Cloud Top Pressure Research Articles

The Top‐of‐Atmosphere, Surface and Atmospheric Cloud Radiative Kernels Based on ISCCP‐H Datasets: Method and Evaluation

AbstractThis study aims to create observation‐based cloud radiative kernel (CRK) datasets and evaluate them by direct comparison of CRK and the CRK‐derived cloud feedback datasets. Based on the International Satellite Cloud Climatology Project (ISCCP) H datasets, we calculate CRKs (called ISCCP‐FH or FH CRKs) as 2D joint function/histogram of cloud optical depth and cloud top pressure for shortwave (SW), longwave (LW), and their sum, Net, at the top of atmosphere (TOA), as well as, for the first time, at the surface (SFC) and in the atmosphere (ATM). With cloud fraction change (CFC) datasets from doubled‐CO2 simulation and short‐term observational anomalies, we derive all the TOA, SFC and ATM cloud feedback for SW, LW and Net using our CRKs.The direct comparison with modeled and observed CRKs (or cloud radiative effects), cloud feedback from previous model results and the Clouds and the Earth's Radiant Energy System products show that our CRKs and CRK‐derived cloud feedback are reasonably well validated. We estimate the uncertainty for the CRK‐derived cloud feedback and show that the CFC‐associated uncertainty contributes >98.5% of the total cloud feedback uncertainty while CRK's is very small. Our preliminary evaluation also shows that some near‐zero/small cloud feedback in the TOA‐alone feedback indeed results from the compensation of sizable cloud feedback of the SFC and ATM feedback and reveals some significant surface and atmospheric cloud feedback whose sum appears insignificant in TOA‐alone feedback. In addition, the atmospheric longwave cloud feedback seems to play a role in enhancing meridional atmospheric energy transport.

Improved cloud detection for the Aura Microwave Limb Sounder (MLS): training an artificial neural network on colocated MLS and Aqua MODIS data

Abstract. An improved cloud detection algorithm for the Aura Microwave Limb Sounder (MLS) is presented. This new algorithm is based on a feedforward artificial neural network and uses as input, for each MLS limb scan, a vector consisting of 1710 brightness temperatures provided by MLS observations from 15 different tangent altitudes and up to 13 spectral channels in each of 10 different MLS bands. The model has been trained on global cloud properties reported by Aqua's Moderate Resolution Imaging Spectroradiometer (MODIS). In total, the colocated MLS–MODIS data set consists of 162 117 combined scenes sampled on 208 d over 2005–2020. A comparison to the current MLS cloudiness flag used in “Level 2” processing reveals a huge improvement in classification performance. For previously unseen data, the algorithm successfully detects > 93 % of profiles affected by clouds, up from ∼ 16 % for the Level 2 flagging. At the same time, false positives reported for actually clear profiles are comparable to the Level 2 results. The classification performance is not dependent on geolocation but slightly decreases over low-cloud-cover regions. The new cloudiness flag is applied to determine average global cloud cover maps over 2015–2019, successfully reproducing the spatial patterns of mid-level to high clouds seen in MODIS data. It is also applied to four example cloud fields to illustrate its reliable performance for different cloud structures with varying degrees of complexity. Training a similar model on MODIS-retrieved cloud top pressure (pCT) yields reliable predictions with correlation coefficients > 0.82. It is shown that the model can correctly identify > 85 % of profiles with pCT < 400 hPa. Similar to the cloud classification model, global maps and example cloud fields are provided, which reveal good agreement with MODIS results. The combination of the cloudiness flag and predicted cloud top pressure provides the means to identify MLS profiles in the presence of high-reaching convection.

A correlational study on size differentiated aerosols on monsoonal and pre-monsoonal cloud properties over the Indo Gangetic Basin

Particle size is a critical parameter in deciding the cloud condensation nuclei activation efficiency and hence largely influential in the cloud formation and dynamics. Here we study the size differentiated influence of aerosol optical depth (AOD) on cloud properties for the densely polluted Indo-Gangetic Basin (IGB) for a period of 2000–2017 using satellite observations. Terra on board MISR derived AOD for two size ranges, small (aerodynamic radius < 0.35 μm) and large (aerodynamic radius > 0.7 μm) are correlated with MODIS derived cloud properties such as cloud fraction (CF), cloud optical thickness (COT), cloud top pressure (CTP) and cloud effective radius – liquid (CER-Liq) for monsoon and pre monsoon period, over the study area. Our study reveals that the size differentiated aerosols interacts differently with the cloud properties sometimes even contrarily. Small aerosol particles have shown better correlation with cloud properties than coarser particle. Furthermore, estimation of aerosol indirect effect has shown that small particles favour the Twomey effect while large particles follow the anti Twomey effect over the IGB. The anti Twomey effect for large particles i.e., positive AOD-CER relationship could be due to the elevated absorbing aerosol over the region causing aerosol induced heating of the cloud. In order to understand the aerosol characteristics over the IGB region, AERONET datasets from four IGB stations have been analysed, which indicated the presence of increased amount of coarser mode particles and absorbing aerosols over the study region. Aerosol-cloud interactions (ACI) are often overshadowed by internal cloud dynamics and upper air meteorology. Cloud segregated analysis using ISCCP classification suggests that the dominant clouds such as cirrostratus and altostratus influences the correlation statistics considerably. Partial correlation studies on four meteorological parameters (RH, vertical velocity, U and V component of wind) have revealed that ACI is also influenced by the upper air dynamics, particularly during monsoon.

EVALUATION OF CLOUDS, RADIATION, AND PRECIPITATION IN CMIP6 MODELS USING GLOBAL WEATHER STATES DERIVED FROM ISCCP-H CLOUD PROPERTY DATA

AbstractA clustering methodology is applied to cloud optical depth cloud top pressure (TAU-PC) histograms from the new, 1-degree resolution, ISCCP-H dataset, to derive an updated global Weather State (WS) dataset. Then, PC-TAU histograms from current-climate CMIP6 model simulations are assigned to the ISCCP-H WSs along with their concurrent radiation and precipitation properties, to evaluate model cloud, radiation, and precipitation properties in the context of the Weather States. The new ISCCP-H analysis produces WSs that are very similar to those previously found in the lower resolution ISCCP-D dataset. The main difference lies in the splitting of the ISCCP-D thin stratocumulus WS between the ISCCP-H shallow cumulus and stratocumulus WSs, which results in the reduction by one of the total WS number. The evaluation of the CMIP6 models against the ISCCP-H Weather States, shows that, in the ensemble mean, the models are producing an adequate representation of the frequency and geographical distribution of the WSs, with measurable improvements compared to the WSs derived for the CMIP5 ensemble. However, the frequency of shallow cumulus clouds continues to be underestimated, and, in some WSs the good agreement of the ensemble mean with observations comes from averaging models that significantly overpredict and underpredict the ISCCP-H WS frequency. In addition, significant biases exist in the internal cloud properties of the model WSs, such as the model underestimation of cloud fraction in middle-top clouds and secondarily in midlatitude storm and stratocumulus clouds, that result in an underestimation of cloud SW cooling in those regimes.

Classifying planetary cloudiness with an updated set of MODIS Cloud Regimes

AbstractWe present an updated Cloud Regime (CR) dataset based on Moderate resolution Imaging Spectroradiometer (MODIS) Collection 6.1 cloud products, specifically joint histograms that partition cloud fraction within distinct combinations of cloud top pressure and cloud optical thickness ranges. The paper focuses on an edition of the CR dataset derived from our own aggregation of MODIS pixel-level cloud retrievals on an equal area grid and pre-specified 3-hour UTC intervals that spatiotemporally match International Satellite Cloud Climatology Project (ISCCP) gridded cloud data. The other edition comes from the 1-degree daily aggregation provided by standard MODIS Level-3 data, as in previous versions of the MODIS CRs, for easier use with datasets mapped on equal angle grids. Both editions consist of 11 clusters whose centroids are nearly identical.We provide a physical interpretation of the new CRs and aspects of their climatology that have not been previously examined, such as seasonal and interannual variability of CR frequency of occurrence. We also examine the makeup and precipitation properties of the CRs assisted by independent datasets originating from active observations, and provide a first glimpse of how MODIS CRs relate to clouds as seen by ISCCP.

Spectral and synoptic analysis of Haboob in Tehran, Iran

On 2 June 2014, a Haboob dust storm occurred in Tehran, which lasted less than 2 h, caused severe damages to the properties and involved loss of human life. This paper describes the behavior of this Haboob dust storm, by analyzing of metrological satellites data, as well as assessing the mesoscale and microscale patterns that led to the occurrence of the dust. A dust detection scheme was developed to monitor the dust formation using the Infrared (IR) channels of the Spinning-Enhanced Visible and Infrared Imager (SEVIRI), carried on board MSG satellites. Restrictive thresholds were placed on the individual components to maximize detection success, and to minimize the misidentification of dust. The results indicated cold and strong downdrafts along with the cold front activity during the maximum temperature over the central hot desert caused a strengthened and intensified wind velocity that led to a strong Haboob in Tehran province. The synoptic analysis indicated that a low-pressure system stretching from the southeast of Iran to the northwest of Iran and Iraq was the dominant feature, despite the presence of a weak high-pressure in the center of Iran. The satellite analysis indicates an extreme dustiness discernible in the southwest of Tehran following the formation of a convective storm; however, uncertainty in dust identification increases as the IR dust signal weakens because of underlying dust cloud beneath the thick convective clouds. The analysis of could physical properties reveals the formation of a convective storm after dramatically decrease in cloud top temperature (CTT) and cloud top pressure (CTP), and increasing the cloud optical depth (COT) which led to development of an overshooting cold cloud over Tehran province before dust formation.

Cloud-Precipitation Hybrid Regimes and their Projection onto IMERG Precipitation Data

AbstractIn order to better understand cloud-precipitation relationships, we extend the concept of cloud regimes (CRs) developed from two-dimensional joint histograms of cloud optical thickness and cloud top pressure from the Moderate Resolution Imaging Spectroradiometer (MODIS), to include precipitation information. Taking advantage of the high-resolution Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation dataset, we derive cloud-precipitation “hybrid” regimes by implementing a k-means clustering algorithm with advanced initialization and objective measures to determine the optimal number of clusters. By expressing the variability of precipitation rates within 1-degree grid cells as histograms and varying the relative weight of cloud and precipitation information in the clustering algorithm, we obtain several editions of hybrid cloud-precipitation regimes (CPRs), and examine their characteristics.In the deep tropics, when precipitation is weighted weakly, the cloud part centroids of the hybrid regimes resemble their counterparts of cloud-only regimes, but combined clustering tightens the cloud-precipitation relationship by decreasing each regime’s precipitation variability. As precipitation weight progressively increases, the shape of the cloud part centroids becomes blunter, while the precipitation part sharpens. When cloud and precipitation are weighted equally, the CPRs representing high clouds with intermediate to heavy precipitation exhibit distinct enough features in the precipitation parts of the centroids to allow us to project them onto the 30-min IMERG domain. Such a projection overcomes the temporal sparseness of MODIS cloud observations associated with substantial rainfall, suggesting great application potential for convection-focused studies where characterization of the diurnal cycle is essential.

Convection over the eastern equatorial Indian Ocean and Iranian branch of Asian summer monsoon anticyclone modulates the wet and dry phases of summer monsoon rainfall over Kerala

AbstractThis study examined factors affecting wet and dry phases of monsoon rainfall over Kerala, using modern‐era retrospective analysis for research and applications (MERRA 2) data set. Based on circulation pattern, our study shows that the wet and dry phases of monsoon over Kerala are related to modulation of convective activity over the eastern equatorial Indian Ocean (EEIO) and the Iranian branch (Western flank) of Asian Summer monsoon anticyclone (ASMA). Outgoing longwave radiation (OLR) and cloud top pressure (CTP) show an anomalous dipole (quadrupole) pattern over the Equatorial Indian Ocean (EIO) during the wet (dry) phase of Kerala summer monsoon rainfall (KSMR). We found that KSMR is enhanced during intensification of the Iranian branch of ASMA and suppressed by anomalous deep convection over the EEIO. Further, anomalous lower level cyclonic circulation over the Western North Pacific (WNP) is pulling low‐level jet (LLJ) through Southern Peninsular India, hence playing a vital role in establishing the KSMR wet phase. Contrarily, the dry phase of KSMR is associated with weakening of the Iranian branch of ASMA in the upper level.

Changes in HIRS Detection of Cloud over Australia from 1985 to 2001

A long-term archive of cloud properties (cloud top pressure, CTP; and cloud effective emissivity, ε) determined from High-resolution Infrared Radiation Sounder (HIRS) data is investigated for evidence of regional cloud cover change. In the 17 years between 1985 and 2001, different cloud types are analysed over the Australian region (10° S–45° S, 105° E–160° E) and areas of change in total cloud frequency examined. Total cloud frequency change over the Australian region between two adjacent eight-year time periods (1994 to 2001 minus 1985 to 1992) shows the largest increases (ranges between 6% and 12%) of average HIRS total cloud cover occurring over the offshore regions to the northwest and northeast of the continent. Over land, the largest reduction of average HIRS total cloud frequency is in the southwestern region of Australia (between 2% and 8%). Through central Australia, there is a 2% to 7% increase in average HIRS total cloud frequency when comparing these eight-year periods. This paper examines the regional cloud changes in 17 years over Australia that are embedded in global cloud statistics. Examining total HIRS cloud cover frequency over Australia and comparing two different eight-year time periods, has highlighted notable areas of average change. Preliminary reporting of satellite-derived HIRS cloud products and Global Precipitation Climatology Project (GPCP) rainfall products during La Niña seasons between 1985 and 2001 has also been undertaken.

A Fast Retrieval of Cloud Parameters Using a Triplet of Wavelengths of Oxygen Dimer Band around 477 nm

Clouds act as a major reflector that changes the amount of sunlight reflected to space. Change in radiance intensity due to the presence of clouds interrupts the retrieval of trace gas or aerosol properties from satellite data. In this paper, we developed a fast and robust algorithm, named the fast cloud retrieval algorithm, using a triplet of wavelengths (469, 477, and 485 nm) of the O2–O2 absorption band around 477 nm (CLDTO4) to derive the cloud information such as cloud top pressure (CTP) and cloud fraction (CF) for the Geostationary Environment Monitoring Spectrometer (GEMS). The novel algorithm is based on the fact that the difference in the optical path through which light passes with regard to the altitude of clouds causes a change in radiance due to the absorption of O2–O2 at the three selected wavelengths. To reduce the time required for algorithm calculations, the look-up table (LUT) method was applied. The LUT was pre-constructed for various conditions of geometry using Vectorized Linearized Discrete Ordinate Radiative Transfer (VLIDORT) to consider the polarization of the scattered light. The GEMS was launched in February 2020, but the observed data of GEMS have not yet been widely released. To evaluate the performance of the algorithm, the retrieved CTP and CF using observational data from the Global Ozone Monitoring Experiment-2 (GOME-2), which cover the spectral range of GEMS, were compared with the results of the Fast Retrieval Scheme for Clouds from the Oxygen A band (FRESCO) algorithm, which is based on the O2 A-band. There was good agreement between the results, despite small discrepancies for low clouds.

Data Validation and Mesoscale Assimilation of Himawari-8 Optimal Cloud Analysis Products

AbstractHimawari-8 optimal cloud analysis (OCA), which employs all 16 channels of the Advanced Himawari Imager, provides cloud properties such as cloud phase, top pressure, optical thickness, effective radius, and water path. By using OCA, the water vapor distribution can be inferred with high spatiotemporal resolution and with a wide coverage, including over the ocean, which can be useful for improving initial states for prediction of the torrential rainfalls that occur frequently in Japan. OCA products were first evaluated by comparing them with different kinds of datasets (surface, sonde, and ceilometer observations) and with model outputs, to determine their data characteristics. Overall, OCA data were consistent with observations of water clouds with moderate optical thicknesses at low to midlevels. Next, pseudorelative humidity data were derived from the OCA products, and utilized in assimilation experiments of a few heavy rainfall cases, conducted with the Japan Meteorological Agency’s nonhydrostatic model–based Variational Data Assimilation System. Assimilation of OCA pseudorelative humidities caused there to be significant differences in the initial conditions of water vapor fields compared to the control, especially where OCA clouds were detected, and their influence lasted relatively long in terms of forecast hours. Impacts of assimilation on other variables, such as wind speed, were also seen. When the OCA data successfully represented low-level inflows from over the ocean, they positively impacted precipitation forecasts at extended forecast times.

Development of CO2 Band-Based Cloud Emission and Scattering Indices and Their Applications to FY-3D Hyperspectral Infrared Atmospheric Sounder

The Hyperspectral Infrared Atmospheric Sounder (HIRAS) onboard the Feng Yun-3D (FY-3D) satellite is the first Chinese hyperspectral infrared instrument. In this study, an improved cloud detection scheme using brightness temperature observations from paired HIRAS long-wave infrared (LWIR) and short-wave infrared (SWIR) channels at CO2 absorption bands (15-μm and 4.3-μm) is developed. The weighting function broadness and a set of height-dependent thresholds of cloud-sensitive-level differences are incorporated into pairing LWIR and SWIR channels. HIRAS brightness temperature observations made under clear-sky conditions during a training period are used to develop a set of linear regression equations between paired LWIR and SWIR channels. Moderate-resolution Imaging Spectroradiometer (MODIS) cloud mask data are used for selecting HIRAS clear-sky observations. Cloud Emission and Scattering Indices (CESIs) are defined as the differences in SWIR channels between HIRAS observations and regression simulations from LWIR observations. The cloud retrieval products of ice cloud optical depth and cloud-top pressure from the Atmospheric Infrared Sounder (AIRS) are used to illustrate the effectiveness of the proposed cloud detection scheme for FY-3D HIRAS observations. Results show that the distributions of modified CESIs at different altitudes can capture features in the distributions of AIRS-retrieved ice cloud optical depth and cloud-top pressure better than the CESIs obtained by the original method.

Transmission Spectroscopy for the Warm Sub-Neptune HD 3167c: Evidence for Molecular Absorption and a Possible High-metallicity Atmosphere

Abstract We present a transmission spectrum for the warm (500−600 K) sub-Neptune HD 3167c obtained using the Hubble Space Telescope Wide Field Camera 3 infrared spectrograph. We combine these data, which span the 1.125–1.643 μm wavelength range, with broadband transit measurements made using Kepler/K2 (0.6–0.9 μm) and Spitzer/IRAC (4–5 μm). We find evidence for absorption by at least one of H2O, HCN, CO2, and CH4 (Bayes factor 7.4; 2.5σ significance), although the data precision does not allow us to unambiguously discriminate between these molecules. The transmission spectrum rules out cloud-free hydrogen-dominated atmospheres with metallicities ≤100× solar at &gt;5.8σ confidence. In contrast, good agreement with the data is obtained for cloud-free models assuming metallicities &gt;700× solar. However, for retrieval analyses that include the effect of clouds, a much broader range of metallicities (including subsolar) is consistent with the data, due to the degeneracy with cloud-top pressure. Self-consistent chemistry models that account for photochemistry and vertical mixing are presented for the atmosphere of HD 3167c. The predictions of these models are broadly consistent with our abundance constraints, although this is primarily due to the large uncertainties on the latter. Interior structure models suggest that the core mass fraction is &gt;40%, independent of a rock or water core composition, and independent of atmospheric envelope metallicity up to 1000× solar. We also report abundance measurements for 15 elements in the host star, showing that it has a very nearly solar composition.

Tropical Cyclone Temperature Profiles and Cloud Macro-/Micro-Physical Properties Based on AIRS Data

We used the observations from Atmospheric Infrared Sounder (AIRS) onboard Aqua over the northwest Pacific Ocean from 2006–2015 to study the relationships between (i) tropical cyclone (TC) temperature structure and intensity and (ii) cloud macro-/micro-physical properties and TC intensity. TC intensity had a positive correlation with warm-core strength (correlation coefficient of 0.8556). The warm-core strength increased gradually from 1 K for tropical depression (TD) to &gt;15 K for super typhoon (Super TY). The vertical areas affected by the warm core expanded as TC intensity increased. The positive correlation between TC intensity and warm-core height was slightly weaker. The warm-core heights for TD, tropical storm (TS), and severe tropical storm (STS) were concentrated between 300 and 500 hPa, while those for typhoon (TY), severe typhoon (STY), and Super TY varied from 200 to 350 hPa. Analyses of the cloud macro-/micro-physical properties showed that the top of TC cloud systems mainly consisted of ice clouds. For TCs of all intensities, areas near the TC center showed lower cloud-top pressures and lower cloud-top temperatures, more cloud fractions, and larger ice-cloud effective diameters. With the increase in TC intensity, the levels of ice clouds around the TC center became higher and the spiral cloud-rain bands became larger. When a TC developed into a TY, STY, or Super TY, the convection in the clouds was stronger, releasing more heat, thus forming a much warmer warm core.

ACCESS: Confirmation of No Potassium in the Atmosphere of WASP-31b

Abstract We present a new optical (400–950 nm) transmission spectrum of the hot Jupiter WASP-31b (M = 0.48 M J; R = 1.54 R J; P = 3.41 days), obtained by combining four transit observations. These transits were observed with IMACS on the Magellan Baade Telescope at Las Campanas Observatory as part of the ACCESS project. We investigate the presence of clouds/hazes in the upper atmosphere of this planet, as well as the contribution of stellar activity on the observed features. In addition, we search for absorption features of the alkali elements Na i and K i, with particular focus on K i, for which there have been two previously published disagreeing results. Observations with Hubble Space Telescope (HST)/STIS detected K i, whereas ground-based low- and high-resolution observations did not. We use equilibrium and nonequilibrium chemistry retrievals to explore the planetary and stellar parameter space of the system with our optical data combined with existing near-IR observations. Our best-fit model is that with a scattering slope consistent with a Rayleigh slope ( ), high-altitude clouds at a log cloud top pressure of −3.6 bars, and possible muted H2O features. We find that our observations support other ground-based claims of no K i. Clouds are likely why signals like H2O are extremely muted and Na or K cannot be detected. We then juxtapose our Magellan/IMACS transmission spectrum with existing VLT/FORS2, HST/WFC3, HST/STIS, and Spitzer observations to further constrain the optical-to-infrared atmospheric features of the planet. We find that a steeper scattering slope (α = 8.3 ± 1.5) is anchored by STIS wavelengths blueward of 400 nm and only the original STIS observations show significant potassium signal.

Cloud-top pressure retrieval with DSCOVR EPIC oxygen A- and B-band observations

Abstract. An analytic transfer inverse model for Earth Polychromatic Imaging Camera (EPIC) observations is proposed to retrieve the cloud-top pressure (CTP) with the consideration of in-cloud photon penetration. In this model, an analytic equation was developed to represent the reflection at the top of the atmosphere from above cloud, in cloud, and below cloud. The coefficients of this analytic equation can be derived from a series of EPIC simulations under different atmospheric conditions using a nonlinear regression algorithm. With estimated cloud pressure thickness, the CTP can be retrieved from EPIC observation data by solving the analytic equation. To simulate the EPIC measurements, a program package using the double-k approach was developed. Compared to line-by-line calculation, this approach can calculate high-accuracy results with a 100-fold computation time reduction. During the retrieval processes, two kinds of retrieval results, i.e., baseline CTP and retrieved CTP, are provided. The baseline CTP is derived without considering in-cloud photon penetration, and the retrieved CTP is derived by solving the analytic equation, taking into consideration in-cloud and below-cloud interactions. The retrieved CTPs for the oxygen A and B bands are smaller than their related baseline CTP. At the same time, both baseline CTP and retrieved CTP at the oxygen B band are larger than those at the oxygen A band. Compared to the difference in baseline CTP between the B band and A band, the difference in retrieved CTP between these two bands is generally reduced. Out of around 10 000 cases, in retrieved CTP between the A and B bands we found an average bias of 93 mb with a standard deviation of 81 mb. The cloud layer top pressure from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements is used for validation. Under single-layer cloud situations, the retrieved CTPs for the oxygen A band agree well with the CTPs from CALIPSO, the mean difference of which within 5 mb in the case study. Under multiple-layer cloud situations, the CTPs derived from EPIC measurements may be larger than the CTPs of high-level thin clouds due to the effect of photon penetration.

Optical Transmission Spectroscopy of the Terrestrial Exoplanet LHS 3844b from 13 Ground-based Transit Observations

Abstract Atmospheric studies of spectroscopically accessible terrestrial exoplanets lay the groundwork for comparative planetology between these worlds and the solar system terrestrial planets. LHS 3844b is a highly irradiated terrestrial exoplanet (R = 1.303 ± 0.022R ⊕) orbiting a mid-M dwarf 15 parsecs away. Work based on near-infrared Spitzer phase curves ruled out atmospheres with surface pressures ≥10 bars on this planet. We present 13 transit observations of LHS 3844b taken with the Magellan Clay telescope and the LDSS3C multi-object spectrograph covering 620–1020 nm. We analyze each of the 13 data sets individually using a Gaussian process regression, and present both white and spectroscopic light curves. In the combined white light curve we achieve an rms precision of 65 ppm when binning to 10 minutes. The mean white light-curve value of (R p/R s)2 is 0.4170 ± 0.0046%. To construct the transmission spectrum, we split the white light curves into 20 spectrophotometric bands, each spanning 20 nm, and compute the mean values of (R p/R s)2 in each band. We compare the transmission spectrum to two sets of atmospheric models. We disfavor a clear, solar composition atmosphere (μ = 2.34) with surface pressures ≥0.1 bar to 5.2σ confidence. We disfavor a clear, H2O steam atmosphere (μ = 18) with surface pressures ≥0.1 bar to low confidence (2.9σ). Our observed transmission spectrum favors a flat line. For solar composition atmospheres with surface pressures ≥1 bar we rule out clouds with cloud-top pressures of 0.1 bar (5.3σ), but we cannot address high-altitude clouds at lower pressures. Our results add further evidence that LHS 3844b is devoid of an atmosphere.

Seeing above the clouds with high-resolution spectroscopy

ABSTRACT In the last decade, ground-based high-resolution Doppler spectroscopy (HRS) has detected numerous species in transiting and non-transiting hot Jupiters, and is ideally placed for atmospheric characterization of warm Neptunes and super Earths. Many of these cooler and smaller exoplanets have shown cloudy atmospheres from low-resolution near-infrared observations, making constraints on chemical species difficult. We investigate how HRS can improve on these given its sensitivity to spectral line cores which probe higher altitudes above the clouds. We model transmission spectra for the warm Neptune GJ 3470b and determine the detectability of H2O with the CARMENES, GIANO, and SPIRou spectrographs. We also model a grid of spectra for another warm Neptune, GJ 436b, over a range of cloud-top pressure and H2O abundance. We show H2O is detectable for both planets with modest observational time and that the high H2O abundance-high cloud deck degeneracy is broken with HRS. However, meaningful constraints on abundance and cloud-top pressure are only possible in the high-metallicity scenario. We also show that detections of CH4 and NH3 are possible from cloudy models of GJ 436b. Lastly, we show how the presence of the Earth’s transmission spectrum hinders the detection of H2O for the most cloudy scenarios given that telluric absorption overlaps with the strongest H2O features. The constraints possible with HRS on the molecular species can be used for compositional analysis and to study the chemical diversity of such planets in the future.

Contrasting changes in cloud optical properties and the influence of aerosols, meteorology and radiation feedback in the Himalaya Karakoram region

The spatio-temporal variations in cloud optical properties and the influence of aerosols, radiation feedback and meteorological parameters were investigated at high altitudes of Diamir, Gilgit and Skardu in the Himalaya Karakoram (HK) region of northern Pakistan from 2004 to 2016. The aerosol optical depth (AOD) depicted significant variation with high values during spring months as compared to other months. The results revealed high values of cloud fraction (CF), cloud water path (CWP) and cloud optical depth (COD) in winter months, while contrasting response was observed in summer months. Due to Twomey effect, clouds become thicker and brighter with maximum COD and liberation of latent heat, which modifies temperature gradient of vertical profile. Similarly, an uneven distribution of cloud effective radius (CER) was observed throughout the study period. An increasing trend of cloud top temperature (CTT) from February to September was observed, while an opposite response was found from September to January during the study period. Likewise, minimum and maximum cloud top pressure (CTP) was found in February and November, respectively. AOD is positively correlated with CF and COD due to high humidity and the existence of hydrophilic aerosols. The results of AOD and CER correlation were in good agreement with Twomey effect. However, AOD showed contrasting relationship with CWP over Diamir and Gilgit. The negative relationships of AOD with CTP and CTT indicated the suppression of precipitation process and variability of meteorological parameters. In addition, a positive correlation was observed between COD and CTP against top of the atmosphere shortwave cloud radiative forcing (TOASWCRF), which indicates the cooling effect due to increasing COD and CTP. With TOASWCRF, a variation in CWP and CER may also lead to cooling effect due to reflection of solar radiations. While the meteorology depicted an uneven relationship with cloud optical properties at observation sites.

Investigating the relationship between aerosol and cloud optical properties inferred from the MODIS sensor in recent decades over East China

Abstract In the present paper, we have analyzed the spatiotemporal distributions and trends of aerosol optical depth observed at 550 nm (AOD550), and its relation with the optical properties of clouds over East China. For this purpose, we have used the long-term (2000–2017) data obtained from the Moderate-resolution Imaging Spectroradiometer (MODIS) Terra satellite to examine and understand the existing relationship between them. The spatial gradient of AOD550 showed an increase from the South to the North of the study domain. However, the seasonal variation of AOD550 was found high in summer and low during the winter. We have noticed a significant increasing trend in AOD over the northern part of the study area, especially in autumn and winter seasons. The study also investigated the spatial and temporal changes to understand the relationship between AOD and cloud properties, namely cloud fraction (CF), cloud top temperature (CTT), Cloud effective radius (CER) and cloud top pressure (CTP), respectively. Besides, the linear regression analysis was conducted to estimate the time series trend for the aerosol and cloud properties during the study period. Further, the regional correlation maps were adopted to improve our understanding of the existing relationship between aerosol and cloud properties. A positive correlation between AOD and CF and CER is evident in most of the places in East China.