Shortwave Flux Research Articles

The analysis of pre-monsoon dust storm over Delhi using ground-based observations

Three major sequential widespread dust events were experienced in the northern parts of India in May 2018. A significant impact of these pre-monsoon dust storms on the aerosol characteristics over the Indian National capital region (NCR) has been studied using remotely sensed ceilometer and ground-based measurements at Indira Gandhi International airport, New Delhi, India. The results show that after each dust activity, the significant inclusion of dust aerosols loaded in the free troposphere. Consequently, the direct impact on the lower atmospheric parameters like increase in daily average temperature (by 4–5 K), stepped up (stepped down) diurnal cycles of longwave fluxes (shortwave fluxes), has been recorded within 15 days of dust span. Mainly, the adverse meteorological and radiation features noticed before the first dust storm (DS1), which pinpoints the sudden dust intrusion over NCR, Delhi. However, this dust storm has extensively impacted on the atmospheric vertical dust loading, surface boundary layer mechanisms, and socioeconomic way. Therefore, the detailed analysis of vertical dust distribution and its interaction with mid-tropospheric processes has been carried by using the vertical normalized attenuated backscatter coefficients accompanying the radiosonde observation. The aloft floating dust layer up to 3–4 km has been noticed even after shallow rainfall and persisted at almost the same height for the next 34 h due to low-level clouds. Meanwhile, the sub-dust layer below 1 km is formed due to local activity, which also sustains for a long time.

Observational evaluation of global climate model simulations of arctic sea ice and adjacent land pertaining to the radiative effects of frozen hydrometeors

This study explores the linkage of frozen hydrometeors (cloud ice and falling ice/snow) with sea ice and adjacent lands through surface energy budget using model-observation comparisons to quantify the roles of the falling ice radiative effects (FIREs) in determining the extent and thickness of Arctic sea ice and adjacent land surface radiation budget and land surface skin (Ts) and surface (SAT) temperatures. The Coupled Model Intercomparison Project Phase 5 (CMIP5) models without FIREs tend to produce underestimated downward longwave radiation, and overestimated shortwave downward radiation and surface albedo, resulting in too-cold skin temperature (TS) and surface air temperature (SAT) and overestimated sea ice concentration (SIC) and thickness (SIT). By comparing two simulations of late 20th Century climate from CESM1-CAM5 model with inclusion and exclusion of FIREs, it is found that TS, SAT, radiation, SIC, and SIT and their seasonal cycles are improved with the inclusion of FIREs. Exclusion of FIREs results in underestimated net downward longwave radiative flux, which is highly correlated with overestimated surface albedo, colder TS, and SAT with a confidence level at 99% (p < 1%). These biases in CESM1-CAM5 resemble those in CMIP5 models without FIREs. With the inclusion of FIREs, the SIC bias is reduced by 2%–15% in summer, while the SIT is improved up to 90% in winter despite little improvement in SIC. These findings suggest a potential link among the increased downward longwave flux, decreased downward shortwave flux, and decreased surface air and land surface temperatures locally, which then drives SIC melting and SIT thinning when FIREs are included relative to when FIREs are excluded. It is suggested that the roles played by FIREs over the Arctic regions are of the same order of importance as those over the Southern Oceans despite the differences in geography and impact of human activity.

Association of the occurrence of deep convective cloud cores with sea surface temperatures over the equatorial Indian and the western Pacific oceans

In the tropical region, convection is highly associated with sea surface temperature (SST). The convective cores of the deep convective clouds, which exclude the non-precipitating anvils, account for a significant fraction of tropical rainfall and strongly impact large-scale dynamics of the free troposphere. In the present study, association between the occurrence of deep convective cloud cores (DCCCs) and SST over the tropical region is examined using three years (2012–2014) brightness temperature (TB) data of the water vapour absorption channels of Sondeur Atmosphérique du Profil d’Humidité Intertropicale par Radiométrie (SAPHIR), aboard Megha-Tropiques satellite. Occurrence frequency of DCCCs (OFD) increases when SST increases above 26.5 ∘C. The increase in OFD is apparent up to 30.5 ∘C and decreases for the further increase in SST. The association between OFD with SST, surface latent heat flux, free tropospheric humidity, and downwelling shortwave flux are examined over two dedicated deep convective regions, namely the equatorial Indian Ocean (EIO) and the western Pacific Ocean (WPO), for all seasons by applying the lead-lag correlation. The present study shows that the response of DCCCs to SST is faster over the EIO than over the WPO. Over the EIO and the WPO, DCCCs lag SST by 7 days and 12 days, respectively. When the SST-DCCC relation is analysed after removing the response time or lag, occurrence of DCCCs increases with SST even above 30.5 ∘C. Though similar studies have been done with precipitation, the tropical DCCCs are attempted for the first time. The observed lags are a few days shorter than those derived for precipitation since the present method considers only DCCCs and excludes the adjoining anvils and stratiform precipitation.

Ensemble forecast experiments of summertime sea ice in the Arctic Ocean using the TOPAZ4 ice-ocean data assimilation system

Precise information on sea ice thickness (SIT) and its prediction at medium-range (2-week) timescale is crucial for the safe maritime navigation in the Arctic Ocean. In this study, we investigate the sensitivity of medium-range prediction skill of summertime SIT distribution in the Arctic marginal seas to atmospheric forecast data, using the 51-member ECMWF operational ensemble prediction system (EPS). For a synoptic-scale cyclone event occurred in July 5–6, 2015, two-week probabilistic forecast experiments were conducted with the TOPAZ4 ice-ocean forecast system, starting on 1st July. The ensemble correlation analysis between the forecast SIT and the meteorological parameters shows that the forecast error of SIT distribution is sensitive to the sea ice drift speed until 1-week, indicating that realistic sea ice drift improves the sea ice thickness prediction. On the other hand, beyond 1 week lead, the forecast error of SIT distribution is more sensitive to surface heat flux rather than sea ice drift. The surface heat flux signal is confined to the sea ice edge region, where the shortwave radiation flux is related to the SIT change through the sea ice melting process. The shortwave radiation flux in the sea ice edge is mostly determined by the sea ice distribution, suggesting that the skillful prediction of sea ice distribution, which is largely affected by synoptic-scale disturbance, at shorter lead times indirectly affects the medium-range forecast skill. A comparison of different ensemble perturbation techniques shows that the prediction skill is better at shorter lead times (up to 1 week), when using an atmospheric EPS rather than the random perturbations used in the operational forecast system, but the random perturbations are advantageous beyond 1 week. Thus, the application of the EPS to an ice-ocean coupled forecast system leads to a more precise sea ice prediction on medium-range timescale, which we expect to become of practical use for the optimum shipping route in the Arctic Ocean.

Sensitivity of Summertime Convection to Aerosol Loading and Properties in the United Arab Emirates

The Weather Research and Forecasting (WRF) model is used to investigate convection–aerosol interactions in the United Arab Emirates (UAE) for a summertime convective event. Both an idealized and climatological aerosol distributions are considered. The convection on 14 August 2013 was triggered by the low-level convergence of the cyclonic circulation associated with the Arabian Heat Low (AHL) and the daytime sea-breeze circulation. Numerical experiments reveal a high sensitivity to aerosol properties. In particular, replacing 20% of the rural aerosols by carbonaceous particles has a comparable impact on the surface radiative fluxes to increasing the aerosol loading by a factor of 10. In both cases, the UAE-averaged net shortwave flux is reduced by ~90 W m−2 while the net longwave flux increases by ~51 W m−2. However, when the aerosol composition is changed, WRF generates 20% more precipitation than when the aerosol loading is increased, due to a broader and weaker AHL. The surface downward and upward shortwave and upward longwave radiation fluxes are found to scale linearly with the aerosol loading. An increase in the amount of aerosols also leads to drier conditions and a delay in the onset of convection due to changes in the AHL.

Evaluation of CloudSat Radiative Kernels Using ARM and CERES Observations and ERA5 Reanalysis

AbstractDespite the widespread use of the radiative kernel technique for studying radiative feedbacks and radiative forcings, there has not been any systematic, observation‐based validation of the radiative kernel method. Here, we utilize observed and reanalyzed radiative fluxes and atmospheric profiles from the Atmospheric Radiation Measurement (ARM) program and ERA5 reanalysis to assess a set of observation‐based radiative kernels from CloudSat for six ARM sites. The CloudSat radiative kernels, convoluted with the ERA5 state variables, can almost perfectly reconstruct the monthly anomalies of shortwave (SW) and longwave (LW) radiative fluxes in ERA5 at the surface (SFC) and top‐of‐atmosphere (TOA) with correlations significantly being greater than 0.95. The biases of kernel‐estimated flux anomalies calculated using the ARM‐observed state variables can be more than twice as large when compared with the ARM‐observed surface flux anomalies and Clouds and Earth's Radiant Energy System observed anomalies at the TOA. Generally, clouds contribute to most (&gt;60%) of the variance of flux anomalies at Southern Great Plain (SGP), Tropical Western Pacific (TWP), and Eastern North Atlantic (ENA), and surface albedo dominates (&gt;69%) the variance of SW flux anomalies at North Slope of Alaska. The radiative kernels exhibit the lowest correlation (r∼[0.55,0.85]) when reconstructing SFC LW flux anomalies at SGP, TWP, and ENA, whose biases are related to the possibility that the kernels may not fully capture the characteristics associated with Madden‐Julian oscillation and El Niño‐Southern Oscillation at TWP and the presence of clouds at SGP and ENA.

Contribution of Changes in Snow Cover Extent to Shortwave Radiation Perturbations at the Top of the Atmosphere over the Northern Hemisphere during 2000–2019

Snow-induced radiative forcing (SnRF), defined as the instantaneous perturbation of the Earth’s shortwave radiation at the top of the atmosphere (TOA), results from variations in the terrestrial snow cover extent (SCE), and is critical for the regulation of the Earth’s energy budget. However, with the growing seasonal divergence of SCE over the Northern Hemisphere (NH) in the past two decades, novel insights pertaining to SnRF are lacking. Consequently, the contribution of SnRF to TOA shortwave radiation anomalies still remains unclear. Utilizing the latest datasets of snow cover, surface albedo, and albedo radiative kernels, this study investigated the distribution of SnRF over the NH and explored its changes from 2000 to 2019. The 20-year averaged annual mean SnRF in the NH was −1.13 ± 0.05 W m−2, with a weakening trend of 0.0047 Wm−2 yr−1 (p &lt; 0.01) during 2000–2019, indicating that an extra 0.094 W m−2 of shortwave radiation was absorbed by the Earth climate system. Moreover, changes in SnRF were highly correlated with satellite-observed TOA shortwave flux anomalies (r = 0.79, p &lt; 0.05) during 2000–2019. Additionally, a detailed contribution analysis revealed that the SnRF in snow accumulation months, from March to May, accounted for 58.10% of the annual mean SnRF variability across the NH. These results can assist in providing a better understanding of the role of snow cover in Earth’s climate system in the context of climate change. Although the rapid SCE decline over the NH has a hiatus for the period during 2000–2019, SnRF continues to follow a weakening trend. Therefore, this should be taken into consideration in current climate change models and future climate projections.

A study on diurnal microclimate hysteresis and plant morphology of a Buxus sempervirens using PIV, infrared thermography, and X-ray imaging

Plants modify the climate and provide natural cooling through transpiration. However, plant response is not only dependent on the atmospheric evaporative demand due to the combined effects of wind speed, air temperature, humidity, and solar radiation, but is also dependent on the water transport within the plant leaf-xylem-root system. These interactions result in a dynamic response of the plant where transpiration hysteresis can influence the cooling provided by the plant. Therefore, a detailed understanding of such dynamics is key to the development of appropriate mitigation strategies and numerical models. In this study, we unveil the diurnal dynamics of the microclimate of a Buxus sempervirens plant using multiple high-resolution non-intrusive imaging techniques. The wake flow field is measured using stereoscopic particle image velocimetry, the spatiotemporal leaf temperature history is obtained using infrared thermography, and additionally, the plant porosity is obtained using X-ray tomography. We find that the wake velocity statistics are not directly linked with the distribution of the porosity but depends mainly on the geometry of the plant foliage which generates the shear flow. The interaction between the shear regions and the upstream boundary layer profile is seen to have a dominant effect on the wake turbulent kinetic energy distribution. Furthermore, the leaf area density distribution has a direct impact on the short-wave radiative heat flux absorption inside the foliage where 50% of the radiation is absorbed in the top 20% of the foliage. This localized radiation absorption results in a high local leaf and air temperature. Furthermore, a comparison of the diurnal variation of leaf temperature and the net plant transpiration rate enabled us to quantify the diurnal hysteresis resulting from the stomatal response lag. The day of this plant is seen to comprise of four stages of climatic conditions: no-cooling, high-cooling, equilibrium, and decaying-cooling stages.

A Decade of Poland-AOD Aerosol Research Network Observations

The Poland-AOD aerosol research network was established in 2011 to improve aerosol–climate interaction knowledge and provide a real-time and historical, comprehensive, and quantitative database for the aerosol optical properties distribution over Poland. The network consists of research institutions and private owners operating 10 measurement stations and an organization responsible for aerosol model transport simulations. Poland-AOD collaboration provides observations of spectral aerosol optical depth (AOD), Ångstrom Exponent (AE), incoming shortwave (SW) and longwave (LW) radiation fluxes, vertical profiles of aerosol optical properties and surface aerosol scattering and absorption coefficient, as well as microphysical particle properties. Based on the radiative transfer model (RTM), the aerosol radiative forcing (ARF) and the heating rate are simulated. In addition, results from GEM-AQ and WRF-Chem models (e.g., aerosol mass mixing ratio and optical properties for several particle chemical components), and HYSPLIT back-trajectories are used to interpret the results of observation and to describe the 3D aerosol optical properties distribution. Results of Poland-AOD research indicate progressive improvement of air quality and at mospheric turbidity during the last decade. The AOD was reduced by about 0.02/10 yr (at 550 nm), which corresponds to positive trends in ARF. The estimated clear-sky ARF trend is 0.34 W/m2/10 yr and 0.68 W/m2/10 yr, respectively, at TOA and at Earth’s surface. Therefore, reduction in aerosol load observed in Poland can significantly contribute to climate warming.

Spatio-temporal distribution of aerosol direct radiative forcing over mid-latitude regions in north hemisphere estimated from satellite observations

An empirical method is used to estimate the aerosol direct radiative forcing (ADRF) over 20oN − 40oN regions from March 2000 to March 2019. The ADRF is calculated as the difference between the cloud-free sky and clean-sky (non-aerosol) radiative fluxes, which are fitted to an exponential function of the aerosol optical depth (AOD). The regional averaged ADRFs are negative (cooling effect) at the surface (SUR) and the top of atmosphere (TOA) and positive (warming effect) in the atmosphere (ATM). The spatial and temporal distributions of ADRF are closely linked to the spatio-temporal distributions of AOD. Higher AOD and stronger ADRF are found in spring (March to May) and summer (June to August). ADRFs are larger in regions with frequent sandstorm outbreaks and rapid economic growth since 2000 than other regions. The uncertainty of ADRF due to data source is 1.12 W/m2 at the surface and 0.91 W/m2 at the TOA according to the stochastic error propagation function. The ADRFs in our study regions show statistically significant but different changes of −0.074 W/m2 /year and 0.1 W/m2 /year at the surface during 2000 to 2009 and 2010 to 2019, respectively. Recent trend analysis also shows that the reduced aerosol contributes to the increasing short-wave flux about 0.32 W/m2 under the background of the global warming during the period from 2000 to 2019 in our study area, which indicates that it may alter the pattern of atmospheric circulation or enhance the global warming effect.

An Investigation on Seasonal and Diurnal Cycles of TOA Shortwave Radiations from DSCOVR/EPIC, CERES, MERRA-2, and ERA5

Reflected shortwave (SW) solar radiations at the top of atmosphere from Clouds and the Earth’s Radiant Energy System (CERES), Modern Era-Retrospective analysis for Research and Applications version 2 (MERRA-2), and ECMWF Reanalysis 5th Generation (ERA5) are examined to better understand their differences in spatial and temporal variations (seasonal and diurnal cycle timescale) with respect to the observations from the Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory (DSCOVR) satellite. Comparisons between two reanalyses (MERRA-2 and ERA5) and EPIC reveal that MERRA-2 has a generally larger deviation from EPIC than ERA5 in terms of the SW radiance and diurnal variability in all seasons, which can be attributed to larger cloud biases in MERRA-2. MERRA-2 produces more ice/liquid water content than ERA5 over the tropical warm pool, leading to positive SW biases in cloud and radiance, while both reanalyses underestimate the observed SW radiance from EPIC in the stratus-topped region off the western coast of US/Mexico in the boreal summer. Himalaya/Tibet region in the boreal spring/summer and the midlatitude Southern Hemisphere in the boreal winter are the regions where MERRA-2 and ERA5 deviate largely from EPIC, but their deviations have the opposite sign. Vertical structures of cloud ice/liquid water content explain reasonably well these contrasting differences between the two reanalyses. As two independent observations, CERES and EPIC agree well with each other in terms of the SW radiance maps, showing 2–3% mean absolute errors over the tropical midlatitudes. The CERES-EPIC consistency further confirms that the reanalyses still have challenges in representing the SW flux and its global distribution. In the CERES-EPIC observation differences, CERES slightly overestimates the diurnal cycle (as a function of local solar time) of the observed EPIC irradiance in the morning and underestimates it in the afternoon, while the opposite is the case in the reanalyses.

An investigation on the radiant heat balance for different urban tissues in Mediterranean climate: a case study

The outdoor radiant field is a key aspect to determine outdoor comfort conditions for humans, especially in urban areas. In order to unveil the dependence of the radiant field on the features of the urban fabrics, this study analyses the space distribution of the Mean Radiant Temperature (TMRT) and the radiant field in various urban tissues of the city of Catania (Italy) in a typical Mediterranean climate. The study is based on simulations through the Solar and LongWave Environmental Irradiance Geometry model (SOLWEIG) implemented in UMEP. Results show that the worst conditions occur in areas with moderately deep urban canyons, abundant impervious surfaces and lack of vegetation: here, the TMRT can easily reach 78 °C while in more than 80% of the area it exceeds 60 °C. By modelling the time trends of the shortwave and longwave radiant heat fluxes perceived by a pedestrian, it has been possible to observe that the highest contribution to the outdoor radiant field comes from the downward solar irradiance. However, the downward and upward longwave radiant flux closely follows: this suggests the importance of providing shading rather than using highly reflective surfaces that can exacerbate heat stress by means of the increased reflected shortwave radiation.

Evaluation of Reanalysis Datasets for Solar Radiation with In Situ Observations at a Location over the Gobi Region of Xinjiang, China

Solar radiation is the most important source of energy on the Earth. The Gobi area in the eastern Xinjiang region, due to its geographic location and climate characteristics, has abundant solar energy resources. In order to provide detailed scientific data supporting solar energy development in this area, we used ground-based data to evaluate the applicability of the five reanalysis data sources: the Clouds and the Earth’s Radiant Energy System (CERES), the European Center for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5), the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA2), and the Japanese 55-year Reanalysis (JRA-55). Our results indicated that the CERES data show underestimated short-wave radiation and overestimated long-wave radiation. The correlation coefficients (r) between the ERA5 dataset and the net long-wave and short-wave radiation in observation were 0.92 and 0.91, respectively, and the r between the MERRA2 dataset and the net long-wave and short-wave radiation in observation were both 0.88. The JRA-55 dataset overestimated the long-wave radiation flux and underestimated the short-wave radiation flux. The clearness index (kt) of all datasets was poor during autumn and winter, the ERA5 estimates were cloudy when the actual condition was sunny, while the JRA-55 estimates were sunny when the actual condition was cloudy. Overall, the radiation flux in the ERA5 dataset had the highest applicability in the Gobi region.

Global Daytime Mean Shortwave Flux Consistency Under Varying EPIC Viewing Geometries

One of the most crucial tasks of measuring top-of-atmosphere (TOA) radiative flux is to understand the relationships between radiances and fluxes, particularly for the reflected shortwave (SW) fluxes. The radiance-to-flux conversion is accomplished by constructing angular distribution models (ADMs). This conversion depends on solar-viewing geometries as well as the scene types within the field of view. To date, the most comprehensive observation-based ADMs are developed using the Clouds and the Earth’s Radiant Energy System (CERES) observations. These ADMs are used to derive TOA SW fluxes from CERES and other Earth radiation budget instruments which observe the Earth mostly from side-scattering angles. The Earth Polychromatic Imaging Camera (EPIC) onboard Deep Space Climate Observatory observes the Earth at the Lagrange-1 point in the near-backscattering directions and offers a testbed for the CERES ADMs. As the EPIC relative azimuth angles change from 168◦ to 178◦, the global daytime mean SW radiances can increase by as much as 10% though no notable cloud changes are observed. The global daytime mean SW fluxes derived after considering the radiance anisotropies at relative azimuth angles of 168◦ and 178◦ show much smaller differences (&amp;lt;1%), indicating increases in EPIC SW radiances are due mostly to changes in viewing geometries. Furthermore, annual global daytime mean SW fluxes from EPIC agree with the CERES equivalents to within 0.5 Wm−2 with root-mean-square errors less than 3.0 Wm−2. Consistency between SW fluxes from EPIC and CERES inverted from very different viewing geometries indicates that the CERES ADMs accurately quantify the radiance anisotropy and can be used for flux inversion from different viewing perspectives.

Phytoplankton Bloom Changes under Extreme Geophysical Conditions in the Northern Bering Sea and the Southern Chukchi Sea

The northern Bering Sea and the southern Chukchi Sea are undergoing rapid regional biophysical changes in connection with the recent extreme climate change in the Arctic. The ice concentration in 2018 was the lowest since observations began in the 1970s, due to the unusually warm southerly wind in winter, which continued in 2019. We analyzed the characteristics of spring phytoplankton biomass distribution under the extreme environmental conditions in 2018 and 2019. Our results show that higher phytoplankton biomass during late spring compared to the 18-year average was observed in the Bering Sea in both years. Their spatial distribution is closely related to the open water extent following winter-onset sea ice retreat in association with dramatic atmospheric conditions. However, despite a similar level of shortwave heat flux, the 2019 springtime biomass in the Chukchi Sea was lower than that in 2018, and was delayed to summer. We confirmed that this difference in bloom timing in the Chukchi Sea was due to changes in seawater properties, determined by a combination of northward oceanic heat flux modulation by the disturbance from more extensive sea ice in winter and higher surface net shortwave heat flux than usual.

Understanding the surface temperature response and its uncertainty to CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;, CH&amp;lt;sub&amp;gt;4&amp;lt;/sub&amp;gt;, black carbon, and sulfate

Abstract. Understanding the regional surface temperature responses to different anthropogenic climate forcing agents, such as greenhouse gases and aerosols, is crucial for understanding past and future regional climate changes. In modern climate models, the regional temperature responses vary greatly for all major forcing agents, but the causes of this variability are poorly understood. Here, we analyze how changes in atmospheric and oceanic energy fluxes due to perturbations in different anthropogenic climate forcing agents lead to changes in global and regional surface temperatures. We use climate model data on idealized perturbations in four major anthropogenic climate forcing agents (CO2, CH4, sulfate, and black carbon aerosols) from Precipitation Driver Response Model Intercomparison Project (PDRMIP) climate experiments for six climate models (CanESM2, HadGEM2-ES, NCAR-CESM1-CAM4, NorESM1, MIROC-SPRINTARS, GISS-E2). Particularly, we decompose the regional energy budget contributions to the surface temperature responses due to changes in longwave and shortwave fluxes under clear-sky and cloudy conditions, surface albedo changes, and oceanic and atmospheric energy transport. We also analyze the regional model-to-model temperature response spread due to each of these components. The global surface temperature response stems from changes in longwave emissivity for greenhouse gases (CO2 and CH4) and mainly from changes in shortwave clear-sky fluxes for aerosols (sulfate and black carbon). The global surface temperature response normalized by effective radiative forcing is nearly the same for all forcing agents (0.63, 0.54, 0.57, 0.61 K W−1 m2). While the main physical processes driving global temperature responses vary between forcing agents, for all forcing agents the model-to-model spread in temperature responses is dominated by differences in modeled changes in longwave clear-sky emissivity. Furthermore, in polar regions for all forcing agents the differences in surface albedo change is a key contributor to temperature responses and its spread. For black carbon, the modeled differences in temperature response due to shortwave clear-sky radiation are also important in the Arctic. Regional model-to-model differences due to changes in shortwave and longwave cloud radiative effect strongly modulate each other. For aerosols, clouds play a major role in the model spread of regional surface temperature responses. In regions with strong aerosol forcing, the model-to-model differences arise from shortwave clear-sky responses and are strongly modulated by combined temperature responses to oceanic and atmospheric heat transport in the models.

Long-Term Trend Comparison of Planetary Boundary Layer Height in Observations and CMIP6 Models over China

AbstractThe planetary boundary layer (PBL) plays an essential role in climate and air quality simulations. Nevertheless, large uncertainties remain in understanding the drivers for long-term trends of PBL height (PBLH) and its simulation. Here we combine the radiosonde data and reanalysis datasets to analyze PBLH long-term trends over China, and to further explore the performance of CMIP6 climate models in simulating these trends. Results show that the observed long-term “positive-to-negative” trend shift of PBLH is related to the variation in the surface upward sensible heat flux (SHFLX), and the SHFLX is further controlled by the synergistic effect of low cloud cover (LCC) and soil moisture (SM) changes. Variabilities in LCC and SM directly influence the energy balance via surface net downward shortwave flux (SWF) and the latent heat flux (LHFLX), respectively. The CMIP6 climate models, however, cannot reproduce the observed PBLH long-term trend shift over China. The CMIP6 results illustrate an overwhelming continuous downward PBLH trend during the 1979–2014 period, which is largely caused by the poor capability in simulating long-term variations of cloud radiative effect. Our results reveal that the long-term cloud radiative effect simulation is critical for CMIP6 models in reproducing the long-term trend of PBLH. This study highlights the importance of processes associated with LCC and SM in modulating PBLH long-term variations and calls attention to improve these processes in climate models in order to improve the PBLH long-term trend simulations.

Beyond Runaway: Initiation of the Post-runaway Greenhouse State on Rocky Exoplanets

Abstract The runaway greenhouse represents the ultimate climate catastrophe for rocky, Earth-like worlds: when the incoming stellar flux cannot be balanced by radiation to space, the oceans evaporate and exacerbate heating, turning the planet into a hot wasteland with a steam atmosphere overlying a possibly molten magma surface. The equilibrium state beyond the runaway greenhouse instellation limit depends on the radiative properties of the atmosphere and its temperature structure. Here, we use 1D radiative-convective models of steam atmospheres to explore the transition from the tropospheric radiation limit to the post-runaway climate state. To facilitate eventual simulations with 3D global circulation models, a computationally efficient band-gray model is developed, which is capable of reproducing the key features of the more comprehensive calculations. We analyze two factors that determine the equilibrated surface temperature of post-runaway planets. The infrared cooling of the planet is strongly enhanced by the penetration of the dry adiabat into the optically thin upper regions of the atmosphere. In addition, thermal emission of both shortwave and near-IR fluxes from the hot lower atmospheric layers, which can radiate through window regions of the spectrum, is quantified. Astronomical surveys of rocky exoplanets in the runaway greenhouse state may discriminate these features using multiwavelength observations.

Summer Cyclones and Their Association With Short-Term Sea Ice Variability in the Pacific Sector of the Arctic

We investigate the effects of summer cyclones on sea ice within the Pacific sector of the Arctic by analyzing the surface energy flux and wind forcing from a large sample of cyclones. Consistent with recent studies, we find that cyclones earlier in the melt season tend to be associated with less 1–5 day sea ice loss than what occurs in the absence of cyclones. In contrast, cyclones later in the melt season slightly accelerate the 1-day sea ice loss. The reduced ice loss following cyclones in June is primarily due to increased cloud cover reducing the net shortwave flux at the surface. Clouds associated with cyclones in July and August also reduce the net shortwave flux at the surface, but only over high-concentration sea ice. Southerly winds associated with August cyclones increase both the negative local sea ice advection and the surface heat flux, particularly for the low concentration sea ice that is prevalent in August. Sea ice advection and surface heat flux are the only two factors we examined that can explain the enhanced ice loss on cyclone days in August. We also examined two cyclone cases that impacted sea ice in the East Siberian Sea in June 2012 and August 2016, and found for both cyclones that the sensible heat flux is the largest positive anomalous forcing and the shortwave radiative flux is the largest negative anomalous forcing. Similar to the large sample of cyclones, the shortwave flux has a stronger relationship to local changes in SIC in June than in August. Part of the reason for this is that the cloud shortwave radiative forcing during the August cyclone is 26% weaker than during the June cyclone. In an area averaged sense, the anomalous surface energy and wind forcing of both cyclone cases is similar in magnitude, yet the August cyclone is followed by a greater reduction in both sea ice area and mean sea ice concentration than the June cyclone. This result emphasizes how the underlying sea ice characteristics largely determine cyclone impacts on sea ice on short time scales.

Understanding Top‐of‐Atmosphere Flux Bias in the AeroCom Phase III Models: A Clear‐Sky Perspective

AbstractBiases in aerosol optical depths (AOD) and land surface albedos in the AeroCom models are manifested in the top‐of‐atmosphere (TOA) clear‐sky reflected shortwave (SW) fluxes. Biases in the SW fluxes from AeroCom models are quantitatively related to biases in AOD and land surface albedo by using their radiative kernels. Over ocean, AOD contributes about 25% to the S–N mean SW flux bias for the multi‐model mean (MMM) result. Over land, AOD and land surface albedo contribute about 40% and 30%, respectively, to the S–N mean SW flux bias for the MMM result. Furthermore, the spatial patterns of the SW flux biases derived from the radiative kernels are very similar to those between models and CERES observation, with the correlation coefficient of 0.6 over ocean and 0.76 over land for MMM using data of 2010. Satellite data used in this evaluation are derived independently from each other, consistencies in their bias patterns when compared with model simulations suggest that these patterns are robust. This highlights the importance of evaluating related variables in a synergistic manner to provide an unambiguous assessment of the models, as results from single parameter assessments are often confounded by measurement uncertainty. Model biases in land surface albedos can and must be corrected to accurately calculate TOA flux. We also compare the AOD trend from three models with the observation‐based counterpart. These models reproduce all notable trends in AOD except the decreasing trend over eastern China and the adjacent oceanic regions due to limitations in the emission data set.