scholarly journals Merging High-Resolution Satellite Surface Radiation Data with Meteorological Sunshine Duration Observations over China from 1983 to 2017

2021 ◽  
Vol 13 (4) ◽  
pp. 602
Author(s):  
Fei Feng ◽  
Kaicun Wang
Keyword(s):  
High Resolution ◽  
Sunshine Duration ◽  
Surface Radiation ◽  
Surface Solar Radiation ◽  
Direct Observations ◽  
Lack Of Information ◽  
The 1960S ◽  
Climate Studies ◽  
Very High

Surface solar radiation (Rs) is essential to climate studies. Thanks to long-term records from the Advanced Very High-Resolution Radiometers (AVHRR), the recent release of International Satellite Cloud Climatology Project (ISCCP) HXG cloud products provide a promising opportunity for building long-term Rs data with high resolutions (3 h and 10 km). In this study, we compare three satellite Rs products based on AVHRR cloud products over China from 1983 to 2017 with direct observations of Rs and sunshine duration (SunDu)-derived Rs. The results show that SunDu-derived Rs have higher accuracy than the direct observed Rs at time scales of a month or longer by comparing with the satellite Rs products. SunDu-derived Rs is available from the 1960s at more than 2000 stations over China, which provides reliable decadal estimations of Rs. However, the three AVHRR-based satellite Rs products have significant biases in quantifying the trend of Rs from 1983 to 2016 (−4.28 W/m2/decade to 2.56 W/m2/decade) due to inhomogeneity in satellite cloud products and the lack of information on atmospheric aerosol optical depth. To adjust the inhomogeneity of the satellite Rs products, we propose a geographically weighted regression fusion method (HGWR) to merge ISCCP-HXG Rs with SunDu-derived Rs. The merged Rs product over China from 1983 to 2017 with a spatial resolution of 10 km produces nearly the same trend as that of the SunDu-derived Rs. This study makes a first attempt to adjust the inhomogeneity of satellite Rs products and provides the merged high-resolution Rs product from 1983 to 2017 over China, which can be downloaded freely.

scholarly journals Merging ground-based sunshine duration observations with satellite cloud and aerosol retrievals to produce high-resolution long-term surface solar radiation over China

2021 ◽  
Vol 13 (3) ◽  
pp. 907-922
Author(s):  
Fei Feng ◽  
Kaicun Wang
Keyword(s):  
Standard Deviation ◽  
High Resolution ◽  
Solar Radiation ◽  
Spatial Resolution ◽  
Sunshine Duration ◽  
Ordinary Least Squares ◽  
Cloud Fraction ◽  
Surface Solar Radiation ◽  
The Impact

Abstract. Although great progress has been made in estimating surface solar radiation (Rs) from meteorological observations, satellite retrieval, and reanalysis, getting best-estimated long-term variations in Rs are sorely needed for climate studies. It has been shown that Rs data derived from sunshine duration (SunDu) can provide reliable long-term variability, but such data are available at sparsely distributed weather stations. Here, we merge SunDu-derived Rs with satellite-derived cloud fraction and aerosol optical depth (AOD) to generate high-spatial-resolution (0.1∘) Rs over China from 2000 to 2017. The geographically weighted regression (GWR) and ordinary least-squares regression (OLS) merging methods are compared, and GWR is found to perform better. Based on the SunDu-derived Rs from 97 meteorological observation stations, which are co-located with those that direct Rs measurement sites, the GWR incorporated with satellite cloud fraction and AOD data produces monthly Rs with R2=0.97 and standard deviation =11.14 W m−2, while GWR driven by only cloud fraction produces similar results with R2=0.97 and standard deviation =11.41 W m−2. This similarity is because SunDu-derived Rs has included the impact of aerosols. This finding can help to build long-term Rs variations based on cloud data, such as Advanced Very High Resolution Radiometer (AVHRR) cloud retrievals, especially before 2000, when satellite AOD retrievals are not unavailable. The merged Rs product at a spatial resolution of 0.1∘ in this study can be downloaded at https://doi.org/10.1594/PANGAEA.921847 (Feng and Wang, 2020).

scholarly journals Long-term series of surface solar radiation at Athens, Greece

2017 ◽  
Author(s):  
Stelios Kazadzis ◽  
Dimitra Founda ◽  
Bill Psiloglou ◽  
Haralambos Kambezidis ◽  
Nikolaos Mihalopoulos ◽  
...  
Keyword(s):  
Lower Limit ◽  
Sunshine Duration ◽  
Mediterranean Area ◽  
Surface Radiation ◽  
Linear Change ◽  
Surface Solar Radiation ◽  
Clear Sky ◽  
Ssr Analysis ◽  
The Difference

Abstract. We present a long-term series of solar surface radiation (SSR) for the city of Athens, Greece. The SSR measurements were performed from 1953 to 2012, and before that (1900–1952) sunshine duration (SD) records have been used in order to reconstruct monthly SSR. Analysis from the whole dataset (1900–2012) mainly showed: a decrease of 2.9 % per decade in SSR from 1910 to 1940 assuming a linear change in SSR. For the dimming period (1955–1980), a −2 % change per decade has been observed, that matches various European long-term SSR measurement related studies. This percentage for Athens is in the lower limit, compared to other studies for the Mediterranean area. For the brightening period (1980–2012) we have calculated a +1.5 % per decade which is also in the lower limit of the reported positive changes in SSR around Europe. Comparing the 30-year periods (1954–1983 and 1983–2012) we have found a difference of 4.5 %. The difference was observed for all seasons except winter. Using an analysis of SSR calculations of all sky and clear sky (cloudless) conditions/days, we report that most of the observed changes in SSR after 1954 can be attributed partly to cloudiness and mostly to aerosol load changes.

scholarly journals Merging ground-based sunshine duration with satellite cloud and aerosol data to produce high resolution long-term surface solar radiation over China

2020 ◽  
Author(s):  
Fei Feng ◽  
Kaicun Wang
Keyword(s):  
Standard Deviation ◽  
High Resolution ◽  
Solar Radiation ◽  
Spatial Resolution ◽  
Sunshine Duration ◽  
Ordinary Least Squares ◽  
Cloud Fraction ◽  
Surface Solar Radiation ◽  
The Impact

Abstract. Although great progress has been made in estimating surface solar radiation (Rs) from meteorological observations, satellite retrieval and reanalysis, getting best estimated of long-term variations in Rs are sorely needed for climate studies. It has been shown that sunshine duration (SunDu)-derived Rs data can provide reliable long-term Rs variation. Here, we merge SunDu-derived Rs data with satellite-derived cloud fraction and aerosol optical depth (AOD) data to generate high spatial resolution (0.1°) Rs over China from 2000 to 2017. The geographically weighted regression (GWR) and ordinary least squares regression (OLS) merging methods are compared, and GWR is found to perform better. Whether or not AOD is taken as input data makes little difference for the GWR merging results. Based on the SunDu-derived Rs from 97 meteorological observation stations, the GWR incorporated with satellite cloud fraction and AOD data produces monthly Rs with R2 = 0.97 and standard deviation = 11.14 W/m2, while GWR driven by only cloud fraction produces similar results with R2 = 0.97 and standard deviation = 11.41 w/m2. This similarity is because SunDu-derived Rs has included the impact of aerosols. This finding can help to build long-term Rs variations based on cloud data, such as Advanced Very High Resolution Radiometer (AVHRR) cloud retrievals, especially before 2000, when satellite AOD retrievals are not unavailable. The merged Rs product at a spatial resolution of 0.1° in this study can be downloaded at https://doi.pangaea.de/10.1594/PANGAEA.921847 (Feng and Wang, 2020).

scholarly journals Compatibility of different measurement techniques. Long-term global solar radiation observations at Izaña Observatory

2016 ◽  
Author(s):  
Rosa Delia García ◽  
Emilio Cuevas ◽  
Omaira Elena García ◽  
Ramon Ramón ◽  
Pedro Miguel Romero-Campos ◽  
...  
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
Sunshine Duration ◽  
Measurement Techniques ◽  
Temporal Stability ◽  
Global Solar Radiation ◽  
Surface Radiation ◽  
Multifilter Rotating Shadowband Radiometer ◽  
High Consistency

Abstract. A 1-year intercomparison of classical and modern radiation and sunshine duration instruments has been performed at Izaña Atmospheric Observatory (IZO) located in Tenerife (Canary Islands, Spain) starting on July 17, 2014. We compare global solar radiation (GSR) records measured with a CM-21 pyranometer Kipp & Zonen, taken in the framework of the Baseline Surface Radiation Network, with those measured with a Multifilter Rotating Shadowband Radiometer (MFRSR), and a bimetallic pyranometer (PYR), and GSR estimated from sunshine duration performed by a Campbell-Stokes sunshine recorder (CS) and a Kipp & Zonen sunshine duration sensor (CSD). Given the GSR BSRN records are subject of strict quality controls (based on principles of physical limits and comparison with the LibRadtran model), they have been used as reference in the intercomparison study. We obtain an overall root mean square error (RMSE) of ~0.9 MJm2 (4 %) for GSR PYR and GSR MFRSR, 1.9 MJm2 (7 %) and 1.2 MJm2 (5 %) for GSR CS and GSR CSD, respectively. Factors such as temperature, fraction of the clear sky, relative humidity and the solar zenith angle have shown to moderately affect the GSR observations. As application of the methodology developed in this work, we have re-evaluated the GSR time series between 1977 and 1991 obtained with two PYRs at IZO. By comparing with coincident GSR estimates from SD observations, we probe the high consistency of those measurements and their temporal stability. These results demonstrate that 1) the continuous-basis intercomparison of different GSR techniques offers important diagnostics for identifying inconsistencies between GSR data records, and 2) the GSR measurements performed with classical and more simple instruments are consistent with more modern techniques and, thus, valid to recover GSR time series and complete worldwide distributed GSR data. The intercomparison and quality assessment of these different techniques have allowed to obtain a complete and consistent long-term global solar radiation series (1977–2015) at Izaña.

scholarly journals A 16-year dataset (2000–2015) of high-resolution (3 h, 10 km) global surface solar radiation

2019 ◽  
Vol 11 (4) ◽  
pp. 1905-1915 ◽  
Author(s):  
Wenjun Tang ◽  
Kun Yang ◽  
Jun Qin ◽  
Xin Li ◽  
Xiaolei Niu
Keyword(s):  
High Resolution ◽  
Solar Radiation ◽  
Radiant Energy ◽  
Reanalysis Data ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Mean Bias Error ◽  
Bias Error ◽  
Surface Solar Radiation ◽  
Global Surface

Abstract. The recent release of the International Satellite Cloud Climatology Project (ISCCP) HXG cloud products and new ERA5 reanalysis data enabled us to produce a global surface solar radiation (SSR) dataset: a 16-year (2000–2015) high-resolution (3 h, 10 km) global SSR dataset using an improved physical parameterization scheme. The main inputs were cloud optical depth from ISCCP-HXG cloud products; the water vapor, surface pressure and ozone from ERA5 reanalysis data; and albedo and aerosol from Moderate Resolution Imaging Spectroradiometer (MODIS) products. The estimated SSR data were evaluated against surface observations measured at 42 stations of the Baseline Surface Radiation Network (BSRN) and 90 radiation stations of the China Meteorological Administration (CMA). Validation against the BSRN data indicated that the mean bias error (MBE), root mean square error (RMSE) and correlation coefficient (R) for the instantaneous SSR estimates at 10 km scale were −11.5 W m−2, 113.5 W m−2 and 0.92, respectively. When the estimated instantaneous SSR data were upscaled to 90 km, its error was clearly reduced, with RMSE decreasing to 93.4 W m−2 and R increasing to 0.95. For daily SSR estimates at 90 km scale, the MBE, RMSE and R at the BSRN were −5.8 W m−2, 33.1 W m−2 and 0.95, respectively. These error metrics at the CMA radiation stations were 2.1 W m−2, 26.9 W m−2 and 0.95, respectively. Comparisons with other global satellite radiation products indicated that our SSR estimates were generally better than those of the ISCCP flux dataset (ISCCP-FD), the global energy and water cycle experiment surface radiation budget (GEWEX-SRB), and the Earth's Radiant Energy System (CERES). Our SSR dataset will contribute to the land-surface process simulations and the photovoltaic applications in the future. The dataset is available at  https://doi.org/10.11888/Meteoro.tpdc.270112 (Tang, 2019).

scholarly journals Development of a longterm dataset of solid/liquid precipitation

2011 ◽  
Vol 6 (1) ◽  
pp. 39-43 ◽  
Author(s):  
B. Chimani ◽  
R. Böhm ◽  
C. Matulla ◽  
M. Ganekind
Keyword(s):  
High Resolution ◽  
20Th Century ◽  
Alpine Region ◽  
Nonlinear Relationship ◽  
Solid Precipitation ◽  
Temperature And Precipitation ◽  
Solid Liquid ◽  
Climate Studies ◽  
Liquid Precipitation

Abstract. Solid precipitation (mainly snow, but snow and ice pellets or hail as well), is an important parameter for climate studies. But as this parameter usually is not available operationally before the second part of the 20th century and nowadays is not reported by automatic stations, information usable for long term climate studies is rare. Therefore a proxy for the fraction of solid precipitation based on a nonlinear relationship between the percentage of solid precipitation and monthly mean temperature was developed for the Greater Alpine Region of Europe and applied to the existing longterm high resolution temperature and precipitation grids (5 arcmin). In this paper the method is introduced and some examples of the resulting datasets available at monthly resolution for 1800–2003 are given.

scholarly journals A global long term (1981–2019) daily land surface radiation budget product from AVHRR satellite data using a residual convolutional neural network

2021 ◽  
Author(s):  
Jianglei Xu ◽  
Shunlin Liang ◽  
Bo Jiang
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Convolutional Neural Network ◽  
Satellite Data ◽  
Land Surface ◽  
Radiant Energy ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Surface Radiation Budget

Abstract. The surface radiation budget, also known as all-wave net radiation (Rn), is a key parameter for various land surface processes including hydrological, ecological, agricultural, and biogeochemical processes. Satellite data can be effectively used to estimate Rn, but existing satellite products have coarse spatial resolutions and limited temporal coverage. In this study, a point-surface matching estimation (PSME) method is proposed to estimate surface Rn using a residual convolutional neural network (RCNN) integrating spatially adjacent information to improve the accuracy of retrievals. A global high-resolution (0.05°) long-term (1981–2019) Rn product was subsequently generated from Advanced Very High-Resolution Radiometer (AVHRR) data. Specifically, the RCNN was employed to establish a nonlinear relationship between globally distributed ground measurements from 537 sites and AVHRR top of atmosphere (TOA) observations. Extended triplet collocation (ETC) technology was applied to address the spatial scale mismatch issue resulting from the low spatial support of ground measurements within the AVHRR footprint by selecting reliable sites for model training. The overall independent validation results show that the generated AVHRR Rn product is highly accurate, with R2, root-mean-square error (RMSE), and bias of 0.84, 26.66 Wm−2 (31.66 %), and 1.59 Wm−2 (1.89 %), respectively. Inter-comparisons with three other Rn products, i.e., the 5 km Global Land Surface Satellite (GLASS), the 1° Clouds and the Earth's Radiant Energy System (CERES), and the 0.5° × 0.625° Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2), illustrate that our AVHRR Rn retrievals have the best accuracy under all of the considered surface and atmospheric conditions, especially thick cloud or hazy conditions. The spatiotemporal analyses of these four Rn datasets indicate that the AVHRR Rn product reasonably replicates the spatial pattern and temporal evolution trends of Rn observations. This dataset is freely available at https://doi.org/10.5281/zenodo.5509854 for 1981–2019 (Xu et al., 2021).

scholarly journals Malnutrition Rates in Chile from the Nitrate Era to the 1990s

2021 ◽  
Vol 18 (24) ◽  
pp. 13112
Author(s):  
Manuel Llorca-Jaña ◽  
Diego Barría Traverso ◽  
Diego del Barrio Vásquez ◽  
Javier Rivas
Keyword(s):  
Developed Countries ◽  
Mortality Rates ◽  
Adult Males ◽  
Sharp Decline ◽  
Low Levels ◽  
The 1960S ◽  
Chilean Population ◽  
Very High ◽  
Over Time

Following Salvatore and the WHO, in this article, we provide the first long-term estimates of malnutrition rates for Chile per birth cohort, measured through stunting rates of adult males born from the 1870s to the 1990s. We used a large sample of military records, representative of the whole Chilean population, totalling over 38 thousand individuals. Our data suggest that stunting rates were very high for those born between the last three decades of the nineteenth century and the first two decades of the twentieth century. In addition, stunting rates increased from the 1870s to the 1900s. Thereafter, there was a clear downward trend in stunting rates (despite some fluctuations), reaching low levels of malnutrition, in particular, from the 1960s (although these are high if compared to developed countries). The continuous decrease in stunting rates from the 1910s was mainly due to a combination of factors, the importance of which varied over time, namely: Improved health (i.e., sharp decline in infant mortality rates during the whole period); increased energy consumption (from the 1930s onwards, but most importantly during the 1990s); a decline in poverty rates (in particular, between the 1930s and the 1970s); and a reduction in child labour (although we are less able to quantify this).

scholarly journals Retrieval of aerosol optical depth over land surfaces from AVHRR data

2013 ◽  
Vol 6 (1) ◽  
pp. 2227-2251 ◽  
Author(s):  
L. Mei ◽  
Y. Xue ◽  
A. A. Kokhanovsky ◽  
W. von Hoyningen-Huene ◽  
G. de Leeuw ◽  
...  
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Reflectance ◽  
Aerosol Retrieval ◽  
Avhrr Data ◽  
Land Surfaces ◽  
Very High

Abstract. The Advanced Very High Resolution Radiometer (AVHRR) radiance data provide a global, long-term, consistent time series having high spectral and spatial resolution and thus being valuable for the retrieval of surface spectral reflectance, albedo and surface temperature. Long term time series of such data products are necessary for studies addressing climate change, sea ice distribution and movement, and ice sheet coastal configuration. These data have also been used to retrieve aerosol properties over ocean and land surfaces. However, the retrieval of aerosol over land and land surface albedo are challenging because of the information content of the measurement is limited and the inversion of these data products being ill defined. Solving the radiative transfer equations requires additional information and knowledge to reduce the number of unknowns. In this contribution we utilise an empirical linear relationship between the surface reflectances in the AVHRR channels at wavelengths of 3.75 μm and 2.1 μm, which has been identified in Moderate Resolution Imaging Spectroradiometer (MODIS) data. Next, following the MODIS dark target approach, the surface reflectance at 0.64 μm was obtained. The comparison of the estimated surface reflectance at 0.64 μm with MODIS reflectance products (MOD09) shows a strong correlation (R = 0.7835). Once this was established, the MODIS "dark-target" aerosol retrieval method was adapted to Advanced Very High Resolution Radiometer (AVHRR) data. A simplified Look-Up Table (LUT) method, adopted from Bremen AErosol Retrieval (BAER) algorithm, was used in the retrieval. The Aerosol Optical Depth (AOD) values retrieved from AVHRR with this method compare favourably with ground-based measurements, with a correlation coefficient R = 0.861 and Root Mean Square Error (RMSE) = 0.17. This method can be easily applied to other satellite instruments which do not have a 2.1 μm channel, such as those currently planned to geostationary satellites.

scholarly journals SARAH-3 - a new satellite-based Cimate Data Record for surface radiation parameters from the CM SAF

2021 ◽  
Author(s):  
Uwe Pfeifroth ◽  
Jaqueline Drücke ◽  
Jörg Trentmann ◽  
Rainer Hollmann
Keyword(s):  
Water Cycle ◽  
Sunshine Duration ◽  
Global Radiation ◽  
Surface Radiation ◽  
Climate Data ◽  
Surface Solar Radiation ◽  
Data Set ◽  
Time Period ◽  
Data Record ◽  
Climate Data Record

<p>The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates and distributes high quality long-term climate data records (CDR) of energy and water cycle parameters, which are freely available.</p><p>In fall 2021, a new version of the “Surface Solar Radiation data set – Heliosat” will be released: SARAH-3. As the previous editions, the SARAH-3 climate data record is based on satellite observations from the first and second METEOSAT generations and provides various surface radiation parameters, including global radiation, direct radiation, sunshine duration, photosynthetic active radiation and others. SARAH-3 covers the time period 1983 to 2020 and offers 30-minute instantaneous data as well as daily and monthly means on a regular 0.05° x 0.05° lon/lat grid.</p><p>In this presentation, an overview of the SARAH climate data record and their applications will be provided. A focus will be on the SARAH-3 developments and improvements (i.e. improved consideration of snow-covered surfaces). First validation results of the new Climate Data Record using surface reference observations will be presented. Further, SARAH-3 will be used for the analysis of the climate variability in Europe during the last decades.</p><p>. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .</p>

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