Cloud Index Research Articles

A new statistical approach for deriving global solar radiation from satellite images

Solar radiation derived from geostationary satellite images has become an advantageous technique for solar resource characterisation over large areas. The simplest methods for estimate solar radiation from the satellite information rely on straight forward relationships between a normalised parameter of the solar irradiance (such as clearness or clear sky index) and the cloud index. This paper presents a statistical fit of this relationship (fitted and tested using data from 28 Spanish radiometric station) different from the approach used by Heliosat-2 method (Rigollier, C., Lefèvre, M., Wald, L., 2004. The method Heliosat-2 for deriving shortwave solar radiation from satellite images. Solar Energy 77, 159–169), that includes local statistical measures of the cloud index distribution and the air mass. In particular, the inclusion of the local cloud index percentiles (median, first and third quartile) estimated from the whole series on each pixel improves clearly the model response, and is a way to account for the local climatological aspects of any location. The inclusion of the new explicative variables yield to practically unbiased results and the relative RMSE decrease to about 17% from the 21% result of the expression applied in the Heliosat-2 model.

Daily NDVI Relationship to Cloud Cover

Abstract A normalized difference vegetation index (NDVI) cloud index (NCI) was derived from Pathfinder Advanced Very High Resolution Radiometer (AVHRR) daily NDVI data and compared with observed cloud amounts and a sunshine duration–cloud index (SCI) over an area of diverse land cover. Ground observations from 120 meteorological stations were significantly related to the daily NCI and the SCI, with R2 values of 0.41 and 0.50, respectively. The daily NCI and interpolated cloud indices derived from ground observations over the 776 900 km2 study area were compared. The correlation coefficient between the NCI and the observed cloud amount was less than 0.6 for less than 20% of the area. The correlation coefficient between the NCI and the observed sunshine duration index was less than 0.6 for less than 10% of the area and less than 0.7 for 41% of the area. There were strong correlations for high elevations in summer, and correlations for low elevations in winter were weaker. A frozen soil surface or snow cover degrades the NDVI relationship to clouds. The NCI and observed cloud indices had high correlation coefficients in areas with diverse land uses, suggesting that the NCI may be useful in estimating cloudiness over a large region.

Retrieval of stratospheric ozone profiles from MIPAS/ENVISAT limb emission spectra: a sensitivity study

Abstract. We report on the dependence of ozone volume mixing ratio profiles, retrieved from limb emission infrared spectra of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), on different retrieval setups such as the treatment of the background continuum, cloud filtering, spectral regions used for analysis and a series of further more technical parameter choices. The purpose of this investigation is to better understand the error sources of the ozone retrieval, to optimize the current retrieval setup and to document changes in the data versions. It was shown that the cloud clearing technique used so far (cloud index 1.8) does not reliably exclude all cloud-contaminated spectra from analysis. Through analysis of spectra calculated for cloudy atmospheres we found that the cloud index should be increased to a value of 3.0 or higher. Further, it was found that assignment of a common background continuum to adjacent microwindows within 5 cm−1 is advantageous, because it sufficiently represents the continuum emission by aerosols, clouds and gases as reported in the literature, and is computationally more efficient. For ozone retrieval we use ozone lines from MIPAS band A (685–970 cm−1) and band AB (1020–1170 cm−1) as well. Therefore we checked ozone retrievals with lines from bands A or AB only for a systematic difference. Such a difference was indeed found and could, to a major part, be attributed to the spectroscopic data used in these two bands, and to a minor part to neglection of modelling of non-local thermodynamic (non-LTE) emissions. Another potential explanation, a bias in the radiance calibration of level-1B spectra of bands A and AB, could largely be ruled out by correlation analysis and inspection of broadband spectra. Further upgrades in the ozone retrieval consist of application of an all-zero a-priori profile and a weaker regularization. Finally, the ozone distribution obtained with the new retrieval setup (data versions V3o_O3_7) was compared to the data version used before (V2_O3_2). Differences are smaller than ±0.4 ppmv in the altitude region 15–50 km. Further, differences to ozone measured by the HALogen Occultation Experiment (HALOE) on the Upper Atmospheric Research Satellite (UARS) are partly reduced with the new MIPAS data version.

A modified algorithm for calculating the cloud index

The cloud index is an important component of the Heliosat algorithm, which estimates solar radiation components from Meteosat High Resolution Visible images. The cloud index quantifies the reflective properties of the atmosphere, and varies from 0 at clear conditions to 1 at overcast. The algorithm is semi-empirical in the way that it includes several constants that need to be tuned. Some of these were removed in the Heliosat-II algorithm where the Meteosat calibration constant was introduced to replace the “pseudo-reflectivity” with a “real reflectivity”. This approach is followed here, and two additional changes are made: (1) An analytical expression is introduced to correct for backscattered radiation from air molecules. (2) A correction is made for non-lambertian reflectivity, removing the time consuming need for determining the ground reflectivity for each month and each slot. The new cloud index is used to calculate global irradiances which are validated against hourly measurements from five European ground stations. The average root mean square deviation is 15.5% for a six-month spring/summer period, of comparable accuracy as using the more time consuming traditional algorithm used in the EU project Satel-Light.

06/00198 Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index: Zarzalejo, L. F. et al. Energy, 2005, 30, (9), 1685–1697

06/00198 Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index: Zarzalejo, L. F. et al. Energy, 2005, 30, (9), 1685–1697

Polar stratospheric cloud observations by MIPAS on ENVISAT: detection method, validation and analysis of the northern hemisphere winter 2002/2003

Abstract. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on ENVISAT has made extensive measurements of polar stratospheric clouds (PSCs) in the northern hemisphere winter 2002/2003. A PSC detection method based on a ratio of radiances (the cloud index) has been implemented for MIPAS and is validated in this study with respect to ground-based lidar and space borne occultation measurements. A very good correspondence in PSC sighting and cloud altitude between MIPAS detections and those of other instruments is found for cloud index values of less than four. Comparisons with data from the Stratospheric Aerosol and Gas Experiment (SAGE) III are used to further show that the sensitivity of the MIPAS detection method for this threshold value of cloud index is approximately equivalent to an extinction limit of 10-3km-1 at 1022nm, a wavelength used by solar occultation experiments. The MIPAS cloud index data are subsequently used to examine, for the first time with any technique, the evolution of PSCs throughout the Arctic polar vortex up to a latitude close to 90° north on a near-daily basis. We find that the winter of 2002/2003 is characterised by three phases of very different PSC activity. First, an unusual, extremely cold phase in the first three weeks of December resulted in high PSC occurrence rates. This was followed by a second phase of only moderate PSC activity from 5-13 January, separated from the first phase by a minor warming event. Finally there was a third phase from February to the end of March where only sporadic and mostly weak PSC events took place. The composition of PSCs during the winter period has also been examined, exploiting in particular an infra-red spectral signature which is probably characteristic of NAT. The MIPAS observations show the presence of these particles on a number of occasions in December but very rarely in January. The PSC type differentiation from MIPAS indicates that future comparisons of PSC observations with microphysical and denitrification models might be revealing about aspects of solid particle existence and location.

Towards cloud detection and cloud frequency distributions from MIPAS infra-red observations

Historically, clouds have been observed principally using nadir sounding but more recently, limb sounding observations have begun to reveal details of clouds in the upper troposphere, mainly sub-visible cirrus, and in the polar lower stratosphere. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), launched on ENVISAT in March 2002, provides an unprecedented opportunity to examine the infra-red emission spectra of clouds at high spectral resolution (0.025 cm −1 unapodised) and vertical resolutions of 3 km. In this paper, we examine the efficiency of a cloud index which is used operationally to detect clouds in MIPAS data and show that water vapour, the chief gaseous influence on the cloud index, does not affect the detection at altitudes of 12 km and above. We show further that it is possible to map the cloud index to an effective cloud extinction coefficient provided that either water vapour concentrations are known or else: (i) at 18 km and above in the tropics; (ii) at 15 km and above in mid-latitudes; (iii) between 15 and 27 km in polar winter. We apply a conservative cloud detection limit of 2.2 to available MIPAS level 1b off-line data (calibrated emission spectra) versions 4.61 and 4.62, to derive seasonal cloud frequency distributions. For altitudes between 12 and 30 km, higher cloud frequencies are found in the tropics and in the region of the Antarctic ozone hole, whilst relatively low cloud frequencies are observed over mid-latitudes and in the Arctic stratospheric vortex of 2002–2003.

NDVI from low altitude aircraft and composited NOAA AVHRR data for scaling Arctic ecosystem fluxes

The relationship between normalized difference vegetation index (NDVI) patterns obtained from high spatial resolution aircraft and low spatial resolution satellite data (Advanced Very High Resolution Radiometer (AVHRR)) was investigated with the intent of using multilevel data to scale carbon flux models in Arctic tundra ecosystems. Despite variable illumination conditions during the aircraft missions and maximum value compositing of the AVHRR data, the difference between 3 km average aircraft and AVHRR NDVI values was generally constant along each flight transect. However, the magnitude of the offset differed between flight dates and small lakes had a greater effect on area averaged aircraft NDVI values than on the satellite values. A cloud index was calculated using incident solar radiation measured by the aircraft and this index was used to identify periods when the aircraft NDVI values may have been biased by cloud cover. Removal of NDVI values based on a cloud index threshold did not appear to be justified given the marginal improvement in the relationship between the two NDVI datasets. If the systematic difference between AVHRR and aircraft NDVI values can be determined, then the scaling of carbon flux models based on the NDVI should be a viable approach in Arctic ecosystems.

Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models.

Producing satellite-derived irradiances in complex arid terrain

This paper describes a methodology to correct satellite-derived irradiances over complex terrain for models that use the visible satellite channel as main input for cloud index determination. Complex terrain is characterized by high reflectance surface and or the juxtaposition of high and low reflectance surfaces (e.g., desert plains and forested ridges). The correction consists of (1) climate dependent post-model clear sky calibration and (2) singularity identification and removal.

Operational method for deriving high resolution direct normal irradiance from satellite data

Ground-based measurements of solar beam irradiance are expensive and rarely available especially in the sunbelt countries, the favourable regions for concentrating solar energy techniques. A method based on satellite data is presented that calculates hourly solar direct normal irradiance for large regions and for many years with high spatial resolution independently from ground measurements. The attenuation of solar irradiance due to scattering and absorption in the cloud-free atmosphere is calculated by a clear-sky broadband parameterisation model. It uses ozone optical depth from the Total Ozone Mapping Spectrometer, aerosol optical depth from the Global Aerosol Climatology Project and water vapour from the reanalysis of the National Centers for Environmental Prediction. Attenuation due to clouds is taken into account by a cloud index that is derived from the infrared and the visible channel of the geostationary Meteosat weather satellites. As clouds have the strongest impact on beam irradiance at ground, the resolution of the cloud parameterisation dominates the overall spatial and temporal resolution. The presented algorithm provides hourly data of direct normal irradiance related to the nominal 5 × 5 km 2 resolution of Meteosat.

On The Relationship between the QBO and Tropical Deep Convection

Abstract The height and amount of tropical deep convection are examined for a correlation with the stratospheric quasi-biennial oscillation (QBO). A new 23-yr record of outgoing longwave radiation (OLR) and a corrected 17-yr record of the highly reflective cloud (HRC) index are used as measures of convection. When binned by phase of the QBO, zonal means and maps of OLR and HRC carry a QBO signal. The spatial patterns of the maps highlight the QBO signal of OLR and HRC in typically convective regions. Spectral analysis of zonal mean OLR and HRC near the equator reveals significant peaks at QBO frequencies. Rotated empirical orthogonal function (REOF) analysis is used to determine if ENSO variations of convection are aliased into the observed QBO signals. Some analyses are repeated using the OLR record after ENSO REOF modes have been removed, yielding very similar results compared to the original analyses. It appears that the QBO signal is distinct from the ENSO signal, although the relative brevity of the ...

A model for calculating global illuminance from satellite data

A model for calculating global illuminance on horizontal surfaces from meteorological satellite data was developed. The data used for developing the model are global illuminance measured at four solar monitoring stations situated in different parts of Thailand and 8-bit digital data from visible channel of GMS-5 satellite covering the whole country for the period of 1–2 years. Values of normalized global illuminance defined as a ratio of global illuminance to clear sky global illuminance were calculated. These values were used to correlate with those of cloud index derived from the satellite data. From the correlation, a model relating the normalized global illuminance to cloud index was established. The performance of this model was investigated using an independent illuminance data set. It was found that the global illuminance calculated from the model agreed well with that obtained from the measurement, with a root mean square difference of 5.38 klux or 7.0% of the mean values.

Solar Radiation Mapping from NOAA AVHRR Data in Catalonia, Spain

Abstract A statistical model is presented for the determination of hourly global solar radiation from the National Oceanic and Atmospheric Administration advanced very high resolution radiometer (NOAA AVHRR) satellite data, which provide wide coverage together with adequate spatial resolution (around 1.1 km at the nadir). The process is divided into three steps. The first step consists of a cloud detection procedure. The second step determines the cloud index for each point on the satellite image, which is then used for the third step, which is the application of the global solar radiation statistical model. The coefficients for the model are determined by regression from the data obtained from 11 global surface solar radiation measurement stations (pyranometers). Once the coefficients have been determined, a surface interpolation is performed to obtain the entire coefficient field for the area under study, with the objective of applying the model. The estimates obtained from the model were compared with ...

Automated, high temporal resolution, thermal analysis of Kilauea volcano, Hawai'i, using GOES satellite data

Thermal data are directly available from the Geostationary Operational Environmental Satellites (GOES) every 15 minutes at existing or inexpensively installed receiving stations. This data stream is ideal for monitoring high temperature features such as active lava flows and fires. To provide a near-real-time hot spot monitoring tool, we have developed, tested and installed software to analyse GOES data on-reception and then make results available in a timely fashion via the web. Our software automatically: (1) produces hot spot images and movies; (2) uses a thresholding procedure to generate a hot spot map; (3) updates hot spot radiance and cloud index time series; and (4) issues a threshold-based e-mail alert. Results are added to http://volcano1.pgd.hawaii.edu/goes/ within ∼12 minutes of image acquisition and are updated every 15 minutes. Analysis of GOES data acquired for effusive activity at Kilauea volcano (Hawai'i) during 1997-98 show that short (<1 hour long) events producing 100m long (102 to 103 m2) lava flows are detectable. This means that time constraints can be placed on sudden, rapidly evolving efflusive events with an accuracy of 7.5 minutes. Changes in activity style and extent can also be documented using hot spot size, intensity and shape. From radiance time series we distinguish (1) tube-fed activity (low radiance, <10 MW m2 m-1); (2) activity pauses (no radiance); (3) lava lake activity (low radiance, <5 MW m2 m-1); (4) short (<3 km long) flow extension (moderate radiance, 10-20 MW m2 m 1 ); and (5) 12 km long flow extension (high radiance, 15-30 MW m2 m-1). The ability of GOES to detect short-lived effusive events, coupled with the speed with which GOES-based hot spot information can be processed and disseminated, means that GOES offers a valuable additional volcano monitoring tool.

Assessment of solar electricity potentials in North Africa based on satellite data and a geographic information system

Solar thermal power plants will provide a major share of the renewable energy sources needed in the future. STEPS, an evaluation system for solar thermal power stations, was designed to calculate the performance of such power stations as a function of direct solar radiation, geographical conditions (land slope, land cover, distance from cooling water resources, etc.), infrastructure (pipelines, electricity grids, streets etc.) and the configuration and performance of a selected solar thermal power plant concept. A cloud index derived from METEOSAT satellite images is used to calculate the direct solar radiation resource. A geographic information system (GIS) is used to process all the parameters for site assessment. In order to demonstrate the concept, an analysis of Northern Africa was performed with STEPS providing a ranking of sites with respect to the potential and cost of solar thermal electricity for a particular power plant configuration. Results were obtained with high spatial and temporal resolution.

Cloud‐vegetation interaction: Use of normalized difference cloud index for estimation of cloud optical thickness

A new technique to retrieve cloud optical depth for broken clouds above green vegetation using ground‐based zenith radiance measurements is developed. By analogy with the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Cloud Index (NDCI) is defined as a ratio between the difference and the sum of two zenith radiances measured for two narrow spectral bands in the visible and near‐IR regions. The very different spectral behavior of cloud liquid water drops and green vegetation is the key physics behind the NDCI. It provides extra tools to remove the radiative effects of the 3D cloud structure. Numerical calculations based on fractal clouds and real measurements of NDCI and cloud liquid water path confirm the improvements.

Derivation of Cloud Index from Geostationary Satellites and Application to the Production of Solar Irradiance and Daylight Illuminance Data

We investigate in the present paper the relationship between satellite count, global irradiance and other solar and illumination resource components, bringing a particular attention to low solar elevation situations (below 20 °) which are very important in northern latitudes. Our investigation is based on data from two geostationary satellites, METEOSAT and GOES, backed by ground measurements in Switzerland and the northeastern USA. The study of different clear sky normalizations lead to the conclusion that a linear correlation between the global clearness index and the irradiance (like the heliosat method) would be inaccurate for low solar elevations, and therefore for high latitude regions. We developed a model that directly relates an elevation dependent clearness index to the could index. This methodology presents a definite advantage because it can be generalized to address the clearness index of other solar radiation components, besides global irradiance, such as direct irradiance, diffuse illuminance, etc. The correlations described in this paper were developed on the data from Geneva (in the frame of the EC program “Satellight”) and evaluated on two other independent data sets (Albany, USA and Lausanne, Switzerland). Their precisions, on a hourly basis, are respectively 30%, 40% and 60% for the global, diffuse and beam components) (90,55 and 95 W/m2). The use of independent data for thederivation and the validation of the models shows thatthose can be used in a wide range of locations, even if the applicability has to be assessed for very different climates.

Ionospheric potential as a proxy index for global temperature

Since the global circuit is maintained by currents from thunderstorms and electrified clouds, which are controlled by temperature, we are investigating the use of ionospheric potential ( V I) as a measure of the variation of global temperature. We report positive correlation between V I and global temperature obtained from three different data sets. V I is also positively correlated with an inferred global lightning/deep cloud index which is positively correlated with global temperature. Thus, there is a consistent picture of warmer temperatures leading to more deep convection and higher V I. Since a series of single V I soundings at any appropriate location may provide a globally representative measure of temperature variation in real time, it is suggested that routine monitoring of this parameter could provide considerable cost and operational advantages compared to current methodology involving observations at thousands of ground stations and satellite radiation measurements.

Cloud Color and Ocean Radiant Heating

It is well recognized that clouds regulate the flux of solar radiation reaching the sea surface. Clouds also affect the spectral distribution of incident irradiance. Observations of spectral and total incident solar irradiance made from the western equatorial Pacific Ocean are used to investigate the ‘‘color’’ of clouds and to evaluate its role in upper-ocean radiant heating. Under a cloudy sky, values of the near-ultraviolet to green spectral irradiance are a significantly larger fraction of their clear-sky flux than are corresponding clear-sky fractions calculated for the total solar flux. For example, when the total solar flux is reduced by clouds to one-half of that for a clear sky, the near-ultraviolet spectral flux is only reduced ;35% from its clear-sky value. An empirical parameterization of the spectral cloud index is developed from field observations and is verified using a planeparallel, cloudy-sky radiative transfer model. The implications of cloud color on the determination of ocean radiant heating rates and solar radiation transmission are assessed using both model results and field determinations. The radiant heating rate of the upper 10 cm of the ocean (normalized to the climatological incident solar flux) may be reduced by a factor of 2 in the presence of clouds. This occurs because the near-infrared wavelengths of solar radiation, which are preferentially attenuated by clouds, are absorbed within the upper 10 cm or so of the ocean while the near-ultraviolet and blue spectral bands propagate farther within the water column. The transmission of the solar radiative flux to depth is found to increase under a cloudy sky. The results of this study strongly indicate that clouds must be included in the specification of ocean radiant heating rates for air‐sea interaction studies.