Atmospheric Longwave Radiation Research Articles

Drivers of the mean biases of the tropical atmospheric circulation in a moist static energy framework

In this study, we apply the moist static energy for first baroclinic mode (MSEB) model to examine the drivers of the mean tropical atmospheric circulation biases over oceanic regions. The model diagnoses the vertical motion in an air column of the tropical regions based on net energy heat flux and advection of moisture or heat into the air column in relation to the stability of the air column due to the gradients in moist static energy. Analysis of Coupled Model Intercomparison Project (CMIP) and Atmospheric Model Intercomparison Project (AMIP) simulations helped to identified errors intrinsic to the atmospheric models or errors due to atmosphere–ocean coupling process. Despite some limitations of the MSEB model, our multi-model mean analysis over the entire tropical ocean reveals that the primary drivers of the tropical circulation biases mostly result from intrinsic atmospheric model errors in top of the atmosphere longwave radiation and surface latent heats fluxes, suggesting a link to biases in the hydrological cycle. Oceanic coupling significantly enhanced some of the biases. Biases in the advection of moist static energy also play an important role, while biases in the gross moist stability profiles play only a minor role. Further, we examine the inter-model variations in four main regional large-scale biases (double-ITCZ, Pacific cold tongue, southward shift of ITCZ over the Atlantic, and dipole bias over the Indian Ocean). The analysis suggests that regional bias patterns across general circulation models are primarily driven by coupling errors, except for the bias in the Indian Ocean, which is intrinsic to the atmospheric model but amplified by coupling. Notably, longwave radiation biases at the top of the atmosphere are prevalent among the four bias patterns, as well as biases in moisture advection over the Atlantic. Our results underscore the significant role of net longwave radiation at the top of the atmosphere, an aspect not sufficiently emphasized in previous studies.

Urban heat and pollution island in the Moscow megacity: Urban environmental compartments and their interactions

Cities are highly interconnected systems where specific interactions between various urban environments occur due to the Urban Heat Island (UHI) and Urban Pollution Island (UPI) effects. Four compartments of the environment (atmospheric air, road dust, streamflow, and people) are discussed for Moscow city. Long-term meteorological, radiative, air quality, and precipitation measurements, the non-hydrostatic regional numerical COSMO model, and extensive hydrological and geochemical sampling were used. To characterize mortality and UPI interaction, a family of distributed lag non-linear models (DLNM) was applied. The study reveals increased aerosols concentrations which reduce the incoming solar radiation and increase the atmospheric longwave radiation. UHI strengthens the low-troposphere convergence due to urban breeze circulation and atmospheric circulation due to elevated surface roughness, the effect which leads to 11.6% heaviest precipitation increase compared to background values. Increased precipitation doubles streamflow rates and enhances the contribution of rain floods to annual flow. Similar geochemical associations with Sb, W, Zn, Cd, Pb, and Cu were found in aerosol PM10, indicating transport and road dust impact. Finally, associations between high temperatures and human mortality which are generally stronger at high levels of air pollution for both PM10 and NO2, and for lag 1 day and 2–6 days are discussed.

Using an Absolute Cavity Pyrgeometer to Calibrate Pyrgeometers Outdoors with Respect to the International System of Units

Accurate measurement of the atmospheric longwave irradiance is important for renewable energy and atmospheric science applications. Pyrgeometers are deployed outdoors all over the world to measure the atmospheric longwave irradiance and presently are calibrated with traceability to the interim standards for atmospheric longwave radiation measurement, the standards are based on four pyrgeometers and their average irradiance is the World InfraRed Standard Group (WISG) which is developed and maintained by The Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC). Since 2013 the InfraRed Integrating Sphere (IRIS) developed by PMOD/WRC and the Absolute Cavity Pyrgeometer (ACP) developed by the National Renewable Energy Laboratory (NREL) have been compared outdoors six times at different locations and the difference between the measured atmospheric longwave irradiance by ACP and IRIS was less than 2 W/m<sup>2</sup> with traceability to the International System of Units (SI). During the six comparisons the irradiance measured by the interim WISG was 5 W/m<sup>2</sup> lower than the irradiance measured by the average irradiance measured by the ACP and IRIS [1]. Based on this discrepancy, the World Meteorological Organization’s Commission for Instruments and Methods of Observation (CIMO) recommended that the interim WISG should be adjusted to be traceable to SI units [2]. In anticipation of CIMO’s expert team agreement on establishing the world reference using the average irradiance measured by ACP and IRIS in this article we describe a procedure to calibrate pyrgeometers with traceability to SI. One Absolute Cavity Pyrgeometer (ACP95F3) was used to calibrate four pyrgeometers traceable to SI units. Three Eppley PIRs and one Kipp&Zonen CG4 were originally calibrated with traceability to the interim WISG. Using the described procedure below, the responsivity of each pyrgeometer was then adjusted to match the irradiance measured by ACP. Outdoor data was collected during one clear sky nights monitored by the output thermopile voltage of ACP95F3. The irradiance measured by the PIRs was calculated using NREL equation and the CG4 using NREL equation and PMOD/WRC equation. Using the NREL equation, the calculated uncertainty (<i>U</i><sup>95</sup>) of the PIRs varied from 2.43 W/m<sup>2</sup> to 2.67 W/m<sup>2</sup>, and for the CG4 using the NREL equation <i>U</i><sub>95</sub> equals 1.97 W/m<sup>2</sup>, and using the PMOD equation <i>U</i><sub>95</sub> equals 2.88 W/m<sup>2</sup> with respect to SI.

Clouds drive differences in future surface melt over the Antarctic ice shelves

Abstract. Recent warm atmospheric conditions have damaged the ice shelves of the Antarctic Peninsula through surface melt and hydrofracturing and could potentially initiate future collapse of other Antarctic ice shelves. However, model projections with similar greenhouse gas scenarios suggest large differences in cumulative 21st-century surface melting. So far it remains unclear whether these differences are due to variations in warming rates in individual models or whether local feedback mechanisms of the surface energy budget could also play a notable role. Here we use the polar-oriented regional climate model MAR (Modèle Atmosphérique Régional) to study the physical mechanisms that would control future surface melt over the Antarctic ice shelves in high-emission scenarios RCP8.5 and SSP5-8.5. We show that clouds enhance future surface melt by increasing the atmospheric emissivity and longwave radiation towards the surface. Furthermore, we highlight that differences in meltwater production for the same climate warming rate depend on cloud properties and particularly cloud phase. Clouds containing a larger amount of supercooled liquid water lead to stronger melt, subsequently favouring the absorption of solar radiation due to the snowmelt–albedo feedback. As liquid-containing clouds are projected to increase the melt spread associated with a given warming rate, they could be a major source of uncertainties in projections of the future Antarctic contribution to sea level rise.

Trends and Variability of Atmospheric Downward Longwave Radiation Over China From 1958 to 2015

AbstractSurface downward longwave radiation (SDLR) is a major component of the energy budget. Although studies have reported the spatiotemporal variations of SDLR in China, the spatiotemporal coverage of the situ measurements used is always limited. In this study, the gradient boosting regression tree (GBRT) was developed to reconstruct SDLR based on air temperature (Ta), relative humidity (RH), and downward shortwave radiation (DSR). Ground measurements collected at the Baseline Surface Radiation Network (BSRN) and the Arid and Semi‐arid Region Collaborative Observation Project (ASRCOP) were used to build and evaluate the GBRT model. The evaluation results showed that the daily SDLR estimates are correlated well with the SDLR in situ, with an overall root mean square errors (RMSE) of 16.5 Wm−2 and a correlation coefficient (R) value of 0.91 for the validation data set. Comparison with existing SDLR products showed that accuracy and trends of the SDLR estimates based on the GBRT method are reasonable. To obtain long‐term SDLR data for spatiotemporal analysis over China, densely distributed reconstructed DSR and ground measured Ta and RH collected at 756 Chinese Meteorological Administration (CMA) stations were used as input to estimate the SDLR based on the GBRT method over China during 1958–2015. The long‐term estimated SDLRs at the selected 563 stations showed that SDLR increased at an average rate of 1.3 Wm−2 per decade over China from 1958 to 2015. The trend of SDLR is positively correlated with the trend in Ta and water vapor pressure, whereas negatively correlated with the trend in DSR.

Short-term periodicities in the downward longwave radiation and their associations with cosmic ray and solar interplanetary data

In this study downward longwave (LW) atmospheric radiation data for the period of 2014–2020 were used to search for short-term periodicities using fast Fourier transform (FFT). Several local peaks in the power spectrum density were found and established. The time series exhibits a series of significant peaks (exceeding the 95% confidence limit), such as at 273 days, 227 days, 200 days, 178 days, 157 days, 110 days, 120 days, 87 days, 73 days, 53–56 days, 35–30 days, 25–27 days, 21 days, 13 days, and 9–10 days.Moreover, cosmic ray data from KACST muon detector and the Oulu neutron monitor, as well as the data for the solar radio flux at 10.7 cm (F10.7 cm), Dst index, and solar wind speed for the same period as the LW data, were used to look for common cyclic variations and periodicities matching those found in the LW radiation. This was done to investigate the possible effect of the solar activity parameters on LW radiation. Several common periodicities were observed in the spectra of all the variables considered, such as 227 days, 154–157 days, 25–27 days, and 21 days. Some of the periodicities found in the LW radiation spectrum can be attributed to the modulation of the cosmic ray intensity by solar activity. Others are attributed to the disturbances in the interplanetary magnetic field. Based on the spectral results, we suggest that the solar signals may directly or indirectly affect the variations of the downward longwave radiation, which in turn may affect climate change.

Evaluation of Atmospheric Downward Longwave Radiation in the Brazilian Pampa Region

Atmospheric downward longwave radiation flux (L↓) is a variable that directly influences the surface net radiation and consequently, weather and climatic conditions. Measurements of L↓ are scarce, and the use of classical models depending on some atmospheric variables may be an alternative. In this paper, we analyzed L↓ measured over the Brazilian Pampa biome. This region is located in a humid subtropical climate zone and characterized by well defined seasons and well distributed precipitation. Furthermore, we evaluated the performance of the eleven classical L↓ models for clear sky with one-year experimental data collected in the Santa Maria experimental site (SMA) over native vegetation and high relative humidity throughout the year. Most of the L↓ estimations, using the original coefficients, underestimated the experimental data. We performed the local calibration of the L↓ equations coefficients over an annual period and separated them into different sky cover classifications: clear sky, partly cloudy sky, and cloudy sky. The calibrations decreased the errors, especially in cloudy sky classification. We also proposed the joint calibration between the clear sky emissivity equations and cloud sky correction function to reduce errors and evaluate different sky classifications. The results found after these calibrations presented better statistical indexes. Additionally, we presented a new empirical model to estimate L↓ based on multiple regression analysis using water vapor pressure and air temperature. The new equation well represents partial and cloudy sky, even without including the cloud cover parameterization, and was validated with the following five years in SMA and two years in the Cachoeira do Sul experimental site (CAS). The new equation proposed herein presents a root mean square error ranging from 13 to 21 Wm−2 and correlation coefficient from 0.68 to 0.83 for different sky cover classifications. Therefore, we recommend using the novel equation to calculate L↓ over the Pampa biome under these specific climatic conditions.

Constraining Global Changes in Temperature and Precipitation From Observable Changes in Surface Radiative Heating

AbstractChanges in the atmospheric composition alter the magnitude and partitioning between the downward propagating solar and atmospheric longwave radiative fluxes heating the Earth's surface. These changes are computed by radiative transfer codes in Global Climate Models and measured with high precision at surface observation networks. Changes in radiative heating signify changes in the global surface temperature and hydrologic cycle. Here, we develop a conceptual framework using an Energy Balance Model to show that first‐order changes in the hydrologic cycle are mainly associated with changes in solar radiation, while those in surface temperature are mainly associated with changes in atmospheric longwave radiation. These insights are used to explain a range of phenomena including observed historical trends, biases in climate model output, and the intermodel spread in climate change projections. These results may help identify biases in future generations of climate models.

Seasonal division of 850 hPa South China Sea based on multi-element atmospheric condition similarity

Comprehensive consideration of multiple meteorological elements for the objective identification and division of seasonal changes is important in the field of climate monitoring and diagnostic analysis. The development of relevant identification and classification methods will help us better understand the new characteristics of seasonal transitions against the background of climate change. Based on reanalysis data from the National Centers for Environmental Prediction from 1950 to 2015, we used the multi-element atmospheric condition similarity method to seasonally divide the average climatological conditions at 850 hPa over the South China Sea, and analyzed the annual mean results of the onset of seasons and annual mean seasonal variations of meteorological elements in this region. The results show the following. First, the seasonal division results based on multi-element atmospheric condition similarity coincide with the seasonal variation times of each meteorological element with atmospheric conditions comprising five meteorological elements. When the four seasons change, the meteorological elements at 850 hPa in the South China Sea have obvious seasonal variation, and atmospheric circulation and surface upward long-wave radiation change conspicuously with seasonal transformation. This confirms the validity of the method as applied to seasonal divisions in the South China Sea. Second, when the climate system translates from winter to summer in the South China Sea, thermal elements change greatly and rapidly. Changes to thermal elements in spring provide climate conditions for the onset of summer and the onset of the summer monsoon in the South China Sea. Third, when the climate system shifts from summer to winter in the South China Sea, changes to wind elements are obvious and rapid. In autumn, changes in thermal conditions between the Eurasian continent and the Pacific Ocean lead to major changes in atmospheric circulation and wind. In addition, seasonal divisions are no longer just nodes of time. Rather, they can be used as important indicators for further studies of atmospheric circulation changes, short-term climate predictions, and seasonal changes of other climate systems.

Assessing the large-scale variation of heat budget in poorly gauged watershed-shallow lake system using a novel integrated modeling approach

Assessment of large-scale temperature dynamics and heat fluxes in shallow lakes requires comprehensive modeling capabilities to simulate water interactions, the processes related to the heat budget, and their driving forces. In this study, we investigated the spatial and temporal variations in water-surface temperature (WST) and surface heat fluxes for the period between January 2001 and December 2010 in Lake Mirim, a large (surface area ca. 4000 km2) shallow lake on the Brazil-Uruguay border. The aquatic ecosystem was examined using in-situ WST measurements, MODIS land surface temperature (M*D11A1 LST) products, and a coupling between a large-scale hydrologic model (MGB-IPH) and a hydrodynamic/water quality model (IPH-ECO). The WST values estimated by the hydrodynamic model were consistent with measured in-situ data and MODIS-derived WST, using both daytime and nighttime time series (R2 = 0.88; Bias = 1.45 °C; RMSE = 2.16 °C; ENS = 0.77). Our findings also revealed that the dominant heat fluxes in the lake are the atmospheric longwave radiation (annual mean = 303.38 W m−2), water longwave radiation (annual mean = 336.01 W m−2), and the latent heat flux (annual mean = 51.14 W m−2). Additionally, the heat flux from the river inflows contribute minimally to the overall seasonal heat budget in the lake, being the Cebollati river the main contributor (annual average = 4.63 W m−2). Coupled large-scale hydrological and hydrodynamic models will benefit future modeling efforts by providing an effective management tool to study the effect of case scenarios (e.g., climate change) on temperature dynamics, heat fluxes, and physical and ecological processes in these ecosystems.

The effect of screen level and upper air temperatures and atmospheric moisture on the downward atmospheric radiation in the South Australian region

Determination of the long wave (LW) atmospheric radiation (λ = 4–100 μm) is of great importance for several applications. In this study, the effect of screen level and upper air temperatures and water vapour contents on the LW radiation for clear skies has been investigated using 4 years of measurements conducted in Adelaide (34.9° S;130.6° E), South Australia. A two-variable model, which depends on the screen level temperature and vapour pressure, has been developed to calculate the LW radiation. The model can predict the hourly measured data with a correlation coefficient of 0.88, giving mean bias error (MBE) of 0.21 W/m2, root mean square error (RMSE) of 17.3 W/m2, and a mean percentage error (MPE) of − 0.11% with respect to hourly observations. The performance of the multilinear model was tested against a 1-year independent data set. In this case, the MBE, RMSE, MPE, and correlation coefficient were 0.94 W/m2, − 2.2 W/m2, 18.1 W/m2, − 0.5%, and 0.85, respectively. Using radiosonde data, the total atmospheric water content has been calculated and its effect on the LW radiation has been investigated. A simple model that uses the screen level temperature and the precipitable water vapour (PWV) has been proposed. The correlation coefficient, MBE, and RMSE for this model were 0.93, 0.08 W/m2, and 12.12 W/m2, respectively; an MPE of 0.09% was reported by the model. The predictions of ten well-known clear sky models have been evaluated against the measured LW radiation data. These models were, then, adjusted and their performances have been assessed. The impact of the atmospheric mean weighted temperature on the LW radiation was studied. We have found that this temperature has less of an effect on the LW atmospheric radiation than screen level temperature. Finally, the clear sky model which uses the screen level parameters has been adjusted to account for the effect of clouds on the LW radiation. The model shows an acceptable predictability for the LW radiation under all sky conditions. The MBE, RMSE, MPE, and correlation coefficient for this model were 0.51 W/m2, 22.5 W/m2, 0.2% and 0.80, respectively.

Comparison of observed and modeled cloud-free longwave downward radiation (2010–2016) at the high mountain BSRN Izaña station

Abstract. A 7-year (2010–2016) comparison study between measured and simulated longwave downward radiation (LDR) under cloud-free conditions was performed at the Izaña Atmospheric Observatory (IZO, Spain). This analysis encompasses a total of 2062 cases distributed approximately evenly between day and night. Results show an excellent agreement between Baseline Surface Radiation Network (BSRN) measurements and simulations with libRadtran V2.0.1 and MODerate resolution atmospheric TRANsmission model (MODTRAN) V6 radiative transfer models (RTMs). Mean bias (simulated − measured) of < 1.1 % and root mean square of the bias (RMS) of < 1 % are within the instrumental error (2 %). These results highlight the good agreement between the two RTMs, proving to be useful tools for the quality control of LDR observations and for detecting temporal drifts in field instruments. The standard deviations of the residuals, associated with the RTM input parameters uncertainties are rather small, 0.47 and 0.49 % for libRadtran and MODTRAN, respectively, at daytime, and 0.49 to 0.51 % at night-time. For precipitable water vapor (PWV) > 10 mm, the observed night-time difference between models and measurements is +5 W m−2 indicating a scale change of the World Infrared Standard Group of Pyrgeometers (WISG), which serves as reference for atmospheric longwave radiation measurements. Preliminary results suggest a possible impact of dust aerosol on infrared radiation during daytime that might not be correctly parametrized by the models, resulting in a slight underestimation of the modeled LDR, of about −3 W m−2, for relatively high aerosol optical depth (AOD > 0.20).

Interaction between urban heat island and urban pollution island during summer in Berlin

Urban Heat Island (UHI) and Urban Pollution Island (UPI) are two major problems of the urban environment and have become more serious with rapid urbanization. Since UHI and UPI can interact with each other, these two issues should be studied concurrently for a better urban environment. This study investigated the interaction between the UHI and UPI in Berlin, through a combined analysis of in-situ and remote sensing observations of aerosols and meteorological variables in June, July, and August from 2010 to 2017. The atmospheric UHI (AUHI), surface UHI (SUHI), atmospheric UPI (AUPI), and near-surface UPI (NSUPI) were analyzed. The SUHI and AUPI are represented by the remote sensing land surface temperature (LST) and aerosol optical depth (AOD), and the AUHI and NSUPI are represented by the in-situ air temperature and Particulate Matter (PM10) concentrations. The study area shows spatial consistency between SUHI and AUPI, with higher LST and AOD in the urban areas. UHI strengthens the turbulent dispersion of particles in the urban areas, decreasing the NSUPI. The NSUPI intensity shows a negative relationship with the AUHI intensity, especially at night with a correlation coefficient of −0.31. The increased aerosols in urban atmosphere reduce the incoming solar radiation and increase the atmospheric longwave radiation in the urban areas. The response of the surface to the change of absorbed radiation is strong at night and weak during the day. This study estimates that the SUHI intensity is enhanced by around 12% at clear night by the increased absorbed radiation in the urban areas using an attribution method. The goal of this paper is to strengthen the understanding of the interactive influence between UHI and UPI and provide a basis for designing mitigation strategies of UHI and UPI.

Evaluation of the atmospheric longwave radiation models estimated in Brasilia – DF

A radiação atmosférica de ondas prolongadas tem uma importância considerável nos estudos meteorológicos, bem como no aquecimento global. Por estar ligado aos gases atmosféricos e à temperatura do ar. Este artigo tem como objetivo avaliar o desempenho de doze modelos para a estimativa da radiação de onda longa atmosférica em Brasília-DF. Os dados meteorológicos utilizados neste estudo foram adquiridos a partir da rede de dados do Sistema de Organização de Dados Ambientais - SONDA. Neste estudo, os dados da temperatura do ar, umidade relativa, radiação global e radiação atmosférica de onda longa foram utilizados para os modelos avaliados. Os cálculos foram processados com médias horárias e diárias. A avaliação dos modelos e a comparação dos resultados estimados e medidos da radiação da onda longa atmosférica foram realizadas utilizando os métodos estatísticos do erro médio quadrado (RMSE), erro absoluto médio (MAE) e erro médio médio relativo (PMRE). O coeficiente de correlação de Pearson (r) e o coeficiente de determinação (R²) também foram aplicados. Os modelos que tiveram excelentes resultados foram Brunt (1932), Prata (1996), Berdahl e Martin (1984), Idso (1982) e Berger et al. (1984), uma vez que apresentaram um bom desempenho, devido aos menores valores de RMSE , MAE e PMRE

Spectral model for clear sky atmospheric longwave radiation

An efficient spectrally resolved radiative model is used to calculate surface downwelling longwave (DLW) radiation (0 ∼ 2500 cm−1) under clear sky (cloud free) conditions at the ground level. The wavenumber spectral resolution of the model is 0.01 cm−1 and the atmosphere is represented by 18 non-uniform plane-parallel layers with pressure in each layer determined on a pressure-based coordinate system. The model utilizes the most up-to-date (2016) HITRAN molecular spectral data for 7 atmospheric gases: H2O, CO2, O3, CH4, N2O, O2 and N2. The MT_CKD model is used to calculate water vapor and CO2 continuum absorption coefficients. Longwave absorption and scattering coefficients for aerosols are modeled using Mie theory. For the non-scattering atmosphere (aerosol free), the surface DLW agrees within 2.91% with mean values from the InterComparison of Radiation Codes in Climate Models (ICRCCM) program, with spectral deviations below 0.035 W cm m−2. For a scattering atmosphere with typical aerosol loading, the DLW calculated by the proposed model agrees within 3.08% relative error when compared to measured values at 7 climatologically diverse SURFRAD stations. This relative error is smaller than a calibrated parametric model regressed from data for those same 7 stations, and within the uncertainty (+/− 5 W m−2) of pyrgeometers commonly used for meteorological and climatological applications. The DLW increases by 1.86 ∼ 6.57 W m−2 when compared with aerosol-free conditions, and this increment decreases with increased water vapor content due to overlap with water vapor bands. As expected, the water vapor content at the layers closest to the surface contributes the most to the surface DLW, especially in the spectral region 0 ∼ 700 cm−1. Additional water vapor content (mostly from the lowest 1 km of the atmosphere) contributes to the spectral range of 400 ∼ 650 cm−1. Low altitude aerosols ( ∼ 3.46 km or less) contribute to the surface value of DLW mostly in the spectral range 750 ∼ 1400 cm−1.

An Evaluation of the Large-Scale Implementation of Ocean Thermal Energy Conversion (OTEC) Using an Ocean General Circulation Model with Low-Complexity Atmospheric Feedback Effects

Previous investigations of the large-scale deployment of Ocean Thermal Energy Conversions (OTEC) systems are extended by allowing some atmospheric feedback in an ocean general circulation model. A modified ocean-atmosphere thermal boundary condition is used where relaxation corresponds to atmospheric longwave radiation to space, and an additional term expresses horizontal atmospheric transport. This produces lower steady-state OTEC power maxima (8 to 10.2 TW instead of 14.1 TW for global OTEC scenarios, and 7.2 to 9.3 TW instead of 11.9 TW for OTEC implementation within 100 km of coastlines). When power production peaks, power intensity remains practically unchanged, at 0.2 TW per Sverdrup of OTEC deep cold seawater, suggesting a similar degradation of the OTEC thermal resource. Large-scale environmental effects include surface cooling in low latitudes and warming elsewhere, with a net heat intake within the water column. These changes develop rapidly from the propagation of Kelvin and Rossby waves, and ocean current advection. Two deep circulation cells are generated in the Atlantic and Indo-Pacific basins. The Atlantic Meridional Overturning Circulation (AMOC) is reinforced while an AMOC-like feature appears in the North Pacific, with deep convective winter events at high latitudes. Transport between the Indo-Pacific and the Southern Ocean is strengthened, with impacts on the Atlantic via the Antarctic Circumpolar Current (ACC).

Potential impact of reforestation programmes and uncertainties in land cover effects over the loess plateau: a regional climate modeling study

Using the Regional Climate Model version 4.3 (RegCM4.3), this paper investigates the potential effects of reforestation on the regional climate over the Loess Plateau in China with a focus on land-atmosphere interactions. Two land surface schemes are used here: the default Biosphere Atmosphere Transfer Scheme (BATS) and the Community Land Model version 3.5 (CLM3.5). Five simulations using a series of hypothetical reforestation scenarios from 1990 to 2009 have been performed. Results show that in the default BATS simulations, the surface air temperature increases significantly during both summer (June–July-August) and winter (December–January-February) seasons. These patterns are particularly evident over the south-eastern plateau where extensive areas of irrigated crop are converted to forest. In experiments with CLM3.5 and BATS with non-irrigation, in which irrigated crops are specified as regular crops, reforestation generally produces a more pronounced cooling effect in summer, and a slight cooling winter in CLM3.5 but a slight warming in BATS with non-irrigation. The land surface energy balance equation involving latent heat flux (LHF), absorbed solar radiation and downward atmospheric longwave radiation is used to explain the reforestation-induced seasonal responses. In the default BATS simulations, increased temperature induced by reforestation is predominantly driven by the reduced year round LHF. In contrast, the reforestation-induced summer cooling in CLM3.5 and BATS with non-irrigation is caused by the enhanced LHF. This study suggests that the default parameterization of irrigated crop in BATS overestimates soil water content and leading to excessive evapotranspiration (ET) in the Loess Plateau. Hence, non-irrigated cropland would be a more plausible land cover representation for the Loess Plateau, as demonstrated from the reforestation simulations using CLM3.5 and BATS with non-irrigation. An improved description of land characteristics in climate models is highly needed for a more reliable prediction of climate responses to land surface change.

On the determination of atmospheric longwave irradiance under all-sky conditions

In this work we review and recalibrate existing models, and present a novel comprehensive model for estimation of the downward atmospheric longwave (LW) radiation for clear and cloudy sky conditions. LW radiation is an essential component of thermal balances in the atmosphere, playing also a substantial role in the design and operation of solar power plants. Unlike solar irradiance, LW irradiance is not measured routinely by meteorological or solar irradiance sensor networks. In most cases, it must be calculated indirectly from meteorological variables using simple parametric models. Under clear skies, fifteen parametric models for calculating LW irradiance are compared and recalibrated. All models achieve higher accuracy after grid search recalibration, and we show that many of the previously proposed LW models collapse into only a few different families of models. A recalibrated Brunt-family model is recommended for future use due to its simplicity and high accuracy (rRMSE=4.37%). To account for the difference in nighttime and daytime clear-sky emissivities, nighttime and daytime Brunt-type models are proposed. Under all sky conditions, the information of clouds is represented by cloud cover fraction (CF) or cloud modification factor (CMF, available only during daytime). Three parametric models proposed in the bibliography are compared and calibrated, and a new model is proposed to account for the alternation of vertical atmosphere profile by clouds. The proposed all-sky model has 3.8–31.8% lower RMSEs than the other three recalibrated models. If GHI irradiance measurements are available, using CMF as a parameter yields 7.5% lower RMSEs than using CF. For different applications that require LW information during daytime and/or nighttime, coefficients of the proposed models are corrected for diurnal and nocturnal use.

Performance of site-specific parameterizations of longwave radiation

Abstract. In this work 10 algorithms for estimating downwelling longwave atmospheric radiation (L↓) and 1 for upwelling longwave radiation (L↑) are integrated into the JGrass-NewAge modelling system. The algorithms are tested against energy flux measurements available for 24 sites in North America to assess their reliability. These new JGrass-NewAge model components are used (i) to evaluate the performances of simplified models (SMs) of L↓, as presented in literature formulations, and (ii) to determine by automatic calibration the site-specific parameter sets for L↓ in SMs. For locations where calibration is not possible because of a lack of measured data, we perform a multiple regression using on-site variables, i.e. mean annual air temperature, relative humidity, precipitation, and altitude. The regressions are verified through a leave-one-out cross validation, which also gathers information about the possible errors of estimation. Most of the SMs, when executed with parameters derived from the multiple regressions, give enhanced performances compared to the corresponding literature formulation. A sensitivity analysis is carried out for each SM to understand how small variations of a given parameter influence SM performance. Regarding the L↓ simulations, the Brunt (1932) and Idso (1981) SMs, in their literature formulations, provide the best performances in many of the sites. The site-specific parameter calibration improves SM performances compared to their literature formulations. Specifically, the root mean square error (RMSE) is almost halved and the Kling–Gupta efficiency is improved at all sites. Also in this case, Brunt (1932) and Idso (1981) SMs provided the best performances. The L↑ SM is tested by using three different temperatures (surface soil temperature, air temperature at 2 m elevation, and soil temperature at 4 cm depth) and model performances are then assessed. Results show that the best performances are achieved using the surface soil temperature and the air temperature.

CALIBRAÇÃO DE EQUAÇÕES CLÁSSICAS PARA RADIAÇÃO DE ONDA LONGA NA REGIÃO DE PAMPA EM DIAS DE CÉU CLARO

The atmospheric longwave radiation is a fundamental quantity in calculating the radiation balance at the surface. Measures of this magnitude in the gaucho Pampas region are scarce. An alternative estimate for this variable is the use of classical equations that use air temperatures and steam pressure. The objective of this study was to evaluate the performance of five equations in the estimation of the long atmospheric wave radiation for a clear day on a Pampa biome located in Santa Maria-RS. Atmospheric longwave radiation measurements taken throughout the year 2014 on the site of Santa Maria / Brazil were used to validate the performance of equations. After the radiation estimates by classical equations, an adjustment by least squares was empegando to calibrate such equations to the biome Pampa. By adjusting it noted that the equation Brutsaert (1975) was best described obsevada long wave radiation in the PAMPA region.