Abstract
This paper investigates the vertical structure of warm-cloud microphysical properties using a three-dimensional (3D) spectral bin microphysical model. A time series of contoured frequency by ...optical depth diagrams (CFODDs), which were proposed by previous studies, are calculated for the first time by a 3D model assuming two types of aerosol conditions (i.e., polluted and pristine). This contrasts with previous studies that obtained CFODDs using either a two-dimensional model or an accumulation of monthly and global observation data. The results show that the simulated CFODDs are characterized by distinctive patterns of radar reflectivities, similar to the patterns often observed by satellite remote sensing, even though the calculation domain of this study is limited to an area of 30 × 30 km2, whereas the satellite observations are of a global scale. A cloud microphysical box model is then applied to the simulated cloud field at each time step to identify the dominant process for each of the patterns. The results reveal that the wide variety of satellite-observed CFODD patterns can be attributed to different microphysical processes occurring in multiple cloud cells at various stages of the cloud life cycle.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A large number of photovoltaic (PV) power systems have been adopted in Japan after a feed‐in tariff was introduced in 2012. However, PV power generation data from residential rooftop and/or ...ground‐mounted PV systems, and larger MW‐size PV plants have not been measured accurately in real‐time. This is because PV power monitoring instruments (eg, smart meters) have not collected a sufficient amount of power generation data. In order to realize adequate safety control of electric power systems under high PV‐penetration conditions, it is important to fully understand the temporal and spatial variations associated with PV power generation. In this study, we estimated the PV power generation for a regional area (ie, prefecture or municipality) in terms of PV power installation capacity and satellite‐estimated solar irradiance using a Japanese geostationary satellite, Himawari‐8. The satellite‐derived regionally integrated PV power estimations were validated with reference data provided by electric power companies. The validation results showed that these estimations were comparable to the reference data, provided by the Kyushu Electric Power Company Inc. (Kyushu) and the Tokyo Electric Power Company Inc. (TEPCO). However, the results also identified slight overestimations of PV power in the spring and summer seasons. An advantage of the proposed method is that it does not require land‐based monitoring instruments, which can lead to increased operational cost savings for PV power systems. Furthermore, in consideration of future PV power penetration scenarios, it is suggested that PV power in excess of regional power demands could be generated under the same weather conditions.
Regional PV power generation (or prefecture and/or municipality regions) are estimated based on PV system installation capacity and satellite‐estimated solar irradiance by using a geostationary satellite.
The Greenhouse Gases Observing Satellite (GOSAT) was launched in 2009 to measure global atmospheric CO2 and CH4 concentrations. GOSAT is equipped with two sensors: the Thermal And Near infrared ...Sensor for carbon Observations (TANSO)-Fourier transform spectrometer (FTS) and TANSO-Cloud and Aerosol Imager (CAI). The presence of clouds in the instantaneous field of view of the FTS leads to incorrect estimates of the concentrations. Thus, the FTS data suspected to have cloud contamination must be identified by a CAI cloud discrimination algorithm and rejected. Conversely, overestimating clouds reduces the amount of FTS data that can be used to estimate greenhouse gas concentrations. This is a serious problem in tropical rainforest regions, such as the Amazon, where the amount of useable FTS data is small because of cloud cover. Preparations are continuing for the launch of the GOSAT-2 in fiscal year 2018. To improve the accuracy of the estimates of greenhouse gases concentrations, we need to refine the existing CAI cloud discrimination algorithm: Cloud and Aerosol Unbiased Decision Intellectual Algorithm (CLAUDIA1). A new cloud discrimination algorithm using a support vector machine (CLAUDIA3) was developed and presented in another paper. Although the use of visual inspection of clouds as a standard for judging is not practical for screening a full satellite data set, it has the advantage of allowing for locally optimized thresholds, while CLAUDIA1 and -3 use common global thresholds. Thus, the accuracy of visual inspection is better than that of these algorithms in most regions, with the exception of snow- and ice-covered surfaces, where there is not enough spectral contrast to identify cloud. In other words, visual inspection results can be used as truth data for accuracy evaluation of CLAUDIA1 and -3. For this reason visual inspection can be used for the truth metric for the cloud discrimination verification exercise. In this study, we compared CLAUDIA1–CAI and CLAUDIA3–CAI for various land cover types, and evaluated the accuracy of CLAUDIA3–CAI by comparing both CLAUDIA1–CAI and CLAUDIA3–CAI with visual inspection (400 × 400 pixels) of the same CAI images in tropical rainforests. Comparative results between CLAUDIA1–CAI and CLAUDIA3–CAI for various land cover types indicated that CLAUDIA3–CAI had a tendency to identify bright surface and optically thin clouds. However, CLAUDIA3–CAI had a tendency to misjudge the edges of clouds compared with CLAUDIA1–CAI. The accuracy of CLAUDIA3–CAI was approximately 89.5 % in tropical rainforests, which is greater than that of CLAUDIA1–CAI (85.9 %) for the test cases presented here.
Several existing and proposed satellite remote sensing instruments are designed to derive concentrations of trace gases, such as carbon dioxide (CO 2 ) and methane (CH 4 ), from measured spectra of ...reflected sunlight in absorption bands of the gases. Generally, these analyses require that the scenes be free of cloud and aerosol, necessitating robust screening algorithms. In this work, two cloud-screening algorithms are compared. One applies threshold tests, similar to those used by the MODerate resolution Imaging Spectrometer (MODIS), to visible and infrared reflectances measured by the Cloud and Aerosol Imager aboard the Greenhouse gases Observing SATellite (GOSAT). The second is a fast retrieval algorithm that operates on high-resolution spectra in the oxygen A-band measured by the Fourier Transform Spectrometer on GOSAT. Near-simultaneous cloud observations from the MODIS Aqua satellite are used for comparison. Results are expressed in terms of agreement and disagreement in the identification of clear and cloudy scenes for land and non-sun glint viewing over water. The accuracy, defined to be the fraction of scenes that are classified the same, is approximately 80% for both algorithms over land when comparing with MODIS. The accuracy rises to approximately 90% over ocean. Persistent difficulties with identifying cirrus clouds are shown to yield a large fraction of the disagreement with MODIS.
This study investigates the correlation patterns between cloud droplet effective radius (CDR) and cloud optical thickness (COT) of warm clouds with a nonhydrostatic spectral bin microphysics cloud ...model. Numerical experiments are performed with the model to simulate low-level warm clouds. The results show a positive and negative correlation pattern between CDR and COT for nondrizzling and drizzling stages of cloud development, respectively, consistent with findings of previous observational studies. Only a positive correlation is simulated when the collection process is switched off in the experiment, whereas both the positive and negative correlations are reproduced in the simulation with collection as well as condensation processes. The positive and negative correlations can also be explained in terms of an evolution pattern of the size distribution function due to condensation and collection processes, respectively. Sensitivity experiments are also performed to examine how the CDR-COT correlation patterns are influenced by dynamical and aerosol conditions. The dynamical effect tends to change the amplitude of the CDR-COT plot mainly through changing the liquid water path, whereas the aerosol amount significantly modifies the correlation pattern between CDR and COT mainly through changing the cloud particle number concentration. These results suggest that the satellite-observed relationships between CDR and COT can be interpreted as being formed through microphysical particle growth processes under various dynamical and aerosol conditions in the real atmosphere.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
GOSAT-2 CAI-2 L2 Cloud Discrimination Product OISHI, Yu; ISHIDA, Haruma; NAKAJIMA, Takashi Y.
Journal of The Remote Sensing Society of Japan,
2019/02/28, Letnik:
39, Številka:
1
Journal Article
Odprti dostop
The Greenhouse gases Observing SATellite-2 (GOSAT-2) was launched on 29 October, 2018. GOSAT-2 is equipped with two earth-observing instruments: the Thermal And Near-infrared Sensor for carbon ...Observation Fourier Transform Spectrometer 2 (TANSO-FTS-2), and the Cloud and Aerosol Imager 2 (TANSO-CAI-2). Cloud contamination within the instantaneous field-of-view (IFOV) of the FTS-2 leads to incorrect estimates of major greenhouse gases concentration. To solve this problem, the FTS-2 data suspected to have cloud contamination must be identified by a new cloud discrimination algorithm using a support vector machine, the Cloud and Aerosol Unbiased Decision Intellectual Algorithm-3 (CLAUDIA3), used with the CAI-2. The cloud discrimination results will be publicly available as the CAI-2 L2 cloud discrimination products. In this paper, we deal with the CLAUDIA3 and the application of the CLAUDIA3 to CAI-2 data. Moreover, we show several cloud discrimination results of CLAUDIA3 applied to CAI data.
An algorithm is developed for determining the cloud optical thickness and effective particle radius simultaneously on a global scale using Advanced Very High Resolution Radiometer (AVHRR) ...multispectral radiance data. In the algorithm, the treatment of thermal radiation in Nakajima and Nakajima is improved by reformulating the thermal emission in the atmospheric layers. At the same time, the lookup table for thermal emission is parameterized in terms of the equivalent water vapor path in order to include the effect of various vertical water vapor profiles.
The algorithm is applied to AVHRR radiance data corresponding to reported aircraft and balloon measurements of cloud microphysical parameters. A comparison shows a good agreement between in situ and satellite-retrieved values thus obtained. The algorithm is further applied to 4-month Global Area Coverage data of 1987 to generate global distributions of the cloud optical thickness and effective particle radius for every 0.5° × 0.5° box in a −60°−60° latitudinal region. Similarities and differences in the global features of the effective particle radius and the optical thickness are found as compared with the previous studies.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Estimation of electric power and power plant CO2 emissions using satellite remote sensing data is essential for the management of energy consumption and greenhouse gas monitoring. For estimation, the ...relationship between Defense Meteorological Satellite Program Operational Linescan System (DMSP/OLS) annual nighttime stable light product (NSL) for 2006 and statistical data on power generation, power consumption, and power plant CO2 emissions in 10 electric power supply regions of Japan was investigated. Unlike other power plants, thermal plants directly emit CO2 by burning fossil fuels when generating electricity. Among the nighttime lights in the NSL, only light from thermal power is related to power plant CO2 emission. The percentage of thermal power generation to total power generation (K%) is thus a key parameter for estimating nighttime light by power consumption from thermal power plants. In this study, the DMSP/OLS annual nighttime radiance-calibrated product (RCI) for 2006 and the NSL data corrected by K% were employed to estimate electric power and power plant CO2 emissions. Results indicated that the RCI data can offer more accurate estimates of electric power consumption than can the NSL data. It was also found that NSL and RCI data corrected by K% are good proxies for estimating power plant CO2 emissions.
The comprehensive relationship between meteorological conditions and whether low water cloud touches the surface, particularly at sea, is examined with the goal of improving low-cloud detection by ...satellite. Gridpoint-value data provided by an operational mesoscale model with integration ofMultifunction Transport Satellite-2data can provide sufficient data for statistical analyses to find general parameters that can discern whether low clouds touch the surface, compensating for uncertainty due to the scarcity of observation sites at sea and the infrequent incidence of fog. The analyses reveal that surface-touching low clouds tend to have lower cloud-top heights than those not touching the surface, although the frequency distribution of cloud-top height differs by season. The bottom of the Γ > Γ
m
layer (where Γ and Γ
m
are the vertical gradient and the moist-adiabatic lapse rate of the potential temperature, respectively) with surface-touching low-cloud layers tends to be very low or almost attached to the surface. In contrast, the tops of low-cloud layers not touching the surface tend to occur near the bottom of the Γ > Γ
m
layer. Mechanisms to correlate these meteorological conditions with whether low clouds touch the surface are inferred from investigations into the vertical structure of equivalent potential temperature. These results indicate that the temperature difference between cloud-top height and the surface can be an appropriate parameter to infer whether low clouds touch the surface. It is also suggested that only a little addition of meteorological ancillary data, such as the forecast sea surface temperature, to satellite data allows successful performance of the discrimination.
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Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Satellite Data Simulator Unit Masunaga, Hirohiko; Matsui, Toshihisa; Tao, Wei-kuo ...
Bulletin of the American Meteorological Society,
12/2010, Letnik:
91, Številka:
12
Journal Article
Recenzirano
Since the earliest meteorological satellites were sent into orbit in the 1960s, satellite remote sensing has been the vital means to monitor clouds and precipitation uniformly across the Earth. In ...reality, while cloud droplets and raindrops can be thought of as homogeneous liquid water spheres to a reasonable extent, frozen hydrometeors such as cloud ice crystals and snowflakes have highly complicated crystal structures varying dramatically with a number of factors, including ambient temperature and humidity.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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