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Kazuya Kusahara, Hiroaki Tatebe, Tomohiro Hajima, Fuyuki Saito, and Michio Kawamiya

Abstract

Changes in the Antarctic ice sheet play a critical role in the Southern Ocean and global climates. Although many studies have pointed out that enhanced ocean heat delivery onto the Antarctic continental shelf regions can cause significant changes in Antarctic ice-shelf basal melting, the associated physical mechanisms require further research. Here, we perform numerical experiments using an ocean-sea ice model with an ice-shelf component to simulate future projections in Antarctic ice-shelf basal melting in a warming climate, focusing on the driving mechanism and the physical linkages with the seasonal Antarctic sea-ice fields and coastal water masses. The model projects a distinct superlinear response of ice-shelf basal melting to future atmospheric warming, demonstrating that future projections of the Antarctic and Southern Ocean climate bifurcate with the level of global warming. Detailed examinations of sea ice and water masses show that in an extreme warming scenario, a combination of enhanced intrusions of warm deep water and warm summertime surface water can cause the nonlinear response of Antarctic ice-shelf basal melting. A large reduction in Antarctic coastal sea ice and the associated ocean freshening by decreasing coastal sea-ice production in winter provide favorable conditions for summertime warm surface water formation and warm deep water intrusions onto some continental shelves. The model results demonstrate that disappearing summertime sea ice along the Antarctic coastal margins in a warming climate heralds the nonlinear increase in Antarctic ice-shelf basal melting, presumably contributing to the negative mass balance of the Antarctic ice sheet and the sea-level rise.

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Xiquan Dong, Xiaojian Zheng, Baike Xi, and Shaocheng Xie

Abstract

More than four years of ground-based measurements taken at the ARM Eastern North Atlantic (ENA) site between July 2015 and September 2019 have been collected and processed in this study. Monthly and hourly means of clear-sky, all-sky, total cloud fraction (CFT), single-layered low (CFL) and high (CFH) clouds, the impacts of all scene types on the surface radiation budget (SRB), and their cloud radiative effects (CREs) have been examined. The annual averages of CFT, CFL and CFH are 0.785, 0.342, and 0.123, respectively. The annual averages of the SW (LW) CREs for all sky, total, low and high clouds are -56.7 (37.7), -76.6 (48.5), -73.7 (51.4) and -26.8 (13.9) Wm-2, respectively, resulting in the NET CREs of -19.0, - 28.0, -22.2 and -12.9 Wm-2. Comparing the cloud properties and CREs at both ARM ENA and Southern Great Plains (SGP) sites, we found that the clear-sky downwelling SW and LW fluxes at the two sites are similar to each other due to their similar atmospheric background. Compared to SGP, the lower all-sky SW and higher LW fluxes at ENA are caused by its higher CFT and all-sky precipitable water vapor (PWV). With different low cloud microphysical properties and cloud condensation nuclei at the two sites, much higher cloud optical depth at SGP plays an important role in determining its lower SW flux, while Tb and PWV are important for downwelling LW flux at the surface. A sensitivity study has shown that the all-sky SW CREs at SGP are more sensitive to CFT (-1.07 Wm-2 %-1) than at ENA (-0.689 Wm-2 %-1), with the same conclusion for all-sky LW CREs (0.735 Wm-2 %-1 at SGP vs. 0.318 Wm-2 %-1 at ENA). The results over the two sites shed new light on the impacts of clouds on the mid-latitude surface radiation budgets, over both ocean and land.

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Ivan Chavez, Shawn M. Milrad, Daniel J. Halperin, Bryan Mroczka, and Kevin R. Tyle

Abstract

Florida annually leads the United States in lightning-caused fatalities. While many studies have examined the lightning frequency maximum near Cape Canaveral, relatively little attention has been paid to the western Florida peninsula, which features a similar warm-season lightning event density. Of particular concern are first cloud-to-ground (FCG) lightning events in developing thunderstorms, which are difficult to predict with sufficient lead time and can catch people off guard. This study performs an environmental analysis of warm-season (May–September) FCG events (2014–21) across the western Florida peninsula using high-resolution model analysis data, including a comparison to null (No CG) days. FCG events and No CG days are first identified from ground-based lightning data and partitioned into nine synoptic-scale flow regimes. Next, spatiotemporal distributions of FCG events are elucidated for the western Florida peninsula. An ingredients-based analysis shows that the convective environment one hour before FCG events during strong south-southeast flow features the largest amounts of moisture, but the smallest instability values and weak midtropospheric lapse rates, primarily due to warm advection and moisture transport from the Atlantic Ocean. Environments one hour before FCG events in all nine flow regimes feature markedly greater instability values, larger relative humidity values, and steeper midtropospheric lapse rates than do No CG days. Results emphasize that instability and moisture are the key ingredients for warm-season FCG events in the region. Convective parameter statistical distributions and composite soundings populate an online dashboard that can be used by regional forecasters to better predict FCG events and increase alert lead times.

Significance Statement

Florida annually leads the United States in lightning fatalities. Of particular concern are first cloud-to-ground (FCG) lightning events, which are difficult to forecast and can catch people off guard especially during outdoor recreational activities and labor. We investigate the environmental characteristics of warm-season FCG events across the western Florida peninsula. Among nine regional flow patterns, some are associated with a less moist and more unstable atmosphere one hour before an FCG event, while other regimes exhibit a more moist and less unstable atmosphere. However, regardless of flow pattern, FCG events consistently feature substantially greater instability and moisture than do null events. Key findings are displayed on an online dashboard, to better inform regional forecasters.

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Nicholas M. Falk and Susan C. van den Heever

Abstract

Cold pools can initiate new convection by increasing vertical velocity (mechanical forcing) and locally enhancing moisture content (thermodynamic forcing). This study investigates the impact of the environment on mechanical and thermodynamic forcing from cold pool collisions. An ensemble of high-resolution numerical simulations was conducted which tested the sensitivity of cold pool collisions to three parameters: (1) the initial temperature deficit of cold pools, (2) the initial distance between cold pools, and (3) the static stability and moisture content of the environment. These parameters are tested in the absence of condensation, surface fluxes, radiation, and wind shear. Colder initial cold pools increase mechanical and thermodynamic forcing owing to greater horizontal winds during collisions. For all environments tested, mechanical forcing peaked robustly at an optimal initial distance between the cold pools due to a balance between the creation and dissipation of kinetic energy, and the different phases of density current evolution. Thermodynamic forcing peaked for greater initial cold pool distances than those associated with mechanical forcing. Decreased low-level static stability and an increased vertical gradient in low-level moisture enhanced mechanical and thermodynamic forcing, respectively. It is also shown that the initial temperature deficit had the greatest impact on mechanical and thermodynamic forcing, followed by the environment, and finally the initial separation distance. Finally, cold pool collisions are classified as “mechanically strong” or “mechanically weak”, where mechanically strong collisions increased mechanical forcing beyond that driven by the initial outward spreading of the cold pools. An analogous classification of “thermodynamically strong/weak” is also presented.

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Andrew Hazelton, Ghassan J. Alaka Jr., Michael S. Fischer, Ryan Torn, and Sundararaman Gopalakrishnan

Abstract

Hurricane Dorian (2019), a category-five tropical cyclone (TC), was characterized by a large spread in track forecasts as it moved northwest. A set of 80 ensemble forecasts from the Hurricane Analysis and Forecast System (HAFS) was produced to evaluate Dorian’s track spread and the factors that contributed to it. Track spread was particularly critical at long lead times (5–7 days after initialization near the Lesser Antilles), due to the uncertainty in the location of landfall and hazards. Four clusters of members were analyzed based on the 7-day track, characterized by Dorian moving: 1) slowly near the northern Bahamas (closest to reality), 2) across the Florida Peninsula, 3) slowly into Florida’s east coast, and 4) quickly north of The Bahamas. Ensemble sensitivity techniques were applied to identify areas that were most critical for Dorian’s track. Key differences were found in the strength of the subtropical ridge over the western Atlantic with a weaker ridge and slower easterly steering flow in the offshore groups. Subtle differences in the synoptic pattern over the United States also appeared to affect the timing of Dorian’s northward turn, specifically the strength of a shortwave trough moving over the Ohio Valley. Despite some early track differences, the correlation between early and late track errors was not significant. An examination of four members further highlights the differences in steering and the strength of the subtropical ridge. This study demonstrates the utility of ensemble datasets for studying TC forecast uncertainty, and the importance of medium-range modeling of synoptic-scale steering features to accurately predict the track of tropical cyclones.

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Alexander Lemburg and Andreas H. Fink

Abstract

In the last few years, central Europe faced a number of severe, record-breaking heatwaves. Previous studies focused on predictability of heatwaves on medium-range to subseasonal time scales (5–30 days). However, also short-range (3-day) forecasts of maximum temperature (Tmax) can exhibit substantial errors even on larger spatial scales. This study investigates the causes of short-range forecast errors in Tmax over central Europe for the summers of 2015–20 using the 50-member ensemble of the operational ECMWF-IFS (ECMWF-ENS). The 3-day forecast errors, individually calculated for each ensemble member with respect to a 0–18-h control forecast, are fed into a multivariate linear regression model to study the relative importance of different error sources. Outside of heatwaves, errors in Tmax forecasts are predominantly caused by incorrectly predicted downwelling shortwave radiation, mainly due to errors in low cloud cover. During heatwaves, ECMWF-ENS exhibits a systematic underestimation of Tmax (−0.4 K), which is exacerbated under clear-sky and low wind conditions, and other error sources gain importance: the second most important error source is over- or underestimation of nocturnal temperatures in the residual layer. Additional Lagrangian trajectory analysis for the years 2018–20 (due to limited data availability) suggests a link to accumulating errors in near-surface diabatic heating of air masses associated with forecast errors in residence time over land and cloud cover. Regionally, other physical processes can be of dominant importance during heatwaves. Coastal regions are influenced by errors in near-surface wind whereas errors in soil moisture are more important in southeastern parts of central Europe.

Open access
S. Abhik, Harry H. Hendon, and Chidong Zhang

Abstract

The Madden-Julian Oscillation (MJO) is often observed to weaken or sometimes completely decay as its convective anomaly moves from the Indian Ocean over the Maritime Continent (MC), which is known as the MC barrier effect on the MJO. This barrier effect is often exaggerated in numerical models. Using 23 years of the retrospective intraseasonal forecast from two coupled model systems with useful MJO prediction skills, we show that the predictive skill of the RMM index for the continuously propagating MJO events across the MC region is higher than for the blocked MJO events. The greater prediction skill is not related to the higher initial RMM amplitude for the continuous MJO events. Rather the higher skill arises from the more persistent behavior of the propagating MJO events as the convective anomaly moves through the MC region into the western Pacific. The potential predictability is similar for both types of MJO events, suggesting the forecast models hardly differentiate both the MJO events in prediction; they only maintain higher RMM magnitudes of the continuously propagating events. An analysis of a global reanalysis dataset reveals that the blocked events are often associated with persistent higher surface pressures over colder sea surface temperatures in the central Pacific, suggesting the large-scale environment plays a role in promoting or inhibiting the MJO propagation across the MC region. Caveats in the models to reproduce the observed MJO events are discussed.

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Max Mauerman, Emily Black, Victoria L. Boult, Rahel Diro, Dan Osgood, Helen Greatrex, and Thabbie Chillongo

Abstract

Decision-makers in climate risk management often face problems of how to reconcile diverse and conflicting sources of information about weather and its impact on human activity, such as when they are determining a quantitative threshold for when to act on satellite data. For this class of problems, it is important to quantitatively assess how severe a year was relative to other years, accounting for both the level of uncertainty among weather indicators and those indicators’ relationship to humanitarian consequences. We frame this assessment as the task of constructing a probability distribution for the relative severity of each year, incorporating both observational data – such as satellite measurements – and prior information on human impact – such as farmers’ reports – the latter of which may be incompletely measured or partially ordered. We present a simple, extensible statistical method to fit a probability distribution of relative severity to any ordinal data, using the principle of maximum entropy. We demonstrate the utility of the method through application to a weather index insurance project in Malawi, in which the model allows us to quantify the likelihood that satellites would correctly identify damaging drought events as reported by farmers, while accounting for uncertainty both within a set of commonly used satellite indicators and between those indicators and farmers’ ranking of the worst drought years. This approach has immediate utility in the design of weather-index insurance schemes and forecast-based action programs, such as assessing their degree of basis risk or determining the probable needs for post-season food assistance.

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Liu Yang, Shang-Ping Xie, Samuel S. P. Shen, Jing-Wu Liu, and Yen-Ting Hwang

Abstract

Low clouds frequent the subtropical northeastern Pacific (NEP) and interact with the local sea surface temperature (SST) to form positive feedback. Wind fluctuations drive SST variability through wind-evaporation-SST (WES) feedback, and surface evaporation also acts to damp SST. This study investigates the relative contributions of these feedbacks to NEP SST variability. Over the summer NEP, the low cloud-SST feedback is so large that it exceeds the evaporative damping and amplifies summertime SST variations. The WES feedback causes the locally enhanced SST variability to propagate southwestward from the NEP low-cloud deck, modulating the El Niño-Southern Oscillation (ENSO) occurrence upon reaching the equator. As a result, a second-year El Niño (La Niña) tends to occur when there are significant warm (cold) SST anomalies over the subtropical NEP in summer following an antecedent El Niño (La Niña) event. The mediating role of the NEP low cloud-SST feedback is confirmed in a cloud-locking experiment with the Community Earth System Model (CESM1). When the cloud-ocean coupling is disabled, SST variability over the NEP weakens and the modulating effect on ENSO vanishes. The nonlocal effect of the NEP low cloud-SST feedback on ENSO has important implications for climate prediction.

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Qianwen Hu, Xiaodong Huang, Qinbo Xu, Chun Zhou, Shoude Guan, Xing Xu, Wei Zhao, Qingxuan Yang, and Jiwei Tian

Abstract

Internal waves close to the seafloor of abyssal oceans are the key energy suppliers driving near-bottom mixing and the upwelling branches of meridional overturning circulation, but their spatiotemporal variability and intrinsic mechanisms remain largely unclear. In this study, measurements from 10 long-term moorings were used to investigate the internal wave activities in the abyssal South China Sea, which is an important upwelling zone. Strong near-inertial internal waves (NIWs) with current velocity pulses exceeding 5 cm s−1 were observed to dominate the near-bottom internal wave field at approximately 14°N. These abyssal NIWs were phase-coupled with diurnal internal tides (D1), and both displayed common seasonal variations that were larger in winter and summer, providing evidence of diurnal parametric subharmonic instability (PSI) near its critical latitudes (CLs). Emitted from the bottom, near-inertial kinetic energy rapidly decreased by one order of magnitude from depths of ~120 m to ~620 m above the bottom. Near rough topographies, the abyssal PSI was shifted poleward to approximately 14.8°N by negative relative vorticities of passing anticyclonic eddies or topographic Rossby waves. Compared with flat topography, PSI near rough topography was significantly promoted by topographic-localized strong D1 with high-mode structures, creating abyssal NIW bursts. Bottom-reaching shipboard conductivity-temperature-depth profiles revealed that the bottom mixed layers became much thicker when approaching CLs, suggesting that abyssal PSI potentially accelerates the ventilation and upwelling of bottom water. The observational results presented here illustrate notable spatiotemporal variations in abyssal NIWs regulated by PSI and call for consideration of PSI to better understand near-bottom mixing and upwelling.

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