Atmospheric Model Simulations Research Articles

Technical note: Exploring parameter and meteorological uncertainty via emulation in volcanic ash atmospheric dispersion modelling

Abstract. ​​​​​​​Consideration of uncertainty in volcanic ash cloud forecasts is increasingly of interest, with an industry goal to provide probabilistic forecasts alongside deterministic forecasts. Simulations of volcanic clouds via dispersion modelling are subject to a number of uncertainties relating to the eruption itself (mass of ash emitted and when), parameterisations of physical processes, and the meteorological conditions. To fully explore these uncertainties through atmospheric dispersion model simulations alone may be expensive, and instead, an emulator can be used to increase understanding of uncertainties in the model inputs and outputs, going beyond combinations of source, physical, and meteorological inputs that were simulated by the dispersion model. We emulate the NAME (Numerical Atmospheric-dispersion Modelling Environment) dispersion model for simulations of the Raikoke 2019 eruption and use these emulators to compare simulated ash clouds to observations derived from satellites, constraining NAME source and internal parameters via history matching. We demonstrate that the effect of varying both meteorological scenarios and model parameters can be captured in this way with accurate emulation and using only a small number of runs per meteorological scenario. We show that accounting for meteorological uncertainty simultaneously with other uncertainties may lead to the identification of different sensitive model parameters and may lead to less constrained source and internal NAME parameters; however, through idealised experiments, we argue that this is a reasonable result and is properly accounting for all sources of uncertainty in the model inputs.

Open boundary conditions for atmospheric large-eddy simulations and their implementation in DALES4.4

Abstract. Open boundary conditions were developed for atmospheric large-eddy simulation (LES) models and implemented into the Dutch Atmospheric Large-Eddy Simulation model. The implementation was tested in a “Big Brother”-like setup, in which the simulation with open boundary conditions was forced by an identical control simulation with periodic boundary conditions. The results show that the open boundary implementation has minimal influence on the solution. Both the mean state and the turbulent structures are close to the control simulation, and disturbances at the in- and outflow boundaries are negligible. To emulate a setup in which the LES is coupled to a coarser model, the influence of coarse boundary input was tested by smoothing the output of the periodic control simulation both temporally and spatially before feeding it as input to the simulation with open boundary conditions. When smoothing is applied over larger spatial and longer temporal scales, disturbances start to form at the inflow boundary and an area exists where turbulence needs to develop. Adding synthetic turbulence to the smoothed input reduces the size of this area and the magnitude of the disturbances.

A New GFSv15 With FV3 Dynamical Core Based Climate Model Large Ensemble and Its Application to Understanding Climate Variability, and Predictability

AbstractNOAA Climate Prediction Center (CPC) has generated a 100‐member ensemble of atmospheric model simulations from 1979 to present using the Global Forecast System version 15 (GFSv15) with FV3 dynamical core. The intent of this study is to document a development in an infrastructure capability with a focus to demonstrate the quality of these new simulations is on par with the previous GFSv2 Atmospheric Model Intercomparison Project simulations. These simulations are part of CPC's efforts to attribute observed seasonal climate variability to sea surface temperature (SST) forcings and get updated once a month by available observed SST. The performance of these simulations in replicating observed climate variability and trends, together with an assessment of climate predictability and the attribution of some climate events is documented. A particular focus of the analysis is on the US climate trend, Northern Hemisphere winter height variability, US climate response to three strong El Niño events, the analysis of signal to noise ratio, the anomaly correlation for seasonal climate anomalies, and the South Asian flooding of 2022 summer, and thereby samples wide aspects that are important for attributing climate variability. Results indicate that the new model can realistically reproduce observed climate variability, trends, and extreme events, better capturing the US climate response to extreme El Niño events and the 2022 summer South Asian record‐breaking flooding than GFSv2. The new model also shows an improvement in the wintertime simulation fidelity of US surface climate, mainly confined in the Northern and Southeastern US for precipitation and in the east for temperature.

Early 20th century Southern Hemisphere cooling

Abstract. Global surface air temperature increased by ca. 0.5 °C from the 1900s to the mid-1940s, also known as Early 20th Century Warming (ETCW). However, the ETCW started from a particularly cold phase, peaking in 1908–1911. The cold phase was global but more pronounced in the Southern Hemisphere than in the Northern Hemisphere and most pronounced in the Southern Ocean, raising the question of whether uncertainties in the data might play a role. Here we analyse this period based on reanalysis data and reconstructions, complemented with newly digitised ship data from 1903–1916, as well as land observations. The cooling is seen consistently in different data sets, though with some differences. Results suggest that the cooling was related to a La-Niña-like pattern in the Pacific, a cold tropical and subtropical South Atlantic, a cold extratropical South Pacific, and cool southern midlatitude land areas. The Southern Annular Mode was positive, with a strengthened Amundsen–Bellingshausen seas low, although the spread of the data products is considerable. All results point to a real climatic phenomenon as the cause of this anomaly and not a data artefact. Atmospheric model simulations are able to reproduce temperature and pressure patterns, consistent with a real and perhaps ocean-forced signal. Together with two volcanic eruptions just before and after the 1908–1911 period, the early 1900s provided a cold start into the ETCW.

Future changes in the wintertime ENSO-NAO teleconnection under greenhouse warming

El Niño-Southern Oscillation (ENSO) teleconnection to the Euro-Atlantic exhibits strong subseasonal variations, as the North Atlantic Oscillation (NAO) response systematically reverses its phase from early to late winter. Based on two sets of atmospheric model simulations in CMIP6 forced by historical and projected SST, we report a future disappearance of this teleconnection reversal, with the positive early winter ENSO-NAO correlation turning negative and the negative late winter correlation becoming stronger. We suggest that this negative NAO tendency is associated with the strengthening and eastward shift of the ENSO atmospheric teleconnection towards the Euro-Atlantic due to parallel changes in the ENSO tropical convection. While the early winter NAO phase transition is further facilitated by the mean state change in the North Atlantic jet meridional shear, which shifts the ENSO-driven Rossby wave-propagating direction, an intensified stratospheric pathway is demonstrated to play an additional role in strengthening the late winter NAO response.

The 2023 extreme coastal El Niño: Atmospheric and air-sea coupling mechanisms.

In the boreal spring of 2023, an extreme coastal El Niño struck the coastal regions of Peru and Ecuador, causing devastating rainfalls, flooding, and record dengue outbreaks. Observations and ocean model experiments reveal that northerly alongshore winds and westerly wind anomalies in the eastern equatorial Pacific, initially associated with a record-strong Madden-Julian Oscillation and cyclonic disturbance off Peru in March, drove the coastal warming through suppressed coastal upwelling and downwelling Kelvin waves. Atmospheric model simulations indicate that the coastal warming in turn favors the observed wind anomalies over the far eastern tropical Pacific by triggering atmospheric deep convection. This implies a positive feedback between the coastal warming and the winds, which further amplifies the coastal warming. In May, the seasonal background cooling precludes deep convection and the coastal Bjerknes feedback, leading to the weakening of the coastal El Niño. This coastal El Niño is rare but predictable at 1 month lead, which is useful to protect lives and properties.

A Global Assessment of Heatwaves Since 1850 in Different Observational and Model Data Sets

AbstractWe show that ModE‐Sim, a global ensemble of atmospheric model simulations that uses observed ocean boundary conditions and radiative forcings providing 36 members with daily climate information can be used to in‐depth analyze the known spatial and temporal variability of heatwaves in the Northern Hemisphere and Australia during the past 160 years. It can also be used to study actual past extreme events like heatwaves during the El Nino 1877/1878. To analyze past heatwaves we use a novel approach of a transient baseline climatology and compare to different observational data sets. Furthermore, we analyze sea surface temperature anomalies during the most extreme heatwave summers in North America, Europe and Australia and identify the most prominent anomaly patterns over the Subpolar North Atlantic and in the Central Pacific. Using a large ensemble of forced simulations, like ModE‐Sim can consequently contribute to a better understanding of preindustrial heatwaves, their decadal variability and their driving mechanisms.

The Projected Poleward Shift of Tropical Cyclogenesis at a Global Scale Under Climate Change in MRI‐AGCM3.2H

AbstractFuture climate projections suggest a poleward shift of the maximum intensity of tropical cyclones (TCs) over the western North Pacific. However, the global nature of the latitudinal change in TC genesis under global warming remains poorly understood. We show, using large‐ensemble high‐resolution atmospheric model simulations (d4PDF) with four warming scenarios, that the poleward shift is a robust change over the globe, attributable to the weakening of the Hadley circulation. The weakened ascent driven by the upper‐tropospheric warming suppresses the TC genesis within 5°–20° latitudes, whereas the weakened descent enhances the TC genesis in the poleward latitudes. We further estimate the poleward shift of TC genesis to emerge at the 2 K global warming over the Arabian Sea, South Atlantic and Pacific Oceans and at the 4 K warming over the North Pacific. The present results underscore the potential for increasing social and economic risks associated with TCs at higher latitudes.

Delayed Onset of Indian Summer Monsoon in Response to CO2 Removal

AbstractUnderstanding the response of the Indian summer monsoon (ISM) onset to CO2 forcing is of utmost importance for rain‐fed agriculture and water management. In this study, we utilized an idealized symmetric CO2 removal scenario from the sixth phase of the Coupled Model Intercomparison Project to analyze the reversibility of monsoon onset. The results show that ISM onset is reversible but exhibits strong asymmetry: it undergoes minimal changes during the ramp‐up phase, but experiences rapid postponement as the CO2 begins to decline; Eventually, it is delayed more than 1 week when the CO2 concentration is restored to the initial level. To investigate the possible underlying mechanisms, we decomposed the climate response to CO2 forcing into the fast and slow processes. Notably, it is the enhanced slow response, which is driven by long‐term sea surface temperature (SST) changes, that dominates the asymmetric response of ISM onset. This slow response delays the ISM onset by strengthening near‐surface poleward land‐sea moist static energy contrast, thereby weakening the lower‐tropospheric monsoonal circulation. Based on the atmospheric component model simulations, we found that both the uniform SST change and patterned SST changes in the slow response contribute to the delay of ISM onset, but the latter plays a dominant role. Our results emphasize the importance of thoroughly assessing regional hydrological cycle features when designing the CO2 removal pathways.

Neural Network Parameterization of Subgrid‐Scale Physics From a Realistic Geography Global Storm‐Resolving Simulation

AbstractParameterization of subgrid‐scale processes is a major source of uncertainty in global atmospheric model simulations. Global storm‐resolving simulations use a finer grid (less than 5 km) to reduce this uncertainty by explicitly resolving deep convection and details of orography. This study uses machine learning to replace the physical parameterizations of heating and moistening rates, but not wind tendencies, in a coarse‐grid (200 km) global atmosphere model, using training data obtained by spatially coarse‐graining a 40‐day realistic geography global storm‐resolving simulation. The training targets are the three‐dimensional fields of effective heating and moistening rates, including the effect of grid‐scale motions that are resolved but imperfectly simulated by the coarse model. A neural network is trained to predict the time‐dependent heating and moistening rates in each grid column using the coarse‐grained temperature, specific humidity, surface turbulent heat fluxes, cosine of solar zenith angle, land‐sea mask and surface geopotential of that grid column as inputs. The coefficient of determination R2 for offline prediction ranges from 0.4 to 0.8 at most vertical levels and latitudes. Online, we achieve stable 35‐day simulations, with metrics of skill such as the time‐mean pattern of near‐surface temperature and precipitation comparable or slightly better than a baseline simulation with conventional physical parameterizations. However, the structure of tropical circulation and relative humidity in the upper troposphere are unrealistic. Overall, this study shows potential for the replacement of human‐designed parameterizations with data‐driven ones in a realistic setting.

Meteorological characteristics of extreme ozone pollution events in China and their future predictions

Abstract. Ozone (O3) has become one of the most concerning air pollutants in China in recent decades. In this study, based on surface observations, reanalysis data, global atmospheric chemistry model simulations, and multi-model future predictions, meteorological characteristics conducive to extreme O3 pollution in various regions of China are investigated, and their historical changes and future trends are analyzed. During the most severe O3 polluted months, the chemical production of O3 is enhanced under the hot and dry conditions over the North China Plain (NCP) in June 2018 and the Yangtze River Delta (YRD) in July 2017, while regional transport is the main reason for the severe O3 pollution over the Sichuan Basin (SCB) in July 2015 and the Pearl River Delta (PRD) in September 2019. Over the last 4 decades, the frequencies of high-temperature and low-relative-humidity conditions increased in 2000–2019 relative to 1980–1999, indicating that O3 pollution in both the NCP and YRD has become more frequent under historical climate change. In the SCB and PRD, the occurrence of atmospheric circulation patterns similar to those during the most polluted months increased, together with the more frequent hot and dry conditions, contributing to the increases in severe O3 pollution in the SCB and PRD during 1980–2019. In the future (by 2100), the frequencies of months with anomalous high temperature show stronger increasing trends in the high-forcing scenario (Shared Socioeconomic Pathway (SSP5-8.5)) compared to the sustainable scenario (SSP1-2.6) in China. It suggests that high anthropogenic forcing will not only lead to slow economic growth and climate warming but also likely result in environmental pollution issues.

Oceanic Influence and Lapse Rate Changes Dominate the Recent Amplified Saharan Warming

AbstractThe surface air temperature (SAT) over the Sahara Desert has increased at a much faster rate than average tropical land in recent decades. This study examines the relative roles of anthropogenic greenhouse gas (GHG) forcing and sea surface temperature (SST) change in the observed Saharan temperature increase during boreal warm season from 1979 to 2020 using atmospheric general circulation model simulations. It is found that the SST forcing dominates the observed Saharan warming. Further analysis shows that the warming ocean forces the Saharan SAT increase by moving more energy to the Sahara Desert, while the water vapor feedback plays a secondary role. The reason for the stronger Saharan warming than the average tropical land given the same SST forcing is also explored. We found that the largest contributor to the warming contrast is the lapse‐rate feedback, which is attributable to the difference in the vertical warming profile.

Decadal modulation of temperature pattern over East Asia by Pacific Decadal Oscillation

The decadal surface air temperature (SAT) variation over East Asia (EA) is characterized by an opposite pattern, warming over the northern EA along with cooling over the southern EA, and vice versa, fluctuating on decadal time scale. We found that Pacific Decadal Oscillation (PDO) has been largely responsible for the opposite decadal SAT variation. Positive (negative) phase of the PDO is related to the northern warming (cooling) and southern cooling (warming) over EA, and the decadal variation of the opposite SAT pattern is highly correlated with the PDO decadal variability, implying a decadal modulation of SAT by PDO. We investigated the influence of PDO on the opposite decadal SAT pattern by employing a dynamical adjustment method based on constructed circulation analogues. The results showed that the PDO associated variability in the large-scale atmospheric circulation over Eurasia, characterized by a dipole structure with cyclonic circulation occupying the northern Eurasia but anticyclonic circulation over the southern Eurasia when in positive PDO phase, is responsible for the opposite decadal SAT pattern. Further analysis on the origin of the anomalous atmospheric circulation was performed by combining observations and climate model simulations. Based on observations and the multi-model simulations of Atmospheric Model Intercomparison Project (AMIP) from the Coupled Model Intercomparison Project Phase 6 (CMIP6), we found a contribution of intrinsic atmospheric dynamics, which was further suggested by the results using the Community Atmosphere Model simulations.

ModE-RA: a global monthly paleo-reanalysis of the modern era 1421 to 2008

The Modern Era Reanalysis (ModE-RA) is a global monthly paleo-reanalysis covering the period between 1421 and 2008. To reconstruct past climate fields an offline data assimilation approach is used, blending together information from an ensemble of transient atmospheric model simulations and observations. In the early period, ModE-RA utilizes natural proxies and documentary data, while from the 17th century onward instrumental measurements are also assimilated. The impact of each observation on the reconstruction is stored in the observation feedback archive, which provides additional information on the input data such as preprocessing steps and the regression-based forward models. The monthly resolved reconstructions include estimates of the most important climate fields. Furthermore, we provide a reconstruction, ModE-RAclim, which together with ModE-RA and the model simulations allows to disentangle the role of observations and model forcings. ModE-RA is best suited to study intra-annual to multi-decadal climate variability and to analyze the causes and mechanisms of past extreme climate events.

Weaker regional carbon uptake albeit with stronger seasonal amplitude in northern mid-latitudes estimated by higher resolution GEOS-Chem model

Terrestrial ecosystem in the Northern Hemisphere is characterized by a substantial carbon sink in recent decades. However, the carbon sink inferred from atmospheric CO2 data is usually larger than process- and inventory-based estimates, resulting in carbon release or near-neutral carbon exchange in the tropics. The atmospheric approach is known to be uncertain due to systematic biases of coarse atmospheric transport model simulation. Compared to a coarse-resolution inverse estimate at 4° × 5° using GEOS-Chem in the integrated region of N. America, E. Asia, and Europe from 2015 to 2018, the annual carbon sink estimate at a native high-resolution of 0.5° × 0.625° is reduced from −3.0±0.08 gigatons of carbon per year (GtC yr−1) to −2.15±0.08 GtC yr−1 due to prominent more carbon release during the non-growing seasons. The major reductions concentrate in the mid-latitudes (20°N–45°N), where the mean land carbon sinks in China and the USA are reduced from 0.64±0.03 and 0.35±0.02 GtC yr−1 to 0.14±0.03 and 0.15±0.02 GtC yr−1, respectively. The coarse-resolution GEOS-Chem tends to trap both the release and uptake signal within the planetary boundary layer, resulting in weaker estimates of biosphere seasonal strength. Since the strong fossil fuel emissions are persistently released from the surface, the trapped signal leads to the stronger estimates of annual carbon uptakes. These results suggest that high-resolution inversion with accurate vertical and meridional transport is urgently needed in targeting national carbon neutrality.

Hemispheric-scale heavy metal pollution from South American and Australian mining and metallurgy during the Common Era

Records from polar and alpine ice reflect past changes in background and industrial toxic heavy metal emissions. While Northern Hemisphere records have been used to evaluate environmental effects and linkages to historical events such as foreign conquests, plagues, economic downturns, and technological developments during the past three millennia, little is known about the magnitude and environmental effects of such emissions in the Southern Hemisphere or their historical linkages, especially prior to late 19th century industrialization. Here we used detailed measurements of the toxic heavy metals lead, cadmium, and thallium, as well as non-toxic bismuth, cerium, and sulfur in an array of five East Antarctic ice cores to investigate hemispheric-scale pollution during the Common Era. While thallium showed no anthropogenic increases, the other three metals increased by orders of magnitude in recent centuries after accounting for crustal and volcanic components. These first detailed records indicate that East Antarctic lead pollution started in the 13th century coincident with Late Intermediate Period metallurgy in the Andes and was pervasive during the Spanish Colonial period in parallel with large-scale exploitation of Andean silver and other ore deposits. Lead isotopic variations suggest that 19th-century increases in lead, cadmium, and bismuth resulted from Australian lead and Bolivian tin mining emissions, with 20th century pollution largely the result of the latter. As in the Northern Hemisphere, variations in heavy metal pollution coincided with plagues, cultural and technological developments, as well as global economic and political events including the Great Depression and the World Wars. Estimated atmospheric heavy metal emissions from Spanish Colonial-era mining and smelting during the late 16th and early 17th century were comparable to estimated European emissions during the 1st-century apex of the Roman Empire, with atmospheric model simulations suggesting hemispheric-scale toxic heavy metal pollution during the past five centuries as a result.

Characterizing the Madden–Julian Oscillation in the western Pacific Ocean from a regional coupled ocean–atmosphere model simulation

AbstractThis study reports on the analysis of the results from a 20 km grid spacing, Regional Coupled ocean–atmosphere Model (RCM) integration over the Western Pacific Warm Pool (WP2). The RCM was integrated over a 20‐year period (1986–2005) using reanalysis boundary conditions for the atmosphere and the ocean. This is a first‐of‐a‐kind study with an RCM at 20 km over the WP2. The RCM simulation shows reasonable fidelity of the mean state and of the Madden–Julian Oscillation (MJO). We utilize this successful integration of the RCM to understand a well‐known observed feature of MJOs in the WP2 to be of the strongest amplitude during the December–March period of the year. Our analysis of the model integration reveals that the recharge of moist static energy (MSE) prior to peak MJO convection and its discharge during and after the convection explains the MJO in the simulation. The recharge/discharge of the MSE is shown to be largely dictated by horizontal advection, which is stemmed to a small extent by column‐integrated radiative heating and surface evaporation. This balance of forces in the evolution of the MSE anomalies and their corresponding variations with sea‐surface temperature (SST) anomalies at MJO time‐scales in the WP2 is strongest in the December–March period in the RCM simulation.

Multi-decadal variability controls short-term stratospheric water vapor trends

Stratospheric water vapor increases are expected in response to greenhouse gas-forced climate warming, and these changes act as a positive feedback to surface climate. Previous efforts at inferring trends from the 3–4 decade-long observational stratospheric water vapor record have yielded conflicting results. Here we show that a robust multi-decadal variation of water vapor concentrations exists in most parts of the stratosphere based on satellite observations and atmospheric model simulations, which clearly divides the past 40 years into two wet decades (1986–1997; 2010–2020) and one dry decade (1998–2009). This multi-decadal variation, especially pronounced in the lower to middle stratosphere and in the northern hemisphere, is associated with decadal temperature anomalies (±0.2 K) at the cold point tropopause and a hemispheric asymmetry in changes of the Brewer-Dobson circulation modulating methane oxidation. Multi-decadal variability must be taken into account when evaluating stratospheric water vapor trends over recent decades.

Disaggregation of remote sensing and model-based data for 1 km daily seamless soil moisture

High-resolution soil moisture (SM) products are crucial for managing water in agricultural regions, irrigation scheduling, and land–atmosphere model simulations. Most satellite-based SM products have spatial resolutions in the tens of kilometers, which cannot satisfy the aforementioned applications, and there is an urgent need to disaggregate them to fine spatial resolutions. Currently, disaggregation method based on multi-source data fusion tend to be robust, but the following difficulties remain: 1) satellite products (microwave, optical/infrared) are somewhat missing in space and time which hinder the applications; 2) only one model-based product is used in the fusion process and different model-based products were not sufficiently evaluated. To overcome these problems, this work developed an SM disaggregation methodology. The best model-based SM product was first assessed using the triple collocation (TC) method, which allows us to obtain the weight of individual product. The model-based and microwave SM products were combined based on weight to produce daily seamless SM data at 25 km. Second, the iterative multi-temporal reconstruction and the ESTARFM method were combined to solve the invalid grids problem of optical/infrared product, thus obtaining 1 km daily seamless auxiliary data. Finally, daily seamless SM data at 1 km were obtained by geographically weighted regression (GWR) method. The methodology proposed in this study had a well-defined mechanism, and the resulting SM product achieved a satisfied accuracy (ubRMSE = 0.044 m3/m3), with characteristics of spatiotemporal continuity as well as fine spatial detail. The disaggregated SM product makes full use of model-based, microwave, and optical/infrared products, which is valuable in areas such as agricultural management policy, high-resolution hydro-meteorological simulations, and disaster monitoring.

Contrasting changes in ozone during 2019–2021 between eastern and the other regions of China attributed to anthropogenic emissions and meteorological conditions

Ozone pollution is one of the most severe air quality issues in China that poses a serious threat to human health and ecosystems. During 2019–2021, the maximum daily 8-h average ozone concentrations in eastern China (110–122.5°E, 26–42°N) and the rest of China (ROC) show different decreasing patterns, with ozone concentrations in eastern China decreasing by 14.9 μg/m3, which is much larger than 4.8 μg/m3 in ROC. Here, based on two independent methods, the atmospheric chemical transport model (GEOS-Chem) simulations and the machine learning (ML) model (LightGBM) predictions, the reasons for the differences in ozone changes between eastern China and ROC during the warm season (April to September) are investigated. According to the GEOS-Chem (LightGBM) results, changes in the meteorological conditions contributed to an ozone decrease by 7.3 (6.8) μg/m3 in eastern China due to decreased chemical production and an ozone decrease by 6.8 (7.0) μg/m3 in ROC attributed to the weakened horizontal and vertical advection. With the influence of meteorological factors excluded, the observations show that changes in anthropogenic emissions resulted in an ozone decrease by 7.6 (8.1) μg/m3 in eastern China and an ozone increase by 2.0 (2.2) μg/m3 in ROC, which is primarily induced by the changes in NOx emissions. The surface measurements and satellite retrievals also indicate that the reduction in NOx emissions in ROC is less efficient than that in the more developed eastern China, leading to contrasting changes in ozone concentrations between eastern China and ROC during 2019–2021. Our results highlight the critical need to reduce ozone precursor emissions in the rest regions of China apart from eastern China.