Surface Net Radiation Research Articles

Further Development of the Regional Boundary Layer Model to Study the Impacts of Greenery on the Urban Thermal Environment

AbstractA forest canopy model is developed and coupled into the Regional Boundary Layer Model (RBLM) to fully consider the vertical structure of tree morphology. Instead of a slab surface model formerly used to represent trees in RBLM, the new version allows refinement of the radiation budgets as well as sensible and latent heat fluxes and, hence, more precise simulation of the thermal impacts of tree plantings on urban meteorological behavior. By applying this new version of RBLM, sensitivity tests are conducted to explore the potential impacts of different greenery scenarios on the thermal environment in an eastern Chinese city, Suzhou, during hot summer days. Greenings, both tree planting and grass surfacing, are beneficial in cooling the ambient air temperature. In general, tree planting is more beneficial than grass surfacing with the same coverage. In terms of surface energy balance, with tree coverage increasing from 0% to 20%, and then to 40%, the average surface net radiation fluxes at noon (1200 LST) are 591, 512, and 421 W m−2, respectively. Correspondingly, the Bowen ratio is reduced from 8.78 to 1.20 and then to 0.43 as result of the redistribution of solar energy absorbed at the ground. The cooling effect of trees is more significant at noontime and can remarkably lower the daily maximum air temperature in urban areas. The cooling effect of urban greenery increases with its coverage. Using the study results, a tree coverage of around 40% may be a feasible and optimized urban greenery scheme.

Contribution of surface roughness to simulations of historical deforestation

Surface roughness which partitions surface net radiation into energy fluxes is a key parameter for estimation of biosphere–atmosphere interactions and climate variability. An earth system model of intermediate complexity (EMIC), MPM-2, is used to derive the impact of surface roughness on climate from simulations of historical land cover change effects. The direct change in surface roughness leads to a global surface warming of 0.08°C through altering the turbulence in the boundary layer. The regional temperature response to surface roughness associated deforestation is very strong at northern mid-latitudes with a most prominent warming of 0.72°C around 50°N in the Eurasia continent during summer. They can be explained mainly as direct and indirect consequences of decreases in surface albedo and increases in precipitation in response to deforestation, although there are a few significant changes in precipitation. There is also a prominent warming of 0.25°C around 40°N in the North American continent. This study indicates that land surface roughness plays a significant role which is comparable with the whole land conversion effect in climate change. Therefore, further investigation of roughness–climate relationship is needed to incorporate these aspects.

Evaluation of North Eurasian snow-off dates in the ECHAM5.4 atmospheric general circulation model

Abstract. The timing of springtime end of snowmelt (snow-off date) in northern Eurasia in version 5.4 of the ECHAM5 atmospheric general circulation model (GCM) is evaluated through comparison with a snow-off date data set based on space-borne microwave radiometer measurements and with Russian snow course data. ECHAM5 reproduces well the observed gross geographical pattern of snow-off dates, with earliest snow-off (in March) in the Baltic region and latest snow-off (in June) in the Taymyr Peninsula and in northeastern parts of the Russian Far East. The primary biases are (1) a delayed snow-off in southeastern Siberia (associated with too low springtime temperature and too high surface albedo, in part due to insufficient shielding by canopy); and (2) an early bias in the western and northern parts of northern Eurasia. Several sensitivity experiments were conducted, where biases in simulated atmospheric circulation were corrected through nudging and/or the treatment of surface albedo was modified. While this alleviated some of the model biases in snow-off dates, 2 m temperature and surface albedo, especially the early bias in snow-off in the western parts of northern Eurasia proved very robust and was actually larger in the nudged runs. A key issue underlying the snow-off biases in ECHAM5 is that snowmelt occurs at too low temperatures. Very likely, this is related to the treatment of the surface energy budget. On one hand, the surface temperature Ts is not computed separately for the snow-covered and snow-free parts of the grid cells, which prevents Ts from rising above 0 °C before all snow has vanished. Consequently, too much of the surface net radiation is consumed in melting snow and too little in heating the air. On the other hand, ECHAM5 does not include a canopy layer. Thus, while the albedo reduction due to canopy is accounted for, the shielding of snow on ground by the overlying canopy is not considered, which leaves too much solar radiation available for melting snow.

The energy balance over land and oceans: an assessment based on direct observations and CMIP5 climate models

The energy budgets over land and oceans are still afflicted with considerable uncertainties, despite their key importance for terrestrial and maritime climates. We evaluate these budgets as represented in 43 CMIP5 climate models with direct observations from both surface and space and identify substantial biases, particularly in the surface fluxes of downward solar and thermal radiation. These flux biases in the various models are then linearly related to their respective land and ocean means to infer best estimates for present day downward solar and thermal radiation over land and oceans. Over land, where most direct observations are available to constrain the surface fluxes, we obtain 184 and 306 Wm−2 for solar and thermal downward radiation, respectively. Over oceans, with weaker observational constraints, corresponding estimates are around 185 and 356 Wm−2. Considering additionally surface albedo and emissivity, we infer a surface absorbed solar and net thermal radiation of 136 and −66 Wm−2 over land, and 170 and −53 Wm−2 over oceans, respectively. The surface net radiation is thus estimated at 70 Wm−2 over land and 117 Wm−2 over oceans, which may impose additional constraints on the poorly known sensible/latent heat flux magnitudes, estimated here near 32/38 Wm−2 over land, and 16/100 Wm−2 over oceans. Estimated uncertainties are on the order of 10 and 5 Wm−2 for most surface and TOA fluxes, respectively. By combining these surface budgets with satellite-determined TOA budgets we quantify the atmospheric energy budgets as residuals (including ocean to land transports), and revisit the global mean energy balance.

Estimation of Net Radiation using satellite based data inputs

Abstract. Daily net surface radiation fluxes are estimated for Indian land mass at spatial grid intervals of 0.1 degree. Two approaches are employed to obtain daily net radiation for four sample days viz., November 19, 2013, December 16, 2013, January 8, 2014 and March 20, 2014. Both the approaches compute net shortwave and net longwave fluxes, separately and sum them up to obtain net radiation. The first approach computes net shortwave radiation using daily insolation product of Kalpana VHRR and 15 days time composited broadband albedo product of Oceansat OCM2. The net outgoing longwave radiation is computed using Stefan Boltzmann equation corrected for humidity and cloudiness. In the second approach, instantaneous clear-sky net-shortwave radiation is estimated using computed clear-sky incoming shortwave radiation and the gridded MODIS 16-day time composited albedo product. The net longwave radiation is obtained by estimating outgoing and incoming longwave radiation fluxes, independently. In this, MODIS derived surface emissivity and skin temperature parameters are used for estimating outgoing longwave radiation component. In both the approaches, surface air temperature data required for estimation of net longwave radiation fluxes are extracted from India Meteorological Department’s (IMD) Automatic Weather Station (AWS) records. Estimates by the two different approaches are evaluated by comparing daily net radiation fluxes with CERES based estimates corresponding to the sample days, through statistical measures. The estimated all sky daily net radiation using the first approach compared well with CERES SYN1deg daily average net radiation with r2 values of the order of 0.7 and RMS errors of the order of 8–16 w/m2.

Net surface radiation retrieval using Earth Observation Satellite data and machine learning algorithm

Abstract. We present a method to estimate net surface radiation (NSR) from Terra MODIS data using Artificial Neural Network (ANN) technique. For this purpose, we trained the ANN model using MODIS atmospheric profile product of air temperature, dew point temperature, solar zenith angle and land surface temperature from Terra as independent parameters and the net surface radiation from eddy flux tower measurements at Bonnie camp location of Sundarban region as the dependent variable. The NSR is estimated with a root mean square accuracy of 64 w/m2 and the square of the correlation coefficient (R2) is 0.75 respectively. This technique is extended to estimate NSR over the entire Sundarban area and has a potential for climate and agricultural water management studies.

Surface Daytime Net Radiation Estimation Using Artificial Neural Networks

Net all-wave surface radiation (Rn) is one of the most important fundamental parameters in various applications. However, conventional Rn measurements are difficult to collect because of the high cost and ongoing maintenance of recording instruments. Therefore, various empirical Rn estimation models have been developed. This study presents the results of two artificial neural network (ANN) models (general regression neural networks (GRNN) and Neuroet) to estimate Rn globally from multi-source data, including remotely sensed products, surface measurements, and meteorological reanalysis products. Rn estimates provided by the two ANNs were tested against in-situ radiation measurements obtained from 251 global sites between 1991–2010 both in global mode (all data were used to fit the models) and in conditional mode (the data were divided into four subsets and the models were fitted separately). Based on the results obtained from extensive experiments, it has been proved that the two ANNs were superior to linear-based empirical models in both global and conditional modes and that the GRNN performed better and was more stable than Neuroet. The GRNN estimates had a determination coefficient (R2) of 0.92, a root mean square error (RMSE) of 34.27 W∙m−2, and a bias of −0.61 W∙m−2 in global mode based on the validation dataset. This study concluded that ANN methods are a potentially powerful tool for global Rn estimation.

Change in surface energy balance in Alaska due to fire and spring warming, based on upscaling eddy covariance measurements

AbstractWarming in northern high latitudes has changed the energy balance between terrestrial ecosystems and the atmosphere. This study evaluated changes in regional surface energy exchange in Alaska from 2000 to 2011 when substantial declines in spring snow cover due to spring warming and large‐scale fire events were observed. Energy fluxes from a network of 20 eddy covariance sites were upscaled using a support vector regression (SVR) model, by combining satellite remote sensing data and global climate data. Based on site‐scale analysis, SVR reproduced observed net radiation, sensible heat flux, latent heat flux, and ground heat flux; 8 day root‐mean‐square errors for these variables were 15, 10, 9, and 3 W m−2, respectively. Based on upscaled fluxes, decreases in spring snow cover induced an increase in surface net radiation, a net heating effect, of 0.56 W m−2 decade−1. This heating effect was comparable to the net cooling effect due to increased fire extent during the study period (up to 0.59 W m−2 decade−1). These land cover effects were larger than the change in the energy forcing associated with CO2 balance for the Alaska region. Spring warming and postfire land cover change increased the regional latent heat flux. The regional sensible heat flux decreased with the postfire land cover change. Our results highlight the importance of positive spring snow albedo feedback to climate and a postfire negative feedback under the expected warming climate in the Arctic.

A Study of the Relations between Soil Moisture, Soil Temperatures and Surface Temperatures Using ARM Observations and Offline CLM4 Simulations

Soil temperature, soil moisture, skin temperature and 2-m air temperature are examined from both ground observations and the offline community land model (CLM4). Two-layer soil moisture and three-layer soil temperature observations from six-year (2003–2008) ground measurements at the Lamont, Oklahoma site supported by the Atmospheric Radiation Measurement (ARM) Program of the Department of Energy (DOE) show clear vertical and temporal relations between soil temperature and soil moisture with surface skin temperature and 2-m air temperature. First, daily means reveal that all of these variables have clear seasonal variations, with temperatures peaking in summer and minimizing in winter as a result of surface insolation. Nevertheless, the 2-m air temperature and upper soil temperature (−0.05 m) peak at 2 h after that of surface skin temperature because of the lag of transport of heat from the skin level to the 2-m air and to underground respectively. As a result of such lag, at the monthly annual cycle scale, 2-m air temperature has higher correlation with upper soil temperature than skin temperature does. Second, there are little diurnal and annual variations at the lowest soil layer (−0.25 m). Third, a negative correlation (~−0.40) between skin temperature and soil moisture is observed, consistent with the expectation that heat flux and evaporation are competing physical processes for redistributing surface net radiation. Soil moisture, however, minimizes in March and maximizes in winter due to the local rainfall cycle. All of these key observed relations are qualitatively reproduced in the offline CLM4 using the atmosphere forcing derived from ARM observations. Nevertheless, CLM4 is too dry at the upper layer and has less variation at the lower layer than observed. In addition, CLM4 shows stronger correlation between Tsoil and Tskin (r = 0.96) than the observations (r = 0.64), while the predicted nighttime Tskin is 0.5–2 °C higher than the observations.

Sensitivity of high-temperature weather to initial soil moisture: a case study using the WRF model

Abstract. Using a succession of 24 h Weather Research and Forecasting model (WRF) simulations, we investigate the sensitivity to initial soil moisture of a short-range high-temperature weather event that occurred in late July 2003 in East China. The initial soil moisture (SMOIS) in the Noah land surface scheme is adjusted (relative to the control run, CTL) for four groups of simulations: DRY25 (−25%), DRY50 (−50%), WET25 (+25%) and WET50 (+50%). Ten 24 h integrations are performed in each group. We focus on 2 m surface air temperature (SAT) greater than 35 °C (the threshold of "high-temperature" events in China) at 06:00 UTC (roughly 14:00 LT in the study domain) to analyse the occurrence of the high-temperature event. The 10-day mean results show that the 06:00 UTC SAT (SAT06) is sensitive to the SMOIS change; specifically, SAT06 exhibits an apparent increase with the SMOIS decrease (e.g. compared with CTL, DRY25 generally results in a 1 °C SAT06 increase over the land surface of East China), areas with 35 °C or higher SAT06 are the most affected, and the simulations are more sensitive to the SMOIS decrease than to the SMOIS increase, which suggests that hot weather can be amplified under low soil moisture conditions. Regarding the mechanism underlying the extremely high SAT06, sensible heat flux has been shown to directly heat the lower atmosphere, and latent heat flux has been found to be more sensitive to the SMOIS change, resulting in an overall increase in surface net radiation due to the increased greenhouse effect (e.g. with the SMOIS increase from DRY25 to CTL, the 10-day mean net radiation increases by 5 W m−2). Additionally, due to the unique and dynamic nature of the western Pacific subtropical high, negative feedback occurs between the regional atmospheric circulation and the air temperature in the lower atmosphere while positive feedback occurs in the mid-troposphere. Using a method based on an analogous temperature relationship, a detailed analysis of the physical processes shows that for the SAT change, the SMOIS change affects diabatic processes (e.g. surface fluxes) more strongly than the adiabatic process of subsidence in the western Pacific subtropical high in the five groups of simulations. Interestingly, although diabatic processes dominate subsidence during the daytime and night-time separately, they do not necessarily dominate during the 24 h periods (e.g. they are dominant in the WET and CTL simulations only). Further, as the SMOIS decreases, the SAT06 increases, which is largely due to the reduced cooling effect of the diabatic processes, rather than the warming effect of subsidence. Unlike previous studies on heatwave events at climate timescales, this paper presents the sensitivity of simulated short-term hot weather to initial soil moisture and emphasises the importance of appropriate soil moisture initialization when simulating hot weather.

The turbulent structure and transport in fog layers observed over the Tianjin area

This paper investigates the vertical structure and turbulence activities in fog events. Three fog cases that occurred in the winter of 2010 over Tianjin, China were selected, including two advection–radiation fog events and an advection fog event. Field observations collected at a 255-m tall meteorological tower in Tianjin were analyzed, including turbulence measurements using the eddy covariance systems installed at three levels, measurements of temperature, horizontal wind and humidity collected at 15 levels, surface radiation fluxes and horizontal visibility. The results suggest that the advection fog was more enduring and thicker than the advection–radiation fog. The fog events were characterized by low wind speed throughout the fog layer. A temperature inversion and low-level jet were observed above the advection–radiation fog layer. The surface net radiation reflected some differences among the fog events. The collapse of turbulence was a necessity for the formation fog, and moderate turbulence was favorable to the development and maintenance. The heat and water vapor fluxes in the advection–radiation fog were weaker than those in the advection fog, in which the stratification was slightly unstable. The relationships among the turbulent transport efficiencies of water vapor, temperature and momentum were examined. The results suggest the applicability of local similarity in the fog layer for the momentum transport efficiency.

Assessment of future drought in Southwest China based on CMIP5 multimodel projections

In the last decade, a series of severe and extensive droughts have swept across Southwest China, resulting in tremendous economic losses, deaths, and disruption to society. Consequently, this study is motivated by the paramount importance of assessing future changes in drought in Southwest China. Precipitation is likely to decrease over most parts of Southwest China around the beginning of the century, followed by widespread precipitation increases; the increase in potential evapotranspiration (PET), due to the joint effects of increased temperature and surface net radiation and decreased relative humidity, will overwhelm the whole region throughout the entire 21st century. In comparative terms, the enhancement of PET will outweigh that of precipitation, particularly under Representative Concentration Pathway (RCP) 8.5, resulting in intensified drought. Generally, the drying tendency will be in the southeast portion, whereas the mountainous region in the northwest will become increasingly wetter owing to abundant precipitation increases. Droughts classified as moderate/severe according to historical standards will become the norm in the 2080s under RCP4.5/RCP8.5. Future drought changes will manifest different characteristics depending on the time scale: the magnitude of change at a time scale of 48 months is nearly twice as great as that at 3 months. Furthermore, we will see that not only will incidences of severe and extreme drought increase dramatically in the future, but extremely wet events will also become more probable.

Parameterizations of surface radiation in the semiarid grasslands of Inner Mongolia under clear-sky conditions using MODIS data

A set of improved and efficient radiation parameterization schemes for surface radiation balance components under clearsky conditions was developed by using general surface measurements and MODIS data. The set of schemes was then adapted for regions similar to the present study sites under different grazing intensities and varying degrees of drought in the semiarid grasslands of Inner Mongolia. Specifically, we mainly improved two schemes for estimating downward shortwave and longwave radiation at the surface, which could be applied to regions with certain degrees of drought. The validation datasets were from ground-based observations at various grazing sites during the growing season (May to September) of different drought years, 2005 and 2006. Through comparisons of parameterized versus measured radiation values, the increased or modified factors in the original schemes demonstrated improved estimation accuracy, and the rationalities of input parameters and variables were analyzed. The regional instantaneous net radiation estimations had root-mean-square errors of less than 30 Wm−2 compared with ground measurements at the sites during the study period. The statistical results showed the improved schemes are suitable for estimating surface net radiation in regional semiarid areas during the growing season. Analyses of the sensitivity of the schemes to corresponding variables were conducted to ascertain the major error sources of the schemes and potential variables for improving the performance of the schemes in agreement with observations.

ANALYSIS OF ENVIRONMENTAL PARAMETERS IN GILBUÉS – PI USING SATELLITE IMAGES

This paper aims to analyze the desertification process in the Gilbués region, southwestern portion of Piauí state, through remote sensing techniques with a perspective of verify whether there is a relationship of environmental parameters (surface albedo, NDVI, surface temperature, radiation and energy balances, as well as non-evaporative fraction) with the desertification process presented in this study area. We used images from the satellite Landsat 5-TM of August 19, 1994 and August 15, 2010 and applied the SEBAL and S-SEBI algorithms for obtaining environmental parameters analyzed. It was diagnosed cover removal of native vegetation, which may indicate areas undergoing to desertification and/or environmental degradation. Similarly, there was a reduction of surface net radiation, increased soil heat fluxes, reduction of energy used for evaporation and increases in the energy used for heating the soil and air, causing the temperature increase, and a systematic increase of the soil moisture deficit in the studied region.

Daily Evaporative Fraction Parameterization Scheme Driven by Day–Night Differences in Surface Parameters: Improvement and Validation

In a previous study, a daily evaporative fraction (EF) parameterization scheme was derived based on day–night differences in surface temperature, air temperature, and net radiation. Considering the advantage that incoming solar radiation can be readily retrieved from remotely sensed data in comparison with surface net radiation, this study simplified the daily EF parameterization scheme using incoming solar radiation as an input. Daily EF estimates from the simplified scheme were nearly equivalent to the results from the original scheme. In situ measurements from six Ameriflux sites with different land covers were used to validate the new simplified EF parameterization scheme. Results showed that daily EF estimates for clear skies were consistent with the in situ EF corrected by the residual energy method, showing a coefficient of determination of 0.586 and a root mean square error of 0.152. Similar results were also obtained for partly clear sky conditions. The non-closure of the measured energy and heat fluxes and the uncertainty in determining fractional vegetation cover were likely to cause discrepancies in estimated daily EF and measured counterparts. The daily EF estimates of different land covers indicate that the constant coefficients in the simplified EF parameterization scheme are not strongly site-specific.

Spatial distribution of surface energy fluxes over the Loess Plateau in China and its relationship with climate and the environment

China’s Loess Plateau is located at the edge of the Asian summer monsoon in a transition zone of climate and ecology. In the Loess Plateau, climate and environments change along with space, which has an obvious impact on the spatial distribution of surface energy fluxes. Because of scarce land-surface observation sites and short observation time in this area, previous studies have failed to fully understand the land-surface energy balance characteristics over the entire the Loess Plateau and their effect mechanisms. In this paper, we first test the simulation ability of the Community Land Model (CLM) model by comparing its simulated data with observed data. Based on the simulation data for the Loess Plateau over the past thirty years, we then analyze the spatial distribution of surface energy fluxes and compare the pattern differences between the area averages for the driest year and wettest year. Furthermore, we analyze the relationship between the spatial distribution of the components of the surface energy balance with longitude, latitude, altitude, precipitation and temperature. The main results are as follows: the spatial distribution of surface energy fluxes are significantly different, with the surface net radiation and sensible heat flux increasing from south to north and latent heat flux and soil heat flux decreasing from southeast to northwest. The sensible heat flux at the driest point is nearly twice as high as that at the wettest point, whereas the latent heat flux and soil heat flux at the driest point are half as much as that at the wettest point. The impact of variations of annual precipitation on the components of the surface energy balance is also obvious, and the maximum magnitude of the changes to the sensible heat flux and latent heat flux is nearly 30%. To a certain extent, geographical factors (including longitude, latitude, and altitude) and climate factors (including temperature and precipitation) affect the surface energy fluxes. However, the surface net radiation is more closely related to latitude and altitude, sensible heat flux is more closely related to the monsoon rainfall and latitude, and latent heat flux and soil heat flux are more closely related to the monsoon rainfall.

Global warming and 21st century drying

Global warming is expected to increase the frequency and intensity of droughts in the twenty-first century, but the relative contributions from changes in moisture supply (precipitation) versus evaporative demand (potential evapotranspiration; PET) have not been comprehensively assessed. Using output from a suite of general circulation model (GCM) simulations from phase 5 of the Coupled Model Intercomparison Project, projected twenty-first century drying and wetting trends are investigated using two offline indices of surface moisture balance: the Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Evapotranspiration Index (SPEI). PDSI and SPEI projections using precipitation and Penman-Monteith based PET changes from the GCMs generally agree, showing robust cross-model drying in western North America, Central America, the Mediterranean, southern Africa, and the Amazon and robust wetting occurring in the Northern Hemisphere high latitudes and east Africa (PDSI only). The SPEI is more sensitive to PET changes than the PDSI, especially in arid regions such as the Sahara and Middle East. Regional drying and wetting patterns largely mirror the spatially heterogeneous response of precipitation in the models, although drying in the PDSI and SPEI calculations extends beyond the regions of reduced precipitation. This expansion of drying areas is attributed to globally widespread increases in PET, caused by increases in surface net radiation and the vapor pressure deficit. Increased PET not only intensifies drying in areas where precipitation is already reduced, it also drives areas into drought that would otherwise experience little drying or even wetting from precipitation trends alone. This PET amplification effect is largest in the Northern Hemisphere mid-latitudes, and is especially pronounced in western North America, Europe, and southeast China. Compared to PDSI projections using precipitation changes only, the projections incorporating both precipitation and PET changes increase the percentage of global land area projected to experience at least moderate drying (PDSI standard deviation of ≤−1) by the end of the twenty-first century from 12 to 30 %. PET induced moderate drying is even more severe in the SPEI projections (SPEI standard deviation of ≤−1; 11 to 44 %), although this is likely less meaningful because much of the PET induced drying in the SPEI occurs in the aforementioned arid regions. Integrated accounting of both the supply and demand sides of the surface moisture balance is therefore critical for characterizing the full range of projected drought risks tied to increasing greenhouse gases and associated warming of the climate system.

Climatology of aerosol and cloud optical properties at the Atmospheric Radiation Measurements Climate Research Facility Barrow and Atqasuk sites

The long-term measurements at the Barrow and Atqasuk sites have been processed to develop the climatology of aerosol and cloud properties at interannual, seasonal, and diurnal temporal scales. At the Barrow site, the surface temperature exhibits an increasing trend in both thawed and frozen seasons over the period studied here, about one decade. Corresponding to the warming, the snow melting day arrives earlier, and the non-snow-cover duration increases. Aerosol optical depth increased during 2001–2003 and 2005–2009 and decreased during 2003–2005. The liquid water path (LWP), cloud optical depth (COD), and cloud fraction exhibit apparently decreasing trends from 2002 to 2007 and increased significantly after 2008. In the frozen season, the arctic haze and ice clouds are dominant, while in the thawed season, the oceanic biogenic aerosols and liquid water clouds or mixed-phase clouds are dominant. The cloud droplet effective radius during the thawed season is larger than that during the frozen season. The diurnal variations of aerosol and cloud-related atmospheric properties are not obvious at these two sites. During the sunshine periods, the aerosol has a cooling effect on the surface through direct aerosol radiative forcing. In the frozen season, clouds have a positive impact on the net surface radiation, and the water vapor path, LWP, and COD have good positive correlations with the surface temperature, suggesting that the cloud radiation feedback is positive. In the thawed season, clouds have a negative impact on the net surface radiation.

A Lagrangian Analysis of Deep Convective Systems and Their Local Environmental Effects

Abstract Life cycles of deep convective raining systems are documented through use of a Lagrangian tracking algorithm applied to high-resolution Climate Prediction Center morphing technique (CMORPH) rainfall data, permitting collocation with related environmental ancillary fields and the International Satellite Cloud Climatology Project (ISCCP) cloud states (Rossow et al. 2005). System life cycles are described in terms of propagation speed, duration, and dominant cloud structures. Tracked systems are usually associated with the ISCCP weather state 1 (WS1) deep convection cloud state and an independent, microwave-based deep convective precipitation regime developed here. The distribution and characteristics of tracked systems are found to be similar between ocean basins in terms of system speed and duration, with westward-propagating systems predominant in every basin. The effects that these systems have on environmental parameters are assessed, stratified according to their average propagation speed and by ocean basin. Regardless of system speed the net effect on the environment is similar, with the largest difference being how quickly changes occur, with net surface radiation decreasing about 150 W m−2 and total precipitable water perturbed by 5–7 kg m−2; sea surface temperature (SST) drops 0.2°–0.3°C over 24 h, with system speed affecting how long SSTs remain depressed. The observed drop in SST is partly caused by the presence of widespread, optically thick clouds that greatly decrease the net surface radiative flux. Quick changes in SSTs caused by tracked systems are captured by buoys but not represented well in gridded SST products, as these regions remain largely under the precipitating cloud cover associated with these systems.

Summer Arctic sea ice albedo in CMIP5 models

Abstract. Spatial and temporal variations of summer sea ice albedo over the Arctic are analyzed using an ensemble of historical CMIP5 model simulations. The results are compared to the CLARA-SAL product that is based on long-term satellite observations. The summer sea ice albedo varies substantially among CMIP5 models, and many models show large biases compared to the CLARA-SAL product. Single summer months show an extreme spread of ice albedo among models; July values vary between 0.3 and 0.7 for individual models. The CMIP5 ensemble mean, however, agrees relatively well in the central Arctic but shows too high ice albedo near the ice edges and coasts. In most models, the ice albedo is spatially too uniformly distributed. The summer-to-summer variations seem to be underestimated in many global models, and almost no model is able to reproduce the temporal evolution of ice albedo throughout the summer fully. While the satellite observations indicate the lowest ice albedos during August, the models show minimum values in July and substantially higher values in August. Instead, the June values are often lower in the models than in the satellite observations. This is probably due to too high surface temperatures in June, leading to an early start of the melt season and too cold temperatures in August causing an earlier refreezing in the models. The summer sea ice albedo in the CMIP5 models is strongly governed by surface temperature and snow conditions, particularly during the period of melt onset in early summer and refreezing in late summer. The summer surface net solar radiation of the ice-covered Arctic areas is highly related to the ice albedo in the CMIP5 models. However, the impact of the ice albedo on the sea ice conditions in the CMIP5 models is not clearly visible. This indicates the importance of other Arctic and large-scale processes for the sea ice conditions.