric moisture budget based on the ERA5 reanalysis. El Niño is related to precipitation anomalies that build during December–March, the core of the rainy season, culminating in significantly below average values stretching across a semiarid region from central Mozambique to southeastern Angola. A broad anticyclone centered over Botswana drives these precipitation anomalies primarily through anomalous mass divergence, with moisture advection and transient eddies playing secondary roles. La Niña is related to significantly above average daily precipitation characteristics over all Africa south of 20°S in February and much less so during the other five months. February precipitation anomalies are primarily driven through mass divergence due to a strong anomalous cyclonic circulation, whereas a similar circulation is more diffuse during the other months. The spatiotemporal evolutions of anomalies in daily precipitation characteristics across southern Africa related to El Niño and La Niña are not equal and opposite. The robustness of an asymmetric evolution, which could have implications for subseasonal forecasts, needs to be confirmed with analysis of additional empirical data and established with climate model experimentation.

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Saïd Qasmi, Emilia Sanchez-Gomez, Yohan Ruprich-Robert, Julien Boé, and Christophe Cassou

Abstract

The influence of the Atlantic multidecadal variability (AMV) and its amplitude on the Euro-Mediterranean summer climate is studied in two climate models, namely CNRM-CM5 and EC-Earth3P. Large ensembles of idealized experiments have been conducted in which North Atlantic sea surface temperatures are relaxed toward different amplitudes of the observed AMV anomalies. In agreement with observations, during a positive phase of the AMV both models simulate an increase (decrease) in temperature of 0.2°–0.8°C and a decrease (increase) in precipitation over the Mediterranean basin of 0.1–0.2 mm day−1 (northern half of Europe) compared to a negative phase. Heatwave durations over the Mediterranean land regions are 40% (up to 85% over the eastern regions) longer for a moderate amplitude of the AMV. Lower and higher amplitudes lead to longer durations of ~30% and ~100%, respectively. A comparison with observed heatwaves indicates that the AMV can considerably modulate the current anthropogenically forced response on heatwaves durations depending on the area and on the AMV amplitude. The related anticyclonic anomalies over the Mediterranean basin are associated with drier soils and a reduction of cloud cover, which concomitantly induce a decrease (increase) of the latent (sensible) heat flux, and an enhancement of the downward radiative fluxes over lands. It is found that both tropical and extratropical forcings from the AMV are needed to trigger mechanisms, which modulate the atmospheric circulation over the Euro-Atlantic region. The amplitude of the local climate response over the Mediterranean basin evolves linearly with the amplitude of the AMV. However, the strength of this relationship differs between the models, and depends on their intrinsic biases.

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Mengyuan Long, Lujun Zhang, Siyu Hu, and Shimeng Qian

Abstract

This paper evaluates the ability of 35 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) to simulate Arctic sea ice by comparing simulated results with observation from the aspects of spatial patterns and temporal variation. The simulation ability of each model is also quantified by the Taylor score and e score from these two aspects. Results show that biases between observed and simulated Arctic sea ice concentration (SIC) are mainly located in the East Greenland, Barents, and Bering Seas and the Sea of Okhotsk. The largest difference between the observed and simulated SIC spatial patterns occurs in September. Since the beginning of the twenty-first century, the ability of most models to simulate summer SIC spatial patterns has decreased. We also find that models with the Sea Ice Simulator (SIS) sea ice component in CMIP6 show a consistent larger positive simulation biases of SIC in the East Greenland and Barents Seas. In addition, for most models, the higher the model resolution is, the better the match between the simulated and observed spatial patterns of winter Arctic SIC is. Furthermore, this paper makes a detailed assessment for temporal variation of Arctic sea ice extent (SIE) with regard to climatological average, seasonal SIE, multiyear linear trend, and detrended standard deviation of SIE. The sensitivity of September Arctic SIE to a given change of Arctic surface air temperature over 1979–2014 in each model has also been investigated. Most models simulate a smaller loss of September Arctic SIE per degree of warming than is observed (1.37 × 106 km2 K−1).

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Lavinia Patara, Claus W. Böning, and Toste Tanhua

Abstract

Enhanced Southern Ocean ventilation in recent decades has been suggested to be a relevant modulator of the observed changes in ocean heat and carbon uptake. This study focuses on the Southern Ocean midlatitude ventilation changes from the 1960s to the 2010s. A global 1/4° configuration of the NEMO–Louvain-la-Neuve sea ice model, version 2 (LIM2), including the inert tracer CFC-12 (a proxy of ocean ventilation) is forced with the CORE, phase II (CORE-II), and JRA-55 driving ocean (JRA55-do) atmospheric reanalyses. Sensitivity experiments, where the variability of wind stress and/or the buoyancy forcing is suppressed on interannual time scales, are used to unravel the mechanisms driving ventilation changes. Ventilation changes are estimated by comparing CFC-12 interior inventories among the different experiments. All simulations suggest a multidecadal fluctuation of Southern Ocean ventilation, with a decrease until the 1980s–90s and a subsequent increase. This evolution is related to the atmospheric forcing and is caused by the (often counteracting) effects of wind stress and buoyancy forcing. Until the 1980s, increased buoyancy gains caused the ventilation decrease, whereas the subsequent ventilation increase was driven by strengthened wind stress causing deeper mixed layers and a stronger meridional overturning circulation. Wind stress emerges as the main driver of ventilation changes, even though buoyancy forcing modulates its trend and decadal variability. The three Southern Ocean basins take up CFC-12 in distinct density intervals but overall respond similarly to the atmospheric forcing. This study suggests that Southern Ocean ventilation is expected to increase as long as the effect of increasing Southern Hemisphere wind stress overwhelms that of increased stratification.

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