Climate System Model Research Articles

Evaluation of the CAMS-CSM Model in predicting a Northeast Cold Vortex Event at the early Onset of 2020 Mei-yu season

Intimately related to the Asian summer monsoon, the Mei-yu rainfall is also strongly influenced by atmospheric circulation in the middle to high latitudes, especially the Northeast Cold Vortex (NECV), and thus making prediction of the Mei-yu rainfall a challenging issue. The prediction skills of the CAMS-CSM (full name as the Chinese Academy of Meteorological Sciences Climate System Model) for a NECV event at the early onset of 2020 Mei-yu season and the associated Mei-yu rainfall are evaluated. Hindcast experiments with two different horizontal resolutions are employed to assess the climate model in predicting the synoptic system. The ERA5 reanalysis data and the CN05.1 precipitation data are adopted for comparison. Results indicate that both the middle-resolution (T106, ∼1°) and high-resolution (T255, ∼0.47°) version of the CAMS-CSM model are able to capture this NECV event, while showing some biases on its intensity, duration and location. Overpredictions in the strength and duration of the NECV are found in the T106 version, which could be attributed to a stronger dry invasion from higher levels during the development stage, an intensified Okhotsk blocking high, and a weakened upper-level jet at the decaying phase. As for the T255 version, a stronger NECV is predicted further north than the reanalysis, and sources of the biases are identified, including northward displacements of the high-level dry invasion and the westerly jet. Further investigation suggests that the T106 version performs better than the T255 version in predicting the Mei-yu rainfall because of a more accurate prediction on the location of the NECV. Positive biases in the cold advection and Mei-yu front are identified in the T106 version, contributing to a stronger Mei-yu rainfall than the observation. The Mei-yu rainfall is poorly predicted in T255 version due to prediction errors in the location of the NECV-induced cold advection. Therefore, improving the prediction skill of the NECV, not only its intensity but also location, is of vital significance to achieve a better prediction of the Mei-yu rainfall.

Comparison of middle- and low-latitude sodium layer from a ground-based lidar network, the Odin satellite, and WACCM–Na model

Abstract. The ground-based measurements obtained from a lidar network and the 6-year OSIRIS (optical spectrograph and infrared imager system) limb-scanning radiance measurements made by the Odin satellite are used to study the climatology of the middle- and low-latitude sodium (Na) layer. Up to January 2021, four Na resonance fluorescence lidars at Beijing (40.5∘ N, 116.0∘ E), Hefei (31.8∘ N, 117.3∘ E), Wuhan (30.5∘ N, 114.4∘ E), and Haikou (19.5∘ N, 109.1∘ E) collected vertical profiles of Na density for a total of 2136 nights (19 587 h). These large datasets provide multi-year routine measurements of the Na layer with exceptionally high temporal and vertical resolution. The lidar measurements are particularly useful for filling in OSIRIS data gaps since the OSIRIS measurements were not made during the dark winter months because they utilize the solar-pumped resonance fluorescence from Na atoms. The observations of Na layers from the ground-based lidars and the satellite are comprehensively compared with a global model of meteoric Na in the atmosphere (WACCM–Na). The lidars present a unique test of OSIRIS and WACCM (Whole Atmosphere Community Climate Model), because they cover the latitude range along 120∘ E longitude in an unusual geographic location with significant gravity wave generation. In general, good agreement is found between lidar observations, satellite measurements, and WACCM simulations. On the other hand, the Na number density from OSIRIS is larger than that from the Na lidars at the four stations within one standard deviation of the OSIRIS monthly average, particularly in autumn and early winter arising from significant uncertainties in Na density retrieved from much less satellite radiance measurements. WACCM underestimates the seasonal variability of the Na layer observed at the lower latitude lidar stations (Wuhan and Haikou). This discrepancy suggests the seasonal variability of vertical constituent transport modelled in WACCM is underestimated because much of the gravity wave spectrum is not captured in the model.

Influences of stratospheric intrusions to high summer surface ozone over a heavily industrialized region in northern China

The stratospheric contribution to tropospheric ozone has long been a topic of much debate over the past few decades. In this study, we leveraged multiple datasets from surface, sounding and satellite observations to reanalysis datasets, along with a global chemical transport model (Global Nested Air Quality Prediction Modelling System, GNAQPMS) to investigate the impact of a stratospheric-to-tropospheric transport (STT) event characterized by long duration and wide range in the summer on surface high ozone episodes over heavily industrialized regions in northern China. In 14–18 August 2019, the ERA5 reanalysis datasets showed a potential vorticity (PV) tongue and a deep, upper-level trough penetrate towards 35° N over the North China Plain (NCP), indicating the occurrence of a stratospheric intrusion. From Atmospheric Infrared Sounder (AIRS) measurements, we found that the ozone-rich, stratospheric air mass had been injected into the lower altitudes. The GNAQPMS generally captured the featured layers, although there was a slight underestimation in the low troposphere. The averaged magnitudes of stratospheric contribution (O3S) and percentage (O3F) simulated by GNAQPMS were 3–20 μg m−3 and 6%–20%, respectively, while the Whole Atmosphere Community Climate Model (WACCM) indicated a higher stratospheric contribution by 3–5 μg m−3. Through this study, we give our opinions on the controversial topic of a more thorough understanding of the influence of natural processes apart from anthropogenic emissions, even in a heavily polluted region during summer.

Importance of lower atmospheric forcing and magnetosphere-ionosphere coupling in simulating neutral density during the February 2016 geomagnetic storm

During geomagnetic storms a large amount of energy is transferred into the ionosphere-thermosphere (IT) system, leading to local and global changes in e.g., the dynamics, composition, and neutral density. The more steady energy from the lower atmosphere into the IT system is in general much smaller than the energy input from the magnetosphere, especially during geomagnetic storms, and therefore details of the lower atmosphere forcing are often neglected in storm time simulations. In this study we compare the neutral density observed by Swarm-C during the moderate geomagnetic storm of 31 January to 3 February 2016 with the Thermosphere-Ionosphere-Electrodynamics-GCM (TIEGCM) finding that the model can capture the observed large scale neutral density variations better in the southern than northern hemisphere. The importance of more realistic lower atmospheric (LB) variations as specified by the Whole Atmosphere Community Climate Model eXtended (WACCM-X) with specified dynamics (SD) is demonstrated by improving especially the northern hemisphere neutral density by up to 15% compared to using climatological LB forcing. Further analysis highlights the importance of the background atmospheric condition in facilitating hemispheric different neutral density changes in response to the LB perturbations. In comparison, employing observationally based field-aligned current (FAC) versus using an empirical model to describe magnetosphere-ionosphere (MI) coupling leads to an 7–20% improved northern hemisphere neutral density. The results highlight the importance of the lower atmospheric variations and high latitude forcing in simulating the absolute large scale neutral density especially the hemispheric differences. However, focusing on the storm time variation with respect to the quiescent time, the lower atmospheric influence is reduced to 1–1.5% improvement with respect to the total observed neutral density. The results provide some guidance on the importance of more realistic upper boundary forcing and lower atmospheric variations when modeling large scale, absolute and relative neutral density variations.

Predicting Present and Future Distribution Ranges of an Endemic Flea Beetle, Psylliodes anatolicus Gök and Çilbiroğlu 2004 (Coleoptera: Chrysomelidae) in Türkiye

This study aimed to construct species distribution models (SDMs) to predict present and future (2050 and 2070) potential distribution ranges of the endemic leaf beetle Psylliodes anatolicus Gök and Çilbiroğlu, 2004 under different climate change scenarios (Representative Concentration Pathway (RCP) 4.5 and 8.5). The distribution records were gathered from the related literature and unpublished data of the authors. SDMs were constructed by the maximum entropy (MaxEnt) method using the bioclimatic variables of Community Climate System Model 4 (CCSM4). As a result of this study, the most effective bioclimatic factors determining the distribution of species were isothermality, temperature seasonality, and mean temperature of the wettest quarter. The SDM conducted for the present distribution showed that the species may occur in large parts of the Aegean and Mediterranean Regions of Türkiye, beyond the known records. The SDMs for 2050 and 2070 suggest that the range of the species will shrink considerably or go extinct totally in the next 50 years, probably due to the changing climate. In conclusion, this study revealed that changing climate threatens the endemic members of Anatolian biodiversity, especially the endemic species living in mountain ecosystems.

Observed and predicted precipitation variability across Pakistan with special focus on winter and pre-monsoon precipitation.

This study utilises ground, satellite and model data to investigate the observed and future precipitation changes in Pakistan. Pakistan Meteorological Department's (PMD) monthly precipitation data set along with the Tropical Rainfall Measuring Mission (TRMM) monthly dataset TRMM_3B43 (0.25° × 0.25° resolution) and European Centre for Medium-Range Weather Forecasts's (ECMWF) monthly reanalysis product ERA5 have been used to evaluate rainfall trends over the climatic zones of Pakistan through Mann-Kendall test, Sen's slope estimator and innovative trend analysis for the time period 1978-2018. Community Climate System Model (CCSM4) projections have been employed to explore the projected changes in precipitation until 2099. Furthermore, TRMM and CCSM4 projections have been correlated and validated using root mean square error (RMSE) and mean bias error (MBE). There is a good correlation between TRMM and PMD ground observation at all stations of the country for all seasons, with correlation coefficient values ranging from 0.89 (November) to 0.97 (July and August). However, ERA5 monthly precipitation tends to overestimate rainfall in the winter months. The study shows a decreasing trend in winter precipitation in all zones of the country with a significant decrease over western mountains, i.e. zone C of the country. During 2008-2018, a sharp decrease in winter precipitation is observed as compared to the baseline value of 1978-2007 in all climatic zones. Rainy days have also shown a decrease in winter and pre-monsoon seasons. There seems to be a shift in precipitation from winter towards pre-monsoon season as pre-monsoon precipitation in the last 11years increased in all zones except for zone C. Coherently, there is a decrease in an area affected by winter precipitation and an increase in area for pre-monsoon precipitation. Future precipitation estimates from the CCSM4 model for RCP 4.5 and RCP 8.5 overestimate precipitation in most parts of the country for the first 9 observed years (2010-2018) and predict a rise in precipitation by 2099 which is more pronounced in the northern and western Pakistan while a decrease is predicted for the plains of the country, which might have negative consequences for agriculture.

How well do the CMIP6 HighResMIP models simulate precipitation over the Tibetan Plateau?

The simulation of precipitation over the Tibetan Plateau (TP) is still a challenge in climate modeling community, although there have been a number of improvements in recent global climate models. In this study, we evaluate the differences in the simulation of precipitation over the TP using multi–resolution outputs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) High Resolution Model Intercomparison Project (HighResMIP). Our results show that both the high resolution (HR) and low resolution (LR) models could generally simulate the annual precipitation well over the TP during the period of 1998–2014. With their finer resolution, the HR models, give some improvements in the simulation of annual precipitation, showing a significantly reduced “wet bias” over the TP compared with the LR models. In addition, the increased resolution performs a better simulation of the precipitation extremes, especially over the southern and southeastern TP, revealing the added value of HR models. We further investigate the differences in the simulation of precipitation between the LR and HR models using a linearized moisture budget equation, which suggests that the underlying differences can be largely explained by the contribution of the dynamic effect (δDY). This effect, dominated by the differences in the simulation of the atmospheric circulation, could induce local moisture convergence, generating excessive precipitation in the LR models compared with the HR models. This implies that the large–scale circulation and moisture conditions can be resolved more realistically in HR models, which is an important factor in determining the simulation of precipitation over the TP.

Modelling the influence of coral-reef-derived dimethylsulfide on the atmosphere of the Great Barrier Reef, Australia

Marine dimethylsulfide (DMS) is an important source of natural sulfur to the atmosphere, with potential implications for the Earth’s radiative balance. Coral reefs are important regional sources of DMS, yet their contribution is not accounted for in global DMS climatologies or in model simulations. This study accounts for coral-reef-derived DMS and investigates its influence on the atmosphere of the Great Barrier Reef (GBR), Australia, using the Australian Community Climate and Earth System Simulator Atmospheric Model version 2 (ACCESS-AM2). A climatology of seawater surface DMS (DMSw) concentration in the GBR and an estimate of direct coral-to-air DMS flux during coral exposure to air at low tide are incorporated into the model, increasing DMS emissions from the GBR region by 0.02 Tg yr-1. Inclusion of coral-reef-derived DMS increased annual mean atmospheric DMS concentration over north-eastern Australia by 29%, contributing to an increase in gas-phase sulfate aerosol precursors of up to 18% over the GBR. The findings suggest that the GBR is an important regional source of atmospheric sulfur, with the potential to influence local-scale aerosol-cloud processes. However, no influence on sulfate aerosol mass or number concentration was detected, even with a reduction in anthropogenic sulfur dioxide emissions, indicating that DMS may not significantly influence the regional atmosphere at monthly, annual or large spatial scales. Further research is needed to improve the representation of coral-reef-derived DMS in climate models and determine its influence on local, sub-daily aerosol-cloud processes, for which observational studies suggest that DMS may play a more important role.

Evaluation of Polar Winter Mesopause Wind in WACCMX+DART.

This work evaluates zonal winds in both hemispheres near the polar winter mesopause in the Whole Atmosphere Community Climate Model (WACCM) with thermosphere‐ionosphere eXtension combined with data assimilation using the Data Assimilation Research Testbed (DART) (WACCMX+DART). We compare 14 years (2006–2019) of WACCMX+DART zonal mean zonal winds near 90 km to zonal mean zonal winds derived from Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) geopotential height measurements during Arctic mid‐winter. 10 years (2008–2017) of WACCMX+DART zonal mean zonal winds are compared to SABER in the Antarctic mid‐winter. It is well known that WACCM, and WACCM‐X, zonal winds at the polar winter mesopause exhibit a strong easterly (westward) bias. One explanation for this is that the models omit higher order gravity waves (GWs), and thus the eastward drag caused by these GWs. We show for the first time that the model winds near the polar winter mesopause are in closer agreement with SABER observations when the winds near the stratopause are weak or reversed. The model and observed mesosphere and lower thermosphere winds agree most during dynamically disturbed times often associated with minor or major sudden stratospheric warming events. Results show that the deceleration of the stratospheric and mesospheric polar night jet allows enough eastward GWs to propagate into the mesosphere, driving eastward zonal winds that are in agreement with the observations. Thus, in both hemispheres, the winter polar night jet speed and direction near the stratopause may be a useful proxy for model fidelity in the polar winter upper mesosphere.

Arecibo measurements of D-region electron densities during sunset and sunrise: implications for atmospheric composition

Abstract. Earth's lower ionosphere is the region where terrestrial weather and space weather come together. Here, between 60 and 100 km altitude, solar radiation governs the diurnal cycle of the ionized species. This altitude range is also the place where nanometre-sized dust particles, recondensed from ablated meteoric material, exist and interact with free electrons and ions of the ionosphere. This study reports electron density measurements from the Arecibo incoherent-scatter radar being performed during sunset and sunrise conditions. An asymmetry of the electron density is observed, with higher electron density during sunset than during sunrise. This asymmetry extends from solar zenith angles (SZAs) of 80 to 100∘. This D-region asymmetry can be observed between 95 and 75 km altitude. The electron density observations are compared to the one-dimensional Sodankylä Ion and Neutral Chemistry (SIC) model and a variant of the Whole Atmosphere Community Climate Model incorporating a subset SIC's ion chemistry (WACCM-D). Both models also show a D-region sunrise–sunset asymmetry. However, WACCM-D compares slightly better to the observations than SIC, especially during sunset, when the electron density gradually fades away. An investigation of the electron density continuity equation reveals a higher electron–ion recombination rate than the fading ionization rate during sunset. The recombination reactions are not fast enough to closely match the fading ionization rate during sunset, resulting in excess electron density. At lower altitudes electron attachment to neutrals and their detachment from negative ions play a significant role in the asymmetry as well. A comparison of a specific SIC version incorporating meteoric smoke particles (MSPs) to the observations revealed no sudden changes in electron density as predicted by the model. However, the expected electron density jump (drop) during sunrise (sunset) occurs at 100∘ SZA when the radar signal is close to the noise floor, making a clear falsification of MSPs' influence on the D region impossible.

A Hybrid Dynamical Approach for Seasonal Prediction of Sea‐Level Anomalies: A Pilot Study for Charleston, South Carolina

AbstractUsing Earth system models for seasonal sea‐level prediction remains challenging due to model biases and initialization shocks. Here we present a hybrid dynamical approach for seasonal sea‐level prediction to alleviate some of these issues. The approach is based on convolving atmospheric forcings with sea‐level sensitivities to these forcings. The sensitivities are pre‐computed by the adjoint model of the Estimating Circulation and Climate of the Ocean (ECCO) system. The forcings are a concatenation of ECCO forcings before prediction initialization and a 10‐member predicted atmospheric forcing ensemble from the Community Climate System Model version 4 (CCSM4) after initialization, with offline forcing bias corrections applied using the observationally‐constrained ECCO seasonal forcing climatology. As a pilot study, we conducted 12‐month hindcasts from 1995 to 2016 in Charleston (United States East Coast). Our approach avoids drifts in CCSM4 sea‐level predictions and beats seasonal climatology and damped persistence as predictors up to a 6‐month lead time. The prediction skill comes from two factors: (a) ECCO forcings prior to prediction initialization influence sea level after initialization through delayed oceanic adjustments (e.g., coastally‐trapped waves, open‐ocean Rossby waves, and advection of steric anomalies) leading to skillful predictions beyond 2 months after initialization, and (b) the 10‐member CCSM4 ensemble forcing predictions have relatively good skill at 1–2 months lead times. Our method is computationally efficient for operational sea‐level prediction at specific locations and can attribute sea‐level prediction skill and uncertainty to specific forcings or forcing from particular regions, thereby providing useful information to seasonal prediction centers for improving their prediction systems.

Radar observations of winds, waves and tides in the mesosphere and lower thermosphere over South Georgia island (54° S, 36° W) and comparison with WACCM simulations

Abstract. The mesosphere and lower thermosphere (MLT) is a dynamic layer of the earth's atmosphere. This region marks the interface at which neutral atmosphere dynamics begin to influence the upper atmosphere and ionosphere. However, our understanding of this region and our ability to accurately simulate it in global circulation models (GCMs) is limited by a lack of observations, especially in remote locations. To this end, a meteor radar was deployed from 2016 to 2020 on the remote mountainous island of South Georgia (54∘ S, 36∘ W) in the Southern Ocean. In this study we use these new measurements to characterise the fundamental dynamics of the MLT above South Georgia including large-scale winds, solar tides, planetary waves (PWs), and mesoscale gravity waves (GWs). We first present an improved method for time–height localisation of radar wind measurements and characterise the large-scale MLT winds. We then determine the amplitudes and phases of the diurnal (24 h), semidiurnal (12 h), terdiurnal (8 h), and quardiurnal (6 h) solar tides at this latitude. We find very large amplitudes up to 30 m s−1 for the quasi 2 d PW in summer and, combining our measurements with the meteor SAAMER radar in Argentina, show that the dominant modes of the quasi 5, 10, and 16 d PWs are westward 1 and 2. We investigate and compare wind variance due to both large-scale “resolved” GWs and small-scale “sub-volume” GWs in the MLT and characterise their seasonal cycles. Last, we use our radar observations and satellite temperature observations from the Microwave Limb Sounder to test a climatological simulation of the Whole Atmosphere Community Climate Model (WACCM). We find that WACCM exhibits a summertime mesopause near 80 km altitude that is around 10 K warmer and 10 km lower in altitude than observed. Above 95 km altitude, summertime meridional winds in WACCM reverse to poleward, but this not observed in radar observations in this altitude range. More significantly, we find that wintertime zonal winds between 85 to 105 km altitude are eastward up to 40 m s−1 in radar observations, but in WACCM they are westward up to 20 m s−1. We propose that this large discrepancy may be linked to the impacts of secondary GWs (2GWs) on the residual circulation, which are not included in most global models, including WACCM. These radar measurements can therefore provide vital constraints that can guide the development of GCMs as they extend upwards into this important region of the atmosphere.

Aspects related to variability of radiative cooling by NO in lower thermosphere, TEC and O/N2 correlation, and diffusion of NO into mesosphere during the Halloween storms

Nitric Oxide is a very important trace species which plays a significant role acting as a natural thermostat in Earth’s thermosphere during strong geomagnetic activity. In this paper, we present various aspects related to the variation in the NO Infrared radiative flux (IRF) exiting the thermosphere by utilizing the TIMED/SABER (Thermosphere Ionosphere Mesosphere Energetics and Dynamics/ Sounding of the Atmosphere using Broadband Emission Radiometry) observational data during the Halloween storm which occurred in late October 2003. The Halloween storm comprised of three intense-geomagnetic storms. The variability of NO infrared flux during these storm events and its connection to the strength of the geomagnetic storms were found to be different in contrast to similar super storms. The connection between the quantum of energy outflux from the upper atmosphere into space in terms of NO IRF and the duration of storms is established. The NO radiative cooling, and the closely correlated depletion in O/N2 ratio are controlled by the Joule heating intensity (proxied by AE-index). The collisional excitation rate of NO, calculated using the modelled datasets of WACCM-X (Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension), correlates well with the observed pattern of radiative emission by NO. Observational datasets from TIMED/GUVI (Global Ultra-Violet Imager) and MIT Haystack observatory madrigal GNSS (Global navigation satellite system) total electron content (TEC) database shows that the TEC and O/N2 enhancement in low-mid northern hemispheric latitudes are mainly controlled by the z-component of Interplanetary magnetic field (IMF-Bz). The penetration of eastward electric field during the storm events is found to be responsible for the overall enhancement of TEC. The contribution of enhanced day-side TEC in observed variation of O/N2 ratio by GUVI is also reported. It is also seen that during substorms related events the night-time polar region experiences more cooling due to NO than the daytime polar region. The connections between the mid- and low-latitude enhancement in NO IRF with the propagation of LSTIDs (Large-scale traveling ionospheric disturbances) in combination with the O/N2 variability, and the altitudinal variation in NO flux with the progression of the storm is also investigated. This study presents the evidence on the role of diffusion processes in the large scale enhancement of NO in the mesospheric altitudes.

Future rise of the Great Lakes water levels under climate change

The Great Lakes of North America are the largest unfrozen surface freshwater system in the world and many ecosystems, industries, and coastal processes are sensitive to the changes in their water levels. The water levels of the Great Lakes are primarily governed by the net basin supplies (NBS) of each lake which are the sum of over-lake precipitation and basin runoff minus lake evaporation. Recent studies projected the future NBS of the Great Lakes by dynamically downscaling General Circulation Models (GCMs) using Regional Climate Models (RCMs). However, their RCMs had been coupled to one-dimensional (1D) lake column models which lack the ability to accurately simulate the Great Lakes’ hydrodynamics and thermal structure. In this study, an ensemble of three dynamical downscalings based on the Great Lakes-Atmosphere Regional Model (GLARM) is used to project the future NBS and water level of the Great Lakes. GLARM is a three-dimensional (3D) regional climate modeling system for the Great Lakes region that two-way couples an RCM to a 3D hydrodynamic lake and ice model, making this the first study to use such an advanced model for water level projection of the Great Lakes. For the present-day climate, over-lake precipitation and lake evaporation simulated by GLARM, along with the basin runoff simulated by the GLARM-driven Large Basin Runoff Model (LBRM), track the mean seasonal cycle of the NBS components remarkably well. In particular, compared to previous studies, the most significant improvements are made in estimating the lake evaporation. For future hydroclimate, the ensemble average projects an increase in annual NBS and average annual water level for each lake. The projected NBS increase is mostly due to an increase in over-lake precipitation and basin runoff combined with a relatively smaller increase in lake evaporation. According to the ensemble average, by 2040–2049, the average annual water levels of Lake Superior, Michigan-Huron, and Erie are projected to increase by +0.19, +0.44, and +0.28 m, respectively, relative to 2010–2019. The individual downscaling cases highlight the uncertainty in climate projection, showing both increases and decreases in annual NBS and water level projection. The projected changes in the average annual water levels by 2040–2049 relative to 2010–2019 range from −0.01 to +0.32 m in Lake Superior, −0.13 to +0.80 m in Lake Michigan-Huron and −0.09 to +0.54 m in Lake Erie.

Variability of Water Vapor in the Tropical Middle Atmosphere Observed From Satellites and Interpreted Using SD‐WACCM Simulations

AbstractWater vapor in the middle atmosphere plays an essential role in global warming, ozone depletion, and the formation of polar stratospheric and mesospheric clouds. We show that tropical middle atmospheric water vapor simulated with the specified‐dynamics version of the Whole Atmosphere Community Climate Model (SD‐WACCM) is consistent with changes observed in a merged satellite data set, which encompasses the period 1993–2020. Consistent with previous work, we find no significant trend in the stratosphere in either the observations or the simulation; in the mesosphere, we find a long‐term trend of 0.1 ppmv per decade, but only in the observations. We also analyze an SD‐WACCM simulation for the longer period 1980–2019 to quantify the contribution of various factors to the decadal variation of middle atmospheric water vapor. Over 1980–1995, the simulated water vapor in the upper stratosphere and mesosphere, averaged zonally and over ±30° latitude, increases by 0.30 ppmv per decade due to increasing methane emissions. After 1995, a significant abrupt decrease of water vapor of 0.37 ppmv per decade and then a gradual increase of 0.33 ppmv per decade result from changes in stratospheric cold point temperature. The cold‐point temperature is strongly influenced by the strength of the Brewer‐Dobson circulation. The acceleration of the Brewer‐Dobson circulation before about 2003 leads to a cooler tropical tropopause and a decrease of water vapor, and the deceleration thereafter leads to corresponding warming of the tropopause and an increase in water vapor.

The Redistribution of Air–Sea Momentum and Turbulent Kinetic Energy Fluxes by Ocean Surface Gravity Waves

Abstract The momentum flux to the ocean interior is commonly assumed to be identical to the momentum flux lost from the atmosphere in traditional atmosphere, ocean, and coupled models. However, ocean surface gravity waves (hereafter waves) can alter the magnitude and direction of the ocean-side stress (τoc) from the air-side stress (τa). This is rarely considered in coupled climate and forecast models. Based on a 30-yr wave hindcast, the redistribution of the global wind stress and turbulent kinetic energy (TKE) flux by waves was investigated. Waves play a more important role in the windy oceans in middle and high latitudes than that in the oceans in the tropics (i.e., the central portion of the Pacific and Atlantic Oceans). On average, the relative difference between τoc and τa, γτ, can be up to 6% in middle and high latitudes. The frequency of occurrence of γτ > 9% can be up to 10% in the windy extratropics. The directional difference between τoc and τa exceeds 3.5° in the middle and high latitudes 10% of the time. The difference between τoc and τa becomes more significant closer to the coasts of the continents due to strong wind gradients. The friction velocity-based approach overestimates (underestimates) the breaking-induced TKE flux in the tropics (middle and high latitudes). The findings presented in the current study show that coupled climate and Earth system models would clearly benefit from the inclusion of a wave model. Significance Statement The purpose of this study is to investigate the redistribution of the global wind stress and turbulent kinetic energy flux due to surface waves based on a 30-yr wave hindcast. The mean relative difference of the magnitude between the air-side and ocean-side stress is up to 6% with a 90th percentile of more than 9% in the windy extratropics. Due to strong wind gradients, the redistributive role of waves in the stress becomes more significant closer to coasts. The results indicate that we should consider the redistributive role of waves in the momentum and energy fluxes in climate and Earth system models since they are the key elements in the predictability of weather forecasting models and climate models.

Overcoming the disconnect between energy system and climate modeling

Energy system models underpin decisions by energy system planners and operators. Energy system modelling faces a transformation: accounting for changing meteorological conditions imposed by climate change. To enable that transformation, a community of practice in energy-climate modelling has started to form that aims to better integrate energy system models with weather and climate models. Here, we evaluate the disconnects between the energy system and climate modelling communities, then lay out a research agenda to bridge those disconnects. In the near-term, we propose interdisciplinary activities for expediting uptake of future climate data in energy system modelling. In the long-term, we propose a transdisciplinary approach to enable development of (1) energy-system-tailored climate datasets for historical and future meteorological conditions and (2) energy system models that can effectively leverage those datasets. This agenda increases the odds of meeting ambitious climate mitigation goals by systematically capturing and mitigating climate risk in energy sector decision making.

Calibrating anomalies improves forecasting of daily reference crop evapotranspiration

• We develop a new calibration strategy to enhance ET o forecasting. • This strategy improves the representation of ET o seasonality. • This strategy adds skills to calibrated ET o forecasts. • We validate the effectiveness and robustness of the strategy. Forecasting of short-term reference crop evapotranspiration (ET o ) provides valuable information for hydrological, agricultural, and ecological applications. ET o forecasts can be derived from weather forecasts of Numerical Weather Prediction (NWP) models, but such raw forecasts need to be calibrated to correct errors and improve reliability. This study calibrates the short-term ET o forecasts constructed with weather forecasts from the Australian Bureau of Meteorology's Australian Community Climate and Earth-System Simulator G2 version (ACCESS-G2) model, using the recently developed Seasonally Coherent Calibration (SCC) model. The monthly parameterization of the SCC model will not be able to capture the increasing or decreasing trends in ET o at the submonthly scale, posing a challenge for effective forecast calibration. To address this challenge, we developed a new calibration strategy based on ET o anomalies and climatological mean. We thoroughly evaluated this strategy at both the continental and weather station scales. Results indicate that calibrating ET o anomalies improves the correlation coefficient between calibrated forecasts and observations by up to 10%, and increases forecast skill scores by up to 200%, with more significant improvements found at longer lead times (9-day lead time vs. 1-day lead time). Improvements in forecast quality in calibrations across two spatial scales based on different types of observations (gridded observations vs. weather station observations) validate the effectiveness and robustness of the developed strategy. We anticipate that this strategy will be applicable to other calibration models to enhance NWP-based ET o forecasting.

Methane Emission From Global Lakes: New Spatiotemporal Data and Observation-Driven Modeling of Methane Dynamics Indicates Lower Emissions.

Lakes have been highlighted as one of the largest natural sources of the greenhouse gas methane (CH4) to the atmosphere. However, global estimates of lake CH4 fluxes over the last 20 years exhibit widely different results ranging from 6 to 185 Tg CH4 yr−1, which is to a large extent driven by differences in lake areas and thaw season lengths used. This has generated uncertainty regarding both lake fluxes and the global CH4 budget. This study constrains global lake water CH4 emissions by using new information on lake area and distribution and CH4 fluxes distinguished by major emission pathways; ecoclimatic lake type; satellite‐derived ice‐free emission period length; and diel‐ and temperature‐related seasonal flux corrections. We produced gridded data sets at 0.25° latitude × 0.25° longitude spatial resolution, representing daily emission estimates over a full annual climatological cycle, appropriate for use in global CH4 budget estimates, climate and Earth System Models, bottom‐up biogeochemical models, and top‐down inverse model simulations. Global lake CH4 fluxes are 41.6 ± 18.3 Tg CH4 yr−1 with approximately 50% of the flux contributed by tropical/subtropical lakes. Strong temperature‐dependent flux seasonality and satellite‐derived freeze/thaw dynamics limit emissions at high latitudes. The primary emission pathway for global annual lake fluxes is ebullition (23.4 Tg) followed by diffusion (14.1 Tg), ice‐out and spring water‐column turnover (3.1 Tg), and fall water‐column turnover (1.0 Tg). These results represent a major contribution to reconciling differences between bottom‐up and top‐town estimates of inland aquatic system emissions in the global CH4 budget.

The 1–31-Day Predictions of the South China Sea Summer Monsoon in the CAMS-CSM Climate Forecast System

The South China Sea summer monsoon (SCSSM) is crucial for the East Asian monsoon system, which has been detected from plenty of aspects, while its prediction has been relatively less investigated on the subseasonal timescale. The 1–31-day predictions of SCSSM, including fundamental dynamic and thermodynamic characteristics, indices, onset date and associated circulations, are examined and diagnosed for different climate systems, i.e., T106 and T106 × T255 (with a nudging process added) in the Chinese Academy of Meteorological Sciences climate system model (CAMS-CSM). The results indicate the general decreasing prediction skills of the model with the growing lead times. For lead times of 1–10 days, zonal winds at the lower (850 hPa) and higher (200 hPa) levels can be reasonably predicted, as well as the pseudo-equivalent potential temperatures at 850 hPa. Meanwhile, the prediction skill for the higher level generally shows a better performance than that for the lower level. The prediction capability is relatively weak during the circulation adjustment period before the monsoon onset, while a significant enhancement occurs after that. During the analyzed period of 2011–2020, the prediction of SCSSM onset date is mainly skillful in most years, while the year of 2015 shows a prediction result with at least six pentads earlier than the observation, which is subsequently taken as a failure case for further investigation. At the lower level, the model could not effectively predict the weakening and eastward withdrawal of the Western Pacific subtropical high and the shift in wind field during the SCSSM onset. As for the upper level, the rapid northward movement of the South Asia high and its establishment in the Indochina Peninsula are neither well captured. In addition, the models of T106 and T106 × T255 do not show significant differences in most cases, but the latter tends to be more skillful on the continent.