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Abstract
Biases in simulating the diurnal cycle of convection near the western coast of the island of Sumatra have been investigated using the data from the pilot field campaign of the Years of the Maritime Continent (pre-YMC). The campaign was carried out at a sea [Research Vessel (R/V) Mirai] and a land (Bengkulu, Sumatra) site. Simulations are performed using a tropical configuration of the Met Office model at a grid resolution of 1.5 km in a limited-area mode. The focus of this study is to understand how biases in the input conditions from ECMWF high-resolution deterministic forecast affect the diurnal cycle. Modeled precipitation is found to be delayed and weak, with cold SST bias in the model as the key contributing factor affecting convection at both sites. Colder SST causes a delay in the trigger of convection at Bengkulu by delaying the onset of the local land breeze, which in turn delays the local convergence. The cold outflow from precipitation over the adjacent mountain is also found to be delayed in the model, contributing to the total delay. This delay in the evening convection at Bengkulu is shown to directly affect the timing of nighttime convection at Mirai. Weaker convection at Bengkulu is argued to be due to lower-tropospheric dry humidity bias in the model initial condition. Convection at Mirai is shown to be caused by the convergence of the cold outflow from Bengkulu with the prevailing landward wind over the sea. Both thermodynamic and dynamic conditions near the cold outflow front are found to be less favorable for intense convection in the simulation, the reason for which is argued to be a combination of the cold SST bias and a weaker cold outflow.
Abstract
Biases in simulating the diurnal cycle of convection near the western coast of the island of Sumatra have been investigated using the data from the pilot field campaign of the Years of the Maritime Continent (pre-YMC). The campaign was carried out at a sea [Research Vessel (R/V) Mirai] and a land (Bengkulu, Sumatra) site. Simulations are performed using a tropical configuration of the Met Office model at a grid resolution of 1.5 km in a limited-area mode. The focus of this study is to understand how biases in the input conditions from ECMWF high-resolution deterministic forecast affect the diurnal cycle. Modeled precipitation is found to be delayed and weak, with cold SST bias in the model as the key contributing factor affecting convection at both sites. Colder SST causes a delay in the trigger of convection at Bengkulu by delaying the onset of the local land breeze, which in turn delays the local convergence. The cold outflow from precipitation over the adjacent mountain is also found to be delayed in the model, contributing to the total delay. This delay in the evening convection at Bengkulu is shown to directly affect the timing of nighttime convection at Mirai. Weaker convection at Bengkulu is argued to be due to lower-tropospheric dry humidity bias in the model initial condition. Convection at Mirai is shown to be caused by the convergence of the cold outflow from Bengkulu with the prevailing landward wind over the sea. Both thermodynamic and dynamic conditions near the cold outflow front are found to be less favorable for intense convection in the simulation, the reason for which is argued to be a combination of the cold SST bias and a weaker cold outflow.
Abstract
From late January to early February 2019, a quasi-stationary monsoon depression situated over northeast Australia caused devastating floods. During the first week of February, when the event had its greatest impact in northwest Queensland, record-breaking precipitation accumulations were observed in several locations, accompanied by strong winds, substantial cold maximum temperature anomalies, and related wind chill. In spite of the extreme nature of the event, the monthly rainfall outlook for February issued by Australia’s Bureau of Meteorology on 31 January provided no indication of the event. In this study, we evaluate the dynamics of the event and assess how predictable it was across a suite of ensemble model forecasts using the Met Office numerical weather prediction (NWP) system, focusing on a 1-week lead time. In doing so, we demonstrate the skill of the NWP system in predicting the possibility of such an extreme event occurring. We further evaluate the benefits derived from running the ensemble prediction system at higher resolution than used operationally at the Met Office and with a fully coupled dynamical ocean. We show that the primary forecast errors are generated locally, with key sources of these errors including atmosphere–ocean coupling and a known bias associated with the behavior of the convection scheme around the coast. We note that a relatively low-resolution ensemble approach requires limited computing resources, yet has the capacity in this event to provide useful information to decision-makers with over a week’s notice, beyond the duration of many operational deterministic forecasts.
Abstract
From late January to early February 2019, a quasi-stationary monsoon depression situated over northeast Australia caused devastating floods. During the first week of February, when the event had its greatest impact in northwest Queensland, record-breaking precipitation accumulations were observed in several locations, accompanied by strong winds, substantial cold maximum temperature anomalies, and related wind chill. In spite of the extreme nature of the event, the monthly rainfall outlook for February issued by Australia’s Bureau of Meteorology on 31 January provided no indication of the event. In this study, we evaluate the dynamics of the event and assess how predictable it was across a suite of ensemble model forecasts using the Met Office numerical weather prediction (NWP) system, focusing on a 1-week lead time. In doing so, we demonstrate the skill of the NWP system in predicting the possibility of such an extreme event occurring. We further evaluate the benefits derived from running the ensemble prediction system at higher resolution than used operationally at the Met Office and with a fully coupled dynamical ocean. We show that the primary forecast errors are generated locally, with key sources of these errors including atmosphere–ocean coupling and a known bias associated with the behavior of the convection scheme around the coast. We note that a relatively low-resolution ensemble approach requires limited computing resources, yet has the capacity in this event to provide useful information to decision-makers with over a week’s notice, beyond the duration of many operational deterministic forecasts.
Kinematic GNSS Estimation of Zenith Wet Delay over a Range of AltitudesAbstract
Atmospheric water vapor estimates from static ground-based Global Navigation Satellite System (GNSS) receivers are now operationally assimilated into numerical weather prediction models, either as total precipitable water vapor (PWV) or zenith total delay. To extend this concept, the estimation of water vapor using kinematic GNSS has been investigated for over a decade. Previous kinematic GNSS PWV studies suggest a 2–3-mm PWV measurement agreement with radiosondes, almost commensurate with static GNSS PWV measurement accuracy, but the only comprehensive experiments undertaken have been shipborne. As a first step toward extending sea level–based studies to airborne experiments that obtain atmospheric profiles, the authors considered the kinematic GNSS estimation of atmospheric water vapor along a repeatable trajectory spanning substantial topographic relief, namely, the Snowdon Mountain Railway, United Kingdom. The atmospheric water vapor was indirectly quantified through the GNSS estimation of zenith wet delay (ZWD). Static GNSS [GPS+ Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS)] reference receivers were installed at the 950-m-altitude profile’s extremities, providing ZWD reference values that were interpolated to the train’s altitude, together with profiles from 100-m-resolution runs of the Met Office Unified Model. Similar GNSS ZWD accuracies to those from shipborne studies are demonstrated, namely, 12.1 mm (RMS) using double-difference relative kinematic GPS and 16.2 mm using kinematic GPS precise point positioning (PPP), but which is improved to 11.6 mm when using kinematic GPS+GLONASS PPP, commensurate with the relative kinematic GPS. The PPP solution represents a more typical airborne estimation scenario, that is, without relying on nearby GNSS reference stations.
Abstract
Atmospheric water vapor estimates from static ground-based Global Navigation Satellite System (GNSS) receivers are now operationally assimilated into numerical weather prediction models, either as total precipitable water vapor (PWV) or zenith total delay. To extend this concept, the estimation of water vapor using kinematic GNSS has been investigated for over a decade. Previous kinematic GNSS PWV studies suggest a 2–3-mm PWV measurement agreement with radiosondes, almost commensurate with static GNSS PWV measurement accuracy, but the only comprehensive experiments undertaken have been shipborne. As a first step toward extending sea level–based studies to airborne experiments that obtain atmospheric profiles, the authors considered the kinematic GNSS estimation of atmospheric water vapor along a repeatable trajectory spanning substantial topographic relief, namely, the Snowdon Mountain Railway, United Kingdom. The atmospheric water vapor was indirectly quantified through the GNSS estimation of zenith wet delay (ZWD). Static GNSS [GPS+ Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS)] reference receivers were installed at the 950-m-altitude profile’s extremities, providing ZWD reference values that were interpolated to the train’s altitude, together with profiles from 100-m-resolution runs of the Met Office Unified Model. Similar GNSS ZWD accuracies to those from shipborne studies are demonstrated, namely, 12.1 mm (RMS) using double-difference relative kinematic GPS and 16.2 mm using kinematic GPS precise point positioning (PPP), but which is improved to 11.6 mm when using kinematic GPS+GLONASS PPP, commensurate with the relative kinematic GPS. The PPP solution represents a more typical airborne estimation scenario, that is, without relying on nearby GNSS reference stations.
Abstract
This paper describes the current status and discuss the validity of the fluorescent particle (FP) tracer technique. Properties of the material itself, the blower generator, membrane filter, drum impactor, and Rotorod samplers, and of counting techniques, are described. The inherent and operational errors involved are evaluated, and evidence on the atmospheric diffusion, fallout and impaction, and fluorescent stability of the particles is presents. It is concluded that in the present state of development of the technique the errors, in terms of 90% confidence Intervals, are approximately ±5–10% for source strength determination, ±10–12% (if 300 particles are counted) for dosages determined by the Rotorod, and ±17–20% for dosages determined by the membrane filter sampler. The effects of atypical diffusion on the validity of the method appear to be insignificant, and fluorescence losses may be controlled by proper selection of materials. For ground releases the losses by fallout and impaction may amount to from 1% to 10% during the first few miles of travel, depending on the rate of rise of the cloud and the nature of the ground cover. For larger travel distances, if the cloud height exceeds 100 meters the fallout loss should he below 2% per hour.
Abstract
This paper describes the current status and discuss the validity of the fluorescent particle (FP) tracer technique. Properties of the material itself, the blower generator, membrane filter, drum impactor, and Rotorod samplers, and of counting techniques, are described. The inherent and operational errors involved are evaluated, and evidence on the atmospheric diffusion, fallout and impaction, and fluorescent stability of the particles is presents. It is concluded that in the present state of development of the technique the errors, in terms of 90% confidence Intervals, are approximately ±5–10% for source strength determination, ±10–12% (if 300 particles are counted) for dosages determined by the Rotorod, and ±17–20% for dosages determined by the membrane filter sampler. The effects of atypical diffusion on the validity of the method appear to be insignificant, and fluorescence losses may be controlled by proper selection of materials. For ground releases the losses by fallout and impaction may amount to from 1% to 10% during the first few miles of travel, depending on the rate of rise of the cloud and the nature of the ground cover. For larger travel distances, if the cloud height exceeds 100 meters the fallout loss should he below 2% per hour.
Abstract
The Lake Victoria region in East Africa is a hot spot for intense convective storms that are responsible for the deaths of thousands of fishermen each year. The processes responsible for the initiation, development, and propagation of the storms are poorly understood and forecast skill is limited. Key processes for the life cycle of two storms are investigated using Met Office Unified Model convection-permitting simulations with 1.5 km horizontal grid spacing. The two cases are analyzed alongside a simulation of a period with no storms to assess the roles of the lake–land breeze, downslope mountain winds, prevailing large-scale winds, and moisture availability. While seasonal changes in large-scale moisture availability play a key role in storm development, the lake–land-breeze circulation is a major control on the initiation location, timing, and propagation of convection. In the dry season, opposing offshore winds form a bulge of moist air above the lake surface overnight that extends from the surface to ~1.5 km and may trigger storms in high CAPE/low CIN environments. Such a feature has not been explicitly observed or modeled in previous literature. Storms over land on the preceding day are shown to alter the local atmospheric moisture and circulation to promote storm formation over the lake. The variety of initiation processes and differing characteristics of just two storms analyzed here show that the mean diurnal cycle over Lake Victoria alone is inadequate to fully understand storm formation. Knowledge of daily changes in local-scale moisture variability and circulations are keys for skillful forecasts over the lake.
Abstract
The Lake Victoria region in East Africa is a hot spot for intense convective storms that are responsible for the deaths of thousands of fishermen each year. The processes responsible for the initiation, development, and propagation of the storms are poorly understood and forecast skill is limited. Key processes for the life cycle of two storms are investigated using Met Office Unified Model convection-permitting simulations with 1.5 km horizontal grid spacing. The two cases are analyzed alongside a simulation of a period with no storms to assess the roles of the lake–land breeze, downslope mountain winds, prevailing large-scale winds, and moisture availability. While seasonal changes in large-scale moisture availability play a key role in storm development, the lake–land-breeze circulation is a major control on the initiation location, timing, and propagation of convection. In the dry season, opposing offshore winds form a bulge of moist air above the lake surface overnight that extends from the surface to ~1.5 km and may trigger storms in high CAPE/low CIN environments. Such a feature has not been explicitly observed or modeled in previous literature. Storms over land on the preceding day are shown to alter the local atmospheric moisture and circulation to promote storm formation over the lake. The variety of initiation processes and differing characteristics of just two storms analyzed here show that the mean diurnal cycle over Lake Victoria alone is inadequate to fully understand storm formation. Knowledge of daily changes in local-scale moisture variability and circulations are keys for skillful forecasts over the lake.
Abstract
Forecasting rainfall in the tropics is a major challenge for numerical weather prediction. Convection-permitting (CP) models are intended to enable forecasts of high-impact weather events. Development and operation of these models in the tropics has only just been realized. This study describes and evaluates a suite of recently developed Met Office Unified Model CP ensemble forecasts over three domains in Southeast Asia, covering Malaysia, Indonesia, and the Philippines. The fractions skill score is used to assess the spatial scale dependence of skill in forecasts of precipitation during October 2018–March 2019. CP forecasts are skillful for 3-h precipitation accumulations at spatial scales greater than 200 km in all domains during the first day of forecasts. Skill decreases with lead time but varies depending on time of day over Malaysia and Indonesia, due to the importance of the diurnal cycle in driving rainfall in those regions. Skill is largest during daytime when precipitation is over land and is constrained by orography. Comparison of CP ensembles using 2.2-, 4.5-, and 8.8-km grid spacing and an 8.8-km ensemble with parameterized convection reveals that varying resolution has much less effect on ensemble skill and spread than the representation of convection. The parameterized ensemble is less skillful than CP ensembles over Malaysia and Indonesia and more skillful over the Philippines; however, the parameterized ensemble has large drops in skill and spread related to deficiencies in its diurnal cycle representation. All ensembles are underspread indicating that future model development should focus on this issue.
Abstract
Forecasting rainfall in the tropics is a major challenge for numerical weather prediction. Convection-permitting (CP) models are intended to enable forecasts of high-impact weather events. Development and operation of these models in the tropics has only just been realized. This study describes and evaluates a suite of recently developed Met Office Unified Model CP ensemble forecasts over three domains in Southeast Asia, covering Malaysia, Indonesia, and the Philippines. The fractions skill score is used to assess the spatial scale dependence of skill in forecasts of precipitation during October 2018–March 2019. CP forecasts are skillful for 3-h precipitation accumulations at spatial scales greater than 200 km in all domains during the first day of forecasts. Skill decreases with lead time but varies depending on time of day over Malaysia and Indonesia, due to the importance of the diurnal cycle in driving rainfall in those regions. Skill is largest during daytime when precipitation is over land and is constrained by orography. Comparison of CP ensembles using 2.2-, 4.5-, and 8.8-km grid spacing and an 8.8-km ensemble with parameterized convection reveals that varying resolution has much less effect on ensemble skill and spread than the representation of convection. The parameterized ensemble is less skillful than CP ensembles over Malaysia and Indonesia and more skillful over the Philippines; however, the parameterized ensemble has large drops in skill and spread related to deficiencies in its diurnal cycle representation. All ensembles are underspread indicating that future model development should focus on this issue.
Abstract
Analysis of a high-resolution, convection-permitting simulation of the tropical Indian Ocean has revealed empirical relationships between precipitation and gravity wave vertical momentum flux on grid scales typical of earth system models. Hence, the authors take a rough functional form, whereby the wave flux source spectrum has an amplitude proportional to the square root of total precipitation, to represent gravity wave source strengths in the Met Office global model’s spectral nonorographic scheme. Key advantages of the new source are simplicity and responsiveness to changes in convection processes without dependence upon model-specific details of their representation. Thus, the new source scheme is potentially a straightforward adaptation for a class of spectral gravity wave schemes widely used for current state-of-the-art earth system models. Against an invariant source, the new parameterized source generates launch-level flux amplitudes with greater spatial and temporal variability, producing probability density functions for absolute momentum flux over the ocean that have extended tails of large-amplitude, low-occurrence events. Such distributions appear more realistic in comparison with reported balloon observations. Source intermittency at the launch level affects mean fluxes at higher levels in two ways: directly, as a result of upward propagation of the new source variation, and indirectly, through changes in filtering characteristics that arise from intermittency. Initial assessment of the new scheme in the Met Office global model indicates an improved representation of the quasi-biennial oscillation and sensitivity that offers potential for further impact in the future.
Abstract
Analysis of a high-resolution, convection-permitting simulation of the tropical Indian Ocean has revealed empirical relationships between precipitation and gravity wave vertical momentum flux on grid scales typical of earth system models. Hence, the authors take a rough functional form, whereby the wave flux source spectrum has an amplitude proportional to the square root of total precipitation, to represent gravity wave source strengths in the Met Office global model’s spectral nonorographic scheme. Key advantages of the new source are simplicity and responsiveness to changes in convection processes without dependence upon model-specific details of their representation. Thus, the new source scheme is potentially a straightforward adaptation for a class of spectral gravity wave schemes widely used for current state-of-the-art earth system models. Against an invariant source, the new parameterized source generates launch-level flux amplitudes with greater spatial and temporal variability, producing probability density functions for absolute momentum flux over the ocean that have extended tails of large-amplitude, low-occurrence events. Such distributions appear more realistic in comparison with reported balloon observations. Source intermittency at the launch level affects mean fluxes at higher levels in two ways: directly, as a result of upward propagation of the new source variation, and indirectly, through changes in filtering characteristics that arise from intermittency. Initial assessment of the new scheme in the Met Office global model indicates an improved representation of the quasi-biennial oscillation and sensitivity that offers potential for further impact in the future.
Abstract
Convection-permitting ensemble prediction systems (CP-ENS) have been implemented in the midlatitudes for weather forecasting time scales over the past decade, enabled by the increase in computational resources. Recently, efforts are being made to study the benefits of CP-ENS for tropical regions. This study examines CP-ENS forecasts produced by the Met Office over tropical East Africa, for 24 cases in the period April–May 2019. The CP-ENS, an ensemble with parameterized convection (Glob-ENS), and their deterministic counterparts are evaluated against rainfall estimates derived from satellite observations (GPM-IMERG). The CP configurations have the best representation of the diurnal cycle, although heavy rainfall amounts are overestimated compared to observations. Pairwise comparisons between the different configurations reveal that the CP-ENS is generally the most skillful forecast for both 3- and 24-h accumulations of heavy rainfall (97th percentile), followed by the CP deterministic forecast. More precisely, probabilistic forecasts of heavy rainfall, verified using a neighborhood approach, show that the CP-ENS is skillful at scales greater than 100 km, significantly better than the Glob-ENS, although not as good as found in the midlatitudes. Skill decreases with lead time and varies diurnally, especially for CP forecasts. The CP-ENS is underspread both in terms of forecasting the locations of heavy rainfall and in terms of domain-averaged rainfall. This study demonstrates potential benefits in using CP-ENS for operational forecasting of heavy rainfall over tropical Africa and gives specific suggestions for further research and development, including probabilistic forecast guidance.
Abstract
Convection-permitting ensemble prediction systems (CP-ENS) have been implemented in the midlatitudes for weather forecasting time scales over the past decade, enabled by the increase in computational resources. Recently, efforts are being made to study the benefits of CP-ENS for tropical regions. This study examines CP-ENS forecasts produced by the Met Office over tropical East Africa, for 24 cases in the period April–May 2019. The CP-ENS, an ensemble with parameterized convection (Glob-ENS), and their deterministic counterparts are evaluated against rainfall estimates derived from satellite observations (GPM-IMERG). The CP configurations have the best representation of the diurnal cycle, although heavy rainfall amounts are overestimated compared to observations. Pairwise comparisons between the different configurations reveal that the CP-ENS is generally the most skillful forecast for both 3- and 24-h accumulations of heavy rainfall (97th percentile), followed by the CP deterministic forecast. More precisely, probabilistic forecasts of heavy rainfall, verified using a neighborhood approach, show that the CP-ENS is skillful at scales greater than 100 km, significantly better than the Glob-ENS, although not as good as found in the midlatitudes. Skill decreases with lead time and varies diurnally, especially for CP forecasts. The CP-ENS is underspread both in terms of forecasting the locations of heavy rainfall and in terms of domain-averaged rainfall. This study demonstrates potential benefits in using CP-ENS for operational forecasting of heavy rainfall over tropical Africa and gives specific suggestions for further research and development, including probabilistic forecast guidance.
Abstract
The Maritime Continent experiences some of the world’s most severe convective rainfall, with an intense diurnal cycle. Akey feature is offshore propagation of convection overnight, having peaked over land during the evening. Existing hypotheses suggest this propagation is due to the nocturnal land breeze and environmental wind causing low-level convergence; and/or gravity waves triggering convection as they propagate. We use a convection-permitting configuration of the Met Office Unified Model over Sumatra to test these hypotheses, verifying against observations from the Japanese Years of the Maritime Continent field campaign. In selected case studies there is an organized squall line propagating with the land breeze density current, possibly reinforced by convective cold pools, at ∼3 m s−1 to around 150–300 km offshore. Propagation at these speeds is also seen in a composite mean diurnal cycle. The density current is verified by observations, with offshore low-level wind and virtual potential temperature showing a rapid decrease consistent with a density current front, accompanied by rainfall. Gravity waves are identified in the model with a typical phase speed of 16 m s−1. They trigger isolated cells of convection, usually further offshore and with much weaker precipitation than the squall line. Occasionally, the isolated convection may deepen and the rainfall intensify, if the gravity wave interacts with a substantial pre-existing perturbation such as shallow cloud. The localized convection triggered by gravity waves does not generally propagate at the wave’s own speed, but this phenomenon may appear as propagation along a wave trajectory in a composite that averages over many days of the diurnal cycle.
Abstract
The Maritime Continent experiences some of the world’s most severe convective rainfall, with an intense diurnal cycle. Akey feature is offshore propagation of convection overnight, having peaked over land during the evening. Existing hypotheses suggest this propagation is due to the nocturnal land breeze and environmental wind causing low-level convergence; and/or gravity waves triggering convection as they propagate. We use a convection-permitting configuration of the Met Office Unified Model over Sumatra to test these hypotheses, verifying against observations from the Japanese Years of the Maritime Continent field campaign. In selected case studies there is an organized squall line propagating with the land breeze density current, possibly reinforced by convective cold pools, at ∼3 m s−1 to around 150–300 km offshore. Propagation at these speeds is also seen in a composite mean diurnal cycle. The density current is verified by observations, with offshore low-level wind and virtual potential temperature showing a rapid decrease consistent with a density current front, accompanied by rainfall. Gravity waves are identified in the model with a typical phase speed of 16 m s−1. They trigger isolated cells of convection, usually further offshore and with much weaker precipitation than the squall line. Occasionally, the isolated convection may deepen and the rainfall intensify, if the gravity wave interacts with a substantial pre-existing perturbation such as shallow cloud. The localized convection triggered by gravity waves does not generally propagate at the wave’s own speed, but this phenomenon may appear as propagation along a wave trajectory in a composite that averages over many days of the diurnal cycle.
Abstract
A convection-permitting multiyear regional climate simulation using the Met Office Unified Model has been run for the first time on an Africa-wide domain. The model has been run as part of the Future Climate for Africa (FCFA) Improving Model Processes for African Climate (IMPALA) project, and its configuration, domain, and forcing data are described here in detail. The model [Pan-African Convection-Permitting Regional Climate Simulation with the Met Office UM (CP4-Africa)] uses a 4.5-km horizontal grid spacing at the equator and is run without a convection parameterization, nested within a global atmospheric model driven by observations at the sea surface, which does include a convection scheme. An additional regional simulation, with identical resolution and physical parameterizations to the global model, but with the domain, land surface, and aerosol climatologies of CP4-Africa, has been run to aid in the understanding of the differences between the CP4-Africa and global model, in particular to isolate the impact of the convection parameterization and resolution. The effect of enforcing moisture conservation in CP4-Africa is described and its impact on reducing extreme precipitation values is assessed. Preliminary results from the first five years of the CP4-Africa simulation show substantial improvements in JJA average rainfall compared to the parameterized convection models, with most notably a reduction in the persistent dry bias in West Africa, giving an indication of the benefits to be gained from running a convection-permitting simulation over the whole African continent.
Abstract
A convection-permitting multiyear regional climate simulation using the Met Office Unified Model has been run for the first time on an Africa-wide domain. The model has been run as part of the Future Climate for Africa (FCFA) Improving Model Processes for African Climate (IMPALA) project, and its configuration, domain, and forcing data are described here in detail. The model [Pan-African Convection-Permitting Regional Climate Simulation with the Met Office UM (CP4-Africa)] uses a 4.5-km horizontal grid spacing at the equator and is run without a convection parameterization, nested within a global atmospheric model driven by observations at the sea surface, which does include a convection scheme. An additional regional simulation, with identical resolution and physical parameterizations to the global model, but with the domain, land surface, and aerosol climatologies of CP4-Africa, has been run to aid in the understanding of the differences between the CP4-Africa and global model, in particular to isolate the impact of the convection parameterization and resolution. The effect of enforcing moisture conservation in CP4-Africa is described and its impact on reducing extreme precipitation values is assessed. Preliminary results from the first five years of the CP4-Africa simulation show substantial improvements in JJA average rainfall compared to the parameterized convection models, with most notably a reduction in the persistent dry bias in West Africa, giving an indication of the benefits to be gained from running a convection-permitting simulation over the whole African continent.
