DSCOVR/EPIC-derived global hourly and daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution

Abstract. Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique means for mapping accurate spatiotemporally continuous SW–PAR, globally. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multisource data from complementary satellites/sensors is challenging because of co-registration, intercalibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR), launched in February 2015, offers an unprecedented possibility to bridge the gap between high temporal resolution and global coverage and characterize the diurnal cycles of SW–PAR globally. In this study, we adopted a suite of well-validated data-driven machine-learning models to generate the first global land products of SW–PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The derived products have high temporal resolution (hourly) and medium spatial resolution (0.1∘×0.1∘), and they include estimates of the direct and diffuse components of SW–PAR. We used independently widely distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA's Global Monitoring Division and the U.S. Department of Energy's Atmospheric System Research (ASR) program to evaluate the performance of our products, and we further analyzed and compared the spatiotemporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. We found both the hourly and daily products to be consistent with ground-based observations (e.g., hourly and daily total SWs have low biases of −3.96 and −0.71 W m−2 and root-mean-square errors (RMSEs) of 103.50 and 35.40 W m−2, respectively). The developed products capture the complex spatiotemporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations in SW–PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications worldwide and can be used to improve our understanding of the diurnal and seasonal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales. The products are freely available at https://doi.org/10.25584/1595069 (Hao et al., 2020).

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DSCOVR/EPIC-derived global hourly/daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution

10.5194/essd-2020-19 ◽

2020 ◽

Author(s):

Dalei Hao ◽

Ghassem R. Asrar ◽

Yelu Zeng ◽

Qing Zhu ◽

Jianguang Wen ◽

...

Keyword(s):

Temporal Resolution ◽

Photosynthetically Active Radiation ◽

Spatial Scales ◽

Surface Radiation ◽

Radiation Budget ◽

High Temporal Resolution ◽

Active Radiation ◽

Global Coverage ◽

Spatio Temporal ◽

Mean Square Errors

Abstract. Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique means for mapping accurate spatio-temporally-continuous SW/PAR, globally. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multi-source data from complementary satellites/sensors is challenging because of co-registration, inter-calibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR), launched in February 2015, offers an unprecedented possibility to bridge the gap between high temporal resolution and global coverage, and characterize the diurnal cycles of SW/PAR globally. In this study, we adopted a suite of well-validated data-driven machine-learning models to generate the first global land products of SW/PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The derived products have high temporal resolution (hourly) and medium spatial resolution (0.1° × 0.1°), and include estimates of the direct and diffuse components of SW/PAR. We used independently widely-distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA's Global Monitoring Division and the U.S. Department of Energy’s Atmospheric System Research (ASR) program to evaluate the performance of our products, and further analyzed and compared the spatio-temporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. We found both the hourly and daily products to be consistent with ground-based observations (e.g., hourly and daily total SWs have low biases of −3.96 and −0.71 W/m2 and root mean square errors (RMSEs) of 103.50 and 35.40 W/m2, respectively). The developed products capture the complex spatio-temporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations of SW/PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications worldwide and can be used to improve our understanding of the diurnal and seasonal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales. The products are freely available at https://doi.org/10.25584/1595069 (Hao et al., 2020).

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A New Clear-Sky Method for Assessing Photosynthetically Active Radiation at the Surface Level

Atmosphere ◽

10.3390/atmos10040219 ◽

2019 ◽

Vol 10 (4) ◽

pp. 219

Author(s):

William Wandji Nyamsi ◽

Philippe Blanc ◽

John A. Augustine ◽

Antti Arola ◽

Lucien Wald

Keyword(s):

Photosynthetically Active Radiation ◽

Photosynthetic Photon Flux Density ◽

Surface Radiation ◽

Radiation Budget ◽

Photon Flux ◽

Photon Flux Density ◽

Distribution Method ◽

Active Radiation ◽

Surface Level ◽

Clear Sky

A clear–sky method to estimate the photosynthetically active radiation (PAR) at the surface level in cloudless atmospheres is presented and validated. It uses a fast and accurate approximation adopted in several radiative transfer models, known as the k-distribution method and the correlated-k approximation, which gives a set of fluxes accumulated over 32 established wavelength intervals. A resampling technique, followed by a summation, are applied over the wavelength range [0.4, 0.7] µm in order to retrieve the PAR fluxes. The method uses as inputs the total column contents of ozone and water vapor, and optical properties of aerosols provided by the Copernicus Atmosphere Monitoring Service. To validate the method, its outcomes were compared to instantaneous global photosynthetic photon flux density (PPFD) measurements acquired at seven experimental sites of the Surface Radiation Budget Network (SURFRAD) located in various climates in the USA. The bias lies in the interval [−12, 61] µmol m−2 s−1 ([−1, 5] % in values relative to the means of the measurements at each station). The root mean square error ranges between 37 µmol m−2 s−1 (3%) and 82 µmol m−2 s−1 (6%). The squared correlation coefficient fluctuates from 0.97 to 0.99. This comparison demonstrates the high level of accuracy of the presented method, which offers an accurate estimate of PAR fluxes in cloudless atmospheres at high spatial and temporal resolutions useful for several bio geophysical models.

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Lagrange Point Missions: The Key to next Generation Integrated Earth Observations. DSCOVR Innovation

Frontiers in Remote Sensing ◽

10.3389/frsen.2021.745938 ◽

2021 ◽

Vol 2 ◽

Author(s):

Francisco P. J. Valero ◽

Alexander Marshak ◽

Patrick Minnis

Keyword(s):

Temporal Resolution ◽

Large Scale ◽

Surface Radiation ◽

Atmospheric Composition ◽

Radiation Budget ◽

High Temporal Resolution ◽

Polar Regions ◽

The Moon ◽

Next Generation ◽

Lagrange Points

A new perspective for studying Earth processes has been soundly demonstrated by the Deep Space Climate Observatory (DSCOVR) mission. For the past 6 years, the first Earth-observing satellite orbiting at the Lagrange 1 (L1) point, the DSCOVR satellite has been viewing the planet in a fundamentally different way compared to all other satellites. It is providing unique simultaneous observations of nearly the entire sunlit face of the Earth at a relatively high temporal resolution. This capability enables detailed coverage of evolving atmospheric and surface systems over meso- and large-scale domains, both individually and as a whole, from sunrise to sunset, under continuously changing illumination and viewing conditions. DSCOVR’s view also contains polar regions that are only partially seen from geostationary satellites (GEOs). To exploit this unique perspective, DSCOVR instruments provide multispectral imagery and measurements of the Earth’s reflected and emitted radiances from 0.2 to 100 µm. Data from these sensors have been and continue to be utilized for a great variety of research involving retrievals of atmospheric composition, aerosols, clouds, ocean, and vegetation properties; estimates of surface radiation and the top-of-atmosphere radiation budget; and determining exoplanet signatures. DSCOVR’s synoptic and high temporal resolution data encompass the areas observed during the day from low Earth orbiting satellites (LEOs) and GEOs along with occasional views of the Moon. Because the LEO and GEO measurements can be easily matched with simultaneous DSCOVR data, multiangle, multispectral datasets can be developed by integrating DSCOVR, LEO, and GEO data along with surface and airborne observations, when available. Such datasets can open the door for global application of algorithms heretofore limited to specific LEO satellites and development of new scientific tools for Earth sciences. The utility of the integrated datasets relies on accurate intercalibration of the observations, a process that can be facilitated by the DSCOVR views of the Moon, which serves as a stable reference. Because of their full-disc views, observatories at one or more Lagrange points can play a key role in next-generation integrated Earth observing systems.

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Estimation of Daily Mean Photosynthetically Active Radiation under All-Sky Conditions Based on Relative Sunshine Data

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-10-05018.1 ◽

2012 ◽

Vol 51 (1) ◽

pp. 150-160 ◽

Cited By ~ 22

Author(s):

Jun Qin ◽

Kun Yang ◽

Shunlin Liang ◽

Wenjun Tang

Keyword(s):

Photosynthetically Active Radiation ◽

Sunshine Duration ◽

Surface Radiation ◽

Radiation Budget ◽

Mean Bias Error ◽

Bias Error ◽

Active Radiation ◽

Clear Sky ◽

Surface Radiation Budget ◽

Sky Conditions

AbstractPhotosynthetically active radiation (PAR) is absorbed by plants to carry out photosynthesis. Its estimation is important for many applications such as ecological modeling. In this study, a broadband transmittance scheme for solar radiation at the PAR band is developed to estimate clear-sky PAR values. The influence of clouds is subsequently taken into account through sunshine-duration data. This scheme is examined without local calibration against the observed PAR values under both clear- and cloudy-sky conditions at seven widely distributed Surface Radiation Budget Network (SURFRAD) stations. The results indicate that the scheme can estimate the daily mean PAR at these seven stations under all-sky conditions with root-mean-square error and mean bias error values ranging from 6.03 to 6.83 W m−2 and from −2.86 to 1.03 W m−2, respectively. Further analyses indicate that the scheme can estimate PAR values well with globally available aerosol and ozone datasets. This suggests that the scheme can be applied to regions for which observed aerosol and ozone data are not available.

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Multimodal in vivo recording using transparent graphene microelectrodes illuminates spatiotemporal seizure dynamics at the microscale

Communications Biology ◽

10.1038/s42003-021-01670-9 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Nicolette Driscoll ◽

Richard E. Rosch ◽

Brendan B. Murphy ◽

Arian Ashourvan ◽

Ramya Vishnubhotla ◽

...

Keyword(s):

Temporal Resolution ◽

Spatial Scales ◽

Epileptic Seizures ◽

Therapeutic Interventions ◽

State Transitions ◽

Integrated Analysis ◽

High Temporal Resolution ◽

Seizure Onset ◽

Acute Seizures

AbstractNeurological disorders such as epilepsy arise from disrupted brain networks. Our capacity to treat these disorders is limited by our inability to map these networks at sufficient temporal and spatial scales to target interventions. Current best techniques either sample broad areas at low temporal resolution (e.g. calcium imaging) or record from discrete regions at high temporal resolution (e.g. electrophysiology). This limitation hampers our ability to understand and intervene in aberrations of network dynamics. Here we present a technique to map the onset and spatiotemporal spread of acute epileptic seizures in vivo by simultaneously recording high bandwidth microelectrocorticography and calcium fluorescence using transparent graphene microelectrode arrays. We integrate dynamic data features from both modalities using non-negative matrix factorization to identify sequential spatiotemporal patterns of seizure onset and evolution, revealing how the temporal progression of ictal electrophysiology is linked to the spatial evolution of the recruited seizure core. This integrated analysis of multimodal data reveals otherwise hidden state transitions in the spatial and temporal progression of acute seizures. The techniques demonstrated here may enable future targeted therapeutic interventions and novel spatially embedded models of local circuit dynamics during seizure onset and evolution.

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Estimation of Incident Photosynthetically Active Radiation from GOES Visible Imagery

Journal of Applied Meteorology and Climatology ◽

10.1175/2007jamc1475.1 ◽

2008 ◽

Vol 47 (3) ◽

pp. 853-868 ◽

Cited By ~ 43

Author(s):

Tao Zheng ◽

Shunlin Liang ◽

Kaicun Wang

Keyword(s):

Photosynthetically Active Radiation ◽

Terrestrial Ecosystem ◽

New Method ◽

High Temporal Resolution ◽

Atmospheric Conditions ◽

Ecosystem Models ◽

Surface Conditions ◽

Active Radiation ◽

Ground Measurement ◽

Visible Imagery

Abstract Incident photosynthetically active radiation (PAR) is an important parameter for terrestrial ecosystem models. Because of its high temporal resolution, the Geostationary Operational Environmental Satellite (GOES) observations are very suited to catch the diurnal variation of PAR. In this paper, a new method is developed to derive PAR using GOES data. What makes this new method distinct from the existing method is that it does not need external knowledge of atmospheric conditions. The new method retrieves both atmospheric and surface conditions using only at-sensor radiance through interpolation of time series of observations. Validations against ground measurement are carried out at four “FLUXNET” sites. The values of RMSE of estimated and ground-measured instantaneous PAR at the four sites are 130.71, 131.44, 141.16, and 190.22 μmol m−2 s−1, respectively. At the four validation sites, the RMSE as the percentage of estimated mean PAR value are 9.52%, 13.01%, 13.92%, and 24.09%, respectively; the biases are −101.54, 16.56, 11.09, and 53.64 μmol m−2 s−1, respectively. The independence of external atmospheric information enables this method to be applicable to many situations in which external atmospheric information is not available. In addition, topographic impacts on surface PAR are examined at the 1-km resolution at which PAR is retrieved using the GOES visible band data.

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A statistics-based temporal filter algorithm to map spatiotemporally continuous shortwave albedo from MODIS data

Hydrology and Earth System Sciences ◽

10.5194/hess-17-2121-2013 ◽

2013 ◽

Vol 17 (6) ◽

pp. 2121-2129 ◽

Cited By ~ 50

Author(s):

N. F. Liu ◽

Q. Liu ◽

L. Z. Wang ◽

S. L. Liang ◽

J. G. Wen ◽

...

Keyword(s):

Time Series ◽

Temporal Resolution ◽

Land Surface ◽

Surface Albedo ◽

Critical Role ◽

Radiant Energy ◽

High Temporal Resolution ◽

Land Surface Parameter ◽

Temporal Filter ◽

Moderate Resolution Imaging Spectroradiometer

Abstract. Land-surface albedo plays a critical role in the earth's radiant energy budget studies. Satellite remote sensing provides an effective approach to acquire regional and global albedo observations. Owing to cloud coverage, seasonal snow and sensor malfunctions, spatiotemporally continuous albedo datasets are often inaccessible. The Global LAnd Surface Satellite (GLASS) project aims at providing a suite of key land surface parameter datasets with high temporal resolution and high accuracy for a global change study. The GLASS preliminary albedo datasets are global daily land-surface albedo generated by an angular bin algorithm (Qu et al., 2013). Like other products, the GLASS preliminary albedo datasets are affected by large areas of missing data; beside, sharp fluctuations exist in the time series of the GLASS preliminary albedo due to data noise and algorithm uncertainties. Based on the Bayesian theory, a statistics-based temporal filter (STF) algorithm is proposed in this paper to fill data gaps, smooth albedo time series, and generate the GLASS final albedo product. The results of the STF algorithm are smooth and gapless albedo time series, with uncertainty estimations. The performance of the STF method was tested on one tile (H25V05) and three ground stations. Results show that the STF method has greatly improved the integrity and smoothness of the GLASS final albedo product. Seasonal trends in albedo are well depicted by the GLASS final albedo product. Compared with MODerate resolution Imaging Spectroradiometer (MODIS) product, the GLASS final albedo product has a higher temporal resolution and more competence in capturing the surface albedo variations. It is recommended that the quality flag should be always checked before using the GLASS final albedo product.

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

Earth System Science Data ◽

10.5194/essd-11-1905-2019 ◽

2019 ◽

Vol 11 (4) ◽

pp. 1905-1915 ◽

Cited By ~ 8

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).

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Impact of synthetic space-borne NO<sub>2</sub> observations from the Sentinel-4 and Sentinel-5P missions on tropospheric NO<sub>2</sub> analyses

Atmospheric Chemistry and Physics ◽

10.5194/acp-19-12811-2019 ◽

2019 ◽

Vol 19 (19) ◽

pp. 12811-12833 ◽

Cited By ~ 2

Author(s):

Renske Timmermans ◽

Arjo Segers ◽

Lyana Curier ◽

Rachid Abida ◽

Jean-Luc Attié ◽

...

Keyword(s):

Error Estimates ◽

Temporal Resolution ◽

Transport Model ◽

Surface Ozone ◽

Low Earth Orbit ◽

Added Value ◽

High Temporal Resolution ◽

Chemistry Transport Model ◽

European Continent ◽

Global Coverage

Abstract. We present an Observing System Simulation Experiment (OSSE) dedicated to the evaluation of the added value of the Sentinel-4 and Sentinel-5P missions for tropospheric nitrogen dioxide (NO2). Sentinel-4 is a geostationary (GEO) mission covering the European continent, providing observations with high temporal resolution (hourly). Sentinel-5P is a low Earth orbit (LEO) mission providing daily observations with a global coverage. The OSSE experiment has been carefully designed, with separate models for the simulation of observations and for the assimilation experiments and with conservative estimates of the total observation uncertainties. In the experiment we simulate Sentinel-4 and Sentinel-5P tropospheric NO2 columns and surface ozone concentrations at 7 by 7 km resolution over Europe for two 3-month summer and winter periods. The synthetic observations are based on a nature run (NR) from a chemistry transport model (MOCAGE) and error estimates using instrument characteristics. We assimilate the simulated observations into a chemistry transport model (LOTOS-EUROS) independent of the NR to evaluate their impact on modelled NO2 tropospheric columns and surface concentrations. The results are compared to an operational system where only ground-based ozone observations are ingested. Both instruments have an added value to analysed NO2 columns and surface values, reflected in decreased biases and improved correlations. The Sentinel-4 NO2 observations with hourly temporal resolution benefit modelled NO2 analyses throughout the entire day where the daily Sentinel-5P NO2 observations have a slightly lower impact that lasts up to 3–6 h after overpass. The evaluated benefits may be even higher in reality as the applied error estimates were shown to be higher than actual errors in the now operational Sentinel-5P NO2 products. We show that an accurate representation of the NO2 profile is crucial for the benefit of the column observations on surface values. The results support the need for having a combination of GEO and LEO missions for NO2 analyses in view of the complementary benefits of hourly temporal resolution (GEO, Sentinel-4) and global coverage (LEO, Sentinel-5P).

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Aerosol trends as a potential driver of regional climate in the central United States: evidence from observations

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-13559-2017 ◽

2017 ◽

Vol 17 (22) ◽

pp. 13559-13572 ◽

Cited By ~ 6

Author(s):

Daniel H. Cusworth ◽

Loretta J. Mickley ◽

Eric M. Leibensperger ◽

Michael J. Iacono

Keyword(s):

United States ◽

Radiative Transfer ◽

Southeastern United States ◽

Radiant Energy ◽

Surface Radiation ◽

Radiation Budget ◽

Radiative Transfer Model ◽

Transfer Model ◽

Clear Sky

Abstract. In situ surface observations show that downward surface solar radiation (SWdn) over the central and southeastern United States (US) has increased by 0.58–1.0 Wm−2 a−1 over the 2000–2014 time frame, simultaneously with reductions in US aerosol optical depth (AOD) of 3.3–5.0  ×  10−3 a−1. Establishing a link between these two trends, however, is challenging due to complex interactions between aerosols, clouds, and radiation. Here we investigate the clear-sky aerosol–radiation effects of decreasing US aerosols on SWdn and other surface variables by applying a one-dimensional radiative transfer to 2000–2014 measurements of AOD at two Surface Radiation Budget Network (SURFRAD) sites in the central and southeastern United States. Observations characterized as clear-sky may in fact include the effects of thin cirrus clouds, and we consider these effects by imposing satellite data from the Clouds and Earth's Radiant Energy System (CERES) into the radiative transfer model. The model predicts that 2000–2014 trends in aerosols may have driven clear-sky SWdn trends of +1.35 Wm−2 a−1 at Goodwin Creek, MS, and +0.93 Wm−2 a−1 at Bondville, IL. While these results are consistent in sign with observed trends, a cross-validated multivariate regression analysis shows that AOD reproduces 20–26 % of the seasonal (June–September, JJAS) variability in clear-sky direct and diffuse SWdn at Bondville, IL, but none of the JJAS variability at Goodwin Creek, MS. Using in situ soil and surface flux measurements from the Ameriflux network and Illinois Climate Network (ICN) together with assimilated meteorology from the North American Land Data Assimilation System (NLDAS), we find that sunnier summers tend to coincide with increased surface air temperature and soil moisture deficits in the central US. The 1990–2015 trends in the NLDAS SWdn over the central US are also of a similar magnitude to our modeled 2000–2014 clear-sky trends. Taken together, these results suggest that climate and regional hydrology in the central US are sensitive to the recent reductions in aerosol concentrations. Our work has implications for severely polluted regions outside the US, where improvements in air quality due to reductions in the aerosol burden could inadvertently pose an enhanced climate risk.

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