Column Water Vapor Research Articles

Impact of water vapor content on visibility: Fog-haze conversion and its implications to pollution control

Atmospheric water vapor content, which reflects the total change of water vapor in the whole atmosphere, has an important effect on the atmospheric visibility (VIS). To investigate the variation of the VIS in Beijing during the past decades and to address the key factors affecting the VIS, the relationships of the VIS with the PM2.5 concentrations, the relative humidity (RH) and the total column water vapor (TCWV) have been explored in this study. The evolution characteristics of these factors in the fog-haze conversion process during the low-visibility (LVIS, VIS <10 km) events are also analyzed. Based on the relations between the TCWV and VIS, a novel method to distinguish haze and fog has been developed and employed in this study. The results show that the frequency of LVIS increases with the increasing of RH, TCWV and PM2.5 concentration. Under dry conditions (RH ≤ 40%), the VIS variation is mainly affected by the PM2.5 concentrations. Under moderate RH conditions (86% > RH > 40%), the VIS is more influenced by TCWV and RH. Under high RH and extremely low visibility conditions (RH > 86% and VIS <1 km), the water vapor is absorbed by aerosols, resulting in the conversion of haze to fog. This process leads to sharp decreases in TCWV and VIS, but an increase in PM2.5 concentrations simultaneously. This study provides a meaningful approach to identify the VIS evolution under the variations of RH, TCWV and PM2.5, which is helpful to the forecasting and early warning of LVIS events.

Observation of absorbing aerosols above clouds over the south-east Atlantic Ocean from the geostationary satellite SEVIRI – Part 2: Comparison with MODIS and aircraft measurements from the CLARIFY-2017 field campaign

Abstract. To evaluate the SEVIRI retrieval for aerosols above clouds presented in Part 1 of the companion paper, the algorithm is applied over the south-east Atlantic Ocean during the CLARIFY-2017 field campaign period. The first step of our analysis compares the retrieved aerosol and cloud properties against equivalent products from the MODIS MOD06ACAERO retrieval (Meyer et al., 2015). While the correlation between the two satellite retrievals of the above-cloud aerosol optical thickness (AOT) is good (R = 0.78), the AOT retrieved by SEVIRI is 20.3 % smaller than that obtained from the MODIS retrieval. This difference in AOT is attributed mainly to the more absorbing aerosol model assumed for the SEVIRI retrieval compared to MODIS. The underlying cloud optical thickness (COT) derived from the two satellites is in good agreement (R = 0.90). The cloud droplet effective radius (CER) retrieved by SEVIRI is consistently smaller than MODIS by 2.2 µm, which is mainly caused by the use of different spectral bands of the satellite instruments. In the second part of our analysis, we compare the forecast water vapour profiles used for the SEVIRI atmospheric correction as well as the aforementioned aerosol and cloud products with in situ measurements made from the Facility for Airborne Atmospheric Measurements (FAAM) aircraft platform during the CLARIFY-2017 campaign. Around Ascension Island, the column water vapour used to correct the SEVIRI signal is overestimated by 3.1 mm in the forecast compared to that measured by dropsondes. However, the evidence suggests that the accuracy of the atmospheric correction improves closer to the African coast. Consistency is observed between the SEVIRI above-cloud AOT and in situ measurements (from cavity ring-down spectroscopy instruments) when the measured single-scattering albedo is close to that assumed in the retrieval algorithm. On the other hand, the satellite retrieval overestimates the AOT when the assumed aerosol model is not absorbing enough. Consistency is also found between the cloud properties retrieved by SEVIRI and the CER measured by a cloud droplet probe and the liquid water path derived from a microwave radiometer. Despite the instrumental limitations of the geostationary satellite, the consistency obtained between SEVIRI, MODIS and the aircraft measurements demonstrates the ability of the retrieval in providing additional information on the temporal evolution of the aerosol properties above clouds.

Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces

A new retrieval of total column water vapour (TCWV) from daytime measurements over land of the Ocean and Land Colour Instrument (OLCI) on-board the Copernicus Sentinel-3 missions is presented. The Copernicus Sentinel-3 OLCI Water Vapour product (COWa) retrieval algorithm is based on the differential absorption technique, relating TCWV to the radiance ratio of non-absorbing band and nearby water vapour absorbing band and was previously also successfully applied to other passive imagers Medium Resolution Imaging Spectrometer (MERIS) and Moderate Resolution Imaging Spectroradiometer (MODIS). One of the main advantages of the OLCI instrument regarding improved TCWV retrievals lies in the use of more than one absorbing band. Furthermore, the COWa retrieval algorithm is based on the full Optimal Estimation (OE) method, providing pixel-based uncertainty estimates, and transferable to other Near-Infrared (NIR) based TCWV observations. Three independent global TCWV data sets, i.e., Aerosol Robotic Network (AERONET), Atmospheric Radiation Measurement (ARM) and U.S. SuomiNet, and a German Global Navigation Satellite System (GNSS) TCWV data set, all obtained from ground-based observations, serve as reference data sets for the validation. Comparisons show an overall good agreement, with absolute biases between 0.07 and 1.31 kg/m2 and root mean square errors (RMSE) between 1.35 and 3.26 kg/m2. This is a clear improvement in comparison to the operational OLCI TCWV Level 2 product, for which the bias and RMSEs range between 1.10 and 2.55 kg/m2 and 2.08 and 3.70 kg/m2, respectively. A first evaluation of pixel-based uncertainties indicates good estimated uncertainties for lower retrieval errors, while the uncertainties seem to be overestimated for higher retrieval errors.

Regional‐scale variability and change in daily precipitation across the contiguous United States, 1949–2018

AbstractRecent research suggests that the characteristics of precipitation are changing with a warming global climate. This study uses two traditional measures of precipitation, amount and frequency, in addition to two metrics that have not been widely used in hydroclimatological research, the Gini coefficient (GC) and the Lorenz asymmetry coefficient (LAC), to analyse change and variability in precipitation characteristics across the United States from 1949 through 2018. The GC quantifies the inequity of an accumulating variable across individual contributors. For this study, the GC was used to quantify equity in the accumulating distribution of daily precipitation amounts through an annual timeframe. The LAC quantifies the relative magnitude of individual contributors which were primarily responsible for inequity in an accumulating distribution. For this analysis, the LAC assesses the relative magnitude of precipitation events (light, heavy) primarily responsible for occurrences of inequity in the temporal distribution of precipitation. Time series analysis of regionally averaged values of precipitation amount, precipitation frequency, GC, and LAC values suggest change in the hydroclimate for many regions across the United States, including a trend towards greater inequity in the temporal distribution of precipitation. The more recent trends and variability of the four precipitation characteristics were statistically examined for relationships with time series of two key atmospheric features – total column water vapour (moisture availability) and the 850 hPa–500 hPa lapse rate (static stability). Results of this study show that change and variability in the atmospheric characteristics likely help explain the observed trends and variability of several precipitation characteristics across the United States.

The Distribution of Frosts on Mars: Links to Present‐Day Gully Activity

AbstractNumerous types of activity in mid latitude martian gullies have been observed over the last decade. Some activity has been constrained to occur in the coldest times of year, suggesting that surficial frosts that form seasonally and diurnally might play a key role in this activity. Here we use thermal infrared data to explore the global, spatial and temporal variation of temperatures conducive to CO2 and H2O frost formation on Mars, and assess their distribution relative to gully landforms. CO2 frost detections are observed at all latitudes and are strongly correlated with dusty, low thermal inertia regions near the equator. While it is difficult to accurately detect the formation of H2O frost, the global H2O frost point distribution generally follows water vapor column abundance, and is weakly correlated with surface pressure. Most global CO2 frost detections do not contain gullies, but 47% of all gullies, and 73% of active gullies (76% in the south, and 25% in the north) do overlap with CO2 frost detections. We predict that the conditions necessary for significant present‐day gully activity include a few centimeters of CO2 frost within loose, unconsolidated sediments (I ∼ 300 ) on relatively steep (&gt;20°) slopes. Additionally, it could be possible for small amounts of H2O frosts to play a role in present‐day equatorial mass wasting events. However, whether present‐day gully activity is representative of gully formation is still open to debate, because it seems unlikely that frosts can erode channels into rocky substrates–even considering geologic timescales.

The Amazon Water Cycle: Perspectives from Water Budget Closure and Ocean Salinity

AbstractGlobal and regional water cycle includes precipitation, water vapor divergence, and change of column water vapor in the atmosphere, and land surface evapotranspiration, terrestrial water storage change, and river discharge, which is linked to ocean salinity near the river mouth. The water cycle is a crucial component of the Earth system, and numerous studies have addressed its individual components (e.g., precipitation). Here we assess, for the first time, if remote sensing and reanalysis datasets can accurately and self-consistently portray the Amazon water cycle. This is further assisted with satellite ocean salinity measurements near the mouth of the Amazon River. The widely used practice of taking the mean of an ensemble of datasets to represent water cycle components (e.g., precipitation) can produce large biases in water cycle closure. Closure is achieved with only a small subset of data combinations (e.g., ERA5 precipitation and evapotranspiration plus GRACE satellite terrestrial water storage), which rules out the lower precipitation and higher evapotranspiration estimates, providing valuable constraints on assessments of precipitation, evapotranspiration, and their ratio. The common approach of using the Óbidos stream gauge (located hundreds of kilometers from the river mouth) multiplied by a constant (1.25) to represent the entire Amazon discharge is found to misrepresent the seasonal cycle, and this can affect the apparent influence of Amazon discharge on tropical Atlantic salinity.

Development of a laser heterodyne spectroradiometer for high-resolution measurements of CO2, CH4, H2O and O2 in the atmospheric column.

We have developed a portable near-infrared laser heterodyne radiometer (LHR) for quasi-simultaneous measurements of atmospheric carbon dioxide (CO2), methane (CH4), water vapor (H2O) and oxygen (O2) column absorption by using three distributed-feedback diode lasers as the local oscillators of the heterodyne detection. The developed system shows good performance in terms of its high spectral resolution of 0.066 cm-1 and a low solar power detection noise which was about 2 times the theoretical quantum limit. Its measurement precision of the column-averaged mole fraction for CO2 and CH4 is within 1.1%, based on the standard deviation from the mean value of the retrieved results for a clean sky. The column abundance information of the O2 is used to correct for the variations and uncertainties of atmosphere pressure, the solar altitude angle, and the prior profiles of pressure and temperature. Comparison measurements of daily column-averaged atmospheric mole fractions of CO2, CH4 and H2O, between our developed LHR and a greenhouse gas observing satellite, show a good agreement, which proves the reliability of our developed system.

Intercomparison of freshwater fluxes over ocean and investigations into water budget closure

Abstract. The development of algorithms for the retrieval of water cycle components from satellite data – such as total column water vapor content (TCWV), precipitation (P), latent heat flux, and evaporation (E) – has seen much progress in the past 3 decades. In the present study, we compare six recent satellite-based retrieval algorithms and ERA5 (the European Centre for Medium-Range Weather Forecasts' fifth reanalysis) freshwater flux (E−P) data regarding global and regional, seasonal and interannual variation to assess the degree of correspondence among them. The compared data sets are recent, freely available, and documented climate data records (CDRs), developed with a focus on stability and homogeneity of the time series, as opposed to instantaneous accuracy. One main finding of our study is the agreement of global ocean means of all E−P data sets within the uncertainty ranges of satellite-based data. Regionally, however, significant differences are found among the satellite data and with ERA5. Regression analyses of regional monthly means of E, P, and E−P against the statistical median of the satellite data ensemble (SEM) show that, despite substantial differences in global E patterns, deviations among E−P data are dominated by differences in P throughout the globe. E−P differences among data sets are spatially inhomogeneous. We observe that for ERA5 long-term global E−P is very close to 0 mm d−1 and that there is good agreement between land and ocean mean E−P, vertically integrated moisture flux divergence (VIMD), and global TCWV tendency. The fact that E and P are balanced globally provides an opportunity to investigate the consistency between E and P data sets. Over ocean, P (nearly) balances with E if the net transport of water vapor from ocean to land (approximated by over-ocean VIMD, i.e., ∇⋅(vq)ocean) is taken into account. On a monthly timescale, linear regression of Eocean-∇⋅(vq)ocean with Pocean yields R2=0.86 for ERA5, but smaller R2 values are found for satellite data sets. Global yearly climatological totals of water cycle components (E, P, E−P, and net transport from ocean to land and vice versa) calculated from the data sets used in this study are in agreement with previous studies, with ERA5 E and P occupying the upper part of the range. Over ocean, both the spread among satellite-based E and the difference between two satellite-based P data sets are greater than E−P, and these remain the largest sources of uncertainty within the observed global water budget. We conclude that, for a better understanding of the global water budget, the quality of E and P data sets needs to be improved, and the uncertainties more rigorously quantified.

Growing Operational Use of FY-3 Data in the ECMWF System

This paper reviews the data quality and impact of observations from the FY-3 satellite series used operationally in the ECMWF system. This includes data from the passive microwave radiometers MWHS-1, MWHS-2 and MWRI, as well as observations from the radio occultation receiver GNOS. Evaluations against background equivalents show that the quality of the observations is broadly comparable to that of similar instruments on other polar-orbiting satellites, even though biases for the passive microwave observations can be somewhat larger and more complex for some channels. An observing system experiment shows that the FY-3 instruments jointly contribute significantly to the forecast skill in the ECMWF system. Positive impact of up to 2% is seen for most variables out to the day-2 forecasts over hemispheric scales, with significant benefits for total column water vapor or for temperature and wind in the stratosphere out to day 4.

The Effect of the Atmospheric and Cloud Properties on the Retrieval of Fog Microphysics at Night for MSG/SEVIRI: A Sensitivity Test Using LibRadtran

The simplest way of building a look-up table (LUT) for the retrieval of cloud microphysical properties is to use a standard atmospheric profile and vertically uniform cloud microphysics. Such an assumption has been demonstrated to be incoherent with in-cloud observations. This paper aims to show the effect of some atmospheric conditions associated with fog as well as its macro-and microstructure on brightness temperature (BT) for the MSG/ SEVIRI satellite using libRadtran. The sensitivity tests were performed by gradually changing some features from the initial data, such as cloud cover, total water vapor column, thermal inversion intensity, fog depth, fog microstructure, and others. The results revealed that some variables can cause significant variations on BT and, consequently, discrepancies in the retrieval of fog microphysical properties. Also, a variation as high as 0.5°C was found on BT just by switching uniform to the non-uniform profile of fog microphysics depending on the channel, the droplet size, and optical thickness.

The Role of the Mean State on MJO Simulation in CESM2 Ensemble Simulation

AbstractThis study examines the role of the mean state in the propagation of the Madden‐Julian oscillation (MJO) over the Maritime Continent (MC). We use an ensemble of simulations made with a single model—the Community Earth System Model version 2—to assess the effect of the mean state that is unaffected by that of model components such as parameterization schemes. Results show that the background meridional moisture gradient is much steeper over the MC region in the periods with a stronger MJO propagation. Column water vapor budget of the MJO strongly suggests that the simulated mean state affects MJO via its impacts on moisture dynamics—a greater advection of mean moisture by MJO wind in the MC region is responsible for the anomalous MJO activity.

Bolometric night sky temperature and subcooling of telescope structures

Context.The termsky temperatureis used in the literature to refer to different phenomena in different contexts which often leads to confusion. In this work, we studyTsky, the effective bolometric sky temperature at which a hemispherical black body would radiate the same power onto a flat horizontal structure on the ground as the night sky, integrated over the entire thermal wavelength range of 1–100μm. We then analyze the thermal physics of radiative cooling with special focus on telescopes and discuss mitigation strategies.Aims.The quantityTskyis useful to quantify the subcooling in telescopes which can deteriorate the image quality by introducing an optical path difference (OPD) and induce thermal stress and mechanical deflections on structures.Methods.We employ the Cerro Paranal Sky Model of the European Southern Observatory to derive a simple formula ofTskyas a function of atmospheric parameters. The structural subcooling and the induced OPD are then expressed as a function of surface emissivity, sky view factor, local air speed, and structure dimensions.Results.At Cerro Paranal (2600m) and Cerro Armazones (3060m) in the Atacama desert,Tskytowards the zenith mostly lies 25–50 Kelvin below the ambient temperature near the ground, depending to a great extent on the precipitable water vapor column in the atmosphere. The temperature difference can decrease by several Kelvin for higher zenith distances. The subcooling OPD scales linearly to quadratically with the telescope diameter and is inversely proportional to the local air speed near the telescope structure.

Influences of atmospheric water vapor on spectral effective emissivity of a single-layer radiative cooling coating

Radiative cooling technology can emit infrared heat to the outer space through the "sky window" for cooling without consuming energy, which had drawn more and more attention. However, some researches reported that there was a significantly different cooling performance at different atmospheric total water vapor columns (TWC) conditions. In this study, taking a simple single-layer radiative cooling coating containing two kinds of particle mixture (SiO₂, TiO₂) as example, the spectral effective emissivity of the radiative cooling coating was proposed to evaluate the effect of the atmospheric water vapor on the cooling performance. The spectral effective emissivity of the coating was obtained through multiplying spectral emissivity of the coating by the atmospheric transmittivity, where the spectral emissivity was calculated by combining an algorithm for calculating radiative properties of the multi-particle system with the Monte Carlo ray-tracing method (MCRT). The effects of different atmospheric water vapor on the spectral effective emissivity of the simple single-layer radiative cooling coating containing different particles size, volume fraction and thickness were studied to improve the cooling performance of the coating. The results showed that with increasing TWC from 0 to 7000 atm-cm, the average effective emissivity of the simple single-layer coating decreased from 79.5% to 35.3%, with a decrease of 44.2%. The research results are of great significance to the further application development and the design criterion of radiative cooling materials in different atmospheric water vapor environments.

Atmospheric water vapor radiative effects on shortwave radiation under clear skies: A global spatiotemporal analysis

This global study analyzes how the total column water vapor (in terms of precipitable water, PW) is related to the attenuation of shortwave solar radiation (SWR) using data from the MERRA-2 reanalysis during 2000–2014 and SWR simulations obtained with the REST2 clear-sky radiation model. The water vapor radiative effect (WVRE) on SWR attenuation is investigated by comparing the clear-sky SWR predictions under humid and ideally dry atmospheres, whereas the quantitative effect of PW on WVRE is determined using the concept of precipitable water efficiency (PWE).At global scale, WVRE exhibits a distinct seasonal pattern ranging from –80.2 to 0 W m‐2, with lower values in humid regions where PW is typically high (>4 cm), making the water vapor contribution relatively small. This is attributed to the saturation effect in water vapor absorption. Over arid regions, the solar irradiance attenuation is mainly controlled by the high aerosol loads, and less negative WVRE values are found. Over high-altitude regions, the low PW reduces the atmospheric absorption, resulting in low absolute WVRE magnitudes.PWE is found to extend globally between –133.7 and 0 W m‐2 cm‐1 on a monthly scale. This range is smaller on a long-term mean monthly or annual basis. On a long-term basis, the monthly PWE results are mainly concentrated between −20 and 0 W m−2 cm−1, generating leptokurtic and left-skewed distributions peaking between −10 and −8 W m−2 cm−1, depending on month. PWE is inversely related to PW on a long-term annual scale, indicating that PWE tends to zero under very humid conditions. A general nonlinear model is proposed to evaluate the hourly PWE at global scale on a monthly basis, separately for the two hemispheres.A PW trend analysis reveals that the Middle East, equatorial regions, central Europe, and Australia exhibit significant temporal trends, further inducing significant trends in WVRE. For those areas, WVRE trends are calculated between −3.3 and 1.5 W m−2 over the entire 15-year period.In addition, the global WVRE over landmasses is classified in terms of the Köppen-Geiger (KG) climate classification system. The most pronounced radiative effects are found over the equatorial regions, with an average WVRE of −63 W m−2. The Arid KG class provides a complex WVRE pattern ranging from −66 to −24 W m−2. Further segregation of this class shows strongly variable WVRE, induced by local climate differentiation. Over Warm Temperate climates, WVRE is found to vary widely according to the various KG subclasses. For the Cold climate class, PW is mainly concentrated around 1 cm and WVRE is low. The Polar regions include high mountains where WVRE is low, with a median close to −28 W m−2.

A global long-term (1981–2000) land surface temperature product for NOAA AVHRR

Abstract. Land surface temperature (LST) plays an important role in the research of climate change and various land surface processes. Before 2000, global LST products with relatively high temporal and spatial resolutions are scarce, despite a variety of operational satellite LST products. In this study, a global 0.05∘×0.05∘ historical LST product is generated from NOAA advanced very-high-resolution radiometer (AVHRR) data (1981–2000), which includes three data layers: (1) instantaneous LST, a product generated by integrating several split-window algorithms with a random forest (RF-SWA); (2) orbital-drift-corrected (ODC) LST, a drift-corrected version of RF-SWA LST; and (3) monthly averages of ODC LST. For an assumed maximum uncertainty in emissivity and column water vapor content of 0.04 and 1.0 g cm−2, respectively, evaluated against the simulation dataset, the RF-SWA method has a mean bias error (MBE) of less than 0.10 K and a standard deviation (SD) of 1.10 K. To compensate for the influence of orbital drift on LST, the retrieved RF-SWA LST was normalized with an improved ODC method. The RF-SWA LST were validated with in situ LST from Surface Radiation Budget (SURFRAD) sites and water temperatures obtained from the National Data Buoy Center (NDBC). Against the in situ LST, the RF-SWA LST has a MBE of 0.03 K with a range of −1.59–2.71 K, and SD is 1.18 K with a range of 0.84–2.76 K. Since water temperature only changes slowly, the validation of ODC LST was limited to SURFRAD sites, for which the MBE is 0.54 K with a range of −1.05 to 3.01 K and SD is 3.57 K with a range of 2.34 to 3.69 K, indicating good product accuracy. As global historical datasets, the new AVHRR LST products are useful for filling the gaps in long-term LST data. Furthermore, the new LST products can be used as input to related land surface models and environmental applications. Furthermore, in support of the scientific research community, the datasets are freely available at https://doi.org/10.5281/zenodo.3934354 for RF-SWA LST (Ma et al., 2020a), https://doi.org/10.5281/zenodo.3936627 for ODC LST (Ma et al., 2020c), and https://doi.org/10.5281/zenodo.3936641 for monthly averaged LST (Ma et al., 2020b).

Assessment of Sampling Sufficiency for Low-Cost Satellite Missions: Application to PREFIRE

AbstractThe Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) mission will, for the first time, systematically document the far-infrared (15–54 µm) spectral region from space. The environmental sampling characteristics of the PREFIRE CubeSats, defined in terms of surface temperature (Tsfc) and column water vapor (CWV) are evaluated for a range of possible orbit scenarios for both clear-sky and all-sky conditions over a variety of surface types (land, ocean, sea ice, snow, glacier ice) at both poles. Using NASA Aqua’s Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) retrievals to define the climatological ranges of Tsfc and CWV, the fraction of environmental regimes observed by distinct PREFIRE configurations are evaluated. The sampling rates within any single year for two-orbit CubeSat launches spanning both polar regions are ~75% for clear-sky and ~85% for all-sky compared to the AIRS/AMSU climatology. Decreasing mission duration from 12 to 3 months decreases sampling much more (10%–20%) than decreasing the swath width from 15 to 8 footprints (6%–9%). For a single CubeSat launch, a 98° orbital inclination provides slightly better sampling than either 93° or 103°. For a two-orbit CubeSat launch, a combination of 93° + 98° is somewhat preferable to 103° + 98°. Finally, a 50% data loss rate simulated by dropping out every other orbit leads to only a modest 7%–8% reduction in sampling from full data coverage. This statistical analysis demonstrates that low-cost platforms could offer similar coverage as present-day flagship missions for sampling wide-ranging Tsfc and CWV states over polar regions.

Environmental Controls on Tropical Mesoscale Convective System Precipitation Intensity

AbstractUsing multiple independent satellite and reanalysis datasets, we compare relationships between mesoscale convective system (MCS) precipitation intensity Pmax, environmental moisture, large-scale vertical velocity, and system radius among tropical continental and oceanic regions. A sharp, nonlinear relationship between column water vapor and Pmax emerges, consistent with nonlinear increases in estimated plume buoyancy. MCS Pmax increases sharply with increasing boundary layer and lower free tropospheric (LFT) moisture, with the highest Pmax values originating from MCSs in environments exhibiting a peak in LFT moisture near 750 hPa. MCS Pmax exhibits strikingly similar behavior as a function of water vapor among tropical land and ocean regions. Yet, while the moisture–Pmax relationship depends strongly on mean tropospheric temperature, it does not depend on sea surface temperature over ocean or surface air temperature over land. Other Pmax-dependent factors include system radius, the number of convective cores, and the large-scale vertical velocity. Larger systems typically contain wider convective cores and higher Pmax, consistent with increased protection from dilution due to dry air entrainment and reduced reevaporation of precipitation. In addition, stronger large-scale ascent generally supports greater precipitation production. Last, temporal lead–lag analysis suggests that anomalous moisture in the lower–middle troposphere favors convective organization over most regions. Overall, these statistics provide a physical basis for understanding environmental factors controlling heavy precipitation events in the tropics, providing metrics for model diagnosis and guiding physical intuition regarding expected changes to precipitation extremes with anthropogenic warming.

Seasonality and Trends of Drivers of Mesoscale Convective Systems in Southern West Africa

AbstractMesoscale convective systems (MCSs) are the major source of extreme rainfall over land in the tropics and are expected to intensify with global warming. In the Sahel, changes in surface temperature gradients and associated changes in wind shear have been found to be important for MCS intensification in recent decades. Here we extend that analysis to southern West Africa (SWA) by combining 34 years of cloud-top temperatures with rainfall and reanalysis data. We identify clear trends in intense MCSs since 1983 and their associated atmospheric drivers. We also find a marked annual cycle in the drivers, linked to changes in the convective regime during the progression of the West African monsoon. Before the peak of the first rainy season, we identify a shear regime where increased temperature gradients play a crucial role for MCS intensity trends. From June onward, SWA moves into a less unstable, moist regime during which MCS trends are mainly linked to frequency increase and may be more influenced by total column water vapor. However, during both seasons we find that MCSs with the most intense convection occur in an environment with stronger wind shear, increased low-level humidity, and drier midlevels. Comparing the sensitivity of MCS intensity and peak rainfall to low-level moisture and wind shear conditions preceding events, we find a dominant role for wind shear. We conclude that MCS trends are directly linked to a strengthening of two distinct convective regimes that cause the seasonal change of SWA MCS characteristics. However, the convective environment that ultimately produces the most intense MCSs remains the same.

Applying Deep Learning to Clear-Sky Radiance Simulation for VIIRS with Community Radiative Transfer Model—Part 2: Model Architecture and Assessment

A fully connected “deep” neural network algorithm with the Community Radiative Transfer Model (FCDN_CRTM) is proposed to explore the efficiency and accuracy of reproducing the Visible Infrared Imaging Radiometer Suite (VIIRS) radiances in five thermal emission M (TEB/M) bands. The model was trained and tested in the nighttime global ocean clear-sky domain, in which the VIIRS observation minus CRTM (O-M) biases have been well validated in recent years. The atmosphere profile from the European Centre for Medium-Range Weather Forecasts (ECMWF) and sea surface temperature (SST) from the Canadian Meteorology Centre (CMC) were used as FCDN_CRTM input, and the CRTM-simulated brightness temperatures (BTs) were defined as labels. Six dispersion days’ data from 2019 to 2020 were selected to train the FCDN_CRTM, and the clear-sky pixels were identified by an enhanced FCDN clear-sky mask (FCDN_CSM) model, which was demonstrated in Part 1. The trained model was then employed to predict CRTM BTs, which were further validated with the CRTM BTs and the VIIRS sensor data record (SDR) for both efficiency and accuracy. With iterative refinement of the model design and careful treatment of the input data, the agreement between the FCDN_CRTM and the CRTM was generally good, including the satellite zenith angle and column water vapor dependencies. The mean biases of the FCDN_CRTM minus CRTM (F-C) were typically ~0.01 K for all five bands, and the high accuracy persisted during the whole analysis period. Moreover, the standard deviations (STDs) were generally less than 0.1 K and were consistent for approximately half a year, before they significantly degraded. The validation with VIIRS SDR data revealed that both the predicted mean biases and the STD of the VIIRS observation minus FCDN_CRTM (V-F) were comparable with the VIIRS minus direct CRTM simulation (V-C). Meanwhile, both V-F and V-C exhibited consistent global geophysical and statistical distribution, as well as stable long-term performance. Furthermore, the FCDN_CRTM processing time was more than 40 times faster than CRTM simulation. The highly efficient, accurate, and stable performances indicate that the FCDN_CRTM is a potential solution for global and real-time monitoring of sensor observation minus model simulation, particularly for high-resolution sensors.

Identifying meteorological influences on marine low cloud mesoscale morphology using deep learning classifications

Abstract. Marine low cloud mesoscale morphology in the southeastern Pacific Ocean is analyzed using a large dataset of machine-learning generated classifications spanning three years. Meteorological variables and cloud properties are composited by mesoscale cloud type, showing distinct meteorological regimes of marine low cloud organization from the tropics to the midlatitudes. The presentation of mesoscale cellular convection, with respect to geographic distribution, boundary layer structure, and large-scale environmental conditions, agrees with prior knowledge. Two tropical and subtropical cumuliform boundary layer regimes, suppressed cumulus and clustered cumulus, are studied in detail. The patterns in precipitation, circulation, column water vapor, and cloudiness are consistent with the representation of marine shallow mesoscale convective self-aggregation by large eddy simulations of the boundary layer. Although they occur under similar large-scale conditions, the suppressed and clustered low cloud types are found to be well-separated by variables associated with low-level mesoscale circulation, with surface wind divergence being the clearest discriminator between them, whether reanalysis or satellite observations are used. Clustered regimes are associated with surface convergence and suppressed regimes are associated with surface divergence.