Longwave Flux Research Articles

Field assessment of winter outdoor 3-D radiant environment and its impact on thermal comfort in a severely cold region

According to the Code for Design of Civil Buildings (GB 50352-2005), the severely cold region of China is defined as the area where the monthly mean air temperature is lower than or equal to −10 °C in January, and is lower than or equal to 25 °C in July, and mean relative humidity is higher than or equal to 50% in July. This study investigates outdoor 3-D short- and long-wave radiant flux densities (Ki and Li) from six perpendicular directions, and their effects on human thermal comfort during winter daytime in a severely cold region of China. Mean radiant temperature Tmrt, the representative parameter of the radiant environment, was determined by the “six-directional method”. Physiologically Equivalent Temperature PET, and Universal Thermal Climate Index UTCI were used to quantify denizens' perception of the thermal environment, particularly the response to the outdoor radiant environment. Results showed that building obstacles significantly influenced Ki and Li components, and thus Tmrt, and human thermal comfort and stress. The absorbed long-wave radiant flux densities by human body especially those from the horizontal directions primarily affected the magnitude of Tmrt, while the absorbed short-wave radiant flux densities by human body mainly governed the fluctuation of Tmrt. Furthermore, a simplified method of estimating Tmrt for the severely cold region was obtained from two representative radiant variables. The consideration of Tmrt as an independent variable to represent the radiant environment can be used to accurately estimate PET and UTCI in winter in the severely cold region.

The Role of Clouds and Surface Heat Fluxes in the Maintenance of the 2013–2016 Northeast Pacific Marine Heatwave

AbstractStarting in late 2013, the Northeast (NE) Pacific Ocean experienced anomalously warm sea surface temperatures (SSTs) that persisted for over 2 years. This marine heatwave, known as “the Blob,” produced many devastating ecological impacts with socioeconomic implications for coastal communities. The warm waters observed during the NE Pacific 2013/2016 marine heatwave altered the surface energy balance and disrupted ocean–atmosphere interactions in the region. In principle, ocean–atmosphere interactions following the formation of the marine heatwave could have perpetuated warm SSTs through a positive SST‐cloud feedback. The actual situation was more complicated. While reanalysis data show a decrease in boundary layer cloud fraction and an increase in downward shortwave radiative flux at the surface coincident with warm SSTs, this was accompanied by an increase in longwave radiative fluxes at the surface, as well as an increase in sensible and latent heat fluxes out of the ocean mixed layer. The result is a small negative net heat flux anomaly (compared to the anomalies of the individual terms contributing to the net heat flux). This provides new information about the midlatitude ocean–atmosphere system while it was in a perturbed state. More specifically, a mixed layer heat budget reveals that anomalies in both the atmospheric and oceanic processes offset each other such that the anomalously warm SSTs persisted for multiple years. The results show how the atmosphere–ocean system in the NE Pacific is able to maintain itself in an anomalous state for an extended period of time.

The response of the ozone layer to quadrupled CO2 concentrations.

An accurate quantification of the stratospheric ozone feedback in climate change simulations requires knowledge of the ozone response to increased greenhouse gases. Here, we present an analysis of the ozone layer response to an abrupt quadrupling of CO2 concentrations in four chemistry-climate models. We show that increased CO2 levels lead to a decrease in ozone concentrations in the tropical lower stratosphere, and an increase over the high latitudes and throughout the upper stratosphere. This pattern is robust across all models examined here, although important inter-model differences in the magnitude of the response are found. As a result of the cancellation between upper and lower stratospheric ozone, the total column ozone response in the tropics is small, and appears to be model dependent. A substantial portion of the spread in the tropical column ozone is tied to inter-model spread in upwelling. The high latitude ozone response is strongly seasonally dependent, and shows increases peaking in late-winter and spring of each hemisphere, with prominent longitudinal asymmetries. The range of ozone responses to CO2 reported in this paper has the potential to induce significant radiative and dynamical effects on the simulated climate. Hence, these results highlight the need of using an ozone dataset consistent with CO2 forcing in models involved in climate sensitivity studies.

Cloud scattering impact on thermal radiative transfer and global longwave radiation

The potential importance of longwave (LW) cloud scattering has been recognized but the actual estimate of this effect on thermal radiation varies greatly among different studies. General circulation models (GCMs) generally neglect or simplify the multiple scattering in the LW. In this study, we use a rigorous radiative transfer algorithm to explicitly consider LW multiple-scattering and apply the GCM to quantify the impact of cloud LW scattering on thermal radiation fluxes. Our study shows that the cloud scattering effect on downward thermal radiation at the surface is concentrated in the infrared atmospheric window spectrum (800–1250 cm−1). The scattering effect on the outgoing longwave radiation (OLR) is also present in the window region over low clouds but it is mainly in the far-infrared spectrum (300–600 cm−1) over high clouds. For clouds with small to moderate optical depth (τ < 10), the scattering effect on thermal fluxes shows large variation with the cloud τ and has a maximum at an optical depth of ∼3. For opaque clouds, the scattering effect approaches an asymptote and is smaller and less important.The 2-stream radiative transfer scheme could have an error over 10% with an RMS error around 3.5%–4.0% in the calculated LW flux. This algorithm error of the 2-stream approximation could readily exceed the no-scattering error in the LW, and thus it is worthless to include the time-consuming computation of multiple scattering in a 2-stream radiative transfer scheme. However, the calculation error rapidly decreases as stream number increases and the RMS error in LW flux using the 4-stream scheme is under 0.3%, an accuracy sufficient for most climate studies. We implement the 4-stream discrete-ordinate algorithm in the GISS GCM and run the GCM for 20 years with and without the LW scattering effect, respectively. When cloud LW scattering is included, we find that the global annual mean OLR is reduced by 2.7 W/m2, and the downward surface flux and the net atmospheric absorption are increased by 1.6 W/m2 and 1.8 W/m2, respectively. Using one year of ISCCP clouds and running the standalone radiative transfer offline, the global annual mean non-scattering errors in OLR, surface LW downward flux and net atmospheric absorption are 3.6 W/m2, −1.1 W/m2, and −2.5 W/m2, respectively. The global scattering impact of 2.7 W/m2 on the OLR is small when compared to the typical global OLR value of 240 W/m2, but it is significant when compared to cloud LW radiative forcing (30 W/m2) and net cloud forcing (−14 W/m2). Overall, the effect of neglecting scattering on the thermal fluxes is comparable to the reported clear sky radiative effect of doubling CO2.

Evaluation of surface shortwave and longwave downwelling radiations over the global tropical oceans

In the present study, daily downwelling shortwave (QS) and longwave radiation (QL) data from one satellite and two hybrid products have been evaluated using Global Tropical Moored Buoy Array during 2001–2009 in the tropical oceans. Daily satellite data are used from the Clouds and Earth’s Radiant Energy System (CERES) program. Data are obtained using Moderate Resolution Imaging Spectroradiometer (MODIS) (CM) aboard the Terra and Aqua satellites. Coordinated Ocean Research Experiments (CORE-II) and Tropical Flux data (TropFlux) are the other two hybrid products used in this study. The analysis shows that majority of QS observations as well as derived products lie in 200–300 Wm−2 range in all the three tropical oceans. Both QS and QL in all products overestimated the majority of the observations. Yet, they underestimated the lower (0–100 Wm−2) values in QS and higher (300–440 Wm−2) values in QL. Majority of the QL observations lie within 390–420 Wm−2 range, and CM slightly overestimated this observed distribution in the Pacific and the Atlantic Oceans. But, majority of the observations in the Indian Ocean lie within 420–450 Wm−2 range. This implies that the tropical Indian Ocean receives 30 Wm−2 more energy as compared to the tropical Pacific and the Atlantic in the form of downwelling longwave radiation. Daily observed QS shows dominant seasonal cycle over the central, the eastern Pacific and the eastern Atlantic. On the other hand, the western Pacific, the central Atlantic and the Indian Oceans show intraseasonal variations. All products show this variation with high root-mean-square error (RMSE) values (QS and QL) over the Indian Ocean than in the Pacific and the Atlantic Oceans. Downwelling radiation from CORE-II shows highest RMSE (for both QS and QL) with least correlation coefficient (CC), and TropFlux has lowest RMSE and highest CC among all products in all three tropical oceans. CM has intermediate values of standard deviation, CC and RMSE. These results are not seasonally dependent, since the seasonal statistics are consistent with seasonal changes. Assuming that the SST is only driven by the downwelling shortwave and longwave fluxes, the errors associated with monthly SST can be as large as 0.2–0.3 (0.1–0.2) °C associated with errors in QS (QL). Both QS and QL in CORE-II have lower spatial variability as compared to other datasets. QL in the tropical oceans shows seasonal spatial variability determined by intertropical convergence zone positions. This variability does not change significantly over the Pacific and the Atlantic Oceans. The summer and winter monsoon patterns in the Indian Ocean guide the QL variability. Opposite to QS, higher QL values have lower variability. Thus, this study aims at finding better radiation dataset to use in the numerical models and deduce that satellite data could be an alternative to existing reanalysis products.

Retrieval of ice cloud microphysical properties at the SACOL

Ice clouds are one of the most widely distributed cloud types in the world and play an important role in the radiation budget. The microphysical parameters of ice clouds, such as ice water content, effective radius and particle concentration, have a significant effect on the artificial influences on weather, the calculation of the radiation effect and climate feedback of ice clouds. Because of their unique physical and optical properties, ice clouds play an important and unique role in the radiation budget. Understanding and recognizing the microphysical properties of ice clouds are of great significance for studying the effects of ice clouds on climate change. Ka-band zenith radar (KAZR), which has been deployed at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) since July 2013, has continuously operated for many years. By using the observation data from KAZR and micropulse lidar (MPL), we compare the microphysical properties of ice clouds, including ice effective particle size (Dge) and ice water content (IWC), which were derived from three algorithms: a traditional algorithm (Microbase), the Z-IWC-T relationship algorithm (Hogan) and the KAZR-MPL retrieval algorithm (Combined). Then, we compute and examine the radiative fluxes using each set of cloud properties as inputs to a radiative transfer model and compare the top-of-atmosphere (TOA) radiative fluxes to the satellite measurements to assess the impact of the differences in the microphysical quantities of different ice clouds on radiation. Our analysis shows that ice clouds mainly appear from 2 to 14 km and peak by approximately 13.02% at 7 km. The ice water contents retrieved from the three different inversion methods show a unimodal distribution. The ice water content is mainly concentrated in the range of 0.01−10 mg/m3, and the corresponding maximum probability of ice water content is concentrated in the vicinity of 0.1 mg/m3. However, there are some differences between the degrees of data concentration and the peak probabilities of the different algorithms. The effective particle size distributions obtained by the three methods are quite different. The effective particle size of the ice crystal inversion by the Microbase algorithm is unimodal, and the data are mainly concentrated in the small particle radius region of 0−100 μm. The KAZR-MPL algorithm has a wider range of particle distributions, with two peaks at 40 and 96 μm. However, the distribution of the ice effective particle radius shows significant discrepancies, which sometimes translate into large differences in the cloud shortwave radiative effect. Using the results of three different microphysical properties, the longwave and shortwave radiation fluxes at the top of the atmosphere are calculated through the Fu-Liou radiation transfer model. The results show that the longwave radiation fluxes calculated by using different cloud microphysical characteristics are in good agreement with the satellite observation data. The average error is 5.04%, and the correlation coefficients are all greater than 0.6. Compared with the observed longwave radiation, the Hogan algorithm that considers the temperature effect has a better simulation effect, the correlation coefficient is larger, and the root mean square error is smaller. The shortwave radiation is smaller than the observed values in the case of clouds, and the maximum error reaches 24.61%. The shortwave radiation flux simulated by the traditional empirical algorithm is closest to the satellite observations, and its root mean square error is significantly reduced compared with that of the other methods.

The Out-of-Phase Variation in Vertical Thermal Contrast Over the Western and Eastern Sides of the Northern Tibetan Plateau

The upper tropospheric thermal contrast over the northern Tibetan Plateau and the Tianshan Mountains during the peak summer monsoon is found to have experienced a significant change since the late 1990s, and the change is out of phase on the western and eastern sides of the northern Tibetan Plateau. Using the National Center for Environmental Prediction (NCEP)–DOE AMIP-II reanalysis daily data sets, we found that in the late 1990s, there was an increase/decrease in the tropospheric temperature (TT) at 100 hPa/300 hPa on the western side, whereas on the eastern side the TT changed in the opposite fashion. Associated with the TT change is an increase (decrease) in convection in the west (east). This is in agreement with the patterns of humidity fluxes and ascending/descending favorable winds, and has been further substantiated in a causal inference, which identifies a dominant causality from the TT variation over the western side of the northern Tibetan Plateau to the longwave and shortwave fluxes through the top of the atmosphere. The lack of causality from the eastern TT variation suggests a reduction in convection, hence cloudiness, over that region, which may account for the flash drought over China during the recent global warming hiatus.

Local and Remote Controls on Arctic Mixed‐Layer Evolution

AbstractIn this study Lagrangian large‐eddy simulation of cloudy mixed layers in evolving warm air masses in the Arctic is constrained by in situ observations from the recent PASCAL field campaign. A key novelty is that time dependence is maintained in the large‐scale forcings. An iterative procedure featuring large‐eddy simulation on microgrids is explored to calibrate the case setup, inspired by and making use of the typically long memory of Arctic air masses for upstream conditions. The simulated mixed‐phase clouds are part of a turbulent mixed layer that is weakly coupled to the surface and is occasionally capped by a shallow humidity layer. All eight simulated mixed layers exhibit a strong time evolution across a range of time scales, including diurnal but also synoptic fingerprints. A few cases experience rapid cloud collapse, coinciding with a rapid decrease in mixed‐layer depth. To gain insight, composite budget analyses are performed. In the mixed‐layer interior the heat and moisture budgets are dominated by turbulent transport, radiative cooling, and precipitation. However, near the thermal inversion the large‐scale vertical advection also contributes significantly, showing a distinct difference between subsidence and upsidence conditions. A bulk mass budget analysis reveals that entrainment deepening behaves almost time‐constantly, as long as clouds are present. In contrast, large‐scale subsidence fluctuates much more strongly and can both counteract and boost boundary‐layer deepening resulting from entrainment. Strong and sudden subsidence events following prolonged deepening periods are found to cause the cloud collapses, associated with a substantial reduction in the surface downward longwave radiative flux.

Accounting for Several Infrared Radiation Processes in Climate Models

AbstractThree aspects of longwave (LW) radiation processes are investigated using numerical experiments with the Canadian Atmospheric Global Climate Model version 4.3 (CanAM4.3). These are the overlapping LW and shortwave (SW) radiation, scattering by clouds, and specification of ocean emissivity. For the overlapping of solar and infrared spectra, using a single band scheme was compared against a method directly inputting solar energy. Offline calculations show that for high clouds using the single band can cause an overestimate of the downward LW flux, whereas a method that accounts for input solar energy in the LW yields results that are more accurate. Longwave scattering by clouds traps more infrared energy in the atmosphere and reduces the outgoing radiation to space. Simulations with CanAM4.3 show that cloud LW scattering can enhance the LW cooling rate above the tropopause and reduce it inside the troposphere, resulting in warmer temperatures, especially in the tropics and low latitudes. This implies a larger temperature gradient toward the polar region, which causes a strengthening of the Hadley circulation and shifting of the intertropical convergence zone (ITCZ). The increase in lower tropospheric temperature also affects the lower troposphere water vapor and precipitation. Sensitivity to the specification of ocean emissivity is examined by comparing a broadband scheme dependent on the surface wind and solar zenith angle against one that resolves the wavelength dependence. Experiments with CanAM4.3 show that the two oceanic emissivity schemes can produce over 1 W m−2 seasonal mean difference of the upward flux at the surface.

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.

Thicker Clouds and Accelerated Arctic Sea Ice Decline: The Atmosphere‐Sea Ice Interactions in Spring

AbstractObservations show that increased Arctic cloud cover in the spring is linked with sea ice decline. As the atmosphere and sea ice can influence each other, which one plays the leading role in spring remains unclear. Here we demonstrate, through observational data diagnosis and numerical modeling, that there is active coupling between the atmosphere and sea ice in early spring. Sea ice melting and thus the presence of more open water lead to stronger evaporation and promote cloud formation that increases downward longwave flux, leading to even more ice melt. Spring clouds are a driving force in the disappearance of sea ice and displacing the mechanism of atmosphere‐sea ice coupling from April to June. These results suggest the need to accurately model interactions of Arctic clouds and radiation in Earth System Models in order to improve projections of the future of the Arctic.

Assessment of urban sprawl effects on regional climate change using a hybrid model of factor analysis and analytical network process in the Mashhad city, Iran

BackgroundUrban sprawl, as an unsustainable urban expansion, relates to direct and indirect impacts on regional climate change in urbanized regions. In this paper, the effect of urban sprawl on regional climate change has been studied using a hybrid factor analysis (FA) and analytical network process (ANP) model in Mashhad city, Iran. The methodology was divided into two main parts based on the identification of 18 urban sprawl characteristics and six climatic parameters during three time-windows of 1996, 2006, and 2016.ResultsBased on the FA, a set of chosen sprawl characteristics were reduced into five factors with a maximized total variance of the loading variables and were weighted by ANP super-matrix. Results of urban sprawl index (USI) indicated that Mashhad city had experienced rapid horizontal growth by values from 0.47 to 1.74 within 1996–2016, revealing an indication of unsustainable urban sprawl during the last decades. Based on the correlation test, a positive relation between four climatic parameters (surface temperature, surface long-wave flux, total ozone, and black carbon density) and urban sprawl was observed (R from 0.827 to 0.981). In parallel, a negative relationship between two climatic parameters (total precipitation and convective precipitation) and urban sprawl was estimated (R from − 0.691 to − 0.805).ConclusionsThe result confirmed the possible effects of urban sprawl on climatic variations. This outcome relates to a chain of urban sprawl effects on growth of construction, transportation, the assumption of fuels and subsequently high emission of greenhouse gasses such as ozone concentration, long-wave flux, and carbon density in the urban atmosphere.

Effects of Partial Cloudiness in a Cloud Microphysics Scheme on Simulated Precipitation Processes During a Boreal Summer

AbstractThe effect of partial cloudiness is included in a cloud microphysics scheme, and its impact on precipitation processes is examined through global‐model simulations for a boreal summer. An excessive precipitation rate in the simulations is reduced by considering the partial cloudiness effect in microphysical processes, especially in the tropical western Pacific region where convective activity is strong. The reduction of the precipitation rate in this region is mainly due to a decrease in convective precipitation, as the partial cloudiness effect in cloud microphysical processes modulates the convective activity by interacting with radiative processes. Cloud radiative forcings are weaker in the simulations including the partial cloudiness effect, as more cloud water and ice are converted to rain and snow mainly due to enhanced accretion rates. This leads to a decrease in cloud radiative forcing for both shortwave and longwave fluxes, which is overestimated overall over the ocean in the simulations. Temperature is lowered overall as increased longwave radiative cooling overcompensates increased shortwave radiative heating. This reduces the convective available potential energy and results in a decrease in convective precipitation. The weakened instability and upward motion over the tropical western Pacific region due to the partial cloudiness effect not only affect the local precipitation processes in this region but also suppress the downward motion over the tropical eastern Pacific regions by modulating the large‐scale zonal circulation over the tropical Pacific ocean.

Modelling Sea Surface Temperature (SST) in the Hudson Bay Complex Using Bulk Heat Flux Parameterization: Sensitivity to Atmospheric Forcing, and Model Resolution

ABSTRACTSea surface temperature (SST) from four Nucleus for European Modelling of the Ocean (NEMO) model simulations is analyzed to study the bulk flux parameterization to compute SST over the Hudson Bay Complex (HBC) for the summer months (August and September) from 2002 to 2009. The NEMO simulation was forced with two atmospheric forcing sets with different resolutions: the Coordinated Ocean-ice Reference Experiment, version 2 (COREv2), as the lower resolution and the Canadian Meteorological Centre’s Global Deterministic Prediction System Reforecasts (CGRF) as the higher resolution. The CGRF forcing is also implemented in the third and fourth runs using different runoff data and different NEMO resolutions (1/12° versus 1/4°). Results show that all four modelled SSTs followed observed SST patterns, with regional differences in SST bias between simulations with different atmospheric forcing. The SST differences are small between simulations forced with the same atmospheric forcing but with different model resolution or runoff. This implies that the model resolution and runoff have a small effect on the simulated SST in the HBC. Moreover, to better capture the effect of near-surface temperature (Tair) on simulated SST, we conducted three analyses using the Haney flux linearization formula. Results from these assessments did not indicate any direct influence on the model-simulated SSTs by Tair. Looking at the heat flux as a signature for SST showed that both averaged spatial distribution and time series of net heat flux produced by the three CGRF forcing simulations were higher than the net heat flux generated by the CORE 2 simulation. This was generally true for all four components of the total heat flux (sensible, latent, shortwave, and longwave) individually as well. Total heat flux in summer is governed by the shortwave heat flux, with values up to 120 W m−2 in August, and the longwave heat flux is the main contributor to the total heat flux differences. These heat flux differences lead to corresponding colder model SSTs for the CGRF runs and warmer SSTs for the CORE 2 simulations.

The Global Radiative Energy Budget in MERRA and MERRA-2: Evaluation with Respect to CERES EBAF Data

AbstractThe representation of the long-term radiative energy budgets in NASA’s MERRA and MERRA-2 reanalyses has been evaluated, emphasizing changes associated with the reanalysis system update. Data from the CERES EBAF Edition 2.8 satellite product over 2001–15 were used as a reference. For both MERRA and MERRA-2, the climatological global means of most TOA radiative flux terms agree to within ~3 W m−2 of EBAF. However, MERRA-2’s all-sky reflected shortwave flux is ~7 W m−2 higher than either MERRA or EBAF’s, resulting in a net TOA flux imbalance of −4 W m−2. At the surface, all-sky downward longwave fluxes are problematic for both reanalyses, while high clear-sky downward shortwave fluxes indicate that their atmospheres are too transmissive. Although MERRA-2’s individual all-sky flux terms agree better with EBAF, its net flux agreement is worse (−8.3 vs −3.3 W m−2 for MERRA) because MERRA benefits from cancellation of errors. Analysis by region and surface type gives mixed outcomes. The results consistently indicate that clouds are overrepresented over the tropical oceans in both reanalyses, particularly MERRA-2, and somewhat underrepresented in marine stratocumulus areas. MERRA-2 also exhibits signs of excess cloudiness in the Southern Ocean. Notable discrepancies occur in the polar regions, where the effects of snow and ice cover are important. In most cases, MERRA-2 better represents variability and trends in the global mean radiative fluxes over the period of analysis. Overall, the performance of MERRA-2 relative to MERRA is mixed; there is still room for improvement in the radiative fluxes in this family of reanalysis products.

Atmospheric Dynamics Footprint on the January 2016 Ice Sheet Melting in West Antarctica

AbstractIn January of 2016, the Ross Sea sector of the West Antarctica ice sheet experienced a 3‐week‐long melting episode. Here we quantify the association of the large‐extent and long‐lasting melting event with the enhancement of the downward longwave (LW) radiative fluxes at surface due to water vapor, cloud, and atmospheric dynamic feedbacks using the ERA‐Interim data set. The abnormally long‐lasting temporal surges of atmospheric moisture, warm air, and low‐level clouds increase the downward LW radiative energy flux at the surface during the massive ice‐melting period. The concurrent timing and spatial overlap between poleward wind anomalies and positive downward LW radiative surface energy flux anomalies over West Antarctica due to warmer air temperature and increases in atmospheric water vapor and cloud coverage provide direct evidence that warm and moist air advection from lower latitudes to West Antarctica causes the rapid long‐lasting warming and vast ice mass loss in January of 2016.

Solar variability manifestations in weather and climate characteristics

We discuss the issues of primary importance to understand the nature of climate changes in the 20th century and main physical processes responsible for these changes and present a physical model for the solar activity (SA) effect on climate characteristics. A key concept of this model is the heliogeophysical disturbance effect on the Earth climate system parameters driving the long-wave radiation flux moving away from the Earth out into space in high-latitude regions. We address the solar activity effect on the changes in the temperature of the atmosphere and of the World Ocean. The aa–index of the geomagnetic activity (GA) was used as an SA proxy index. We discuss the results of analyzing the regularities and peculiarities of the tropospheric and sea surface temperature (SST) responses to both separate heliogeophysical disturbances and long-term changes in solar and geomagnetic activity. The structure of the tropospheric and SST temperature responses was shown to feature a spatial time irregularity. We revealed the regions, where long-term SST changes are determined mainly by SA variations.

The Role of Internal Variability in Twenty‐First‐Century Projections of the Seasonal Cycle of Northern Hemisphere Surface Temperature

AbstractThe seasonal cycle is fundamental to the Earth's climate system, accounting for the vast majority of temperature variance. Understanding how the seasonal cycle will change in the future, and by when, is a key question with important implications. Here a 40‐member initial condition climate model ensemble is used to investigate the influence of internal variability on the detection of changes in the amplitude and timing of the seasonal cycle of surface temperature over Northern Hemisphere land in response to increasing greenhouse gases. Internal variability renders the detection of these changes challenging; even by the mid‐twenty‐first century, small ensembles will be insufficient to separate the forced signals from internal variability over many continental regions in the Northern Hemisphere. Despite this, projected changes over Europe, North Africa, and Siberia are large and easily detectable, even in a single member. Specifically, amplitude increases over Europe and North Africa while it decreases over Siberia. On the other hand, the timing of the seasonal cycle is delayed over all three regions. It is found that these changes are remarkably robust across model ensembles from the Coupled Model Intercomparison Project phase 5 archive. To understand the mechanisms underlying these robust changes, a simple energy balance model is used to partition changes into contributions arising from changes in the physical parameters that control the seasonal cycle. It is found that future changes in the seasonal cycle over the three regions are most strongly controlled by changes in surface longwave and turbulent heat fluxes.

Energy balance and snowmelt drivers of a marginal subalpine snowpack

AbstractSnowmelt from the seasonal snowpack in the Australian Alps is a significant source of water for irrigated agriculture, electricity generation, and environmental flows in the Murray–Darling Basin. Previous studies have reported negative decadal to multidecadal trends in maximum snow depth, snow season duration, and snow‐covered area. Here, we characterise the energy balance of this marginal maritime snowpack for the first time. Turbulent fluxes measured using the eddy covariance and bulk aerodynamic methods are compared; discrepancies are attributed to the differing assumptions of the methods and characteristics of the measurement site. We examine the variability of the individual energy balance components and the drivers of snowmelt, and we find that incoming longwave radiation is the dominant control on snowmelt, providing more than 80% of the total energy to the snowpack over the season. During a midwinter rain‐on‐snow event, the advected rain heat flux provided 8% of the daily total, with the incoming longwave flux still accounting for almost 80%. The ground heat flux contributes a small proportion of the seasonal total but increases in patchy or intermittent snow cover. Comparing these results with those of studies in other maritime locations, we find that the turbulent fluxes are likely to make a proportionally higher contribution to the energy balance due to the short Australian snow season, underpinning the sensitivity of this environment to climate variability and change. These results extend the limited body of knowledge on highly marginal snowpacks and may be relevant to other regions with no direct measurements of the energy balance.

Seasonal climatic effects and feedbacks of anthropogenic heat release due to global energy consumption with CAM5

Anthropogenic heat release (AHR) is the heat generated in global energy consumption, which has not been considered in global climate models generally. The global high-resolution AHR from 1992 to 2013, which is estimated by using the Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) satellite data, is implemented into the Community Atmosphere Model version 5 (CAM5). The seasonal climatic effects and possible feedbacks of AHR are examined in this study. The modeling results show that AHR increases the global annual mean surface temperature and land surface temperature by 0.02 ± 0.01 K (1σ uncertainty) and 0.05 ± 0.02 K (1σ uncertainty), respectively. The global climatic effect of AHR varies with season: with a stronger climatic effect in the boreal winter leading to global mean land surface temperature increases by 0.10 ± 0.01 K (1σ uncertainty). In the selected regions (40°N–60°N, 0°E–45°E) of Central and Western Europe the average surface temperature increases by 0.46 K in the boreal summer, and in the selected regions (45°N–75°N, 30°E–140°E) of northern Eurasia the average surface temperature increases by 0.83 K in the boreal winter. AHR changes the height and thermodynamic structure of the global planetary boundary layer, as well as the stability of the lower troposphere, which affects the global atmospheric circulation and low cloud fraction. In addition, at the surface both the shortwave radiation flux in the boreal summer and the down-welling longwave flux in the boreal winter change significantly, as a result of the change in low clouds caused by the effect of AHR. This study suggests a possible new mechanism of AHR effect on global climate through changing the global low-cloud fraction, which is crucial for global energy balance, by modifying the thermodynamic structure and stability of the lower troposphere. Thus this study improves our understanding of the global climate change caused by human activities.