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José M. Castanheira and Carlos A. F. Marques

Abstract

Two ensembles of Atmospheric Model Intercomparison Project (AMIP) simulations, in the scope of the current Coupled Model Intercomparison Project (CMIP6), are compared with their fully coupled counterparts. The atmospheric models simulate less barotropic atmospheric circulation variability over the North Atlantic and more barotropic atmospheric circulation variability over the North Pacific when compared with reanalysis variability, at intraseasonal and interannual scales. The coupled climate simulations have smaller global barotropic variability than the corresponding AMIP simulations. The smaller variability of the coupled simulations results in no mean overestimation of the subtropical jet variability in the North Pacific, but further underestimation of the jet stream variability in the North Atlantic. The results suggest that the reduction of the biases, in the North Pacific barotropic atmospheric variability, of coupled climate simulations is achieved through compensating biases in the mean sea surface temperatures (SSTs). Moreover, the reduction of the positive biases in the North Pacific seems to be associated with a reduction of the excitation of the most unstable barotropic mode of the atmospheric circulation, which contributes also to a reduction of the barotropic atmospheric variability in the North Atlantic.

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Ping Liu, Kevin A. Reed, Stephen T. Garner, Ming Zhao, and Yuejian Zhu

Abstract

The frequency of atmospheric blocking has been largely underestimated by general circulation models (GCMs) participating in the Coupled Model Intercomparison Project (CMIP). Errors in the onset, persistence, barotropicity, geographical preference, seasonality, intensity, and moving speed of global blocking were diagnosed in 10 Geophysical Fluid Dynamics Laboratory (GFDL) GCMs for recent CMIP5 and CMIP6 using a detection approach that combines zonal eddies and the reversal of zonal winds. The blocking frequency, similar at 500 and 250 hPa, is underestimated by 50% in the Atlantic–Europe region during December–February but is overestimated by 60% in the Pacific–North America region during that season and by 70% in the southwest Pacific during July–August. These blocking biases at 500 hPa were investigated in the five CMIP6 models that showed improvements over the CMIP5 versions. The Atlantic–Europe underestimate corresponds to lower instantaneous blocking rates, lower persistent blocking rates, and higher persistent stationary ridge rates; the number of blocks with a duration of 4–5 days is only 40%–65% of that in observations. In contrast, the overestimate consists of excessive blocks with a duration longer than 12 days in the Pacific–North America and up to twice as many 4–6-day events in the southwest Pacific. Simulated December–February blocks up to 12 days in the Pacific–North America region tend to be stronger and to move more slowly than those in observations. Diagnostic sensitivity tests indicated that the zonal mean and zonal eddy components of the mean state play a key role, as replacing each with that of observations substantially reduced many of the outstanding biases in these GCMs.

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Jinlin Zha, Cheng Shen, Deming Zhao, Jinming Feng, Zhongfeng Xu, Jian Wu, Wenxuan Fan, Meng Luo, and Liya Zhang

Abstract

Summer mean (June, July, and August) surface air temperature (SSAT) in East Asia during the period from 1958 to 2001 has shown a warming. However, the relative contributions of external forcing (EF) and internal climate variability (ICV) to the SSAT changes over East Asia remain unclear. In this study, a new approach is applied to estimate the changes in the SSAT determined by the effects of EF and ICV over East Asia during the period from 1958 to 2001. Reanalysis data as well as simulated results from both global atmosphere–ocean coupled model outputs and a regional climate model (RCM) are used for this approach. The observed SSATs over East Asia have undergone a decreasing trend from 1958 to 1972 (−0.14°C decade−1, p < 0.01) and an increasing trend after 1972 (0.24°C decade−1, p < 0.01). While these features are not captured by the reanalysis studied here, they are reproduced when the reanalysis output is downscaled using an RCM. The effects of the EF and the ICV on the SSAT can be separated based on the RCM downscaling simulation. The results show that the SSAT with EF displayed significant warming over most regions of East Asia, whereas the SSAT with ICV mainly exhibited cooling over East Asia. Furthermore, EF mainly influenced the decadal changes of the SSAT, whereas the ICV mainly influenced the interannual changes in the SSAT over East Asia. The interannual changes of the SSAT over East Asia that were influenced by the ICV are mainly manifested as the combined effects of the large-scale ocean–atmosphere circulations, which expressed 79% explanatory power on the SSAT changes.

Open access
Tan Phan-Van, Phuong Nguyen-Ngoc-Bich, Thanh Ngo-Duc, Tue Vu-Minh, Phong V. V. Le, Long Trinh-Tuan, Tuyet Nguyen-Thi, Ha Pham-Thanh, and Duc Tran-Quang

Abstract

In this study, the spatiotemporal variability of drought over the entire Southeast Asia (SEA) region and its associations with the large-scale climate drivers during the period 1960–2019 are investigated for the first time. The 12-month Standardized Precipitation Evapotranspiration Index (SPEI) was computed based on the monthly Global Precipitation Climatology Centre (GPCC) precipitation and the monthly Climate Research Unit (CRU) 2-m temperature. The relationships between drought and large-scale climate drivers were examined using the principal component analysis (PCA) and maximum covariance analysis (MCA) techniques. Results showed that the spatiotemporal variability of drought characteristics over SEA is significantly different between mainland Indochina and the Maritime Continent and the difference has been increased substantially in recent decades. Moreover, the entire SEA is divided into four homogeneous drought subregions. Drought over SEA is strongly associated with oceanic and atmospheric large-scale drivers, particularly El Niño–Southern Oscillation (ENSO), following by other remote factors such as the variability of sea surface temperature (SST) over the tropical Atlantic, the Pacific decadal oscillation (PDO), and the Indian Ocean dipole mode (IOD). In addition, there exists an SST anomaly dipole over the Pacific Ocean, which modulates the atmospheric circulations and consequently precipitation over SEA, affecting drought conditions in the study region.

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Jilong Chen, Chi Yung Tam, Ziqian Wang, Kevin Cheung, Ying Li, Ngar-Cheung Lau, and Dick-Shum Dickson Lau

Abstract

Possible thermodynamic effects of global warming on the landfalling typhoons that affect South China and their associated storm surges over Pearl River Delta region are investigated, using the Weather Research and Forecasting (WRF) Model and the Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model based on the pseudo–global warming (PGW) technique. Twenty intense historical TCs that brought extreme storm surges to Hong Kong since the 1960s are selected and replicated by the 3-km WRF Model, with the outputs to drive the SLOSH model in storm surge simulation. The tracks, intensities, storm structure, and induced storm surges are well simulated. The PGW technique is then used to build a warmer background climate for the 20 selected TCs in the period of 2075–99 under the RCP8.5 scenario. To obtain a better adjusted warming environment, a pre-PGW adjustment method is developed. Comparing the same TCs in PGW experiments and historical runs, the TC lifetime peak (landfall) intensity can be intensified by about 9% ± 8% (12% ± 13%), with a ∼3% increase of TC peak intensity per degree of SST warming being inferred. The TCs are projected to be more compact, with the radius of maximum wind (RMW) reduced by ∼7% ± 10%. TC precipitation is also expected to increase, with the extreme precipitation within the eyewall strengthened by 22% ± 12%. All the above characters have passed the Student’s t test at 0.05 significance level. Finally, the projected induced storm surges near the Hong Kong waters are not significantly tested, although a weak storm surge height increase tendency is revealed.

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Xiaofan Li, Zeng-Zhen Hu, Zhiqiang Gong, and Bhaskar Jha

Abstract

Climate predictability at seasonal to interannual time scales is mainly associated with sea surface temperature anomalies (SSTAs). How to quantitatively assess the impact of SSTAs on climate variability and predictability is an unresolved topic. Using a novel metric [bulk connectivity (BC)], the integrated influences of global SSTAs on precipitation anomalies over land are examined in observations and compared with Atmospheric Model Intercomparison Project (AMIP) simulations in 1957–2018. The hotspots of the land precipitation variation affected by global SSTA are identified, and the seasonality is evaluated. Such hotspots indicate the regions of land precipitation predictability caused by SSTAs. The hotspots are observed in the Sahel region in September–March, in the Indochina Peninsula in April and May, and in southwestern United States in December–March, which are mostly linked to the influence of El Niño–Southern Oscillation (ENSO). The overall impact of SSTAs on land precipitation is larger in the Southern Hemisphere than in the Northern Hemisphere. The spatial variations of BC and hotspots in the observations are partially reproduced in the AMIP simulations. However, an individual run in the AMIP simulations underestimates the integrated influence of global SSTA on land precipitation anomalies, while the ensemble mean amplifies the integrated influence, and both show a challenge in capturing the seasonality of the SST influence, particularly the time of the strongest impact. The results of the BC metric can serve as a benchmark to evaluate climate models and to identify the predictability sources.

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Louis Clément, E. L. McDonagh, J. M. Gregory, Q. Wu, A. Marzocchi, J. D. Zika, and A. J. G. Nurser

Abstract

Warming of the climate system accumulates mostly in the ocean and discrepancies in how this is modeled contribute to uncertainties in predicting sea level rise. In this study, regional temperature changes in an atmosphere–ocean general circulation model (HadCM3) are partitioned between excess (due to perturbed surface heat fluxes) and redistributed (arising from changing circulation and perturbations to mixing) components. In simulations with historical forcing, we first compare this excess–redistribution partitioning with the spice and heave decomposition, in which temperature anomalies enter the ocean interior either along isopycnals (spice) or across isopycnals (heave, without affecting the temperature–salinity curve). Second, heat and salinity budgets projected into thermohaline space naturally reveal the mechanisms behind temperature change by spice and heave linked with water mass generation or destruction. Excess warming enters the ocean as warming by heave in subtropical gyres whereas it mainly projects onto warming by spice in the Southern Ocean and the tropical Atlantic. In subtropical gyres, Ekman pumping generates excess warming as confirmed by Eulerian heat budgets. In contrast, isopycnal mixing partly drives warming and salinification by spice, as confirmed by budgets in thermohaline space, underlying the key role of salinity changes for the ocean warming signature. Our study suggests a method to detect excess warming using spice and heave calculated from observed repeat profiles of temperature and salinity.

Open access
Casey J. Wall, Trude Storelvmo, Joel R. Norris, and Ivy Tan

Abstract

Shortwave radiative feedbacks from Southern Ocean clouds are a major source of uncertainty in climate projections. Much of this uncertainty arises from changes in cloud scattering properties and lifetimes that are caused by changes in cloud thermodynamic phase. Here we use satellite observations to infer the scattering component of the cloud-phase feedback mechanism and determine its relative importance by comparing it with an estimate of the overall temperature-driven cloud feedback. The overall feedback is dominated by an optical thinning of low-level clouds. In contrast, the scattering component of cloud-phase feedback is an order of magnitude smaller and is primarily confined to free-tropospheric clouds. The small magnitude of this feedback component is a consequence of counteracting changes in albedo from cloud optical thickening and enhanced forward scattering by cloud particles. These results indicate that shortwave cloud feedback is likely positive over the Southern Ocean and that changes in cloud scattering properties arising from phase changes make a small contribution to the overall feedback. The feedback constraints shift the projected 66% confidence range for the global equilibrium temperature response to doubling atmospheric CO2 by about +0.1 K relative to a recent consensus estimate of cloud feedback.

Significance Statement

Understanding how clouds respond to global warming is a key challenge of climate science. One particularly uncertain aspect of the cloud response involves a conversion of ice particles to liquid droplets in extratropical clouds. Here we use satellite data to infer how cloud-phase conversions affect climate by changing cloud albedo. We find that ice-to-liquid conversions increase cloud optical thickness and shift the scattering angles of cloud particles toward the forward direction. These changes in optical properties have offsetting effects on cloud albedo. This finding provides new insight about how changes in cloud phase affect climate change.

Open access
Partha Roy and T. Narayana Rao

Abstract

The relative contributions of cyclonic disturbances (CDs; i.e., low pressure systems, depressions, and cyclonic storms) and non-CDs to annual and seasonal rainfall are studied using 22 years of TRMM and GPM measurements during the passage of 866 CDs in the South Asia region (SAR). The changes in stratiform and convective precipitation within the cyclonic storm and in different CDs are also examined. The rainfall in the wettest regions of the SAR, the west coasts of India and Myanmar, and the slopes of the Himalayas is of non-CD origin, while CD rainfall peaks in the eastern parts of the monsoon trough and the northern Bay of Bengal (BOB). The CD rain fraction (RF) of annual and seasonal rainfall exhibits large spatial variation in the range of 4%–55%. The land–ocean dichotomy exhibited by CD RF is not uniform across India. Large CD RF is confined to the coast in some regions due to topographical barriers, but extends to 800–1000 km inland from the coast in the monsoon trough region. Low pressure systems contribute more to annual rain than depressions and cyclonic storms in the monsoon trough and the northern BOB (∼40%), particularly during the monsoon, mainly due to their frequent occurrence. The stratiform RF and occurrence are higher in CDs than in non-CDs, with the greatest contribution in central India (>80%), whereas the non-CDs are characterized by having higher convective RFs. The stratiform rain occurrence increases with intensification of CDs over both land and ocean, indicating its importance in the intensification of CDs and organizing large-scale systems.

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Mason O. Stahl and Kaighin A. McColl

Abstract

The seasonal cycle contributes substantially to soil moisture temporal variability in many parts of the world, with important implications for seasonal forecasting relevant to agriculture and the health of humans and ecosystems. There is considerable spatial variability in the seasonal cycle of soil moisture, yet a lack of global observations has hindered the development of parsimonious theories explaining that variability. Here, we use 6 years of global satellite observations to describe and explain the seasonal cycle of surface soil moisture globally. An unsupervised clustering algorithm is used to identify five distinct seasonal cycle regimes. Each seasonal cycle regime typically arises in both hemispheres, on multiple continents, and across substantially different local climates. To explain this spatial variability, we then show that the observed seasonal cycle regimes are reproduced very well by a simple but physically based water balance model, which only uses precipitation and downwelling surface shortwave radiation as inputs, and includes no free parameters. Surprisingly, no information on vegetation or land cover is required. To our knowledge, this is the first characterization of the seasonal cycle of surface soil moisture based on global observations.

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