CMIP5 Historical Simulations Research Articles

Diurnal cycle of precipitation over global monsoon systems in CMIP6 simulations

Accurate simulation of the diurnal cycle of precipitation over different climate regimes, including global monsoon systems, is an ongoing challenge for current state-of-the-art climate models. In this study, the diurnal cycles of summertime precipitation from 21 CMIP6 historical simulations are evaluated with the NASA IMERG data via the diurnal harmonic amplitude and phase from the Fourier analysis in seven regional monsoon systems: Northern and Southern Africa monsoons, South Asia monsoon, East Asia monsoon, Australia monsoon, and North and South America monsoons. Particularly, we focus on four subregions including ocean, coastal ocean, land, and coastal land considering the different underlying physical processes. It is found that the CMIP6 historical simulations perform fairly well on reproducing the diurnal cycle of precipitation over ocean and coastal ocean, while the simulated diurnal harmonic phase and amplitude over land and coastal land show larger biases and model spread compared to biases over ocean and coastal ocean. The simulation of precipitation diurnal cycle is substantially improved in the multi-model mean of both CMIP6 historical and CMIP6 AMIP simulations compared with that of CMIP5 historical simulations. But the model bias of precipitation diurnal cycle is in general similar between CMIP6 AMIP and CMIP6 historical simulations, which suggests that the impact of the interactive ocean on the simulated diurnal precipitation averaged over a large domain is generally minor. The influence of model resolution on the diurnal cycle is shown in mixed directions across various subregions, and significant improvement from the low- to high-resolution models is only notable over coastal ocean.

Asymmetry variations in Arctic summer onset and ending: Role of sea-ice melting

Previous studies found that in Arctic regions with severe sea ice melting, summer ending (SE) variations are significantly larger than summer onset (SO) variations in the past few decades. Based on short-term observations, researchers preliminarily suggested that radiation variations caused by an earlier melting onset could be the possible reason for asymmetric Arctic SO/ending variations (AASV). Based on observations and National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis I dataset, here we quantitatively characterize AASV by calculating the difference between the 11 year sliding trend of Arctic SO and SE. The results show that AASV positively correlates with sea ice melting in summer. The increased summer sea ice melting increases the area to absorb short-wave radiation in summer and then release more long-wave radiation to heat the lower atmosphere and delay the peak time of long-wave radiation releasing. The variations in radiation lead to a significant delay of the Arctic SE, with no significant variations in SO. We introduce CMIP6 historical and future simulations of 15 models to verify further the relationship between AASV and summer sea ice melting. Historical run reproduces the observed asymmetry, and future simulations under various warming levels show that AASV will vanish with disappeared melting variations or be strengthened with increased melting. The latter could delay freeze-up and further exacerbate the following years’ melting, which will enhance AASV. Furthermore, AASV will delay the onset and peak time of Arctic amplification.

The Role of Anthropogenic Aerosol Forcing in the 1850–1985 Strengthening of the AMOC in CMIP6 Historical Simulations

Abstract Previous work has shown that anthropogenic aerosol (AA) forcing drives a strengthening in the Atlantic meridional overturning circulation (AMOC) in CMIP6 historical simulations over 1850–1985, but the mechanisms have not been fully understood. Across CMIP6 models, it is shown that there is a strong correlation between surface heat loss over the subpolar North Atlantic (SPNA) and the forced strengthening of the AMOC. Despite the link to AA forcing, the AMOC response is not strongly related to the contribution of anomalous downwelling surface shortwave radiation to SPNA heat loss. Rather, the spread in AMOC response is primarily due to the spread in turbulent heat loss. We hypothesize that turbulent heat loss is larger in models with strong AA forcing because the air advected over the ocean is colder and drier, in turn because of greater AA-forced cooling over the continents upwind, especially North America. The strengthening of the AMOC also feeds back on itself positively in two distinct ways: by raising the sea surface temperature and hence further increasing turbulent heat loss in the SPNA, and by increasing the sea surface density across the SPNA due to increased northward transport of saline water. A comparison of key indices suggests that the AMOC response in models with strong AA forcing is not likely to be consistent with observations.

Preliminary study on hydrological angular momentum determined from CMIP6 historical simulations

Polar motion (PM) is an essential parameter needed to transform coordinates between celestial and terrestrial reference frames, thus playing a crucial role in precise positioning and navigation. The role of hydrological signals in PM excitation is not yet fully understood, which is largely because of the lack of agreement between estimates of hydrological angular momentum (HAM) computed from different data sources. In this study, we used data obtained from the latest, sixth phase of the Coupled Model Intercomparison Project (CMIP6) to assess the impact of the continental hydrosphere on PM excitation. To do so, we exploited soil moisture and snow water variables obtained from historical simulations of CMIP6 to estimate climate-based HAM. The HAM series were computed, then we analysed their variability in terms of trends, seasonal and non-seasonal oscillations. An important part of this study is the validation of HAM estimates based on comparison with the hydrological signal in geodetically observed PM excitation (geodetic residuals, GAO). In addition, HAM series based on climate models were compared with those determined from global gravimetric data provided by the Gravity Recovery and Climate Experiment (GRACE) mission, and from the Land Surface Discharge Model (LSDM). This study also aimed to identify the most appropriate CMIP6 models for interpretation of PM variations. Overall, the correspondence between GAO and HAM received from CMIP6 was lower than the previously obtained consistency with GRACE results, and the level of agreement was dependent on the oscillation considered and the model used. However, it may be possible to identify several CMIP6 models from among the almost 100 available that provides a HAM series more compatible with GAO than HAM from GRACE or LSDM, especially in annual oscillations. The GISS-E2-1-G_historical_r10i1p1f1 model was found to provide the highest consistency with GAO for annual prograde amplitudes, GFDL-CM4_historical_r1i1p1f1 for annual retrograde amplitudes, BCC-ESM1_historical_r3i1p1f1 for the annual prograde phase, and MIROC-ES2L_historical_r2i1p1f2 for the annual retrograde phase. Because of their length, the CMIP6 data allow for analysis of the past and future changes in HAM from 1850 to 2100, which is of particular importance in the exploration of the impact of climate change on PM excitation.Graphical

CMIP6 model simulation of concurrent continental warming holes in Eurasia and North America since 1990 and their relation to the Indo-Pacific SST warming

Observations during 1990–2014 depict concurrent cooling trends in land surface air temperature (LSAT) over central-eastern Eurasia (CEE) and northwestern North America (NWNA), while significant warming trends are observed in other areas across the Northern Hemisphere (NH). This lack of surface warming of the continental CEE and NWNA is termed continental warming holes (CWH) here. The ability of the 6th phase of the Coupled Model Intercomparison Project (CMIP6) to reproduce the LSAT trends during 1990–2014 over the continental NH is evaluated, and the evaluation includes all CMIP6 historical simulations from 32 unique models and their multi-model ensemble mean (MMEM). The results show that the performances of the different models vary greatly. GISS-E2–1-G-CC model performs best among the 32 models, considering reproducing the correct sign of the LSAT trends as well as reproducing the trend magnitude. However, the MMEM simulates uniformly significant warming trends in NH and fails to capture the continental warming holes, indicating a role of internal variability in the CWH. The mechanisms of the continental warming holes are further investigated using reanalysis datasets, CMIP6 models and AGCM simulations. GISS-E2–1-G-CC also shows a better simulation ability, including the trends in NH sea level pressure and tropical sea surface temperature than other models. Both reanalysis data and GISS-E2–1-G-CC model show high-pressure trends over mid-high latitudes, which corresponded to enhanced Siberia High and weakened Aleutian Low. These atmospheric circulation changes result in cold advection over the CEE and NWNA regions, offsetting anthropogenic warming and leading to the emergence of the warming holes. Further analysis and AGCM simulations link these atmospheric circulation trends to Indo-Pacific SST warming. In response to the Indo-Pacific SST warming, tropical tropospheric warming leads to the equatorward shift of the mid-latitude jet stream, and subsequently, anomalous easterly and high pressure over mid-high latitudes tend to influence the Siberia High and Aleutian low, resulting in the LSAT cooling over the CEE and NWNA.

Atmospheric rivers in CMIP5 climate ensembles downscaled with a high-resolution regional climate model

Abstract. Atmospheric rivers (ARs) are important drivers of hazardous precipitation levels and are often associated with intense floods. So far, the response of ARs to climate change in Europe has been investigated using global climate models within the CMIP5 framework. However, the spatial resolution of those models (1–3∘) is too coarse for an adequate assessment of local to regional precipitation patterns. Using a regional climate model with 0.22∘ resolution, we downscaled an ensemble consisting of 1 ERA-Interim (ERAI) reanalysis data hindcast simulation, 9 global historical, and 24 climate scenario simulations following greenhouse gas emission scenarios RCP2.6, RCP4.5, and RCP8.5. The performance of the climate model to simulate AR frequencies and AR-induced precipitation was tested against ERAI. Overall, we find a good agreement between the downscaled CMIP5 historical simulations and ERAI. However, the downscaled simulations better represented small-scale spatial characteristics. This was most evident over the terrain of the Iberian Peninsula, where the AR-induced precipitation pattern clearly reflected prominent east–west topographical elements, resulting in zonal bands of high and low AR impact. Over central Europe, the models simulated a smaller propagation distance of ARs toward eastern Europe than obtained using the ERAI data. Our models showed that ARs in a future warmer climate will be more frequent and more intense, especially in the higher-emission scenarios (RCP4.5, RCP8.5). However, assuming low emissions (RCP2.6), the related changes can be mostly mitigated. According to the high-emission scenario RCP8.5, AR-induced precipitation will increase by 20 %–40 % in western central Europe, whereas mean precipitation rates increase by a maximum of only 12 %. Over the Iberian Peninsula, AR-induced precipitation will slightly decrease (∼6 %) but the decrease in the mean rate will be larger (∼15 %). These changes will lead to an overall increased fractional contribution of ARs to heavy precipitation, with the greatest impact over the Iberian Peninsula (15 %–30 %) and western France (∼15 %). Likewise, the fractional share of yearly maximum precipitation attributable to ARs will increase over the Iberian Peninsula, the UK, and western France. Over Norway, average AR precipitation rates will decline by −5 % to −30 %, most likely due to dynamic changes, with ARs originating from latitudes > 60∘ N decreasing by up to 20 % and those originating south of 45∘ N increasing. This suggests that ARs over Norway will follow longer routes over the continent, such that additional moisture uptake will be impeded. By contrast, ARs from >60∘ N will take up moisture from the North Atlantic before making landfall over Norway. The found changes in the local AR pathway are probably driven by larger-scale circulation changes such as a change in dominating weather regimes and/or changes in the winter storm track over the North Atlantic.

The July 2019 European Heat Wave in a Warmer Climate: Storyline Scenarios with a Coupled Model Using Spectral Nudging

Abstract Extreme weather events are triggered by atmospheric circulation patterns and shaped by slower components, including soil moisture and sea surface temperature, and by the background climate. This separation of factors is exploited by the storyline approach in which an atmospheric model is nudged toward the observed dynamics using different climate boundary conditions to explore their influence. The storyline approach disregards uncertain climatic changes in the frequency and intensity of dynamical conditions, focusing instead on the thermodynamic influence of climate on extreme events. Here we demonstrate an advanced storyline approach that employs a coupled climate model (AWI-CM-1-1-MR) in which the large-scale free-troposphere dynamics are nudged toward ERA5 data. Five-member ensembles are run for present-day (2017–19), preindustrial, +2-K, and +4-K climates branching off from CMIP6 historical and scenario simulations of the same model. In contrast to previous studies, which employed atmosphere-only models, feedbacks between extreme events and the ocean and sea ice state, and the dependence of such feedbacks on the climate, are consistently simulated. Our setup is capable of reproducing observed anomalies of relevant unconstrained parameters, including near-surface temperature, cloud cover, soil moisture, sea surface temperature, and sea ice concentration. Focusing on the July 2019 European heat wave, we find that the strongest warming amplification expands from southern to central Europe over the course of the twenty-first century. The warming reaches up to 10 K in the 4-K-warmer climate, suggesting that an analogous event would entail peak temperatures around 50°C in central Europe. Significance Statement This work explores a new storyline method to determine the impact of climate change on specific recent extreme events. The observed evolution of the large-scale atmospheric circulation is imposed in a coupled climate model. Variations in climate parameters, including ocean temperatures and sea ice, are well reproduced. By varying the background climate, including CO2 concentrations, it is demonstrated how the July 2019 European heat wave could have evolved in preindustrial times and in warmer climates. For example, up to 10°C warmer peak temperatures could occur in central Europe in a 4°C warmer climate. The method should be explored for other types of extreme events and has the potential to make climate change more tangible and to inform adaptation measures.

Probabilistic Evaluation of Drought in CMIP6 Simulations.

As droughts have widespread social and ecological impacts, it is critical to develop long‐term adaptation and mitigation strategies to reduce drought vulnerability. Climate models are important in quantifying drought changes. Here, we assess the ability of 285 CMIP6 historical simulations, from 17 models, to reproduce drought duration and severity in three observational data sets using the Standardized Precipitation Index (SPI). We used summary statistics beyond the mean and standard deviation, and devised a novel probabilistic framework, based on the Hellinger distance, to quantify the difference between observed and simulated drought characteristics. Results show that many simulations have less than ±10% error in reproducing the observed drought summary statistics. The hypothesis that simulations and observations are described by the same distribution cannot be rejected for more than 80% of the grids based on our H distance framework. No single model stood out as demonstrating consistently better performance over large regions of the globe. The variance in drought statistics among the simulations is higher in the tropics compared to other latitudinal zones. Though the models capture the characteristics of dry spells well, there is considerable bias in low precipitation values. Good model performance in terms of SPI does not imply good performance in simulating low precipitation. Our study emphasizes the need to probabilistically evaluate climate model simulations in order to both pinpoint model weaknesses and identify a subset of best‐performing models that are useful for impact assessments.

Removing the Effects of Tropical Dynamics from North Pacific Climate Variability

AbstractTeleconnections from the Tropics energize variations of the North Pacific climate, but detailed diagnosis of this relationship has proven difficult. Simple univariate methods, such as regression on El Niño-Southern Oscillation (ENSO) indices, may be inadequate since the key dynamical processes involved -- including ENSO diversity in the Tropics, re-emergence of mixed layer thermal anomalies, and oceanic Rossby wave propagation in the North Pacific -- have a variety of overlapping spatial and temporal scales. Here we use a multivariate Linear Inverse Model to quantify tropical and extra-tropical multi-scale dynamical contributions to North Pacific variability, in both observations and CMIP6 models. In observations, we find that the Tropics are responsible for almost half of the seasonal variance, and almost three quarters of the decadal variance, along the North American coast and within the subtropical front region northwest of Hawaii. SST anomalies that are generated by local dynamics within the Northeast Pacific have much shorter time scales, consistent with transient weather forcing by Aleutian low anomalies. Variability within the Kuroshio-Oyashio Extension (KOE) region is considerably less impacted by the Tropics, on all time scales. Consequently, without tropical forcing the dominant pattern of North Pacific variability would be a KOE pattern, rather than the Pacific Decadal Oscillation (PDO). In contrast to observations, most CMIP6 historical simulations produce North Pacific variability that maximizes in the KOE region, with amplitude significantly higher than observed. Correspondingly, the simulated North Pacific in all CMIP6 models is shown to be relatively insensitive to the Tropics, with a dominant spatial pattern generally resembling the KOE pattern, not the PDO.

A Spatial Evaluation of Arctic Sea Ice and Regional Limitations in CMIP6 Historical Simulations

AbstractThe Arctic sea ice response to a warming climate is assessed in a subset of models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6), using several metrics in comparison with satellite observations and results from the Pan-Arctic Ice Ocean Modeling and Assimilation System and the Regional Arctic System Model. Our study examines the historical representation of sea ice extent, volume, and thickness using spatial analysis metrics, such as the integrated ice edge error, Brier score, and spatial probability score. We find that the CMIP6 multimodel mean captures the mean annual cycle and 1979–2014 sea ice trends remarkably well. However, individual models experience a wide range of uncertainty in the spatial distribution of sea ice when compared against satellite measurements and reanalysis data. Our metrics expose common and individual regional model biases, which sea ice temporal analyses alone do not capture. We identify large ice edge and ice thickness errors in Arctic subregions, implying possible model specific limitations in or lack of representation of some key physical processes. We postulate that many of them could be related to the oceanic forcing, especially in the marginal and shelf seas, where seasonal sea ice changes are not adequately simulated. We therefore conclude that an individual model’s ability to represent the observed/reanalysis spatial distribution still remains a challenge. We propose the spatial analysis metrics as useful tools to diagnose model limitations, narrow down possible processes affecting them, and guide future model improvements critical to the representation and projections of Arctic climate change.

Evaluating the physical and biogeochemical state of the global ocean component of UKESM1 in CMIP6 historical simulations

Abstract. The ocean plays a key role in modulating the climate of the Earth system (ES). At the present time it is also a major sink both for the carbon dioxide (CO2) released by human activities and for the excess heat driven by the resulting atmospheric greenhouse effect. Understanding the ocean's role in these processes is critical for model projections of future change and its potential impacts on human societies. A necessary first step in assessing the credibility of such future projections is an evaluation of their performance against the present state of the ocean. Here we use a range of observational fields to validate the physical and biogeochemical performance of the ocean component of UKESM1, a new Earth system model (ESM) for CMIP6 built upon the HadGEM3-GC3.1 physical climate model. Analysis focuses on the realism of the ocean's physical state and circulation, its key elemental cycles, and its marine productivity. UKESM1 generally performs well across a broad spectrum of properties, but it exhibits a number of notable biases. Physically, these include a global warm bias inherited from model spin-up, excess northern sea ice but insufficient southern sea ice and sluggish interior circulation. Biogeochemical biases found include shallow remineralization of sinking organic matter, excessive iron stress in regions such as the equatorial Pacific, and generally lower surface alkalinity that results in decreased surface and interior dissolved inorganic carbon (DIC) concentrations. The mechanisms driving these biases are explored to identify consequences for the behaviour of UKESM1 under future climate change scenarios and avenues for model improvement. Finally, across key biogeochemical properties, UKESM1 improves in performance relative to its CMIP5 precursor and performs well alongside its fellow members of the CMIP6 ensemble.

First assessment of the earth heat inventory within CMIP5 historical simulations

Abstract. The energy imbalance at the top of the atmosphere over the last century has caused an accumulation of heat within the ocean, the continental subsurface, the atmosphere and the cryosphere. Although ∼90 % of the energy gained by the climate system has been stored in the ocean, the other components of the Earth heat inventory cannot be neglected due to their influence on associated climate processes dependent on heat storage, such as sea level rise and permafrost stability. However, there has not been a comprehensive assessment of the heat inventory within global climate simulations yet. Here, we explore the ability of 30 advanced general circulation models (GCMs) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) to simulate the distribution of heat within the Earth's energy reservoirs for the period 1972–2005 of the Common Era. CMIP5 GCMs simulate an average heat storage of 247±172 ZJ (96±4 % of total heat content) in the ocean, 5±9 ZJ (2±3 %) in the continental subsurface, 2±3 ZJ (1±1 %) in the cryosphere and 2±2 ZJ (1±1 %) in the atmosphere. However, the CMIP5 ensemble overestimates the ocean heat content by 83 ZJ and underestimates the continental heat storage by 9 ZJ and the cryosphere heat content by 5 ZJ, in comparison with recent observations. The representation of terrestrial ice masses and the continental subsurface, as well as the response of each model to the external forcing, should be improved in order to obtain better representations of the Earth heat inventory and the partition of heat among climate subsystems in global transient climate simulations.

Comparison of CMIP6 historical climate simulations and future projected warming to an empirical model of global climate

Abstract. The sixth phase of the Coupled Model Intercomparison Project (CMIP6) is the latest modeling effort for general circulation models to simulate and project various aspects of climate change. Many of the general circulation models (GCMs) participating in CMIP6 provide archived output that can be used to calculate effective climate sensitivity (ECS) and forecast future temperature change based on emissions scenarios from several Shared Socioeconomic Pathways (SSPs). Here we use our multiple linear regression energy balance model, the Empirical Model of Global Climate (EM-GC), to simulate and project changes in global mean surface temperature (GMST), calculate ECS, and compare to results from the CMIP6 multi-model ensemble. An important aspect of our study is a comprehensive analysis of uncertainties due to radiative forcing of climate from tropospheric aerosols (AER RF) in the EM-GC framework. We quantify the attributable anthropogenic warming rate (AAWR) from the climate record using the EM-GC and use AAWR as a metric to determine how well CMIP6 GCMs replicate human-driven global warming over the last 40 years. The CMIP6 multi-model ensemble indicates a median value of AAWR over 1975–2014 of 0.221 ∘C per decade (range of 0.151 to 0.299 ∘C per decade; all ranges given here are for 5th and 95th confidence intervals), which is notably faster warming than our median estimate for AAWR of 0.157 ∘C per decade (range of 0.120 to 0.195 ∘C per decade) inferred from the analysis of the Hadley Centre Climatic Research Unit version 5 data record for GMST. Estimates of ECS found using the EM-GC assuming that climate feedback does not vary over time (best estimate 2.33 ∘C; range of 1.40 to 3.57 ∘C) are generally consistent with the range of ECS of 1.5 to 4.5 ∘C given by the IPCC's Fifth Assessment Report. The CMIP6 multi-model ensemble exhibits considerably larger values of ECS (median 3.74 ∘C; range of 2.19 to 5.65 ∘C). Our best estimate of ECS increases to 3.08 ∘C (range of 2.23 to 5.53 ∘C) if we allow climate feedback to vary over time. The dominant factor in the uncertainty for our empirical determinations of AAWR and ECS is imprecise knowledge of AER RF for the contemporary atmosphere, though the uncertainty due to time-dependent climate feedback is also important for estimates of ECS. We calculate the likelihood of achieving the Paris Agreement target (1.5 ∘C) and upper limit (2.0 ∘C) of global warming relative to pre-industrial for seven of the SSPs using both the EM-GC and the CMIP6 multi-model ensemble. In our model framework, SSP1-2.6 has a 53 % probability of limiting warming at or below the Paris target by the end of the century, and SSP4-3.4 has a 64 % probability of achieving the Paris upper limit. These estimates are based on the assumptions that climate feedback has been and will remain constant over time since the prior temperature record can be fit so well assuming constant climate feedback. In addition, we quantify the sensitivity of future warming to the curbing of the current rapid growth of atmospheric methane and show that major near-term limits on the future growth of methane are especially important for achievement of the 1.5 ∘C goal of future warming. We also quantify warming scenarios assuming climate feedback will rise over time, a feature common among many CMIP6 GCMs; under this assumption, it becomes more difficult to achieve any specific warming target. Finally, we assess warming projections in terms of future anthropogenic emissions of atmospheric carbon. In our model framework, humans can emit only another 150±79 Gt C after 2019 to have a 66 % likelihood of limiting warming to 1.5 ∘C and another 400±104 Gt C to have the same probability of limiting warming to 2.0 ∘C. Given the estimated emission of 11.7 Gt C per year for 2019 due to combustion of fossil fuels and deforestation, our EM-GC simulations suggest that the 1.5 ∘C warming target of the Paris Agreement will not be achieved unless carbon and methane emissions are severely curtailed in the next 10 years.

Observed and Projected Frontal Activities in East Asia

AbstractAn objective front detection method is applied to ERA5, CMIP5 historical, and RCP8.5 simulations to evaluate climate model performance in simulating front frequency and to understand future projections of seasonal front activities. The study area is East Asia for two natural seasons, defined as winter (2 December–14 February) and spring (15 February–15 May), in accordance with regional circulation and precipitation patterns. Seasonal means of atmospheric circulation and thermal structures are analyzed to understand possible factors responsible for future front changes. The front location and frequency in CMIP5 historical simulations are captured reasonably. Frontal precipitation accounts for more than 30% of total precipitation over subtropical regions. Projections suggest that winter fronts will decrease over East Asia, especially over southern China. Frontal precipitation is projected to decrease for 10%–30%. Front frequency increases in the South China Sea and tropical western Pacific because of more tropical moisture supply, which enhances local moisture contrasts. During spring, southern China and Taiwan will experience fewer fronts and less frontal precipitation while central China, the Korean Peninsula, and Japan may experience more fronts and more frontal precipitation due to moisture flux from the south that enhances wet-bulb potential temperature θw gradients. Consensus among CMIP5 models in front frequency tendency is evaluated. The models exhibit relatively high consensus in the decreasing trend over polar and subtropical frontal zone in winter and over southern China and Taiwan in spring that may prolong the dry season. Spring front activities are crucial for water resource and risk management in the southern China and Taiwan.

The Relationship between Precipitation and Precipitable Water in CMIP6 Simulations and Implications for Tropical Climatology and Change

AbstractIt is well documented that over the tropical oceans, column-integrated precipitable water (pw) and precipitation (P) have a nonlinear relationship. In this study moisture budget analysis is used to examine this P–pw relationship in a normalized precipitable water framework. It is shown that the parameters of the nonlinear relationship depend on the vertical structure of moisture convergence. Specifically, the precipitable water values at which precipitation is balanced independently by evaporation versus by moisture convergence define a critical normalized precipitable water, pwnc. This is a measure of convective inhibition that separates tropical precipitation into two regimes: a local evaporation-controlled regime with widespread drizzle and a precipitable water–controlled regime. Most of the 17 CMIP6 historical simulations examined here have higher pwnc compared to ERA5, and more frequently they operate in the drizzle regime. When compared to observations, they overestimate precipitation over the high-evaporation oceanic regions off the equator, thereby producing a “double ITCZ” feature, while underestimating precipitation over the large tropical landmasses and over the climatologically moist oceanic regions near the equator. The responses to warming under the SSP585 scenario are also examined using the normalized precipitable water framework. It is shown that the critical normalized precipitable water value at which evaporation versus moisture convergence balance precipitation decreases as a result of the competing dynamic and thermodynamic responses to warming, resulting in an increase in drizzle and total precipitation. Statistically significant historical trends corresponding to the thermodynamic and dynamic changes are detected in ERA5 and in low-intensity drizzle precipitation in the PERSIANN precipitation dataset.

The Thermocline Biases in the Tropical North Pacific and Their Attributions

AbstractThe tropical thermocline plays an important role in regulating equatorial sea surface temperature (SST); at present, it is still poorly simulated in the state-of-the-art climate models. In this paper, thermocline biases in the tropical North Pacific are investigated using the newly released CMIP6 historical simulations. It is found that CMIP6 models tend to produce an overly shallow thermocline in the northwestern tropics, accompanied by a deep thermocline in the northeastern tropics. A pronounced thermocline strength bias arises in the tropical northeastern Pacific, demonstrating a dipole structure with a sign change at about 8°N. These thermocline biases are accompanied with biases in the simulations of oceanic circulations, including a too weak North Equatorial Countercurrent (NECC), a reduction in water exchanges between the subtropics and the equatorial regions, and an eastward extension of the equatorward interior water transport. The causes of these thermocline biases are further analyzed. The thermocline bias is primarily caused by the model deficiency in simulating the surface wind stress curl, which can be further attributed to the longstanding double-ITCZ bias in the tropical North Pacific. Besides, thermocline strength bias can be partly attributed to the poor prescription of oceanic background diffusivity. By constraining the diffusivity to match observations, the thermocline strength in the tropical northeastern Pacific is greatly increased.

An evaluation of CMIP6 historical simulations of the cold season teleconnection between tropical Indo-Pacific sea surface temperatures and precipitation in Southwest Asia, the coastal Middle East, and Northern Pakistan and India

AbstractThe ability of six CMIP6 models to reproduce the observed cold season teleconnection between tropical Indo-Pacific sea surface temperatures (SSTs) and precipitation in Southwest Asia, the coastal Middle East (CME), and Northern Pakistan and India (NPI) is examined. The 1979-2014 period is analyzed, to maximize observations over both the tropical ocean and the regions. Nine historical simulations for the same period are examined for each model, to account for the internal variability of the coupled system. The teleconnection is examined in terms of SSTs, precipitation, 200 hPa geopotential heights, and derived quantities.All the models capture some of the broadest features of the teleconnections, but there is a wide range in the ability of the models to reproduce the magnitude and details. The differences appear related to both the models’ ability to capture the details of the tropical variability, including the position and strength of the precipitation anomalies in the Indo-west Pacific, as well as the models’ ability to accurately propagate the tropically-forced response into the region. The teleconnections to the CME and NPI regions on the eastern and western margins, respectively, of the strongest signal are very similar in structure and have similar results, except that the models’ ability to reproduce the strength and details of the teleconnection is even more limited, consistent with their marginal locations and known influence of other modes of variability. For all three areas, the wide range in model ability to capture the leading teleconnection suggests caution in interpreting climate regional projections.

Overview of the Norwegian Earth System Model (NorESM2) and key climate response of CMIP6 DECK, historical, and scenario simulations.

Overview of the Norwegian Earth System Model (NorESM2) and key climate response of CMIP6 DECK, historical, and scenario simulations.

Description and evaluation of aerosol in UKESM1 and HadGEM3-GC3.1 CMIP6 historical simulations

Abstract. We document and evaluate the aerosol schemes as implemented in the physical and Earth system models, the Global Coupled 3.1 configuration of the Hadley Centre Global Environment Model version 3 (HadGEM3-GC3.1) and the United Kingdom Earth System Model (UKESM1), which are contributing to the sixth Coupled Model Intercomparison Project (CMIP6). The simulation of aerosols in the present-day period of the historical ensemble of these models is evaluated against a range of observations. Updates to the aerosol microphysics scheme are documented as well as differences in the aerosol representation between the physical and Earth system configurations. The additional Earth system interactions included in UKESM1 lead to differences in the emissions of natural aerosol sources such as dimethyl sulfide, mineral dust and organic aerosol and subsequent evolution of these species in the model. UKESM1 also includes a stratospheric–tropospheric chemistry scheme which is fully coupled to the aerosol scheme, while GC3.1 employs a simplified aerosol chemistry mechanism driven by prescribed monthly climatologies of the relevant oxidants. Overall, the simulated speciated aerosol mass concentrations compare reasonably well with observations. Both models capture the negative trend in sulfate aerosol concentrations over Europe and the eastern United States of America (US) although the models tend to underestimate sulfate concentrations in both regions. Interactive emissions of biogenic volatile organic compounds in UKESM1 lead to an improved agreement of organic aerosol over the US. Simulated dust burdens are similar in both models despite a 2-fold difference in dust emissions. Aerosol optical depth is biased low in dust source and outflow regions but performs well in other regions compared to a number of satellite and ground-based retrievals of aerosol optical depth. Simulated aerosol number concentrations are generally within a factor of 2 of the observations, with both models tending to overestimate number concentrations over remote ocean regions, apart from at high latitudes, and underestimate over Northern Hemisphere continents. Finally, a new primary marine organic aerosol source is implemented in UKESM1 for the first time. The impact of this new aerosol source is evaluated. Over the pristine Southern Ocean, it is found to improve the seasonal cycle of organic aerosol mass and cloud droplet number concentrations relative to GC3.1 although underestimations in cloud droplet number concentrations remain. This paper provides a useful characterisation of the aerosol climatology in both models and will facilitate understanding in the numerous aerosol–climate interaction studies that will be conducted as part of CMIP6 and beyond.

Overview of the Norwegian Earth System Model (NorESM2) and key climate response of CMIP6 DECK, historical, and scenario simulations

Abstract. The second version of the coupled Norwegian Earth System Model (NorESM2) is presented and evaluated. NorESM2 is based on the second version of the Community Earth System Model (CESM2) and shares with CESM2 the computer code infrastructure and many Earth system model components. However, NorESM2 employs entirely different ocean and ocean biogeochemistry models. The atmosphere component of NorESM2 (CAM-Nor) includes a different module for aerosol physics and chemistry, including interactions with cloud and radiation; additionally, CAM-Nor includes improvements in the formulation of local dry and moist energy conservation, in local and global angular momentum conservation, and in the computations for deep convection and air–sea fluxes. The surface components of NorESM2 have minor changes in the albedo calculations and to land and sea-ice models. We present results from simulations with NorESM2 that were carried out for the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Two versions of the model are used: one with lower (∼ 2∘) atmosphere–land resolution and one with medium (∼ 1∘) atmosphere–land resolution. The stability of the pre-industrial climate and the sensitivity of the model to abrupt and gradual quadrupling of CO2 are assessed, along with the ability of the model to simulate the historical climate under the CMIP6 forcings. Compared to observations and reanalyses, NorESM2 represents an improvement over previous versions of NorESM in most aspects. NorESM2 appears less sensitive to greenhouse gas forcing than its predecessors, with an estimated equilibrium climate sensitivity of 2.5 K in both resolutions on a 150-year time frame; however, this estimate increases with the time window and the climate sensitivity at equilibration is much higher. We also consider the model response to future scenarios as defined by selected Shared Socioeconomic Pathways (SSPs) from the Scenario Model Intercomparison Project defined under CMIP6. Under the four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), the warming in the period 2090–2099 compared to 1850–1879 reaches 1.3, 2.2, 3.0, and 3.9 K in NorESM2-LM, and 1.3, 2.1, 3.1, and 3.9 K in NorESM-MM, robustly similar in both resolutions. NorESM2-LM shows a rather satisfactory evolution of recent sea-ice area. In NorESM2-LM, an ice-free Arctic Ocean is only avoided in the SSP1-2.6 scenario.