Thin Cirrus Research Articles

Climatology of Cirrus Clouds over Observatory of Haute-Provence (France) Using Multivariate Analyses on Lidar Profiles

This study aims to achieve the classification of the cirrus clouds over the Observatory of Haute-Provence (OHP) in France. Rayleigh–Mie–Raman lidar measurements, in conjunction with the ERA5 dataset, are analyzed to provide geometrical morphology and optical cirrus properties over the site. The method of cirrus cloud climatology presented here is based on a threefold classification scheme based on the cirrus geometrical and optical properties and their formation history. Principal component analysis (PCA) and subsequent clustering provide four morphological cirrus classes, three optical groups, and two origin-related categories. Cirrus clouds occur approximately 37% of the time, with most being single-layered (66.7%). The mean cloud optical depth (COD) is 0.39 ± 0.46, and the mean heights range around 10.8 ± 1.35 km. Thicker tropospheric cirrus are observed under higher temperature and humidity conditions than cirrus observed in the vicinity of the tropopause level. Monthly cirrus occurrences fluctuate irregularly, whereas seasonal patterns peak in spring. Concerning the mechanism of the formation, it is found that the majority of cirrus clouds are of in situ origin. The liquid-origin cirrus category consists nearly entirely of thick cirrus. Overall results suggest that in situ origin thin cirrus, located in the upper tropospheric and tropopause regions, have the most noteworthy occurrence over the site.

Correction of Thin Cirrus Absorption Effects in Landsat 8 Thermal Infrared Sensor Images Using the Operational Land Imager Cirrus Band on the Same Satellite Platform.

Data from the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS) instruments onboard the Landsat 8 and Landsat 9 satellite platforms are subject to contamination by cloud cover, with cirrus contributions being the most difficult to detect and mask. To help address this issue, a cirrus detection channel (Band 9) centered within the 1.375-μm water vapor absorption region was implemented on OLI, with a spatial resolution of 30 m. However, this band has not yet been fully utilized in the Collection 2 Landsat 8/9 Level 2 surface temperature data products that are publicly released by U.S. Geological Survey (USGS). The temperature products are generated with a single-channel algorithm. During the surface temperature retrievals, the effects of absorption of infrared radiation originating from the warmer earth's surfaces by ice clouds, typically located in the upper portion of the troposphere and re-emitting at much lower temperatures (approximately 220 K), are not taken into consideration. Through an analysis of sample Level 1 TOA and Level 2 surface data products, we have found that thin cirrus cloud features present in the Level 1 1.375-μm band images are directly propagated down to the Level 2 surface data products. The surface temperature errors resulting from thin cirrus contamination can be 10 K or larger. Previously, we reported an empirical and effective technique for removing thin cirrus scattering effects in OLI images, making use of the correlations between the 1.375-μm band image and images of any other OLI bands located in the 0.4-2.5 μm solar spectral region. In this article, we describe a variation of this technique that can be applied to the thermal bands, using the correlations between the Level 1 1.375-μm band image and the 11-μm BT image for the effective removal of thin cirrus absorption effects. Our results from three data sets acquired over spatially uniform water surfaces and over non-uniform land/water boundary areas suggest that if the cirrus-removed TOA 11-μm band BT images are used for the retrieval of the Level 2 surface temperature (ST) data products, the errors resulting from thin cirrus contaminations in the products can be reduced to about 1 K for spatially diffused cirrus scenes.

Evaluating the representation of Arctic cirrus solar radiative effects in the Integrated Forecasting System with airborne measurements

Abstract. In two case studies, airborne measurements of broadband solar irradiances above and below Arctic cirrus are compared to simulations of the Integrated Forecasting System (IFS) operated by the European Centre for Medium-Range Weather Forecasts (ECMWF) using offline runs of ECMWF's operational radiation scheme, “ecRad”. Furthermore, independent of the solar irradiances, cirrus properties are derived from collocated airborne active remote sensing observations to evaluate the optical and microphysical parameterizations in ecRad. The data were collected in the central Arctic over sea ice (81–90° N) with instrumentation installed aboard the High Altitude LOng range research aircraft (HALO) during a campaign in March and April 2022. Among others, the HALO instrumentation included upward- and downward-looking pyranometers to measure broadband solar irradiances, a cloud radar, and a multi-wavelength water vapour differential absorption lidar. Extended horizontal flight legs above and below single-layer cirrus were performed. The solar radiation measurements are used to evaluate ecRad in two case studies of optically thin and thick cirrus, with an average transmissivity of 0.9 and 0.6, respectively. Different ice optics parameterizations optionally available in ecRad are applied to test the match between simulation and measurements. Furthermore, the IFS-predicted ice water content and ice effective radius are replaced by values retrieved with the radar and lidar. The choice of ice optics parameterizations does not significantly improve the model–measurement agreement. However, introducing the retrieved ice microphysical properties brings measured and modelled irradiances in closer agreement for the optically thin cirrus, while the optically thick cirrus case is simulated as too thick. It is concluded that the ice water content simulated by the IFS is realistic and that the mismatch between observed and simulated solar irradiances mostly originates from the assumed or parameterized ice effective radius.

Extensive coverage of ultrathin tropical tropopause layer cirrus clouds revealed by balloon-borne lidar observations

Abstract. Tropical tropopause layer (TTL) clouds have a significant impact on the Earth's radiative budget and regulate the amount of water vapor entering the stratosphere. Estimating the total coverage of tropical cirrus clouds is challenging, since the range of their optical depth spans several orders of magnitude, from thick opaque cirrus detrained from convection to sub-visible clouds just below the stratosphere. During the Strateole-2 observation campaign, three microlidars were flown on board stratospheric superpressure balloons from October 2021 to late January 2022, slowly drifting only a few kilometers above the TTL. These measurements have unprecedented sensitivity to thin cirrus and provide a fine-scale description of cloudy structures both in time and in space. Case studies of collocated observations with the spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) show very good agreement between the instruments and highlight the Balloon-borne Cirrus and convective overshOOt Lidar's (BeCOOL) higher detection sensitivity. Indeed, the microlidar is able to detect optically very thin clouds (optical depth τ<2×10-3) that are undetected by CALIOP. Statistics on cloud occurrence show that TTL cirrus appear in about 50 % of the microlidar profiles and have a mean geometrical depth of 1 km. Ultrathin TTL cirrus (τ<2×10-3) have a significant coverage (23 % of the profiles), and their mean geometrical depth is 0.5 km.

Properties of Cirrus Cloud Observed over Koror, Palau (7.3°N, 134.5°E), in Tropical Western Pacific Region

This study presented an analysis of the geometric and optical properties of cirrus clouds with data produced by Compact Cloud-Aerosol Lidar (ComCAL) over Koror, Palau (7.3°N, 134.5°E), in the Tropical Western Pacific region. The lidar measurement dataset covers April 2018 to May 2019 and includes data collected during March, July and August 2022. The results show that cirrus clouds occur approximately 47.9% of the lidar sampling time, predominantly between altitudes of 15 and 18 km. Seasonal variations in cirrus top height closely align with those of the cold point tropopause. Most cirrus clouds exhibit low cloud optical depth (COD < 0.1), with an annual mean depolarization ratio of 31 ± 19%. Convective-forming cirrus clouds during the summer monsoon season exhibit a larger size by notably lower values in terms of color ratio. Extremely thin cirrus clouds (COD < 0.005) constituting 1.6% of total cirrus occurrences are frequently observed at 1–2 km above the cold point, particularly during winter and summer, suggesting significant stratosphere–troposphere exchange. The coldest and highest tropopause over Palau is persistent during winter, and related to the pathway of tropospheric air entering the stratosphere through the cold trap. In summer, the extremely thin cirrus above the cold point is likely correlated with equatorial Kelvin waves induced by western Pacific monsoon convection.

Introduction to the NJIAS Himawari-8/9 Cloud Feature Dataset for climate and typhoon research

Abstract. The use of remote sensing methods to accurately measure cloud properties and their spatiotemporal changes has been widely welcomed in many fields of atmospheric research. The Nanjing Joint Institute for Atmospheric Sciences (NJIAS) Himawari-8/9 Cloud Feature Dataset (HCFD) provides a comprehensive description of cloud features over the East Asia and west North Pacific regions for the 7-year period from April 2016 to December 2022. Multiple cloud variables, such as cloud mask, phase/type, top height, optical thickness, and particle effective radius, as well as snow, dust, and haze masks, were generated from the visible and infrared measurements of the Advanced Himawari Imager (AHI) on board the Japanese geostationary satellites Himawari-8 and Himawari-9 using a series of recently developed cloud retrieval algorithms. Verifications with the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) 1 km cloud layer product and the Moderate Resolution Imaging Spectroradiometer (MODIS) Level-2 cloud product (MYD06) demonstrate that the NJIAS HCFD gives higher skill scores than the Japanese Himawari-8/9 operational cloud product for all cloud variables except for cloud particle effective radius. The NJIAS HCFD even outperforms the MYD06 in nighttime cloud detection; cloud-top height, pressure, and temperature estimation; and infrared-only cloud-top phase determination. All evaluations are performed at the nominal 2 km scale, not including the effects of sub-pixel cloudiness or very thin cirrus. Two examples are presented to demonstrate applications of the NJIAS HCFD for climate and typhoon research. The NJIAS HCFD has been published in the Science Data Bank (https://doi.org/10.57760/sciencedb.09950, Zhuge 2023a; https://doi.org/10.57760/sciencedb.09953, Zhuge 2023b; https://doi.org/10.57760/sciencedb.09954, Zhuge 2023c; https://doi.org/10.57760/sciencedb.10158, Zhuge 2023d; https://doi.org/10.57760/sciencedb.09945, Zhuge 2023e).

Radiative effect of thin cirrus clouds in the extratropical lowermost stratosphere and tropopause region

Abstract. Cirrus clouds play an important role in the radiation budget of the Earth; nonetheless, the radiative effect of ultra-thin cirrus clouds in the tropopause region and in the lowermost stratosphere remains poorly constrained. These clouds have a small vertical extent and optical depth and are frequently neither observed even by sensitive sensors nor considered in climate model simulations. In addition, their short-wave (cooling) and long-wave (warming) radiative effects are often in approximate balance, and their net effect strongly depends on the shape and size of the cirrus particles. However, the CRyogenic Infrared Spectrometers and Telescopes for the Atmosphere instrument (CRISTA-2) allows ultra-thin cirrus clouds to be detected. Here we use CRISTA-2 observations in summer 1997 in the Northern Hemisphere midlatitudes together with the Suite Of Community RAdiative Transfer codes based on Edwards and Slingo (SOCRATES) radiative transfer model to calculate the radiative effect of observed ultra-thin cirrus. Using sensitivity simulations with different ice effective particle size and shape, we provide an estimate of the uncertainty in the radiative effect of ultra-thin cirrus in the extratropical lowermost stratosphere and tropopause region during summer and – by extrapolation of the summer results – for winter. Cloud top height and ice water content are based on CRISTA-2 measurements, while the cloud vertical thickness was predefined to be 0.5 or 2 km. Our results indicate that if the ice crystals of these thin cirrus clouds are assumed to be spherical, their net cloud radiative effect is generally positive (warming). In contrast, assuming aggregates or a hexagonal shape, their net radiative effect is generally negative (cooling) during summer months and very likely positive (warming) during winter. The radiative effect is in the order of ±(0.1–0.01) W m−2 for a realistic global cloud coverage of 10 %, similar to the magnitude of the contrail cirrus radiative forcing (of ∼ 0.1 W m−2). The radiative effect is also dependent on the cloud vertical extent and consequently the optically thickness and effective radius of the particle size distribution (e.g. effective radius increase from 5 to 30 µm results in a factor ∼ 6 smaller long- and short-wave effects, respectively). The properties of ultra-thin cirrus clouds in the lowermost stratosphere and tropopause region need to be better observed, and ultra-thin cirrus clouds need to be evaluated in climate model simulations.

The evolution of deep convective systems and their associated cirrus outflows

Abstract. Tropical deep convective clouds, particularly their large cirrus outflows, play an important role in modulating the energy balance of the Earth's atmosphere. Whilst the cores of these deep convective clouds have a significant short-wave (SW) cooling effect, they dissipate quickly. Conversely, the thin cirrus that flow from these cores can persist for days after the core has dissipated, reaching hundreds of kilometres in extent. These thin cirrus have a potential for large warming in the tropics. Understanding the evolution of air parcels from deep convection, clouds along these trajectories, and how they change in response to anthropogenic emissions is therefore important to understand past and future climate change. This work uses a novel approach to investigate the evolution of tropical convective clouds by introducing the concept of “time since convection” (TSC). This is used to build a composite picture of the lifecycle of air parcels from deep convection. Cloud properties are a strong function of TSC, showing decreases in the optical thickness, cloud-top height, and cloud fraction over time, thereby driving the latitudinal structure of cloudiness. After an initial dissipation of the convective core, changes in thin cirrus cloud amount were seen beyond 200 h from convection. Changes in cloud are shown to be a strong function of TSC and not simply reflective of latitudinal changes as air moves from the tropics to the extratropics. Finally, in the initial stages of convection there was a large net negative cloud radiative effect (CRE). However, once the convective core had dissipated, the sign of the CRE flipped and there was a sustained net warming CRE beyond 120 h from the convective event. Changes are present in the cloud properties long after the main convective activities have dissipated, signalling the need to continue further analysis at longer timescales than previously studied.

Tropical Convection Overshoots the Cold Point Tropopause Nearly as Often Over Warm Oceans as Over Land

AbstractTropical convection that overshoots the cold point tropopause can impact the climate by directly influencing water vapor, temperatures, and thin cirrus in the upper troposphere‐lower stratosphere (UTLS) region. The distribution of cold point overshoots between land and ocean may help determine how the overshoots will affect the UTLS in a changing climate. Using 4 years of satellite and reanalysis data, we test a brightness temperature proxy calibrated by radar/lidar data to identify cold point‐overshooting convection across the global tropics. We find evidence of cold point‐overshooting convection throughout the tropics, though other cirrus above the cold point cover an area 100 times larger than overshooting tops. Cold point‐overshooting convection occurs 30%–40% more often over convectively active land areas than over the warmest oceans. This proxy can be generalized to evaluate the fidelity of cold point overshoots simulated by storm‐resolving models.

All-Day Cloud Classification via a Random Forest Algorithm Based on Satellite Data from CloudSat and Himawari-8

It remains challenging to accurately classify complicated clouds owing to the various types of clouds and their distribution on multiple layers. In this paper, multi-band radiation information from the geostationary satellite Himawari-8 and the cloud classification product of the polar orbit satellite CloudSat from June to September 2018 are investigated. Based on sample sets matched by two types of satellite data, a random forest (RF) algorithm was applied to train a model, and a retrieval method was developed for cloud classification. With the use of this method, the sample sets were inverted and classified as clear sky, low clouds, middle clouds, thin cirrus, thick cirrus, multi-layer clouds and deep convection (cumulonimbus) clouds. The results indicate that the average accuracy for all cloud types during the day is 88.4%, and misclassifications mainly occur between low and middle clouds, thick cirrus clouds and cumulonimbus clouds. The average accuracy is 79.1% at night, with more misclassifications occurring between middle clouds, multi-layer clouds and cumulonimbus clouds. Moreover, Typhoon Muifa from 2022 was selected as a sample case, and the cloud type (CLT) product of an FY-4A satellite was used to examine the classification method. In the cloud system of Typhoon Muifa, a cumulonimbus area classified using the method corresponded well with a mesoscale convective system (MCS). Compared to the FY-4A CLT product, the classifications of ice-type (thick cirrus) and multi-layer clouds are effective, and the location, shape and size of these two varieties of cloud are similar.

Radiative heating and upwelling by different types of TTL clouds over the tropical convective regions

Tropical tropopause layer (TTL) clouds, defined as clouds whose tops are located above the tropopause level, play important roles in Earth's radiation balance and troposphere-to-stratosphere transport. Examining how different TTL cloud type gives influence on the radiative heating, we classified TTL clouds into three types (i.e., deep convective cloud, optically thick convective anvil cloud, and optically thin cirrus cloud) over the convectively active four tropical regions (i.e., Central Africa and South America continental regions and the Central and Western Pacific oceanic regions), using the combined Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat data. Using the classified cloud data, we first examined characteristics of the macrophysical and microphysical properties of the classified cloud types. Amongst three types of TTL clouds over selected four regions, thin cirrus clouds are most abundant (almost four-fifths), and approximately 7% and 17% of TTL clouds are deep convective cloud and thick convective anvil clouds, respectively. It is noted that the land–ocean contrast in TTL clouds appears weak in spite of well-known land–ocean contrast in the convection intensity, suggesting that TTL cirrus clouds may be dominated by in situ cirrus clouds. We further examined radiative heating over the TTL altitudes by each cloud type and the associated radiatively-driven upwelling motion. It is revealed that the dominant contribution to the overall radiative heating is from thin cirrus clouds (∼48.4%) because of their abundance. Nevertheless, convective anvil clouds and deep convective clouds are also found to give significant contribution to the radiative heating. Such cloud radiative heating tends to lower the level of zero net radiative heating rate found in the clear sky by ∼400–900 m. The TTL clouds play an important role in the secondary circulation in the TTL by inducing the upwelling motion throughout the TTL, supporting the mechanism that the radiative effect of TTL clouds can enhance the mass flux from the troposphere to the stratosphere.

Fusion of MISR Stereo Cloud Heights and Terra‐MODIS Thermal Infrared Radiances to Estimate Two‐Layered Cloud Properties

AbstractOur longest, stable record of cloud‐top pressure (CTP) and cloud‐top height (CTH) are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi‐Angle Imaging Spectroradiometer (MISR) on Terra. Because of single cloud‐layer assumptions in their standard algorithms, they provide only single CTP/CTH retrievals in multi‐layered situations. In the predominant multi‐layered regime of thin cirrus over low clouds, MODIS significantly overestimates cirrus CTP and emissivity, while MISR accurately retrieves low‐cloud CTH. Utilizing these complementary capabilities, we develop a retrieval algorithm for accurately determining both‐layer CTP and cirrus emissivity for such 2‐layered clouds, by applying the MISR low‐cloud CTH as a boundary condition to a modified MODIS CO2‐slicing retrieval. We evaluate our 2‐layered retrievals against collocated Cloud‐Aerosol Transport System (CATS) lidar observations. Relative to CATS, the mean bias of the upper cloud CTP and emissivity are reduced by ∼90% and ∼75% respectively in the new technique, compared to standard MODIS products. We develop an error model for the 2‐layered retrieval accounting for systematic and random errors. We find up to 87% of all residuals lie within modeled 95% confidence intervals, indicating a near‐closure of error budget. This reduction in error leads to a reduction in modeled atmospheric longwave radiative flux biases ranging between 5 and 40 W m−2, depending on the position and optical properties of the layers. Given this large radiative impact, we recommend that the pixel‐level 2‐layered MODIS + MISR fusion algorithm be applied over the entire MISR swath for the 22‐year Terra record, leading to a first‐of‐its‐kind 2‐layered cloud climatology from Terra's morning orbit.

Cloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products

Abstract. The EarthCARE (Earth Clouds, Aerosols and Radiation Explorer) satellite mission will provide new insights into aerosol–cloud–radiation interactions by means of synergistic observations of the Earth's atmosphere from a collection of active and passive remote sensing instruments, flying on a single satellite platform. The Multi-Spectral Imager (MSI) will provide visible and infrared images in the cross-track direction with a 150 km swath and a pixel sampling at 500 m. The suite of MSI cloud algorithms will deliver cloud macro- and microphysical properties complementary to the vertical profiles measured from the Atmospheric Lidar (ATLID) and the Cloud Profiling Radar (CPR) instruments. This paper provides an overview of the MSI cloud mask algorithm (M-CM) being developed to derive the cloud flag, cloud phase and cloud type products, which are essential inputs to downstream EarthCARE algorithms providing cloud optical and physical properties (M-COP) and aerosol optical properties (M-AOT). The MSI cloud mask algorithm has been applied to simulated test data from the EarthCARE end-to-end simulator and satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) as well as from the Spinning Enhanced Visible InfraRed Imager (SEVIRI). Verification of the MSI cloud mask algorithm to the simulated test data and the official cloud products from SEVIRI and MODIS demonstrates a good performance of the algorithm. Some discrepancies are found, however, for the detection of thin cirrus clouds over bright surfaces like desert or snow. This will be improved by tuning of the thresholds once real observations are available.

The classification of atmospheric hydrometeors and aerosols from the EarthCARE radar and lidar: the A-TC, C-TC and AC-TC products

Abstract. The EarthCARE mission aims to probe the Earth's atmosphere by measuring cloud and aerosol profiles using its active instruments, the Cloud Profiling Radar (CPR) and ATmospheric LIDar (ATLID). The correct identification of hydrometeors and aerosols from atmospheric profiles is an important step in retrieving the properties of clouds, aerosols and precipitation. Ambiguities in the nature of atmospheric targets can be removed using the synergy of collocated radar and lidar measurements, which is based on the complementary spectral response of radar and lidar relative to atmospheric targets present in the profiles. The instruments are sensitive to different parts of the particle size distribution and provide independent but overlapping information in optical and microwave wavelengths. ATLID is sensitive to aerosols and small cloud particles, and CPR is sensitive to large ice particles, snowflakes and raindrops. It is therefore possible to better classify atmospheric targets when collocated radar and lidar measurements exist compared to using a single instrument. The cloud phase, precipitation and aerosol type within the column sampled by the two instruments can then be identified. ATLID-CPR target classification (AC-TC) is the product created for this purpose by combining the ATLID target classification (A-TC) and CPR target classification (C-TC). AC-TC is crucial for the subsequent synergistic retrieval of cloud, aerosol and precipitation properties. AC-TC builds upon previous target classifications using CloudSat and CALIPSO synergy while providing richer target classification using the enhanced capabilities of EarthCARE's instruments, specifically CPR's Doppler velocity measurements to distinguish snow and rimed snow from ice clouds and ATLID's lidar ratio measurements to objectively discriminate between different aerosol species and optically thin ice clouds. In this paper, we first describe how the single-instrument A-TC and C-TC products are derived from ATLID and CPR measurements. Then the AC-TC product, which combines the A-TC and C-TC classifications using a synergistic decision matrix, is presented. Simulated EarthCARE observations based on combined cloud-resolving and aerosol model data are used to test the processors generating the target classifications. Finally, the target classifications are evaluated by quantifying the fractions of ice and snow, liquid clouds, rain, and aerosols in the atmosphere that can be successfully identified by each instrument and their synergy. We show that radar–lidar synergy helps better detect ice and snow, with ATLID detecting radiatively important optically thin cirrus and cloud tops, while CPR penetrates most deep and highly concentrated ice clouds. The detection of rain and drizzle is entirely due to C-TC, while that of liquid clouds and aerosols is due to A-TC. The evaluation also shows that simple assumptions can be made to compensate for when the instruments are obscured by extinction (ATLID) or surface clutter and multiple scattering (CPR); this allows for the recovery of the majority of liquid cloud not detected by the active instruments.

Convective organization and 3D structure of tropical cloud systems deduced from synergistic A-Train observations and machine learning

Abstract. We are building a 3D description of upper tropospheric (UT) cloud systems in order to study the relation between convection and cirrus anvils. For this purpose we used cloud data from the Atmospheric InfraRed Sounder and the Infrared Atmospheric Sounding Interferometer and atmospheric and surface properties from the meteorological reanalyses ERA-Interim and machine learning techniques. The different artificial neural network models were trained on collocated radar–lidar data from the A-Train in order to add cloud top height, cloud vertical extent and cloud layering, as well as a rain intensity classification to describe the UT cloud systems. The latter has an accuracy of about 65 % to 70 % and allows us to build objects of strong precipitation, used to identify convective organization. This rain intensity classification is more efficient to detect large latent heating than cold cloud temperature. In combination with a cloud system analysis, we found that deeper convection leads to larger heavy rain areas and a larger detrainment, with a slightly smaller thick anvil emissivity. This kind of analysis can be used for a process-oriented evaluation of convective precipitation parameterizations in climate models. Furthermore, we have shown the usefulness of our data to investigate tropical convective organization metrics. A comparison of different tropical convective organization indices and proxies to define convective areas has revealed that all indices show a similar annual cycle in convective organization, in phase with convective core height and anvil detrainment. The geographical patterns and magnitudes in radiative heating rate interannual changes with respect to one specific convective organization index (Iorg) for the period 2008 to 2018 are similar to the ones related to the El Niño–Southern Oscillation. However, since the interannual anomalies of the convective organization indices are very small and noisy, it was impossible to find a coherent relationship with those of other tropical mean variables such as surface temperature, thin cirrus area or subsidence area.

The PACE-MAPP algorithm: Simultaneous aerosol and ocean polarimeter products using coupled atmosphere-ocean vector radiative transfer

We describe the PACE-MAPP algorithm that simultaneously retrieves aerosol and ocean optical parameters using multiangle and multispectral polarimeter measurements from the SPEXone, Hyper-Angular Rainbow Polarimeter 2 (HARP2), and Ocean Color Instrument (OCI) instruments onboard the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) observing system. PACE-MAPP is adapted from the Research Scanning Polarimeter (RSP) Microphysical Aerosol Properties from Polarimetry (RSP-MAPP) algorithm. The PACE-MAPP algorithm uses a coupled vector radiative transfer model such that the atmosphere and ocean are always considered together as one system. Consequently, this physically consistent treatment of the system across the ultraviolet, (UV: 300–400 nm), visible (VIS: 400–700 nm), near-infrared (NIR: 700–1100 nm), and shortwave infrared (SWIR: 1100–2400 nm) spectral bands ensures that negative water-leaving radiances do not occur. PACE-MAPP uses optimal estimation to simultaneously characterize the optical and microphysical properties of the atmosphere’s aerosol and ocean constituents, find the optimal solution, and evaluate the uncertainties of each parameter. This coupled approach, together with multiangle, multispectral polarimeter measurements, enables retrievals of aerosol and water properties across the Earth’s oceans. The PACE-MAPP algorithm provides aerosol and ocean products for both the open ocean and coastal areas and is designed to be accurate, modular, and efficient by using fast neural networks that replace the time-consuming vector radiative transfer calculations in the forward model. We provide an overview of the PACE-MAPP framework and quantify its expected retrieval performance on simulated PACE-like data using a bimodal aerosol model for observations of fine-mode absorbing aerosols and coarse-mode sea salt particles. We also quantify its performance for observations over the ocean of dust-laden scenes using a trimodal aerosol model that incorporates non-spherical coarse-mode dust particles. Lastly, PACE-MAPP’s modular capabilities are described, and we discuss plans to implement a new ocean bio-optical model that uses a mixture of coated and uncoated particles, as well as a thin cirrus model for detecting and correcting for sub-visual ice clouds.

Determination of Cirrus Occurrence and Distribution Characteristics Over the Tibetan Plateau Based on the SWOP Campaign

AbstractBalloon sounding with the Compact Optical Backscatter Aerosol Detector (COBALD) and Frost Point hygrometers (FPs) provides in situ data for a better understanding of the vertical distribution of cirrus clouds. In this study, eight summer balloon‐borne measurements in Kunming (2012, 2014, 2015, and 2017) and Lhasa (2013, 2016, 2018, and 2020) over the Tibetan Plateau were used to show the distribution characteristics of cirrus clouds. Differences of cirrus occurrence were compared by different indices: the backscatter ratio (BSR) at a 455 nm/940 nm wavelength (BSR455 > 1.2/BSR940 > 2), the color index (CI > 7), and the relative humidity with respect to ice (RHice > 70%). Analysis of the profiles indicated that BSR455 > 1.2 was the optimal criterion to identify the cirrus layer and depict the distribution of the CI and RHice within cirrus clouds. The results showed that the median CI (RHice) within the cirrus clouds at both sites was mostly in the 18–20 (90%–110%) range at pressures below 120 hPa. Furthermore, the balloon‐borne measurements combined with Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements indicated a high frequency of cirrus occurrence near the tropopause in Kunming and Lhasa. The top height of cirrus occurrence at both sites was above the cold point tropopause and the lapse rate tropopause. Both Kunming and Lhasa had the highest frequency of thin cirrus clouds in the 0–0.4 km vertical cirrus thickness range.

The CHROMA cloud-top pressure retrieval algorithm for the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission

Abstract. This paper provides the theoretical basis and simulated retrievals for the Cloud Height Retrieval from O2 Molecular Absorption (CHROMA) algorithm. Simulations are performed for the Ocean Color Instrument (OCI), which is the primary payload on the forthcoming NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, and the Ocean Land Colour Instrument (OLCI) currently flying on the Sentinel 3 satellites. CHROMA is a Bayesian approach which simultaneously retrieves cloud optical thickness (COT), cloud-top pressure and height (CTP and CTH respectively), and (with a significant prior constraint) surface albedo. Simulated retrievals suggest that the sensor and algorithm should be able to meet the PACE mission goal for CTP error, which is ±60 mb for 65 % of opaque (COT ≥3) single-layer clouds on global average. CHROMA will provide pixel-level uncertainty estimates, which are demonstrated to have skill at telling low-error situations from high-error ones. CTP uncertainty estimates are well-calibrated in magnitude, although COT uncertainty is overestimated relative to observed errors. OLCI performance is found to be slightly better than OCI overall, demonstrating that it is a suitable proxy for the latter in advance of PACE's launch. CTP error is only weakly sensitive to correct cloud phase identification or assumed ice crystal habit/roughness. As with other similar algorithms, for simulated retrievals of multi-layer systems consisting of optically thin cirrus clouds above liquid clouds, retrieved height tends to be underestimated because the satellite signal is dominated by the optically thicker lower layer. Total (liquid plus ice) COT also becomes underestimated in these situations. However, retrieved CTP becomes closer to that of the upper ice layer for ice COT ≈3 or higher.

The VIIRS Cirrus Reflectance Algorithm.

The VIIRS instrument (Visible Infrared Imaging Radiometer Suite) on board the SNPP (Suomi National Polar-orbiting Partnership) satellite contains 11 narrow channels (M1-M11) in the 0.4-2.5 μm solar spectral region. The M9 channel is specifically designed for detecting thin cirrus clouds. It is centered at 1.378 μm with a width of 15 nm, which is located within a strong atmospheric water vapor band absorption region. In comparison with the corresponding MODIS Channel 26, the VIIRS M9 channel is narrower and more sensitive for cirrus detections. Because the radiances of the M9 channel over cirrus pixels are subjected to absorption by atmospheric water vapor molecules above and within the cirrus clouds, the water vapor absorption effect needs to be properly taken into consideration when using the M9 channel for quantitative removal of cirrus effects in other VIIRS channels in the 0.4-2.5 μm spectral range. In this article, we describe in detail an empirical technique for the retrieval of cirrus reflectances in the visible and near-IR (VNIR, 0.4-1.0 μm), where ice particles within cirrus clouds have negligible absorption effects, and in shortwave IR (SWIR, 1.0-2.5 μm) where ice particles' absorption effects are observed. The descriptions include all elements leading to the development of the operational VIIRS cirrus reflectance algorithm, the journal literature backing up the approach, theoretical descriptions of the algorithm's physics and mathematical background, and sample retrieval results from the VIIRS data. The SNPP VIIRS cirrus reflectance data products from 1 March 2012 to the present are available from a NASA data center.

The Role of Mineral Dust Aerosol Particles in Aviation Soot‐Cirrus Interactions

AbstractPredicting cirrus cloud properties with confidence requires a sound understanding of the relative roles of homogeneous and heterogeneous ice formation. This study explores the effect of mineral dust and contrail‐processed aviation soot particles as ice‐nucleating particles (INPs) competing with liquid solution droplets in cirrus formation. We study aerosol‐cirrus interactions by accounting for atmospheric variability in updraft speeds and INP number concentrations. Our results confirm the dominant role of mineral dust in ice nucleation events in cirrus clouds. In addition, we show that pre‐existing thin cirrus may suppress ice formation when updraft speeds are low. We find that homogeneous freezing of liquid solution droplets dominates clear‐sky aerosol‐cirrus interaction above a threshold updraft speed determined by total number concentrations and ice nucleation abilities of INPs. When mineral dust particles exceed number concentrations of 10 L−1, they reduce homogeneously nucleated ice crystal numbers significantly and even prevent homogeneous freezing for frequently observed local updraft speeds between 10 and 20 cm s−1. When both mineral dust and aviation soot particles coexist with solution droplets, dust typically prevents ice nucleation by aviation soot. Aviation soot exerts a notable impact on cirrus ice numbers only if updrafts are weak, large soot particles are present in number concentrations that are considerably higher than typically observed in emission measurements, and/or number concentrations of mineral dust and other INPs are low. Overall, our results elucidate the role of aviation soot‐cirrus interactions in the presence of other INP types.