Absorbed Solar Radiation Research Articles

South Asian Summer Monsoon Precipitation Is Sensitive to Southern Hemisphere Subtropical Radiation Changes

AbstractWe study the sensitivity of South Asian Summer Monsoon (SASM) precipitation to Southern Hemisphere (SH) subtropical Absorbed Solar Radiation (ASR) changes using Community Earth System Model 2 simulations. Reducing positive ASR biases over the SH subtropics impacts SASM, and is sensitive to the ocean basin where changes are imposed. Radiation changes over the SH subtropical Indian Ocean (IO) shifts rainfall over the equatorial IO northward causing 1–2 mm/day drying south of equator, changes over the SH subtropical Pacific increases precipitation over northern continental regions by 1–2 mm/day, and changes over the SH subtropical Atlantic have little effect on SASM precipitation. Radiation changes over the subtropical Pacific impacts the SASM through zonal circulation changes, while changes over the IO modify meridional circulation to bring about changes in precipitation over northern IO. Our findings suggest that reducing SH subtropical radiation biases in climate models may also reduce SASM precipitation biases.

Observational Assessment of Changes in Earth’s Energy Imbalance Since 2000

AbstractSatellite observations from the Clouds and the Earth’s Radiant Energy System show that Earth’s energy imbalance has doubled from 0.5 ± 0.2 Wm−2 during the first 10 years of this century to 1.0 ± 0.2 Wm−2 during the past decade. The increase is the result of a 0.9 ± 0.3 Wm−2 increase absorbed solar radiation (ASR) that is partially offset by a 0.4 ± 0.25 Wm−2 increase in outgoing longwave radiation (OLR). Despite marked differences in ASR and OLR trends during the hiatus (2000–2010), transition-to-El Niño (2010–2016) and post-El Niño (2016–2022) periods, trends in net top-of-atmosphere flux (NET) remain within 0.1 Wm−2 per decade of one another, implying a steady acceleration of climate warming. Northern and southern hemisphere trends in NET are consistent to 0.06 ± 0.31 Wm−2 per decade due to a compensation between weak ASR and OLR hemispheric trend differences of opposite sign. We find that large decreases in stratocumulus and middle clouds over the sub-tropics and decreases in low and middle clouds at mid-latitudes are the primary reasons for increasing ASR trends in the northern hemisphere (NH). These changes are especially large over the eastern and northern Pacific Ocean, and coincide with large increases in sea-surface temperature (SST). The decrease in cloud fraction and higher SSTs over the NH sub-tropics lead to a significant increase in OLR from cloud-free regions, which partially compensate for the NH ASR increase. Decreases in middle cloud reflection and a weaker reduction in low-cloud reflection account for the increase in ASR in the southern hemisphere, while OLR changes are weak. Changes in cloud cover in response to SST increases imply a feedback to climate change yet a contribution from radiative forcing or internal variability cannot be ruled out.

Development of statistical seasonal prediction models of Arctic Sea Ice concentration using CERES absorbed solar radiation

Statistical seasonal prediction models for the Arctic sea ice concentration (SIC) were developed for the late summer (August-October) when the downward trend is dramatic. The absorbed solar radiation (ASR) at the top of the atmosphere in June has a significant seasonal leading role on the SIC. Based on the lagged ASR-SIC relationship, two simple statistical models were established: the Markovian stochastic and the linear regression models. Crossvalidated hindcasts of SIC from 1979 to 2014 by the two models were compared with each other and observation. The hindcasts showed general agreement between the models as they share a common predictor, ASR in June and the observed SIC was well reproduced, especially over the relatively thin-ice regions (of one- or multi-year sea ice). The robust predictability confirms the functional role of ASR in the prediction of SIC. In particular, the SIC prediction in October was quite promising probably due to the pronounced icealbedo feedback. The temporal correlation coefficients between the predicted SIC and the observed SIC were 0.79 and 0.82 by the Markovian and regression models, respectively. Small differences were observed between the two models; the regression model performed slightly better in August and September in terms of temporal correlation coefficients. Meanwhile, the prediction skills of the Markovian model in October were higher in the north of Chukchi, the East Siberian, and the Laptev Seas. A strong non-linear relationship between ASR in June and SIC in October in these areas would have increased the predictability of the Markovian model.

Relationships among top‐of‐atmosphere radiation and atmospheric state variables in observations and CESM

AbstractA detailed examination is made in both observations and the Community Earth System Model (CESM) of relationships among top‐of‐atmosphere radiation, water vapor, temperatures, and precipitation for 2000–2014 to assess the origins of radiative perturbations and climate feedbacks empirically. The 30‐member large ensemble coupled runs are analyzed along with one run with specified sea surface temperatures for 1994 to 2005 (to avoid volcanic eruptions). The vertical structure of the CESM temperature profile tends to be top heavy in the model, with too much deep convection and not enough lower stratospheric cooling as part of the response to tropospheric heating. There is too much absorbed solar radiation (ASR) over the Southern Oceans and not enough in the tropics, and El Niño–Southern Oscillation (ENSO) is too large in amplitude in this version of the model. However, the covariability of monthly mean anomalies produces remarkably good replication of most of the observed relationships. There is a lot more high‐frequency variability in radiative fluxes than in temperature, highlighting the role of clouds and transient weather systems in the radiation statistics. Over the Warm Pool in the tropical western Pacific and Indian Oceans, where nonlocal effects from the Walker circulation driven by the ENSO events are important, several related biases emerge: in response to high SST anomalies there is more precipitation, water vapor, and cloud and less ASR and outgoing longwave radiation in the model than observed. Different model global mean trends are evident, however, possibly hinting at too much positive cloud feedback in the model.

Shortwave and longwave radiative contributions to global warming under increasing CO2.

In response to increasing concentrations of atmospheric CO2, high-end general circulation models (GCMs) simulate an accumulation of energy at the top of the atmosphere not through a reduction in outgoing longwave radiation (OLR)—as one might expect from greenhouse gas forcing—but through an enhancement of net absorbed solar radiation (ASR). A simple linear radiative feedback framework is used to explain this counterintuitive behavior. It is found that the timescale over which OLR returns to its initial value after a CO2 perturbation depends sensitively on the magnitude of shortwave (SW) feedbacks. If SW feedbacks are sufficiently positive, OLR recovers within merely several decades, and any subsequent global energy accumulation is because of enhanced ASR only. In the GCM mean, this OLR recovery timescale is only 20 y because of robust SW water vapor and surface albedo feedbacks. However, a large spread in the net SW feedback across models (because of clouds) produces a range of OLR responses; in those few models with a weak SW feedback, OLR takes centuries to recover, and energy accumulation is dominated by reduced OLR. Observational constraints of radiative feedbacks—from satellite radiation and surface temperature data—suggest an OLR recovery timescale of decades or less, consistent with the majority of GCMs. Altogether, these results suggest that, although greenhouse gas forcing predominantly acts to reduce OLR, the resulting global warming is likely caused by enhanced ASR.

Role of snow-albedo feedback in higher elevation warming over the Himalayas, Tibetan Plateau and Central Asia

Recent literature has shown that surface air temperature (SAT) in many high elevation regions, including the Tibetan Plateau (TP) has been increasing at a faster rate than at their lower elevation counterparts. We investigate projected future changes in SAT in the TP and the surrounding high elevation regions (between 25°–45°N and 50°–120°E) and the potential role snow-albedo feedback may have on amplified warming there. We use the Community Climate System Model version 4 (CCSM4) and Geophysical Fluid Dynamics Laboratory (GFDL) model which have different spatial resolutions as well as different climate sensitivities. We find that surface albedo (SA) decreases more at higher elevations than at lower elevations owing to the retreat of the 0 °C isotherm and the associated retreat of the snow line. Both models clearly show amplified warming over Central Asian mountains, the Himalayas, the Karakoram and Pamir during spring. Our results suggest that the decrease of SA and the associated increase in absorbed solar radiation (ASR) owing to the loss of snowpack play a significant role in triggering the warming over the same regions. Decreasing cloud cover in spring also contributes to an increase in ASR over some of these regions in CCSM4. Although the increase in SAT and the decrease in SA are greater in GFDL than CCSM4, the sensitivity of SAT to changes in SA is the same at the highest elevations for both models during spring; this suggests that the climate sensitivity between models may differ, in part, owing to their corresponding treatments of snow cover, snow melt and the associated snow/albedo feedback.

Connecting early summer cloud‐controlled sunlight and late summer sea ice in the Arctic

AbstractThis study demonstrates that absorbed solar radiation (ASR) at the top of the atmosphere in early summer (May–July) plays a precursory role in determining the Arctic sea ice concentration (SIC) in late summer (August–October). The monthly ASR anomalies are obtained over the Arctic Ocean (65°N–90°N) from the Clouds and the Earth's Radiant Energy System during 2000–2013. The ASR changes primarily with cloud variation. We found that the ASR anomaly in early summer is significantly correlated with the SIC anomaly in late summer (correlation coefficient, r ≈ −0.8 with a lag of 1 to 4 months). The region exhibiting high (low) ASR anomalies and low (high) SIC anomalies varies yearly. The possible reason is that the solar heat input to ice is most effectively affected by the cloud shielding effect under the maximum TOA solar radiation in June and amplified by the ice‐albedo feedback. This intimate delayed ASR‐SIC relationship is not represented in most of current climate models. Rather, the models tend to over‐emphasize internal sea ice processes in summer.

A technique using principal component analysis to compare seasonal cycles of Earth radiation from CERES and model computations

A method for quantitatively comparing the seasonal cycles of two global data sets is presented. The seasonal cycles of absorbed solar radiation (ASR) and outgoing longwave radiation (OLR) have been computed from an eight‐year data set from the Clouds and Earth's Radiant Energy System (CERES) scanning radiometers and from a model data set produced by the NASA Goddard Space Flight Center Global Modeling and Assimilation Office. To compare the seasonal cycles from these two data sets, principal component (PC) analysis is used, where the PCs express the time variations and the corresponding empirical orthogonal functions (EOFs) describe the geographic variations. Ocean has a long thermal response time compared to land, so land and ocean are separated for the analysis. The root‐mean square values for the seasonal cycles of ASR and OLR are extremely close for the two data sets. The first three PCs are quite close, showing that the time responses and magnitudes over the globe are very similar. The agreement between the two sets of PCs is quantified by computing the matrix of inner products of the two sets. For ASR over land, the first PCs of CERES and the model agree to better than 99.9%. The EOF maps are similar for most of the globe, but differ in a few places, and the agreement of the EOF maps is likewise quantified. Maps of differences between the annual cycles show regions of agreement and disagreement.

The Annual Cycle of Earth Radiation Budget from Clouds and the Earth’s Radiant Energy System (CERES) Data

AbstractThe seasonal cycle of the Earth radiation budget is investigated by use of data from the Clouds and the Earth’s Radiant Energy System (CERES). Monthly mean maps of reflected solar flux and Earth-emitted flux on a 1° equal-angle grid are used for the study. The seasonal cycles of absorbed solar radiation (ASR), outgoing longwave radiation (OLR), and net radiation are described by use of principal components for the time variations, for which the corresponding geographic variations are the empirical orthogonal functions. Earth’s surface is partitioned into land and ocean for the analysis. The first principal component describes more than 95% of the variance in the seasonal cycle of ASR and the net radiation fluxes and nearly 90% of the variance of OLR over land. Because one term can express so much of the variance, principal component analysis is very useful to describe these seasonal cycles. The annual cycles of ASR are about 100 W m−2 over land and ocean, but the amplitudes of OLR are about 27 W m−2 over land and 15 W m−2 over ocean. The magnitude of OLR and its time lag relative to that of ASR are important descriptors of the climate system and are computed for the first principal components. OLR lags ASR by about 26 days over land and 42 days over ocean. The principal components are useful for comparing the observed radiation budget with that computed by a model.

Using a global climate model to evaluate the influences of water vapor, snow cover and atmospheric aerosol on warming in the Tibetan Plateau during the twenty-first century

We examine trends in climate variables and their interrelationships over the Tibetan Plateau using global climate model simulations to elucidate the mechanisms for the pattern of warming observed over the plateau during the latter half of the twentieth century and to investigate the warming trend during the twenty-first century under the SRES A1B scenario. Our analysis suggests a 4°C warming over the plateau between 1950 and 2100. The largest warming rates occur during winter and spring. For the 1961–2000 period, the simulated warming is similar to the observed trend over the plateau. Moreover, the largest warming occurs at the highest elevation sites between 1950 and 2100. We find that increases in (1) downward longwave radiation (DLR) influenced by increases in surface specific humidity (q), and (2) absorbed solar radiation (ASR) influenced by decreases in snow cover extent are, in part, the reason for a large warming trend over the plateau, particularly during winter and spring. Furthermore, elevation-based increases in DLR (influenced by q) and ASR (influenced by snow cover and atmospheric aerosols) appear to affect the elevation dependent warming trend simulated in the model.

The Annual Cycle of the Energy Budget. Part II: Meridional Structures and Poleward Transports

Abstract Meridional structure and transports of energy in the atmosphere, ocean, and land are evaluated holistically for the mean and annual cycle zonal averages over the ocean, land, and global domains, with discussion and assessment of uncertainty. At the top of the atmosphere (TOA), adjusted radiances from the Earth Radiation Budget Experiment (ERBE) and Clouds and Earth’s Radiant Energy System (CERES) are used along with estimates of energy storage and transport from two global reanalysis datasets for the atmosphere. Three ocean temperature datasets are used to assess changes in the ocean heat content (OE) and their relationship to the net upward surface energy flux over ocean (FoS), which is derived from the residual of the TOA and atmospheric energy budgets. The surface flux over land is from a stand-alone simulation of the Community Land Model forced by observed fields. In the extratropics, absorbed solar radiation (ASR) achieves a maximum in summer with peak values near the solstices. Outgoing longwave radiation (OLR) maxima also occur in summer but lag ASR by 1–2 months, consistent with temperature maxima over land. In the tropics, however, OLR relates to high cloud variations and peaks late in the dry monsoon season, while the OLR minima in summer coincide with deep convection in the monsoon trough at the height of the rainy season. Most of the difference between the TOA radiation and atmospheric energy storage tendency is made up by a large heat flux into the ocean in summer and out of the ocean in winter. In the Northern Hemisphere, the transport of energy from ocean to land regions is substantial in winter, and modest in summer. In the Southern Hemisphere extratropics, land − ocean differences play only a small role and the main energy transport by the atmosphere and ocean is poleward. There is reasonably good agreement between FoS and observed changes in OE, except for south of 40°S, where differences among several ocean datasets point to that region as the main source of errors in achieving an overall energy balance. The winter hemisphere atmospheric circulation is the dominant contributor to poleward energy transports outside of the tropics [6–7 PW (1 petawatt = 1015 W)], with summer transports being relatively weak (∼3 PW)—slightly more in the Southern Hemisphere and slightly less in the Northern Hemisphere. Ocean transports outside of the tropics are found to be small (<2 PW) for all months. Strong cross-equatorial heat transports in the ocean of up to 5 PW exhibit a large annual cycle in phase with poleward atmospheric transports of the winter hemisphere.

Simulation of the Earth's radiation budget by the European Centre for Medium‐Range Weather Forecasts 40‐year reanalysis (ERA40)

The radiation budget simulated by the European Centre for Medium‐Range Weather Forecasts (ECMWF) 40‐year reanalysis (ERA40) is evaluated for the period 1979–2001 using independent satellite data and additional model data. This provides information on the quality of the radiation products and indirect evaluation of other aspects of the climate produced by ERA40. The climatology of clear‐sky outgoing longwave radiation (OLR) is well captured by ERA40. Underestimations of about 10 W m−2 in clear‐sky OLR over tropical convective regions by ERA40 compared to satellite data are substantially reduced when the satellite sampling is taken into account. The climatology of column‐integrated water vapor is well simulated by ERA40 compared to satellite data over the ocean, indicating that the simulation of downward clear‐sky longwave fluxes at the surface is likely to be good. Clear‐sky absorbed solar radiation (ASR) and clear‐sky OLR are overestimated by ERA40 over north Africa and high‐latitude land regions. The observed interannual changes in low‐latitude means are not well reproduced. Using ERA40 to analyze trends and climate feedbacks globally is therefore not recommended. The all‐sky radiation budget is poorly simulated by ERA40. OLR is overestimated by around 10 W m−2 over much of the globe. ASR is underestimated by around 30 W m−2 over tropical ocean regions. Away from marine stratocumulus regions, where cloud fraction is underestimated by ERA40, the poor radiation simulation by ERA40 appears to be related to inaccurate radiative properties of cloud rather than inaccurate cloud distributions.

エアロゾルと雲の放射がアジアモンスーンに及ぼす影響とその長期予報における意義

The influence of aerosol and cloud radiations upon the Asian summer monsoon was studied by using the global numerical weather prediction (NWP) model at the Japan Meteorological Agency (JMA). We parameterize both the direct and indirect effects of aerosols on radiative processes. In addition, criteria of cloud diagnosis are modified to enhance the cloud cover over the land in contrast to that over the ocean, considering that clouds form more easily over the land due to surface inhomogeneity and stay longer in the atmosphere due to smaller droplet size over the land than over the ocean. We confirm that the prediction of Asian monsoon activity is very sensitive to inclusions of aerosols and land-cloud enhancement. The control model, which uses the same cloud diagnosis scheme both over the land and over the ocean and does not include any effects of aerosols, systematically overpredicts the absorbed solar radiation (ASR) over land. The test model with these processes fairly reduces the systematic errors of land-ocean contrast of ASR. Over the Eurasian continent, the test model reduces ASR and lowers low-level temperature through land-atmosphere interactions. It suppresses monsoonal circulations in Southeast Asia and significantly delays northward migration of the typical fronts around East Asia, such as the Meiyu, Changma and Baiu fronts. The impact of land-cloud enhancement on one-month forecasts of the Asian monsoon seems to be similar to that of aerosols. Although the reduction of systematic errors of ASR indicates the relevance of the total effects of the two parameterization schemes, relative magnitudes of their impacts in nature are still uncertain. Further studies are required on distributions of aerosols and their optical properties, and cloud formation mechanisms particularly associated with the land-ocean difference, including aerosol-cloud interactions.

Annual and interannual variations of absorbed solar radiation based on a 10‐year data set

Annual and interannual variations of absorbed solar radiation (ASR) are studied using the 10‐year Earth radiation budget data set from the Nimbus 6 and 7 Earth radiation budget instruments in the form of monthly averaged maps of ASR. Empirical orthogonal functions (EOFs) are computed for the global distribution of ASR. Six EOFs are found which have physical significance and which account for 97.8% of the spatial variance of the data set. The first EOF describes the annual cycle and is primarily a latitudinal variation which is driven by the incident solar radiation. The second and fourth EOFs are semiannual cycles. EOFs 3 through 6 are strongly longitudinally dependent. EOF 3 describes the spring/fall part of the annual cycle, and EOF 4 describes the part of the semiannual cycle which is out of phase with EOF 2. EOF 5 is the response of the ASR to El Niño. The annual cycle and its harmonics account for 97.6% of the variance with time. When the data set is deseasonalized, the first two EOFs of the resulting set are found to correspond closely to EOFs 5 and 6 of the data set with season included. As with outgoing longwave radiation, most of the interannual variation is found over the tropical oceans.