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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
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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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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Xing Luo, Jun Ge, Weidong Guo, Lei Fan, Chaorong Chen, Yu Liu, and Limei Yang

Abstract

Deforestation can impact precipitation through biophysical processes and such effects are commonly examined by models. However, previous studies mostly conduct deforestation experiments with a single model and the simulated precipitation responses to deforestation diverge across studies. In this study, 11 Earth system models are used to robustly examine the biophysical impacts of deforestation on precipitation, precipitation extremes, and the seasonal pattern of the rainy season through a comparison of a control simulation and an idealized global deforestation simulation with clearings of 20 million km2 of forests. The multimodel mean suggests decreased precipitation, reduced frequency and intensity of heavy precipitation, and shortened duration of rainy seasons over deforested areas. The deforestation effects can even propagate to some regions that are remote from deforested areas (e.g., the tropical and subtropical oceans and the Arctic Ocean). Nevertheless, the 11 models do not fully agree on the precipitation changes almost everywhere. In general, the models exhibit higher consistency over the deforested areas and a few regions outside the deforested areas (e.g., the subtropical oceans) but lower consistency over other regions. Such intermodel spread mostly results from divergent responses of evapotranspiration and atmospheric moisture convergence to deforestation across the models. One of the models that has multiple simulation members also reveals considerable spread of the precipitation responses to deforestation across the members due to internal model variability. This study highlights the necessity of robustly examining precipitation responses to deforestation based on multiple models and each model with multiple simulation members.

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Sarah M. Larson, Yuko Okumura, Katinka Bellomo, and Melissa L. Breeden

Abstract

Identifying the origins of wintertime climate variations in the Northern Hemisphere requires careful attribution of the role of El Niño–Southern Oscillation (ENSO). For example, Aleutian low variability arises from internal atmospheric dynamics and is remotely forced mainly via ENSO. How ENSO modifies the local sea surface temperature (SST) and North American precipitation responses to Aleutian low variability remains unclear, as teasing out the ENSO signal is difficult. This study utilizes carefully designed coupled model experiments to address this issue. In the absence of ENSO, a deeper Aleutian low drives a positive Pacific decadal oscillation (PDO)-like SST response. However, unlike the observed PDO pattern, a coherent zonal band of turbulent heat flux–driven warm SST anomalies develops throughout the subtropical North Pacific. Furthermore, non-ENSO Aleutian low variability is associated with a large-scale atmospheric circulation pattern confined over the North Pacific and North America and dry precipitation anomalies across the southeastern United States. When ENSO is included in the forcing of Aleutian low variability in the experiments, the ENSO teleconnection modulates the turbulent heat fluxes and damps the subtropical SST anomalies induced by non-ENSO Aleutian low variability. Inclusion of ENSO forcing results in wet precipitation anomalies across the southeastern United States, unlike when the Aleutian low is driven by non-ENSO sources. Hence, we find that the ENSO teleconnection acts to destructively interfere with the subtropical North Pacific SST and southeastern United States precipitation signals associated with non-ENSO Aleutian low variability.

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Jiabin Liu, Inez Y. Fung, and John C. H. Chiang

Abstract

Rainbands that migrate northward from spring to summer are persistent features of the East Asian summer monsoon. This study employs a machine learning algorithm to identify individual East Asian rainbands from May to August in the 6-hourly ERA-Interim reanalysis product and captures rainband events during these months for the period 1979–2018. The median duration of rainband events at any location in East Asia is 12 h, and the centroids of these rainbands move northward continuously from approximately 28°N in late May to approximately 33°N in July, instead of making jumps between quasi-stationary periods. Whereas the length and overall area of the rainbands grow monotonically from May to June, the intensity of the rainfall within the rainband dips slightly in early June before it peaks in late June. We find that extratropical northerly winds on all pressure levels over East China are the most important anomalous flow accompanying the rainband events. The anomalous northerlies augment climatological background northerlies in bringing low moist static energy air and thus generate the front associated with the rainband. Persistent lower-tropospheric southerly winds bring in moisture that feeds the rainband and are enhanced a few days prior to rainband events, but they are not directly tied to the actual rainband formation. The background northerlies could originate as part of the Rossby waves resulting from the jet stream interaction with the Tibetan Plateau. The ageostrophic circulation in the jet entrance region peaks in May and weakens in June and July and does not prove to be critical to the formation of the rainbands.

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Zhuolin Xuan, Wenjun Zhang, Feng Jiang, and Fei-Fei Jin

Abstract

Current climate models have relatively high skills in predicting El Niño–Southern Oscillation (ENSO) phase (i.e., El Niño, neutral, and La Niña), once leaping over the spring predictability barrier. However, it is still a big challenge to realistically forecast the ENSO amplitude, for instance, whether a predicted event will be strong, moderate, or weak. Here we demonstrate that the accumulated westerly wind events (WWEs)/easterly wind surges (EWSs) and oceanic recharged/discharged states are both of importance in accurate ENSO amplitude forecasts. El Niño and La Niña events exhibit asymmetric temporal and spatial features in the atmospheric and oceanic preconditions. El Niño amplitude at the peak season is closely associated with the accumulated WWEs over the eastern equatorial Pacific from the previous December to May and the recharged state in the western equatorial Pacific during February. In contrast, the amplitude of La Niña events is sensitive to the accumulated EWSs over the equatorial western Pacific from the previous November to April and the discharged state extending from the equatorial western to central Pacific during February. Considering these asymmetric atmospheric and oceanic preconditions of El Niño and La Niña cases, a statistical model is established to accurately forecast the ENSO amplitude at its mature phase during 1982–2018, which is validated to be robust based on a 1-yr cross-validation and independent sample tests. The feasibility and the limitation of the established statistical model are also discussed by examining its practical utility.

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Xian Wu, Yuko M. Okumura, Pedro N. DiNezio, Stephen G. Yeager, and Clara Deser

Abstract

The mean-state bias and the associated forecast errors of the El Niño–Southern Oscillation (ENSO) are investigated in a suite of 2-yr-lead retrospective forecasts conducted with the Community Earth System Model, version 1, for 1954–2015. The equatorial Pacific cold tongue in the forecasts is too strong and extends excessively westward due to a combination of the model’s inherent climatological bias, initialization imbalance, and errors in initial ocean data. The forecasts show a stronger cold tongue bias in the first year than that inherent to the model due to the imbalance between initial subsurface oceanic states and model dynamics. The cold tongue bias affects not only the pattern and amplitude but also the duration of ENSO in the forecasts by altering ocean–atmosphere feedbacks. The predicted sea surface temperature anomalies related to ENSO extend to the far western equatorial Pacific during boreal summer when the cold tongue bias is strong, and the predicted ENSO anomalies are too weak in the central-eastern equatorial Pacific. The forecast errors of pattern and amplitude subsequently lead to errors in ENSO phase transition by affecting the amplitude of the negative thermocline feedback in the equatorial Pacific and tropical interbasin adjustments during the mature phase of ENSO. These ENSO forecast errors further degrade the predictions of wintertime atmospheric teleconnections, land surface air temperature, and rainfall anomalies over the Northern Hemisphere. These mean-state and ENSO forecast biases are more pronounced in forecasts initialized in boreal spring–summer than other seasons due to the seasonal intensification of the Bjerknes feedback.

Open access
Haruki Hirasawa, Paul J. Kushner, Michael Sigmond, John Fyfe, and Clara Deser

Abstract

Sahel summertime precipitation declined from the 1950s to 1970s and recovered from the 1970s to 2000s. Anthropogenic aerosol contributions to this evolution are typically attributed to interhemispheric gradient changes of Atlantic Ocean sea surface temperature (SST). However recent work by Hirasawa et al. indicates a more complex picture, with the response being a combination of “fast” direct atmospheric (DA) processes and “slow” ocean-mediated (OM) processes. Here, we extend this understanding using the Community Atmosphere Model 5 to determine the role of regional ocean-basin perturbations and regional aerosol emission changes in the overall aerosol-driven OM and DA responses, respectively. From the 1950s to 1970s, there was an OM Sahel wetting response due to Pacific Ocean cooling that was offset by drying due to Atlantic cooling. By contrast, from the 1970s to 2000s, Atlantic trends reversed and amplified the Pacific cooling-induced wetting. This wetting was partially offset by drying driven by Indian Ocean cooling. Thus, the OM Sahel precipitation response to aerosol crucially depends on the balance of responses to Atlantic, Pacific, and Indian Ocean SST anomalies. From the 1950s to 1970s, there is DA Sahel drying that was principally due to North American aerosol emissions, with negligible effect from European emissions. DA drying from the 1970s to 2000s was mainly due to African aerosol emissions. Thus, the shifting roles of regional OM and DA effects reveal a complex interplay of direct driving and remote teleconnections in determining the time evolution of Sahel precipitation due to aerosol forcing in the late twentieth century.

Significance Statement

Studies of global climate models consistently indicate that anthropogenic aerosol emissions were a significant contributor to a severe drought that occurred in the Sahel region of Africa in the late twentieth century. The drying influence of aerosol forcing is the combined result of rapid atmospheric responses directly due to the forcing and slower responses due to forced ocean temperature changes. Using a set of simulations targeted at determining the influences from different ocean basins and different emission regions for two periods in the late twentieth century, we find there is a surprising range of mechanisms through which aerosol emissions affect the Sahel. This results in a complex interplay of at times competing and at times complementary regional influences.

Open access