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Zili Shen, Anmin Duan, Dongliang Li, and Jinxiao Li

Abstract

The capability of 36 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) and their 24 CMIP5 counterparts in simulating the mean state and variability of Arctic sea ice cover for the period 1979–2014 is evaluated. In addition, a sea ice cover performance score for each CMIP5 and CMIP6 model is provided that can be used to reduce the spread in sea ice projections through applying weighted averages based on the ability of models to reproduce the historical sea ice state. Results show that the seasonal cycle of the Arctic sea ice extent (SIE) in the multimodel ensemble (MME) mean of the CMIP6 simulations agrees well with observations, with a MME mean error of less than 15% in any given month relative to the observations. CMIP6 has a smaller intermodel spread in climatological SIE values during summer months than its CMIP5 counterpart. In terms of the monthly SIE trends, the CMIP6 MME mean shows a substantial reduction in the positive bias relative to the observations compared with that of CMIP5. The spread of September SIE trends is very large, not only across different models but also across different ensemble members of the same model, indicating a strong influence of internal variability on SIE evolution. Based on the assumptions that the simulations of CMIP6 models are from the same distribution and that models have no bias in response to external forcing, we can infer that internal variability contributes to approximately 22% ± 5% of the September SIE trend over the period 1979–2014.

Open access
David M. Mocko, Sujay V. Kumar, Christa D. Peters-Lidard, and Shugong Wang

Abstract

This study presents an evaluation of the impact of vegetation conditions on a land surface model (LSM) simulation of agricultural drought. The Noah-MP LSM is used to simulate water and energy fluxes and states, which are transformed into drought categories using percentiles over the continental United States from 1979 to 2017. Leaf area index (LAI) observations are assimilated into the dynamic vegetation scheme of Noah-MP. A weekly operational drought monitor (the U.S. Drought Monitor) is used for the evaluation. The results show that LAI assimilation into Noah-MP’s dynamic vegetation scheme improves the model’s ability to represent drought, particularly over cropland areas. LAI assimilation improves the simulation of the drought category, detection of drought conditions, and reduces the instances of drought false alarms. The assimilation of LAI in these locations not only corrects model errors in the simulation of vegetation, but also can help to represent unmodeled physical processes such as irrigation toward improved simulation of agricultural drought.

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John T. Allen, Edwina R. Allen, Harald Richter, and Chiara Lepore

Abstract

During 2013, multiple tornadoes occurred across Australia, leading to 147 injuries and considerable damage. This prompted speculation as to the frequency of these events in Australia, and whether 2013 constituted a record year. Leveraging media reports, public accounts, and the Bureau of Meteorology observational record, 69 tornadoes were identified for the year in comparison to the official count of 37 events. This identified set and the existing historical record were used to establish that, in terms of spatial distribution, 2013 was not abnormal relative to the existing climatology, but numerically exceeded any year in the bureau’s record. Evaluation of the environments in which these tornadoes formed illustrated that these conditions included tornado environments found elsewhere globally, but generally had a stronger dependence on shear magnitude than direction, and lower lifting condensation levels. Relative to local environment climatology, 2013 was also not anomalous. These results illustrate a range of tornadoes associated with cool season, tropical cyclone, east coast low, supercell tornado, and low shear/storm merger environments. Using this baseline, the spatial climatology from 1980 to 2019 as derived from the nonconditional frequency of favorable significant tornado parameter environments for the year is used to highlight that observations are likely an underestimation. Applying the results, discussion is made of the need to expand observing practices, climatology, forecasting guidelines for operational prediction, and improve the warning system. This highlights a need to ensure that the general public is appropriately informed of the tornado hazard in Australia, and provide them with the understanding to respond accordingly.

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Chao Li, Francis Zwiers, Xuebin Zhang, Guilong Li, Ying Sun, and Michael Wehner

Abstract

This study presents an analysis of daily temperature and precipitation extremes with return periods ranging from 2 to 50 years in phase 6 of the Coupled Model Intercomparison Project (CMIP6) multimodel ensemble of simulations. Judged by similarity with reanalyses, the new-generation models simulate the present-day temperature and precipitation extremes reasonably well. In line with previous CMIP simulations, the new simulations continue to project a large-scale picture of more frequent and more intense hot temperature extremes and precipitation extremes and vanishing cold extremes under continued global warming. Changes in temperature extremes outpace changes in global annual mean surface air temperature (GSAT) over most landmasses, while changes in precipitation extremes follow changes in GSAT globally at roughly the Clausius–Clapeyron rate of ~7% °C−1. Changes in temperature and precipitation extremes normalized with respect to GSAT do not depend strongly on the choice of forcing scenario or model climate sensitivity, and do not vary strongly over time, but with notable regional variations. Over the majority of land regions, the projected intensity increases and relative frequency increases tend to be larger for more extreme hot temperature and precipitation events than for weaker events. To obtain robust estimates of these changes at local scales, large initial-condition ensemble simulations are needed. Appropriate spatial pooling of data from neighboring grid cells within individual simulations can, to some extent, reduce the needed ensemble size.

Open access
Adam Vaccaro, Julien Emile-Geay, Dominque Guillot, Resherle Verna, Colin Morice, John Kennedy, and Bala Rajaratnam

Abstract

Surface temperature is a vital metric of Earth’s climate state but is incompletely observed in both space and time: over half of monthly values are missing from the widely used HadCRUT4.6 global surface temperature dataset. Here we apply the graphical expectation–maximization algorithm (GraphEM), a recently developed imputation method, to construct a spatially complete estimate of HadCRUT4.6 temperatures. GraphEM leverages Gaussian Markov random fields (also known as Gaussian graphical models) to better estimate covariance relationships within a climate field, detecting anisotropic features such as land–ocean contrasts, orography, ocean currents, and wave-propagation pathways. This detection leads to improved estimates of missing values compared to methods (such as kriging) that assume isotropic covariance relationships, as we show with real and synthetic data. This interpolated analysis of HadCRUT4.6 data is available as a 100-member ensemble, propagating information about sampling variability available from the original HadCRUT4.6 dataset. A comparison of Niño-3.4 and global mean monthly temperature series with published datasets reveals similarities and differences due in part to the spatial interpolation method. Notably, the GraphEM-completed HadCRUT4.6 global temperature displays a stronger early twenty-first-century warming trend than its uninterpolated counterpart, consistent with recent analyses using other datasets. Known events like the 1877/78 El Niño are recovered with greater fidelity than with kriging, and result in different assessments of changes in ENSO variability through time. Gaussian Markov random fields provide a more geophysically motivated way to impute missing values in climate fields, and the associated graph provides a powerful tool to analyze the structure of teleconnection patterns. We close with a discussion of wider applications of Markov random fields in climate science.

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Ju Liang, Jennifer L. Catto, Matthew Hawcroft, Kevin I. Hodges, Mou Leong Tan, and James M. Haywood

Abstract

Borneo vortices (BVs) are intense precipitating winter storms that develop over the equatorial South China Sea and strongly affect the weather and climate over the western Maritime Continent because of their association with deep convection and heavy rainfall. In this study, the ability of the Hadley Centre Global Environment Model 3–Global Coupled, version 3.1 (HadGEM3-GC3.1), global climate model to simulate the climatology of BVs at different horizontal resolutions is examined using an objective feature-tracking algorithm. The HadGEM3-GC3.1 at the N512 (25 km) horizontal resolution simulates BVs with well-represented characteristics, including their frequency, spatial distribution, and lower-tropospheric structures when compared with BVs identified in a climate reanalysis, whereas the BVs in the N96 (~135 km) and N216 (~65 km) simulations are much weaker and less frequent. Also, the N512 simulation better captures the contribution of BVs to the winter precipitation in Borneo and the Malay Peninsula when compared with precipitation from a reanalysis data and from observations, whereas the N96 and N216 simulations underestimate this contribution because of the overly weak low-level convergence of the simulated BVs. The N512 simulation also exhibits an improved ability to reproduce the modulation of BV activity by the occurrence of northeasterly cold surges and active phases of the Madden–Julian oscillation in the region, including increased BV track densities, intensities, and lifetimes. A sufficiently high model resolution is thus found to be important to realistically simulate the present-climate precipitation extremes associated with BVs and to study their possible changes in a warmer climate.

Open access
Marvin A. Geller, Peter T. Love, and Ling Wang

Abstract

The 1-s-resolution U.S. radiosonde data are analyzed for unstable layers, where the potential temperature decreases with increasing altitude, in the troposphere and lower stratosphere (LS). Care is taken to exclude spurious unstable layers arising from noise in the soundings and also to allow for the destabilizing influence of water vapor in saturated layers. Riverton, Wyoming, and Greensboro, North Carolina, in the extratropics, are analyzed in detail, where it is found that the annual and diurnal variations are largest, and the interannual variations are smallest in the LS. More unstable layer occurrences in the LS at Riverton are found at 0000 UTC, while at Greensboro, more unstable layer occurrences in the LS are at 1200 UTC, consistent with a geographical pattern where greater unstable layer occurrences in the LS are at 0000 UTC in the western United States, while greater unstable layer occurrences are at 1200 UTC in the eastern United States. The picture at Koror, Palau, in the tropics is different in that the diurnal and interannual variations in unstable layer occurrences in the LS are largest, with much smaller annual variations. At Koror, more frequent unstable layer occurrences in the LS occur at 0000 UTC. Also, a “notch” in the frequencies of occurrence of thin unstable layers at about 12 km is observed at Koror, with large frequencies of occurrence of thick layers at that altitude. Histograms are produced for the two midlatitude stations and one tropical station analyzed. The log–log slopes for troposphere histograms are in reasonable agreement with earlier results, but the LS histograms show a steeper log–log slope, consistent with more thin unstable layers and fewer thick unstable layers there. Some radiosonde stations are excluded from this analysis since a marked change in unstable layer occurrences was identified when a change in radiosonde instrumentation occurred.

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Xinyu Li, Riyu Lu, and Joong-Bae Ahn

Abstract

The summer British–Baikal Corridor pattern (BBC) and the Silk Road pattern (SRP) manifest as zonally oriented teleconnections in the high and middle latitudes, respectively, of the Eurasian continent. In this study, we investigate the combined effects of the BBC and SRP on surface air temperatures over the Eurasian continent. It is found that the combination of the BBC and SRP results in two kinds of well-organized, large-scale circulation anomalies: the zonal tripole pattern and the Ω-like pattern in the 200-hPa geopotential height anomalies. The zonal tripole pattern is characterized by opposite variations between western Siberia/western Asia and Europe/central Asia/central Siberia, and the Ω-like pattern manifests as consistent variations over midlatitude Europe, western Siberia, and central Asia. Correspondingly, the resultant large-scale surface air temperature anomalies feature the same zonal tripole pattern and Ω-like pattern, respectively. Further results indicate that these two patterns resemble the two leading modes of surface air temperature anomalies over the middle to high latitudes of Eurasia. This study indicates that the temperature variations in the middle and high latitudes of Eurasia can be coordinated and evidently explained by the combination of the BBC and SRP, and it contributes to a more comprehensive understanding of the large-scale Eurasian climate variability.

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Goodwin Gibbins and Joanna D. Haigh

Abstract

A recent paper by Kato and Rose reports a negative correlation between the annual mean entropy production rate of the climate and the absorption of solar radiation in the CERES SYN1deg dataset, using the simplifying assumption that the system is steady in time. It is shown here, however, that when the nonsteady interannual storage of entropy is accounted for, the dataset instead implies a positive correlation; that is, global entropy production rates increase with solar absorption. Furthermore, this increase is consistent with the response demonstrated by an energy balance model and a radiative–convective model. To motivate this updated analysis, a detailed discussion of the conceptual relationship between entropy production, entropy storage, and entropy flows is provided. The storage-corrected estimate for the mean global rate of entropy production in the CERES dataset from all irreversible transfer processes is 81.9 mW m−2 K−1 and from only nonradiative processes is 55.2 mW m−2 K−1 (observations from March 2000 to February 2018).

Open access
Johannes Mayer, Michael Mayer, and Leopold Haimberger

Abstract

This study uses advanced numerical and diagnostic methods to evaluate the atmospheric energy budget with the fifth major global reanalysis produced by ECMWF (ERA5) in combination with observed and reconstructed top of the atmosphere (TOA) energy fluxes for the period 1985–2018. We assess the meridional as well as ocean–land energy transport and perform internal consistency checks using mass-balanced data. Furthermore, the moisture and mass budgets in ERA5 are examined and compared with previous budget evaluations using ERA-Interim as well as observation-based estimates. Results show that peak annual mean meridional atmospheric energy transports in ERA5 (4.58 ± 0.07 PW in the Northern Hemisphere) are weaker compared to ERA-Interim (4.74 ± 0.09 PW), where the higher spatial and temporal resolution of ERA5 can be excluded as a possible reason. The ocean–land energy transport in ERA5 is reliable at least from 2000 onward (~2.5 PW) such that the imbalance between net TOA fluxes and lateral energy fluxes over land are on the order of ~1 W m−2. Spinup and spindown effects as revealed from inconsistencies between analyses and forecasts are generally smaller and temporally less variable in ERA5 compared to ERA-Interim. Evaluation of the moisture budget shows that the ocean–land moisture transport and parameterized freshwater fluxes agree well in ERA5, while there are large inconsistencies in ERA-Interim. Overall, the quality of the budgets derived from ERA5 is demonstrably better than estimates from ERA-Interim. Still some particularly sensitive budget quantities (e.g., precipitation, evaporation, and ocean–land energy transport) show apparent inhomogeneities, especially in the late 1990s, which warrant further investigation and need to be considered in studies of interannual variability and trends.

Open access