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Bo Sun, Huijun Wang, Biwen Wu, Min Xu, Botao Zhou, Huixin Li, and Teng Wang

Abstract

This study investigates the first two leading modes of the interannual variability of frequency of snowfall events (FSE) over China in the winter during 1986–2018. The positive phase of the first leading mode (EOF1) is mainly characterized by positive FSE anomalies in northeastern–northwestern China and negative FSE anomalies in the three-river-source region. In contrast, the positive phase of the second leading mode (EOF2) is mainly characterized by positive FSE anomalies in central-eastern China (CEC). EOF1 is affected by the synoptic-scale wave activity over the midlatitudes of the East Asian continent, where active synoptic-scale wave activity over the midlatitudes may cause increased FSE over northeastern–northwestern China, and vice versa. In a winter of a negative phase of the North Atlantic Oscillation, an anomalous deep cold low may occur over Siberia, which may induce increased meridional air temperature gradient, increased atmospheric baroclinicity, and hence increased FSE over the midlatitudes of the East Asian continent. The EOF2 is affected by the interaction between anomalous northerly cold advection and anomalous southerly water vapor transport over CEC. The positive phase of EOF2 is associated with negative sea ice anomalies in the Barents Sea–Kara Sea region and negative sea surface temperature anomalies in the central-eastern tropical Pacific. Reduced sea ice in the Barents Sea–Kara Sea during January–February may cause increased northerly cold advection over CEC, while a La Niña–like condition during January may induce southerly water vapor transport anomalies over CEC.

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Zhe Feng, Fengfei Song, Koichi Sakaguchi, and L. Ruby Leung

Abstract

A process-oriented approach is developed to evaluate warm-season mesoscale convective system (MCS) precipitation and their favorable large-scale meteorological patterns (FLSMPs) over the United States. This approach features a novel observation-driven MCS-tracking algorithm using infrared brightness temperature and precipitation features at 12-, 25-, and 50-km resolution and metrics to evaluate the model large-scale environment favorable for MCS initiation. The tracking algorithm successfully reproduces the observed MCS statistics from a reference 4-km radar MCS database. To demonstrate the utility of the new methodologies in evaluating MCS in climate simulations with mesoscale resolution, the process-oriented approach is applied to two climate simulations produced by the Variable-Resolution Model for Prediction Across Scales coupled to the Community Atmosphere Model physics, with refined horizontal grid spacing at 50 and 25 km over North America. With the tracking algorithm applied to simulations and observations at equivalent resolutions, the simulated number of MCS and associated precipitation amount, frequency, and intensity are found to be consistently underestimated in the central United States, particularly from May to August. The simulated MCS precipitation shows little diurnal variation and lasts too long, while the MCS precipitation area is too large and its intensity is too weak. The model is able to simulate four types of observed FLSMP associated with frontal systems and low-level jets (LLJ) in spring, but the frequencies are underestimated because of low-level dry bias and weaker LLJ. Precipitation simulated under different FLSMPs peak during the daytime, in contrast to the observed nocturnal peak. Implications of these findings for future model development and diagnostics are discussed.

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Jesse Norris, Alex Hall, J. David Neelin, Chad W. Thackeray, and Di Chen

Abstract

Daily and subdaily precipitation extremes in historical phase 6 of the Coupled Model Intercomparison Project (CMIP6) simulations are evaluated against satellite-based observational estimates. Extremes are defined as the precipitation amount exceeded every x years, ranging from 0.01 to 10, encompassing the rarest events that are detectable in the observational record without noisy results. With increasing temporal resolution there is an increased discrepancy between models and observations: for daily extremes, the multimodel median underestimates the highest percentiles by about a third, and for 3-hourly extremes by about 75% in the tropics. The novelty of the current study is that, to understand the model spread, we evaluate the 3D structure of the atmosphere when extremes occur. In midlatitudes, where extremes are simulated predominantly explicitly, the intuitive relationship exists whereby higher-resolution models produce larger extremes (r = −0.49), via greater vertical velocity. In the tropics, the convective fraction (the fraction of precipitation simulated directly from the convective scheme) is more relevant. For models below 60% convective fraction, precipitation amount decreases with convective fraction (r = −0.63), but above 75% convective fraction, this relationship breaks down. In the lower-convective-fraction models, there is more moisture in the lower troposphere, closer to saturation. In the higher-convective-fraction models, there is deeper convection and higher cloud tops, which appears to be more physical. Thus, the low-convective models are mostly closer to the observations of extreme precipitation in the tropics, but likely for the wrong reasons. These intermodel differences in the environment in which extremes are simulated hold clues into how parameterizations could be modified in general circulation models to produce more credible twenty-first-century projections.

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Martin Hoerling, Lesley Smith, Xiao-Wei Quan, Jon Eischeid, Joseph Barsugli, and Henry F. Diaz

Abstract

Observed United States trends in the annual maximum 1-day precipitation (RX1day) over the last century consist of 15%–25% increases over the eastern United States (East) and 10% decreases over the far western United States (West). This heterogeneous trend pattern departs from comparatively uniform observed increases in precipitable water over the contiguous United States. Here we use an event attribution framework involving parallel sets of global atmospheric model experiments with and without climate change drivers to explain this spatially diverse pattern of extreme daily precipitation trends. We find that RX1day events in our model ensembles respond to observed historical climate change forcing differently across the United States with 5%–10% intensity increases over the East but no appreciable change over the West. This spatially diverse forced signal is broadly similar among three models used, and is positively correlated with the observed trend pattern. Our analysis of model and observations indicates the lack of appreciable RX1day signals over the West is likely due to dynamical effects of climate change forcing—via a wintertime atmospheric circulation anomaly that suppresses vertical motion over the West—largely cancelling thermodynamic effects of increased water vapor availability. The large magnitude of eastern U.S. RX1day increases is unlikely a symptom of a regional heightened sensitivity to climate change forcing. Instead, our ensemble simulations reveal considerable variability in RX1day trend magnitudes arising from internal atmospheric processes alone, and we argue that the remarkable observed increases over the East has most likely resulted from a superposition of strong internal variability with a moderate climate change signal. Implications for future changes in U.S. extreme daily precipitation are discussed.

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John Turner, Hua Lu, John King, Gareth J. Marshall, Tony Phillips, Dan Bannister, and Steve Colwell

Abstract

We present the first Antarctic-wide analysis of extreme near-surface air temperatures based on data collected up to the end of 2019 as part of the synoptic meteorological observing programs. We consider temperatures at 17 stations on the Antarctic continent and nearby sub-Antarctic islands. We examine the frequency distributions of temperatures and the highest and lowest individual temperatures observed. The variability and trends in the number of extreme temperatures were examined via the mean daily temperatures computed from the 0000, 0600, 1200, and 1800 UTC observations, with the thresholds for extreme warm and cold days taken as the 5th and 95th percentiles. The five stations examined from the Antarctic Peninsula region all experienced a statistically significant increase (p < 0.01) in the number of extreme high temperatures in the late-twentieth-century part of their records, although the number of extremes decreased in subsequent years. For the period after 1979 we investigate the synoptic background to the extreme events using ECMWF interim reanalysis (ERA-Interim) fields. The majority of record high temperatures were recorded after the passage of air masses over high orography, with the air being warmed by the foehn effect. At some stations in coastal East Antarctica the highest temperatures were recorded after air with a high potential temperature descended from the Antarctic plateau, resulting in an air mass 5°–7°C warmer than the maritime air. Record low temperatures at the Antarctic Peninsula stations were observed during winters with positive sea ice anomalies over the Bellingshausen and Weddell Seas.

Open access
Yu-Hsuan Lin, Hen-I Lin, Fang-I Wen, and Sheng-Jang Sheu

Abstract

A better understanding of farmers’ investment strategies associated with climate and weather is crucial to protecting farming and other climate-exposed sectors from extreme hydrometeorological events. Accordingly, this study employed a field experiment to investigate the investment decisions under risk and uncertainty by 213 farmers from four regions of Taiwan. Each was asked 30 questions that paired “no investment,” “investment with crop insurance,” “investment with subsidized crop insurance,” and “investment” as possible responses. By providing imperfect information and various probabilities of certain states occurring, the experimental scenarios mimicked various types of weather-forecasting services. As well as their socioeconomic characteristics, the background information we collected about the participants included their experiences of natural disasters and what actions they take to protect their crops from weather damage. The sampled farmers became more conservative in their decision-making as the weather forecasts they received became more precise, except when increases in risk were associated with high returns. The provision of insurance subsidies also had a conservatizing effect. However, considerable variation in investment preferences was observed according to the farmers’ crop types. For those seeking to create comprehensive policies aimed at helping the agricultural sector deal with the costs of damage from extreme events, this study has important implications. This approach could be extended to research on the perceptions of decision-makers in other climate-exposed sectors such as the construction industry.

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Saurabh Rathore, Nathaniel L. Bindoff, Caroline C. Ummenhofer, Helen E. Phillips, Ming Feng, and Mayank Mishra

Abstract

This study uses sea surface salinity (SSS) as an additional precursor for improving the prediction of summer [December–February (DJF)] rainfall over northeastern Australia. From a singular value decomposition between SSS of prior seasons and DJF rainfall, we note that SSS of the Indo-Pacific warm pool region [SSSP (150°E–165°W and 10°S–10°N) and SSSI (50°–95°E and 10°S–10°N)] covaries with Australian rainfall, particularly in the northeast region. Composite analysis that is based on high or low SSS events in the SSSP and SSSI regions is performed to understand the physical links between the SSS and the atmospheric moisture originating from the regions of anomalously high or low, respectively, SSS and precipitation over Australia. The composites show the signature of co-occurring La Niña and negative Indian Ocean dipole with anomalously wet conditions over Australia and conversely show the signature of co-occurring El Niño and positive Indian Ocean dipole with anomalously dry conditions there. During the high SSS events of the SSSP and SSSI regions, the convergence of incoming moisture flux results in anomalously wet conditions over Australia with a positive soil moisture anomaly. Conversely, during the low SSS events of the SSSP and SSSI regions, the divergence of incoming moisture flux results in anomalously dry conditions over Australia with a negative soil moisture anomaly. We show from the random-forest regression analysis that the local soil moisture, El Niño–Southern Oscillation (ENSO), and SSSP are the most important precursors for the northeast Australian rainfall whereas for the Brisbane region ENSO, SSSP, and the Indian Ocean dipole are the most important. The prediction of Australian rainfall using random-forest regression shows an improvement by including SSS from the prior season. This evidence suggests that sustained observations of SSS can improve the monitoring of the Australian regional hydrological cycle.

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Lei Zhang, Gang Wang, Matthew Newman, and Weiqing Han

Abstract

The Indian Ocean has received increasing attention for its large impacts on regional and global climate. However, sea surface temperature (SST) variability arising from Indian Ocean internal processes has not been well understood particularly on decadal and longer time scales, and the external influence from the tropical Pacific has not been quantified. This paper analyzes the interannual-to-decadal SST variability in the tropical Indian Ocean in observations and explores the external influence from the Pacific versus internal processes within the Indian Ocean using a linear inverse model (LIM). Coupling between Indian Ocean and tropical Pacific SST anomalies (SSTAs) is assessed both within the LIM dynamical operator and the unpredictable stochastic noise that forces the system. Results show that the observed Indian Ocean basin (IOB)-wide SSTA pattern is largely a response to the Pacific ENSO forcing, although it in turn has a damping effect on ENSO especially on annual and decadal time scales. On the other hand, the Indian Ocean dipole (IOD) is an Indian Ocean internal mode that can actively affect ENSO; ENSO also has a returning effect on the IOD, which is rather weak on decadal time scale. The third mode is partly associated with the subtropical Indian Ocean dipole (SIOD), and it is primarily generated by Indian Ocean internal processes, although a small component of it is coupled with ENSO. Overall, the amplitude of Indian Ocean internally generated SST variability is comparable to that forced by ENSO, and the Indian Ocean tends to actively influence the tropical Pacific. These results suggest that the Indian–Pacific Ocean interaction is a two-way process.

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Xiaofang Feng, Qinghua Ding, Liguang Wu, Charles Jones, Ian Baxter, Robert Tardif, Samantha Stevenson, Julien Emile-Geay, Jonathan Mitchell, Leila M. V. Carvalho, Huijun Wang, and Eric J. Steig

Abstract

In the past 40 years, the global annual mean surface temperature has experienced a nonuniform warming, differing from the spatially uniform warming simulated by the forced responses of large multimodel ensembles to anthropogenic forcing. Rather, it exhibits significant asymmetry between the Arctic and Antarctic, with intermittent and spatially varying warming trends along the Northern Hemisphere (NH) midlatitudes and a slight cooling in the tropical eastern Pacific. In particular, this “wavy” pattern of temperature changes over the NH midlatitudes features strong cooling over Eurasia in boreal winter. Here, we show that these nonuniform features of surface temperature changes are likely tied together by tropical eastern Pacific sea surface temperatures (SSTs), via a global atmospheric teleconnection. Using six reanalyses, we find that this teleconnection can be consistently obtained as a leading circulation mode in the past century. This tropically driven teleconnection is associated with a Pacific SST pattern resembling the interdecadal Pacific oscillation (IPO), and hereafter referred to as the IPO-related bipolar teleconnection (IPO-BT). Further, two paleo-reanalysis reconstruction datasets show that the IPO-BT is a robust recurrent mode over the past 400 and 2000 years. The IPO-BT mode may thus serve as an important internal mode that regulates high-latitude climate variability on multidecadal time scales, favoring a warming (cooling) episode in the Arctic accompanied by cooling (warming) over Eurasia and the Southern Ocean (SO). Thus, the spatial nonuniformity of recent surface temperature trends may be partially explained by the enhanced appearance of the IPO-BT mode by a transition of the IPO toward a cooling phase in the eastern Pacific in the past decades.

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Frauke Feser, Oliver Krueger, Katja Woth, and Linda van Garderen

Abstract

This study analyzes changes in extratropical windstorms over the North Atlantic during the last decades. We assessed and compared North Atlantic winter storm activity in a comprehensive approach from three different data sources: modern reanalysis datasets, a dynamically downscaled high-resolution global atmospheric climate simulation, and observations. The multidecadal observations comprise both a storm index derived from geostrophic wind speed triangles and an observational record of low pressure systems counted from weather analyses. Both observational datasets have been compared neither to the most recent reanalyses nor to the downscaled global climate simulation with respect to North Atlantic winter storms before. The similarity of the geostrophic wind speed storm index to reanalyzed high wind speed percentiles and storm numbers confirms its suitability to describe storm frequencies and intensities for multidecadal time scales. The results show that high wind speeds, storm numbers, and spatial storm track distributions are generally alike in high-resolution reanalyses and downscaled datasets and they reveal an increasing similarity to observations over time. Strong decadal and multidecadal variability emerged in high wind speed percentiles and storm frequency, but no long-term changes for the last decades were detected.

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