Net Shortwave Flux Research Articles

Uncovering Interdecadal Pacific Oscillation’s Dominance in Shaping Low-Frequency Sea Level Variability in the South China Sea

The low-frequency sea level variability in the South China Sea (SCS) is examined using high-resolution regional ocean model simulations that span the last six decades. The analysis reveals interdecadal oscillations with a periodicity of 12–13 years as the dominant mode of sea level variability in the SCS. The fluctuations in the Luzon Strait transport (LST) are identified as primary drivers of interannual to interdecadal sea level variability, rather than atmospheric forcing within the SCS. Fourier spectrum analysis is employed to investigate the association between SCS sea level variability and the Interdecadal Pacific Oscillation (IPO), using principal components of SCS sea surface height anomalies, wind stress curl, wind stress components, net short wave flux, as well as the LST and various climate indices. The variations in the SCS sea level are driven by the IPO, which modifies the LST and ocean heat content, impacting the steric sea level.

Shortwave Radiative Flux Variability Through the Lens of the Pacific Decadal Oscillation

AbstractThe variability of the shortwave radiative fluxes at the surface and top of atmosphere (TOA) is examined in a pre‐industrial modeling setup using the Pacific Decadal Oscillation (PDO) as a possible pacemaker of atmospheric decadal‐scale variability. Within models from the Coupled Model Intercomparison Project—Phase 6, downwelling shortwave radiation at the surface, the net shortwave fluxes at the surface and TOA, as well as cloud radiative effects show remarkably similar patterns associated with the PDO. Through ensemble simulations designed with a pure PDO pattern in the North Pacific only, we show that the PDO relates to about 20%–40% of the unforced year‐to‐year variability of these shortwave fluxes over the Northern Hemispheric continents. The sea surface temperature imprint on shortwave‐flux variability over land is larger for spatially aggregated time series as compared to smaller areas, due to the blurring effect of small‐scale atmospheric noise. The surface and TOA radiative flux anomalies associated with the PDO index range of [−1.64; 1.64] are estimated to reach up to ±6 Wm−2 for North America, ∓3 Wm−2 for India and ±2 Wm−2 for Europe. We hypothesize that the redistribution of clouds in response to a North Pacific PDO anomaly can impact the South Pacific and North Atlantic SSTs.

An asymmetric relationship between Tibetan Plateau surface temperature regimes and oceanic–atmospheric circulations

AbstractAs a high‐altitude region, the Tibetan Plateau (TP) is sensitive to climate change. Since the 1960s, the TP has experienced significant spatial‐variant warming, vital to changing the region's terrestrial ecosystem. To understand surface air temperature (SAT) regimes over the TP, we investigated their link with teleconnections using observational and reanalysis datasets from 1982 to 2019. We employed wavelet analysis, empirical orthogonal teleconnection (EOT), partial regression, canonical correlation analysis and t test. Our results indicate an asymmetrical connection between teleconnections and SAT, with Atlantic Multidecadal Oscillation (AMO) predominant over the northern TP. In contrast, the El Niño–Southern Oscillation (ENSO) is more prevalent in the southern part. The spatial variance was potentially related to windspeed, total cloud cover (TCC), net longwave radiation (NLWR), net shortwave radiation (NSWR), cloud‐forcing net longwave flux (CF‐NLWF) and cloud‐forcing net shortwave flux (CF‐NLWF) anomalies. ENSO and Pacific Decadal Oscillation (PDO) modulate cloud cover variation in the southern TP, mainly the southwest, via the monsoon and subtropical westerlies. In the north, cloud cover variation is related to the moisture transported by the AMO‐induced prevailing westerlies. The study examined the complex interplay between teleconnections, SAT and cloud radiative forcing by examining the cloud cover and radiation balance relationship. These findings contribute to understanding climate change impacts on the TP, informing climate projections and guiding adaptation strategies by elucidating the relationship between TP temperature variation and oceanic–atmospheric oscillation patterns.

Assessment of Top of Atmosphere, Atmospheric and Surface Energy Budgets in CMIP6 Models on Regional Scales

AbstractWe examine top of atmosphere (TOA), atmospheric, and surface energy budget components of 53 CMIP6 models for the period 2000–2009 on regional scales with respect to two reference data sets: the NASA Energy and Water cycle Study (NEWS), from which we adopt the regional decomposition, and the Clouds and the Earth's Radiant Energy System (CERES) Energy Balanced and Filled (EBAF). Focusing on regional scale, CMIP6 models tend to have more energy entering or less energy leaving the climate systems at TOA over the Northern Hemisphere land, Southern Hemisphere ocean and the polar regions compared to CERES EBAF, while the contrary applies in other regions. Atmospheric net shortwave and longwave fluxes both tend to be underestimated in CMIP6 models as compared to EBAF, with substantial regional differences. Regional surface radiative fluxes as reported by NEWS and EBAF can differ substantially. Nevertheless, robust regional biases exist in CMIP6. Surface upward shortwave radiation is overestimated by 43 (81%) models over Eurasia. For almost all surface radiative flux components over the North Atlantic and Indian Ocean, there are at least 21 (40%) models which fall outside the NEWS uncertainty range. Latent heat flux is overestimated over most of the land and ocean regions while firm conclusions for sensible heat flux remain elusive due to discrepancies between different reference data sets. Compared to CMIP5, there is an overall improvement in CMIP6 on regional scale. Still, substantial deficiencies and spreads on regional scale remain, which are potentially translated into an inadequate simulation of atmospheric dynamics or hydrological cycle.

Heat budget of lake ice during a complete seasonal cycle in lake Hanzhang, northeast China

The seasonal cycle of ice formation and breakup in Lake Hanzhang, China, was monitored during the winter of 2020–2021 using a float equipped with meteorological, hydrological, and optical instruments. This lake is located in mid-latitude cold and dry climate zone. We categorized the ice season into growth, equilibrium, and melting stages. The thickness of ice increased by an average of 0.7 cm day−1 at the bottom of the ice during the growth stage, and during the equilibrium stage it was stable at 35.0 ± 0.5 cm. During the melting stage, the internal melting dominated the ice ablation (1.0 cm day−1), followed by bottom melting (0.45 cm day−1) and surface melting (0.25 cm day−1). The net short-wave and long-wave radiative fluxes dominated the heat budget throughout the seasonal cycle. Sublimation was 1.1 cm, 73% of that in the growth stage. During the melting stage, the absorbed short-wave radiative flux promoted internal melting, enlarged the porosity, and enhanced further surface melting. The frequent negative air temperature during nighttime hindered the phase changes of the lake ice surface layer. In addition, the upward sensible heat flux in the lake water body increased from 7.8 to 14.5 W m−2 due to the increased light transmittance by lake ice. The heat balance and heat fluxes in ice-covered lakes in mid-latitude dry climate have rarely been explored. The results increase the knowledge of lake ice geophysics and are also useful for calibration and validation of lake ice models.

Toward a more realistic representation of surface albedo in NASA CERES-derived surface radiative fluxes

Accurate multidecadal radiative flux records are vital to understand Arctic amplification and constrain climate model uncertainties. Uncertainty in the NASA Clouds and the Earth’s Radiant Energy System (CERES)-derived irradiances is larger over sea ice than any other surface type and comes from several sources. The year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic provides a rare opportunity to explore uncertainty in CERES-derived radiative fluxes. First, a systematic and statistically robust assessment of surface shortwave and longwave fluxes was conducted using in situ measurements from MOSAiC flux stations. The CERES Synoptic 1degree (SYN1deg) product overestimates the downwelling shortwave flux by +11.40 Wm–2 and underestimates the upwelling shortwave flux by –15.70 Wm–2 and downwelling longwave fluxes by –12.58 Wm–2 at the surface during summer. In addition, large differences are found in the upwelling longwave flux when the surface approaches the melting point (approximately 0°C). The biases in downwelling shortwave and longwave fluxes suggest that the atmosphere represented in CERES is too optically thin. The large negative bias in upwelling shortwave flux can be attributed in large part to lower surface albedo (–0.15) in satellite footprint relative to surface sensors. Additionally, the results show that the spectral surface albedo used in SYN1deg overestimates albedo in visible and mid-infrared bands. A series of radiative transfer model perturbation experiments are performed to quantify the factors contributing to the differences. The CERES-MOSAiC broadband albedo differences (approximately 20 Wm–2) explain a larger portion of the upwelling shortwave flux difference than the spectral albedo shape differences (approximately 3 Wm–2). In addition, the differences between perturbation experiments using hourly and monthly MOSAiC surface albedo suggest that approximately 25% of the sea ice surface albedo variability is explained by factors not correlated with daily sea ice concentration variability. Biases in net shortwave and longwave flux can be reduced to less than half by adjusting both albedo and cloud inputs toward observed values. The results indicate that improvements in the surface albedo and cloud data would substantially reduce the uncertainty in the Arctic surface radiation budget derived from CERES data products.

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.

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.

Ozone-aerosol and land use reversed temperature increase over some northern mid-latitude regions between the 20th century and the Little Ice Age based on the CESM-LME

Global warming is a widely concerned topic, and the surface temperature has shown an accelerated warming trend during the past several decades. From the perspective of a longer time scale, the 20th century (1900–2000) could be the warmest period in the last millennium, and the global or hemispheric averaged temperature over this period is higher than that over other centuries, particularly compared with that over the Little Ice Age (LIA; 1450–1850). However, we recently found that, in the reconstruction, the 20th-century temperature over some northern mid-latitude regions could be significantly lower than that during the LIA, which contradicts our previous perceptions regarding global warming. Modeling results from the Last Millennium Ensemble Project also reproduce a similar phenomenon, that is, the 20th-century cooling over some northern mid-latitude regions (CNMR). The simulated CNMR can be found in all four seasons. Further analysis indicates that the cooling effects from ozone-aerosol and land use forcings, overcoming greenhouse gas and solar forcing induced warming, play dominant roles in causing the CNMR. The ozone-aerosol forcing reduces the surface net shortwave flux through both direct aerosol–radiation interaction and atmosphere–cloud feedback, while the land use forcing causes negative net shortwave flux anomalies through modulation of surface albedo. Overall, the ozone-aerosol and land use forcings shape the CNMR phenomenon by inducing anomalous surface net shortwave flux, with the ozone-aerosol forcing playing a dominant role. This study highlights the important influences of ozone-aerosol and land use cooling effects on local climate.

Validation of Landsat-8 satellite-derived radiative energy fluxes using wireless sensor network data over Beas River basin, India

ABSTRACT In the present paper, spatio-temporal variability in surface radiative energy fluxes has been estimated for snow/ice-covered Beas River basin, lower Western Himalaya, India using remote sensing technology and evaluated with wireless sensor network (WSN) collected data at various elevation levels. Surface energy fluxes are derived using Landsat-8 satellite images and digital elevation model (DEM) at fine spatial resolution (~30-m) during clear-sky days of the year 2016–2017. RMSE have been estimated in incoming shortwave, incoming longwave, outgoing longwave, net shortwave and net radiation flux and observed to be ~5%, ~ 6.3%, ~2.4%, ~18.9%, and ~28.3% of the respective mean values. Landsat-8 images in conjunction with DEM have shown the potential to retrieve variability in surface radiative energy fluxes at fine resolution in mountain terrain. Additionally, temporal variability in radiative radiation fluxes have also been explored on different elevation ranges and aspects slopes. The high energy fluxes have been estimated on southern slopes during analysis as compared to northern slopes in the present study. The paper appears to be the first for reporting net radiation flux for Himalayan snow cover at 30-m spatial resolution. The satellite-derived energy fluxes may be valuable in various applications associated with climatology, hydrology, wet-snow avalanche detection, land use land cover, mass balance, ecology, etc., especially in the absence of in situ data.

Surface Radiative Flux Bias Reduction Through Regionally Varying Cloud Fraction Parameter Nudging in a Global Coupled Forecast System

AbstractA simple parameter nudging procedure is described that systematically reduces near‐analysis time errors in the surface net shortwave flux in the Navy ESPC (Earth System Prediction Capability) system, a global coupled forecast system that is the product of a continuing development effort at the U. S. Naval Research Laboratory. The procedure generates geographically varying perturbations to one of the cloud fraction parameters in the atmospheric model component of the system during the data assimilation cycle, resulting in large improvements in near‐analysis time surface net shortwave flux biases. After a several week spin‐up period, the global RMSE of the succeeding 10‐day mean bias computed for lead times of 6–12 hours is reduced by 40 percent. Results from application of the approach in a series of 45‐day integrations show that improvements are realized at longer forecast lead times as well. The global RMSE of the surface net shortwave flux averaged over these integrations improves by 37 percent for lead times from 1–5 days, decreasing to 18 percent for lead times from 31–45 days. The corresponding longwave flux errors are slightly degraded, ranging from a 2 percent increase for lead times from 1–5 days to a 0.5 percent increase for lead times from 31–45 days. Global‐mean reductions in ground and sea surface temperature errors are obtained through most of the 45‐day integration period due to improvements over ocean and polar regions. Potential steps for extension and operational application of the method are discussed.

An evaluation of the Arctic clouds and surface radiative fluxes in CMIP6 models

To assess the performances of state-of-the-art global climate models on simulating the Arctic clouds and surface radiation balance, the 2001–2014 Arctic Basin surface radiation budget, clouds, and the cloud radiative effects (CREs) in 22 coupled model intercomparison project 6 (CMIP6) models are evaluated against satellite observations. For the results from CMIP6 multi-model mean, cloud fraction (CF) peaks in autumn and is lowest in winter and spring, consistent with that from three satellite observation products (CloudSat-CALIPSO, CERES-MODIS, and APP-x). Simulated CF also shows consistent spatial patterns with those in observations. However, almost all models overestimate the CF amount throughout the year when compared to CERES-MODIS and APP-x. On average, clouds warm the surface of the Arctic Basin mainly via the longwave (LW) radiation cloud warming effect in winter. Simulated surface energy loss of LW is less than that in CERES-EBAF observation, while the net surface shortwave (SW) flux is underestimated. The biases may result from the stronger cloud LW warming effect and SW cooling effect from the overestimated CF by the models. These two biases compensate each other, yielding similar net surface radiation flux between model output (3.0 W/m2) and CERES-EBAF observation (6.1 W/m2). During 2001–2014, significant increasing trend of spring CF is found in the multi-model mean, consistent with previous studies based on surface and satellite observations. Although most of the 22 CMIP6 models show common seasonal cycles of CF and liquid water path/ice water path (LWP/IWP), large inter-model spreads exist in the amounts of CF and LWP/IWP throughout the year, indicating the influences of different cloud parameterization schemes used in different models. Cloud Feedback Model Intercomparison Project (CFMIP) observation simulator package (COSP) is a great tool to accurately assess the performance of climate models on simulating clouds. More intuitive and credible evaluation results can be obtained based on the COSP model output. In the future, with the release of more COSP output of CMIP6 models, it is expected that those inter-model spreads and the model-observation biases can be substantially reduced. Longer term active satellite observations are also necessary to evaluate models’ cloud simulations and to further explore the role of clouds in the rapid Arctic climate changes.

Estimation of the distribution of the total net radiative flux from satellite and automatic weather station data in the Upper Blue Nile basin, Ethiopia

Net radiation is an important factor in studies of land–atmosphere processes, water resource management, and global climate change. This is particularly true for the Upper Blue Nile (UBN) basin, where significant parts of the basin are dry and evapotranspiration (ET) is a major mechanism for water loss. However, net radiation has not yet been appropriately parameterized in the basin. In this study, we estimated the instantaneous distribution of the net radiation flux in the basin using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra satellite and Automatic Weather Station (AWS) data. Downward shortwave radiation and air temperature usually vary with topography, so we applied residual kriging spatial interpolation techniques to convert AWS data for point locations into gridded surface data. Simulated net radiation outputs were validated through comparison with independent field measurements. Validation results show that our method successfully reproduced the downward shortwave, upward shortwave, and net radiation fluxes. Using AWS data and residual kriging spatial interpolation techniques makes our results robust and comparable to previous works that used satellite data at a finer spatial resolution than MODIS. The estimated net shortwave, longwave, and total radiation fluxes were in close agreement with ground truth measurements, with mean bias (MB) values of − 14.84, 5.7, and 20.53 W m−2 and root mean square error (RMSE) values 83.43, 32.54, and 78.07 W m−2, respectively. The method presented here has potential applications in research focused on energy balance, ET estimation, and weather prediction for regions with similar physiographic features to those of the Nile basin.

Ensemble daily simulations for elucidating cloud–aerosol interactions under a large spread of realistic environmental conditions

Abstract. Aerosol effects on cloud properties and the atmospheric energy and radiation budgets are studied through ensemble simulations over two month-long periods during the NARVAL campaigns (Next-generation Aircraft Remote-Sensing for Validation Studies, December 2013 and August 2016). For each day, two simulations are conducted with low and high cloud droplet number concentrations (CDNCs), representing low and high aerosol concentrations, respectively. This large data set, which is based on a large spread of co-varying realistic initial conditions, enables robust identification of the effect of CDNC changes on cloud properties. We show that increases in CDNC drive a reduction in the top-of-atmosphere (TOA) net shortwave flux (more reflection) and a decrease in the lower-tropospheric stability for all cases examined, while the TOA longwave flux and the liquid and ice water path changes are generally positive. However, changes in cloud fraction or precipitation, that could appear significant for a given day, are not as robustly affected, and, at least for the summer month, are not statistically distinguishable from zero. These results highlight the need for using a large sample of initial conditions for cloud–aerosol studies for identifying the significance of the response. In addition, we demonstrate the dependence of the aerosol effects on the season, as it is shown that the TOA net radiative effect is doubled during the winter month as compared to the summer month. By separating the simulations into different dominant cloud regimes, we show that the difference between the different months emerges due to the compensation of the longwave effect induced by an increase in ice content as compared to the shortwave effect of the liquid clouds. The CDNC effect on the longwave flux is stronger in the summer as the clouds are deeper and the atmosphere is more unstable.

Radiative Effect of Clouds at Ny-Ålesund, Svalbard, as Inferred from Ground-Based Remote Sensing Observations

AbstractFor the first time, the cloud radiative effect (CRE) has been characterized for the Arctic site Ny-Ålesund, Svalbard, Norway, including more than 2 years of data (June 2016–September 2018). The cloud radiative effect, that is, the difference between the all-sky and equivalent clear-sky net radiative fluxes, has been derived based on a combination of ground-based remote sensing observations of cloud properties and the application of broadband radiative transfer simulations. The simulated fluxes have been evaluated in terms of a radiative closure study. Good agreement with observed surface net shortwave (SW) and longwave (LW) fluxes has been found, with small biases for clear-sky (SW: 3.8 W m−2; LW: −4.9 W m−2) and all-sky (SW: −5.4 W m−2; LW: −0.2 W m−2) situations. For monthly averages, uncertainties in the CRE are estimated to be small (~2 W m−2). At Ny-Ålesund, the monthly net surface CRE is positive from September to April/May and negative in summer. The annual surface warming effect by clouds is 11.1 W m−2. The longwave surface CRE of liquid-containing cloud is mainly driven by liquid water path (LWP) with an asymptote value of 75 W m−2 for large LWP values. The shortwave surface CRE can largely be explained by LWP, solar zenith angle, and surface albedo. Liquid-containing clouds (LWP > 5 g m−2) clearly contribute most to the shortwave surface CRE (70%–98%) and, from late spring to autumn, also to the longwave surface CRE (up to 95%). Only in winter are ice clouds (IWP > 0 g m−2; LWP < 5 g m−2) equally important or even dominating the signal in the longwave surface CRE.

Evaluation of Six Atmospheric Reanalyses over Arctic Sea Ice from Winter to Early Summer

AbstractThis study evaluates the performance of six atmospheric reanalyses (ERA-Interim, ERA5, JRA-55, CFSv2, MERRA-2, and ASRv2) over Arctic sea ice from winter to early summer. The reanalyses are evaluated using observations from the Norwegian Young Sea Ice campaign (N-ICE2015), a 5-month ice drift in pack ice north of Svalbard. N-ICE2015 observations include surface meteorology, vertical profiles from radiosondes, as well as radiative and turbulent heat fluxes. The reanalyses simulate surface analysis variables well throughout the campaign, but have difficulties with most forecast variables. Wintertime (January–March) correlation coefficients between the reanalyses and observations are above 0.90 for the surface pressure, 2-m temperature, total column water vapor, and downward longwave flux. However, all reanalyses have a positive wintertime 2-m temperature bias, ranging from 1° to 4°C, and negative (i.e., upward) net longwave bias of 3–19 W m−2. These biases are associated with poorly represented surface inversions and are largest during cold-stable periods. Notably, the recent ERA5 and ASRv2 datasets have some of the largest temperature and net longwave biases, respectively. During spring (April–May), reanalyses fail to simulate observed persistent cloud layers. Therefore they overestimate the net shortwave flux (5–79 W m−2) and underestimate the net longwave flux (8–38 W m−2). Promisingly, ERA5 provides the best estimates of downward radiative fluxes in spring and summer, suggesting improved forecasting of Arctic cloud cover. All reanalyses exhibit large negative (upward) residual heat flux biases during winter, and positive (downward) biases during summer. Turbulent heat fluxes over sea ice are simulated poorly in all seasons.

Inter-relationship between subtropical Pacific sea surface temperature, Arctic sea ice concentration, and North Atlantic Oscillation in recent summers

The inter-relationship between subtropical western–central Pacific sea surface temperatures (STWCPSST), sea ice concentrations in the Beaufort Sea (SICBS), and the North Atlantic Oscillation (NAO) in summer are investigated over the period 1980–2016. It is shown that the Arctic response to the remote impact of the Pacific SST is more dominant in recent summers, leading to a frequent occurrence of the negative phase of the NAO following the STWCPSST increase. Lag–correlations of STWCPSST positive (negative) anomalies in spring with the negative (positive) NAO and SICBS loss (recovery) in summer have increased over the last two decades, reaching r = 0.4–0.5 with significance at the 5 percent level. Both observations and the atmospheric general circulation model experiments suggest that the positive STWCPSST anomaly and subsequent planetary-scale wave propagation act to increase the Arctic upper-level geopotential heights and temperatures in the following season. This response extends to Greenland, providing favorable conditions for developing the negative phase of the NAO. Connected with this atmospheric response, SIC and surface albedo decrease with an increase in the surface net shortwave flux over the Beaufort Sea. Examination of the surface energy balance (radiative and turbulent fluxes) reveals that surplus energy that can heat the surface increases over the Arctic, enhancing the SIC reduction.

CAUSES: On the Role of Surface Energy Budget Errors to the Warm Surface Air Temperature Error Over the Central United States

AbstractMany weather forecast and climate models simulate warm surface air temperature (T2m) biases over midlatitude continents during the summertime, especially over the Great Plains. We present here one of a series of papers from a multimodel intercomparison project (CAUSES: Cloud Above the United States and Errors at the Surface), which aims to evaluate the role of cloud, radiation, and precipitation biases in contributing to the T2m bias using a short‐term hindcast approach during the spring and summer of 2011. Observations are mainly from the Atmospheric Radiation Measurement Southern Great Plains sites. The present study examines the contributions of surface energy budget errors. All participating models simulate too much net shortwave and longwave fluxes at the surface but with no consistent mean bias sign in turbulent fluxes over the Central United States and Southern Great Plains. Nevertheless, biases in the net shortwave and downward longwave fluxes as well as surface evaporative fraction (EF) are contributors to T2m bias. Radiation biases are largely affected by cloud simulations, while EF bias is largely affected by soil moisture modulated by seasonal accumulated precipitation and evaporation. An approximate equation based upon the surface energy budget is derived to further quantify the magnitudes of radiation and EF contributions to T2m bias. Our analysis ascribes that a large EF underestimate is the dominant source of error in all models with a large positive temperature bias, whereas an EF overestimate compensates for an excess of absorbed shortwave radiation in nearly all the models with the smallest temperature bias.

Cloud–Atmospheric Boundary Layer–Surface Interactions on the Greenland Ice Sheet during the July 2012 Extreme Melt Event

Regional model simulations of the 10–13 July 2012 extreme melt event over the Greenland Ice Sheet (GIS) are used to investigate how low-level liquid-bearing clouds impact surface energy fluxes, and therefore the energy available for melt. A sensitivity study in which the radiation code is modified so that cloud liquid and ice do not emit, absorb, or reflect radiation is used to identify cloud impacts beyond the cloud radiative effect. It is found that Arctic mixed-phase stratocumuli are not produced in the sensitivity experiment, highlighting that cloud radiative fluxes are required to maintain the clouds. A number of feedbacks are found that damp the warming effect of the clouds. Thin mixed-phase clouds increase the downward longwave fluxes by 100 W m−2, but upward daytime surface longwave fluxes increase by 20 W m−2 (60 W m−2 at night) and net shortwave fluxes decrease by 40 W m−2 (partially due to a 0.05 increase in surface albedo), leaving only 40 W m−2 available for melt. This 40 W m−2 is distributed between the turbulent and conductive ground fluxes, so it is only at times of weak turbulent fluxes (i.e., at night or during melt) that this energy goes into the conductive ground flux, providing energy for melt. From these results it is concluded that it is the integrated impact of the clouds over the diurnal cycle (the preconditioning of the snowpack by the clouds at night) that made melt possible during this 3-day period. These findings are extended to understand the pattern of melt observed over the GIS.

Impact of anthropogenic aerosols from global, East Asian, and non-East Asian sources on East Asian summer monsoon system

The impact of the total effects due to anthropogenic aerosols from global, East Asian, and non-East Asian sources on East Asian summer monsoon (EASM) system is studied using an aerosol-climate online model BCC_AGCM2.0.1_CUACE/Aero. The results show that the summer mean net all-sky shortwave fluxes averaged over East Asian monsoon region (EAMR) at the top of the atmosphere (TOA) and surface reduce by 4.8 and 5.0Wm−2, respectively, due to the increases of global aerosol emissions in 2000 relative to 1850. Changes in radiations and their resulting changes in heat and water transport and cloud fraction contribute together to the surface cooling over EAMR in summer. The increases in global anthropogenic aerosols lead to a decrease of 2.1K in summer mean surface temperature and an increase of 0.4hPa in summer mean surface pressure averaged over EAMR, respectively. It is shown that the changes in surface temperature and pressure are significantly larger over land than ocean, thus decreasing the contrast of land-sea surface temperature and pressure. This results in the marked anomalies of north and northeast winds over eastern and southern China and the surrounding oceans in summer, thereby weakening the EASM. The summer mean precipitation averaged over the EAMR reduces by 12%. The changes in non-East Asian aerosol emissions play a more important role in inducing the changes of local temperature and pressure, and thus significantly exacerbate the weakness of the EASM circulation due to local aerosol changes. The weakening of circulation due to both is comparable, and even the effect of non-local aerosols is larger in individual regions. The changes of local and non-local aerosols contribute comparably to the reductions in precipitation over oceans, whereas cause opposite changes over eastern China. Our results highlight the importance of aerosol changes outside East Asia in the impact of the changes of anthropogenic aerosols on EASM.