scholarly journals Analysis of Long-Term Solar Resource Variability Using NSRDB Version 3

2021 ◽  
Author(s):  
Manajit Sengupta ◽  
Aron Habte
Keyword(s):  
Solar Radiation ◽  
Spatial Variability ◽  
Temporal Variability ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Spatial And Temporal Variability ◽  
Cloud Optical Depth ◽  
Resource Variability ◽  
Solar Resource

<p>Understanding long-term solar resource variability is essential for planning and deployment of solar energy systems. These variabilities occur due to deterministic effects such as sun cycle and nondeterministic such as complex weather patterns. The NREL’s National Solar Radiation Database (NSRDB) provides long term solar resource data covering 1998- 2019 containing more than 2 million pixels over the Americas and gets updated on an annual basis. This dataset is satellite-based and uses a two-step physical model for it’s development. In the first step we retrieve cloud properties such as cloud mask, cloud type, cloud optical depth and effective radius. The second step uses a fast radiative transfer model to compute solar radiation.  This dataset is ideal for studying solar resource variability. For this study, NSRDB version 3 which contains data from 1998-2017 on a half hourly and 4x4 km temporal and spatial resolution was used. The study analyzed the spatial and temporal trend of solar resource of global horizontal irradiance (GHI) and direct normal irradiance (DNI) using long-term 20-years NSRDB data. The coefficient of variation (COV) was used to analyze the spatio-temporal interannual and seasonal variabilities. The spatial variability was analyzed by comparing the center pixel to neighboring pixels. The spatial variability result showed higher COV as the number of neighboring pixels increased. Similarly, the temporal variability for the NSRDB domain ranges on average from ±10% for GHI and ±20% for DNI. Furthermore, the long-term variabilities were also analyzed using the Köppen-Geiger climate classification. This assisted in the interpretation of the result by reducing the originally large number of pixels into a smaller number of groups. This presentation will provided a unique look at long-term spatial and temporal variability of solar radiation using high-resolution satellite-based datasets.</p>

scholarly journals A hydrochemical modelling framework for combined assessment of spatial and temporal variability in stream chemistry: application to Plynlimon, Wales

2001 ◽  
Vol 5 (1) ◽  
pp. 49-58 ◽  
Author(s):  
H.J. Foster ◽  
M.J. Lees ◽  
H.S. Wheater ◽  
C. Neal ◽  
B. Reynolds
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Spatial Variability ◽  
Temporal Variability ◽  
Biological Diversity ◽  
Spatial And Temporal Variability ◽  
Stream Chemistry ◽  
Two Component ◽  
End Members

Abstract. Recent concern about the risk to biota from acidification in upland areas, due to air pollution and land-use change (such as the planting of coniferous forests), has generated a need to model catchment hydro-chemistry to assess environmental risk and define protection strategies. Previous approaches have tended to concentrate on quantifying either spatial variability at a regional scale or temporal variability at a given location. However, to protect biota from ‘acid episodes’, an assessment of both temporal and spatial variability of stream chemistry is required at a catchment scale. In addition, quantification of temporal variability needs to represent both episodic event response and long term variability caused by deposition and/or land-use change. Both spatial and temporal variability in streamwater chemistry are considered in a new modelling methodology based on application to the Plynlimon catchments, central Wales. A two-component End-Member Mixing Analysis (EMMA) is used whereby low and high flow chemistry are taken to represent ‘groundwater’ and ‘soil water’ end-members. The conventional EMMA method is extended to incorporate spatial variability in the two end-members across the catchments by quantifying the Acid Neutralisation Capacity (ANC) of each in terms of a statistical distribution. These are then input as stochastic variables to a two-component mixing model, thereby accounting for variability of ANC both spatially and temporally. The model is coupled to a long-term acidification model (MAGIC) to predict the evolution of the end members and, hence, the response to future scenarios. The results can be plotted as a function of time and space, which enables better assessment of the likely effects of pollution deposition or land-use changes in the future on the stream chemistry than current methods which use catchment average values. The model is also a useful basis for further research into linkage between hydrochemistry and intra-catchment biological diversity. Keywords: hydrochemistry, End-Member Mixing Analysis (EMMA), uplands, acidification

scholarly journals Interannual climate variability data improves niche estimates in species distribution models

2021 ◽  
Author(s):  
Dirk Nikolaus Karger ◽  
Bianca Saladin ◽  
Rafael O. Wueest ◽  
Catherine H. Graham ◽  
Damaris Zurell ◽  
...  
Keyword(s):  
Climate Variability ◽  
Spatial Variability ◽  
Species Distribution ◽  
Temporal Variability ◽  
Species Distribution Models ◽  
Essential Element ◽  
Spatial And Temporal Variability ◽  
Distribution Models ◽  
Mammal Species

Aim: Climate is an essential element of species' niche estimates in many current ecological applications such as species distribution models (SDMs). Climate predictors are often used in the form of long-term mean values. Yet, climate can also be described as spatial or temporal variability for variables like temperature or precipitation. Such variability, spatial or temporal, offers additional insights into niche properties. Here, we test to what degree spatial variability and long-term temporal variability in temperature and precipitation improve SDM predictions globally. Location: Global. Time period: 1979-2013. Major taxa studies: Mammal, Amphibians, Reptiles. Methods: We use three different SDM algorithms, and a set of 833 amphibian, 779 reptile, and 2211 mammal species to quantify the effect of spatial and temporal climate variability in SDMs. All SDMs were cross-validated and accessed for their performance using the Area under the Curve (AUC) and the True Skill Statistic (TSS). Results: Mean performance of SDMs with climatic means as predictors was TSS=0.71 and AUC=0.90. The inclusion of spatial variability offers a significant gain in SDM performance (mean TSS=0.74, mean AUC=0.92), as does the inclusion of temporal variability (mean TSS=0.80, mean AUC=0.94). Including both spatial and temporal variability in SDMs shows similarly high TSS and AUC scores. Main conclusions: Accounting for temporal rather than spatial variability in climate improved the SDM prediction especially in exotherm groups such as amphibians and reptiles, while for endotermic mammals no such improvement was observed. These results indicate that more detailed information about temporal climate variability offers a highly promising avenue for improving niche estimates and calls for a new set of standard bioclimatic predictors in SDM research.

scholarly journals Long-term stability of TES satellite radiance measurements

2011 ◽  
Vol 4 (7) ◽  
pp. 1481-1490 ◽  
Author(s):  
T. C. Connor ◽  
M. W. Shephard ◽  
V. H. Payne ◽  
K. E. Cady-Pereira ◽  
S. S. Kulawik ◽  
...  
Keyword(s):  
Optical Depth ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Radiometric Calibration ◽  
Cloud Optical Depth ◽  
Brightness Temperatures ◽  
The Difference ◽  
The Stability ◽  
Reference Measurements

Abstract. The utilization of Tropospheric Emission Spectrometer (TES) Level 2 (L2) retrieval products for the purpose of assessing long term changes in atmospheric trace gas composition requires knowledge of the overall radiometric stability of the Level 1B (L1B) radiances. The purpose of this study is to evaluate the stability of the radiometric calibration of the TES instrument by analyzing the difference between measured and calculated brightness temperatures in selected window regions of the spectrum. The Global Modeling and Assimilation Office (GMAO) profiles for temperature and water vapor and the Real-Time Global Sea Surface Temperature (RTGSST) are used as input to the Optimal Spectral Sampling (OSS) radiative transfer model to calculate the simulated spectra. The TES reference measurements selected cover a 4-year period of time from mid 2005 through mid 2009 with the selection criteria being; observation latitudes greater than −30° and less than 30°, over ocean, Global Survey mode (nadir view) and retrieved cloud optical depth of less than or equal to 0.01. The TES cloud optical depth retrievals are used only for screening purposes and no effects of clouds on the radiances are included in the forward model. This initial screening results in over 55 000 potential reference spectra spanning the four year period. Presented is a trend analysis of the time series of the residuals (observation minus calculations) in the TES 2B1, 1B2, 2A1, and 1A1 bands, with the standard deviation of the residuals being approximately equal to 0.6 K for bands 2B1, 1B2, 2A1, and 0.9 K for band 1A1. The analysis demonstrates that the trend in the residuals is not significantly different from zero over the 4-year period. This is one method used to demonstrate that the relative radiometric calibration is stable over time, which is very important for any longer term analysis of TES retrieved products (L2), particularly well-mixed species such as carbon dioxide and methane.

scholarly journals Spatial and Temporal Trends of Irrigated Cotton Yield in the Southern High Plains

Agronomy ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. 298 ◽  
Author(s):  
Wenxuan Guo
Keyword(s):  
Spatial Variability ◽  
Temporal Variability ◽  
Yield Variability ◽  
High Plains ◽  
Spatial And Temporal Variability ◽  
Cotton Yield ◽  
Site Specific ◽  
Growing Seasons ◽  
Specific Management

Understanding spatial and temporal variability patterns of crop yield and their relationship with soil properties can provide decision support to optimize crop management. The objectives of this study were to (1) determine the spatial and temporal variability of cotton (Gossypium hirsutum L.) lint yield over different growing seasons; (2) evaluate the relationship between spatial and temporal yield patterns and apparent soil electrical conductivity (ECa). This study was conducted in eight production fields, six with 50 ha and two with 25 ha, on the Southern High Plains (SHP) from 2000 to 2003. Cotton yield and ECa data were collected using a yield monitor and an ECa mapping system, respectively. The amount and pattern of spatial and temporal yield variability varied with the field. Fields with high variability in ECa exhibited a stronger association between spatial and temporal yield patterns and ECa, indicating that soil properties related to ECa were major factors influencing yield variability. The application of ECa for site-specific management is limited to fields with high spatial variability and with a strong association between yield spatial and temporal patterns and ECa variation patterns. For fields with low variability in yield, spatial and temporal yield patterns might be more influenced by weather or other factors in different growing seasons. Fields with high spatial variability and a clear temporal stability pattern have great potential for long-term site-specific management of crop inputs. For unstable yield, however, long-term management practices are difficult to implement. For these fields with unstable yield patterns, within season site-specific management can be a better choice. Variable rate application of water, plant growth regulators, nitrogen, harvest aids may be implemented based on the spatial variability of crop growth conditions at specific times.

scholarly journals Long-term stability of TES satellite radiance measurements

2011 ◽  
Vol 4 (2) ◽  
pp. 1723-1749
Author(s):  
T. C. Connor ◽  
M. W. Shephard ◽  
V. H. Payne ◽  
K. E. Cady-Pereira ◽  
S. S. Kulawik ◽  
...  
Keyword(s):  
Optical Depth ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Radiometric Calibration ◽  
Cloud Optical Depth ◽  
Brightness Temperatures ◽  
The Difference ◽  
The Stability ◽  
Reference Measurements

Abstract. The utilization of Tropospheric Emission Spectrometer (TES) Level 2 (L2) retrieval products for the purpose of assessing long term changes in atmospheric trace gas composition requires knowledge of the overall radiometric stability of the Level 1B (L1B) radiances. The purpose of this study is to evaluate the stability of the radiometric calibration of the TES instrument by analyzing the difference between measured and calculated brightness temperatures in selected window regions of the spectrum. The Global Modeling and Assimilation Office (GMAO) profiles for temperature and water vapor and the Real-Time Global Sea Surface Temperature (RTGSST) are used as input to the Optimal Spectral Sampling (OSS) radiative transfer model to calculate the simulated spectra. The TES reference measurements selected cover a 4-year period of time from mid 2005 through mid 2009 with the selection criteria being; observation latitudes greater than −30° and less than 30°, over ocean, Global Survey mode (nadir view) and retrieved cloud optical depth of less than 0.01. The TES cloud optical depth retrievals are used only for screening purposes and no effects of clouds on the radiances are included in the forward model. This initial screening results in over 55 000 potential reference spectra spanning the four year period. Presented is a trend analysis of the time series of the residuals (observation minus calculations) in the TES 2B1, 1B2, 2A1, and 1A1 bands which demonstrates that the trend in the residuals is not significantly different from zero over the 4-year period. This is one method used to demonstrate that the relative radiometric calibration is stable over time, which is very important for any longer term analysis of TES retrieved products (L2) particularly well-mixed species such as carbon dioxide and methane.

scholarly journals Ozone formation under low solar radiation in eastern China

2019 ◽  
Author(s):  
Xuexi Tie ◽  
Xin Long ◽  
Guohui Li ◽  
Shuyu Zhao ◽  
Jianming Xu
Keyword(s):  
Solar Radiation ◽  
Eastern China ◽  
Threshold Level ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Oh Radicals ◽  
Chemical Production ◽  
The Past ◽  
Photochemical Production ◽  
Steady State Model

Abstract. PM2.5, a particulate matter with a diameter of 2.5 micrometers or less, is one of the major components of the air pollution in eastern China. In the past few years, China's government made strong efforts to reduce the PM2.5 pollutions. However, another important pollutant (ozone) becomes an important problem in eastern China. Ozone (O3) is produced by photochemistry, which requires solar radiation for the formation of O3. Under heavy PM2.5 pollution, the solar radiation is often depressed, and the photochemical production of O3 is prohibited. This study shows that during fall in eastern China, under heavy PM2.5 pollutions, there were often strong O3 photochemical productions, causing a co-occurrence of high PM2.5 and O3 concentrations. This co-occurrence of high PM2.5 and O3 is un-usual and is the main focus of this study. Recent measurements show that there were often high HONO surface concentrations in major Chinese mega cities, especially during daytime, with maximum concentrations ranging from 0.5 to 2 ppbv. It is also interesting to note that the high HONO concentrations were occurred during high aerosol concentration periods, suggesting that there were additional HONO surface sources in eastern China. Under the high daytime HONO concentrations, HONO can be photo-dissociated to be OH radicals, which enhance the photochemical production of O3. In order to study the above scientific issues, a radiative transfer model (TUV; Tropospheric Ultraviolet-Visible) is used in this study, and a chemical steady state model is established to calculate OH radical concentrations. The calculations show that by including the OH production of the photo-dissociated of HONO, the calculated OH concentrations are significantly higher than the values without including this production. For example, by including HONO production, the maximum of OH concentration under the high aerosol condition (AOD = 2.5) is similar to the value under low aerosol condition (AOD = 0.25) in the no-HONO case. This result suggests that even under the high aerosol condition, the chemical oxidizing process for O3 production can occurred, which explain the co-occurrence of high PM2.5 and high O3 in fall season in eastern China. However, the O3 concentrations were not significantly affected by the appearance of HONO in winter. This study shows that the seasonal variation of solar radiation plays important roles for controlling the OH production in winter. When the solar radiation is in a very low level in winter, it reaches the threshold level to prevent the OH chemical production, even by including the HONO production of OH. This study provides some important scientific highlights to better understand the O3 pollutions in eastern China.

scholarly journals Thunderstorms and thunderstorm precipitations in southern Poland

2014 ◽  
Vol 2 (3) ◽  
pp. 33-46
Author(s):  
Zuzanna Bielec-Bąkowska
Keyword(s):  
Temporal Variability ◽  
Daily Precipitation ◽  
Overwhelming Majority ◽  
Spatial And Temporal Variability ◽  
Southern Poland ◽  
Clear Cut ◽  
Term Change ◽  
Atmospheric Fronts ◽  
Precipitation Events

AbstractThis paper addresses spatial and temporal variability in the occurrence of thunderstorms and related precipitation in southern Poland between 1951 and 2010. The analysis was based on thunderstorm observations and daily precipitation totals (broken down into the few ranges) from 15 meteorological stations. It was found that precipitation accompanied an overwhelming majority of thunderstorms. The most frequent range of thunderstorm precipitation totals was 0.1–10.0 mm which accounted for 60% of all values while precipitation higher than 20.0 mm accounted only for ca. 8%. During the study period, long-term change in the number of days with thunderstorm precipitation within a certain range displayed no clear-cut trends. Exceptions included: 1) an increase in the number of days with thunderstorm precipitation in the lowest range of totals (0.1–10.0 mm) at Katowice, Tarnów, Rzeszów and Lesko and decrease at Mt. Kasprowy Wierch, 2) an increase in the range 10.1–20.0 mm at Zakopane and 20.1–30.0 mm at Opole, 3) a decrease of the top range (more than 30.0 mm) at Mt. Śnieżka. It was found that the heaviest thunderstorm precipitation events, i.e. totalling more than 30 mm, and those events that covered all or most of the study area, occurred at the time of air advection from the southern or eastern sectors and a passage of atmospheric fronts.

Polar  Stratospheric Clouds detection at Belgrano II Antarctic station from DOAS measurements

2021 ◽  
Author(s):  
Laura Gómez Martín ◽  
Daniel Toledo ◽  
Margarita Yela ◽  
Cristina Prados-Román ◽  
José Antonio Adame ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Color Index ◽  
Radiative Transfer Model ◽  
Optical Absorption Spectroscopy ◽  
Transfer Model ◽  
Meteorological Model ◽  
Weather Forecasts ◽  
Stratospheric Temperature ◽  
Stratospheric Clouds

<p><span>Ground-based zenith DOAS (Differential Optical Absorption Spectroscopy) measurements have been used to detect and estimate the altitude of PSCs over Belgrano II Antarctic station during the polar sunrise seasons of 2018 and 2019. The method used in this work studies the evolution of the color index (CI) during twilights. The CI has been defined here as the ratio of the recorded signal at 520 and 420 nm. In the presence of PSCs, the CI shows a maximum at a given solar zenith angle (SZA). The value of such SZA depends on the altitude of the PSC. By using a spherical Monte Carlo radiative transfer model (RTM), the method has been validated and a function relating the SZA of the CI maximum and the PSC altitude has been calculated. Model simulations also show that PSCs can be detected and their altitude can be estimated even in presence of optically thin tropospheric clouds or aerosols. Our results are in good agreement with the stratospheric temperature evolution obtained through the ERA5 data reanalysis from the global meteorological model ECMWF (European Centre for Medium Range Weather Forecasts) and the PSCs observations from CALIPSO (Cloud-Aerosol-Lidar and Infrared Pathfinder Satellite Observations).</span></p><p><span>The methodology used in this work could also be applied to foreseen and/or historical measurements obtained with ground-based spectrometers such e. g. the DOAS instruments dedicated to trace gas observation in Arctic and Antarctic sites. This would also allow to investigate the presence and long-term evolution of PSCs.</span></p><p><span><strong>Keywords: </strong>Polar stratospheric clouds; color index; radiative transfer model; visible spectroscopy.</span></p>

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