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The orographic effect on the spatial structure of precipitation is a fundamental problem in hydrometeorology that still requires a better understanding of the physical processes involved in the emergence of rainfall patterns and their complex statistical structure. In tropical regions, where meteorological measurements are notoriously sparse and data quality control is often poor or missing, the study of precipitation modeling and prediction is challenging. This research aims to show an innovative approach based on a random cascade downscaling method to generate high‐resolution precipitation products from coarse‐scale precipitation products. This approach also includes a topographic enhancement function for describing the altitudinal variability of precipitation and a numerical diffusion filter to lessen the blockiness problem of random cascades. The suggested approach was applied to analyze some long‐term precipitation statistics in the metropolitan area of Mexico City. The model result agrees closely with the temporal statistics of the selected precipitation products and reflects complex orographic constraints. The proposed downscaling approach becomes an alternative to expensive computational methods and allows urban hydrology applications and analysis of small watersheds to incorporate the effects of complex orography. Plain Language Summary: The Topographic Random Cascade approach is a data‐driven model that may describe the main elements of the space‐time structure of precipitation. This approach also includes a first subcomponent that explains how precipitation changes with the topographic altitude of the terrain and another that smooths the original simulated field and prevents some known technical problems derived from the application of random cascade techniques. In this study, the Topographic Random Cascade approach was applied to describe precipitation in the metropolitan area of Mexico City and surrounding areas; it was also used to improve the spatial resolution of 2‐dimensional precipitation products from IMERG and CHIRPS. In the studied region, where complex orography is present, the influence of terrain on precipitation was considered and an adaptation of a fractal‐based precipitation model was needed to generate a realistic version of precipitation fields at smaller scales than those found in large‐scale precipitation data. The results obtained from this approach highlight the ability to preserve long‐term statistics and represent the overall spatial composition of the orographic precipitation. Based on the achievements of the Topographic Random Cascade approach, its usage can be extended to hydrological and meteorological applications by scientists and practitioners. Key Points: An innovative random cascade approach was used to downscale coarse‐scale precipitation products in a highly complex topographic areaSimulated precipitation fields preserve the overall structure of spatial geometry and the long‐term statistics of the precipitation productsA generalized topographic precipitation enhancement function allows for a better description of the altitudinal variability of precipitation [ABSTRACT FROM AUTHOR]

We investigated the influence of the El Niño‐Southern Oscillation (ENSO) on inter‐annual precipitation variability in the far‐eastern Pacific (FEP) and northern South America (NSA) using an approach based on phase synchronization (PS). First, we carried out a detailed analysis of observational data to define the inter‐annual variability, eliminate the seasonal residual frequencies in hydro‐climatic anomalies, and assess the statistical significance of PS. Additionally, we characterized the seasonality of regional patterns of sea surface temperature, surface pressure levels, low‐level winds and precipitation anomalies associated with the ENSO states. We found that the positive (negative) precipitation anomalies experienced in the FEP and NSA differ from those previously reported in the literature. In particular, the Guianas (northeastern Amazon) and the Caribbean constitute two regions with negative (positive) rainfall anomalies during El Niño (La Niña), separated by a zone of non‐significant anomalies along the Orinoco Low‐level Jet corridor. Moreover, we showed that the ENSO signal is phase‐locked with inter‐annual rainfall and low‐level wind variability in most of the study regions. Furthermore, we found consistency in the PS between the Central and Eastern Pacific El Niño indices and hydroclimatic anomalies over the Pacific. However, some areas exhibited PS, although they did not show significant precipitation anomalies, suggesting that the influence of ENSO on tropical climatology manifests not only in terms of the magnitude of anomalies but also in terms of the phases only. Our approach advances the understanding of climatic anomalies in tropical regions and provides new insights into the non‐linear interactions between ENSO and hydroclimatic processes in tropical Americas. [ABSTRACT FROM AUTHOR]

In January–February 2019, a monsoon low developed over northeastern Australia and brought extreme flooding to much of tropical Queensland. The European Centre for Medium Range Weather Forecasts reanalyses are used to explain the formation and severity of the event. Strong anticyclonic Rossby wave breaking to the southeast of Australia produced weak steering winds over northern Australia, and consequently the low remained nearly stationary for over a week, contributing to the extreme rainfall. Furthermore, the tropical moist margin was deformed by a series of disturbances along the monsoon trough, which drew moist maritime air over land. The event examined has much in common with the composite mean of slow‐moving potential vorticity anomalies in North Queensland, including weak background winds and heavy precipitation. An ensemble subseasonal forecast with the Australian Bureau of Meteorology's Australian Community Climate and Earth System Simulator Seasonal prediction version system 1 shows the same relationship between the background flow, the steering, and the subsequent rainfall. Hence, accurately forecasting the background winds is a prerequisite to forecasting such extreme rainfall. [ABSTRACT FROM AUTHOR]

Global Precipitation Measurement satellite and ERA5 reanalysis data are used to study the 4D (latitude, longitude, altitude, time) distribution of rainfall intensity and latent heating fields over the rainiest region on Earth, located over western Colombia and the far eastern equatorial Pacific. The annual and interannual variability and the location of both variables' maxima are identified, and their spatiotemporal correlations are quantified. Static analyses of the winds show that the colder Choco low‐level jet (LLJ) and the warmer Caribbean‐Panama jet form a tropical frontal system. Dynamic analyses of 3D streamlines reveal that the Choco LLJ is at the core of a quasi‐permanent mini‐Hadley cell over the Pacific, with sinking motion between 6°S‐Equator and rising motion at 5°N–8°N, comprised between 1,000 and 700 hPa. Such vortex dynamics enhances the convergence of the northerly winds and the Panama jet, and exacerbates deep convection in association with the orographic lifting over the Colombian Andes. The large‐scale branches of that flow illuminate the shape and dynamics of the Walker cell over tropical South America. Correlation analyses illustrate the connections between rainfall and 3D winds as moisture transport mechanisms. Correlation and singular value decomposition analyses suggest that oceanic (continental) evaporation is associated with rainfall during the drier (wetter) season, and the importance of high‐levels temperatures and vertical integrals of diverse thermal and energy variables on rainfall bolster the view that the condensational heating is strongly coupled with the moisture transport flow and the convective ascent required to explain such extraordinary amounts of rainfall. Plain Language Summary: The rainiest region on Earth is located over western Colombia and the far eastern equatorial Pacific. It constitutes an exceptional geographical setting to study the mechanisms controlling extreme tropical rainfall. We investigate the spatiotemporal distribution of rainfall and atmospheric heating resulting from condensation at monthly, annual, and interannual timescales, using satellite data. Correlations and locations (latitude, longitude, height) of both variables' maxima are identified. We investigate the main physical mechanisms behind such a record‐breaking rainfall region, finding that: (a) the strong ascent of moist air is driven by a tropical warm/cold frontal system formed by the colder Choco low‐level jet (LLJ) and the warmer Panama jet, enhanced by the orography of the Andes; (b) a dynamic analysis reveals that the Choco LLJ constitutes the inner vortex of a mini‐Hadley cell acting over the Pacific ocean with sinking motion around 6°S‐Equator and rising motion at 5°N–8°N, restricted to the lower atmospheric levels; (c) the Andes contribute to shape the dynamics of the Walker cell over north tropical South America; (d) the upward winds and vertical atmospheric accumulations of diverse thermal and energy variables are strongly associated with rainfall; and (e) evapotranspiration also plays an important role in driving regional precipitation. Key Points: Annual and interannual variability, maxima locations and space‐time correlations of 3D rainfall and latent heating rates are estimatedA frontal system formed by the Panama/Choco jets and a mini‐Hadley cell (engulfing the Choco jet) drive and enhance deep moist convectionVertical winds, evapotranspiration and thermal variables correlate with rainfall. The Andes add orographic lifting and shape the Walker cell [ABSTRACT FROM AUTHOR]

This study shows the influence of El Niño–Southern Oscillation (ENSO) over the seasonal and diurnal variability of the Orinoco low‐level jet (OLLJ) during the December–January–February (DJF) season. Results show changes in the occurrence and intensity of the OLLJ winds during the phases of ENSO (El Niño and La Niña) in relation to Neutral conditions. During El Niño (La Niña), the OLLJ days decrease (increase) over the mid and exit of the OLLJ corridor. Furthermore, the mean wind vertical profiles (and the intensity of the diurnal cycle) decrease (increase) with values ranging from 5 to 9 m·s−1. We highlight that the OLLJ days decrease (increase) in January (February) during El Niño (La Niña) up to 24% (15%). These changes are modulated by the pressure gradient between the Atlantic subtropical high and the near‐equatorial trough regions that decreases (increases) during El Niño (La Niña) and thus induces a decrease (increase) of the OLLJ winds. Moreover, the water vapour flux and precipitation reduce during both phases of ENSO along the OLLJ corridor. This work shows new insights on the OLLJ features during ENSO, which contributes to improving our understanding of the processes that influence the hydro‐climatology of northern South America. [ABSTRACT FROM AUTHOR]

Tropical rainfall is important for regional climate around the globe. In a warming climate forced by rising CO 2 , the tropical rainfall will increase over the equatorial Pacific where sea surface warming is locally enhanced. Here, we analyze an idealized CO 2 removal experiment from the Carbon Dioxide Removal Model Intercomparison Project (CDRMIP) and show that the tropical rainfall change features a stronger pattern during CO 2 ramp-down than ramp-up, even under the same global mean temperature increase, such as the 2 °C goal of the Paris Agreement. The tropical rainfall during CO 2 ramp-down increases over the equatorial Pacific with a southward extension, and decreases over the Pacific intertropical convergence zone and South Pacific convergence zone. The asymmetric rainfall changes between CO 2 ramp-down and ramp-up result from time-varying contributions of the fast and slow oceanic responses to CO 2 forcing, defined as the responses to abrupt CO 2 forcing in the first 10 years and thereafter, respectively, in the abrupt-4xCO2 experiment. The fast response follows the CO 2 evolution, but the slow response does not peak until 60 years after the CO 2 peak. The slow response features a stronger El Niño-like pattern, as the ocean dynamical thermostat effect is suppressed under stronger subsurface warming. The delayed and stronger slow response leads to stronger tropical rainfall changes during CO 2 ramp-down. Our results indicate that returning the global mean temperature increase to below a certain goal, such as 2 °C, by removing CO 2 , may fail to restore tropical convection distribution, with potentially devastating effects on climate worldwide. [ABSTRACT FROM AUTHOR]

Equatorial waves (EWs) are synoptic‐ to planetary‐scale propagating disturbances at low latitudes with periods from a few days to several weeks. Here, this term includes Kelvin waves, equatorial Rossby waves, mixed Rossby–gravity waves, and inertio‐gravity waves, which are well described by linear wave theory, but it also other tropical disturbances such as easterly waves and the intraseasonal Madden–Julian Oscillation with more complex dynamics. EWs can couple with deep convection, leading to a substantial modulation of clouds and rainfall. EWs are amongst the dynamic features of the troposphere with the longest intrinsic predictability, and models are beginning to forecast them with an exploitable level of skill. Most of the methods developed to identify and objectively isolate EWs in observations and model fields rely on (or at least refer to) the adiabatic, frictionless linearized primitive equations on the sphere or the shallow‐water system on the equatorial β$$ \beta $$‐plane. Common ingredients to these methods are zonal wave‐number–frequency filtering (Fourier or wavelet) and/or projections onto predefined empirical or theoretical dynamical patterns. This paper gives an overview of six different methods to isolate EWs and their structures, discusses the underlying assumptions, evaluates the applicability to different problems, and provides a systematic comparison based on a case study (February 20–May 20, 2009) and a climatological analysis (2001–2018). In addition, the influence of different input fields (e.g., winds, geopotential, outgoing long‐wave radiation, rainfall) is investigated. Based on the results, we generally recommend employing a combination of wave‐number–frequency filtering and spatial‐projection methods (and of different input fields) to check for robustness of the identified signal. In cases of disagreement, one needs to carefully investigate which assumptions made for the individual methods are most probably not fulfilled. This will help in choosing an approach optimally suited to a given problem at hand and avoid misinterpretation of the results. [ABSTRACT FROM AUTHOR]

Investigating climatology and predicting rainfall amounts are crucial for planning and mitigating the risks caused by variable rainfall. This study utilized two multivariate polynomial regressions (MPR) and twelve machine learning algorithms, namely three artificial neural networks (ANN), four adaptive neuro-fuzzy inference system (ANFIS) and five support vector machine (SVM) algorithms, to estimate monthly and annual rainfalls in a tropical location. The ground measured rainfall data were collected from the Nigerian Meteorological Agency (NIMET), Lagos spanning 31 years (1983–2013) spatially distributed across Nigeria. The proposed models employed geoclimatic coordinates such as longitude, latitude, and altitude as input variables. Analyses based on general performance index (c) showed that the adaptive neuro-fuzzy inference system (ANFIS) model’s algorithms outscored the MPR, ANN and SVM models in the ten months of the year. Its the generalized bell-shaped algorithm (ANFIS-GBELL) performed best for January, April, May, July, October and annual rainfalls, the Gaussian algorithm (ANFIS-GAUSS) for November and December, the subtractive clustered algorithms (ANFIS-SC) for August and September rainfalls, and fuzzy c-means algorithms (ANFIS-FCM) for June rainfall. Also, the multivariate polynomial regression of second order (MPR-2) model performed best for February and March rainfalls. These models’ algorithms have general performance index ranging from 0.906 to 0.996 and they are thereby proposed for the estimation of rainfall amounts over Nigeria.

Sub-daily extreme precipitation in Jakarta exhibits trends that are related to local temperature, seasonal tropical monsoon circulations, and other environmental drivers. An analysis of 81 years of hourly rainfall between 1900 and 2010 shows a significant increase of about doubling the number of short-duration rainfall events in the wet season. In recent decades, rainfall is found to be higher in intensity and shorter in duration relative to preceding decades. These short-duration rain showers develop typically between afternoon and late night or during early morning hours. Changing short-duration rainfall characteristics throughout the last century are partly attributed to changes in the surface environment of urban Jakarta. A recent temperature increase and land surface drying in the city, in combination with a small increase in the atmospheric moisture content, promote intensified atmospheric convection. A combination of rain gauge data with upper-air observations collected during 2002 -- 2016 reveals that surface warming in the urbanized city accompanied by enhanced availability of moisture results in an increase in convective available potential energy, which contributes to enhanced intense precipitation. Super Clausius--Clapeyron scaling (CC) of high-intensity rainfall is attributed to high near-surface temperature and atmospheric moisture content in the morning. This super-CC scaling is present in a relatively small range of surface temperature values. Results of this study are in agreement with earlier findings exploring the intensification of extreme morning precipitation and a temporal shift of the diurnal convective maximum from late afternoon to late night/early morning in response to local warming. For a delta city such as Jakarta with abundant convection and heavy precipitation, a well-maintained rainfall database is crucial to assist urban flood early warning. [ABSTRACT FROM AUTHOR]

The synoptic mode of variability (SMV) refers to changes in atmospheric conditions over periods ranging from 2 to 10 days. In tropical regions, this variability is driven by tropical waves that have a clear signal on the wavenumber–frequency power spectra of precipitation. This study uses the ensemble empirical mode decomposition (EEMD) method to identify the SMV in daily precipitation and streamflows in 47 river basins over northern South America. We found the presence of the frequency bands with periods of 3–12 days and 6–18 days, which agrees with the SMV associated with tropical waves that modulate precipitation over the region. Furthermore, our results reveal that variance explained by the SMV in rainfall over each catchment is greater than the variance explained by those SMV in streamflows, which suggests that catchments efficiently filter out this variability. We found that SMV explains from 5% to 20% of streamflow variability for catchments ranging from 1000 km 2 to 5000 km 2 . Additionally, the variance explained by SMV decreases as a power fit with the catchment area. Thus, this study characterizes the SMV for potential applications on regional hydrology, diagnosis, modeling, short-time forecasting, prediction, and management of water resources. [ABSTRACT FROM AUTHOR]

A new parametrization scheme representing the lifecycle and effects of convective cold pools (C-POOL) is presented. The scheme comprises a column-crossing prognostic model of the initiation by downdraughts, interaction and decay of cold pools, based upon approximations taken from similarity modelling of gravity currents. The prognostic variables are drawn upon to feed back into the convection parametrization scheme. These feedbacks affect the convective diagnosis, initiation from the boundary layer, parcel ascent and entrainment. Tests of the model show that it improves representation of the diurnal cycle of tropical rainfall, previously well-known as a weakness of parametrized convection. [ABSTRACT FROM AUTHOR]

Aided by progress in the theoretical understanding, new knowledge on tropical rainfall annual cycle changes under global warming background has been advanced in the past decade. In this review, we focus on recent advances in understanding the changes of tropical rainfall annual cycle, including its four distinct features: amplitude, pattern shift, phase and wet/dry season length changes. In a warming climate, the amplitude of tropical rainfall annual cycle is enhanced, more evidently over ocean, while the phase of tropical rainfall annual cycle is delayed, mainly over land. The former is explained by the wet-get-wetter mechanism and the latter is explained by the enhanced effective atmospheric heat capacity and increased convective barrier. The phase delay over land has already emerged in the past four decades. The pattern shift under warming is marked by two features: equatorward shift of the inter-tropical convergence zone throughout the year and the land-to-ocean precipitation shift in the rainy season. The former is explained by the upped-ante mechanism and/or related to the enhanced equatorial warming in a warmer world. The latter is suggested to be caused by the opposite land and ocean surface temperature annual cycle changes in the tropics. Over tropical rainforest regions such as Amazon and Congo Basin, the dry season has lengthened in the recent decades, but the fundamental reason is still unclear. Despite the notable progress of the last decade, many gaps remain in understanding the mechanism, quantifying and attributing the emergence, narrowing the inter-model uncertainty, and evaluating the impact of tropical rainfall annual cycle changes, motivating future work guided by some directions proposed in this review.

• A point-process modelling and rainfall disaggregation framework is proposed. • PPMRD offers greater flexibility in having subdaily upper-level rainfall series. • The study method is successfully applied to the rainfall in the tropical region. Analyzing high-temporal-resolution rainfall data with disaggregation tools is vital for understanding precipitation variability, especially in climate change studies with limited access to such data. To facilitate such study for tropical region, we proposed a Point-Process Modelling and Rainfall Disaggregation (PPMRD) framework for rainfall disaggregation with flexible time scales. The framework was tested on two tropical sites in Singapore, using six point-process models and four disaggregation schemes (24 h to 5 min, 3 h to 5 min, 24 h to 1 h, and 6 h to 1 h). Most models excelled fundamental statistics and extreme value analysis. The Bartlett-Lewis Rectangular Pulse Seven parameter (BLRP7) model was found to be the best performer for simulating and disaggregating tropical rainfall. The study findings emphasized the utility of disaggregation models in generating fine-resolution time series for analyzing rainfall extremes. However, it is crucial to underscore the importance of employing ensembles to comprehensively address uncertainties arising from the stochastic nature of rainfall. The study also emphasized the importance of model selection in the proposed framework, as the disaggregation method depends on the generator's performance. The PPMRD surpasses traditional methods by handling subdaily upper-level series disaggregation to minute-level rainfall. This advancement offers greater capabilities and flexibility, promising benefits for generating high-temporal-resolution rainfall data in hydrological modeling and climate change impact studies. [ABSTRACT FROM AUTHOR]

Abstract The Intertropical Convergence Zone (ITCZ) is a discontinuous, zonal precipitation band that plays a crucial role in the global hydrological cycle. Previous studies using prescribed sea surface temperature (SST) aquaplanets show the ITCZ is sensitive to convective mixing, but such a framework is energetically inconsistent. Studies also show that atmosphere‐ocean coupling reduces the sensitivity of the ITCZ to hemispherically asymmetric forcing. We investigate the effect of atmosphere‐ocean coupling on the sensitivity of the ITCZ to convective mixing using an idealized modeling framework with an Ekman‐driven ocean energy transport (OET). Coupling reduces the sensitivity of the ITCZ location to convective mixing due to SST changes. In prescribed‐SST simulations reducing convective mixing promotes a double ITCZ, while in coupled simulations, it increases the meridional SST gradient which promotes an equatorward ITCZ shift. Prescribing OET in additional experiments has a minimal effect on the sensitivity of the ITCZ location to mixing but does increase the sensitivity of the ITCZ intensity by constraining the net‐downward surface energy flux. Decreasing convective mixing increases net‐downward shortwave cloudy‐sky radiation associated with increased latent heat fluxes and an intensified ITCZ. For simulations analyzed the atmospheric energy input framework is inadequate to study ITCZ dynamics due to the contribution of transient eddies to the atmospheric energy transport. Prescribing SST or OET may strengthen the sensitivity of the ITCZ to a change in parameterization or atmospheric forcing. Future modeling studies investigating the precipitation response to such changes should be aware of the potential sensitivity of their results to atmosphere‐ocean interactions.

We use Recurrence Quantification Analysis (RQA) to study features of Generalized Synchronization (GS) between El Niño-Southern Oscillation (ENSO) and monthly hydrological anomalies (HyAns) of rainfall and streamflows in Colombia. To that end, we check the sensitivity of the RQA concerning diverse HyAns estimation methods, which constitutes a fundamental procedure for any climatological analysis at inter-annual timescales. In general, the GS and its sensitivity to HyAns methods are quantified by means of time-lagged joint recurrence analysis. Then, we link the GS results with the dynamics of major physical mechanisms that modulate Colombia's hydroclimatology, including the Caribbean, the CHOCO and the Orinoco Low-Level Jets (LLJs), and the Cross-Equatorial Flow (CEF) over northwestern Amazonia (southern Colombia). Our findings show that RQA exhibits significant differences depending on the HyAns methods. GS results are similar for the HyAns methods with variable annual cycle but the time-lags seem to be sensitive. On the other hand, our results make evident that HyAns in the Pacific, Caribbean, and Andean regions of Colombia exhibit strong (weak) GS with the ENSO signal during La Niña (El Niño), when hydrological anomalies are positive (negative). Results from the GS analysis allow us to identify spatial patterns of non-linear dependence between ENSO and the Colombian's climatology. The mentioned moisture transport sources constitute the interdependence mechanism and contribute to explain hydrological anomalies in Colombia during the phases of ENSO. During La Niña (El Niño), GS is strong (weak) for the Caribbean and the CHOCO LLJs whereas GS is moderate (strong) for the Orinoco LLJ. Moreover, moisture advection by the Caribbean and CHOCO LLJs exhibit synchrony with HyAns at 0–2 (2–4) months-lags over north-western Colombia and the Orinoco LLJ moisture advection synchronizes with HyAns at similar month-lags over the Amazon region of Colombia. Furthermore, our results suggest a strong (weak) GS between negative (positive) Sea Surface Temperatures (SST) anomalies in the Eastern Pacific and rainfall anomalies in Colombia. In contrast, GS is strong (weak) for positive (negative) SST anomalies in the Central Pacific. Our GS results contribute to advance our understanding on the regional effects of both phases of ENSO in Colombia, whose socio-economical, environmental and ecological impacts cannot be overstated. This work provides a novel approach that reveals new insights into the impact of ENSO on northern South America.

The synoptic mode of variability (SMV) refers to changes in atmospheric conditions over periods ranging from 2 to 10 days. In tropical regions, this variability is driven by tropical waves that have a clear signal on the wavenumber–frequency power spectra of precipitation. This study uses the ensemble empirical mode decomposition (EEMD) method to identify the SMV in daily precipitation and streamflows in 47 river basins over northern South America. We found the presence of the frequency bands with periods of 3–12 days and 6–18 days, which agrees with the SMV associated with tropical waves that modulate precipitation over the region. Furthermore, our results reveal that variance explained by the SMV in rainfall over each catchment is greater than the variance explained by those SMV in streamflows, which suggests that catchments efficiently filter out this variability. We found that SMV explains from 5% to 20% of streamflow variability for catchments ranging from 1000 km2 to 5000 km2. Additionally, the variance explained by SMV decreases as a power fit with the catchment area. Thus, this study characterizes the SMV for potential applications on regional hydrology, diagnosis, modeling, short-time forecasting, prediction, and management of water resources.

A method that formulates the retrieval of drop size distribution (DSD) parameters from polarimetric radar variables at attenuating frequency as the solution of an inverse problem is presented. The DSD in each radar bin is represented by a normalized Gamma distribution defined by three parameters (Dm,N0*,μ). The direct problem that describes polarimetric radar observables—scattering and propagation terms—and their dependency on DSD parameters is analyzed based on T-matrix scattering simulations. The inverse algorithm and its application to the DSD retrieval are then presented. The inverse method is applied to an African Monsoon Multidisciplinary Analysis (AMMA) field campaign that deployed an X-band dual-polarization Doppler radar and optical disdrometers in Benin, West Africa, in 2006 and 2007. The dataset is composed of X-band polarimetric radar PPIs and disdrometer data for 15 organized convective systems observed in 2006. A priori information on DSD parameters (benchmark method) is derived from the polarimetric radar observables by applying power law relationships. The proposed retrieval method of DSD parameters leads to the following results as compared to the benchmark: (i) we found a better spatial consistency of the retrieved parameters, (ii) the reconstructed polarimetric radar observables are closer to the observations, (iii) The validation with disdrometer data confirms an improved estimation of the DSD parameters.

The Intertropical Convergence Zone (ITCZ) is a discontinuous, zonal precipitation band that plays a crucial role in the global hydrological cycle. Previous studies using prescribed sea surface temperature (SST) aquaplanets show the ITCZ is sensitive to convective mixing, but such a framework is energetically inconsistent. Studies also show that atmosphere‐ocean coupling reduces the sensitivity of the ITCZ to hemispherically asymmetric forcing. We investigate the effect of atmosphere‐ocean coupling on the sensitivity of the ITCZ to convective mixing using an idealized modeling framework with an Ekman‐driven ocean energy transport (OET). Coupling reduces the sensitivity of the ITCZ location to convective mixing due to SST changes. In prescribed‐SST simulations reducing convective mixing promotes a double ITCZ, while in coupled simulations, it increases the meridional SST gradient which promotes an equatorward ITCZ shift. Prescribing OET in additional experiments has a minimal effect on the sensitivity of the ITCZ location to mixing but does increase the sensitivity of the ITCZ intensity by constraining the net‐downward surface energy flux. Decreasing convective mixing increases net‐downward shortwave cloudy‐sky radiation associated with increased latent heat fluxes and an intensified ITCZ. For simulations analyzed the atmospheric energy input framework is inadequate to study ITCZ dynamics due to the contribution of transient eddies to the atmospheric energy transport. Prescribing SST or OET may strengthen the sensitivity of the ITCZ to a change in parameterization or atmospheric forcing. Future modeling studies investigating the precipitation response to such changes should be aware of the potential sensitivity of their results to atmosphere‐ocean interactions. Plain Language Summary: The Intertropical Convergence Zone (ITCZ) is a discontinuous tropical rainfall band with over three billion livelihoods dependent on its seasonal cycle. However, even the latest state‐of‐the‐art climate models poorly simulate the real‐world ITCZ. Previous modeling studies which fix sea surface temperatures and have no land show that the ITCZ is sensitive to the model's representation of deep clouds. However, it is yet to be determined whether ocean dynamics that are influenced by the atmosphere removes this sensitivity. In this study we couple the atmosphere to an ocean model with a circulation that depends on near‐surface winds. Through doing so we highlight that interactions between the atmosphere and ocean reduce changes in ITCZ location when varying the representation of deep clouds. This is predominately associated with sea surface temperature changes rather than changes in ocean circulation. However, fixing the ocean circulation and only allowing sea surface temperatures to vary, can cause different changes in ITCZ intensity when changing the representation of deep clouds. We therefore highlight that fixing either sea surface temperatures or the ocean circulation can affect how the ITCZ responds to changes in model design. Key Points: Atmosphere‐ocean coupling reduces the sensitivity of the simulated ITCZ to convective mixingSea surface temperature variations are predominately responsible for the reduced sensitivityAtmospheric energy input framework to understand ITCZ behavior has significant limitations due to strong transient eddies [ABSTRACT FROM AUTHOR]

We report a land‐ocean contrast in the phase change of precipitation annual cycle in multimodel ensemble simulations as climate warms, with a robust delay over land (0–40°N/S) versus an advance (0–40°N/S) or no clear (0–25°N/S) phase changes over ocean. The robust delay over land is caused by the increased effective atmospheric heat capacity CA. Over ocean, the increased CA favors a phase delay, while the land‐ocean precipitation contrast during the peak rainy season favors a phase advance. The latter overwhelms the former and causes a seasonal advance over 0–40°N/S, while the two factors cancel out and result in no phase changes over 0–25°N/S. Under the atmospheric energetic constraint, the land‐ocean precipitation contrast in the peak rainy season is related to their opposite amplitude changes of surface temperature annual cycle: Seasonally different wind changes enhance the amplitude over ocean, while increased CA and surface cooling feedback reduce the amplitude over land. Plain Language Summary: The seasonal monsoon rainfall provides water resources for ~40% of the world population, but it has been a longstanding challenge to predict the arrival timing of monsoon rain, especially at the regional scale. By separating land from ocean, we revealed that the previous finding of seasonal delay of rainfall under warming mainly occurs over land, where most human activities take place, while ocean shows uncertain phase changes. This contrasting phase behavior between land and ocean is shown to be rooted in the first‐principle physical constraints related to energy and climate feedbacks, thus lending confidence to the differential phase response between land and ocean under climate warming. Key Points: The delay of precipitation annual cycle under warming is more robust over land due to the increased effective atmospheric heat capacityCompetition between atmospheric heat capacity increase and summer land‐ocean precipitation contrast causes uncertain phase change over oceanThe land‐ocean precipitation contrast in summer is related to the enhanced (reduced) surface temperature annual cycle over ocean (land) [ABSTRACT FROM AUTHOR]

This study investigates how teleconnections linking tropical rainfall anomalies and wintertime circulation in the northern extra-tropics are represented in historical simulations for the period 1950–2010 run by partners of the EU-funded PRIMAVERA project, following the HighResMIP protocol of CMIP6. The analysis focusses on teleconnections from the western/central Indian Ocean in mid-winter and from the NINO4 region in both the early and the late part of winter; this choice is justified by a substantial change in the relationship between ENSO and the North Atlantic Oscillation (NAO) in the two parts of the season. Model results for both coupled integrations and runs with prescribed sea-surface temperature (SST) are validated against data from the latest ECMWF 20th-century re-analysis, CERA20C. Simulations from six modelling groups are considered, comparing the impact of increasing atmospheric resolution in runs with prescribed SST, and of moving from uncoupled to coupled simulations in the high-resolution version of each model. Single runs were available for each model configurations at the time of writing, with one centre (ECMWF) also providing a 6-member ensemble. Results from this ensemble are compared with those of a 6-member multi-model ensemble (MME) formed by including one simulation from each model. Using only a single historical simulation from each model configuration, it is difficult to detect a consistent change in the fidelity of model-generated teleconnections when either atmospheric resolution is increased or ocean coupling is introduced. However, when simulations from six different models are pooled together in the MME, some improvements in teleconnection patterns can be seen when moving from uncoupled to coupled simulations. For the ECMWF ensemble, improvements in the coupled simulations are only apparent for the late-winter NINO4 teleconnection. While the Indian Ocean teleconnection and the late-winter NINO4 teleconnection appear equally robust in the re-analysis record, the latter is well simulated in the majority of both uncoupled and coupled runs, while the former is reproduced with (generally) much larger errors, and a high degree of variability between individual models and ensemble members. Most of the simulations with prescribed SST fail to produce a realistic estimate of multi-decadal changes between the first and the second part of the 60-year record. This is (at least partially) due to their inability to simulate an Indian Ocean rainfall change which, in observations, has a zonal gradient out of phase with SST changes. In coupled runs, at least one model run with both realistic teleconnections and a good simulation of the inter-decadal pattern of Indian Ocean rainfall also shows a realistic NAO signal in extratropical multi-decadal variability. [ABSTRACT FROM AUTHOR]

For tropical rainfall, there are several potential sources of predictability, including synoptic‐scale convectively coupled equatorial waves (CCEWs) and intraseasonal oscillations such as the Madden–Julian Oscillation (MJO). In prior work, predictability of these waves and rainfall has mainly been explored using forecast model data. Here, the goal is to estimate the intrinsic predictability using, instead, mainly observational data. To accomplish this, Tropical Rainfall Measuring Mission (TRMM) data are decomposed into different wave types using spectral/Fourier filtering. The predictability of MJO rainfall is estimated to be 22–31 days, depending on longitude, as measured by the lead time when the pattern correlation skill drops below 0.5. The predictability of rainfall associated with convectively coupled equatorial Rossby waves, Kelvin waves, and a background spectrum or nonwave component is estimated to be 8–12, 2–3, and 0–3 days, respectively. Combining all wave types, the overall predictability of tropical rainfall is estimated to be 3–6 days over the Indian and Pacific Ocean regions and on equatorial synoptic and planetary length‐scales. For comparison, outgoing longwave radiation (OLR) was more predictable than rainfall by 5–10 days over these regions. Wave‐removal tests were also conducted to estimate the contribution of each wave type to the overall predictability of rainfall. In summary, no single wave type dominates the predictability of tropical rainfall; each of the types (MJO, CCEWs, and nonwave component) has an appreciable contribution, due to the variance contribution, length of decorrelation time, or a combination of these factors. [ABSTRACT FROM AUTHOR]

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From observations, we identify a wave‐like pattern associated with northwestern European seasonal precipitation events. These events are associated with tropical precipitation anomalies, prompting us to investigate if there are any tropical–extratropical teleconnections, in particular the role of tropical anomalies in driving extratropical dynamics through Rossby wave propagation. Using a hierarchy of models from ray tracing to barotropic and baroclinic models, we investigate the Rossby wave mechanism and test potential tropical drivers and yield qualitative results. Using a barotropic model, we identify potential Rossby wave source regions which are consistent between the observations and the model. These regions include the tropical western and eastern Atlantic, the subtropical eastern Atlantic and, to a smaller degree, the subtropical eastern Pacific. Zonal wavenumber 2 and 3 components of the barotropic model responses match well with the observations and ray tracing supports the importance of these components. We use a baroclinic model to investigate the link between the observed Rossby wave source anomalies and the observed tropical precipitation anomalies. The reduced precipitation observed in the tropical Atlantic just north of the Equator can generate some of the observed Rossby wave source anomalies in the tropical Atlantic, while the increased precipitation observed in the tropical eastern Pacific can generate some of the observed Rossby wave source anomalies in the subtropical eastern Pacific. Our results can also be applied to European drought events because of the qualitative linearity in the observations and in our linear methods. [ABSTRACT FROM AUTHOR]

This study aimed to analyze the spatiotemporal changes of historical droughts over the Muda River basin (MRB), Malaysia, from 1985 to 2019 using the Standardized Precipitation Index (SPI) and the Standardized Streamflow Index (SSI). The Mann–Kendall test and Sens’ slope were used to evaluate the trends and magnitude changes in the droughts, respectively, while Spearman’s rho was applied to understand the relationships of the droughts with large-scale atmospheric circulations, such as the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), and the Madden–Julian Oscillation (MJO). The results show that the intense droughts in the MRB mostly occurred in 1991–1992, 1995, 1998, 2002–2003, 2005–2006, 2008, 2012–2013, and 2016. In addition, a declining SPI trend was found from May to December at most of the stations. About 80% of the stations experienced about 10 severely dry droughts, while almost all stations experienced at least 5 extremely dry events. Moreover, a higher response rate of the SSI than the SPI was found during low-rainfall months from January to May. Lastly, ENSO had a larger impact on the drought formations over the MRB compared to the IOD and MJO, especially during the dry period.

There is a rainfall variability biennial relationship between Central America (CA) and equatorial South America (ESA) over the tropical western hemisphere, which is known to have arisen due to the combined effects of ENSO and tropical North Atlantic (TNA) SST. Here, the authors report that this biennial rainfall relationship between CA and ESA has weakened remarkably since 2000, with weakening in both in-phase and out-of-phase rainfall transitions. The observed decadal changes in the biennial relationship between CA and ESA rainfall can be attributed to changes in the effects of ENSO and TNA SST since 2000, which may be associated with more frequent occurrences of the central Pacific or ‘Modoki’ type El Niño. The weakening of the association with ENSO for CA rainfall since 2000 might have given rise to the weakening of the in-phase rain transition from CA rainfall to the following ESA rainfall. The weakened linkage between boreal-winter ESA rainfall and the subsequent boreal-summer TNA SST since 2000 may have resulted in the weakening of the out-of-phase rainfall transition from boreal-winter ESA rainfall to the subsequent boreal-summer CA rainfall.

Recent studies suggest that the interannual variability in the tropical Pacific associated with the El Niño–Southern Oscillation has weakened since 2000. In this study, the authors report that the interannual variability of the contrast in rainfall between the eastern equatorial Pacific and equatorial Atlantic has also weakened remarkably since 2000, attributable to the weakened interannual variability in the zonal sea surface temperature gradient between the eastern equatorial Pacific and equatorial Atlantic and in the associated equatorial low-level zonal wind across South America linking the two ocean basins. Diagnosis of a column-integrated moisture budget indicates that the weakening in the interannual variability of the contrast in rainfall is primarily attributable to the changes in moisture convergence associated with vertical motion. The results highlight the clear weakened interannual variability in the coupled equatorial Pacific–Atlantic climate system since 2000, including the Pacific El Niño, Atlantic Niño, equatorial zonal wind across South America, and rainfall over the eastern equatorial Pacific and equatorial Atlantic.

Developing countries with a paucity of direct rainfall measuring systems on the ground, satellite remote sensing is increasingly being relied upon as a means through which national governmental response and future strategies to manage natural disasters, such as drought and flooding are decided upon. The aim of this study was to assess the performance of the Tropical Applications of Meteorology Using Satellite Data and Ground-Based Observations (TAMSAT) monthly rainfall dataset for southern Africa by comparing it to two widely used stable global rainfall datasets, the Global Precipitation Climatology Centre (GPCC) and the Global Precipitation Climatology Project (GPCP) datasets. Using rainfall records for the period 1984–2010, four statistical measures namely, the correlation coefficient, the Root Mean Square Error (RMSE), relative bias, mean absolute deviation and the Nash Sutcliffe Efficiency index were calculated to facilitate pair-wise comparisons. This inter-product comparison study found a good agreement between TAMSAT satellite rainfall and the two global rainfall products with regard to the spatial and temporal representation of monthly rainfall over the region. However, it was found that TAMSAT consistently provides lower monthly rainfall estimates compared to both GPCC and GPCP rainfall estimates over southern Africa. The relative bias between TAMSAT and the two global rainfall products (GPCC and GPCP) was much lower (≤10%) during the austral summer months (November–March) compared to winter when the relative bias surpassed 70%. These findings indicate TAMSAT is geared more towards convective precipitation brought about by the inter-tropical convergence zone in summer. The observed large discrepancy between TAMSAT estimates and those from two mature global rainfall products during winter raises a key concern regarding the use of TAMSAT as a tool for monitoring rainfall patterns and volumes across the southern reaches of the African continent. Overall, the findings of this study demonstrate the diminished ability for TAMSAT to "see" non-convective precipitation from frontal systems as well as orographic rainfall due to its reliance upon the observation of the cold cloud duration and convection characteristics of tropical rainfall systems. This calls for the need to further optimise the TAMSAT algorithm using gauge data so that TAMSAT is better able to characterise different precipitation events in those regions where convective rainfall is far from the only major source of rainfall. • Rainfall is a key determinant of vegetation and crop growth over southern Africa. • Correlation amongst the rainfall estimates was higher during summer. • TAMSAT consistently provides lower monthly rainfall estimates compared to both GPCC and GPCP. • TAMSAT algorithm should be optimized using gauge data to minimize systematic bias. [ABSTRACT FROM AUTHOR]

We quantify seasonal prediction skill of tropical winter rainfall in 14 climate forecast systems. High levels of seasonal prediction skill exist for year‐to‐year rainfall variability in all tropical ocean basins. The tropical East Pacific is the most skilful region, with very high correlation scores, and the tropical West Pacific is also highly skilful. Predictions of tropical Atlantic and Indian Ocean rainfall show lower but statistically significant scores. We compare prediction skill (measured against observed variability) with model predictability (using single forecasts as surrogate observations). Model predictability matches prediction skill in some regions but it is generally greater, especially over the Indian Ocean. We also find significant inter‐basin connections in both observed and predicted rainfall. Teleconnections between basins due to El Niño–Southern Oscillation (ENSO) appear to be reproduced in multi‐model predictions and are responsible for much of the prediction skill. They also explain the relative magnitude of inter‐annual variability, the relative magnitude of predictable rainfall signals and the ranking of prediction skill across different basins. These seasonal tropical rainfall predictions exhibit a severe wet bias, often in excess of 20% of mean rainfall. However, we find little direct relationship between bias and prediction skill. Our results suggest that future prediction systems would be best improved through better model representation of inter‐basin rainfall connections as these are strongly related to prediction skill, particularly in the Indian and West Pacific regions. Finally, we show that predictions of tropical rainfall alone can generate highly skilful forecasts of the main modes of extratropical circulation via linear relationships that might provide a useful tool to interpret real‐time forecasts. Tropical rainfall and its year‐to‐year variability. Seasonal mean climatological rainfall (top left) and inter‐annual variability (top right) of global rainfall from GPCP observations. Tropical rainfall is analysed in the boxed regions for the Indian (45°–100°E, 5°S–10°N), West Pacific (110°–140°E, 5°S–25°N), East Pacific (200 –90 W, 5°S–10°N) and Atlantic (60°–0 W, 5°S–5°N) regions. Mean and standard deviation of ensemble member rainfall over the same years (1993–2012) from a single example prediction system (bottom panels, GloSea5). Note the logarithmic contour interval. Units are mm/day. [ABSTRACT FROM AUTHOR]

The global paleomonsoon concept predicts an antiphase response of monsoon rainfall in the Northern and Southern Hemispheres at timescales where there is asymmetric solar forcing and/or asymmetric hemispheric temperature changes. However, as different monsoon systems have different sensitivities to local, regional, and global forcing, rainfall response may vary regionally, particularly during large global climatic changes such as the last deglaciation where warming occurred in both hemispheres. Despite its role as a key Southern Hemisphere counterpart to the Arabian and Indian summer monsoons, the behavior of the summer monsoon in the Southern Hemisphere of the Indian Ocean during the last deglaciation is unknown. Therefore, we present a new high‐resolution, precisely dated, and replicated speleothem stable isotope record from Tsimanampesotse National Park in southwest Madagascar that covers the last deglaciation. We show that speleothem growth phases respond largely to movements of the Southern Hemisphere summer Hadley circulation (summer extent of the tropical rainbelt/mean Intertropical Convergence Zone location), with some contribution from sea surface temperature changes at key times, such as during the Bølling‐Allerød. In contrast, speleothem δ18Ο responds primarily to sea surface temperature, in particular the location of the deep atmospheric convection isotherm, while summer Hadley circulation changes take a secondary role. Separating the varying influences of temperature and atmospheric circulation in controlling southwest Madagascan rainfall is critical to understanding rainfall variability in both the past and the future. Plain Language Summary: Understanding how monsoon rainfall might change under a changing climate is important to ensure the water supply for millions of people who depend on monsoon rainfall. Despite this, how Southern Hemisphere monsoon systems such as the Madagascan summer monsoon varied in the past are not well understood. We use stalagmites from Tsimanampesotse National Park in southwest Madagascar to create a new record of past changes in monsoon rainfall in the region. We use the timing of stalagmite growth and the stable isotopes of these stalagmites to reveal a series of wet and dry periods during the last deglaciation, a time of rapid climate change. Our new record shows that variability in monsoon rainfall is dependent on both temperature and atmospheric circulation changes. Both southward shifts in the tropical rainfall belt and warmer sea surface temperatures contributed to periods of higher rainfall in southwest Madagascar. Our rainfall sensitive site is able to detect changes in the monsoon that correspond to millennial‐ and centennial‐scale climatic events in the Northern Hemisphere, indicating links with the global tropical monsoon system. Key Points: Speleothem growth and stable isotopes in southwest Madagascar controlled by sea surface temperature and summer Hadley circulation movementSpeleothem δ18Ο follows a threshold response to sea surface temperatures above/below the deep atmospheric circulation isothermSecond order speleothem δ18Ο variability antiphase to northern hemisphere monsoon records, consistent with the global paleomonsoon concept [ABSTRACT FROM AUTHOR]

Accurate seasonal predictions of rainfall may reduce climatic risks that farmers are usually faced with across the tropical and subtropical zones. However, although regional-scale seasonal amounts have regularly been forecasted since 1997/98, the practical use of these seasonal predictions is still limited by myriad factors. This paper synthesizes the main results of a multi-disciplinary ethnographic and climatic project (PICREVAT). Its main objective was to seek the climatic information – beyond the seasonal amounts – critical for crops, both as an actual constraint to crop yields and as identified by the current and past practices and perceptions of farmers. A second goal was to confront the relevance and significance of this climatic information with its spatial coherence, which gives an upper bound of its potential predictability. The ethnographic and climatic analyses were carried out on three very different fields: North Cameroon (mixed food crops associated with a cash crop – cotton – integrated into a national program); Eastern slopes of Mt Kenya (mixed food crops, with a recent development of maize at the expense of sorghum and pearl millet); and Central Argentina (mixed crops and livestock recently converting to monoculture of transgenic soybean, referred to as soybeanization). The ethnographic surveys, as well as yield–climate functions, emphasized the role played by various intra-seasonal characteristics of the rainy seasons beyond the seasonal rainfall amounts, in both actual yields and people’s representations and/or crop management strategies. For instance, the onset of the rainy season in East Africa and North Cameroon, the season duration in the driest district of the eastern slopes of Mount Kenya, or rains at the core (August) and at the end of the rainy season in North Cameroon have been highlighted. The dynamics of farming systems (i.e. soybeanization in Central Argentina, increasing popularity of maize in East Africa, recent decline of cotton in North Cameroon) were also emphasized as active drivers; these slow changes could increase climatic vulnerability (i.e. soybean is far more sensitive to rainfall variations than wheat, maize is less drought-resistant than sorghum or millet), at least for the least flexible actors (such as the non-capitalized farmers in Central Argentina). The cross between ethnographic surveys and climatic analyses enabled us to identify climate variables that are both useful to farmers and potentially predictable. These variables do not appear to be common across the surveyed fields. The best example is the rainy season onset date whose variations, depending on regions, crop species and farming practices may either have a major/minor role in crop performance and/or crop management, or may have a high/low potential predictability.

ABSTRACT: In this study, we investigate a possible mechanism for the dichotomy in climatology of marine rainfall and sea surface temperature (SST) over a part of the Southwest Indian Ocean (SWIO) during boreal winter (January and February) with state‐of‐the‐art satellite and reanalysis data sets. Rainfall to the north of the Mozambique Channel, bounded 10°–5°S and 40°–50°E, is found to be quite feeble despite being in the warm SST regime of up to 29–29.5 °C. The rainfall intensity is rather found to be highly associated with the atmospheric surface divergence. The vigorous rainfall is associated with the more convergence over the Intertropical Convergence Zone (ITCZ), while the weak rainfall is linked with the divergence to the north of the Mozambique Channel. The surface divergent flow to the north of the Mozambique Channel is associated with a deep southward penetration of the northerly Indian Winter Monsoon (IWM). Corresponding to the surface divergent field, a relatively high sea level pressure (SLP) compared to the SLP in the ITCZ, weak subsidence, and low‐level stratiform clouds are formed to the north of the Mozambique Channel, despite the warm, tropical SST. These atmospheric conditions are most likely conductive to the inhibition of cumulus convection over the region and the unique relationship between rainfall and SST seems peculiar. Our analysis also shows that the rare occurrence of tropical cyclones over the area is attributed to a high‐pressure surge and the associated positive surface vorticity (anti‐cyclonic). This study suggests that the area to the north of the Mozambique Channel is dynamically interesting for climatological studies. [ABSTRACT FROM AUTHOR]