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We assess whether tropical islands tend to warm or cool the troposphere. To this end, we use idealized simulations of the Radiative‐Convective Equilibrium employing a simulation domain that contains flat tropical islands represented by a land surface scheme. Results show more frequent precipitation over land as coastal breezes establish, and gravity waves triggered by afternoon convection propagating away from the islands. These waves horizontally homogenize density and in doing so communicate convectively‐induced temperature anomalies from the islands onto the ocean. What is the influence of the islands on tropospheric temperature? The diurnal surface warming of the islands tends to push the afternoon convection over land towards a warmer moist adiabat, and along with it, the temperature profile of the troposphere. However, at the same time, drying of the land surface pulls it towards a colder moist adiabat. All in all, we find that islands rather cool than warm the troposphere. More specifically, we obtain a weakly colder domain‐mean troposphere during episodes with a larger share of precipitation over land, or when the prescribed land fraction is increased. In particular, we find that the cooling becomes more pronounced over large islands. Overall, the results indicate that the inability of evaporation to keep up with the daytime surface warming over land, in contrast to the ocean, is of key relevance for understanding land effects on the mean climate

To advance the understanding of the interplay among clouds, convection, and circulation, and its role in climate change, the Elucidating the role of clouds–circulation coupling in climate campaign (EUREC4A) and Atlantic Tradewind Ocean–Atmosphere Mesoscale Interaction Campaign (ATOMIC) collected measurements in the western tropical Atlantic during January and February 2020. Upper-air radiosondes were launched regularly (usually 4-hourly) from a network consisting of the Barbados Cloud Observatory (BCO) and four ships within 6–16∘ N, 51–60∘ W. From 8 January to 19 February, a total of 811 radiosondes measured wind, temperature, and relative humidity. In addition to the ascent, the descent was recorded for 82 % of the soundings. The soundings sampled changes in atmospheric pressure, winds, lifting condensation level, boundary layer depth, and vertical distribution of moisture associated with different ocean surface conditions, synoptic variability, and mesoscale convective organization. Raw (Level 0), quality-controlled 1 s (Level 1), and vertically gridded (Level 2) data in NetCDF format (Stephan et al., 2020) are available to the public at AERIS (https://doi.org/10.25326/137). The methods of data collection and post-processing for the radiosonde data set are described here.

Warm season moist diurnal convection can be particularly sensitive to changes in land surface characteristics such as snow cover and soil moisture. Over regions of mountainous terrain, climate change is expected to reduce snow cover along the low-elevation seasonal snowpack margin. These snow reductions alter surface albedo and soil moisture content, leading to changes in surface fluxes and alterations in mesoscale orographic circulations that act to transport moisture and provide ascent. A set of convection-permitting regional climate simulations centered on the Rocky Mountains of Colorado are conducted from April through July across a period of 12 years (2002–2013). These include a reanalysis forced control run (CTR), a pseudo global warming run (PGW), and an additional altered land surface run (DSURF) used to isolate the effects of the snow albedo and soil moisture changes on orographic convection. Over the mountains, daytime hourly precipitation accumulation (0900–1800 MST) decreased in PGW by an average of 4.2% while precipitation in DSURF increased by 12.5%. On days with weak synoptic forcing, the PGW response more closely follow the DSURF response with daytime hourly increases averaging 29.7% for PGW and 28.7% for DSURF. For PGW, hourly daytime precipitation intensity increases of up to 82% overcome reductions in precipitation frequency to produce higher accumulations. DSURF shows smaller increases in intensity of up to 23% and broad increases in daytime frequency indicating that surface changes act to moderate reductions in the frequency of convective precipitation. Reduced snow cover contributes to this convective response by increasing convective instability and boundary layer moisture and decreasing lifting condensation level over the high terrain. Alterations in orographic thermal circulations contribute to this response by converging moisture over the high terrain and enhancing mesoscale ascent.

In this study, an extreme rainfall event that occurred on 25 May 2018 over Shanghai and its nearby area was simulated using the Weather Research and Forecasting model, with a focus on the effects of planetary boundary layer (PBL) physics using double nesting with large grid ratios (15:1 and 9:1). The sensitivity of the precipitation forecast was examined through three PBL schemes: the Yonsei University Scheme, the Mellor–Yamada–Nakanishi Niino Level 2.5 (MYNN) scheme, and the Mellor–Yamada–Janjic scheme. The PBL effects on boundary layer structures, convective thermodynamic and large-scale forcings were investigated to explain the model differences in extreme rainfall distributions and hourly variations. The results indicated that in single coarser grids (15 km and 9 km), the extreme rainfall amount was largely underestimated with all three PBL schemes. In the inner 1-km grid, the underestimated intensity was improved; however, using the MYNN scheme for the 1-km grid domain with explicitly resolved convection and nested within the 9-km grid using the Kain–Fritsch cumulus scheme, significant advantages over the other PBL schemes are revealed in predicting the extreme rainfall distribution and the time of primary peak rainfall. MYNN, with the weakest vertical mixing, produced the shallowest and most humid inversion layer with the lowest lifting condensation level, but stronger wind fields and upward motions from the top of the boundary layer to upper levels. These factors all facilitate the development of deep convection and moisture transport for intense precipitation, and result in its most realistic prediction of the primary rainfall peak.

We extend upon previous work to examine the relationship between low-level cloud amount (LCA) and various proxies for LCA – estimated low-level cloud fraction (ELF), lower tropospheric stability (LTS), and estimated inversion strength (EIS) – by low-level cloud type (CL) over the globe using individual surface and upper-air observations. Individual CL has its own distinct environmental structure, and therefore our extended analysis by CL can provide insights into the strengths and weaknesses of various proxies and help to improve them. Overall, ELF performs better than LTS and EIS in diagnosing the variations in LCA among various CLs, indicating that a previously identified superior performance of ELF compared to LTS and EIS as a global proxy for LCA comes from its realistic correlations with various CLs rather than with a specific CL. However, ELF, LTS, and EIS have a problem in diagnosing the changes in LCA when noCL (no low-level cloud) is reported and also when Cu (cumulus) is reported over deserts where background stratus does not exist. This incorrect diagnosis of noCL as a cloudy condition is more clearly seen in the analysis of individual CL frequencies binned by proxy values. If noCL is excluded, ELF, LTS, and EIS have good inter-CL correlations with the amount when present (AWP) of individual CLs. In the future, an advanced ELF needs to be formulated to deal with the decrease in LCA when the inversion base height is lower than the lifting condensation level to diagnose cumulus updraft fraction, as well as the amount of stratiform clouds and detrained cumulus, and to parameterize the scale height as a function of appropriate environmental variables.

Based on precipitation observations from 256 gauges in the westerly and monsoon dominated upstream river basins of the Third Pole (TP), this study determined the relationships between precipitation and elevation. The basins include the upper basins of the Yangtze, Yellow, Lancang, Nujiang, Yarlung Zangbo, Yarkant, Indus, Amu Darya, and Syr Darya. Using the ERA5 data, this work examined the possible reasons for the difference in the characteristics of precipitation gradient, i.e. analyzing the relationships between the total column water vapor (TCWV), convective available potential energy (CAPE), lifting condensation level (LCL) and elevation, respectively. The feasibility of orographic corrections of precipitation data or observation is validated with the improved VIC land surface hydrological model in two mountain basins in the TP. Mean annual precipitation from gauges generally show decreasing trends (17–128 mm/100 m) with increased elevation (2500–5500 m a.s. l.) in the monsoon dominated basins, i.e. upper Yangtze, Yellow, Lancang, Nujiang, and Yarlung Zangbo, while the orographic enhancements are observed at relatively smaller scales, such as, in the very source regions of the upper Lancang and Nujiang, and Rikaze sub-basin with areas of 11000−67740 km2. On the other hand, in the westerly dominated basins, mean annual precipitation tends to increase with elevation (5–64 mm/ 100 m) in the upper Yarkant, Indus, Amu Darya, and Syr Darya. The precipitation estimates from ERA5 show a good correspondence with the gauge data ( R =0.6−0.9, P

The Tibetan Plateau (TP) plays an important role in formation and development of the East Asian atmospheric circulation, climate variability, and disastrous weathers in China. Among the many topics on TP meteorology, it is critical to understand the microphysical characteristics of clouds over the TP; however, observations of the cloud micro-physics in this area are insufficient mainly due to sparse stations and limited cloud physical data. The Visible Infrared Imaging Radiometer Suite (VIIRS), onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite, has an improved imaging spectroradiometer with 17 channels of 750-m moderate resolution and 5 channels of 375-m image resolution. The high-resolution instrument has an advantage for observing the small or initial convective clouds. Based on the methodologies that we proposed before for retrieving cloud microphysical properties from SNPP, an automated mapping software package named Automatic Mapping of Convective Clouds (AMCC) has been developed at the scale of satellite swath. The properties of convective clouds are retrieved by AMCC and their values are averaged over 0.33° × 0.33° grids based on the SNPP/VIIRS satellite data over the TP during the summers of 2013–17. The results show that: (1) the temperature of lifting condensation level (TLCL) at Naqu meteorological station and the cloud base temperature (Tb) retrieved from VIIRS are linearly correlated, with a correlation coefficient of 0.87 and standard deviation (STD) of 3.0°C; (2) convective clouds over the TP have the following macro- and micro-physical properties. First, the cloud base temperature (Tb) is about −5°C, the cloud base height above the ground (Hb) ranges between 1800 and 2200 m, and the cloud water content is low. Second, the cloud condensation nuclei concentration (NCCN) is between 200 and 400 mg−1 with 0.7% in maximum supersaturation (Smax); consequently, the condensation growth of water cloud droplet with less NCCN and higher Smax is fast. Third, because the precipitation initiation depth (D14) varies within 1500–2000 m and 500–1000 m at the Yarlung Zangbo River basin and southern Tibet, respectively, the clouds over these areas are more prone to precipitation. Fourth, mean height of the cloud top above sea level (Htop) is between 10 and 13 km, but the cloud depth (Dcld) is rather small, which is about 5000 m in southern TP and gradually reduces to 2500 m in northern TP. Fifth, the glaciation temperature (Tg) ranges from −30°C in central and southern TP to −25°C in northern TP, which, combined with the warmer Tg and the Tb less than 0°C, leads to the domination of ice process in the clouds; (3) the macro- and microphysical properties of convective clouds over the TP explain why rainfall there is frequent and lasts over a short time with small amount and large rain drops.

This paper reports on results of idealized numerical simulations testing the influence of low-level humidity, and thus lifting condensation level (LCL), on the morphology and evolution of low-level rotation in supercell thunderstorms. Previous studies have shown that the LCL can influence outflow buoyancy, which can in turn affect generation and stretching of near-surface vertical vorticity. A less explored hypothesis is tested: that the LCL affects the relative positioning of near-surface circulation and the overlying mesocyclone, thus influencing the dynamic lifting and intensification of near-surface vertical vorticity. To test this hypothesis, a set of three base-state thermodynamic profiles with varying LCLs are implemented and compared over a variety of low-level wind profiles. The thermodynamic properties of the simulations are sensitive to variations in the LCL, with higher LCLs contributing to more negatively buoyant cold pools. These outflow characteristics allow for a more forward propagation of near-surface circulation relative to the midlevel mesocyclone. When the mid- and low-level mesocyclones become aligned with appreciable near-surface circulation, favorable dynamic updraft forcing is able to stretch and intensify this rotation. The strength of the vertical vorticity generated ultimately depends on other interrelated factors, including the amount of near-surface circulation generated within the cold pool and the buoyancy of storm outflow. However, these simulations suggest that mesocyclone alignment with near-surface circulation is modulated by the ambient LCL, and is a necessary condition for the strengthening of near-surface vertical vorticity. This alignment is also sensitive to the low-level wind profile, meaning that the LCL most favorable for the formation of intense vorticity may change based on ambient low-level shear properties.

Aerosol-cloud interactions and feedbacks play an important role in modulating cloud development, microphysical and optical properties thus enhancing or reducing precipitation over polluted/pristine regions. The lockdown enforced on account of Covid-19 pandemic is a unique opportunity to verify the influence of drastic reduction in aerosols on cloud development and its vertical distribution embedded in identical synoptic conditions. Cloud bases measured by ceilometer in Delhi, the capital of India, are observed to propagate from low level to higher levels as the lockdown progresses. It is explained in terms of trends in temporal variation of cloud condensation nuclei (CCN) and precursor gases to secondary hygroscopic aerosols. The large reduction (47%) in CCN estimated from aerosol extinction coefficient during the lockdown results in upward shift of cloud bases. Low clouds with bases located below 3 km are found to have reduced significantly from 63% (of total clouds distributed in the vertical) during pre-lockdown to 12% in lockdown period (less polluted). Cloud base height is found to have an inverse correlation with CCN (r = -0.64) and NO2/NH3 concentrations (r = -0.7). The role of meteorology and CCN in modulating the cloud vertical profiles is discussed in terms of anomalies of various controlling factors like lifting condensation level (LCL), precipitable water content (PWC) and mixing layer height (MLH).

Earth's modern climate is characterized by wet, rainy deep tropics, however paleoclimate and planetary science have revealed a wide range of hydrological cycle regimes connected to different external parameters. Here we investigate how surface wetness affects the tropical hydrological cycle. When surface wetness is decreased in an Earth-like general circulation model, the tropics remain wet but transition from a rainy to rain-free regime. The rain-free regime occurs when surface precipitation is suppressed as negative evaporation (surface condensation) balances moisture flux convergence. The regime transition is dominated by near-surface relative humidity changes in contrast to the hypothesis that relative humidity changes are small. We show near-surface relative humidity changes responsible for the regime transition are controlled by re-evaporation of stratiform precipitation near the lifting condensation level. Re-evaporation impacts the near-surface through vertical mixing. Our results reveal a new rain-free tropical hydrological cycle regime that goes beyond the wet/dry paradigm., Comment: 9 pages, 4 figures, accepted by Geophysical Research Letters

The vertical distribution of water vapor affects the intensity of the updraft, downdraft and cold pool in convection, so how to adjust lightning proxy-humidity in the vertical direction is very important for convective scale numerical weather prediction (NWP). In this study, a data assimilation approach is presented that uses information from FengYun4 (FY4) lightning data with cloud top height (CTH) data. Specifically, the FY4 CTH is used to locate the upper boundary of the relative humidity adjustment. This method can effectively determine the vertical distribution of water vapor and obtain accurate pseudo-observations. Two severe convection events with different characteristics were studied to evaluate the data assimilation approach for short-term precipitation forecast. For comparison, two other relative humidity adjustment schemes with different vertical ranges were performed. One scheme adjusted the relative humidity between two isothermal layers and introduced the smallest water vapor increments compared with the other two data assimilation experiments and showed a slight improvement on precipitation forecast. The other scheme adjusted the relative humidity between the lifting condensation level (LCL) and a fixed height and introduced the maximum water vapor increments and exhibited better precipitation forecast based on Equitable Threat Scores (ETSs). The adjustment between LCL and CTH introduced appropriate amounts of water vapor and was adaptable for various convection developments and effectively avoided producing spurious convection in the particular case. Assimilation of FY4 lightning and CTH data improves the short-term precipitation forecast and provides the best forecast skill in a particular forecast period.

Airborne remote sensing observations over the tropical Atlantic Ocean upstream of Barbados are used to characterize trade wind shallow cumulus clouds and to benchmark two cloud-resolving ICON (ICOsahedral Nonhydrostatic) model simulations at kilo- and hectometer scales. The clouds were observed by an airborne nadir pointing backscatter lidar, a cloud radar, and a microwave radiometer in the tropical dry winter season during daytime. For the model benchmark, forward operators convert the model data into the observational space for considering instrument specific cloud detection thresholds. The forward simulations reveal the different detection limits of the lidar and radar observations, i.e., most clouds with cloud liquid water content greater than 10−7 kg/kg are detectable by the lidar, whereas the radar is primarily sensitive to the rain-category hydrometeors in the models and can detect even low amounts of rain. The observations reveal two prominent modes of cumulus cloud top heights separating the clouds into two layers. The lower mode relates to boundary layer convection with tops closely above the lifted condensation level, which is at about 700 m above sea level. The upper mode is driven by shallow moist convection, also contains shallow outflow anvils, and is closely related to the trade inversion at about 2.3 km above sea level. The two cumulus modes are reflected differently by the lidar and the radar observations and under different liquid water path (LWP) conditions. The storm-resolving model (SRM) at kilometer scale reproduces the cloud modes barely and shows the most cloud tops slightly above the observed lower mode. The large-eddy model (LEM) at hectometer scale reproduces better the observed cloudiness distribution with a clear bimodal separation. We hypothesize that slight differences in the autoconversion parametrizations could have caused the different cloud development in the models. Neither model seems to account for in-cloud drizzle particles that do not precipitate down to the surface but generate a stronger radar signal even in scenes with low LWP. Our findings suggest that even if the SRM is a step forward for better cloud representation in climate research, the LEM can better reproduce the observed shallow cumulus convection and should therefore in principle represent cloud radiative effects and water cycle better.

Forest evaporation exports a vast amount of water vapor from land ecosystems into the atmosphere. Meanwhile, evaporation during rain events is neglected or considered of minor importance in dense ecosystems. Air convection moves the water vapor upwards leading the formation of large invisible vapor plumes, while the identification of visible vapor plumes has not been studied yet. This work describes the formation process of vapor plumes in a tropical wet forest as evidence of evaporation processes happening during rain events. In the dry season of 2018 at La Selva Biological Station (LSBS) in Costa Rica it was possible to spot visible vapor plumes within the forest canopy. The combination of time-lapse videos at the canopy top with meteorological measurements along the canopy profile allowed to identify the conditions required for this process to happen. This phenomenon happened only during rain events, where evaporation measurements showed contributions of 1.8 mm d−1. Visible vapor plumes during day time occurred on the presence of precipitation (P), air convection identified by the temperature gradient (Δϴv / Δz) at 2 m height, and a lifting condensation level at 43 m height (Zlcl.43) smaller than 100 m.

Climatology of atmospheric instability is studied over Gadanki using high-resolution radiosonde launched daily during April 2006 to April 2017. The diurnal and seasonal variation of instability parameters is discussed in relation with surface meteorological parameters. Seasonal variations depict strong variability in instability which is masked by stronger diurnal variation with descending Lifting Condensation Level (LCL) and Level of Free Convection (LFC) between 11 and 18 IST resulting in high Convective Available Potential Energy (CAPE) values and heavy rainfall. On a seasonal basis, parcel parameters are high during the late monsoon and post-monsoon while the instability parameters like Total Totals index (TT) and Vertical Totals index (VT) show highest values in the pre-monsoon associated with strong convection. LFC and LCL start descending with ascent in Equilibrium Level (EL) before the monsoon onset. However after the onset, atmospheric instability falls sharply as supported by decreasing TT, VT and CAPE with increasing LI. The 11-year long-term variation depicts slightly elevated LFC and LCL and declining EL values indicating a decrease in the instability with a decrease in CAPE and K Index (KI) and increase in Lifted Index (LI) and Convective Inhibition (CIN).

The Congo Basin, one of the three most convective regions in the world, has recently experienced a large-scale drying trend accompanied by an increase in thunderstorm activity. This study analyzes changes in the diurnal variations of cloudiness and deep convection from 1979 to 2019 over the Congo, evaluates their associations with trends in precipitation efficiency, and explores their possible connections to the observed decrease in precipitation. Analyses of GridSat-B1 and MODIS satellite datasets in conjunction with ERA5 reanalysis data show that cloud cover has decreased, and brightness temperature (Tb) has increased during the morning hours, while convective activity has increased and Tb has decreased during the afternoon hours, possibly due to the observed warming and drying trend over the Congo. The combined effects of decreasing clouds during the morning and the subsequent increasing convection during the afternoon have led to an amplification of the diurnal amplitude in Tb over the Congo. Our results also indicate a decrease in precipitation efficiency and an increase in cloud base height. Such changes may be attributable to the Congo drought as increased surface temperatures and decreased surface relative humidity would raise the lifted condensation level, and thus increase the cloud base height and decrease the precipitation efficiency. This positive-feedback mechanism may ultimately result in the observed decrease of precipitation at the surface, further accelerating the drying trend over the Congo.

Spatial and temporal variability in the convective boundary layer (CBL) height for the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) study period are examined using the data collected from high-resolution radiosondes during May–September 2009 over the Indian monsoon region. In total, 57 radiosonde launchings were carried out at ∼ 11:00–17:00 IST over six different stations covering a large geographical region, ranging from latitude ∼ 13 to 32° N and longitude 73 to 92° E. Of the total 57 launchings, 17 were made during cloudy conditions during which relative humidity (RH) was found to be greater than 83 % for an ∼ 1.0 km layer at various altitudes below 6 km. Within the layer the difference between saturated equivalent potential temperature and equivalent potential temperature is small, and it satisfies the condition that RH > 83 % for about 1 km is considered as the cloudy layer. There are eight cases when the cloud-topped boundary layer (CTBL) and 19 cases when fair-weather boundary layer (FWBL) is observed. The CBL heights are obtained using thermodynamic profiles, which vary from ∼ 0.4 to 2.5 km a. g. l. The formation of the cloud layers above the boundary layer generally lowers the CBL height and is responsible for its day-to-day variability. The development of the cloud beneath the boundary layer generally elevates the CBL, which is also responsible for the large day-to-day variability in the CBL. The FWBL identified using relative invariance of the thermodynamic profiles varies from ∼ 2.0 to 5.5 km, which is clearly marked by a local minimum in the refractivity gradient. During cloudy days, the CBL is found to be shallow and the surface temperature lower when compared to clear-sky days. The CBL and the lifting condensation level (LCL) heights are randomly related and are found to be at a lower height during cloudy days when compared to clear-sky days. Finally, the typical comparison between the CBL height obtained using thermodynamic profiles and backscattering profiles using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) is examined.

The Weather Research and Forecasting (WRF) model can be used to diagnose regional land-atmosphere (L-A) coupling strength in the absence of sufficient observations but subjected to uncertainties associated with model physical parameterizations. In this study, we propose a framework to quantify and reduce model physical parameterization uncertainties associated with surface fluxes and L-A coupling. An ensemble of WRF simulations with different physical schemes is used to simulate surface fluxes and land-atmosphere coupling strength over the Amazon region. The physical parameterizations investigated include cloud microphysics (MP), land surface processes (LSM), planetary boundary layer (PBL), surface layer (SL), and cumulus (CU). We perform 120 ensemble simulations using the WRF model and different combinations of six MPs, three LSMs, six PBLs and SLs and three CUs. The measurements from the GoAMAZON field campaign and satellite data are used to evaluate model performance. A Multi-way analysis of variance (ANOVA) approach is applied to quantify the relative importance of different physics processes on L-A coupling. The Tukey's test is used to sort schemes that have no significant differences into one group. The suite of physics that result in the best simulations of the corresponding variables are selected based on the Taylor skill score. Results show that the relative importance of processes and their interaction vary with the variables of interest. For example, CU was the most important process in modulating soil moisture, 2 m-humidity, latent heat, and net radiation. LSM showed dominant effects on 2 m-temperature and also has the largest impact on sensible heat and the lifting condensation level. The best physical parameterization ensembles show much narrower ranges of the variables of interest than the priori ensemble. Results of this study show the roles of different physical processes in modulating L-A interactions, quantify model uncertainties from physical processes, and provide insights for improving the model physics parameterizations.

In this study, air accumulation in vapor condensation across a horizontal tube was investigated experimentally. A total of 16 thermistors were mounted uniformly on the horizontal tube wall along the circumference of z = 0.17 m and z = 0.63 m to measure wall temperature. Results show that vapor exists as a three-dimensional diffusion flow and air is carried by vapor toward the downstream at θ = 135°–225° and z = 0–0.6 m, and forms a saturated moist air region there, whereas another region is full of moist vapor. A vapor flowing front lies at the joint of two regions, where interdiffusion between vapor and air is in dynamic equilibrium. In the saturated moist air region, the ratio of gas film layer to overall thermal resistance is within the range of 0.92–0.97, the air mole fraction on the gas–liquid interface is within the range of 0.75–0.87, and the heat transfer coefficient at the condensation side is less than 300 W m−2 K−1. An increase in cooling water mass flux pushes the vapor flowing front forward, expanding the moist vapor region, ultimately enlarging the vapor condensation area. The present experimental results were compared with the results of the works of Zhou and Rose (1996), Sherkriladze and Gomelauri (1966), Rose (1984), Fujii et al. (1972), Memory et al. (1993), and Chen and Lin (2009). The wall temperature distribution and Nu ‾ / Re l 0.5 variation are reasonable.

Indian summer monsoon rainfall is characterized by large intra-seasonal fluctuations in the form of active and break spells in rainfall. This study investigates the role of soil moisture and vegetation on 30-h precipitation forecasts during the break monsoon period using Weather Research and Forecast (WRF) model. The working hypothesis is that reduced rainfall, clear skies, and wet soil condition during the break monsoon period enhance land-atmosphere coupling over central India. Sensitivity experiments are conducted with modified initial soil moisture and vegetation. The results suggest that an increase in antecedent soil moisture would lead to an increase in precipitation, in general. The precipitation over the core monsoon region has increased by enhancing forest cover in the model simulations. Parameters such as Lifting Condensation Level, Level of Free Convection, and Convective Available Potential Energy indicate favorable atmospheric conditions for convection over forests, when wet soil conditions prevail. On spatial scales, the precipitation is more sensitive to soil moisture conditions over northeastern parts of India. Strong horizontal gradient in soil moisture and orographic uplift along the upslopes of Himalaya enhanced rainfall over the east of Indian subcontinent.

Using radiosonde measurements from 26 July to 30 July 2014 at Baiqi over the Inner Mongolia grassland of China, the vertical structure of shallow cumulus (SCu) clouds and associated environmental conditions were investigated. The cloud base height and the cloud top height of SCu was 3.4 km and 5 km, respectively. The temperature of the SCu layer was less than 0°C. The horizontal advection of specific humidity was smaller than the vertical transport in the atmosphere below 5 km. Above 5 km, the thermodynamic structure of the atmosphere remained stable. At the interface of the cloud layer and free air atmosphere, there was obvious wind shear and a temperature inversion (~2.9°C). Comparisons of environmental parameters associated with cumulus congestus, rain and clear days, showed that the formation of SCu was characterized by a higher Bowen ratio (high sensible heat flux and low latent heat flux), which indicated intensive turbulence in the boundary layer. The formation of SCu was associated with the boundary layer height exceeding the lifting condensation level. The maintenance of SCu was likely associated with the lower convective available potential energy, weak wind shear, and weak subsidence of the synoptic system, which did not favor the dramatic vertical development of SCu and thereby the transformation of SCu to cumulus congestus.

In this study, the authors developed a new irrigation scheme based on the Noah land surface model, and then coupled it with the Weather Research and Forecasting regional climate model. Two simulations (with and without irrigation) were conducted over the Yellow River basin for the period April to October 2000–2010. The results indicated that the WRF model is able to successfully capture the spatial pattern and seasonal changes in observed temperature and precipitation over the Yellow River basin. When irrigation was induced, the mean surface air temperature at 2 m (T2m) decreased by 0.1–0.4 K, and there was a correspond increase (decrease) in latent (sensible) heat flux over the irrigated areas, wherein the increase (decrease) reached more than 10 W m−2 over the largest irrigated areas. The cooling effect was consistent with the changes in evapotranspiration and heat fluxes due to irrigation. The changes in lifting condensation level and planetary boundary layer height led to a greater probability of cloud formation and bore a close association with surface fluxes and soil moisture, which then impacted the spatial distribution of T2m and precipitation.

In this study, precipitation isotopic variations at Barrow, AK, USA, are linked to conditions at the moisture source region, along the transport path, and at the precipitation site. Seventy precipitation events between January 2009 and March 2013 were analyzed for δ2H and deuterium excess. For each precipitation event, vapor source regions were identified with the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) air parcel tracking program in back-cast mode. The results show that the vapor source region migrated annually, with the most distal (proximal) and southerly (northerly) vapor source regions occurring during the winter (summer). This may be related to equatorial expansion and poleward contraction of the polar circulation cell and the extent of Arctic sea ice cover. Annual cycles of vapor source region latitude and δ2H in precipitation were in phase; depleted (enriched) δ2H values were associated with winter (summer) and distal (proximal) vapor source regions. Precipitation δ2H responded to variation in vapor source region as reflected by significant correlations between δ2H with the following three parameters: (1) total cooling between lifted condensation level (LCL) and precipitating cloud at Barrow, ΔTcool, (2) meteorological conditions at the evaporation site quantified by 2 m dew point, Td, and (3) whether the vapor transport path crossed the Brooks and/or Alaskan ranges, expressed as a Boolean variable, mtn. These three variables explained 54 % of the variance (p 7°C), ΔTcool explained 22 %, Td explained only 1 %, and mtn explained 18 %. The deuterium excess annual cycle lagged by 2–3 months during the δ2H cycle, so the direct correlation between the two variables is weak. Vapor source region relative humidity with respect to the sea surface temperature, hss, explained 34 % of variance in deuterium excess, (−0.395 ± 0.067 ‰ %−1, p

Observed proximity soundings from Europe are used to highlight how well environmental parameters discriminate different kind of severe thunderstorm hazards. In addition, the skill of parameters in predicting lightning and waterspouts is also tested. The research area concentrates on central and western European countries and the years 2009–15. In total, 45 677 soundings are analyzed including 169 associated with extremely severe thunderstorms, 1754 with severe thunderstorms, 8361 with nonsevere thunderstorms, and 35 393 cases with nonzero convective available potential energy (CAPE) that had no thunderstorms. Results indicate that the occurrence of lightning is mainly a function of CAPE and is more likely when the temperature of the equilibrium level drops below −10°C. The probability for large hail is maximized with high values of boundary layer moisture, steep mid- and low-level lapse rates, and high lifting condensation level. The size of hail is mainly dependent on the deep layer shear (DLS) in a moderate to high CAPE environment. The likelihood of tornadoes increases along with increasing CAPE, DLS, and 0–1-km storm-relative helicity. Severe wind events are the most common in high vertical wind shear and steep low-level lapse rates. The probability for waterspouts is maximized in weak vertical wind shear and steep low-level lapse rates. Wind shear in the 0–3-km layer is the best at distinguishing between severe and extremely severe thunderstorms producing tornadoes and convective wind gusts. A parameter WMAXSHEAR multiplying square root of 2 times CAPE (WMAX) and DLS turned out to be the best in distinguishing between nonsevere and severe thunderstorms, and for assessing the severity of convective phenomena.

This paper uses 620 station years of hourly Canadian Prairie climate data to analyze the coupling of monthly near-surface climate with opaque cloud, a surrogate for radiation, and precipitation anomalies. While the cloud–climate coupling is strong, precipitation anomalies impact monthly climate for as long as 5 months. The April climate has memory of precipitation anomalies back to freeze-up in November, mostly stored in the snowpack. The summer climate has memory of precipitation anomalies back to the beginning of snowmelt in March. In the warm season, mean temperature is strongly correlated to opaque cloud anomalies, but only weakly to precipitation anomalies. Mixing ratio anomalies are correlated to precipitation, but only weakly to cloud. The diurnal cycle of mixing ratio shifts upward with increasing precipitation anomalies. Positive precipitation anomalies are coupled to a lower afternoon lifting condensation level and a higher afternoon equivalent potential temperature; both favor increased convection and precipitation. Regression coefficients on precipitation increase from wet to dry conditions. This is consistent with increased uptake of soil water when monthly precipitation is low, until drought conditions are reached, and also consistent with gravity satellite observations. Regression analysis shows monthly opaque cloud cover is tightly correlated to three climate variables that are routinely observed: diurnal temperature range, mean temperature, and mean relative humidity. The set of correlation coefficients, derived from cloud and climate observations, could be used to evaluate the representation of the land–cloud–atmosphere system in both forecast and climate models.

The diurnal variation of atmospheric boundary layer (ABL) height is studied using high-resolution radiosonde observations available at 3 h intervals for 3 days continuously from 34 intensive campaigns conducted during the period December 2010–March 2014 over a tropical station Gadanki (13.5° N, 79.2° E; 375 m), in the Indian monsoon region. The heights of the ABL during the different stages of its diurnal evolution, namely, the convective boundary layer (CBL), the stable boundary layer (SBL), and the residual layer (RL) are obtained to study the diurnal variabilities. A clear diurnal variation is observed in 9 campaigns out of the 34 campaigns. In 7 campaigns the SBL did not form in the entire day and in the remaining 18 campaigns the SBL formed intermittently. The SBL forms for 33–55 % of the time during nighttime and 9 and 25 % during the evening and morning hours, respectively. The mean SBL height is within 0.3 km above the surface which increases slightly just after midnight (02:00 IST) and remains almost constant until the morning. The mean CBL height is within 3.0 km above the surface, which generally increases from morning to evening. The mean RL height is within 2 km above the surface which generally decreases slowly as the night progresses. The diurnal variation of the ABL height over the Indian region is stronger during the pre-monsoon and weaker during winter season. The CBL is higher during the summer monsoon and lower during the winter season while the RL is higher during the winter season and lower during the summer season. During all the seasons, the ABL height peaks during the afternoon (∼ 14:00 IST) and remains elevated until evening (∼ 17:00 IST). The ABL suddenly collapses at 20:00 IST and increases slightly in the night. Interestingly, it is found that the low level clouds have an effect on the ABL height variability, but the deep convective clouds do not. The lifting condensation level (LCL) is generally found to occur below the ABL for the majority of the database and they are randomly related.

A Lagrangian diagnostic adjusted using specific humidity, with 6 h intervals along the trajectory and with lifting condensation level as cloud base height, was employed to identify the moisture source regions around the Tianshan Mountains, northwest China. Then, the relationship between precipitation stable isotopes and diagnosed duration&ndash, distance of moisture trajectory was analyzed. In this region, the median value of transport duration from moisture source to precipitation sampling site is approximately 3 days, and most moisture sources are closer than 1000 km. According to the Lagrangian diagnosed moisture sources, the higher precipitation summer months usually have rapid air mass movement, and remotely sourced moisture can be delivered to arid central Asia, in the dryer winter months, the moisture loading is weak, and longer transport duration and shorter source distances are observed. As trajectory duration increases, &delta, 18O in sampled precipitation shows a positive trend, especially on the northern slope, and the short-duration events are usually significantly impacted by local recycled moisture with depleted isotopic signatures. The northern slope usually shows relatively shorter duration and longer distance, and more distant sources have more enriched isotopic values.

Based on the decoupling parameterization of the cloud-topped planetary boundary layer, a simple equation is derived to compute the inversion height. In combination with the lifting condensation level and the amount of water vapor in near-surface air, we propose a low-level cloud suppression parameter (LCS) and estimated low-level cloud fraction (ELF), as new proxies for the analysis of the spatiotemporal variation of the global low-level cloud amount (LCA). Individual surface and upper-air observations are used to compute LCS and ELF as well as lower-tropospheric stability (LTS), estimated inversion strength (EIS), and estimated cloud-top entrainment index (ECTEI), three proxies for LCA that have been widely used in previous studies. The spatiotemporal correlations between these proxies and surface-observed LCA were analyzed. Over the subtropical marine stratocumulus deck, both LTS and EIS well diagnose seasonal-interannual variations of LCA. However, their use as global proxy for LCA is limited due to their weaker and inconsistent relationship with LCA over land. EIS is anti-correlated with the decoupling strength more strongly than it is correlated with the inversion strength. Compared with LTS and EIS, ELF and LCS better diagnose temporal variations of LCA, not only over the marine stratocumulus deck but also in other regions. However, all proxies have a weakness in diagnosing interannual variations of LCA in several subtropical stratocumulus decks. In the analysis using all data, ELF achieves the best performance in diagnosing spatiotemporal variation of LCA, explaining about 60 % of the spatial-seasonal-interannnual variance of the seasonal LCA over the globe, which is a much larger percentage than those explained by LTS (2 %) and EIS (4 %). Our study implies that accurate prediction of inversion base height and lifting condensation level is a key factor necessary for successful simulation of global low-level clouds in general circulation models (GCMs). Strong spatiotemporal correlation between ELF (or LTS) and LCA identified in our study can be used to evaluate the performance of GCMs, identify the source of inaccurate simulation of LCA, and better understand climate sensitivity.

A total of 3047 individual shallow cumuli were identified from 9 years of polarization lidar measurements (2011–2019) at Wuhan, China (30.5°N, 114.4°E). These fair-weather shallow cumuli occurred at the top edge of the convective boundary layer between April and October with the maximum occurrence in July over the 30°N plain site. They persisted mostly (>92%) for a short period of ~1–10 min and had a geometrical thickness of ~50–600 m (a mean of 209 ± 138 m). The majority (>94%) of the cloud bases of these cumuli were found to appear ~50–560 m (a mean of 308 ± 254 m) above the lifting condensation level (LCL). In this height range from the LCL to the cloud base, the lidar volume depolarization ratio (δδV) slightly decreased with increasing height, showing gradually increasing condensation in this sub-cloud region due to penetrative thermals. Most of the observed shallow cumuli (79%) formed under the conditions of high near-surface air temperature (>30 °C) and water vapor mixing ratio (>15 g kg−1).

In this study, a 13-yr climatology of tornado event and warning environments, including metrics of tornado intensity and storm morphology, is investigated with particular focus on the environments of tornadoes associated with quasi-linear convective systems and right-moving supercells. The regions of the environmental parameter space having poor warning performance in various geographical locations, as well as during different times of the day and year, are highlighted. Kernel density estimations of the tornado report and warning environments are produced for two parameter spaces: mixed-layer convective available potential energy (MLCAPE) versus 0–6-km vector shear magnitude (SHR6), and mixed-layer lifting condensation level (MLLCL) versus 0–1-km storm-relative helicity (SRH1). The warning performance is best in environments characteristic of severe convection (i.e., environments featuring large values of MLCAPE and SHR6). For tornadoes occurring during the early evening transition period, MLCAPE is maximized, MLLCL heights decrease, SHR6 and SRH1 increase, tornadoes rated as 2 or greater on the enhanced Fujita scale (EF2+) are most common, the probability of detection is relatively high, and false alarm ratios are relatively low. Overall, the parameter-space distributions of warnings and events are similar; at least in a broad sense, there is no systematic problem with forecasting that explains the high overall false alarm ratio, which instead seems to stem from the inability to know which storms in a given environment will be tornadic.

This work evaluates the performance of the assimilation of total lightning data within a three-dimensional variational (3DVAR) framework for the analysis and short-term forecast of the 24 May 2011 tornado outbreak using the Weather Research and Forecasting (WRF) Model at convection-allowing scales. Between the lifted condensation level and a fixed upper height, pseudo-observations for water vapor mass first are created based on either the flash extent densities derived from Oklahoma Lightning Mapping Array data or the lightning source densities derived from the Earth Networks pulse data, and then assimilated by the 3DVAR system. Assimilation of radar data with 3DVAR and a cloud analysis algorithm (RAD) also are performed as a baseline for comparison and in tandem with lightning to evaluate the added value of this lightning data assimilation (LDA) method.Given a scenario wherein the control experiment without radar or lightning data assimilation fails to accurately initiate and forecast the observed storms, the LDA and RAD yield comparable short-term forecast improvements. The RAD alone produces storms of similar strength to the observations during the first 30 min of forecast more rapidly than the LDA alone; however, the LDA is able to better depict individual supercellular features at 1-h forecast. When both the lightning and radar data are assimilated, the 30-min forecast showed noteworthy improvements over RAD in terms of the model’s ability to better resolve individual supercell structures and still maintained a 1-h forecast similar to that from the LDA. The results chiefly illustrate the potential value of assimilating total lightning data along with radar data.

Short squall lines that occurred over Lishui, southwestern Zhejiang Province, China, on 5 July 2012, were investigated using the WRF model based on 1°×1° gridded NCEP Final Operational Global Analysis data. The results from the numerical simulations were particularly satisfactory in the simulated radar echo, which realistically reproduced the generation and development of the convective cells during the period of severe convection. The initiation of this severe convective case was mainly associated with the uplift effect of mesoscale mountains, topographic convergence, sufficient water vapor, and enhanced low-level southeasterly wind from the East China Sea. An obvious wind velocity gradient occurred between the Donggong Mountains and the southeast coastline, which easily enabled wind convergence on the windward slope of the Donggong Mountains; both strong mid–low-level southwesterly wind and low-level southeasterly wind enhanced vertical shear over the mountains to form instability; and a vertical coupling relation between the divergence on the upper-left side of the Donggong Mountains and the convergence on the lower-left side caused the convection to develop rapidly. The convergence centers of surface streams occurred over the mountain terrain and updrafts easily broke through the lifting condensation level (LCL) because of the strong wind convergence and topographic lift, which led to water vapor condensation above the LCL and the generation of the initial convective cloud. The centers of surface convergence continually created new convective cells that moved with the southwest wind and combined along the Donggong Mountains, eventually forming a short squall line that caused severe convective weather.

The sensitivity of tropical cyclone spinup time to the initial entropy deficit of the troposphere is examined in an axisymmetric hurricane model. Larger initial entropy deficits correspond to less moisture above the initial lifting condensation level of a subcloud-layer parcel. The spinup time is quantified in terms of thresholds of integrated horizontal kinetic energy within a radius of 300 km and below a height of 1.5 km. The spinup time increases sublinearly with increasing entropy deficit, indicating the greatest sensitivity lies with initial moisture profiles closer to saturation. As the moisture profile approaches saturation, there is a large increase in the low-level, area-averaged, vertical mass flux over the spinup period because of the predominance of deep convection. Higher entropy deficit experiments have a greater amount of cumulus congestus and reduced vertical mass flux over a longer duration. Consequently, the secondary circulation takes longer to build upward, and the radial influx of angular momentum is reduced. There is also a reduction in the conversion of potential available enthalpy to horizontal kinetic energy, as a result of reduced flow down the radial pressure gradient early in the spinup period. Later in the spinup period, the low-level vortex spins up relatively quickly near the nascent radius of maximum wind in the high-entropy deficit experiments, whereas the low-level vortex spins up over a wider area in the low-entropy deficit experiments.

Cloud convection of a CO2 atmosphere where the major constituent condenses is numerically investigated under a setup idealizing a possible warm atmosphere of early Mars, utilizing a two-dimensional cloud-resolving model forced by a fixed cooling profile as a substitute for a radiative process. The authors compare two cases with different critical saturation ratios as condensation criteria and also examine sensitivity to number mixing ratio of condensed particles given externally. When supersaturation is not necessary for condensation, the entire horizontal domain above the condensation level is continuously covered by clouds irrespective of number mixing ratio of condensed particles. Horizontal-mean cloud mass density decreases exponentially with height. The circulations below and above the condensation level are dominated by dry cellular convection and buoyancy waves, respectively. When 1.35 is adopted as the critical saturation ratio, clouds appear exclusively as intense, short-lived, quasi-periodic events. Clouds start just above the condensation level and develop upward, but intense updrafts exist only around the cloud top; they do not extend to the bottom of the condensation layer. The cloud layer is rapidly warmed by latent heat during the cloud events, and then the layer is slowly cooled by the specified thermal forcing, and supersaturation gradually develops leading to the next cloud event. The periodic appearance of cloud events does not occur when number mixing ratio of condensed particles is large.

Based on the precipitable water observations easily available from in situ and remote sensing sensors, a simple approach to define the lifting condensation level (LCL) is proposed in this study. High-resolution radiosonde and microwave radiometer observations over peninsular Indian region during the Cloud Aerosol Interaction and Precipitation Enhancement Experiment Integrated Ground Observational Campaign (CAIPEEX-IGOC) during the monsoon season of 2011 are used to illustrate the unique relationship. The inferences illustrate a linear relationship between the precipitable water (PW) and the LCL temperature. This relationship is especially valuable because PW is easily available as a derived parameter from various remote sensing and ground-based observations. Thus, it could be used to estimate the LCL height and perhaps also the boundary layer height. LCL height and PW correlations are established from historical radiosonde data (1984–2012). This finding could be used to illustrate the boundary layer-cloud interactions during the monsoon and is important for parameterization of boundary layer clouds in numerical models. The relationships are illustrated to be robust and seem promising to get reasonable estimates of the LCL height over other locations as well using satellite observations of PW.

PUBLICATIONS Journal of Advances in Modeling Earth Systems RESEARCH ARTICLE 10.1002/2016MS000689 Key Points: Superparameterization improves the global distribution of the strong terrestrial coupling signals Superparameterization reduces TFS (rainfall triggering signal) but enhances AFS (rainfall amount signal) globally Superparameterization tightens the connection between the responses of PBL properties and rainfall triggering to surface turbulent fluxes Correspondence to: J. Sun, jians910@gmail.com Citation: Sun, J., and M. S. Pritchard (2016), Effects of explicit convection on global land-atmosphere coupling in the superparameterized CAM, J. Adv. Model. Earth Syst., 8, 1248–1269, doi:10.1002/2016MS000689. Received 11 APR 2016 Accepted 21 JUL 2016 Accepted article online 25 JUL 2016 Published online 12 AUG 2016 Effects of explicit convection on global land-atmosphere coupling in the superparameterized CAM Jian Sun 1 and Michael S. Pritchard 1 Department of Earth System Science, University of California, Irvine, California, USA Abstract Conventional global climate models are prone to producing unrealistic land-atmosphere coupling signals. Cumulus and convection parameterizations are natural culprits but the effect of bypassing them with explicitly resolved convection on global land-atmosphere coupling dynamics has not been explored systematically. We apply a suite of modern land-atmosphere coupling diagnostics to isolate the effect of cloud Superparameterization in the Community Atmosphere Model (SPCAM) v3.5, focusing on both the terrestrial segment (i.e., soil moisture and surface turbulent fluxes interaction) and atmospheric segment (i.e., surface turbulent fluxes and precipitation interaction) in the water pathway of the land- atmosphere feedback loop. At daily timescales, SPCAM produces stronger uncoupled terrestrial signals (negative sign) over tropical rainforests in wet seasons, reduces the terrestrial coupling strength in the Central Great Plain in American, and reverses the coupling sign (from negative to positive) over India in the boreal summer season—all favorable improvements relative to reanalysis-forced land modeling. Analysis of the triggering feedback strength (TFS) and amplification feedback strength (AFS) shows that SPCAM favorably reproduces the observed geographic patterns of these indices over North America, with the probability of afternoon precipitation enhanced by high evaporative fraction along the eastern United States and Mexico, while conventional CAM does not capture this signal. We introduce a new diagnostic called the Planetary Boundary Layer (PBL) Feedback Strength (PFS), which reveals that SPCAM exhibits a tight connection between the responses of the lifting condensation level, the PBL height, and the rainfall triggering to surface turbulent fluxes; a triggering disconnect is found in CAM. 1. Introduction C 2016. The Authors. V This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. SUN AND PRITCHARD The land is coupled with the overlying atmosphere through complex physical mechanisms that govern water, energy, carbon, and other trace gas exchanges. Seneviratne et al. [2010] define a soil moisture- precipitation feedback loop depicting important pathways through which water cycles between the land and the atmosphere. From this view, soil moisture feeds back to itself via atmospheric precipitation through two physical segments [Seneviratne et al., 2010; Santanello, 2011; Ferguson et al., 2012; Guillod et al., 2014]. In the terrestrial segment, soil moisture is a major source of water for evapotranspiration and plays a vital role in determining the surface flux partitioning [Dirmeyer, 2011; Sun et al., 2011]. In the atmospheric segment, the turbulent fluxes (both sensible heat flux and latent heat flux) impact convection and precipitation through altering Planetary Boundary Layer (PBL) dynamics. For instance, wetter soil yields more latent heat flux, which can reduce the altitude of the condensation level, favoring shallow convection and moist, cool PBL conditions. Alternately, dryer soil yields more sensible heat flux, which can promote the boundary layer growth, breaking stable layer barriers aloft and resulting in deep convection. Counterintuitive effects of explicit entrainment can also introduce exotic behaviors [Hohenegger et al., 2009]. Thus, both positive and negative soil moisture feedback on precipitation can occur as shown in many studies [Hohenegger et al., 2009; Findell et al., 2011; Taylor et al., 2011, 2012; Gentine et al., 2013c; Guillod et al., 2015]. The atmospheric segment is the most complicated and uncertain part in the full soil moisture-precipitation feedback loop. It is especially uncertain in modern climate models that heavily parameterize the dynamics of the PBL, clouds, convective triggering, and entrainment. How tightly the land couples to the atmosphere is vital to predicting weather [Koster et al., 2006, 2010, 2011; Guo et al., 2012] and the climate system [Dirmeyer, 2003; Dirmeyer et al., 2013, 2014]. The ‘‘coupling strength’’ is generally measured by the degree to which one variable controls or exhibits statistical dependence on EXPLICIT CONVECTION ON GLOBAL LAND-ATMOSPHERE COUPLING

Comprehensive meteorological observations collected during GOAmazon2014/15 using the Atmospheric Radiation Measurement Mobile Facility #1 (AMF1) and assimilated observations from the Modern Era Retrospective Analysis for Research and Applications -Version 2 (MERRA-2) are used to document the seasonal cycle of cloudiness, thermodynamics, and precipitation above the Amazon Rainforest. The reversal of synoptic scale vertical motions modulates the transition between a wet and dry season. Ascending moist air during the wet season originates near the surface of the Atlantic Ocean and is advected into the Amazon Rainforest where it experiences convergence and, ultimately, precipitates. The dry season is characterized by weaker winds and synoptic scale subsidence with little or no moisture convergence accompanying moisture advection. This combination results in the drying of the mid-troposphere during June through October as indicated by a decrease in liquid water path, integrated water, and the vertical profile of water vapor mixing ratio. The vertical profile of cloud fraction exhibits a relatively consistent decline in cloud fraction from the LCL to the freezing level where a minimum is observed, unlike many other tropical regions. Coefficients of determination between the Lifting Condensation Level (LCL) and cloud fractional coverage suggest a relatively robust relationship between the LCL and cloudiness beneath 5 km during the dry season (R2 = 0.42), but a weak relationship during the wet season (0.12).

Cloud droplet response to entrainment and mixing between a cloud and its environment is often considered by itself, without accounting for subsequent growth after the mixing event. Here we consider the change in cloud properties when the mixed parcel rises adiabatically after the mixing event. The vertical profile for liquid water mixing ratio after a mixing event is derived analytically, allowing the reduction due to mixing to be predicted from the mixing fraction and the cloud and environment temperature and humidity. It is derived for the limit of homogeneous mixing. The expression leads to a critical height above the mixing level: At the critical height the cloud droplet radius is the same for both mixed and unmixed parcels, and the critical height is independent of the updraft velocity and mixing fraction. Cloud droplets in a mixed parcel are larger than in an unmixed parcel above the critical height, which we refer to as the "super-adiabatic" growth region. Analytical results are confirmed by a bin microphysics cloud model. Using the model, we explore the effects of updraft velocity, aerosol source in the environmental air, and polydisperse cloud droplets. Results show that the mixing parcel is more likely to reach the super-adiabatic growth region when the environmental air is humid and clean. It is also confirmed that the analytical predictions are matched by the volume-mean cloud droplet radius under polydisperse conditions. The findings have implications for the origin of large cloud droplets that may contribute to onset of collision-coalescence in warm clouds.

Canopy height is closely related to biomass and aerodynamic properties, which regulate turbulent transfer of energy and mass at the soil-vegetation-atmosphere continuum. However, this key information has been prescribed as a constant value in a fixed plant functional type in atmospheric models. This paper is the first to report impacts of using realistic forest canopy height, retrieved from spaceborne lidar, on regional climate simulation by using the canopy height data in the Weather Research and Forecasting (WRF) model's land surface model. Numerical simulations were conducted over the Amazon Basin during summer season. Over this region, the lidar-retrieved canopy heights were higher than the default values used in the WRF, which are dependent only on plant functional type. By modifying roughness length and zero-plane displacement height, the change of canopy height resulted in changes in surface energy balance by regulating aerodynamic conductances and vertical temperature gradient, thus modifying the lifting condensation level and equivalent potential temperature in the atmospheric boundary layer. Our analysis also showed that the WRF model better reproduced the observed precipitation when lidar-retrieved canopy height was used over the Amazon Basin.

In this paper we present the first direct observational evidence that the condensation level in pyrocumulus and pyrocumulonimbus clouds can be significantly higher than the ambient lifted condensation level. In addition, we show that the environmental thermodynamic profile, day-to-day variations in humidity, and ambient wind shear all exert significant influence over the onset and development of pyroconvective clouds. These findings are established using a scanning Doppler lidar and mobile radiosonde system during two large wildfires in northern California, the Bald Fire and the Rocky Fire. The lidar is used to distinguish liquid water from smoke backscatter during the plume rise, and thus provides a direct detection of plume condensations levels. Plume tops are subsequently determined from both the lidar and nearby radar observations. The radiosonde data, obtained adjacent to the fires, contextualize the lidar and radar observations, and enable estimates of the plume ascent, convective available potential energy, and equilibrium level. A noteworthy finding is that in these cases, the convective condensation level, not the lifted condensation level, provides the best estimate of the pyrocumulus initiation height.

Hourly maximum fields of simulated storm diagnostics from experimental versions of convection-permitting models (CPMs) provide valuable information regarding severe weather potential. While past studies have focused on predicting any type of severe weather, this study uses a CPM-based Weather Research and Forecasting (WRF) Model ensemble initialized daily at the National Severe Storms Laboratory (NSSL) to derive tornado probabilities using a combination of simulated storm diagnostics and environmental parameters. Daily probabilistic tornado forecasts are developed from the NSSL-WRF ensemble using updraft helicity (UH) as a tornado proxy. The UH fields are combined with simulated environmental fields such as lifted condensation level (LCL) height, most unstable and surface-based CAPE (MUCAPE and SBCAPE, respectively), and multifield severe weather parameters such as the significant tornado parameter (STP). Varying thresholds of 2–5-km updraft helicity were tested with differing values of σ in the Gaussian smoother that was used to derive forecast probabilities, as well as different environmental information, with the aim of maximizing both forecast skill and reliability. The addition of environmental information improved the reliability and the critical success index (CSI) while slightly degrading the area under the receiver operating characteristic (ROC) curve across all UH thresholds and σ values. The probabilities accurately reflected the location of tornado reports, and three case studies demonstrate value to forecasters. Based on initial tests, four sets of tornado probabilities were chosen for evaluation by participants in the 2015 National Oceanic and Atmospheric Administration’s Hazardous Weather Testbed Spring Forecasting Experiment from 4 May to 5 June 2015. Participants found the probabilities useful and noted an overforecasting tendency.

A comprehensive understanding of the spatial, seasonal, and diurnal patterns in cloud cover frequency over the Hawaiian Islands was developed using high-resolution image data from the National Aeronautics and Space Administration’s Moderate Resolution Imaging Spectroradiometer (MODIS) sensors aboard the Terra and Aqua satellites. The Terra and Aqua MODIS cloud mask products, which provide the confidence that a given 1-km pixel is unobstructed by cloud, were obtained for the entire MODIS time series (10-plus years) over the main Hawaiian Islands. Monthly statistics were generated from the daily cloud mask data, including mean cloud cover frequency at the four daily overpass times. The derived mean cloud cover frequency showed patterns that were generally consistent with the known distribution of mean rainfall and with the results from previous studies. Cloud cover frequency was the highest over land areas with elevations between the lifting condensation level (~600 m) and the mean height of the trade wind inversion (TWI) base (~2200 m), especially for the windward (northeastern) mountain slopes. Above the TWI, cloud frequency decreased sharply with elevation. Irrespective of season, cloud cover frequency was generally higher in the afternoon than in the morning and higher in daytime than at nighttime although these trends varied spatially. The dry season months (May–October) were less cloudy than the wet season months (November–April) at nighttime. The analysis also revealed a local December–January minimum in the annual cycle of cloud cover frequency. The monthly time series produced in this study is the first high-spatial-resolution cloud cover dataset in Hawaii.

The thermodynamical and microphysical response during the transition from southwest to northeast monsoon season is studied. Unique mixed phase cloud observations from the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) and ground based observations from Integrated Ground Observation Campaign (IGOC), high resolution (3 km) mesoscale forecasts with the nested Weather Research and Forecasting (WRF) model are used in the study. Convective available potential energy (CAPE), liquid water path (LWP) and precipitable water (PW) increased 3 days before the onset and further enhanced with the onset of the northeast monsoon. A systematic decrease in lifting condensation level (LCL) height and increase in midlevel moisture before and during the onset period are observed, which resulted in increase in moist static energy in the midlayer for supporting deeper convection during the onset. Cloud microphysical response is noted with the mixed phase cloud observations of liquid water and ice water content. The model has simulated the mixed phase clouds in the area of detailed observations. Major cloud microphysical changes observed are (a) shallow warm clouds before the onset, (b) elevated supercooled liquid water content at the tops of clouds and (c) low ice water content during the onset period compared to subsequent periods after the onset with more ice water content.

Most parameterizations of droplet concentration at cloud base in cloud models are derived under the assumption that all droplets at the cloud base form by nucleation of dry CCN crossing the lifting condensation level in updraft. In this study, a novel method of calculation of the supersaturation maximum and droplet concentration at cloud base is described that takes into account the existence of liquid at the level of droplet nucleation. Liquid exists in haze particles, as well as in the form of cloud droplets and raindrops. It is shown that the presence of liquid water inside non-activated CCN, as well as of cloud droplets and raindrops substantially decreases supersaturation maximum in case of high aerosol concentration. The possible effect of the supersaturation maximum decrease on formation of DSD in clouds is discussed. The method can be also applied to calculation of supersaturation and droplet nucleation at cloud edges.

Analysis of the hourly Canadian Prairie data for the past 60 years has transformed our quantitative understanding of land–atmosphere–cloud coupling. The key reason is that trained observers made hourly estimates of the opaque cloud fraction that obscures the sun, moon, or stars, following the same protocol for 60 years at all stations. These 24 daily estimates of opaque cloud data are of sufficient quality such that they can be calibrated against Baseline Surface Radiation Network data to yield the climatology of the daily short-wave, long-wave, and total cloud forcing (SWCF, LWCF and CF, respectively). This key radiative forcing has not been available previously for climate datasets. Net cloud radiative forcing changes sign from negative in the warm season, to positive in the cold season, when reflective snow reduces the negative SWCF below the positive LWCF. This in turn leads to a large climate discontinuity with snow cover, with a systematic cooling of 10 °C or more with snow cover. In addition, snow cover transforms the coupling between cloud cover and the diurnal range of temperature. In the warm season, maximum temperature increases with decreasing cloud, while minimum temperature barely changes; while in the cold season with snow cover, maximum temperature decreases with decreasing cloud, and minimum temperature decreases even more. In the warm season, the diurnal ranges of temperature, relative humidity, equivalent potential temperature, and the pressure height of the lifting condensation level are all tightly coupled to the opaque cloud cover. Given over 600 station-years of hourly data, we are able to extract, perhaps for the first time, the coupling between the cloud forcing and the warm season imbalance of the diurnal cycle, which changes monotonically from a warming and drying under clear skies to a cooling and moistening under cloudy skies with precipitation. Because we have the daily cloud radiative forcing, which is large, we are able to show that the memory of water storage anomalies, from precipitation and the snowpack, goes back many months. The spring climatology shows the memory of snowfall back through the entire winter, and the memory in summer, goes back to the months of snowmelt. Lagged precipitation anomalies modify the thermodynamic coupling of the diurnal cycle to the cloud forcing, and shift the diurnal cycle of the mixing ratio, which has a double peak. The seasonal extraction of the surface total water storage is a large damping of the interannual variability of precipitation anomalies in the growing season. The large land-use change from summer fallow to intensive cropping, which peaked in the early 1990s, has led to a coupled climate response that has cooled and moistened the growing season, lowering cloud-base, increasing equivalent potential temperature, and increasing precipitation. We show a simplified energy balance of the Prairies during the growing season, and its dependence on reflective cloud.

It is commonly accepted, that cloud formation is caused by the humidity flux directed from the warm bottom atmospheric layers towards the cold dry heights, and the transportation mechanism in stable stratification is due to development of so-called turbulent boundary layer. The transportation of vapor can be described by buoyancy profile, and requires two significant characteristics of the atmosphere. The first is the heat and water vapor fluxes from the underlying surface which has been investigated by Smith (1988). The second is the temperature profile in the atmosphere, which is usually approximated and parameterized in various ways, because the exact solution is complicated and difficult to use. In this paper we construct a theory of three-component gas mixture, containing air, vapor, and water droplets. This model can be applied for the internal cloud region. Later we use buoyancy to investigate the dynamics of cloud formation, taking into account condensation of the water vapor inside the cloud. The obtained results suggest a typical time of 10 h required for development of intense cloud layer over a sea surface.

Many analytic, but approximate, expressions have been proposed for the height of the lifting condensation level (LCL), including the popular expressions by Espy, Bolton, and Lawrence. Here, the exact, explicit, analytic expression is derived for an air parcel’s LCL as a function of its temperature and relative humidity. Unlike previous analytic expressions, some of which can have errors as high as hundreds or thousands of meters, this exact expression is accurate to within the uncertainty of empirical vapor pressure measurements: this translates into an uncertainty of around 5 m for all temperatures and relative humidities. An exact, explicit, analytic expression for the lifting deposition level (LDL) is also derived, and its behavior is compared to the LCL. At sufficiently cold temperatures, aerosols freeze homogeneously below the LCL; an approximate, implicit, analytic expression is given for this lifting freezing level (LFL). By comparing the LCL, LDL, and LFL, it is found that a well-mixed boundary layer can have an ice-supersaturated layer that is no thicker than 400 m.