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Natalia Pilguj, Mateusz Taszarek, John T. Allen, and Kimberly A. Hoogewind

Abstract

In this work, long-term trends in convective parameters are compared between ERA5, MERRA-2, and observed rawinsonde profiles over Europe and the United States including surrounding areas. A 39-yr record (1980–2018) with 2.07 million quality-controlled measurements from 84 stations at 0000 and 1200 UTC is used for the comparison, along with collocated reanalysis profiles. Overall, reanalyses provide signals that are similar to observations, but ERA5 features lower biases. Over Europe, agreement in the trend signal between rawinsondes and the reanalyses is better, particularly with respect to instability (lifted index), low-level moisture (mixing ratio), and 0–3-km lapse rates as compared with mixed trends in the United States. However, consistent signals for all three datasets and both domains are found for robust increases in convective inhibition (CIN), downdraft CAPE (DCAPE), and decreases in mean 0–4-km relative humidity. Despite differing trends between continents, the reanalyses capture well changes in 0–6-km wind shear and 1–3-km mean wind with modest increases in the United States and decreases in Europe. However, these changes are mostly insignificant. All datasets indicate consistent warming of almost the entire tropospheric profile, which over Europe is the fastest near ground whereas across the Great Plains it is generally between 2 and 3 km above ground level, thus contributing to increases in CIN. Results of this work show the importance of intercomparing trends between various datasets, as the limitations associated with one reanalysis or observations may lead to uncertainties and lower our confidence in how parameters are changing over time.

Open access
Veeshan Narinesingh, James F. Booth, and Yi Ming

Abstract

This study examines the climatology and dynamics of atmospheric blocking, and the general circulation features that influence blocks in GFDL’s atmosphere-only (AM4) and coupled atmosphere–ocean (CM4) comprehensive models. We compare AM4 and CM4 with reanalysis, focusing on winter in the Northern Hemisphere. Both models generate the correct blocking climatology and planetary-scale signatures of the stationary wave. However, at regional scales some biases exist. In the eastern Pacific and over western North America, both models generate excessive blocking frequency and too strong of a stationary wave. In the Atlantic, the models generate too little blocking and a weakened stationary wave. A block-centered compositing analysis of block-onset dynamics reveals that the models 1) produce realistic patterns of high-frequency (1–6-day) eddy forcing and 2) capture the notable differences in the 500-hPa geopotential height field between Pacific and Atlantic blocking. However, the models fail to reproduce stronger wave activity flux convergence in the Atlantic compared to the Pacific. Overall, biases in the blocking climatology in terms of location, frequency, duration, and area are quite similar between AM4 and CM4 despite the models having large differences in sea surface temperatures and climatological zonal circulation. This could suggest that other factors could be more dominant in generating blocking biases for these GCMs.

Significance Statement

Atmospheric blocks are persistent high pressure systems that can lead to hazardous weather. Historically, climate models have had trouble capturing blocks, but recent changes in the models might lead to improvements. As such, the work herein investigates the spatial distribution, prevalence, duration, size, and dynamics of wintertime blocking in recent NOAA climate models. Overall, these models capture the long-term-average spatial pattern of blocking, and properly reproduce key dynamical features. However, the models produce too much blocking in the western United States, and too little over the northern Atlantic Ocean and Europe. These blocking biases are consistent with atmospheric stationary waves biases, but not jet stream bias. This downplays the role of jet biases in the models being responsible for blocking biases.

Open access
Yanbo Nie and Jianqi Sun

Abstract

The interannual variability in summer precipitation intraseasonal oscillation intensity over southwest China (SWC) is investigated in this study. The results indicate that the 7–20-day period dominates the intraseasonal variability in summer SWC precipitation. The leading mode of summer SWC precipitation 7–20-day oscillation intensity (SPOI) is a north–south dipole pattern with prominent interannual variability. The atmospheric circulation anomalies from both tropics and mid- to high latitudes are responsible for the interannual variability in the dipole pattern. In the tropics, an enhanced local Hadley cell and an anomalous anticyclone over southern China and the northwest Pacific contribute to the north-positive–south-negative pattern of SPOI by inducing moisture convergence (divergence) over northern (southern) SWC in the background state. In the mid- to high latitudes, the 7–20-day Rossby wave trains along the subtropical jet are crucial for the 7–20-day precipitation over northern SWC. Further analyses suggest that the sea surface temperature (SST) anomalies over the Maritime Continent (MC) and the North Atlantic (NA) are associated with the SPOI dipole pattern. The MC SST warming causes convection anomalies over the tropical Indo-Pacific, consequently triggering a Matsuno–Gill-type atmospheric response conducive to the north-positive–south-negative pattern of SPOI. The NA SST tripole triggers a Rossby wave train across Eurasia that strengthens the East Asian westerly jet and enhances 7–20-day atmospheric variability, consequently favoring the variability of 7–20-day precipitation over northern SWC. Diagnoses of moisture and vorticity budgets further indicate the importance of the interaction between intraseasonal fluctuations and atmospheric background in the formation of the north–south difference in 7–20-day precipitation variability over SWC.

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L. Ruby Leung, William R. Boos, Jennifer L. Catto, Charlotte A. DeMott, Gill M. Martin, J. David Neelin, Travis A. O’Brien, Shaocheng Xie, Zhe Feng, Nicholas P. Klingaman, Yi-Hung Kuo, Robert W. Lee, Cristian Martinez-Villalobos, S. Vishnu, Matthew D. K. Priestley, Cheng Tao, and Yang Zhou

Abstract

Precipitation sustains life and supports human activities, making its prediction one of the most societally relevant challenges in weather and climate modeling. Limitations in modeling precipitation underscore the need for diagnostics and metrics to evaluate precipitation in simulations and predictions. While routine use of basic metrics is important for documenting model skill, more sophisticated diagnostics and metrics aimed at connecting model biases to their sources and revealing precipitation characteristics relevant to how model precipitation is used are critical for improving models and their uses. This paper illustrates examples of exploratory diagnostics and metrics including 1) spatiotemporal characteristics metrics such as diurnal variability, probability of extremes, duration of dry spells, spectral characteristics, and spatiotemporal coherence of precipitation; 2) process-oriented metrics based on the rainfall–moisture coupling and temperature–water vapor environments of precipitation; and 3) phenomena-based metrics focusing on precipitation associated with weather phenomena including low pressure systems, mesoscale convective systems, frontal systems, and atmospheric rivers. Together, these diagnostics and metrics delineate the multifaceted and multiscale nature of precipitation, its relations with the environments, and its generation mechanisms. The metrics are applied to historical simulations from phases 5 and 6 of the Coupled Model Intercomparison Project. Models exhibit diverse skill as measured by the suite of metrics, with very few models consistently ranked as top or bottom performers compared to other models in multiple metrics. Analysis of model skill across metrics and models suggests possible relationships among subsets of metrics, motivating the need for more systematic analysis to understand model biases for informing model development.

Open access
Yoo-Geun Ham, Seon-Yu Kang, Yerim Jeong, Jee-Hoon Jeong, and Tim Li

Abstract

This study examined the contribution of the Pacific decadal oscillation (PDO) to the record-breaking 2013–17 drought in the Korean Peninsula. The meteorological drought signal, measured by the Standardized Precipitation Index (SPI), in 2013 and 2016 co-occurred with a heat wave. The positive phase of the PDO during the mid-2010s was responsible for the precipitation deficit, particularly in 2014, 2015, and 2017, resulting in 5 years of meteorological drought. The enhanced atmospheric heating anomalies over the subtropical central Pacific, induced by the in situ PDO-related sea surface temperature (SST) warming, led to a low-atmospheric cyclonic flow centered over the midlatitude Pacific. The northerly wind anomalies at the western edge of this low-level cyclonic flow were responsible for the horizontal negative advection of moist energy, which contributed to the decreased precipitation and the resultant negative SPI over the Korean Peninsula in 2014, 2015, and 2017. The large-ensemble simulation supported the observational findings that the composited SST anomalies during the 5 years of persistent drought exhibited prominent and persistent SST warming over the subtropical central Pacific, along with large-scale cyclonic flow over the North Pacific. The findings of this study imply that the SST anomalies over the North Pacific and subtropical central Pacific can be a predictable source to potentially increase the ability to forecast multiyear droughts over the Korean Peninsula.

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Sai Wang, Minghu Ding, Ge Liu, and Wen Chen

Abstract

Using ERA-Interim and output of the regional climate model MAR (Modèle Atmosphérique Régional) forced by ERA-Interim, this study investigates the mechanisms governing the persistent extreme rainfall events (PEREs) in the Antarctic Peninsula (AP) during austral summer (December–February) for the period 1980–2017. Due to the topography’s blocking effect on the warm and humid airflow, the increase in the rainfall is concentrated over the western AP during the periods of the PEREs. Contributed mainly by the low-frequency variations, the positive rainfall anomalies on the western AP can persist for multiple days, leading to the persistence of the extreme rainfall events. The additional rainfall anomalies can be attributed to the increase in the total precipitation. Through regulating the total precipitation, the low-frequency atmospheric circulation anomalies are vital to the formation of the PEREs. Specifically, a persistent circulation pattern with an anomalous cyclone (anticyclone) to the east (west) of the AP is conductive to the enhancement of poleward moisture fluxes. As a result, the total precipitation around the AP is strengthened, as well as the rainfall. Further investigation reveals that the barotropic feedback of the high-frequency eddies plays an important role in maintaining the low-frequency circulation anomalies.

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G. Srinivas, J. Vialard, M. Lengaigne, T. Izumo, and E. Guilyardi

Abstract

Here, we investigate the relative roles of atmospheric nonlinearities and asymmetrical sea surface temperature (SST) forcing in the El Niño–Southern Oscillation (ENSO) asymmetrical rainfall response. Applying a vertically integrated water vapor budget to the ERA5 reanalysis leads to a simple analytical equation for precipitation anomalies. This formulation reveals that ENSO rainfall anomalies are dominated by the linear component of the dynamical term (i.e., the anomalous moisture convergence due to the effect of circulation anomalies on climatological humidity). Nonlinearities in this term and the linear thermodynamical term (i.e., the effect of climatological circulation on humidity anomalies) both strengthen central Pacific rainfall anomalies for both ENSO phases. In contrast, the nonlinear term associated with the effect of anomalous divergence on anomalous moisture (i.e., the mixed term) weakens La Niña dry and strengthens El Niño wet anomalies, in particular during extreme El Niño events when it contributes to about 40% of the eastern Pacific wet anomalies. Overall, atmospheric nonlinearities directly account for ∼70% of the positively skewed ENSO rainfall distribution east of the date line, and ∼50% of the negatively skewed rainfall distribution in the western Pacific. The remaining ENSO rainfall asymmetries are attributable to the asymmetrical ENSO SST pattern. This asymmetrical SST pattern also has contributions from atmospheric nonlinearities through the Bjerknes feedback loop, in addition to those from oceanic nonlinearities. Our estimates are thus likely a lower bound of the contribution of atmospheric nonlinearities to the overall ENSO rainfall asymmetry.

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Cheng Zheng, Mingfang Ting, Yutian Wu, Nathan Kurtz, Clara Orbe, Patrick Alexander, Richard Seager, and Marco Tedesco

Abstract

We investigate wintertime extreme sea ice loss events on synoptic to subseasonal time scales over the Barents–Kara Sea, where the largest sea ice variability is located. Consistent with previous studies, extreme sea ice loss events are associated with moisture intrusions over the Barents–Kara Sea, which are driven by the large-scale atmospheric circulation. In addition to the role of downward longwave radiation associated with moisture intrusions, which is emphasized by previous studies, our analysis shows that strong turbulent heat fluxes are associated with extreme sea ice melting events, with both turbulent sensible and latent heat fluxes contributing, although turbulent sensible heat fluxes dominate. Our analysis also shows that these events are connected to tropical convective anomalies. A dipole pattern of convective anomalies with enhanced convection over the Maritime Continent and suppressed convection over the central to eastern Pacific is consistently detected about 6–10 days prior to extreme sea ice loss events. This pattern is associated with either the Madden–Julian oscillation (MJO) or El Niño–Southern Oscillation (ENSO). Composites show that extreme sea ice loss events are connected to tropical convection via Rossby wave propagation in the midlatitudes. However, tropical convective anomalies alone are not sufficient to trigger extreme sea ice loss events, suggesting that extratropical variability likely modulates the connection between tropical convection and extreme sea ice loss events.

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Elliott M. Sainsbury, Reinhard K. H. Schiemann, Kevin I. Hodges, Alexander J. Baker, Len C. Shaffrey, and Kieran T. Bhatia

Abstract

Recurving tropical cyclones (TCs) can cause extensive damage along the U.S. East Coast and later in their life cycle over Europe as post-tropical cyclones. While the existing literature attempts to understand the drivers of basinwide and regional TC variability, less work has been undertaken looking at recurving TCs. The roles played by the interannual variabilities of TC frequency and the steering flow in governing recurving TC interannual variability are investigated in this study. Using a track-matching algorithm, we identify observed TC tracks from the NHC “best track” hurricane database, version 2 (HURDAT2) in the ERA5 and MERRA2 reanalyses. This allows for detailed analysis of the post-tropical stages of the tracks in the observational TC record, enabling robust identification and separation of TCs that recurve. We show that over 75% of the interannual variance in annual recurving TC frequency can be explained by just two predictors—the frequency of TCs forming in the subtropical Atlantic, and hurricanes (TCs with wind speeds > 33 m s−1) forming in the main development region (MDR). An index describing the seasonal mean meridional steering flow shows a weak, nonsignificant relationship with recurving TC frequency, supported by composite analysis. These results show that the interannual variability in recurving TC frequency is primarily driven by the seasonal TC activity of the MDR and the subtropical Atlantic, with seasonal anomalies in the steering flow playing a much smaller, secondary role. These results help to quantify the extent to which skillful seasonal forecasts of Atlantic hurricane activity benefit regions vulnerable to recurving TCs.

Significance Statement

Recurving tropical cyclones (TCs) can cause extensive damage to the U.S. East Coast, eastern Canada, and Europe. It is, therefore, crucial to understand why some years have a higher frequency of recurving TCs than other years. In this study, we show that the frequency of recurving TCs is very strongly linked to the frequency that hurricanes (TCs with wind speeds > 33 m s−1) form in the main development region, and the frequency that TCs form in the subtropical Atlantic. This result suggests that skillful seasonal prediction of hurricane activity could be used to give enhanced seasonal warning to the regions often impacted by recurving TCs.

Open access
Andrzej Z. Kotarba and Z˙aneta Nguyen Huu

Abstract

The longest cirrus time series are ground-based, visual observations captured by human observers [synoptic observations (SYNOP)]. However, their reliability is impacted by an unfavorable viewing geometry (cloud overlap) and misclassification due to low cloud optical thickness, especially at night. For the very first time, this study assigns a quantitative value to uncertainty. We validate 15 years of SYNOP observations (2006–20) against data from the cloud lidar flown on board the Cloud–Aerosol Lidar and Infrared Pathfinder (CALIPSO) spacecraft. We develop a dedicated method to match SYNOP reports (with a hemispherical field of view) with lidar samples (along-track profiles). Our evaluation of the human eye’s sensitivity to cirrus revealed that it is moderate, at best. In perfect conditions (daytime with no mid/low-level clouds) the probability of correct detection was 44%–83% (Cohen’s kappa coefficient < 0.6), and this fell to 24%–42% (kappa < 0.3) at night. Lunar illumination improved detection, but only when the moon’s phase exceeded 50%. Cirrus optical depth had a clear impact on detection. When clouds at all levels were considered (i.e., real-life conditions), the reliability of the visual method was moderate to poor: it detected 47%–71% of cirrus (kappa < 0.45) during the day and 28%–43% (kappa < 0.2) at night and decreased with an increasing low/midlevel cloud fraction. These kappa coefficients suggest that agreement with CALIPSO data was close to random. Our findings can be directly applied to estimations of cirrus frequency/trends. Our reported probabilities of detection can serve as a benchmark for other ground-based cirrus detection methods.

Significance Statement

Cirrus clouds heat the atmosphere, so any increase in their frequency will contribute to climate warming. The longest cirrus time series (including the presatellite era) are surface-based detections by a human observer at a meteorological station. Our study is the first to quantitatively evaluate the reliability of these observations. Our results show that, because of the viewing geometry (cloud overlap) and human eye sensitivity, reliability ranges from moderate at best to very low. Nighttime detections are especially unreliable, as well as those in the presence of low/midlevel cloud. Cirrus frequencies and trends calculated from visual observations should, thus, be considered with caution.

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