scholarly journals Subpixel Characterization of HIRS Spectral Radiances Using Cloud Properties from AVHRR

2016 ◽  
Vol 33 (7) ◽  
pp. 1519-1538 ◽  
Author(s):  
Paul W. Staten ◽  
Brian H. Kahn ◽  
Mathias M. Schreier ◽  
Andrew K. Heidinger
Keyword(s):  
High Resolution ◽  
Global Scale ◽  
Small Scale ◽  
Spectral Brightness ◽  
Cloud Type ◽  
Brightness Temperatures ◽  
Cloud Properties ◽  
Ocean Region ◽  
Intersatellite Calibration

AbstractThis paper describes a cloud type radiance record derived from NOAA polar-orbiting weather satellites using cloud properties retrieved from the Advanced Very High Resolution Radiometer (AVHRR) and spectral brightness temperatures (Tb) observed by the High Resolution Infrared Radiation Sounder (HIRS). The authors seek to produce a seamless, global-scale, long-term record of cloud type and Tb statistics intended to better characterize clouds from seasonal to decadal time scales. Herein, the methodology is described in which the cloud type statistics retrieved from AVHRR are interpolated onto each HIRS footprint using two cloud classification methods. This approach is tested over the northeast tropical and subtropical Pacific Ocean region, which contains a wide variety of cloud types during a significant ENSO variation from 2008 to 2009. It is shown that the Tb histograms sorted by cloud type are realistic for all HIRS channels. The magnitude of Tb biases among spatially coincident satellite intersections over the northeast Pacific is a function of cloud type and wavelength. While the sign of the bias can change, the magnitudes are generally small for NOAA-18 and NOAA-19, and NOAA-19 and MetOp-A intersections. The authors further show that the differences between calculated standard deviations of cloud-typed Tb well exceed intersatellite calibration uncertainties. The authors argue that consideration of higher-order statistical moments determined from spectral infrared observations may serve as a useful long-term measure of small-scale spatial changes, in particular cloud types over the HIRS–AVHRR observing record.

PATMOS-x v6.0: Improvements to AVHRR Cloud Climate Record and Analysis of the Updated Data

2020 ◽  
Author(s):  
Coda Phillips ◽  
Michael Foster ◽  
Andrew Heidinger
Keyword(s):  
High Resolution ◽  
Detection Accuracy ◽  
Cloud Detection ◽  
Edge Preserving ◽  
Brightness Temperatures ◽  
Cloud Properties ◽  
Satellite Sensors ◽  
The Difference ◽  
Climate Analysis ◽  
Spectral Channels

<p>Since 1978, an Advanced Very-High-Resolution Radiometer (AVHRR) has flown onboard 17 polar-orbiting satellites. Together, they are the longest global record from a homogeneous set of satellite sensors. The Pathfinder Atmosphere’s Extended (PATMOS-x) dataset is a long-term cloud record derived from the AVHRR radiances, and suitable for climate analysis. It has demonstrated intersensor stability and has been rigorously compared with other cloud datasets.</p><p>However, the AVHRR alone has only limited spectral information, so cloud detection during nighttime or over ice is challenging. Therefore, performance degrades over regions with extreme diurnal patterns or low temperatures such as the poles, despite our interest.</p><p>The next production version of PATMOS-x will include numerous algorithmic changes as well as the use of High-resolution Infrared Radiation Sounder (HIRS) spectral channels to improve detection accuracy in previously difficult conditions. The low-resolution HIRS soundings are upsampled to match the AVHRR pixels through an edge-preserving process called “fusion”. The higher-resolution AVHRR imagery guides the upsampling and the resulting combination is spectrally consistent with the AVHRR and has a high spatial resolution.</p><p>For cloud detection, the difference between the AVHRR and HIRS 11μm and HIRS 6.7μm brightness temperatures has been added as a feature in the naive Bayesian cloud detector. The effect on cloud precision is seen especially in the Antarctic where false-positive cloud detections have decreased dramatically.</p><p>Other cloud properties can be improved with the new spectral channels. For example, the new cloud phase algorithm uses the HIRS 6.7μm to determine cloud phase and the AVHRR and HIRS 11μm-13.3μm beta ratio identifies overlapping clouds. Also, the 11μm, 12μm, and HIRS 13.3μm are used in the new cloud height algorithm.</p><p>We report on the development of this new version of the PATMOS-x cloud climate dataset, and the methods used to calibrate and homogenize the participating sensors. Finally, observed trends in the improved dataset will be examined and related to the old dataset. In particular, attention will be given to whether high-latitude analysis of climatic trends is finally possible on the new dataset.</p>

A new method of PWV retrieval over land with remote sensing data: a case of AMSR2

2020 ◽  
Author(s):  
Nan Jiang ◽  
Yan Xu ◽  
Tianhe Xu
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Global Climate ◽  
Weather Prediction ◽  
Remote Sensing Data ◽  
Precipitable Water ◽  
Global Scale ◽  
Brightness Temperatures ◽  
Climate Studies

<p>Precipitable water vapor (PWV) is an important parameter reflecting the amount of solid water in the atmosphere, which is widely utilized in the studies of numerical weather prediction (NWP) and climate change. The microwave radiance measurements made by the space-based remote sensing satellites give us the opportunity to make the climate studies on a global scale. So far, PWV retrieval over the ocean has a long data record and the technology is very mature, but in the case of PWV retrieval over land, it is more challenging to isolate the atmospheric signals from the varied surface signals. In this study, we will apply a new retrieval method over land based on the dual-polarized difference (vertical and horizontal) at 19 GHz and 23 GHz using the brightness temperatures from the Global Change Observation Mission-Water (GCOM-W)/Advanced Microwave Scanning Radiometer 2 (AMSR2). We found polarization difference in brightness temperatures has an exponential relation on the amount of PWV. The validation results of the PWV retrieval from the ground-based GNSS stations show that the proposed method has a mean accuracy of 3.9 mm. Thus, the proposed method can give a possibility to improve the accuracy of data assimilation in the NWP applications and is useful for the studies of global climate change with the long-term data records.</p>

scholarly journals Long-Term and High-Resolution Global Time Series of Brightness Temperature from Copula-Based Fusion of SMAP Enhanced and SMOS Data

2018 ◽  
Vol 10 (11) ◽  
pp. 1842 ◽  
Author(s):  
Christof Lorenz ◽  
Carsten Montzka ◽  
Thomas Jagdhuber ◽  
Patrick Laux ◽  
Harald Kunstmann
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
High Resolution ◽  
Brightness Temperature ◽  
Spatial Resolution ◽  
Prediction Models ◽  
Weather Prediction ◽  
Brightness Temperatures ◽  
Climate Analysis

Long and consistent soil moisture time series at adequate spatial resolution are key to foster the application of soil moisture observations and remotely-sensed products in climate and numerical weather prediction models. The two L-band soil moisture satellite missions SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture and Ocean Salinity) are able to provide soil moisture estimates on global scales and in kilometer accuracy. However, the SMOS data record has an appropriate length of 7.5 years since late 2009, but with a coarse resolution of ∼25 km only. In contrast, a spatially-enhanced SMAP product is available at a higher resolution of 9 km, but for a shorter time period (since March 2015 only). Being the fundamental observable from passive microwave sensors, reliable brightness temperatures (Tbs) are a mandatory precondition for satellite-based soil moisture products. We therefore develop, evaluate and apply a copula-based data fusion approach for combining SMAP Enhanced (SMAP_E) and SMOS brightness Temperature (Tb) data. The approach exploits both linear and non-linear dependencies between the two satellite-based Tb products and allows one to generate conditional SMAP_E-like random samples during the pre-SMAP period. Our resulting global Copula-combined SMOS-SMAP_E (CoSMOP) Tbs are statistically consistent with SMAP_E brightness temperatures, have a spatial resolution of 9 km and cover the period from 2010 to 2018. A comparison with Service Soil Climate Analysis Network (SCAN)-sites over the Contiguous United States (CONUS) domain shows that the approach successfully reduces the average RMSE of the original SMOS data by 15%. At certain locations, improvements of 40% and more can be observed. Moreover, the median NSE can be enhanced from zero to almost 0.5. Hence, CoSMOP, which will be made freely available to the public, provides a first step towards a global, long-term, high-resolution and multi-sensor brightness temperature product, and thereby, also soil moisture.

scholarly journals Modelling of the urban concentrations of PM<sub>2.5</sub> on a high resolution for a period of 35 years, for the assessment of lifetime exposure and health effects

2018 ◽  
Author(s):  
Jaakko Kukkonen ◽  
Leena Kangas ◽  
Mari Kauhaniemi ◽  
Mikhail Sofiev ◽  
Mia Aarnio ◽  
...  
Keyword(s):  
High Resolution ◽  
Health Effects ◽  
Dispersion Model ◽  
Fine Particulate Matter ◽  
Health Impact ◽  
Atmospheric Composition ◽  
Local Source ◽  
Small Scale ◽  
Regional Background

Abstract. Reliable and self-consistent data on air quality is needed for an extensive period of time for conducting long-term, or even lifetime health impact assessments. We have modelled the urban scale concentrations of fine particulate matter (PM2.5) in the Helsinki Metropolitan Area for a period of 35 years, from 1980 to 2014. These high resolution computations included both the emissions originated from vehicular traffic (separately exhaust and suspension emissions) and those from small-scale combustion, and were conducted using the road network dispersion model CAR-FMI and the multiple source Gaussian dispersion model UDM-FMI. The regional background concentrations were evaluated based on reanalyses of the atmospheric composition on global and European scales, using the SILAM model. The modelled concentrations of PM2.5 agreed fairly well or well with the measured data at a regional background station and at four urban measurement stations, during 1999–2014. There was no systematic deterioration of the agreement of predictions and data for earlier years (the 1980's and 1990's), compared with the results for more recent years (2000's and early 2010's). The local vehicular emissions were about five-folds higher in the 1980's, compared with the emissions during the latest considered years. However, the local small-scale combustion emissions increased slightly over time. The highest urban concentrations of PM2.5 occurred in the 1980's; these have since decreased to about to a half of the highest values. However, there is only a very slight decreasing trend of the PM2.5 concentrations during the last decade. Regional background is the largest contribution in this area. Vehicular exhaust has been the most important local source, but the relative shares of both small-scale combustion and vehicular suspension emissions have increased. The study provides long-term, high-resolution concentration databases on regional and urban scales that have been used for the assessment of health effects.

scholarly journals Cloud_cci Advanced Very High Resolution Radiometer post meridiem (AVHRR-PM) dataset version 3: 35-year climatology of global cloud and radiation properties

2020 ◽  
Vol 12 (1) ◽  
pp. 41-60 ◽  
Author(s):  
Martin Stengel ◽  
Stefan Stapelberg ◽  
Oliver Sus ◽  
Stephan Finkensieper ◽  
Benjamin Würzler ◽  
...  
Keyword(s):  
High Resolution ◽  
Radiant Energy ◽  
Energy System ◽  
Global Scale ◽  
Radiative Flux ◽  
Surface Radiation ◽  
Digital Object Identifier ◽  
Cloud Detection ◽  
Cloud Properties ◽  
Very High

Abstract. We present version 3 of the Cloud_cci Advanced Very High Resolution Radiometer post meridiem (AVHRR-PM) dataset, which contains a comprehensive set of cloud and radiative flux properties on a global scale covering the period of 1982 to 2016. The properties were retrieved from AVHRR measurements recorded by the afternoon (post meridiem – PM) satellites of the National Oceanic and Atmospheric Administration (NOAA) Polar Operational Environmental Satellite (POES) missions. The cloud properties in version 3 are of improved quality compared with the precursor dataset version 2, providing better global quality scores for cloud detection, cloud phase and ice water path based on validation results against A-Train sensors. Furthermore, the parameter set was extended by a suite of broadband radiative flux properties. They were calculated by combining the retrieved cloud properties with thermodynamic profiles from reanalysis and surface properties. The flux properties comprise upwelling and downwelling and shortwave and longwave broadband fluxes at the surface (bottom of atmosphere – BOA) and top of atmosphere (TOA). All fluxes were determined at the AVHRR pixel level for all-sky and clear-sky conditions, which will particularly facilitate the assessment of the cloud radiative effect at the BOA and TOA in future studies. Validation of the BOA downwelling fluxes against the Baseline Surface Radiation Network (BSRN) shows a very good agreement. This is supported by comparisons of multi-annual mean maps with NASA's Clouds and the Earth's Radiant Energy System (CERES) products for all fluxes at the BOA and TOA. The Cloud_cci AVHRR-PM version 3 (Cloud_cci AVHRR-PMv3) dataset allows for a large variety of climate applications that build on cloud properties, radiative flux properties and/or the link between them. For the presented Cloud_cci AVHRR-PMv3 dataset a digital object identifier has been issued: https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V003 (Stengel et al., 2019).

scholarly journals Modelling of the urban concentrations of PM<sub>2.5</sub> on a high resolution for a period of 35 years, for the assessment of lifetime exposure and health effects

2018 ◽  
Vol 18 (11) ◽  
pp. 8041-8064 ◽  
Author(s):  
Jaakko Kukkonen ◽  
Leena Kangas ◽  
Mari Kauhaniemi ◽  
Mikhail Sofiev ◽  
Mia Aarnio ◽  
...  
Keyword(s):  
High Resolution ◽  
Health Effects ◽  
Dispersion Model ◽  
Fine Particulate Matter ◽  
Health Impact ◽  
Atmospheric Composition ◽  
Local Source ◽  
Small Scale ◽  
Regional Background

Abstract. Reliable and self-consistent data on air quality are needed for an extensive period of time for conducting long-term, or even lifetime health impact assessments. We have modelled the urban-scale concentrations of fine particulate matter (PM2.5) in the Helsinki Metropolitan Area for a period of 35 years, from 1980 to 2014. The regional background concentrations were evaluated based on reanalyses of the atmospheric composition on global and European scales, using the SILAM model. The high-resolution urban computations included both the emissions originated from vehicular traffic (separately exhaust and suspension emissions) and those from small-scale combustion, and were conducted using the road network dispersion model CAR-FMI and the multiple-source Gaussian dispersion model UDM-FMI. The modelled concentrations of PM2.5 agreed fairly well with the measured data at a regional background station and at four urban measurement stations, during 1999–2014. The modelled concentration trends were also evaluated for earlier years, until 1988, using proxy analyses. There was no systematic deterioration of the agreement of predictions and data for earlier years (the 1980s and 1990s), compared with the results for more recent years (2000s and early 2010s). The local vehicular emissions were about 5 times higher in the 1980s, compared with the emissions during the latest considered years. The local small-scale combustion emissions increased slightly over time. The highest urban concentrations of PM2.5 occurred in the 1980s; these have since decreased to about to a half of the highest values. In general, regional background was the largest contribution in this area. Vehicular exhaust has been the most important local source, but the relative shares of both small-scale combustion and vehicular non-exhaust emissions have increased in time. The study has provided long-term, high-resolution concentration databases on regional and urban scales that can be used for the assessment of health effects associated with air pollution.

scholarly journals Global urban growth between 1870 and 2100 from integrated high resolution mapped data and urban dynamic modeling

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Xuecao Li ◽  
Yuyu Zhou ◽  
Mohamad Hejazi ◽  
Marshall Wise ◽  
Chris Vernon ◽  
...  
Keyword(s):  
High Resolution ◽  
Environmental Impacts ◽  
Urban Growth ◽  
Anthropogenic Activities ◽  
Fold Increase ◽  
Global Scale ◽  
Human Environment ◽  
Urban Dynamics ◽  
Urban Extent

AbstractLong term, global records of urban extent can help evaluate environmental impacts of anthropogenic activities. Remotely sensed observations can provide insights into historical urban dynamics, but only during the satellite era. Here, we develop a 1 km resolution global dataset of annual urban dynamics between 1870 and 2100 using an urban cellular automata model trained on satellite observations of urban extent between 1992 and 2013. Hindcast (1870–1990) and projected (2020–2100) urban dynamics under the five Shared Socioeconomic Pathways (SSPs) were modeled. We find that global urban growth under SSP5, the fossil-fuelled development scenario, was largest with a greater than 40-fold increase in urban extent since 1870. The high resolution dataset captures grid level urban sprawl over 200 years, which can provide insights into the urbanization life cycle of cities and help assess long-term environmental impacts of urbanization and human–environment interactions at a global scale.

scholarly journals High Resolution Sequence Stratigraphy of the Natih Formation (Cenomanian/Turonian) in Northern Oman: Distribution of Source Rocks and Reservoir Facies

GeoArabia ◽  
1996 ◽  
Vol 1 (1) ◽  
pp. 65-91
Author(s):  
Frans S.P. van Buchem ◽  
Philippe Razin ◽  
Peter W. Homewood ◽  
Jean M. Philip ◽  
Gregor P. Eberli ◽  
...  
Keyword(s):  
High Resolution ◽  
Arabian Peninsula ◽  
Carbonate Platform ◽  
Hierarchical Organization ◽  
Source Rocks ◽  
Small Scale ◽  
Depositional Sequences ◽  
Accommodation Space ◽  
Facies Associations

ABSTRACT The Cenomanian of the Arabian Peninsula comprises a carbonate platform setting with rudists, characterized by gradual lateral facies changes including the interfingering of carbonate reservoirs (Natih and Mishrif formations) and source rocks. In order to be more predictive with regard to the distribution and the geometrical aspects of the reservoirs and source rocks, a high resolution sequence stratigraphic study has been carried out in the Adam Foothills of Northern Oman. Based on detailed field sections a correlation scheme covering a transect of 100 kilometers (km) has been established. Three orders of stacked depositional sequences have been found based on the reoccurrence of facies. During long-term increase of accommodation the depositional environment was separated in basinal and platform facies. In contrast, during longer term sea level fall, i.e. long-term decrease of accommodation space, prograding shelfal units extended platform facies over a large part of the basin. The most heterogeneous facies associations are found in times of minimal accommodation space, when incisions and subaerial exposure produce lateral variable strata (e.g. top Natih E). The organic matter is found at the base of two of the three longer term (3rd order) depositional sequences. The organic carbon is contained in marl-limestone couplets (small-scale cyclicity) with a high abundance of oysters and monospecific brachiopod faunas (coquinas). Rudists are found in the progradational part of these sequences, and occur mostly as reworked rudstone layers in meter to decimeter scale, high frequency cycles. The detailed regional correlation depends on the identification of medium- to small-scale (4th to 5th order) depositional sequences which are bounded by regional shifts of the facies belts. The distinct hierarchical organization of the depositional sequences in the Cenomanian, and the relative stability at that time of the Arabian Peninsula, implies a strong correlation potential and thus a broad regional similarity of the architecture of the petroleum systems at that time.

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