Surface Net Longwave Radiation Research Articles

Enhanced seasonality of surface air temperature over China during the mid-Holocene

Using all available simulations performed by climate models participating in PMIP4 (Paleoclimate Modelling Intercomparison Project – Phase 4), the authors quantify the seasonality change of surface air temperature over China during the mid-Holocene (6000 years ago) and the associated physical mechanisms. Relative to the preindustrial period, all 16 models consistently show an enhanced temperature seasonality (i.e., summer minus winter temperature) across China during that interglacial period, with a nationally averaged enhancement of 2.44 °C or 9% for the multimodel mean. The temperature seasonality change is closely related with the seasonal contrast variation of surface energy fluxes mainly due to the mid-Holocene orbital forcing. Specifically, the summer–winter increase in surface net shortwave radiation dominates the intensified temperature seasonality at the large scale of China during the mid-Holocene; the surface net longwave radiation has a minor positive contribution in most of the Tibetan Plateau and eastern China; and both the surface latent and sensible heat fluxes show partial offset effects in most of the country. There are uncertainties in the reconstructed temperature seasonality over China during the mid-Holocene based on the proxy data that can reflect seasonal signals.摘要利用PMIP4多模式试验数据, 作者量化了中全新世 (距今约6000年) 中国温度季节性变化. 结果表明: 相对于工业革命前期, 所有16个模式一致模拟显示中全新世我国温度季节性 (即夏季与冬季温差) 增强, 平均增幅9%; 这与该时期轨道强迫引起的地表能量通量的季节对比变化密切相关, 其中净短波辐射起主导作用, 净长波辐射作用次之, 感热和潜热为负贡献; 与模拟不同, 重建结果存在不确定性.

Evaluation of High Mountain Asia‐Land Data Assimilation System (Version 1) From 2003 to 2016: 2. The Impact of Assimilating Satellite‐Based Snow Cover and Freeze/Thaw Observations Into a Land Surface Model

AbstractThis second paper of the two‐part series focuses on demonstrating the impact of assimilating satellite‐based snow cover and freeze/thaw observations into the hyper‐resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region from 2003 to 2016. To this end, this study systematically evaluates a total of six sets of 0.01° (∼1 km) model simulations forced by different precipitation forcings, with and without the dual assimilation scheme enabled, at point‐scale, basin‐scale, and domain‐scale. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near‐surface soil temperature, snow depth, snow water equivalent (SWE), and total runoff. First, the point‐scale assessment is mainly conducted via evaluating against ground‐based measurements. In general, the assimilation enabled estimates are better than no‐assimilation counterparts. Second, the basin‐scale runoff assessment demonstrates that across three snow‐dominated basins, the assimilation enabled experiment yields systematic improvements in all goodness‐of‐fit statistics through mitigating the negative effects brought by the fixed long‐term precipitation correction factors. For example, when forced by the bias‐corrected precipitation, the assimilation‐enabled experiment improves the bias by 69%, the root‐mean‐squared error by 30%, and the unbiased root‐mean‐squared error by 18% (relative to the no‐assimilation counterpart). Finally, the domain‐scale assessment is conducted via evaluating against satellite‐based SWE and skin temperature products. Both sets of domain‐scale analysis further corroborate the findings in the point‐scale evaluations. Overall, this study suggests the benefits of the proposed multi‐variate assimilation system in improving the cryospheric‐hydrological process within a land surface model for use in HMA.

A simple method for surface radiation estimating using FY-4A data

AbstractFY-4A is a geostationary meteorological satellite with four advanced payloads, which can be used to quantitatively detect the earth's atmospheric system with multi spectral and high spatial-temporal resolution. However, the applicable model limits the application of the FY-4A satellite data. In this paper, the empirical statistical model developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor is extended for FY-4A Advanced Geosynchronous Radiation Imager (AGRI), and it is applied to observed data to evaluate the applicability of the model for AGRI measurements. To improve the accuracy of radiation estimation, the artificial intelligent particle swarm optimization (PSO) algorithm was used for model optimizing. Results show that the estimated radiation has diurnal variation, which accords with the characteristics of radiation variation. The estimated net surface shortwave radiation (Sn) and observed values show good correlation. However, large deviations from observations are found in the estimated values when the empirical model based on MODIS is directly used to process AGRI data. Thus, the empirical statistical model based on MODIS can be applied to AGRI data, but the empirical parameters need to be revised. Optimization of the empirical statistical model by the PSO algorithm can effectively improve the accuracy of radiation estimate. The Mean absolute percentage error (MAPE) of Sn estimated by optimized models is reduced to 15%. The MAPE of the net surface long-wave radiation (Ln) estimated by optimized models is reduced to 31%, and the MAPE of the net radiation (Rn) estimated by optimized models is reduced to 27%. However, for the uncertainty caused by error accumulation effect, the influence of PSO optimization on Rn is not as obvious as that of Ln. However, from the analysis of error distribution, it shows that PSO optimization does improve the estimation results of Rn. Based on AGRI data, the surface radiation can be estimated simply, and the regional or larger scale surface radiation retrieval can quickly realize by this method which has large application potential and popularization value.

Projected changes in the mean and intra-seasonal variability of the Indian summer monsoon in the RegCM CORDEX-CORE simulations under higher warming conditions

The present study employed the latest high-resolution regional climate model (RegCM4), driven by MPI-ESM-MR boundary conditions from the CORDEX-CORE South Asia framework to investigate the possible projected changes in the mean and intra-seasonal variability of the Indian summer monsoon (ISM) precipitation and their associated dynamics during near future (NF; 2041–2060) and far future (FF; 2080–2099) with respect to the historical period (1995–2014) under RCP8.5 scenario. Extensive evaluation analysis indicates that the RegCM4 is fairly able to simulate the spatial–temporal distribution of the observed mean and extreme precipitation, low-level jet, and intra-seasonal variability i.e. active and break composite patterns of the precipitation anomalies over India during the historical period. A substantial decline in the projected precipitation during ISM is estimated over central and northwest India in NF (about 10–30%) as well as in FF (upto 50%), which may be attributed to the weakening and northward shift of low-level winds. The occurrences as well as the intensity of the extreme precipitation events are expected to increase over India in the future. The precipitation during the projected active spells will escalate over the monsoon core region. This is supported by the decrease in sea level pressure over land, which favors the winds to transport more moisture from the adjoining seas for the formation of convective clouds, which is partly indicated through the decline in net surface longwave radiation. On the other hand, the precipitation intensity during the projected break spells is expected to further decrease in the future.

Evaluation of High Mountain Asia‐Land Data Assimilation System (Version 1) From 2003 to 2016, Part I: A Hyper‐Resolution Terrestrial Modeling System

AbstractThis first paper of the two‐part series focuses on demonstrating the accuracy of a hyper‐resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region. To this end, this study systematically evaluates four sets of model simulations at point scale, basin scale, and domain scale obtained from different spatial resolutions including 0.01° (∼1‐km) and 0.25° (∼25‐km). The assessment is conducted via comparisons against ground‐based observations and satellite‐derived reference products. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near‐surface soil temperature, snow depth, snow water equivalent, and total runoff. In the evaluation against ground‐based measurements, the superiority of the 0.01° estimates are mostly demonstrated across relatively complex terrain. Specifically, hyper‐resolution modeling improves the skill in meteorological forcing estimates (except precipitation) by 9% relative to coarse‐resolution estimates. The model forced by downscaled forcings in its entirety yields the highest skill in model output states as well as precipitation, which improves the skill obtained by coarse‐resolution estimates by 7%. These findings, on one hand, corroborate the importance of employing the hyper‐resolution versus coarse‐resolution modeling in areas characterized by complex terrain. On the other hand, by evaluating four sets of model simulations forced with different precipitation products, this study emphasizes the importance of accurate hyper‐resolution precipitation products to drive model simulations.

Emergent Relationships Among Sea Ice, Longwave Radiation, and the Beaufort High Circulation Exposed Through Parameter Uncertainty Analysis

AbstractUsing a perturbed parameter ensemble of a coupled climate model, emerging relationships are identified between sea ice area, net surface longwave radiation, and the atmospheric circulation over the Beaufort gyre. There is a strong positive correlation between sea ice area and the net longwave radiation over the ocean‐ice surface during the melting season and a negative correlation during the freezing season. The mechanisms responsible for the longwave radiation balance at the surface are mainly driven by sea ice variations in the freezing season and by clouds in the melting season. A strong positive (negative) correlation is also found between the fall (summer) total sea ice area in the Arctic and the sea level pressure over the Beaufort High region. It is argued that as sea ice coverage is lost, static stability losses are severe in fall, resulting in enhanced evaporation, vertical motions, and weakening of the general large‐scale anticyclonic circulation of the Beaufort High.

Modeling surface longwave radiation over high-relief terrain

Thermal anisotropy is an important phenomenon in thermal infrared remote sensing as it restricts the retrieval accuracy of surface longwave radiation (SLR). Topography is an essential controlling factor for the directionality of SLR for high-relief regions (e.g., mountain regions) where there is land surface heterogeneity and non-isothermal properties at pixel scales. However, satellite sensors can only receive radiance from a specific surface object at a small number of simultaneous viewing angles, which makes the quantitative modeling of thermal anisotropy challenging. Therefore, we developed the topographic longwave radiation model (TLRM) to describe the directionality of SLR components taking into account the variability of both subpixel topography and thermal anisotropy in high-relief regions. The reliability of TLRM was validated using the Discrete Anisotropic Radiative Transfer (DART) model over two typical geomorphic areas: a valley scene and a peak scene. The preliminary validation shows good agreement in terms of surface upward longwave radiance, which confirms the potential of TLRM for capturing the anisotropic patterns of land surfaces. The radiance values simulated by the DART model were first revised for the spectral mismatch. Then, they are used to correct residual deviation for TLRM using linear regressions. The root mean square error (RMSE) and coefficient of determination (R2) were 0.830 W/(m2 ∙ sr) and 0.746 for the valley scene, respectively, and 0.239 W/(m2 ∙ sr) and 0.711 for the peak scene, respectively. Compared with TLRM, models that do not consider terrain effects generate significant discrepancies in high relief SLR components. The differences in downward longwave radiation can reach −60 W/m2 in valleys without considering terrain effects. Based on the reference of hemispherical upward longwave radiation, surface upward longwave radiation estimated by the direct estimation method had a bias of 11.41 W/m2 and standard deviation (STD) of 7.30 W/m2, while the directional upward longwave radiation had a bias of 5.99 W/m2 and STD of 4.08 W/m2, showing lower estimation variation. The discrepancy between surface net longwave radiation (NLR) and terrain-corrected NLR ranged between 50 and −130 W/m2 with clear negative biases mainly occurring in valleys. With higher spatial resolutions of remotely sensed imagery, the influence of complex terrain on land surface radiative flux has become more significant. This parameterization scheme is expected to better represent the topographic effects on SLR, enhance understanding of thermal anisotropy in non-isothermal mixed pixel areas of high relief, and improve the inversion accuracy of SLR.

Analysis of the temporal–spatial changes in surface radiation budget over the Antarctic sea ice region

The surface radiation budget (SRB) of the Antarctic sea ice region (ASIR) is important for the climate change in Antarctica, which partly explains the global warming. Long-term (1982–2015) satellite-derived (EUMETSAT Satellite Application Facility on Climate Monitoring, CLARA-A2) and reanalysis (European Centre for Medium-Range Weather Forecasts, ERA-Interim) datasets provided high quality and global coverage surface radiation products, which enabled us to quantify the SRB of the ASIR and widen our understanding of the polar climate. The downwelling longwave (LW) and shortwave (SW) radiation from the two datasets were validated at two Baseline Surface Radiation Network Stations (i.e., Neumayer and Syowa). Cloud LW emission dominated over cloud SW reflection and absorption due to high-albedo over the sea ice surface, thereby leading to a positive all-wave cloud radiative forcing (CRF) within 0–100 W m−2. This result indicated a warming effect on the surface of the ASIR, except during the austral summer. Compared with the all sky, substantial solar radiation was absorbed by the surface which under the clear sky will result in the increasing of temperature and sea ice melting during the austral summer; hence, the SW CRF had a major influence on all-wave CRF and caused more than −150 W m−2 of cooling near the edge of the sea ice. The summer averages of all-wave CRF over the ASIR surface were − 43.02 and − 35.74 W m−2 for the ERA-Interim and CLARA-A2 datasets, respectively. Contrary to the effect of CRF, the surface net LW radiation (LWnet) exhibited a cooling effect over the ASIR surface throughout the year and peaks at −47.21 W m−2 for CLARA-A2 dataset in December. Meanwhile, a warming effect was caused by the surface net SW radiation (SWnet) peaks at 101.52 and 104.09 W m−2 for the ERA-Interim and CLARA-A2 datasets, respectively. In summer, the warming effect caused by the surface net all-wave radiation in East Antarctica was deeper than that in West Antarctica. The time series and trend analysis showed that the surface net radiation and CRF over the entire ASIR basically exhibited a decreasing trend. The descending speed of SWnet (−3.652 W m−2 decade−1) about five times faster than that of LWnet (−0.722 W m−2 decade−1). Although a significant trough appeared in 1993/1994 of the time series curves of All-wave CRF, it had a deeply negative trend with about −3.443 W m−2 decade−1. Detailed analysis on the five longitudinal sectors around Antarctica (the Weddell Sea, the Indian Ocean, the Pacific Ocean, the Ross Sea, and the Bellingshausen-Amundsen Sea) can further help us understand the SRB of the ASIR.

Effects of complex terrain on net surface longwave radiation in China

Net surface longwave radiation (NSLR) is one of key meteorological factors and is strongly influenced by cloud cover, surface temperature, humidity, and local micrometeorological conditions as well as terrain conditions. Realistically estimating NSLR is vitally important for understanding surface radiation balance and investigating micrometeorological factors of air pollution dispersion, especially in regions with complicated terrain. In this study, we proposed a distributed model for estimating NSLR by considering effects of complex local terrain conditions in China. Meteorological data (including mean temperature, relative humidity, and sunshine percentage) and observed NSLR data from 1993 to 2001 together with the digital elevation model data were used to parametrize the model and account for the effects of atmospheric factors and surface terrain factors according to the isotropic principle. The monthly NSLR during 1961–2000 was estimated at a spatial resolution of 1 km. Topographic analysis suggests that the distribution characteristics of NSLR with elevation or slope are consistent with those of field observations. In particular, the estimated NSLR is favorably comparable with site-level observations on the Tibetan Plateau (average relative error < 11%). Our results indicate that this model can describe microscale distribution features in mountainous areas in detail and that this improved approach can be used for NSLR spatial estimation in other regions with complicated terrain.

Evaluation and Parameter Optimization of Monthly Net Long-Wave Radiation Climatology Methods in China

Based on surface radiation balance data and meteorological observations at 19 radiation stations in China from 1993 to 2012, we assessed the applicability of seven empirical formulas for the estimation of monthly surface net long-wave radiation (Rnl). We then established a revised method applicable to China by re-fitting the formula using new observational data. The iterative solution method and the multivariate regression analysis method with the minimum root mean square error (RMSE) were used as the objective functions in the revised method. Meanwhile, the accuracy of the CERES (Clouds and the Earth’s Radiant Energy System) estimated Rnl was also evaluated. Results show that monthly Rnl over China was underestimated by the seven formulas and the CERES data. The Tong Hongliang formula with lowest errors was the best among the seven formulas for estimating Rnl over China as a whole, followed by the Penman and the Deng Genyun formulas. The estimated Rnl based on the CERES data also showed relatively higher precision in accordance with the three formulas mentioned above. The FAO56-PM formula (Penman–Monteith formula recommended in the No. 56 report of the Food and Agriculture Organization) without calibration was not applicable to China due to its low accuracy. For individual stations, the Deng Genyun formula was the most accurate in the eastern plain area, while the Tong Hongliang formula was suitable for the plateau. Regional formulas were established based on the geographical distribution of water vapor pressure and elevation over China. The revised national and regional formulas were more accurate than the seven original formulas and the CERES data. Furthermore, the regional formulas produced smaller errors than the national formula at most of the stations. The regional formulas were clearly more accurate than the Deng Genyun formula at stations in Northwestern China and on the Tibetan Plateau. They were also more accurate than the Tong Hongliang formula at the stations located in the eastern area. Therefore, the regional formulas developed in this study are recommended as the standard climatology formulas to calculate monthly Rnl over China.

Estimation of Surface Longwave Radiation over the Tibetan Plateau Region Using MODIS Data for Cloud-Free Skies

This study addressed the estimation of downward surface longwave radiation (R-L,R-D) for the Tibetan Plateau region using the MODerate resolution Imaging Spectroradiometer (MODIS) measurements observed at the top of the atmosphere (TOA) for clear-sky conditions. To extend, the method developed by Tang and Li with only regard to MODIS/Terra data and with surface elevation only lower than 2.5 km, two separate look-up table (LUT) coefficients corresponding to different elevations and viewing zenith angles (VZAs) were developed for MODIS/Terra and MODIS/Aqua, respectively. The upward surface longwave radiation (R-L,R-U) was estimated using the Stefan-Boltzmann law with MODIS surface temperature/emissivity products (MOD11_L2/MYD11_L2). Combining the R-L,R-D and, the R-L,R-U net surface longwave radiation R-L,R-N can then be obtained. The R-L,R-D and R-L,R-N were validated using some in situ measurements from two sites of Asian Automatic Weather Station Network Project (AAN) (Dunhuang and Amdo) and three sites of Environmental and Ecological Science Data Center for West China (Huazhaizi, Yingke, and A'rou) in the Heihe River Basin. The results showed that the root mean square errors (RMSEs) between the estimated R-L,R-N and in situ measurements were about 30 W/m(2). In addition, the schemes developed, respectively, by Bisht et al. and Brutsaert were used to estimate the R-L,R-D and R-L,R-N for comparison with the proposed method. The results showed that the RMSE of the proposed method was the lowest one among the three methods, which indicated that the proposed method can estimate the R-L,R-N accurately for the Tibetan Plateau region.

Estimating net surface longwave radiation from net surface shortwave radiation for cloudy skies

This work addresses the estimation of net surface longwave radiation (NSLR) from net surface shortwave radiation (NSSR) by analysing the Surface Radiation Budget Network (SURFRAD) radiation data under cloudy conditions. A general model is developed to estimate NSLR from the NSSR for cloudy skies with a root mean square error (RMSE) of 23.16 W m−2 compared with in situ data. The model is applied to AmeriFlux data. The results show that the mean error and RMSE are –2.31 W m−2 and 29.25 W m−2, respectively, compared with the measurement of AmeriFlux. To examine the significance of the influence of seasons on the estimated NSLR, the model is proposed as a function of seasonal variation. The results show a slight improvement for winter and spring, whereas a larger error is found for autumn compared with the results obtained by the general model. The influences of land cover and elevation on the model are also investigated. The results show that the model is slightly sensitive to the normalized difference vegetation index (NDVI) and the elevation. The RMSE of the model decreases from 23.16 W m−2 to 21.04 W m−2 when the NDVI and the elevation are considered in the model.

Sensitivity experiments of impacts of large-scale urbanization in East China on East Asian winter monsoon

By using the global atmospheric general circulation model CAM4.0 including an urban canopy parameterization scheme, the possible impacts of large-scale urbanization in East China on East Asian winter monsoon was investigated via idealized numerical experiments. Results suggest that large-scale urbanization can cause a significant warming effect in both surface temperature and air temperature near the surface over most areas of East China. Meanwhile, large-scale urbanization also alters the surface energy balance, causing evident increases in net surface long-wave radiation and sensible heat flux as well as intensified surface thermal heating to the atmosphere. Forced by the surface thermal heating anomalies induced by the large-scale urban expansion, East Asian winter monsoon circulation exhibits distinct changes. Overall, the extensive urbanization over East China will weaken East Asian winter monsoon, but intensify winter monsoon in northeast China.

Estimation of clear‐sky land surface longwave radiation from MODIS data products by merging multiple models

The surface longwave radiation budget plays an important role in the Earth's climate system. Remote sensing provides the most practical way to map surface longwave radiation on a large scale and at a high spatial resolution. In this paper, we evaluate both surface downward longwave radiation (DLR) and upwelling longwave radiation (ULR) models under clear‐sky conditions from MODIS data products. There are multiple DLR models available with variable uncertainties, and the Bayesian Model Averaging (BMA) method is incorporated in this study to combine the predictive distribution of these models for better accuracy. The integrated estimates for DLR based on the BMA method have lower root‐mean‐square errors (RMSEs) and higher coefficients of determination (R2) than the best individual model. The RMSEs decreased by approximately 10 W/m2 at two forest sites and by approximately 4 W/m2 at other sites. The R2value increased at each site by more than 0.05. Two models for calculating the surface upwelling longwave radiation (ULR) are also evaluated at 16 sites. The results show that both the land surface temperature (LST)–emissivity method and the direct method, the Wang‐U model underestimate the clear‐sky ULR. The validation results show that the surface net longwave radiation (NLR) estimated using DLR estimates based on the BMA method and ULR estimates based on the LST‐emissivity method is the most accurate.

Characteristics of land surface thermal-hydrologic processes for different regions over North China during prevailing summer monsoon period

The observation stations of Northern China are divided into three regions: the arid Northwest China, the Loess Plateau, and the cool Northeast China. The consistencies, differences, and associated mechanisms of land surface thermal-hydrologic processes among the three regions were studied based on the normalization of major variables of land surface thermal-hydrologic processes, using data collected during prevailing summer monsoon period (July and August, 2008). It is shown that differences of surface thermal-hydrologic processes are remarkable among the three regions because of different impacts of summer monsoon. Especially their soil wet layers occur at different depths, and the average albedo and its diurnal variations are distinctly different. Surface net short-wave radiation in the Loess Plateau is close to that in the cool Northeast China, but its surface net long-wave radiation is close to that in the arid Northwest China. And the ratio of net radiation to global solar radiation in the cool Northeast China is higher than the other two regions, though its temperature is lower. There are obvious regional differences in the ratios of surface sensible and latent heat fluxes to net radiation for the three regions because of distinct contribution of sensible and latent heat fluxesto land surface energy balance. The three regions are markedly different in the ratio of water vapor flux to pan evaporation, but they are consistent in the ratio of water vapor flux to precipitation. These results not only indicate different influences of climate and environmental factors on land surface thermal-hydrologic processes in the three regions, but also show that summer monsoon is important in the formation and variation of the pattern of land surface thermal-hydrologic processes.

The intraseasonal variability of winter semester surface air temperature in Antarctica

This study investigates systematically the intraseasonal variability of surface air temperature over Antarctica by applying empirical orthogonal function (EOF) analysis to the National Centers for Environmental Prediction, US Department of Energy, Reanalysis 2 data set for the period of 1979 through 2007. The results reveal the existence of two major intraseasonal oscillations of surface temperature with periods of 26 - 30 days and 14 days during the Antarctic winter season in the region south of 60°S. The first EOF mode shows a nearly uniform spatial pattern in Antarctica and the Southern Ocean associated with the Antarctic Oscillation. The mode-1 intraseasonal variability of the surface temperature leads that of upper atmosphere by one day with the largest correlation at 300-hPa level geopotential heights. The intraseasonal variability of the mode-1 EOF is closely related to the variations of surface net longwave radiation the total cloud cover over Antarctica. The other major EOF modes reveal the existence of eastward propagating phases over the Southern Ocean and marginal region in Antarctica. The leading two propagating modes respond to Pacific-South American modes. Meridional winds induced by the wave train from the tropics have a direct influence on the surface air temperature over the Southern Ocean and the marginal region of the Antarctic continent. Key words: Antarctic climate, surface air temperature, intraseasonal variability, Antarctic Oscillation (Published: 22 February 2011) Citation: Polar Research 2011, 30, 6039, DOI: 10.3402/polar.v30i0.6039

A Method for Estimating Clear-Sky Instantaneous Land-Surface Longwave Radiation With GOES Sounder and GOES-R ABI Data

This letter presents new models for estimating clear-sky instantaneous longwave radiation over land surfaces using the Geostationary Operational Environmental Satellites (GOES) Sounders and GOES-R Advanced Baseline Imager (ABI) thermal infrared top-of-atmosphere (TOA) radiances. The method used in this study shares the same hybrid method framework designed for Moderate Resolution Imaging Spectroradiometer. We propose separate surface downward longwave radiation (LWDN) and upwelling longwave radiation (LWUP) models because the two components are dominated by different surface/atmospheric properties. A nonlinear model was developed to estimate LWDN, and a linear model was developed to estimate LWUP. The GOES-12 Sounder-derived LWDN, LWUP, and surface net longwave radiation (LWNT = LWUP-LWDN) were evaluated using one full-year of ground data from the Surface Radiation Budget Network. The root-mean-squared errors (rmses) are less than 22.03 W/m2 at all four sites. Our study indicates that the hybrid method can also be applied to estimate LWUP using the future GOES-R ABI TOA radiances. The lack of a channel beyond 13.3 m in the proposed ABI design may cause larger rmses when estimating LWDN.

An Empirical Study of Geographic and Seasonal Variations in Diurnal Temperature Range

Abstract The diurnal temperature range (DTR) of surface air over land varies geographically and seasonally. The authors have investigated these variations using generalized additive models (GAMs), a nonlinear regression methodology. With DTR as the response variable, meteorological and land surface parameters were treated as explanatory variables. Regression curves related the deviation of DTR from its mean value to values of the meteorological and land surface variables. Cloud cover, soil moisture, distance inland, solar radiation, and elevation were combined as explanatory variables in an ensemble of 84 GAM models that used data grouped into seven vegetation types and 12 months. The ensemble explained 80% of the geographical and seasonal variation in DTR. Vegetation type and cloud cover exhibited the strongest relationships with DTR. Shortwave radiation, distance inland, and elevation were positively correlated with DTR, whereas cloud cover and soil moisture were negatively correlated. A separate analysis of the surface energy budget showed that changes in net longwave radiation represented the effects of solar and hydrological variation on DTR. It is found that vegetation and its associated climate is important for DTR variation in addition to the climatic influence of cloud cover, soil moisture, and solar radiation. It is also found that surface net longwave radiation is a powerful diagnostic of DTR variation, explaining over 95% of the seasonal variation of DTR in tropical regions.

Examination of Relationships between Clear-Sky Longwave Radiation and Aspects of the Atmospheric Hydrological Cycle in Climate Models, Reanalyses, and Observations

Abstract Relationships between clear-sky longwave radiation and aspects of the atmospheric hydrological cycle are quantified in models, reanalyses, and observations over the period 1980–2000. The robust sensitivity of clear-sky surface net longwave radiation (SNLc) to column-integrated water vapor (CWV) of 1–1.5 W m−2 mm−1 combined with the positive relationship between CWV and surface temperature (Ts) explains substantial increases in clear-sky longwave radiative cooling of the atmosphere (QLWc) to the surface over the period. Clear-sky outgoing longwave radiation (OLRc) is highly sensitive to changes in aerosol and greenhouse gas concentrations in addition to temperature and humidity. Over tropical ocean regions of mean descent, QLWc increases with Ts at ∼3.5–5.5 W m−2 K−1 for reanalyses, estimates derived from satellite data, and models without volcanic forcing included. Increased QLWc with warming across the tropical oceans helps to explain model ensemble mean increases in precipitation of 0.1–0.15 mm day−1 K−1, which are primarily determined by ascent regions where precipitation increases at the rate expected from the Clausius–Clapeyron equation. The implications for future projections in the atmospheric hydrological cycle are discussed.

Overview of observations from the RADAGAST experiment in Niamey, Niger: 2. Radiative fluxes and divergences

Broadband shortwave and longwave radiative fluxes observed both at the surface and from space during the Radiative Atmospheric Divergence using ARM Mobile Facility, GERB data and AMMA Stations (RADAGAST) experiment in Niamey, Niger, in 2006 are presented. The surface fluxes were measured by the Atmospheric Radiation Measurement (ARM) Program Mobile Facility (AMF) at Niamey airport, while the fluxes at the top of the atmosphere (TOA) are from the Geostationary Earth Radiation Budget (GERB) instrument on the Meteosat‐8 satellite. The data are analyzed as daily averages, in order to minimize sampling differences between the surface and top of atmosphere instruments, while retaining the synoptic and seasonal changes that are the main focus of this study. A cloud mask is used to identify days with cloud versus those with predominantly clear skies. The influence of temperature, water vapor, aerosols, and clouds is investigated. Aerosols are ubiquitous throughout the year and have a significant impact on both the shortwave and longwave fluxes. The large and systematic seasonal changes in temperature and column integrated water vapor (CWV) through the dry and wet seasons are found to exert strong influences on the longwave fluxes. These influences are often in opposition to each other, because the highest temperatures occur at the end of the dry season when the CWV is lowest, while in the wet season the lowest temperatures are associated with the highest values of CWV. Apart from aerosols, the shortwave fluxes are also affected by clouds and by the seasonal changes in CWV. The fluxes are combined to provide estimates of the divergence of radiation across the atmosphere throughout 2006. The longwave divergence shows a relatively small variation through the year, because of a partial compensation between the seasonal variations in the outgoing longwave radiation (OLR) and surface net longwave radiation. A simple model of the greenhouse effect is used to interpret this result in terms of the dependence of the normalized greenhouse effect at the TOA and of the effective emissivity of the atmosphere at the surface on the CWV. It is shown that, as the CWV increases, the atmosphere loses longwave energy to the surface with about the same increasing efficiency with which it traps the OLR. When combined with the changes in temperature, this maintains the atmospheric longwave divergence within the narrow range that is observed. The shortwave divergence is mainly determined by the CWV and aerosol loadings and the effect of clouds is much smaller than on the component fluxes.