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The Amazon Basin is dominated by convective rainfall with significant spatial and diurnal variability. Diurnal and seasonal distributions of convective events were determined from rainfall and Cloud Top Temperature (CTT) between January 2008 and December 2010 in city Belém-PA. The decis technique was used to select the most intense events (rainfall rate ≥ 15 mm h–1), which were subsequently, subclassified into deep convection events (DCE) and shallow convection events (SCE). Ninety four cases were found, mostly occurring between 12 and 19 LT, and 55% in the rainy season. Another set of DCE and SCE with rainfall rate ≥ 1 mm h–1 was selected to analyze the effect of seasonality. Of these, 42 cases were found also between 12 and 19 LT, with a maximum at 16 LT. Temperature profiles differed between the rainy and less rainy seasons, in the intensification of shallow and deep convection. Moisture profiles showed greater variability between 850 and 500 hPa, indicative of their role in convective activity; during the rainy season the atmosphere was more humid (less humid) before (at the time) of the occurrence of DCE. Wind components showed significant shear between surface and ~850 hPa, with stronger zonal component in the cases of DCE. The highest values of CAPE were observed about 2 to 3 hours before DCE and SCE, with maximum values before DCE in the rainy season. Results presented here are relevant to improve short-term forecasts and convective event simulations with numerical weather and climate models.

Hujan ekstrem yang melanda wilayah Jakarta sejak tanggal 31 Desember 2019 hingga 1 Januari 2020 menyebabkan sejumlah wilayah di Jakarta terendam banjir. Berdasarkan pengukuran curah hujan harian yang diukur pada tanggal 1 Januari 2020, curah hujan tertinggi terukur sebesar 377 mm di Pangkalan TNI Angkatan Udara Halim Perdana Kusuma. Analisis dari kejadian ini menggunakan Teknik RGB (Red Green Blue) pada citra satelit Himawari-8. Terdapat beberapa skema RGB yang mendukung penelitian ini yaitu, skema 24-Hours Microphysics, Day Microphysics, Night Microphysics, Air Mass dan Day Convective Storms. Hasil analisis time series suhu puncak awan menunjukkan pertumbuhan awan penyebab hujan ekstrem dimulai pada pukul 08.00 JLT dan hujan mulai melanda wilayah Jakarta sekitar pukul 09.15 JLT. Dari skema RGB diketahui terdapat massa udara hangat di wilayah Jakarta yang merupakan pemicu pertumbuhan awan Cumulonimbus. Tujuan dari penelitian ini ialah untuk mengetahui dinamika atmosfer dan sebaran awan konvektif saat terjadi banjir di Jakarta tanggal 31 Desember 2019 – 1 Januari 2020

A total of 13 ocean-based wind events from 2018, detected by buoys and Coastal-Marine Automated Network (C-MAN) stations, were analyzed using 1-min mesoscale sector Advanced Baseline Imager (ABI) cloud top brightness temperature (CTTB) data, as well as 1-min Geostationary Lightning Mapper (GLM) lightning data. The ABI and GLM instruments are located on the Geostationary Operational Environmental Satellite-16 (GOES-16) satellite. An oceanic wind event was defined as a buoy or C-MAN station-recorded peak wind gust of at least 14 m s−1, associated with a convective storm. The wind gust was required to exceed the wind speed by at least 4 m s−1 at the time of the event, but not exceed the corresponding wind speed by at least 4 m s−1 for more than 30 min. This study hypothesized that prior to a wind event, there should be unique signatures in ABI CTTB and GLM lightning datasets. The presumption was that the minimum CTTB and maximum flash rate should occur near the same time and prior to the event. The minimum CTTB occurred an average of 10.5 min and a median of 7 min prior to events, with a range from 29 min prior to 1 min after the event. Changes in CTTB were often subtle. A maximum flash rate occurred within 5 min of the minimum CTTB for 11 of the 12 events with lightning and did not exceed 11 flashes per minute for 9 of the 12 events with lightning. Operational weather forecasters might use CTTB and lightning trends to help identify storms capable of producing significant oceanic wind events.

Cloud-top height (CTH) and cloud-top temperature (CTT) retrieved from the Himawari-8 observations are evaluated using the active shipborne radar–lidar observations derived from the 31-day Clouds, Aerosols, Precipitation Radiation and Atmospheric Composition over the Southern Ocean (CAPRICORN) experiment in 2016 and 1-yr observations from the spaceborne Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) cloud product over a large sector of the Southern Ocean. The results show that the Himawari-8 CTH (CTT) retrievals agree reasonably well with both the shipborne estimates, with a correlation coefficient of 0.837 (0.820), a mean bias error of 0.226 km (−2.526°C), and an RMSE of 1.684 km (10.069°C). In the comparison with CALIOP, the corresponding quantities are found to be 0.786 (0.480), −0.570 km (1.343°C), and 2.297 km (25.176°C). The Himawari-8 CTH (CTT) generally falls between the physical CTHs observed by CALIOP and the shipborne radar–lidar estimates. However, major systematic biases are also identified. These errors include (i) a low (warm) bias in CTH (CTT) for warm liquid cloud type, (ii) a cold bias in CTT for supercooled liquid water cloud type, (iii) a lack of CTH at ~3 km that does not have a corresponding gap in CTT, (iv) a tendency of misclassifying some low-/mid-top clouds as cirrus and overlap cloud types, and (v) a saturation of CTH (CTT) around 10 km (−40°C), particularly for cirrus and overlap cloud types. Various challenges that underpin these biases are also explored, including the potential of parallax bias, low-level inversion, and cloud heterogeneity.

Teknik RGB (Red-Green-Blue) merupakan salah satu teknik intepretasi citra satelit dengan mengombinasikan beberapa kanal secara tumpang tindih warna merah, hijau dan biru untuk menyajikan informasi yang lebih mudah dipahami. Teknik RGB dapat digunakan dalam kajian analisis cuaca, terutama untuk mengidentifikasi kondisi khusus seperti bencana hidrometeorologi. Kejadian banjir pada tanggal 20 - 21 Februari 2017 yang merendam sekurangnya 7 kabupaten dan 1 kota di Provinsi Lampung yang dindikasikan terjadi karena hujan ekstrim yang merata di wilayah Lampung. Hasil pelaporan curah hujan di stasiun Klimatologi Masgar terukur 107.0 mm/hari, Pos Pengamatan Politeknik Negeri Lampung terukur 159.6 mm/hari dan Pos Pengamatan Kemiling Bandar Lampung terukur 154.0 mm/hari dimana curah hujan termasuk dalam kategori hujan sangat lebat BMKG (> 100 mm/hari). Hasil analisis kondisi regional menunjukan adanya tekanan udara rendah di barat lampung dan daerah konvergensi serta shearline di Lampung bagian barat dan tengah. Analisis citra satelit menunjukan adanya kumpulan awan dengan suhu puncak yang sangat dingin, teknik RGB menggunakan identifikasi mikrofisis atmosfer pada malam hari (Night Microphysics) dan sebaran massa udara (Air Mass) menunjukan adanya proses mikrofisis yang intensif serta aliran massa udara penyebab awan hujan yang tumbuh dan meluas di wilayah Lampung sebelum dan saat terjadinya banjir. Hasil produk olahan HCAI (Highresolution Cloud Analysis Information) menunjukan awan didominasi oleh awan Comulonimbus (Cb) dan awan konvektif padat (Dense Cloud).

In this paper, we analyze meteorological conditions, thundercloud structure, lightning activity and characteristics of the flashes that strike two towers separated by 1.3 km on Tosa d'Alp (2537 m asl) for two days (March 24 and 31) of the Cerdanya-2017 field campaign. Remote sensing products (cloud top temperature, lightning flash location, volumetric radar scans) and a set of sensors installed at Cerdanya station (electric field mill, microwave radiometer, vertically-pointing K-band Doppler radar, atmospheric soundings) provide the data for the analysis. A total of 20 flashes (72 strokes) have been detected on these towers with a large majority on March 24 (18 flashes and 66 strokes), despite of a lower convective activity in the study region. All these flashes are negative and most of them exhibit the features of upward flashes: large multiplicity (3.67 in average on March 24), strokes with low peak current (−10.6 kA in average on March 24), and short inter-stroke time interval (40 ms in average on March 24). Some flashes are supposed to be self-triggered on the towers because of the absence (the low number) of VHF sources before (after) the strokes. Compared to the instrumented “Eagle Nest Tower”, the “Cerdanya Tardia Antenna” collects a greater number of flashes (strokes) during the most prolific day with 14 out of 18 (57 out of 66). During this day, all flashes that radiate in VHF at less than 5 km from the towers strike them. We observe also that the cloud region around −15 °C favorable for charging process is located at lower altitude (1000 m above tower altitude) and produce strong radar reflectivity values on that day. Furthermore, the wind at the altitude of Tosa d'Alp stronger on March 24 could facilitate the inception from the towers by evacuating the corona ions.

In this work we have produced global maps of Venus nightside atmosphere using the complete infrared dataset of VIRTIS mapping channel onboard Venus Express between 2006 and 2008. Despite the local variability and high dynamics of the clouds, the accumulation of data over several years allowed us to obtain a global mean state of the atmosphere, where we can observe the average structure of the clouds from equator to the polar regions with a high symmetry north/south even for the local time dependencies. We have first obtained a global view of the nightside cloud opacity in the lower clouds mapping the integrated radiance in the infrared atmospheric windows around 1.74 μm and 2.3 μm (left maps in Figure 1). The radiance measured around these wavelengths originate below the cloud layer and both bands reflect the opacity of the lower cloud layer (44-48 km altitude), with common trends and high symmetry between the north and south hemispheres. Despite the common elements, the bands 1.74 and 2.3μm behave very differently with respect to the particle size, therefore the ratio between them provides an indirect estimation of the particle size distribution for these clouds, which is especially evident near the polar regions and also around the mid-latitude cloud belt (middle maps in Figure 1). We have then produced maps of the brightness temperatures in the thermal region around 3.8 μm and 5.0 μm, which provide a direct indication of the temperatures at the top of the clouds (60–70 km altitude) and the cooling with local time visible in both hemispheres (right maps in Figure 1).Figure 1: Maps of Venus nightside atmosphere. Top maps represent latitude and local time (evening on the right, midnight in the center, morning on the left). Bottom maps are centered at the south pole and distributed with longitude. Left: Cloud opacity (inverse of the integrated radiance at 1.74μm, high opacity regions in both poles are dark due to the low radiance, mid-latitude clouds have highest radiance and lowest opacity). Middle: Particle size (ratio of the integrated radiance at 1.74 and 2.3μm, bright areas in both poles indicate larger particle sizes, mid-latitude cloud belt has smallest particle sizes). Right: Cloud top temperature (thermal brightness measured at 3.8μm, cold collar evening-morning cooling is visible and symmetric in both hemispheres). These maps provide a global view of the global atmospheric dynamics at various altitudes, showing the main regions of the planet and the main characteristics in line with the latest general circulation models of Venus. The equatorial region shows a uniform cloud opacity and particle size, with no significant local time variations throughout the night except for the gradual temperature cooling of the cloud tops from evening to morning. The mid-latitude cloud belt extends uniformly over the night with the lowest opacity and lowest particle size distribution for both hemispheres, with an interesting asymmetry as the Northern hemisphere seems to have lower opacity and relative particle sizes. Towards the polar regions, the cold-collar appears with highest opacity and particle sizes, with a clear evening-to-morning cooling that had already been reported separately for the North and South hemispheres, and is now shown simultaneously providing a more global view of the atmospheric symmetry. Reference publication: "Global maps of Venus nightside mean infrared thermal emissions obtained by VIRTIS on Venus Express". ICARUS, Volume 343, June 2020, 113683, https://doi.org/10.1016/j.icarus.2020.113683

Our study analyzed the occurrence frequency and distribution of seedable clouds around the Korean Peninsula in order to better secure water resources. Cloud products from the Communication, Ocean, and Meteorological Satellite (COMS), including cloud fraction, cloud top height, cloud top temperature, cloud phase, cloud top pressure, cloud optical thickness, and rainfall intensity, were used. Daytime hourly data between 0900 and 1800 local standard time (LST) observed from December 2016 to November 2019 was used. Seedable clouds occurring within this period were evaluated based on seasonal cloud phases, occurrence frequency, and cloud characteristics according to land, sea, and cloud type. These clouds exhibited varying average occurrence frequencies in different seasons. Sc (stratocumulus) clouds exhibited the highest occurrence frequency for all seasons, with an average of 63%, followed by Cu (cumulus) at 15%, As (altostratus) at 13%, and Ac (altocumulus) at 6%. We determined that low-level clouds primarily occurred around the Korean Peninsula, and the occurrence frequency of stratiform clouds was highest for water phase seedable clouds, while the occurrence frequency of cumuliform clouds was highest for ice phase seedable clouds. We believe that precipitation enhancement experiments could be suitable for western and eastern seas around the Korean Peninsula as well as for mountainous regions on land.

Regional variation of electrical and lightning properties of thunderclouds is investigated by using simultaneous observations of electric field mill (EFM-100) and lightning detector (LD-350) in synergy with their radiance and bulk microphysical properties. The study is carried out over Kohima in the north-eastern and over Rampurhat in the eastern part of India (20o-30o N, 85o-96o E), during the pre-monsoon season (March–May) of 2017–2018. The occurrence of EFM-100 detected thunderclouds is found to be more over Kohima (111) compared to Rampurhat (88). Whereas, the average number of lightning flash is much higher over Rampurhat (~542 flash/thundercloud) compared to Kohima (~32 flash/thundercloud). Over both the regions, the maximum occurrence of thunderclouds is found during afternoon to evening hours. The upper whisker value in the box plot shows that thunderclouds over Rampurhat are associated with higher CAPE value (Kohima: 1100 J Kg−1; Rampurhat: 5000 J Kg−1). The diurnal variation of CAPE supports relatively early occurrence of thunderclouds over Kohima. Thunderclouds over Rampurhat persists for relatively longer duration. It is observed that overall percentage occurrence of CG lightning is more over Kohima (Kohima: −CG: 28.09% & +CG: 09.74%; Rampurhat (–CG: 12.33% & +CG: 08.60%), with relatively higher −CG lightning compared to +CG, over both the stations. On the contrary, the occurrence of IC lightning is more over Rampurhat (Rampurhat: −IC: 31.75% & +IC: 47.30%; Kohima: −IC: 36.44% & +IC: 25.72%). Over Kohima occurrence of −IC is more than the +IC, whereas over Rampurhat, the occurrence of +IC is more than −IC. The overall higher occurrence of total negative and positive discharges over Kohima and Rampurhat respectively is consistence with EFM observations. The prevalence of positive/negative discharge suggests the presence of a tripole charge structure within thunderclouds over both the regions. The upper whisker value in the box plots revels higher CG flash density, IC:CG and larger log(area) over Rampurhat (Kohima: 3.0 × 10−3 flash km−2 h−1 and Rampurhat: 4.25 × 10−3 flash km−2 h−1; Kohima: 7 and Rampurhat: 15; Kohima: 10.5 km2 and Rampurhat: 11.5 km2). The lower whisker value of cloud top temperature reveals prevalence of colder thunderclouds over Rampurhat (Kohima: 220 K; Rampurhat: 184 K). The thunderclouds over Rampurhat are found to be associated with stronger updrafts and mixed-phase processes. The study reveals that, over these two regions, the electrical and lightning properties have distinct characteristics.

The main results of the development and testing of the cloud detection method are presented. The main purpose of the method is the identification and classification of clouds in satellite images with the subsequent retrieval of quantitative characteristics. The method provides digital datasets in the form of maps of cloud classes, cloud top height, and cloud top temperature. The consecutive stages of cloud detection are considered, and the conditions and basic results of the method testing are presented.

Satellite and reanalysis precipitation products perform poorly over regions with low-density ground observation networks. In order to improve space-dependent parameterization of precipitation estimation models in data-scarce environments, the delineation boundaries of precipitation regimes should be accurately identified. Existing approaches to characterize precipitation regimes by seasonal or other climatological properties do not account for small scale spatial-temporal variability. Precipitation time series can be used to account for this small-scale variability in regime classification. Unfortunately, precipitation products with global coverage perform poorly at small time scales over data scarce regions. A methodology of using satellite-based cloud-top temperature (CTT) time series as a proxy of precipitation time series for precipitation regime classification was developed, and its potential and uncertainty were analyzed. A precipitation regime in this study was defined on the basis of characteristic small-scale temporal distribution and variability of precipitation at a given place. Dynamic time warping was used to calculate the distance between two time series. Criteria to select the optimal temporal scale of time series for clustering and the number of clusters were also developed. The method was validated over Germany and applied to Tanzania, characterized by complex climatology and low density ground observations. This approach was evaluated against precipitation regime classification based on a satellite precipitation product. Results show that CTT outcompetes satellite-based precipitation for classification of precipitation regime classification. The CTT-based classification can be used as precursor to spatially adapted precipitation estimation algorithms where parameters are calibrated by gauge data or other ground-based precipitation observations, and parameterization can be used for satellite-precipitation estimates, precipitation forecasts in numerical or stochastic weather models, etc.

Lightning activities are distributed asymmetrically over the globe. Satellite images show that the Himalayan region is one of the prone zones of lightning activity. We do not understand such an uneven distribution of lightning activities as of today. To elaborate on the present-day understanding of lightning flashes over the Himalayan region, we have analyzed various atmospheric factors in association with Lightning Flash Density (LFD). For this purpose, we divided the Himalayan Range into three sections, namely, eastern, middle, and the western Himalayas. We explored the possible association of monthly mean Convective Available Potential Energy (CAPE), Surface Air Temperature (SAT), thermodynamic temperature of the top of the cloud; Cloud Top Temperature (CTT), Relative Humidity (RH), and Specific Humidity (SH) with LFD over the three sections of the Himalayan range. We observed that CAPE and SAT play a vital role in creating instability over that region. In contrast, moderate moisture (i.e., RH) is the most suitable condition for lightning activities over all three sections. The analysis shows that 50–60% RH at 700hpa is the most favorable condition for lightning over the Himalayan region.

On 29–30 October 2013, a low-light video camera installed at Pic du Midi (2877 m), recorded transient luminous events above a very active storm over the Mediterranean Sea. The minimum cloud top temperature reached −73°C, while its cloud to ground (CG) flash rate exceeded 30 fl min−1. Some sprite events have long duration and resemble to dancing sprites. We analyze in detail the temporal evolution and estimated location of two series of sprite sequences, as well as the cloud structure, the lightning activity, the electric field radiated in a broad range of low frequencies, and the current moment waveform of the lightning strokes. (i) In each series, successive sprite sequences reflect time and location of corresponding positive lightning strokes across the stratiform region. (ii) The longer time-delayed (>20 ms) sprite elements correspond to the lower impulsive charge moment changes (iCMC) of the parent strokes (

In this paper, an algorithm based on the probability of rainfall intensities classification for rainfall estimation from Meteosat Second Generation/Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) has been developed. The classification scheme uses various spectral parameters of SEVIRI that provide information about cloud top temperature and optical and microphysical cloud properties. The presented method is developed and trained for the north of Algeria. The calibration of the method is carried out using as a reference rain classification fields derived from radar for rainy season from November 2006 to March 2007. Rainfall rates are assigned to rain areas previously identified and classified according to the precipitation formation processes. The comparisons between satellite-derived precipitation estimates and validation data show that the developed scheme performs reasonably well. Indeed, the correlation coefficient presents a significant level (r:0.87). The values of POD, POFD and FAR are 80%, 13% and 25%, respectively. Also, for a rainfall estimation of about 614 mm, the RMSD, Bias, MAD and PD indicate 102.06(mm), 2.18(mm), 68.07(mm) and 12.58, respectively.

Weather conditions at night on March 19, 2016, when Boeing 737-800 crashed in Rostov-on-Don, are analyzed using the data of aerodrome observations and radiosounding, satellite data on cloudiness and cloud top temperature, and the data of synoptic and calculated charts of maximum wind.

A temperature inversion layer often occurs above a cloud layer due to longwave cooling in the upper cloud levels; however, few previous studies have been conducted on the climatologic statistics of cloud-top temperature inversion features. By using a high-quality continuous radiosonde dataset from 2002/05 to 2014/05 at the Atmospheric Radiation Measurement (ARM) Tropical Western Pacific (TWP) site at the islands of Manus and North Slope of Alaska (NSA) site near Barrow, Alaska, this study investigated the long-term characteristics of cloud-top temperature inversion over the single- and double-layer clouds (SLC and DLC, respectively) in these two different geographic locations and climate regimes. Cloud tops extended much higher vertically at the TWP than at the NSA due to their different local atmospheric environments. Because of the radiative energy interactions between the two layers of clouds, a thinner temperature inversion depth was presented by the DLC lower clouds than by the DLC higher clouds at the TWP site. However, much weaker temperature inversions were detected above the DLC higher clouds than the DLC lower clouds which were often bounded by a ubiquitous surface radiative cooling-induced inversion at the NSA site. A close temperature inversion was observed between the morning and evening at both sites. A thinner temperature inversion depth was displayed in the summer and autumn melt seasons when weak surface radiative cooling occurred at the NSA, whereas a smooth seasonal temperature inversion occurred at the TWP. The climatologic results of this study are expected to provide a better understanding of the complex interactions between clouds and temperature inversion, especially their unique climatic features in the tropics and Arctic.

Using the Himawari-8 cloud product, this study investigated the seasonal, monthly, diurnal variations as well as spatial and vertical distributions of cloud properties over four typical regions, which are northwest (NW), north (N), southeast (SE) China and Tibetan Plateau (TP). The results show that the cloud occurs most frequently in spring and summer, and the seasonal average cloud top height (CTH) has clear seasonal differences while the cloud top temperature (CTT) is negatively correlated with CTH. A unimodal structure is found for the vertical distribution of occurrence frequency of CTH over SE and TP. By dividing clouds into four types, they show large differences in the probability of occurrence. The study also shows that the monthly cloud fraction (CF) is larger in summer and less in winter except in SE, the monthly CTH changes are relatively small in SE and TP, while the monthly CTT variation is the largest in TP. The total CF increases by 22%, 8%, 3%, and 16% from morning to afternoon in four study areas, respectively. The proportion of four types of cloud families has weak diurnal variation except over TP. In TP, the proportions of high cloud (HC) and low cloud (LC) have a diurnal variation of 30% and 22%, respectively. Note that the relative CF contribution (RCFC) of LC reaches the maximum values in the morning. With the enhancement of convection, the RCFC of DCC and HC increases rapidly. Associated with more active convections, the diurnal variations of CTH and CTT are larger in TP than those in other regions. The clouds in SE have a larger COT and smaller CTH than in other regions, implying more sufficient water supply with low clouds.

By combining AVHRR data from the NOAA satellites with information from a database of in situ measurements, large-scale maps can be generated of the microphysical parameters most immediately significant for the modelling of global circulation and climate. From the satellite data, the clouds can be classified into cumuliform, stratiform and cirrus classes and then into further sub-classes by cloud top temperature. At the same time a database of in situ measurements made by research aircraft is classified into the same sub-classes and a statistical analysis is used to derive relationships between the sub-classes and the cloud microphysical properties. These two analyses are then linked to give estimates of the microphysical properties of the satellite observed clouds. Examples are given of the application of this technique to derive maps of the probability of occurrence of precipitating clouds and of precipitating water content derived from a case study within the International Cirrus Experiment (ICE) held in 1989 over the North Sea.

The applicability of the fixed anvil temperature (FAT) hypothesis is examined using data of a global nonhydrostatic model, focusing particularly on high cloud size dependency. Decomposition of outgoing-longwave radiation (OLR) into three components, including cloud top temperature (TCT), upward cloud emissivity (e), and clear-sky OLR (FCLR), reveals that the relative contributions of these three components to changes of OLR are highly dependent on cloud size. That is, the FAT hypothesis is applicable only for smaller clouds, because the contribution of TCT by those clouds is small, and e is more important. In contrast, for larger clouds, the contribution of e is comparable to that of TCT, and thus, both components are equally important. FCLR slightly reduces OLR but shows dependence on cloud size.

Based on a set of morphological distances computed between the grayscale images (spatial fields) of similar size specifications, the ratios of selected morphological distances, and the ratios of areas of infima and suprema of grayscale images, a new metric to quantify the degree of similarity between the grayscale images is proposed. We denote the two spatial fields (grayscale images), respectively, with $f^{i}$ and $f^{j}$ , and the infima and suprema of these spatial fields with $( {f^{i}\wedge f^{j}} )$ and $( {f^{i}\vee f^{j}} )$ . The three morphology-based distances include: 1) dilation distance $d( {f^{i},f^{j}} )$ ; 2) erosion distance $e( {f^{i},f^{j}} )$ ; and 3) median-based distance $M_{N} ( {f^{i},f^{j}})$ . By employing these parameters, which play vital role in construction of parameter-specific interaction matrices, we provide a metric to designate every possible pair of images that can be considered out of a database consisting of a huge number of images. We demonstrate the whole approach on: 1) synthetic spatial fields; 2) a set of 12 similar-sized grayscale images representing cloud-top temperatures of a specific region for 12 different time instants; and 3) four spatial elevation fields to rank possible pairs of images.

Impacts of aerosols on subfreezing cloud thermodynamic phase change over East Asia are studied by using 4 year combined CloudSat radar and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar measurements. The mean occurrence frequencies of supercooled-liquid, mixed-phase, and glaciated clouds over East Asia are 10.4%, 10.3%, and 16.9%, respectively. Over northwest of East Asia (32–44°N, 75–100°E), subfreezing clouds are dominated by glaciated clouds with a mean relative cloud fraction (RCF) of ~60% and over southeast (16–32°N, 95–120°E) are dominated by supercooled-liquid clouds with a mean RCF of ~50%. Although cloud top temperature (CTT) differences contribute largely to the thermodynamic phase differences, northwest of East Asia has ~20% larger glaciated (smaller mixed-phase) RCFs than those of southeast at the same CTT. Seasonal anomalies of glaciated and mixed-phase RCFs correlate well with the seasonal variations of dust occurrence frequency. In addition, subfreezing clouds associated with mineral dust contain approximately 5%, 10%, and 20% larger glaciated (smaller mixed-phase) RCFs than those associated with polluted dust, smoke, and background aerosols at any given CTT. It is suggested that dust impacts on subfreezing clouds over East Asia by providing abundant effective ice nuclei to glaciate mixed-phase clouds, although the impacts of large-scale dynamics and water supply mechanisms cannot be ruled out.

Investigation of cloud top temperature (CTT) and its diurnal variation is highly reliant on high spatial and temporal resolution satellite data, which is lacking over the Indian region. An algorithm has been developed for detection of clouds and retrieval of CTT from the geostationary satellite INSAT-3D. These retrievals are validated (inter-compared) with collocated in-situ (satellite) measurements with specific intent to generate climate-quality data. The cloud detection algorithm employs nine different tests, in accordance with solar illumination, satellite angle and surface type conditions to generate pixel-resolution cloud mask. Validation of cloud mask with cloud-aerosol lidar with orthogonal polarization (CALIOP) shows that probability of detection (POD) of cloudy (clear) sky is 81% (85%), with 83% hit rate. The algorithm is also implemented on similar channels of moderate resolution imaging spectroradiometer (MODIS), which provides 88% (83%) POD of cloudy (clear) sky, with 86% hit rate. CTT retrieval is done at the pixel level, for all cloud pixels, by employing appropriate methods for various types of clouds. Comparison of CTT with radiosonde and cloud-aerosol lidar and infrared pathfinder satellite observations (CALIPSO) shows mean absolute error less than 3%. The study also examines sensitivity of retrieved CTT to the cloud classification scheme and retrieval criteria. Validation results and their close agreements with those of similar satellites demonstrate the reliability of the retrieved product for climate studies.

This study analyzes seasonal and temporal variations in aerosol optical depth (AOD), and the impact of these variations on the properties of clouds over five cities in Pakistan, using Moderate Resolution Imaging Spectroradiometer (MODIS) data, obtained from the Terra satellite during the period (2001–2011). The obtained results indicated seasonal variation in AOD, with a high value of 2.3, in summer and low values of 0.2, in winter for the costal part of the region. The relationship between AOD and other cloud parameters, namely water vapor (WV), cloud fraction (CF), cloud optical thickness (COT), cloud liquid water path (CLWP), cloud top temperature (CTT), and cloud top pressure (CTP) were analyzed. On a temporal scale, latitudinal variations of both WV and AOD produce high correlations (>0.6) in some regions, and moderate correlations (0.4–0.6) in the other regions. An increasing trend in CF with AOD was found over urban regions in the period of observations. The CF values were higher for Lahore than the other selected regions during the whole period. During autumn and winter seasons the correlation was found to be positive between AOD and CLWP, while negative correlation was observed during the other seasons for all the selected regions. COT showed negative correlation with AOD at all locations except Karachi during spring and summer seasons. AOD showed a positive correlation with CTP and CTT for the spring season and a negative correlation was observed for summer for all investigated regions. Furthermore, in warm clouds AOD and CTP were negatively correlated for all regions except Peshawar, whereas, AOD and CTT were positively correlated for all regions except Karachi. In cold clouds the relationships between AOD and CTP, and AOD and CTT were negative, except Karachi. Thus meteorological parameters, geographical conditions, as well as warm and cold clouds are the causative factors for AOD and CTP, and AOD and CTT variations.

Nighttime sea fog detection from satellite is very hard due to limitation in using visible channels. Currently, most widely used method for the detection is the Dual Channel Difference (DCD) method based on Brightness Temperature Difference between 3.7 and 11 µm channel (BTD). However, this method have difficulty in distinguishing between fog and low cloud, and sometimes misjudges middle/high cloud as well as clear scene as fog. Using CALIPSO Lidar Pro- file measurements, we have analyzed the intrinsic problems in detecting nighttime sea fog from var- ious satellite remote sensing algorithms and suggested the direction for the improvement of the algorithm. From the comparison with CALIPSO measurements for May-July in 2011, the DCD method excessively overestimates foggy pixels (2542 pixels). Among them, only 524 pixel are real foggy pixels, but 331 pixels and 1687 pixels are clear and other type of clouds, respectively. The 514 of real foggy pixels accounts for 70% of 749 foggy pixels identified by CALIPSO. Our pro- posed new algorithm detects foggy pixels by comparing the difference between cloud top tempera- ture and underneath sea surface temperature from assimilated data along with the DCD method. We have used two types of cloud top temperature, which obtained from 11 µm brightness temperature (B_S1) and operational COMS algorithm (B_S2). The detected foggy 1794 pixels from B_S1 and 1490 pixel from B_S2 are significantly reduced the overestimation detected by the DCD method. However, 477 and 446 pixels have been found to be real foggy pixels, 329 and 264 pixels be clear, and 989 and 780 pixels be other type of clouds, detected by B_S1 and B_S2 respectively. The anal- ysis of the operational COMS fog detection algorithm reveals that the cloud screening process was strictly enforced, which resulted in underestimation of foggy pixel. The 538 of total detected foggy pixels obtain only 187 of real foggy pixels, but 61 of clear pixels and 290 of other type clouds. Our analysis suggests that there is no winner for nighttime sea fog detection algorithms, but loser because real foggy pixels are less than 30% among the foggy pixels declared by all algorithms. This overwhelming evidence reveals that current nighttime sea fog algorithms have provided a lot of mis- judged information, which are mostly originated from difficulty in distinguishing between clear and cloudy scene as well as fog and other type clouds. Therefore, in-depth researches are urgently required to reduce the enormous error in nighttime sea fog detection from satellite.

There are many books on atmospheric remote sensing. This chapter revises the clouds shapes, types, and properties and provides a brief review of some of the primary applications of satellite remote sensing of the atmosphere including atmospheric profiling, cloud top temperature, rain rate, atmospheric liquid water, cloud liquid water, and the ground validation using radiosondes and dropsondes.

[1] Understanding the role of contrails in the Earth's radiation budget requires an accurate characterization of their macrophysical and microphysical properties, such as cloud top temperature, optical depth, and effective particle size. These properties are derived from 2006 MODerate-resolution Imaging Spectroradiometer data over the Northern Hemisphere using a bi-spectral, infrared-only retrieval technique. Contrail temperature is estimated using a quadratic relationship of flight track pressure with latitude. The results reveal distinct seasonal trends in contrail microphysical properties, with slightly greater mean optical depths and slightly smaller particle sizes during summer. The average contrail optical depth and particle effective diameter are 0.216 and 35.7 µm, respectively. Although fewer contrails occurred at night, there are no appreciable diurnal differences in their retrieved properties. These results should help to fill the gap in our knowledge of contrail properties and will be valuable for model validation.

A satellite rainfall retrieval technique is proposed here. The relationships of rain rate with each of cloud water path (CWP) and cloud top temperature (CTT) are investigated. The CWP and CTT are retrieved from SEVIRI data (spinning enhanced visible and infrared imager), and corresponding rain rates are measured by weather radar. The rain rates are compared to corresponding CWP and then to corresponding CTT. The investigation demonstrates an exponential functional dependency between rain rates and CWP for low and moderate rain rates (stratiform rainfall). Conversely, the rain rates are more closely related to CTT for high rain rates (convective rainfall). Therefore, two separate relationships are established for rain rate retrievals. The results show rain rates estimated by the developed scheme are in good correlation with those observed by weather radar.