VERIFICATION OF DOWNWARD LONGWAVE RADIATION EQUATION USING BASELINE SURFACE RADIATION NETWORK (BSRN) DATA

Abstract. The trends of meteorological parameters and surface downward shortwave radiation (DSR) and downward longwave radiation (DLR) were analysed at four stations (between 370 and 3580 m a.s.l.) in Switzerland for the 1996–2015 period. Ground temperature, specific humidity, and atmospheric integrated water vapour (IWV) trends were positive during all-sky and cloud-free conditions. All-sky DSR and DLR trends were in the ranges of 0.6–4.3 W m−2 decade−1 and 0.9–4.3 W m−2 decade−1, respectively, while corresponding cloud-free trends were −2.9–3.3 W m−2 decade−1 and 2.9–5.4 W m−2 decade−1. Most trends were significant at the 90 % and 95 % confidence levels. The cloud radiative effect (CRE) was determined using radiative-transfer calculations for cloud-free DSR and an empirical scheme for cloud-free DLR. The CRE decreased in magnitude by 0.9–3.1 W m−2 decade−1 (only one trend significant at 90 % confidence level), which implies a change in macrophysical and/or microphysical cloud properties. Between 10 % and 70 % of the increase in DLR is explained by factors other than ground temperature and IWV. A more detailed, long-term quantification of cloud changes is crucial and will be possible in the future, as cloud cameras have been measuring reliably at two of the four stations since 2013.

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Predicting Downward Longwave Radiation for Various Land Use in All-Sky Condition: Northeast Florida

Advances in Meteorology ◽

10.1155/2014/525148 ◽

2014 ◽

Vol 2014 ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Chi-Han Cheng ◽

Fidelia Nnadi

Keyword(s):

Land Use ◽

Cloud Cover ◽

Water Vapor Pressure ◽

Longwave Radiation ◽

Heat Fluxes ◽

Surface Radiation ◽

Radiation Budget ◽

Seasonal Effects ◽

Land Use Patterns ◽

Downward Longwave Radiation

Accurate estimate of the surface longwave radiation is important for the surface radiation budget, which in turn controls evaporation and sensible heat fluxes. Regional land use changes can impact local weather conditions; for example, heterogeneous land use patterns and temporal changes in atmospheric circulation patterns would affect air temperature and water vapor pressure, which are more commonly used as inputs in existing models for estimating downward longwave radiation (LWd). In this study, first, we analyzed the cloud cover and land use covers impacts onLWd. Next,LWdon all-sky conditions were developed by using the existing land use-adapted model and cloud cover data from the region of Saint Johns River Water Management District (SJRWMD), FL. The results show that factors, such as, seasonal effects, cloud cover, and land use, are of importance in the estimation ofLWdand they cannot be ignored when developing a model forLWdprediction. The all-sky land use-adapted model with all factors taken into account performs better than other existing models statistically. The results of the statistical analyses indicated that the BIAS, RMSE, MAE, and PMRE are −0.18 Wm−2, 10.81 Wm−2, 8.00 Wm−2, and 2.30%; −2.61 Wm−2, 14.45 Wm−2, 10.64 Wm−2, and 3.19%; −0.07 Wm−2, 10.53 Wm−2, 8.03 Wm−2, and 2.27%; and −0.62 Wm−2, 13.97 Wm−2, 9.76 Wm−2, and 2.87% for urban, rangeland, agricultural, and wetland areas, respectively.

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Evaluation of the Surface Radiation Budget in the Atmospheric Component of the Hadley Centre Global Environmental Model (HadGEM1)

Journal of Climate ◽

10.1175/2008jcli2097.1 ◽

2008 ◽

Vol 21 (18) ◽

pp. 4723-4748 ◽

Cited By ~ 34

Author(s):

A. Bodas-Salcedo ◽

M. A. Ringer ◽

A. Jones

Keyword(s):

Land Surface ◽

Surface Albedo ◽

Longwave Radiation ◽

Surface Radiation ◽

Radiation Budget ◽

Surface Radiation Budget ◽

Global Environmental ◽

Downward Longwave Radiation ◽

Global Dimming ◽

Hadley Centre

Abstract The partitioning of the earth radiation budget (ERB) between its atmosphere and surface components is of crucial interest in climate studies as it has a significant role in the oceanic and atmospheric general circulation. An analysis of the present-day climate simulation of the surface radiation budget in the atmospheric component of the new Hadley Centre Global Environmental Model version 1 (HadGEM1) is presented, and the simulations are assessed by comparing the results with fluxes derived from satellite data from the International Satellite Cloud Climatology Project (ISCCP) and ground measurements from the Baseline Surface Radiation Network (BSRN). Comparisons against radiative fluxes from satellite and ground observations show that the model tends to overestimate the surface incoming solar radiation (Ss,d). The model simulates Ss,d very well over the polar regions. Consistency in the comparisons against BSRN and ISCCP-FD suggests that the ISCCP-FD database is a good test for the performance of the surface downwelling solar radiation in climate model simulations. Overall, the simulation of downward longwave radiation is closer to observations than its shortwave counterpart. The model underestimates the downward longwave radiation with respect to BSRN measurements by 6.0 W m−2. Comparisons of land surface albedo from the model and estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) show that HadGEM1 overestimates the land surface albedo over deserts and over midlatitude landmasses in the Northern Hemisphere in January. Analysis of the seasonal cycle of the land surface albedo in different regions shows that the amplitude and phase of the seasonal cycle are not well represented in the model, although a more extensive validation needs to be carried out. Two decades of coupled model simulations of the twentieth-century climate are used to look into the model’s simulation of global dimming/brightening. The model results are in line with the conclusions of the studies that suggest that global dimming is far from being a uniform phenomenon across the globe.

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Antarctic and Southern Ocean Surface Temperatures in CMIP5 Models in the Context of the Surface Energy Budget*

Journal of Climate ◽

10.1175/jcli-d-15-0429.1 ◽

2016 ◽

Vol 29 (5) ◽

pp. 1689-1716 ◽

Cited By ~ 15

Author(s):

David P. Schneider ◽

David B. Reusch

Keyword(s):

Southern Ocean ◽

Ice Sheet ◽

Longwave Radiation ◽

Surface Energy Budget ◽

Surface Radiation ◽

Lower Atmosphere ◽

Cmip5 Models ◽

Warm Bias ◽

Downward Longwave Radiation ◽

Ensemble Mean

Abstract This study examines the biases, intermodel spread, and intermodel range of surface air temperature (SAT) across the Antarctic ice sheet and Southern Ocean in 26 structurally different climate models. Over the ocean (40°–60°S), an ensemble-mean warm bias peaks in late austral summer concurrently with the peak in the intermodel range of SAT. This warm bias lags a spring–summer positive bias in net surface radiation due to weak shortwave cloud forcing and is gradually reduced during autumn and winter. For the ice sheet, inconsistencies among reanalyses and observational datasets give low confidence in the ensemble-mean bias of SAT, but a small summer warm bias is suggested in comparison with nonreanalysis SAT data. The ensemble mean hides a large intermodel range of SAT, which peaks during the summer insolation maximum. In summer on the ice sheet, the SAT intermodel spread is largely associated with the surface albedo. In winter, models universally exhibit a too-strong deficit in net surface radiation related to the downward longwave radiation, implying that the lower atmosphere is too stable. This radiation deficit is balanced by the transfer of sensible heat toward the surface (which largely explains the intermodel spread in SAT) and by a subsurface heat flux. The winter bias in downward longwave radiation is due to the longwave cloud radiative effect, which the ensemble mean underestimates by a factor of 2. The implications of these results for improving climate simulations over Antarctica and the Southern Ocean are discussed.

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Revising short and longwave radiation archives in view of possible revisions of the WSG and WISG reference scales: Methods and implications

10.5194/amt-2017-41 ◽

2017 ◽

Author(s):

Stephan Nyeki ◽

Stefan Wacker ◽

Julian Gröbner ◽

Wolfgang Finsterle ◽

Martin Wild

Keyword(s):

Time Series ◽

Longwave Radiation ◽

Surface Radiation ◽

Shortwave Radiation ◽

Standard Group ◽

Water Vapour Content ◽

Data Archives ◽

Downward Longwave Radiation ◽

Integrated Water Vapour ◽

A Minor

Abstract. A large number of radiometers are traceable to the World Standard Group (WSG) for shortwave radiation and the interim World Infra-red Standard Group (WISG) for longwave radiation, hosted by the Physikalisch Meteorologisches Observatorium Davos/World Radiation Centre (PMOD/WRC, Davos, Switzerland). The WSG and WISG have recently been found to over- and underestimate radiation values, respectively (Fehlmann et al., 2012; Gröbner et al., 2014), although research is still ongoing. In view of a possible revision of the reference scales of both standard groups, this study discusses the methods involved, and the implications on existing archives of radiation time-series, such as the Baseline Surface Radiation Network (BSRN). Based on PMOD/WRC calibration archives and BSRN data archives, the downward longwave radiation (DLR) time-series over the 2006–2015 periods were analysed at four stations (polar and mid-latitude locations). DLR was found to increase by up to 3.5 and 5.4 W m−2, respectively, after applying a WISG reference scale correction and a minor correction for the dependence of pyrgeometer sensitivity on atmospheric integrated water vapour content. Similar increases in DLR may be expected at other BSRN stations. Based on our analysis, a number of recommendations are made for future studies.

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Revising shortwave and longwave radiation archives in view of possible revisions of the WSG and WISG reference scales: methods and implications

Atmospheric Measurement Techniques ◽

10.5194/amt-10-3057-2017 ◽

2017 ◽

Vol 10 (8) ◽

pp. 3057-3071 ◽

Cited By ~ 6

Author(s):

Stephan Nyeki ◽

Stefan Wacker ◽

Julian Gröbner ◽

Wolfgang Finsterle ◽

Martin Wild

Keyword(s):

Time Series ◽

Longwave Radiation ◽

Surface Radiation ◽

Shortwave Radiation ◽

Standard Group ◽

Water Vapour Content ◽

Data Archives ◽

Downward Longwave Radiation ◽

Integrated Water Vapour ◽

A Minor

Abstract. A large number of radiometers are traceable to the World Standard Group (WSG) for shortwave radiation and the interim World Infrared Standard Group (WISG) for longwave radiation, hosted by the Physikalisch-Meteorologisches Observatorium Davos/World Radiation Centre (PMOD/WRC, Davos, Switzerland). The WSG and WISG have recently been found to over- and underestimate radiation values, respectively (Fehlmann et al., 2012; Gröbner et al., 2014), although research is still ongoing. In view of a possible revision of the reference scales of both standard groups, this study discusses the methods involved and the implications on existing archives of radiation time series, such as the Baseline Surface Radiation Network (BSRN). Based on PMOD/WRC calibration archives and BSRN data archives, the downward longwave radiation (DLR) time series over the 2006–2015 period were analysed at four stations (polar and mid-latitude locations). DLR was found to increase by up to 3.5 and 5.4 W m−2 for all-sky and clear-sky conditions, respectively, after applying a WISG reference scale correction and a minor correction for the dependence of pyrgeometer sensitivity on atmospheric integrated water vapour content. Similar increases in DLR may be expected at other BSRN stations. Based on our analysis, a number of recommendations are made for future studies.

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Estimating Surface Downward Longwave Radiation Using Machine Learning Methods

Atmosphere ◽

10.3390/atmos11111147 ◽

2020 ◽

Vol 11 (11) ◽

pp. 1147 ◽

Cited By ~ 1

Author(s):

Chunjie Feng ◽

Xiaotong Zhang ◽

Yu Wei ◽

Weiyu Zhang ◽

Ning Hou ◽

...

Keyword(s):

Machine Learning ◽

Land Cover ◽

Time Scale ◽

Longwave Radiation ◽

Surface Radiation ◽

Gradient Boosting ◽

Support Vector ◽

Learning Methods ◽

Machine Learning Methods ◽

Downward Longwave Radiation

The downward longwave radiation (Ld, 4–100 μm) is a major component of research for the surface radiation energy budget and balance. In this study, we applied five machine learning methods, namely artificial neural network (ANN), support vector regression (SVR), gradient boosting regression tree (GBRT), random forest (RF), and multivariate adaptive regression spline (MARS), to estimate Ld using ground measurements collected from 27 Baseline Surface Radiation Network (BSRN) stations. Ld measurements in situ were used to validate the accuracy of Ld estimation models on daily and monthly time scales. A comparison of the results demonstrated that the estimates on the basis of the GBRT method had the highest accuracy, with an overall root-mean-square error (RMSE) of 17.50 W m−2 and an R value of 0.96 for the test dataset on a daily time scale. These values were 11.19 W m−2 and 0.98, respectively, on a monthly time scale. The effects of land cover and elevation were further studied to comprehensively evaluate the performance of each machine learning method. All machine learning methods achieved better results over the grass land cover type but relatively worse results over the tundra. GBRT, RF, and MARS methods were found to show good performance at both the high- and low-altitude sites.

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Estimation of Long-Term Surface Downward Longwave Radiation over the Global Land from 2000 to 2018

Remote Sensing ◽

10.3390/rs13091848 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1848

Author(s):

Chunjie Feng ◽

Xiaotong Zhang ◽

Yu Wei ◽

Weiyu Zhang ◽

Ning Hou ◽

...

Keyword(s):

Water Vapor ◽

Spatial Resolution ◽

Land Surface ◽

Longwave Radiation ◽

Surface Radiation ◽

Radiation Budget ◽

Mean Bias Error ◽

Downward Longwave Radiation ◽

Global Land

It is of great importance for climate change studies to construct a worldwide, long-term surface downward longwave radiation (Ld, 4–100 μm) dataset. Although a number of global Ld datasets are available, their low accuracies and coarse spatial resolutions limit their applications. This study generated a daily Ld dataset with a 5-km spatial resolution over the global land surface from 2000 to 2018 using atmospheric parameters, which include 2-m air temperature (Ta), relative humidity (RH) at 1000 hPa, total column water vapor (TCWV), surface downward shortwave radiation (Sd), and elevation, based on the gradient boosting regression tree (GBRT) method. The generated Ld dataset was evaluated using ground measurements collected from AmeriFlux, AsiaFlux, baseline surface radiation network (BSRN), surface radiation budget network (SURFRAD), and FLUXNET networks. The validation results showed that the root mean square error (RMSE), mean bias error (MBE), and correlation coefficient (R) values of the generated daily Ld dataset were 17.78 W m−2, 0.99 W m−2, and 0.96 (p < 0.01). Comparisons with other global land surface radiation products indicated that the generated Ld dataset performed better than the clouds and earth’s radiant energy system synoptic (CERES-SYN) edition 4.1 dataset and ERA5 reanalysis product at the selected sites. In addition, the analysis of the spatiotemporal characteristics for the generated Ld dataset showed an increasing trend of 1.8 W m−2 per decade (p < 0.01) from 2003 to 2018, which was closely related to Ta and water vapor pressure. In general, the generated Ld dataset has a higher spatial resolution and accuracy, which can contribute to perfect the existing radiation products.

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Observations of Stratocumulus Clouds and Their Effect on the Eastern Pacific Surface Heat Budget along 20°S

Journal of Climate ◽

10.1175/jcli-d-11-00618.1 ◽

2012 ◽

Vol 25 (24) ◽

pp. 8542-8567 ◽

Cited By ~ 47

Author(s):

Simon P. de Szoeke ◽

Sandra Yuter ◽

David Mechem ◽

Chris W. Fairall ◽

Casey D. Burleyson ◽

...

Keyword(s):

Radiative Forcing ◽

Heat Budget ◽

Coupled Model ◽

Longwave Radiation ◽

Cloud Fraction ◽

Surface Radiation ◽

Cloud Base ◽

Diurnal Cycles ◽

Downward Longwave Radiation ◽

Stratocumulus Clouds

Abstract Widespread stratocumulus clouds were observed on nine transects from seven research cruises to the southeastern tropical Pacific Ocean along 20°S, 75°–85°W in October–November of 2001–08. The nine transects sample a unique combination of synoptic and interannual variability affecting the clouds; their ensemble diagnoses longitude–vertical sections of the atmosphere, diurnal cycles of cloud properties and drizzle statistics, and the effect of stratocumulus clouds on surface radiation. Mean cloud fraction was 0.88, and 67% of 10-min overhead cloud fraction observations were overcast. Clouds cleared in the afternoon [1500 local time (LT)] to a minimum of fraction of 0.7. Precipitation radar found strong drizzle with reflectivity above 40 dBZ. Cloud-base (CB) heights rise with longitude from 1.0 km at 75°W to 1.2 km at 85°W in the mean, but the slope varies from cruise to cruise. CB–lifting condensation level (LCL) displacement, a measure of decoupling, increases westward. At night CB–LCL is 0–200 m and increases 400 m from dawn to 1600 LT, before collapsing in the evening. Despite zonal gradients in boundary layer and cloud vertical structure, surface radiation and cloud radiative forcing are relatively uniform in longitude. When present, clouds reduce solar radiation by 160 W m−2 and radiate 70 W m−2 more downward longwave radiation than clear skies. Coupled Model Intercomparison Project phase 3 (CMIP3) simulations of the climate of the twentieth century show 40 ± 20 W m−2 too little net cloud radiative cooling at the surface. Simulated clouds have correct radiative forcing when present, but models have ~50% too few clouds.

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On the Suitability of Current Atmospheric Reanalyses for Regional Warming Studies over China

10.5194/acp-2017-966 ◽

2017 ◽

Cited By ~ 1

Author(s):

Chunlüe Zhou ◽

Yanyi He ◽

Kaicun Wang

Keyword(s):

Regional Climate ◽

Surface Air Temperature ◽

Longwave Radiation ◽

Regional Climate Change ◽

Precipitation Frequency ◽

Regional Warming ◽

Downward Longwave Radiation ◽

In Situ Observations ◽

Mean Differences

Abstract. Reanalyses have been widely used because they add value to the routine observations by generating physically/dynamically consistent and spatiotemporally complete atmospheric fields. Existing studies have extensively discussed their temporal suitability in global change study. This study moves forward on their suitability for regional climate change study where land–atmosphere interactions play a more important role. Here, surface air temperature (Ta) from 12 current reanalysis products were investigated, focusing on spatial patterns of Ta trends, using homogenized Ta from 1979 to 2010 at ~ 2200 meteorological stations in China. Results show that ~ 80 % of the Ta mean differences between reanalyses and in-situ observations are attributed to station and model-grid elevation differences, denoting good skill in Ta climatology and rebutting the previously reported Ta biases. However, the Ta trend biases in reanalyses display spatial divergence (standard deviation = 0.15–0.30 °C/decade at 1° × 1° grids). The simulated Ta trend biases correlate well with those of precipitation frequency, surface incident solar radiation (Rs), and atmospheric downward longwave radiation (Ld) among the reanalyses (r = −0.83, 0.80 and 0.77, p

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