This paper investigates the mechanisms of convective cloud organization by precipitationdriven cold pools over the warm tropical Indian Ocean during the 2011 Atmospheric Radiation Measurement (ARM) Madden-Julian Oscillation (MJO) Investigation Experiment/Dynamics of the MJO (AMIE/DYNAMO) field campaign. A high-resolution regional model simulation is performed using the Weather Research and Forecasting model during the transition from suppressed to active phases of the November 2011 MJO. The simulated cold pool lifetimes, spatial extent, and thermodynamic properties agree well with the radar and ship-borne observations from the field campaign. The thermodynamic and dynamic structures of the outflow boundaries of isolated and intersecting cold pools in the simulation and the associated secondary cloud populations are examined. Intersecting cold pools last more than twice as long, are twice as large, 41% more intense (measured with buoyancy), and 62% deeper than isolated cold pools. Consequently, intersecting cold pools trigger 73% more convection than do isolated ones. This is due to stronger outflows that enhance secondary updraft velocities by up to 45%. However, cold pool-triggered convective clouds grow into deep convection not because of the stronger secondary updrafts at cloud base, but rather due to closer spacing (aggregation) between clouds and larger cloud clusters that form along the cold pool boundaries when they intersect. The close spacing of large clouds moistens the local environment and reduces entrainment drying, increasing the probability that the clouds further develop into deep convection. Implications for the design of future convective parameterization with cold poolmodulated entrainment rates are discussed.

The changes in extreme rainfall associated with a warming climate have drawn significant attention in recent years. Mounting evidence shows that sub-daily convective rainfall extremes are increasing faster than the rate of change in the atmospheric precipitable water capacity with a warming climate. However, the response of extreme precipitation depends on the type of storm supported by the meteorological environment. Here using long-term satellite, surface radar and rain-gauge network data and atmospheric reanalyses, we show that the observed increases in springtime total and extreme rainfall in the central United States are dominated by mesoscale convective systems (MCSs), the largest type of convective storm, with increased frequency and intensity of long-lasting MCSs. A strengthening of the southerly low-level jet and its associated moisture transport in the Central/Northern Great Plains, in the overall climatology and particularly on days with long-lasting MCSs, accounts for the changes in the precipitation produced by these storms.

The TRMM Precipitation Radar is used to construct a high resolution (0.05°9 0.05°) climatology of rainfall over the latitude band extending to about 36°North and South. This study describes climatological patterns of rainfall frequency and intensity at high spatial resolution, with special focus on the seasonal and diurnal cycles in the frequency of rainfall events. We use this Tropics-wide dataset to highlight small-scale precipitation features that are too fine to be captured by the most widely used satellite-based rainfall datasets. The results shed light on the roles of changes in the wind direction, the land-sea thermal contrast, small-scale variations in sea surface temperature, and orography in shaping the seasonal and diurnal cycles of rainfall. In some regions of the tropics, diurnally locked local circulations are largely responsible for sharp gradients in the spatial distribution of seasonal mean precipitation. In other regions, we show that climatological rainfall frequency changes very sharply at coastlines, even though rainfall in these regions is expected to be controlled by relatively large scale weather systems.

Abstract. Routine cloud, precipitation and thermodynamic observations collected by the Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) and Aerial Facility (AAF) during the 2-year US Department of Energy (DOE) ARM Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) campaign are summarized. These observations quantify the diurnal to large-scale thermodynamic regime controls on the clouds and precipitation over the undersampled, climatically important Amazon basin region. The extended ground deployment of cloud-profiling instrumentation enabled a unique look at multiple cloud regimes at high temporal and vertical resolution. This longerterm ground deployment, coupled with two short-term aircraft intensive observing periods, allowed new opportunities to better characterize cloud and thermodynamic observational constraints as well as cloud radiative impacts for modeling efforts within typical Amazon "wet" and "dry" seasons.

The isolation of the Amazon rain forest makes it challenging to observe precipitation forming there, but it also creates a natural laboratory to study anthropogenic impacts on clouds and precipitation in an otherwise pristine environment. Observations were collected upwind and downwind of Manaus, Brazil, during the “Observations and Modeling of the Green Ocean Amazon 2014–2015” experiment (GoAmazon2014/5). Besides aircraft, most of the observations were point measurements made in a spatially heterogeneous environment, making it hard to distinguish anthropogenic signals from naturally occurring spatial variability. In this study, 15 years of satellite data are used to examine the spatial and temporal variability of deep convection around the GoAmazon2014/5 sites using cold cloud tops (infrared brightness temperatures colder than 240 K) as a proxy for deep convection. During the rainy season, convection associated with the inland propagation of the previous day’s sea-breeze front is in phase with the diurnal cycle of deep convection near Manaus but is out of phase a few hundred kilometers to the east and west. Convergence between the river breezes and the easterly trade winds generates afternoon convection up to 10% more frequently (on average ~4 mm day−1 more intense rainfall) at the GoAmazon2014/5 sites east of the Negro River (T0e, T0t/k, and T1) relative to the T3 site, which was located west of the river. In general, the annual and diurnal cycles of precipitation during 2014 were similar to climatological values that are based on satellite data from 2000 to 2013.

[1] A high-resolution rainfall climatology based on observations from the Tropical Rainfall Measuring Mission's Precipitation Radar (PR) instrument is used to evaluate the influence of small tropical islands on climatological rainfall. Islands with areas between one hundred and several thousand km 2 are considered in both the Indo-Pacific Maritime Continent and Caribbean regions. Annual mean climatological (1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007) rainfall over each island is compared with that over the surrounding ocean region, and the difference is expressed as a percentage. In addition to total rainfall, rain frequency and intensity are also analyzed. Results are stratified into two 12 h halves of the diurnal cycle as well as eight 3 h periods, and also by a measure of each island's topographic relief. In both regions, there is a clear difference between larger islands (areas of a few hundred km 2 or greater) and smaller ones. Both rain frequency and total rainfall are significantly enhanced over larger islands compared to the surrounding ocean. For smaller islands the enhancement is either negligibly small, statistically insignificant, or, in the case of Caribbean rain frequency, negative. The enhancement in total rainfall over larger islands is partly attributable to greater frequency and partly to greater intensity. A diurnal cycle in island enhancement is evident in frequency but not intensity, except over small Caribbean islands where the converse is true. For the larger islands, higher orography is associated with greater rainfall enhancements. The orographic effect is larger (percentagewise) in the Caribbean than in the Maritime Continent. Orographic precipitation enhancement manifests more strongly as increased frequency of precipitation rather than increased intensity and is present at night as well as during the day. The lack of a clear diurnal cycle in orographic enhancement suggests that much of the orographic rainfall enhancement is attributable to mechanically forced upslope flow rather than elevated surface heating.

Influences of the diurnal cycle on the propagation of the Madden‐Julian Oscillation (MJO) convection across the Maritime Continent (MC) are examined using cloud‐permitting regional model simulations and observations. A pair of ensembles of control (CONTROL) and no‐diurnal cycle (NODC) simulations of the November 2011 MJO episode are performed. In the CONTROL simulations, the MJO signal is weakened as it propagates across the MC, with much of the convection stalling over the large islands of Sumatra and Borneo. In the NODC simulations, where the incoming shortwave radiation at the top of the atmosphere is maintained at its daily mean value, the MJO convection signal propagating across the MC is enhanced. Examination of the surface energy fluxes in the simulations indicates that the surface downwelling shortwave radiation is larger in the presence of the diurnal cycle (CONTROL simulations) primarily because clouds preferentially form in the afternoon and are smaller during day time in comparison to nighttime. Furthermore, the diurnal covariability of surface wind speed and skin temperature results in a larger sensible heat flux and a cooler land surface in the CONTROL runs compared to NODC runs. An analysis of observations indicates that ahead of and behind the MJO active phase, the diurnal cycle of cloudiness enhances downwelling shortwave radiation and hence convection over the MC islands. This enhanced stationary convection competes with and disrupts the convective signal of MJO events that propagate over the waters surrounding the islands.

The broader global community is navigating evolving climate risks, rapid energy transitions, and the growing recognition that sustainable future pathways will require fundamental transformations in our collective management of socio-environmental systems (de Vos et al.