Atmospheric Water Vapor Content Research Articles

A software tool for retrieving land surface temperature from ASTER imagery

Cevresel verinin toplanmasi, analizi ve modellemesinde uzaktan algilama cok onemli ve iyi bilinen bir arac olmasina ragmen, termal kizilotesi (TIR) uzaktan algilamasina gereken onem verilmemistir. Kuresel cevre degisimi, iklim modelleri ve insan-cevre etkilesimleri gibi bircok cevresel calismalar icin yer yuzey sicakligi (LST) onemli bir parametredir. Bu calismada, Visual Basic NET programlama dili kullanilarak ASTER uydu goruntusunden yer yuzey sicakligini hesaplayan bir yazilim araci gelistirilmistir. Bu arac bes modulden olusmaktadir: 1- Dijital Sayilari (DN) Radyansa donusturme, 2- Yuzey yansima degerinin hesaplanmasi, 3- NDVI’in hesaplanmasi, 4- Yayinirligin hesaplanmasi ve 5- Sicakligin hesaplanmasi. Bu yazilim aracinda Jimenez Munoz ve Sobrino’nun ASTER uydu goruntusunden yer yuzey sicakliginin hesaplanmasi icin gelistirdigi Tek Kanal (Single Channel) Algoritmasi kullanilmistir. Bu programin termal cevre uzerine calisan bilim insanlari veya konuyla ilgilenen kisiler icin faydali olabilecegi umit edilmektedir.

A Software Tool for Retrieving Land Surface Temperature from

Remote sensing is a powerful and well-known tool in the collection, analysis, and modeling of environmental data, however, not much attention has been given to the use of thermal infrared (TIR) remote sensing. Land surface temperature (LST) is a key parameter for many environmental studies such as global environmental change, climate models, and human-environment interactions. In this study, a software tool which retrieves LST from Advanced Spaceborne Thermal Emission and reflection Radiometer (ASTER) imagery has been developed in Visual Basic .NET. The tool consists of five main modules: 1- Converting DN to Radiances, 2- Calculating surface reflectances, 3- Calculating NDVI, 4- Calculating emissivity and 5- Calculating surface temperature. In this tool, Jimenez Munoz and Sobrino’s Single Channel (SCJM&S) Algorithm for ASTER was employed. With this tool, user can be able to calculate LST using (1) atmospheric parameters such as atmospheric transmissivity, upwelling and downwelling atmospheric radiances, (2) atmospheric water-vapor content. Hopefully, this program will be a useful tool for scientists/persons who are interested in studying thermal environments.

Derivation of split-window algorithm to retrieve land surface temperature from MSG-1 thermal infrared data

One of the most important parameters in the exchange of energy between the ground and the atmosphere is the land surface temperature (LST). In this work, a split-window algorithm for deriving LST from the first Meteosat Second Generation satellite (MSG-1) data using the two thermal infrared channels IR10.8 and IR12.0 is proposed and validated with in-situ measured temperatures. This algorithm is obtained starting from the radiance transfer equation and requires the knowledge of total atmospheric water vapor content (TAWV) and the surface emissivity (ε10.8 and ε12). First, we have simplified the Planck function to retrieve the radiance at MSG-1 from the temperature. Then, the Roberts model was used to create a relationship between atmospheric transmittance and TAWV. Next, sensitivity analysis of the algorithm indicates that the possible error of viewing angle has relatively insignificant impact on the probable LST estimation error, which is sensible to the possible error of ground emissivity and TAWV. Finally, two methods have been used to validate the proposed algorithm. On the one hand, the results show a root mean square error (RMSE) equals 0.79 K and an average accuracy equals 0.45 K for the comparison with another algorithm. On the other hand, the results show a RMSE equals 2.75 K and an average accuracy equals 1.96 K for the comparison with in-situ measurements. We conclude that the proposed algorithm is able to provide an accurate LST.

Decadal variability of extreme precipitation days over Northwest China from 1963 to 2012

Daily precipitation data from 153 meteorological stations over Northwest China during summer from 1963 to 2012 were selected to analyze the spatiotemporal distribution of extreme summer precipitation frequency. The results show that the extreme precipitation frequency was regional dependent. Southern Gansu, northern Qinghai, and southern Shaanxi provinces exhibited a high extreme precipitation frequency and were prone to abrupt changes in the frequency. Northwest China was further divided into three sub-regions (northern, central, and southern) based on cluster analysis of the 50-yr extreme precipitation frequency series for each meteorological station. The extreme precipitation frequency changes were manifested in the northern region during the late 1970s and in the central region from the end of the 1980s to the 1990s. The southern region fluctuated on a timescale of quasi-10 yr. This study also explored the mechanism of changes in extreme precipitation frequency. The results demonstrate that stratification stability, atmospheric water vapor content, and upward motion all affected the changes in extreme precipitation frequency.

Land Surface Temperature Retrieval Methods From Landsat-8 Thermal Infrared Sensor Data

The importance of land surface temperature (LST) retrieved from high to medium spatial resolution remote sensing data for many environmental studies, particularly the applications related to water resources management over agricultural sites, was a key factor for the final decision of including a thermal infrared (TIR) instrument on board the Landsat Data Continuity Mission or Landsat-8. This new TIR sensor (TIRS) includes two TIR bands in the atmospheric window between 10 and 12 μm, thus allowing the application of split-window (SW) algorithms in addition to single-channel (SC) algorithms or direct inversions of the radiative transfer equation used in previous sensors on board the Landsat platforms, with only one TIR band. In this letter, we propose SC and SW algorithms to be applied to Landsat-8 TIRS data for LST retrieval. Algorithms were tested with simulated data obtained from forward simulations using atmospheric profile databases and emissivity spectra extracted from spectral libraries. Results show mean errors typically below 1.5 K for both SC and SW algorithms, with slightly better results for the SW algorithm than for the SC algorithm with increasing atmospheric water vapor contents.

Trend and Variability of the Atmospheric Water Vapor: A Mean Sea Level Issue

Abstract The wet tropospheric path delay is presently the main source of error in the estimation of the mean sea level by satellite altimetry. This correction on altimetric measurements, provided by a dedicated radiometer aboard the satellite, directly depends on the atmospheric water vapor content. Nowadays, water vapor products from microwave radiometers are rather consistent but important discrepancies remain. Understanding these differences can help improve the retrieval of water vapor and reduce at the same time the error on the mean sea level. Three radiometers are compared: the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), Jason-1 microwave radiometer (JMR), and Envisat microwave radiometer (MWR). Water vapor products are analyzed both in terms of spatial and temporal distribution over the period 2004–10, using AMSR-E as a reference. The Interim ECMWF Re-Analysis (ERA-Interim) data are also included in the study as an additional point of comparison. Overall, the study confirms the general good agreement between the radiometers: similar patterns are observed for the spatial distribution of water vapor and the correlation of the times series is better than 0.90. However, regional discrepancies are observed and a quantitative agreement on the trend is not obtained. Regional discrepancies are driven by the annual cycle. The JMR product shows discrepancies are highly dependent on water vapor, which might be related to calibration issues. Furthermore, triple collocation analysis suggests a possible drift of JMR. MWR discrepancies are located in coastal regions and follow a seasonal dynamic with stronger differences in summer. It may result from processing of the brightness temperatures.

Improvements in land surface temperature retrieval based on atmospheric water vapour content and atmospheric temperature

Three methods are currently used to retrieve land surface temperatures (LSTs) from thermal infrared data supplied by the Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) sensors: the radiative transfer equation, mono-window, and generalized single-channel algorithms. Most retrieval results obtained using these three methods have an average error of more than 1 K. But if the regional mean atmospheric water vapour content and temperature are supplied by in situ radiosounding observations, the mono-window algorithm is able to provide better results, with a mean error of 0.5 K. However, there are no in situ radiosounding data for most regions. This article provides an improved method to retrieve LST from Landsat TM and ETM+ data using atmospheric water vapour content and atmospheric temperature, which can be obtained from remote-sensing data. The atmospheric water vapour content at the pixel scale was first calculated from Moderate Resolution Imaging Spectroradiometer (MODIS) data. The emissivities of various land covers and uses were then defined by Landsat TM or ETM+ data. In addition, the temperature–vegetation index method was applied to map area-wide instantaneous near-surface air temperatures. The parameters of mean atmospheric water vapour content and temperature and land surface emissivity were finally inputted to the mono-window algorithm to improve the LST retrieval precision. Our results indicate that this improved mono-window algorithm gave a significantly better retrieval of the estimated LST than that using the standard mono-window algorithm, not only in dry and elevated mountain regions but also in humid regions, as shown by the bias, standard deviation (σ), and root mean square deviation (RMSD). In Madoi County, the improved mono-window algorithm validated against the LST values measured in situ produced a bias and RMSD of –0.63 K and 0.91 K, respectively, compared with the mono-window algorithm’s bias and RMSD of –1.08 K and 1.27 K. Validated against the radiance-based method, the improved algorithm shows bias and RMSD values of –1.08 K and 1.27 K, respectively, compared with the initial algorithm’s bias and RMSD –1.65 K and 1.75 K. Additionally, the improved mono-window algorithm also appeared to be more accurate than the mono-window algorithm, with lower error values when validated against in situ measurement and the radiance-based method in the validation area in Zhangye City, Gansu Province, China. Remarkable LST accuracy improvements are shown by the improved mono-window algorithm, with better agreement not only with the in situ measurements but also with the simulated LSTs in the two validation areas, indicating the soundness and suitability of this method.

Investigation of negative cloud radiative forcing over the Indian subcontinent and adjacent oceans during the summer monsoon season

Abstract. Radiative properties of clouds over the Indian subcontinent and nearby oceanic regions (0–25° N, 60–100° E) during the Asian summer monsoon season (June–September) are investigated using the Clouds and Earth's Radiant Energy System (CERES) top-of-the-atmosphere (TOA) flux data. Using multiyear satellite data, the net cloud radiative forcing (NETCRF) at the TOA over the Indian region during the Asian monsoon season is examined. The seasonal mean NETCRF is found to be negative (with its magnitude exceeding ~30 Wm−2) over (1) the northern Bay of Bengal (close to the Myanmar–Thailand coast), (2) the Western Ghats and (3) the coastal regions of Myanmar. Such strong negative NETCRF values observed over the Indian monsoon region contradict the assumption that near cancellation between LWCRF and SWCRF is a generic property of all tropical convective regions. The seasonal mean cloud amount (high and upper middle) and corresponding cloud optical depth observed over the three regions show relatively large values compared to the rest of the Indian monsoon region. Using satellite-derived cloud data, a statistical cloud vertical model delineating the cloud cover and single-scattering albedo was developed for the three negative NETCRF regions. The shortwave (SW), longwave (LW) and net cloud radiative forcing over the three negative NETCRF regions are calculated using the rapid radiative transfer model (RRTM) with the cloud vertical model as input. The NETCRF estimated from CERES observations show good comparison with that computed using RRTM (within the uncertainty limit of CERES observations). Sensitivity tests are conducted using RRTM to identify the parameters that control the negative NETCRF observed over these regions during the summer monsoon season. Increase in atmospheric water vapor content during the summer monsoon season is found to influence the negative NETCRF values observed over the region.

Simultaneous remote monitoring of atmospheric methane and water vapor using an integrated path DIAL instrument based on a widely tunable optical parametric source

We report on the remote sensing capability of an integrated path differential absorption lidar (IPDIAL) instrument, for multi-species gas detection and monitoring in the 3.3-3.7 µm range. This instrument is based on an optical parametric source composed of a master oscillator-power amplifier scheme--whose core building block is a nested cavity optical parametric oscillator--emitting up to 10 µJ at 3.3 µm. Optical pumping is realized with an innovative single-frequency, 2-kHz repetition rate, nanosecond microchip laser, amplified up to 200 µJ per pulse in a single-crystal fiber amplifier. Simultaneous monitoring of mean atmospheric water vapor and methane concentrations was performed over several days by use of a topographic target, and water vapor concentration measurements show good agreement compared with an in situ hygrometer measurement. Performances of the IPDIAL instrument are assessed in terms of concentration measurement uncertainties and maximum remote achievable range.

Retrieval of land surface temperature from the Kalpana-1 VHRR data using a single-channel algorithm and its validation over western India

Indian geostationary satellite Kalpana-1 (K1) offers a potential to capture the diurnal cycle of land surface temperature (LST) through thermal infrared channel (10.5–12.5μm) observations of the Very High Resolution Radiometer (VHRR) sensor. A study was carried out to retrieve LST by adapting a generalized single-channel (SC) algorithm (Jiménez-Muñoz and Sobrino, 2003) for the VHRR sensor over India. The basis of SC algorithm depends on the concept of Atmospheric Functions (AFs) that are dependent on transmissivity, upwelling and downwelling radiances of the atmosphere. In the present study AFs were computed for the VHRR sensor through the MODTRAN simulations based upon varying atmospheric and surface inputs. The AFs were fitted with the atmospheric columnar water vapour content and a set of coefficients was derived for LST retrieval. The K1-LST derived with the SC algorithm was validated with (a) in situ measurements at two sites located in western parts of India and (b) the MODIS LST products. Comparison of K1-LST with the in situ measurements demonstrated that SC algorithm was successful in capturing the prominent diurnal variations of 283–332K in the LST at desert and agriculture experimental sites with a rmse of 1.6K and 2.7K, respectively. Inter comparison of K1-LST and MODIS LST showed a reasonable agreement between these two retrievals up to LST of 300K, however a cold bias up to 7.9K was observed in MODIS LST for higher LST values (310–330K) over the hot desert region.

The Effect of Atmospheric Water Vapor Content on the Performance of Future Wide-Swath Ocean Altimetry Measurement

Abstract Measurement of sea surface height (SSH) over a finite swath along satellite tracks has been planned for future space missions. The effect of water vapor in the troposphere on the delay of radar signal must be corrected for in the SSH measurement. The efficacy of a nadir-looking radiometer that has been the approach for conventional altimetry is examined in the study. The focus is placed on the cross-track variability of water vapor that is not measured by the nadir-looking radiometer. Simulations of the 2D field of water vapor were performed by spectral analysis of existing radiometer data. The residual error from the application of the correction made by a nadir-looking radiometer was computed over the global ocean and compared to the SSH signal estimated from satellite altimeter data. Global maps of the signal-to-error ratio (the square root of spectral variance at wavelengths shorter than 500 km) were created, showing values of 20–50 in the regions of high SSH variability of the boundary currents and the Antarctic Circumpolar Current, and 3–5 in the regions of low SSH variability in the tropics. Improvement in the correction by using a two-beam radiometer looking off nadir for measuring the slope of the cross-track variability was also explored, leading to a reduction of the error to below 1 cm at wavelengths of 10–500 km.

Evaluations of atmospheric downward longwave radiation from 44 coupled general circulation models of CMIP5

AbstractAtmospheric downward longwave radiation at the surface (Ld) quantifies the atmospheric greenhouse effect. This study evaluated Ld simulations from 44 general circulation models (GCMs) in the Coupled Model Intercomparison Project Phase 5 (CMIP5) with a comprehensive data set of Ld observations at 156 global‐distributed sites from 1992 to 2005. Compared with the Baseline Surface Radiation Network data that are of the highest quality among the available Ld data sets, CMIP5 GCM Ld has a negligible bias, much better than CMIP3 GCMs, likely because of the improvement of low cloud simulations in CMIP5 models. However, the selection of validation data has an important impact on the evaluation results. The global mean Ld inferred from different bias‐removing methods are nearly the same, approximately 341 W m−2 globally averaged from 1992 to 2005. CMIP5 GCMs showed that global Ld increased at a rate of 1.54 W m−2 per decade (p < 0.01) from 1979 to 2005, which is consistent with available reanalyses. This good agreement in long‐term trends of Ld is likely because both reanalyses and CMIP5 models reproduced the observed warming and the associated increase of water vapor content in the lower atmosphere. However, CMIP5 GCMs are still poor in producing monthly anomalies of Ld.

El contenido del vapor de agua de la atmósfera como indicador del calentamiento global en una zona del Caribe de Colombia

This study shows the importance of the atmospheric water vapour content as an indicator of global warming at local scale in part of the middle and lower basin of the Sinú river (Colombia). The climatic regime of the selected zone is represented by the meteorological stations of Turipaná, El Salado, Lorica and La Doctrina. Data series of air temperature T and relative humidity HR of the mentioned stations, between 1968 and 2011, were selected and tested for quality by rigorous statistical and climatic analysis. Furthermore, atmospheric water vapor density data dv were estimated, using mean annual values of T and HR previously calculated for each of the selected 44 years. The interannual trend analysis of the annual means of T and dv, for the four selected stations and the integrated studied zone, demonstrated that even though their climatic variability strongly depends of El Niño and La Niña phenomena, the upward trend of both variables remains since 1968. Particularly in the integrated studied zone, an increment in T of 0.75ºC (2.7%) or 0.17ºC dec-1 was detected, which coincides with the reported global value by WMO, while dv increased in 1.02 g m-3 (5.9%) or 0.23 g m-3 dec-1. It was determinated likewise that 1991-2000 was the warmest decade of the period of time 1968-2011 and not the next one (2001-2010), as it is exposed in diverse studies worldwide. On the contrary of the results obtained from global and regional researchs, in this study the decadal means do not explain completely the great tropical climatic variability at local level and the effect of the global warming. The statistical analysis of T and dv trends for the periods of time 1968-1974 and 1975-2011, allowed to identify evidences of the possible beginning of the global warming in the studied zone, probably due to the most intensive La Niña event of the history, registered between 1973 and 1974 (ONI of -2.0). The results obtained in this study about the global warming in the four selected meteorological stations and the integrated studied zone, probably caused by extense and intense human land intervention, confirm that the atmospheric water vapor content dv is the most adequate thermodynamic variable for the description of the behavior of tropical climatic regimes at local level.

One- and Two-Dimensional Wind Speed Models for Ka-Band Altimetry

abstract SARAL—the Satellite with ARgos and ALtiKa—is the first satellite radar altimetry mission to fly a Ka-band instrument (AltiKa). Ocean backscatter measurements in the Ka band suffer larger signal attenuation due to water vapor and atmospheric liquid water than those from Ku-band altimeters. An attenuation algorithm is provided, based on radar propagation theory, which is a function of atmospheric pressure, temperature, water vapor, and liquid water content. Because of the nature of the air–sea interactions between wind and surface gravity waves, the shorter wavelength Ka-band backscatter exhibits a different relationship with wind speed than at Ku band, particularly at moderate to high wind speeds. This paper presents a new one-dimensional wind speed model, as a function of backscatter only, and a two-dimensional model, as a function of backscatter and significant wave height, tuned to AltiKa’s backscatter measurements. The performance of these new Ka-band altimeter wind speed models is assessed through validation with independent ocean buoy wind speeds. The results indicate wind measurement accuracy comparable to that observed at Ku band with only slightly elevated noise in the wind estimates.

Improving InSAR geodesy using Global Atmospheric Models

Spatial and temporal variations of pressure, temperature, and water vapor content in the atmosphere introduce significant confounding delays in interferometric synthetic aperture radar (InSAR) observations of ground deformation and bias estimates of regional strain rates. Producing robust estimates of tropospheric delays remains one of the key challenges in increasing the accuracy of ground deformation measurements using InSAR. Recent studies revealed the efficiency of global atmospheric reanalysis to mitigate the impact of tropospheric delays, motivating further exploration of their potential. Here we explore the effectiveness of these models in several geographic and tectonic settings on both single interferograms and time series analysis products. Both hydrostatic and wet contributions to the phase delay are important to account for. We validate these path delay corrections by comparing with estimates of vertically integrated atmospheric water vapor content derived from the passive multispectral imager Medium‐Resolution Imaging Spectrometer, onboard the Envisat satellite. Generally, the performance of the prediction depends on the vigor of atmospheric turbulence. We discuss (1) how separating atmospheric and orbital contributions allows one to better measure long‐wavelength deformation and (2) how atmospheric delays affect measurements of surface deformation following earthquakes, and (3) how such a method allows us to reduce biases in multiyear strain rate estimates by reducing the influence of unevenly sampled seasonal oscillations of the tropospheric delay.

The accelerating rate of global change

The Earth’s surface temperature represents a balance between incoming solar energy, partial reflection (planetary albedo) and reradiation from the planet modified by the greenhouse effect of atmospheric gases having three or more atoms per molecule. Over the past 6,000 years the Earth’s surface temperatures have remained remarkably stable. However during the last century it became increasingly apparent that human activities, especially the burning of fossil fuels were affecting the planet and causing global warming. The perturbation of climate brought on by humans has been recognized by the proposal of the terms Anthropocene or Anthropogene for the period since the beginning of the industrial revolution or even earlier, when CO2 levels began to rise rather than decline after the beginning of the current interglacial. There are four major greenhouse gases in Earth’s lower atmospheric layer, the troposphere: water vapor, carbon dioxide, methane, and nitrous oxide. The atmospheric content of water vapor is controlled by temperature, so its distribution is restricted to the tropics and subtropics and lower part of the troposphere. Methane and nitrous oxide both have short atmospheric lifetimes of a decade or two. However, CO2 introduced into the atmosphere has a lifetime of tens of thousands of years or more. Burning of fossil fuels has increased the level of atmospheric CO2 by about 45 % over the level prior to the industrial revolution. The increasing greenhouse effect is augmented by a series of feedbacks, most positive (+), but a few negative (−), which have appeared in the climate system: Changes in (1) the thermohaline circulation system (+ or −); (2) the Atlantic to Pacific vapor transport (+); (3) Arctic river runoff (+); (4) melting of Arctic sea ice (+); (5) the ice-albedo feedback (+); (6) addition of methane from melting permafrost (+); (7) changes in the rate of ocean mixing (+); (8) changes in vegetation (+ or −); (9) wildfires (+); (10) soot accumulation on snow and ice (+); (11) accelerated melting of the Greenland Ice Sheet (+); (12) decay of the Antarctic Ice Sheet (+); (13) expansion of Southern Ocean sea ice (−), and perhaps an additional potential feedback, (14) slowing the rate of organic matter sinking into the deep ocean (+). ‘Global dimming’ refers to a decrease in insolation reaching the surface of the Earth as a result of introduction of aerosols into the atmosphere, resulting in pauses in the general greenhouse warming. The increasingly chaotic weather is an indication that the Earth’s climate system is becoming unstable in response to the ongoing perturbation.

Deriving Solar Radiation in a Mountain Area from MODIS Information

Solar radiation has a direct influence on the air and ground temperature, indirect influence on the value of atmospheric humidity, movement of air masses and precipitations, and it is easy to understand how its evaluation is essential not only in the technological area such as for sizing solar heating and photovoltaic plants, but also in fields such as agriculture or meteorology. Nowadays, the assessment of the solar energy resources over large areas and the elaboration of solar radiation maps are conducted using satellite derived information. Among the existing methodologies, those based on parametric models to firstly estimate the clear-sky solar radiation are usual. The success of that option depends both on the accuracy of the solar radiation algorithm and the satellite derived information and on the relationship between each other.In this work, daily global solar irradiation under clear skies is estimated by means of a model which includes the horizon effects. This characteristic is important in those cases where a complex topography is present, such as mountains. The topographic information is obtained from a digital elevation model. The other inputs to the model are the atmospheric precipitable water vapour content, the Angström's turbidity coefficient and the ground albedo. Experimental values of the atmospheric precipitable water vapour content are obtained from the MODIS sensor. The two latter parameters are averaged values calculated on previous studies.Estimates by the model are compared with ground measurements obtained in fourteen radiometric stations located in a mountain zone (Sierra Nevada, Granada, Spain) recording global solar radiation, atmospheric temperature and relative humidity. Since ground experimental values of precipitable water vapour content are available, a comparison between these values and those derived from the MODIS sensor is also presented.

Estimating Solar Radiation from MODIS Data

The assessment of the solar energy resources over large areas and the elaboration of solar radiation maps are nowdays conducted using satellite derived information. Among the existing methodologies, those based on parametric models to firstly estimate the clear-sky solar radiation are usual. The success of that option depends both on the accuracy of the solar radiation algorithm and the satellite derived information and on the relationship between each other.In this work, a new accurate parametric model to estimate global solar radiation under cloudless conditions is presented. Atmospheric precipitable water vapour content is the only experimental input to the model. These values are derived from the MODIS sensor, the major facility instrument on the EOS polar orbiting satellite platforms. The evaluation of the model performance has been carried on using ground measurements obtained in twelve radiometric stations located in the north face of the Sierra Nevada Natural Park in the surroundings of Huéneja (Granada), a town located in the South East of Spain in a mountain zone (Sierra Nevada, Granada, Spain). The radiometric stations record global solar radiation, atmospheric temperature and relative humidity. Since the precipitable water vapour content is also available from the ground stations, a preliminary analysis comparing both experimental data sets is also presented.

Evaluating Solar Radiation Attenuation Models to Assess the Effects of Climate and Geographical Location on the Heliostat Field Efficiency in Brazil

Most of the solar power plants using a central receiver which are currently in operation are installed in the Sun Belt region, specifically above the Tropic of Cancer. These plants are located in regions characterized by a dry summers and a yearly sum of Direct Normal Irradiation (DNI) of over 2300 kWh/m2. These regions include the Mojave Desert (semi-arid climate) and Andalucía in southern Spain (Mediterranean and semi-arid climate). Potential locations for installing such plants in Brazil, identified in previous studies, are the São Francisco river basin and the Sobradinho area in the Northeast Region of the country. These locations are characterized by high humidity levels and yearly DNI values ranging from 1800 to 2300 kWh/m2, which is in clear contrast with the dry and desert climates where the solar tower projects currently in operation are located. Besides the combined effects of climate and the inter-tropicalization of the site, based on the solar angles and atmospheric attenuation, the potential locations in Brazil provide a small variation between the monthly averages DNI values. In this paper, the effects of these particularities on the performance of a heliostat field are assessed. For instance, the effects of the atmospheric water vapor and aerosol concentration on the optical performance of the heliostat field are analyzed. The results suggest that, for the same DNI level, the heliostat field in Brazil should be 4% larger due to the effect of the water vapor concentration in the atmosphere. This is an important finding, which shows that the current models for calculating the attenuation between the heliostat and the receiver need to be reviewed and compared with experimental observations and validated for the conditions prevailing at potential locations in Brazil.

The characteristics of the summer atmospheric water cycle over China and comparison of ERA-Interim and MERRA reanalysis

Atmospheric water cycle process includes precipitation, evaporation, water vapor transport and other links. The temporal and spatial characteristics of the atmospheric water cycle over China in summer are investigated by using the ERA-Interim and MERRA reanalysis from 1979 to 2012. Comparison and performance analyses of these two reanalysis data are given. The obtained results are as follows. 1) the spatial distributions of precipitation, evaporation and precipitable water are highly similar to each other, and all gradually decrease from southeast coast to northwest inland regions. Because the differences in physical condition, precipitation and evaporation among different underlying surfaces, mutually promot or mutually restrict each other, the interactions among them have positive and negative feedback mechanisms. Precipitable water mainly concentrates in the ground to the 700 hPa height, accounts for about 75% of the total quantity. 2) All of the atmospheric water cycle elements have obvious characteristics of climate change, especially in these areas like Northwest China, Tibet and Northeast China. The zonal flux of water vapor transport significantly decreases in most parts of the northern, while the meridional flux of water vapor transport significantly increases in the northern region of Northwest China. 3)The reproduction ability to change characteristics of precipitation is better than that of evaporation based on these reanalyses. The temporal and spatial distribution characteristics of moisture transport situation and the various levels of atmospheric water vapor content are highly consistent with each other. The simulations of flux climate change trend of precipitation and water vapor transport are more accurate and more reliable. 4) Interim reanalysis is applicable to the study of the southwest, Southeast and northeast regional atmospheric water balance, water cycle elements can maintain balance well, while MERRA reanalysis is more reasonable in Southwest and northwest.