Absorption Of Shortwave Radiation Research Articles

Siberian vegetation growth intensifies monsoon precipitation in southern East Asia in late spring and early summer

Regional hydrological cycle responding to rising temperatures can have significant influences on society and human activities. We suggest a new perspective on East Asia’s enhanced precipitation amount that emphasizes the role of Siberian surface warming. Increased vegetation greenness in late spring and early summer in eastern Siberia, which may be a response to global warming, acts to warm the surface by reducing the surface albedo with an increase in net absorbed shortwave radiation. Subsequently, eastern Siberia warming leads to the strengthening of anti-cyclonic atmospheric circulation over inner East Asia as well as the subtropical western North Pacific high via thermal forcing and the enhanced land-sea thermal contrast, respectively. Consequently, the anticyclonic circulation over inner East Asia transports much drier and cooler air to southern East Asia. This leads to favorable conditions for increased precipitation in combination with an increased tropical moisture flux from the subtropical western North Pacific high. Therefore, continuous Siberian vegetation growth has a potential influence on the future precipitation amount in the subtropics through vegetation–atmosphere coupled processes.

Modelling Heat and Mass Transfer in High-Capacity Natural Convection Solar Dryers

Predicting solar dryer performance under different environmental conditions or assessing their performance to dry different grains is challenging since repeatable full-scale tests are expensive and time consuming. In the present study, computational fluid dynamics approach was used to model the drying of maize in high-capacity dryers such as greenhouse and solar bubble dryer. The absorption of short-wave radiation and the greenhouse effect in the dryer with incident solar radiation was modelled using a dual-band spectrum. The distribution of airflow, temperature, and absolute humidity was analysed in this study to optimise the drying process of maize. Additionally, these results were also used to quantify the drying rate of both greenhouse and solar bubble dryer. The greenhouse dryer model overpredicted the dryer temperatures by an average of 0.12%, and overpredicted absolute humidity by 0.38 per cent. The average Root-Mean-Square Error (RMSE) of temperature prediction was 1.8 °C, and the average RMSE for absolute humidity was 0.0042 for the greenhouse model. On the other hand, the solar bubble dryer model underpredicted temperatures by 1.7%, and underpredicted humidity values by 0.3 per cent. The mean absolute percentage error for the temperature and absolute humidity prediction of the solar bubble dryer model was 1.69% and 0.28%, respectively. The predicted and observed spatial variation in the temperature was similar for both dryers.

Improving Stratocumulus Cloud Amounts in a 200‐m Resolution Multi‐Scale Modeling Framework Through Tuning of Its Interior Physics

AbstractHigh‐Resolution Multi‐scale Modeling Frameworks (HR)—global climate models that embed separate, convection‐resolving models with high enough resolution to resolve boundary layer eddies—have exciting potential for investigating low cloud feedback dynamics due to reduced parameterization and ability for multidecadal throughput on modern computing hardware. However low clouds in past HR have suffered a stubborn problem of over‐entrainment due to an uncontrolled source of mixing across the marine subtropical inversion manifesting as stratocumulus dim biases in present‐day climate, limiting their scientific utility. We report new results showing that this over‐entrainment can be partly offset by using hyperviscosity and cloud droplet sedimentation. Hyperviscosity damps small‐scale momentum fluctuations associated with the formulation of the momentum solver of the embedded large eddy simulation. By considering the sedimentation process adjacent to default one‐moment microphysics in HR, condensed phase particles can be removed from the entrainment zone, which further reduces entrainment efficiency. The result is an HR that can produce more low clouds with a higher liquid water path and a reduced stratocumulus dim bias. Associated improvements in the explicitly simulated sub‐cloud eddy spectrum are observed. We report these sensitivities in multi‐week tests and then explore their operational potential alongside microphysical retuning in decadal simulations at operational 1.5° exterior resolution. The result is a new HR having desired improvements in the baseline present‐day low cloud climatology, and a reduced global mean bias and root mean squared error of absorbed shortwave radiation. We suggest it should be promising for examining low cloud feedbacks with minimal approximation.

The Respective Roles of Ocean Heat Transport and Surface Heat Fluxes in Driving Arctic Ocean Warming and Sea Ice Decline

Abstract Arctic Ocean warming and sea ice loss are closely linked to increased ocean heat transport (OHT) into the Arctic and changes in surface heat fluxes. To quantitatively assess their respective roles, we use the 100-member Community Earth System Model, version 2 (CESM2), Large Ensemble over the 1920–2100 period. We first examine the Arctic Ocean warming in a heat budget framework by calculating the contributions from heat exchanges with atmosphere and sea ice and OHT across the Arctic Ocean gateways. Then we quantify how much anomalous heat from the ocean directly translates to sea ice loss and how much is lost to the atmosphere. We find that Arctic Ocean warming is driven primarily by increased OHT through the Barents Sea Opening, with additional contributions from the Fram Strait and Bering Strait OHTs. These OHT changes are driven mainly by warmer inflowing water rather than changes in volume transports across the gateways. The Arctic Ocean warming driven by OHT is partially damped by increased heat loss through the sea surface. Although absorbed shortwave radiation increases due to reduced surface albedo, this increase is compensated by increasing upwelling longwave radiation and latent heat loss. We also explicitly calculate the contributions of ocean–ice and atmosphere–ice heat fluxes to sea ice heat budget changes. Throughout the entire twentieth century as well as the early twenty-first century, the atmosphere is the main contributor to ice heat gain in summer, though the ocean’s role is not negligible. Over time, the ocean progressively becomes the main heat source for the ice as the ocean warms. Significance Statement Arctic Ocean warming and sea ice loss are closely linked to increased ocean heat transport (OHT) into the Arctic and changes in surface heat fluxes. Here we use 100 simulations from the same climate model to analyze future warming and sea ice loss. We find that Arctic Ocean warming is primarily driven by increased OHT through the Barents Sea Opening, though the Fram and Bering Straits are also important. This increased OHT is primarily due to warmer inflowing water rather than changing ocean currents. This ocean heat gain is partially compensated by heat loss through the sea surface. During the twentieth century and early twenty-first century, sea ice loss is mainly linked to heat transferred from the atmosphere; however, over time, the ocean progressively becomes the most important contributor.

Low cloud response to aerosol‐radiation‐cloud interactions: Idealized WRF numerical experiments for EUREC4A project

AbstractAerosols significantly affect cloud microphysics and energy budget in different ways. The contribution of the direct, semi‐direct, and indirect effects of aerosols on radiation are here investigated over the North Atlantic tropical ocean under different aerosol loadings. The Weather Research and Forecasting Model is used to perform a set of numerical idealized experiments, which are forced with prescribed aerosol profiles. We evaluate the effects of aerosols on modeled shallow clouds and surface radiative budget. The results indicate that large aerosol loadings are associated with enhanced cloudiness and reduced precipitation. While the change in rainfall is mainly due to the larger number of smaller droplets, the change in cloudiness is attributed to the effects of absorbing aerosols, mainly dust particles, which are responsible for a rise of temperature that feeds back onto specific humidity. As in the boundary layer the increase of moisture dominates, the net effect is a higher relative humidity, which favors the formation of thin low non‐precipitating clouds. The feedback accounts for a dynamical change in the lower troposphere: shortwave radiation absorption increases temperature at the top of the marine atmospheric boundary‐layer and reduces entrainment of warm and dry air, increasing low level moisture content. Despite the overall increase in cloudiness, daytime cloud cover is reduced. The semi‐direct effect of aerosols on clouds results in a warming of the surface, opposite to the indirect effect.

The Effects of Land Use and Land Cover Changes on the Land Surface Temperature Over Northeast China

To investigate the impacts of land use and land cover change (LULCC) on regional climate in Northeast China, the weather research and forecasting (WRF) model was run with the satellite land cover type, vegetation fraction (Fg), leaf area index, and albedo in 2001 and 2018, respectively, and the results were compared. The major LULCC during 2001–2018 were conversions from grasslands to croplands over the central regions of Northeast China and conversions from woody savannas to deciduous broadleaf forests in the northern and eastern portions of Northeast China. The changes in Fg and albedo are highly correlated with the daytime land surface temperature (Ts). From 2001 to 2018, the daytime Ts is decreased (increased) over the central regions of Northeast China by more than 1 K in summer (winter). There is also a widespread, about 1 K, cooling in the spring and autumn temperatures. The changes of the nighttime Ts and the daytime Ts from 2001 to 2018 are similar in summer, autumn, and winter, but the nighttime Ts changes are comparatively smaller. Analysis of the surface energy budget and the biophysical effects found that the cooling of the daytime Ts over the central regions of Northeast China in spring, summer, and autumn from 2001 to 2018 can be attributed to a decrease of absorbed shortwave radiation and an increase of latent heat flux corresponding to LULCC. This cooling is weakened by the decrease of the sensible heat flux. In contrast, the widespread warming trend of the daytime Ts in winter is mainly due to an increased net shortwave radiation, which offsets the cooling effects of surface fluxes. During the nighttime, the soil heat flux contributes the most to the changes of Ts.

Simulating the 3D Distribution of Absorbed Shortwave Radiation in a Tree Crown: Comparison of Simplified and Monte Carlo Models

AbstractUrban trees are expected to alleviate severe thermal environments in summer. The absorbed shortwave radiation is a key variable to estimate the microclimatic effects of trees. In numerical simulation tools for the urban and built thermal environment, the difficulty lies in how to calculate the absorbed radiation in terms of accuracy and computational load. Here we investigated the difference between a radiative transfer model calculating scattering by the Monte Carlo method and a simpler model that accounts for scattering by modifying the optical depth. The calculations of absorbed radiation were performed under various conditions of leaf normal distribution and zenith angle of incident radiation, using tree models represented by voxels with different leaf area density values. For the photosynthetically active radiation, the relative difference between models was less than 10% for most cases. For the near‐infrared radiation, the difference was also small for a large canopy consisting of several trees. The difference was 30%–60% and 0%–20% for zenith angles of incident radiation of 0° and 60°, respectively, for small isolated trees with a crown height and width of less than 5 m, which was a significantly different condition from a uniform canopy. This large difference was related to the uniformity of the canopy and was explained by the transmittance from each voxel to the outside of the canopy. The present study enables us to evaluate the applicability of the simple model and correct the difference from the Monte Carlo model.

3D Simulations of the Archean Earth Including Photochemical Haze Profiles

AbstractWe present results from 3D simulations of the Archean Earth including a prescribed (non‐interactive) spherical haze generated through a 1D photochemical model. Our simulations suggest that a thin haze layer, formed when CH4/CO2 = 0.1, leads to global warming of ∼10.6 K due to the change of water vapor and cloud feedback, compared to the simulation without any haze. However, a thicker haze layer, formed when CH4/CO2 > 0.1, leads to global cooling of up to ∼65 K as the scattering and absorption of shortwave radiation from the haze reduces the radiation from reaching the planetary surface. A thermal inversion is formed with a lower tropopause as the CH4/CO2 ratio increases. The haze reaches an optical threshold thickness when CH4/CO2 ∼ 0.175 beyond which the atmospheric structure and the global surface temperature do not vary much.

Potential Predictability of the Spring Bloom in the Southern Ocean Sea Ice Zone

AbstractEvery austral spring when Antarctic sea ice melts, favorable growing conditions lead to an intense phytoplankton bloom, which supports much of the local marine ecosystem. Recent studies have found that Antarctic sea ice is predictable several years in advance, suggesting that the spring bloom might exhibit similar predictability. Using a suite of perfect model predictability experiments, we find that November net primary production (NPP) is potentially predictable 7 to 10 years in advance in many Southern Ocean regions. Sea ice extent predictability peaks in late winter, followed by absorbed shortwave radiation and NPP with a 2 to 3 months lag. This seasonal progression of predictability supports our hypothesis that sea ice and light limitation control the inherent predictability of the spring bloom. Our results suggest skillful interannual predictions of NPP may be achievable, with implications for managing fisheries and the marine ecosystem, and guiding conservation policy in the Southern Ocean.

Large Uncertainties in Precipitation Exert Considerable Impact on Land Surface Temperature Modeling Over the Tibetan Plateau

AbstractThe performance of land surface temperature (LST) simulations in land surface models is subject to uncertainties in atmospheric forcing datasets. However, the contributions of forcing variables in different datasets to the simulated LST over the Tibetan Plateau (TP) remain unclear. To investigate the sensitivity of LST simulation to atmospheric forcing, we conducted a series of experiments using the Community Land Model (CLM5.0) with different forcing datasets. Results showed that the simulated LST displayed large spatiotemporal variations, and the simulation driven by the China Meteorological Forcing Data set produced more reasonable estimates than the other simulations. Sensitivity analysis suggests that the 1% increase in air temperature causes the largest variation in LST (0.54%), while the same percentage change in precipitation leads to the smallest (only 0.002%) LST variation. However, the actual uncertainty in precipitation is much larger than that in air temperature, and thus uncertainty in precipitation contributes 24% of the LST variability in the cold season, compared to 18% for air temperature. Large precipitation uncertainty leads to strong uncertainties in snow processes (snowfall and snow cover fraction), and hence strong uncertainties in surface albedo and ground absorbed shortwave radiation, further exerting the absolute impact on LST in cold season. Moreover, the snowfall is also influenced by different schemes of snowfall/rainfall partitioning. This may result in uncertainties in snowfall and consequently LST for the southeastern TP. Our study highlights the importance of high‐quality precipitation data, a forcing variable usually ignored in previous studies of LST simulation on the TP.

Heat balance characteristics in the South China Sea and surrounding areas simulated using the TRAMS model—a case study of a summer heavy rain and a winter cold spell

Introduction: This study is first to apply d iagnostic analysis of the forecast tendencies to evaluate the simulation of equilibrium features in the South China Sea and its surrounding areas using The Tropical Regional Atmosphere (TRAMS) model, and further identify the sources of simulation biases of the model.Methods: On the basis of the quasi equilibrium between dynamic and physical processes, the deviation of net forecast tendencies, which reflects the overall equilibrium of the model, serves as a good indicator of the model simulations bias. The sources of the forecast error can be further inferred by decomposing the net forecast tendencies into the dynamic and each physical process.Results: Focusing on moisture and temperature tendencies, the results show that the TRAMS model generally captures the thermal equilibrium characteristics and the contributions of each physical process, which are markedly different between summer and winter and are affected by the Northwest Pacific Subtropical High (WPSH) and deep trough of East Asia respectively. Furthermore, the underestimation of vapour consumption by cloud microphysical parameterisation and the overestimation of sea surface heat flux by boundary layer parameterisation near the surface contribute the most to systematic model bias. The temperature bias from 900 to 300 hPa during winter mainly originates from the responses of radiation, cumulus convection, and cloud microphysical parameterisations because water vapour absorbs long wave radiation, heating the atmosphere, and clouds reduce short wave radi ation absorption, cooling it.Discussion: The presented analyses provide a reference for further optimisation and improvement of the model.

Influence of External Surface Radiation Properties on Thermal Performance of Walls——Take a typical office building in Chengdu as an example

In this paper, taking a typical office building in Chengdu as an example, the coupling relationship between the radiation properties (short-wave absorption coefficient and long-wave emission coefficient) of the external surface materials of the wall and the insulation types and the insulation performance is studied by using software simulation method. The results show that the internal insulation wall is beneficial to reduce the heating load while the external insulation wall is beneficial to reduce the cooling load. And the external surface material's radiative properties hardly affect the wall insulation type choice. Still, in the case of Chengdu office buildings, interior insulated walls are more conducive to year-round building energy efficiency. In summer, the radiation characteristics of the outer surface material will affect the choice of the best heat transfer coefficient (U-value) of the wall. When the short-wave radiation absorption coefficient is small, the wall with good insulation performance will appear anti-energy-saving phenomenon. Therefore, it is recommended that the regions with high cooling loads fully consider the influence of the external surface material's radiation properties on the wall's thermal performance in the design of the thermal performance of the wall.

Effects of satellite LAI data on modelling land surface temperature and related energy budget in the Noah-MP land surface model

• Satellite LAI scheme can provide more accurate vegetation dynamic information. • Satellite LAI scheme improved LST simulation in Noah-MP land surface model. • Mechanism of LAI on LST simulation was revealed by energy budget analysis in model. Leaf area index (LAI) is essential for modelling the land surface temperature (LST) and related energy budget in the land surface models (LSMs). Due to the lack of a parameterization scheme based on satellite LAI data, it is unclear whether satellite LAI data can improve the performance of Noah with multi-parameterization (Noah-MP) LSM to model LST in China land data assimilation system (CLDAS). Here, by using satellite LAI data reconstructed by the advanced deep learning method, we established a new vegetation scheme based on satellite data for the Noah-MP LSM in the CLDAS. We quantitatively evaluated simulation effects of different vegetation schemes including the parameter table scheme (TAB), the dynamic vegetation scheme (DVEG), and the satellite LAI data scheme (OBS), on modelling LAI, LST and their related energy budget in China from 2016 to 2018. We found that except for the cropland, the LAI of the vegetation in growing season observed by satellite was lower than that simulated by the Noah-MP LSM. Validations based on the automatic weather stations in the vegetation-covered area showed that compared with the TAB and DVEG scheme, the OBS scheme improved the negative bias and high unbiased root mean square error (ubRMSE) of simulated LST. Compared with the TAB and DVEG scheme, the optimal improvements of the OBS scheme for annual mean bias and annual mean ubRMSE were 0.32 °C and 0.17 °C, respectively. We further revealed the mechanism of LAI on LST simulation in the Noah-MP LSM by decomposed temperature metric method. With the adoption of the new satellite LAI-based scheme, the absorbed radiation (SW), sensible heat flux (H), latent heat flux (LE), and ground heat flux (G) simulated by the Noah-MP LSM tend to change in different directions, leading to an overall increase in the net energy absorbed by the surface, which is consistent with the LST changes. The LAI changes of dense vegetation affect the LST simulation mainly through the competition of the absorbed shortwave radiation and turbulent heat fluxes. Due to the influence of exposed soil, the LAI changes of sparse vegetation mainly affect the LST simulation mainly through the interaction of the absorbed shortwave radiation and ground heat flux. Our study highlighted that the application of satellite LAI data has the potential to improve simulations of multiple land surface processes in the Noah-MP LSM.

Springtime arctic ozone depletion forces northern hemisphere climate anomalies

Large-scale chemical depletion of ozone due to anthropogenic emissions occurs over Antarctica as well as, to a lesser degree, the Arctic. Surface climate predictability in the Northern Hemisphere might be improved due to a previously proposed, albeit uncertain, link to springtime ozone depletion in the Arctic. Here we use observations and targeted chemistry–climate experiments from two models to isolate the surface impacts of ozone depletion from complex downward dynamical influences. We find that springtime stratospheric ozone depletion is consistently followed by surface temperature and precipitation anomalies with signs consistent with a positive Arctic Oscillation, namely, warm and dry conditions over southern Europe and Eurasia and moistening over northern Europe. Notably, we show that these anomalies, affecting large portions of the Northern Hemisphere, are driven substantially by the loss of stratospheric ozone. This is due to ozone depletion leading to a reduction in short-wave radiation absorption, when in turn causing persistent negative temperature anomalies in the lower stratosphere and a delayed break-up of the polar vortex. These results indicate that the inclusion of interactive ozone chemistry in atmospheric models can considerably improve the predictability of Northern Hemisphere surface climate on seasonal timescales. Ozone depletion in the Arctic stratosphere consistently disrupts surface temperature and precipitation patterns across the Northern Hemisphere, according to atmospheric chemistry–climate modelling and observations.

Near Invariance of Poleward Atmospheric Heat Transport in Response to Midlatitude Orography

Abstract Total poleward atmospheric heat transport (AHT) is similar in both magnitude and latitudinal structure between the Northern and Southern Hemispheres. These similarities occur despite more major mountain ranges in the Northern Hemisphere, which help create substantial stationary eddy AHT that is largely absent in the Southern Hemisphere. However, this hemispheric difference in stationary eddy AHT is compensated by hemispheric differences in other dynamic components of AHT so that total AHT is similar between hemispheres. To understand how AHT compensation occurs, we add midlatitude mountain ranges in two different general circulation models that are otherwise configured as aquaplanets. Even when midlatitude mountains are introduced, total AHT is nearly invariant. We explore the near invariance of total AHT in response to orography through dynamic, energetic, and diffusive perspectives. Dynamically, orographically induced changes to stationary eddy AHT are compensated by changes in both transient eddy and mean meridional circulation AHT. This creates an AHT system with three interconnected components that resist large changes to total AHT. Energetically, the total AHT can only change if the top-of-the-atmosphere net radiation changes at the equator-to-pole scale. Midlatitude orography does not create large-enough changes in the equator-to-pole temperature gradient to alter outgoing longwave radiation enough to substantially change total AHT. In the zonal mean, changes to absorbed shortwave radiation also often compensate for changes in outgoing longwave radiation. Diffusively, the atmosphere smooths anomalies in temperature and humidity created by the addition of midlatitude orography, such that total AHT is relatively invariant. Significance Statement The purpose of this study is to better understand how orography influences heat transport in the atmosphere. Enhancing our understanding of how atmospheric heat transport works is important, as heat transport helps moderate Earth’s surface temperatures and influences precipitation patterns. We find that the total amount of atmospheric heat transport does not change in the presence of mountains in the midlatitudes. Different pieces of the heat transport change, but they change in compensatory ways, such that the total heat transport remains roughly constant.

Large-area high spatial resolution albedo retrievals from remote sensing for use in assessing the impact of wildfire soot deposition on high mountain snow and ice melt

Soot deposition from wildfires decreases snow and ice albedo and increases the absorption of shortwave radiation, which advances and accelerates melt. Soot deposition also induces algal growth, which further decreases snow and ice albedo. In recent years, increasingly severe and widespread wildfire activity has occurred in western Canada in association with climate change. In the summers of 2017 and 2018, westerly winds transported smoke from extensive record-breaking wildfires in British Columbia eastward to the Canadian Rockies, where substantial amounts of soot were deposited on high mountain glaciers, snowfields, and icefields. Several studies have addressed the problem of soot deposition on snow and ice, but the spatiotemporal resolution applied has not been compatible with studying mountain icefields that are extensive but contain substantial internal variability and have dynamical albedos. This study evaluates spatial patterns in the albedo decrease and net shortwave radiation (K*) increase caused by soot from intense wildfires in Western Canada deposited on the Columbia Icefield (151 km2), Canadian Rockies, during 2017 and 2018. Twelve Sentinel-2 images were used to generate high spatial resolution albedo retrievals during four summers (2017 to 2020) using a MODIS bidirectional reflectance distribution function (BRDF) model, which was employed to model the snow and ice reflectance anisotropy. Remote sensing estimates were evaluated using site-measured albedo on the icefield's Athabasca Glacier tongue, resulting in a R2, mean bias, and root mean square error (RMSE) of 0.68, 0.019, and 0.026, respectively. The biggest inter-annual spatially averaged soot-induced albedo declines were of 0.148 and 0.050 (2018 to 2020) for southeast-facing glaciers and the snow plateau, respectively. The highest inter-annual spatially-averaged soot-induced shortwave radiative forcing was 203 W/m2 for southeast-facing glaciers (2018 to 2020) and 106 W/m2 for the snow plateau (2017 to 2020). These findings indicate that snow albedo responded rapidly to and recovered rapidly from soot deposition. However, ice albedo remained low the year after fire, and this was likely related to a bio-albedo feedback involving microorganisms. Snow and ice K* were highest during low albedo years, especially for south-facing glaciers. These large-scale effects accelerated melt of the Columbia Icefield. The findings highlight the importance of using large-area high spatial resolution albedo estimates to analyze the effect of wildfire soot deposition on snow and ice albedo and K* on icefields, which is not possible using other approaches.

Characteristics of top-of-atmosphere radiation budget over the Tibetan Plateau and its bias sources in climate models

Observations indicate that the Tibetan Plateau (TP) has an annual-mean ~9.3 W m−2 positive radiation budget (RT) at the top of the atmosphere, the largest at the same continental latitudes. This unique radiative heating is critical to the TP's thermal forcing and hydrological cycle. Here we use satellite and reanalyzed data to investigate the characteristics of RT over the TP in the observation and 28 CMIP6 models. The positive observational RT is mainly caused by low surface temperature associated with high elevation. Most models underestimate annual mean RT over the whole TP, with a multimodel average of 2.0 W m−2. This RT bias results mainly from weaker absorbed shortwave radiation (ASR) that exhibits substantial seasonal and regional differences. Serious RT, ASR, and surface albedo biases appear over the western TP. For instance, their wintertime multimodel-mean biases of −44.9 W m−2, −53.3 W m−2, and 0.23 are larger than the eastern TP's counterparts (−38.6 W m−2, −40.6 W m−2, and 0.15). Simulated RT also shows a large intermodel spread. In the models with worse RT's performance, weaker ASR is primarily attributed to higher surface albedo that coincides well with lower surface temperature. In contrast, the models that reproduce well the RT have less surface albedo bias but somewhat overestimate surface temperature. Weaker simulated cloud radiative cooling reduces reflected shortwave radiation that alleviates the RT bias, especially over the springtime eastern TP. This study highlights the importance of land surface states and clouds in modeling the TP's climate. Significance statementObservations indicate that the Tibetan Plateau (TP) has an annual-mean ~ 9.3 W m−2 positive radiation budget (RT) at the top of the atmosphere, the largest among land regions in the same latitudes. This study aims to investigate the characteristics of RT over the TP in the observation and CMIP6 models. Most models underestimate annual mean RT over the whole TP, with a multimodel average of 2.0 W m−2. This bias results mainly from weaker absorbed shortwave radiation, exhibiting substantial seasonal and regional differences. CMIP6 simulations show a large multimodel spread, especially over the wintertime and springtime western TP. This study highlights the importance of land surface states (e.g., surface temperature and albedo) and clouds in modeling the TP's climate.

The Midlatitude Response to Polar Sea Ice Loss: Idealized Slab-Ocean Aquaplanet Experiments with Thermodynamic Sea Ice

Abstract Slab-ocean aquaplanet simulations with thermodynamic sea ice are used to study the zonally symmetric mechanisms whereby polar sea ice loss impacts the midlatitude atmosphere. Imposed sea ice loss (difference without and with sea ice with historical CO2 concentration) leads to global warming, polar amplified warming, and a weakening of poleward atmospheric energy transport and the midlatitude storm-track intensity. The simulations confirm an energetic mechanism that predicts a weakening of storm-track intensity in response to sea ice loss, given the change of surface albedo and assuming a passive ocean. Namely, sea ice loss increases the absorption of shortwave radiation by the surface (following the decrease of surface albedo), which increases surface turbulent fluxes into the atmosphere thereby weakening poleward atmospheric energy transport. The storm-track intensity weakens because it dominates poleward energy transport. The quantitative prediction underlying the mechanism captures the weakening but underestimates its amplitude. The weakening is also consistent with weaker mean available potential energy (polar amplified warming) and scales with sea ice extent, which is controlled by the slab-ocean depth. The energetic mechanism also operates in response to sea ice loss due to melting (difference of the response to quadrupled CO2 with and without sea ice). Finally, the midlatitude response to sea ice loss in the aquaplanet agrees qualitatively with the response in more complex climate models. Namely, the storm-track intensity weakens and the energetic mechanism operates, but the method used to impose sea ice loss in coupled models impacts the surface response.

The Energy Model of Urban Heat Island

Despite the fact that the presence of a heat island over a city was established quite a long time ago, now there is no versatile algorithm for the determination of the urban heat island intensity. The proposed models either take into account only one or several factors for the formation of an urban heat island or do not consider physical reasons for the difference in thermodynamic conditions between a city and countryside. In this regard, it is impossible to make a forecast and determine the optimal methods for reducing the urban heat island intensity for an arbitrarily chosen city in a wide range of its characteristics and climatic conditions. This paper studies the causes for the formation of an urban heat island in order to develop the quantitative model of this process through the determination of the difference in radiation fluxes of various nature between a city and countryside (background area). A new equation allowing the intensity of an urban heat island in different seasons and different times of day, as well as under various atmospheric conditions, to be calculated from meteorological parameters measured at a stationary observation station is proposed. The model has been tested through the comparison of the results of numerical simulation with direct measurements of the heat island in Tomsk with a mobile station. It is shown that the main contributors to the formation of the heat island in Tomsk are anthropogenic heat emissions (80–90% in winter, 40–50% in summer) and absorption of shortwave radiation by the urban underlying surface (5–15% in winter, 40–50% summer). The absorption of longwave radiation by the urban underlying surface, absorption by atmospheric water vapor and other constituents, and heat consumption for evaporation are insignificant. An increase in the turbulent heat flux is responsible for the outflow of 40–50% of absorbed energy in summer and 20–30% in winter.

Global distribution and variability of subsurface chlorophyll <i>a</i> concentrations

Abstract. Chlorophyll a (Chl a) often exhibits a maximum concentration in the subsurface layer rather that at the surface. The depth of the Chl a maximum primarily depends on the balance between light penetration from the surface and the nutrient supply from the deep ocean. However, a global map of subsurface Chl a concentrations based on observations has not been presented yet. In this study, we integrate Chl a concentration data from recent biogeochemical floats and historical ship-based (and other) observations and present global maps of subsurface Chl a concentrations with related variables. The subsurface Chl a maximum was observed globally throughout the oceans: at depths greater than 80 m in the subtropics and tropics (30∘ S to 30∘ N); in the 40–80 m depth range in the tropics, in the Southern Ocean (south of 40∘ S), and at the midlatitudes (30–40∘ N/S) in the North Pacific; and at depths of less than 40 m in the northern subarctic (north of 40∘ N). The observed maxima all lie below the mixed-layer depth for the entire year in the subtropics and tropics and during summer in the midlatitudes and the northern subarctic. The depths of the subsurface Chl a maxima are greater than those of the photosynthetically active layer in the subtropics but shallower in the tropics and midlatitudes. In the subtropics, a seasonal increase in oxygen below the mixed layer implies substantial new biological production, which corresponds to 10 % of the net primary production in that region. During El Niño, subsurface Chl a concentrations are higher in the middle and eastern equatorial Pacific but lower to the west in comparison with La Niña, a pattern which is opposite to that on the surface. The spatiotemporal variability of the Chl a concentrations described here has implications to not only for the biogeochemical cycling in the ocean but also for understanding the thermal structure and dynamics of the ocean via absorption of shortwave radiation.