Cloud Base Height Research Articles

The Significant Role of Radiosonde-measured Cloud-base Height in the Estimation of Cloud Radiative Forcing

The Significant Role of Radiosonde-measured Cloud-base Height in the Estimation of Cloud Radiative Forcing

Identifying insects, clouds, and precipitation using vertically pointing polarimetric radar Doppler velocity spectra

Abstract. This study presents a method to identify and distinguish insects, clouds, and precipitation in 35 GHz (Ka-band) vertically pointing polarimetric radar Doppler velocity power spectra and then produce masks indicating the occurrence of hydrometeors (i.e., clouds or precipitation) and insects at each range gate. The polarimetric radar used in this study transmits a linear polarized wave and receives signals in collinear (CoPol) and cross-linear (XPol) polarized channels. The measured CoPol and XPol Doppler velocity spectra are used to calculate linear depolarization ratio (LDR) spectra. The insect–hydrometeor discrimination method uses CoPol and XPol spectral information in two separate algorithms with their spectral results merged and then filtered into single value products at each range gate. The first algorithm discriminates between insects and clouds in the CoPol Doppler velocity power spectra based on the spectra texture, or spectra roughness, which varies due to the scattering characteristics of insects vs. cloud particles. The second algorithm distinguishes insects from raindrops and ice particles by exploiting the larger Doppler velocity spectra LDR produced by asymmetric insects. Since XPol power return is always less than CoPol power return for the same target (i.e., insect or hydrometeor), fewer insects and hydrometeors are detected in the LDR algorithm than the CoPol algorithm, which drives the need for a CoPol based algorithm. After performing both CoPol and LDR detection algorithms, regions of insect and hydrometeor scattering from both algorithms are combined in the Doppler velocity spectra domain and then filtered to produce a binary hydrometeor mask indicating the occurrence of cloud, raindrops, or ice particles at each range gate. Forty-seven summertime days were processed with the insect–hydrometeor discrimination method using US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar observations in northern Oklahoma, USA. For these 47 d, over 70 % of the hydrometeor mask column bottoms were within ±100 m of simultaneous ceilometer cloud base heights. All datasets and images are available to the public on the DOE ARM repository.

Improving the Retrieval of Cloudy Atmospheric Profiles from Brightness Temperatures Observed with a Ground-Based Microwave Radiometer

Atmospheric temperature and humidity retrievals from ground-based microwave remote sensing are useful in a variety of meteorological and environmental applications. Though the influence of clouds is usually considered in current retrieval algorithms, the resulting temperature and humidity estimates are still biased high in overcast conditions compared to radiosonde observations. Therefore, there is a need to improve the quality of retrievals in cloudy conditions. This paper presents an approach to make brightness temperature (TB) correction for cloud influence before the data can be used in the inversion of vertical profiles of atmospheric temperature and humidity. A three-channel method is proposed to make cloud parameter estimation, i.e., of the total 22 channels of the ground-based radiometer, three are adopted to set up a relationship between cloud parameters and brightness temperatures, so that the observations from the three channels can be used to estimate cloud thickness and water content and complete the cloud correction for the rest of the channels used in the retrieval. Based on two years of data from the atmosphere in Beijing, a comparison of the retrievals with radiosonde observations (RAOB) shows: (1) the temperature retrievals from this study have a higher correlation with RAOB and are notably better than in the vendor-provided LV2. The bias of the temperature retrievals from this study is close to zero at all heights, and the RMSE is greatly reduced from >5 °C to <2 °C in the layer, from about 1.5 km up to 5 km. The temperature retrievals from this study have higher correlation with RAOB data compared to the vendor-provided LV2, especially at and above a 2 km height. (2) The bias of the water vapor density profile from this study is near to zero, while the LV2 has a positive bias as large as 4 g/m3. The RMSE of the water vapor density profile from this study is <2 g/m3, while the RMSE for LV2 is as large as 10 g/m3. That is, both the bias and RMSE from this study are evidently less than the LV2, with a greater improvement in the lower troposphere below 5 km. Correlation with RAOB is improved even more for the water vapor density. The correlation of the retrievals from this study increases to one within the boundary layer, but the correlation of LV2 with RAOB is only 0.8 at 0.5 km height, 0.7 at 1 km, and even less than 0.5 at 2 km. (3) A parameter named the Cloud Impact index, determined by cloud water concentration and cloud thickness, together with the cloud base height, has been defined to show that both BIAS and RMSE of “high-CI subsample” are larger than those of the “low-CI subsample”, indicating that high-CI cloud has a higher impact on the retrievals and the correction for cloud influence is more necessary.

Maritime Cloud and Drizzle Microphysical Properties Retrieved From Ship‐Based Observations During MAGIC

AbstractThe Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign provided a wealth of information looking at the stratocumulus to cumulus transition (SCT) over the Eastern‐North Pacific (ENP), however, the lack of cloud in situ measurements gave limited information. Using the observations of Marine W‐band ARM cloud radar, ceilometer, and three‐channel microwave radiometer onboard the ship, we retrieve the single‐layer, low‐level cloud‐droplet effective radius and drizzle median radius (rc and rm,d), number concentration (Nc and Nd), and liquid water content (LWCc and LWCd) using the methods in Wu et al. (2020, https://doi.org/10.1029/2019JD032205). Based on the results during MAGIC, we found that both cloud base and top heights increase approximately 0.75 km from Los Angeles (LA) until cloud breakup (CB) before leveling off. Low cloud fractions (CFs) ranged from ∼85% halfway between LA and CB to ∼20% near Hawaii. Retrieved rc values decreased approximately 2 μm from peak CF to Hawaii while rm,d increased more than 20 μm over the same path. Mean values of rc, rm,d, Nc, Nd, LWCc, and LWCd during MAGIC are 12.1 μm, 55.8 μm, 97.9 cm−3, 0.09 cm−3, 0.40 g m−3, and 0.05 g m−3, respectively. Compared to the mean values over the Azores in Wu et al. (2020, https://doi.org/10.1029/2019JD032205), the mean cloud and drizzle microphysical properties during MAGIC, except LWCd which is roughly equal, are greater due to higher liquid water path and warmer sea surface temperature. This information allows for a better understanding of the SCT over the ENP and can be used to better improve model simulations.

Reducing misclassified precipitation phase in conceptual models using cloud base heights and relative humidity to adjust air temperature thresholds

Abstract In cold region, conceptual models assigned precipitation phase, liquid (rain) or solid (snow), cause vastly different atmospheric, hydrological, and ecological responses, along with significant differences in evaporation, runoff, and infiltration fates for measured precipitation mass. A set air temperature threshold (ATT) applied to the over 30% annual precipitation events occurring with surface air temperatures between −3 and 5 °C resulted in 11.0 and 9.8% misclassified precipitation in Norway and Sweden, respectively. Surface air temperatures do not account for atmospheric properties causing precipitation phase changes as snow falls toward the ground. However, cloud base height and relative humidity (RH) measured from the surface can adjust ATT for expected hydrometeor-atmosphere interactions. Applying calibrated cloud base height ATTs or a linear RH function for Norway (Sweden) reduced misclassified precipitation by 4.3% (2.8%) and 14.6% (8.9%) misclassified precipitation, respectively. Cloud base height ATTs had lower miss-rates with low cloud bases, 100 m in Norway and 300 m in Sweden. Combining the RH method with cloud base ATT in low cloud conditions resulted in 16.1 and 10.8% reduction in misclassified precipitation in Norway and Sweden, respectively. Therefore, the conceptual model output should improve through the addition of available surface data without coupling to an atmospheric model.

Cloud vertical structure measurements from a ground-based cloud radar over the southeastern Tibetan Plateau

The southeastern Tibetan Plateau (TP) is the critical region of water vapor transport over the TP. Ground-based Ka-band cloud radar (KaCR) measurements collected at the Motuo National Climate Observatory in 2019 were used to analyze the physical properties of clouds at the front of the water vapor channel over the TP. The cloud top heights (CTHs) measured by the KaCR were verified through a comparison with observations from the Fengyun-4A (FY-4A) satellite at the same location. The KaCR-obtained CTHs were generally consistent with the FY-4A-obtained CTHs, although the KaCR slightly overestimated the CTHs of nonprecipitation clouds and underestimated the CTHs of precipitation clouds. Negative deviations between the KaCR- and FY-4A-obtained CTHs increased with rainfall rate. Cloud cover frequently occurred over Motuo, with an annual mean occurrence frequency of 65.3%. Clouds tended to form frequently at night and dissipate gradually in the daytime. Two peaks in the cloud base height (CBH) distribution were observed in Motuo, located at 0–1 km and 2–3 km, corresponding to precipitation and nonprecipitation clouds, respectively. The CTHs reached a peak at 6–7 km, which might be related to precipitation clouds. Moreover, a maximum CTH probability was observed in the midnight-early morning hours during the rainy season, while the CTH frequency peaked in the evening during the dry season. In addition, low and middle clouds were prevalent in Motuo for the period of observation in 2019. Understanding the characteristics of clouds over the TP will provide key validations of satellite measurements and promote research on cloud forces over the TP.

Detection of signals linked to climate change, land-cover change and climate oscillators in Tropical Montane Cloud Forests

Tropical Montane Cloud Forests (TMCFs) form biodiverse communities that are characterized by frequent occurrence of low-level clouds from which they capture a substantial proportion of their precipitation — here referred to as occult precipitation. TMCFs provide important ecosystem services, in particular the supply of water to their wider surroundings. Throughout the tropics (here 23.5∘ S to 23.5∘ N), they are under pressure from deforestation and poor land management which leads to loss of both forest area and species diversity, and reduces their capture of occult precipitation. Climate change may also reduce occult precipitation in TMCFs since the cloud base may lift in response to higher temperatures — the ‘lifting cloud-base hypothesis’. These threats to TMCFs are well understood, but their quantitative assessment is hampered by 1) uncertainty in the location and spatial extent of TMCFs and 2) limited availability of representative meteorological data. We use a Random Forest Classifier — informed by topographic data, MODIS vegetation data, TRMM precipitation data and ERA5-Land and MERRA-2 reanalysis products — to estimate the spatial distribution and extent of TMCFs (2.1 × 106 km2 ± 0.5 × 106 km2). We analyze temporal changes in climate, tree-cover and greenness of TMCFs over the past two to four decades to detect 1) multi-decadal trends, and 2) associations with the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Evidence for the ‘lifting cloud-base hypothesis’ in reanalysis products was inconsistent across the tropics; a lifting of the cloud base during the past four decades occurred for about 20% of TMCFs, predominantly in the Americas and a few locations in Africa, while in Asia a downward movement of the cloud base was found. However, these results in part depend on the bias correction applied to the reanalyses. Changes in TMCF tree cover and greenness varied by continent; in Africa in 50% of TMCFs tree cover declined, whereas TMCFs in the Americas and in Asia exhibited a net increase in tree cover, despite a reduction in tree cover in ~20% of these TMCFs. An important limitation of the tree-cover data is that they do not distinguish between natural tree cover and agro-forestry. ENSO signals were more strongly present in precipitation in American and Asian TMCFs, whereas IOD signals were stronger in TMCF temperature and dewpoint temperature across the tropics. ENSO and IOD signals were approximately equally important for precipitation in African TMCFs and in cloud-base height across the tropics. An arbitrary warming of 1 ∘C and a 100 m lifting of the cloud base, in accordance with the ‘lifting cloud hypothesis’, imposed on the Random Forest classifier showed a decline in the extent of TMCFs in the Americas and Africa, but an increase in Asia — mostly at the expense of evergreen broadleaf forests. The greater vulnerability of TMCFs in Africa may be linked to their more isolated and scattered distribution across the continent and drier conditions compared to a more continuous distribution and wetter conditions in the Americas and Asia.

Relationship between cloud vertical structures inferred from radiosonde humidity profiles and precipitation over Indonesia

Knowledge of cloud vertical structure, including the presence of multiple cloud layers, is important for several climate-related applications such as for understanding the impact of clouds on Earth’s radiation budget. Moreover, the vertical distribution of latent heat release that affects global circulation and precipitation. The characteristics of cloud vertical structure may change as a consequence of climate change. However, study on cloud vertical structure in Indonesia is limited to case study based on short period observation. This study aims to analyse the vertical structure of clouds, such as cloud base height (CBH), the height of the cloud top (CT) and the number of cloud layers due to climate change in Indonesia, based on ∼ 30 years radiosonde observation. The relation between cloud vertical structures and precipitation was investigated. We used the radiosonde data from nine observation stations in Indonesia. On an average, it is observed that over Indonesia one-layer clouds is most frequently observed cloud, more than 60% of the time. This number is much larger than the fraction of single layer clouds over the globe which is about 58 % of the time. The cloud vertical structures in Indonesia vary from month to month. The cloud vertical structure during wet and dry season is different which indicate a strong relationship between cloud vertical structure and precipitation.

Pyrocumulonimbus Firepower Threshold: Assessing the Atmospheric Potential for pyroCb

AbstractPyrocumulonimbus (pyroCb) clouds are difficult to predict and can produce extreme and unexpected wildfire behavior that can be very hazardous to fire crews. Many forecasters modify conventional thunderstorm diagnostics to predict pyroCb potential, by adding temperature (Δθ) and moisture increments (Δq) to represent smoke plume thermodynamics near the expected plume condensation level. However, estimating these Δθ and Δq increments is a highly subjective process that requires expert knowledge of all factors that might influence future fire size and intensity. In this paper, instead of trying to anticipate these Δθ and Δq increments for a particular fire, the minimum firepower required to generate pyroCb for a given atmospheric environment is considered. This concept, termed the pyroCb firepower threshold (PFT) requires only atmospheric information, removing the need for subjective estimates of the fire contribution. A simple approach to calculating PFT is presented that incorporates only basic plume-rise physics, yielding an analytic solution that offers important insight into plume behavior and pyroCb formation. Minimum increments of Δθ and Δq required for deep, moist convection, plus a minimum cloud-base height (zfc), are diagnosed on a thermodynamic diagram. Briggs’s plume rise equations are used to convert Δθ, zfc, and a mean horizontal wind speed U to a measure of the PFT: the minimum heat flux entering the base of the plume. This PFT is proportional to the product of U, Δθ, and the square of zfc. Plume behavior insights provided by the Briggs’s equations are discussed, and a selection of PFT examples presented.

Characterisation and surface radiative impact of Arctic low clouds from the IAOOS field experiment

Abstract. The Ice, Atmosphere, Arctic Ocean Observing System (IAOOS) field experiment took place from 2014 to 2019. Over this period, more than 20 instrumented buoys were deployed at the North Pole. Once locked into the ice, the buoys drifted for periods of a month to more than a year. Some of these buoys were equipped with 808 nm wavelength lidars which acquired a total of 1777 profiles over the course of the campaign. This IAOOS lidar dataset is exploited to establish a novel statistic of cloud cover and of the geometrical and optical characteristics of the lowest cloud layer. The average cloud frequency from April to December over the course of the campaign was 75 %. Cloud occurrence frequencies were above 85 % from May to October. Single layers are thickest in October/November and thinnest in the summer. Meanwhile, their optical depth is maximum in October. On the whole, the cloud base height is very low, with the great majority of first layer bases beneath 120 m. In April and October, surface temperatures are markedly warmer when the IAOOS profile contains at least one low cloud than when it does not. This temperature difference is statistically insignificant in the summer months. Indeed, summer clouds have a shortwave cooling effect which can reach −60 W m−2 and balance out their longwave warming effect.

GOFOS, ground optical fog observation system for monitoring the vertical stratocumulus-fog cloud distribution in the coast of the Atacama Desert, Chile

Studying fog requires a good understanding of both its horizontal and vertical distributions. Among these two, the vertical one is the most challenging to observe. Different methods have been adopted for observing this variable, among which the most commonly used are satellite datasets, together with airborne and meteorological surface observations. Yet, all these techniques present significant limitations as for spatial and temporal resolution when describing the vertical fog structure. In this manuscript, we introduce the Ground Optical Fog Observation System (GOFOS), a new method to describe the advective fog’s frequency and vertical distribution. This tool is based on in-situ optical observations, taking advantage of the topography of the Atacama Desert coastal mountains, where advective fog is frequent. During 2017, the GOFOS reported a fog presence <10% during summer and of ~50% during winter. Also, the GOFOS shows a diurnal variability of fog presence that decreases around noon and increases again starting from the afternoon. The vertical structure observed by the GOFOS shows a cloud depth of ~250 m, subject to diurnal and seasonal variabilities. By analyzing GOFOS results through a comparison with the ones obtained by standard observations, a ~93% agreement was found between the fog frequencies detected by the GOFOS and GOES. Also, we found a ~80% consistency between GOFOS fog frequency values and marine boundary layer regimes related to fog formation. Moreover, we observed that the cloud base height estimated by the GOFOS is correlated with the Iquique Airport ceilometer measurements (r = +0.6). Finally, the mean cloud top height estimated by the GOFOS differs by 8% from the Antofagasta Airport radio-soundings measurements. These results provide useful information for the selection of optimal sites for fog harvesting and for getting a better understanding of the interactions between fog and its ecosystem. In conclusion, through this study the GOFOS demonstrated its potential as a simple, reliable, and affordable method for systematic fog monitoring that might also be adapted to different topographic conditions.

Assessing the strength of climate and land-use influences on montane epiphyte communities.

Epiphytes, air plants that are structurally dependent on trees, are a keystone group in tropical forests; they support the food and habitat needs of animals and influence water and nutrient cycles. They reach peak diversity in humid montane forests. Climate predictions for Central American mountains include increased temperatures, altered precipitation seasonality, and increased cloud base heights, all of which may challenge epiphytes. Although remaining montane forests are highly fragmented, many tropical agricultural systems include trees that host epiphytes, allowing epiphyte communities to persist even in landscapes with lower forest connectivity. I used structural equations models to test the relative effects of climate, land use, tree characteristics, and biotic interactions on vascular epiphyte diversity with data from 31 shade coffee farms and 2 protected forests in northern Nicaragua. I also tested substrate preferences of common species with randomization tests. Tree size, tree diversity, and climate all affected epiphyte richness, but the effect of climate was almost entirely mediated by bryophyte cover. Bryophytes showed strong sensitivity to mean annual temperature and insolation. Many ferns and some orchids were positively associated with bryophyte mats, whereas bromeliads tended to establish among lichen or on bare bark. The tight relationships between bryophytes and climate and between bryophytes and vascular epiphytes indicated that relatively small climate changes could result in rapid, cascading losses of montane epiphyte communities. Currently, shade coffee farms can support high bryophyte cover and diverse vascular epiphyte assemblages when larger, older trees are present. Agroforests serve as valuable reservoirs for epiphyte biodiversity and may be important early-warning systems as the climate changes.

A Bimodal Diagnostic Cloud Fraction Parameterization. Part II: Evaluation and Resolution Sensitivity

AbstractA wide range of approaches exists to account for subgrid cloud variability in regional simulations of the atmosphere. This paper addresses the following questions: 1) Is there still benefit in representing subgrid variability of cloud in convection-permitting simulations? 2) What is the sensitivity to the cloud fraction parameterization complexity? 3) Are current cloud fraction parameterizations scale-aware across convection-permitting resolutions? These questions are addressed for regional simulations of a 6-week observation campaign in the U.S. southern Great Plains. Particular attention is given to a new diagnostic cloud fraction scheme with a bimodal subgrid saturation-departure PDF, described in Part I. The model evaluation is performed using ground-based remote sensing synergies, satellite-based retrievals, and surface observations. It is shown that not using a cloud fraction parameterization results in underestimated cloud frequency and water content, even for stratocumulus. The use of a cloud fraction parameterization does not guarantee improved cloud property simulations, however. Diagnostic and prognostic cloud schemes with a symmetric subgrid saturation-departure PDF underestimate cloud fraction and cloud optical thickness, and hence overestimate surface shortwave radiation. These schemes require empirical bias-correction techniques to improve the cloud cover. The new cloud fraction parameterization, introduced in Part I, improves cloud cover, liquid water content, cloud-base height, optical thickness, and surface radiation compared to schemes reliant on a symmetric PDF. Furthermore, cloud parameterizations using turbulence-based, rather than prescribed constant subgrid variances, are shown to be more scale-aware across convection-permitting resolutions.

Long-Term Change in Characteristics of Cloud Vertical Structures Over Sumatra from Radiosonde Observations

Study on the vertical structure of cloud in Indonesia in terms of climate change is still very limited. We investigated the long-term change in characteristics of cloud vertical structures over Sumatra from three radiosonde observation stations in this work. The cloud base height (CBH), cloud top height (CT), and the number of cloud layers were retrieved using relative humidity (RH) profiles from radiosonde observation. The height of the cloud base is determined by taking the height of the layer with relative humidity (RH) value &gt; 84% with at least a 3% jump in the RH from the ground level. Sumatra’s most frequently observed cloud layer is a one-layer cloud with an average occurrence rate of &gt; 60%, which is slightly larger than the one-layer cloud globally. The percentage of appearance values at the Padang station, Pangkal Pinang, and Medan are 63.58%, 69.50% and 66.05%. The appearance of low-level clouds also dominates in Sumatra compared to other cloud types. CT and CBH increase with the number of years including all seasons. This is in line with the increase in temperature in Indonesia reported by previous researchers. On the other hand, the clouds’ thickness, especially for the cloud with one layer, varies from one location to another. The thickness of clouds decreases at Padang station and does not change at Pangkal Pinang and Medan stations.

Cloud occurrence frequency and cloud liquid water path for non-precipitating clouds using ground-based measurements over central China

Ground-based microwave radiometer (MWR) is with ability to measure liquid water path (LWP) and cloud base height (CBH) with the aid of infrared thermometer (IRT) under all skies. Using the 6-year MWR observations at Wuhan (WH), Xianning (XN) and Jingzhou (JZ) in central China, variations of cloud occurrence frequency (COF) and LWP as well as vertical structure of COF for non-precipitating clouds are investigated. The COFs of middle and high clouds are high in summer and low in winter, and low clouds show very minimum seasonal variations over all three sites. The total COF can reach to 94% in summer and decrease to 37% in winter. Low clouds have high COF in daytime and low COF in nighttime, yet it is opposite for middle clouds. A quasi-bimodal pattern is found in the annual variation of LWP, especially for middle clouds. The diurnal variation of LWP presents partly dependence on CBH. For high clouds, the high LWP in daytime and low LWP in nighttime become significant, showing obvious response to solar radiation. The mean LWPs at WH, XN and JZ are 0.322, 0.469 and 0.243 kg/m2, respectively, and the high LWP at XN may be related to the dynamic uplift of the nearby hills. Although the vertical structure of COF tends to be unimodal in autumn and bimodal in other seasons, there is a peak of COF always occurring at ~2.5 km. These results benefit the knowledge of cloud properties for non-precipitating clouds over central China.

Passive Remote Sensing of Ice Cloud Properties at Terahertz Wavelengths Based on Genetic Algorithm

Ice clouds play a critical role in the balance of the earth–atmosphere radiation system, but there are some limitations in the existing remote sensing methods for ice clouds. Terahertz wave is expected to be the best waveband for retrieving ice clouds, with terahertz wavelengths in the order of the size of typical ice cloud particles. An inversion method for the remote sensing of ice clouds at terahertz wavelengths based on genetic algorithm is proposed in this paper. First, suitable channel sets in the terahertz band, which are mainly a combination of absorption lines and window regions, are determined. Then, to improve the efficiency of the generation of the retrieval database, based on the brightness temperature simulated by the atmospheric radiative transfer simulator (ARTS) for different cloud parameters, a fast forward operator is constructed using three-dimensional interpolation to simulate the brightness temperature difference between clear sky and a cloudy scene. Finally, an inversion model to retrieve the ice cloud base height, the effective particle diameter and the ice water path is established based on the genetic algorithm, and an analysis of the inversion errors is performed. The results show that the forward operator, constructed by the nearest interpolation, can accurately calculate the brightness temperature difference at a high speed. The proposed inversion method at terahertz wavelengths based on the genetic algorithm can achieve the expected scientific requirement. The absolute error of the cloud height is around 0.2 km, and the absolute error of the low ice water path (below 20 g/m2) is small, while the relative error of the high ice water path is generally maintained at around 10%, and the absolute error of the effective particle diameter is mostly around 4 μm.

Cloud and Cloud-Shadow Detection for Applications in Mapping Small-Scale Mining in Colombia Using Sentinel-2 Imagery

Small-scale placer mining in Colombia takes place in rural areas and involves excavations resulting in large footprints of bare soil and water ponds. Such excavated areas comprise a mosaic of challenging terrains for cloud and cloud-shadow detection of Sentinel-2 (S2A and S2B) data used to identify, map, and monitor these highly dynamic activities. This paper uses an efficient two-step machine-learning approach using freely available tools to detect clouds and shadows in the context of mapping small-scale mining areas, one which places an emphasis on the reduction of misclassification of mining sites as clouds or shadows. The first step is comprised of a supervised support-vector-machine classification identifying clouds, cloud shadows, and clear pixels. The second step is a geometry-based improvement of cloud-shadow detection where solar-cloud-shadow-sensor geometry is used to exclude commission errors in cloud shadows. The geometry-based approach makes use of sun angles and sensor view angles available in Sentinel-2 metadata to identify potential directions of cloud shadow for each cloud projection. The approach does not require supplementary data on cloud-top or bottom heights nor cloud-top ruggedness. It assumes that the location of dense clouds is mainly impacted by meteorological conditions and that cloud-top and cloud-base heights vary in a predefined manner. The methodology has been tested over an intensively excavated and well-studied pilot site and shows 50% more detection of clouds and shadows than Sen2Cor. Furthermore, it has reached a Specificity of 1 in the correct detection of mining sites and water ponds, proving itself to be a reliable approach for further related studies on the mapping of small-scale mining in the area. Although the methodology was tailored to the context of small-scale mining in the region of Antioquia, it is a scalable approach and can be adapted to other areas and conditions.

Breakup of nocturnal low-level stratiform clouds during the southern West African monsoon season

Abstract. Within the framework of the DACCIWA (Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa) project and based on a field experiment conducted in June and July 2016, we analyze the daytime breakup of continental low-level stratiform clouds in southern West Africa. We use the observational data gathered during 22 precipitation-free occurrences at Savè, Benin. Our analysis, which starts from the stratiform cloud formation usually at night, focuses on the role played by the coupling between cloud and surface in the transition towards shallow convective clouds during daytime. It is based on several diagnostics, including the Richardson number and various cloud macrophysical properties. The distance between the cloud base height and lifting condensation level is used as a criterion of coupling. We also make an attempt to estimate the most predominant terms of the liquid water path budget in the early morning. When the nocturnal low-level stratiform cloud forms, it is decoupled from the surface except in one case. In the early morning, the cloud is found coupled with the surface in 9 cases and remains decoupled in the 13 other cases. The coupling, which occurs within the 4 h after cloud formation, is accompanied by cloud base lowering and near-neutral thermal stability in the subcloud layer. Further, at the initial stage of the transition, the stratiform cloud base is slightly cooler, wetter and more homogeneous in coupled cases. The moisture jump at the cloud top is usually found to be lower than 2 g kg−1 and the temperature jump within 1–5 K, which is significantly smaller than typical marine stratocumulus and explained by the monsoon flow environment in which the stratiform cloud develops over West Africa. No significant difference in liquid water path budget terms was found between coupled and decoupled cases. In agreement with previous numerical studies, we found that the stratiform cloud maintenance before sunrise results from the interplay between the predominant radiative cooling, entrainment and large-scale subsidence at its top. Three transition scenarios were observed depending on the state of coupling at the initial stage. In coupled cases, the low-level stratiform cloud remains coupled until its breakup. In five of the decoupled cases, the cloud couples with the surface as the lifting condensation level rises. In the eight remaining cases, the stratiform cloud remains hypothetically decoupled from the surface throughout its life cycle since the height of its base remains separated from the condensation level. In cases of coupling during the transition, the stratiform cloud base lifts with the growing convective boundary layer roughly between 06:30 and 08:00 UTC. The cloud deck breakup, occurring at 11:00 UTC or later, leads to the formation of shallow convective clouds. When the decoupling subsists, shallow cumulus clouds form below the stratiform cloud deck between 06:30 and 09:00 UTC. The breakup time in this scenario has a stronger variability and occurs before 11:00 UTC in most cases. Thus, we argue that the coupling with the surface during daytime hours has a crucial role in the low-level stratiform cloud maintenance and its transition towards shallow convective clouds.

Comparison of Cloud Vertical Structure Retrieved from Radiosonde and Millimeter Wave Cloud Radar

Owing to the synchronizing continuous observation of Ka-band millimeter-wave cloud radar (MMCR), L-band radiosonde, ceilometer, Himawari-8 satellite, and Total Sky Imager (TSI) from 13 December 2016 to 13 March 2017, at Beijing Nanjiao Weather Observatory (BNWO), the cloud vertical structure (CVS, including cloud bottom height, cloud top height, cloud layers, etc.) derived from radiosonde and MMCR is compared, and the causes of observation deviation are analyzed. The results show that cloud top heights observed by MMCR are lower by 422.0 m on average, while cloud base heights are higher by 350.7 m. Generally, there is a good consistency between them. The difference of physical theory, balloon drifting, attenuation of MMCR during precipitation, and the limitations of algorithm for retrieving CVS, among others, are found to be the main causes of the deviation.

Exploring the Potential of Statistical Modeling to Retrieve the Cloud Base Height from Geostationary Satellites: Applications to the ABI Sensor on Board of the GOES-R Satellite Series.

Although cloud base height is a relevant variable for many applications, including aviation, it is not routinely monitored by current geostationary satellites. This is probably a consequence of the difficulty of providing reliable estimations of the cloud base height from visible and infrared radiances from current imagers. We hypothesize that existing algorithms suffer from the accumulation of errors from upstream retrievals necessary to estimate the cloud base height, and that this hampers higher predictability in the retrievals to be achieved. To test this hypothesis, we trained a statistical model based on the random forest algorithm to retrieve the cloud base height, using as predictors the radiances from Geostationary Operational Environmental Satellites (GOES-16) and variables from a numerical weather prediction model. The predictand data consisted of cloud base height observations recorded at meteorological aerodrome report (METAR) stations over an extended region covering the contiguous USA. Our results indicate the potential of the proposed methodology. In particular, the performance of the cloud base height retrievals appears to be superior to the state-of-the-science algorithms, which suffer from the accumulation of errors from upstream retrievals. We also find a direct relationship between the errors and the mean cloud base height predicted over the region, which allowed us to obtain estimations of both the cloud base height and its error.