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Rory G. J. Fitzpatrick, Caroline L. Bain, Peter Knippertz, John H. Marsham, and Douglas J. Parker

Abstract

Accurate prediction of the commencement of local rainfall over West Africa can provide vital information for local stakeholders and regional planners. However, in comparison with analysis of the regional onset of the West African monsoon, the spatial variability of the local monsoon onset has not been extensively explored. One of the main reasons behind the lack of local onset forecast analysis is the spatial noisiness of local rainfall. A new method that evaluates the spatial scale at which local onsets are coherent across West Africa is presented. This new method can be thought of as analogous to a regional signal against local noise analysis of onset. This method highlights regions where local onsets exhibit a quantifiable degree of spatial consistency (denoted local onset regions or LORs). It is found that local onsets exhibit a useful amount of spatial agreement, with LORs apparent across the entire studied domain; this is in contrast to previously found results. Identifying local onset regions and understanding their variability can provide important insight into the spatial limit of monsoon predictability. While local onset regions can be found over West Africa, their size is much smaller than the scale found for seasonal rainfall homogeneity. A potential use of local onset regions is presented that shows the link between the annual intertropical front progression and local agronomic onset.

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Caroline L. Bain, Douglas J. Parker, Christopher M. Taylor, Laurent Kergoat, and Françoise Guichard

Abstract

A set of nighttime tethered balloon and kite measurements from the central Sahel (15.2°N, 1.3°W) in August 2005 were acquired and analyzed. A composite of all the nights’ data was produced using boundary layer height to normalize measured altitudes. The observations showed some typical characteristics of nocturnal boundary layer development, notably a strong inversion after sunset and the formation of a low-level nocturnal jet later in the night. On most nights, the sampled jet did not change direction significantly during the night.

The boundary layer thermodynamic structure displayed some variations from one night to the next. This was investigated using two contrasting case studies from the period. In one of these case studies (18 August 2005), the low-level wind direction changed significantly during the night. This change was captured well by two large-scale models, suggesting that the large-scale dynamics had a significant impact on boundary layer winds on this night. For both case studies, the models tended to underestimate near-surface wind speeds during the night, which is a feature that may lead to an underestimation of moisture flux northward by models.

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Rory G. J. Fitzpatrick, Caroline L. Bain, Peter Knippertz, John H. Marsham, and Douglas J. Parker

Abstract

The onset of the West African monsoon (WAM) marks a vital time for local and regional stakeholders. While the seasonal progression of monsoon winds and the related migration of precipitation from the Guinea Coast toward the Sudan/Sahel is apparent, there exist contrasting man-made definitions of what the WAM onset means. Broadly speaking, onset can be analyzed regionally, locally, or over a designated intermediate scale. There are at least 18 distinct definitions of the WAM onset in publication, with little work done on comparing observed onset from different definitions or comparing onset realizations across different datasets and resolutions. Here, nine definitions have been calculated using multiple datasets of different metrics at different resolutions. It is found that mean regional onset dates are consistent across multiple datasets and different definitions. There is low interannual variability in regional onset, suggesting that regional seasonal forecasting of the onset provides few benefits over climatology. In contrast, local onsets show high spatial, interannual, and interdefinition variability. Furthermore, it is found that there is little correlation between local onset dates and regional onset dates across West Africa, implying a disharmony between regional measures of onset and the experience on a local scale. The results of this study show that evaluation of seasonal monsoon onset forecasts is far from straightforward. Given a seasonal forecasting model, it is possible to simultaneously have a good and a bad prediction of monsoon onset simply through selection of the onset definition and observational dataset used for comparison.

Open access
Beth J. Woodhams, Cathryn E. Birch, John H. Marsham, Todd P. Lane, Caroline L. Bain, and Stuart Webster

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.

Open access
Beth J. Woodhams, Cathryn E. Birch, John H. Marsham, Caroline L. Bain, Nigel M. Roberts, and Douglas F. A. Boyd

ABSTRACT

Forecasting convective rainfall in the tropics is a major challenge for numerical weather prediction. The use of convection-permitting (CP) forecast models in the tropics has lagged behind the midlatitudes, despite the great potential of such models in this region. In the scientific literature, there is very little evaluation of CP models in the tropics, especially over an extended time period. This paper evaluates the prediction of convective storms for a period of 2 years in the Met Office operational CP model over East Africa and the global operational forecast model. A novel localized form of the fractions skill score is introduced, which shows variation in model skill across the spatial domain. Overall, the CP model and the global model both outperform a 24-h persistence forecast. The CP model shows greater skill than the global model, in particular on subdaily time scales and for storms over land. Forecasts over Lake Victoria are also improved in the CP model, with an increase in hit rate of up to 20%. Contrary to studies in the midlatitudes, the skill of both models shows a large dependence on the time of day and comparatively little dependence on the forecast lead time within a 48-h forecast. Although these results provide more motivation for forecasters to use the CP model to produce subdaily forecasts with increased detail, there is a clear need for more in situ observations for data assimilation into the models and for verification. A move toward ensemble forecasting could have further benefits.

Open access
Wilfried M. Pokam, Caroline L. Bain, Robin S. Chadwick, Richard Graham, Denis Jean Sonwa, and Francois Mkankam Kamga

Abstract

This paper investigates and characterizes the control mechanisms of the low-level circulation over west equatorial Africa (WEA) using four reanalysis datasets. Emphasis is placed on the contribution of the divergent and rotational circulation to the total flow. Additional focus is made on analyzing the zonal wind component, in order to gain insight into the processes that control the variability of the low-level westerlies (LLW) in the region. The results suggest that the control mechanisms differ north and south of 6°N. In the north, the LLW are primarily a rotational flow forming part of the cyclonic circulation driven primarily by the heat low of the West African monsoon system. This northern branch of the LLW is well developed from June to August and disappears in December–February. South of 6°N, the seasonal variability of the LLW is controlled by the heating contrast between cooling associated with subsidence over the ocean and heating over land regions largely south of the equator, where ascent prevails. The heating contrasts lead to a Walker-type circulation with development of LLW as its lower branch. Thus, evidence is presented that the LLW are driven by differential heating. This contrasts with the traditional conceptual view that the Saint Helena high is the primary driver of low-level circulation off the Atlantic Ocean to WEA. Forest cover in WEA may modulate the latent heating that helps to drive the differential heating and maintain the LLW, and this interaction should be the focus of further study.

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Caroline L. Bain, Jorge De Paz, Jason Kramer, Gudrun Magnusdottir, Padhraic Smyth, Hal Stern, and Chia-chi Wang

Abstract

A Markov random field (MRF) statistical model is introduced, developed, and validated for detecting the east Pacific intertropical convergence zone in instantaneous satellite data from May through October. The MRF statistical model uses satellite data at a given location as well as information from its neighboring points (in time and space) to decide whether the given point is classified as ITCZ or non-ITCZ. Two different labels of ITCZ occurrence are produced. IR-only labels result from running the model with 3-hourly infrared data available for a 30-yr period, 1980–2009. All-data labels result from running the model with additional satellite data (visible and total precipitable water), available from 1995 to 2008. IR-only labels detect less area of ITCZ than all-data labels, especially where the ITCZ is shallower. Yet, qualitatively, the results for the two sets of labels are similar.

The seasonal distribution of the ITCZ through the summer half year is presented, showing typical location and extent. The ITCZ is mostly confined to the eastern Pacific in May, and becomes more zonally distributed toward September and October each year. Northward and westward shifts in the location of the ITCZ occur in line with the seasonal cycle and warm sea surface temperatures. The ITCZ is quite variable on interannual time scales and highly correlated with ENSO variability. When the ENSO signal was removed from labels, interannual variability remained high. The resulting IR-only labels, representing the longer time series, showed no evidence of a trend in location nor evidence of a trend in area for the 30-yr period.

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Carlo Cafaro, Beth J. Woodhams, Thorwald H. M. Stein, Cathryn E. Birch, Stuart Webster, Caroline L. Bain, Andrew Hartley, Samantha Clarke, Samantha Ferrett, and Peter Hill

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.

Open access
Kenneth R. Knapp, Steve Ansari, Caroline L. Bain, Mark A. Bourassa, Michael J. Dickinson, Chris Funk, Chip N. Helms, Christopher C. Hennon, Christopher D. Holmes, George J. Huffman, James P. Kossin, Hai-Tien Lee, Alexander Loew, and Gudrun Magnusdottir

Geostationary satellites have provided routine, high temporal resolution Earth observations since the 1970s. Despite the long period of record, use of these data in climate studies has been limited for numerous reasons, among them that no central archive of geostationary data for all international satellites exists, full temporal and spatial resolution data are voluminous, and diverse calibration and navigation formats encumber the uniform processing needed for multisatellite climate studies. The International Satellite Cloud Climatology Project (ISCCP) set the stage for overcoming these issues by archiving a subset of the full-resolution geostationary data at ~10-km resolution at 3-hourly intervals since 1983. Recent efforts at NOAA's National Climatic Data Center to provide convenient access to these data include remapping the data to a standard map projection, recalibrating the data to optimize temporal homogeneity, extending the record of observations back to 1980, and reformatting the data for broad public distribution. The Gridded Satellite (GridSat) dataset includes observations from the visible, infrared window, and infrared water vapor channels. Data are stored in Network Common Data Format (netCDF) using standards that permit a wide variety of tools and libraries to process the data quickly and easily. A novel data layering approach, together with appropriate satellite and file metadata, allows users to access GridSat data at varying levels of complexity based on their needs. The result is a climate data record already in use by the meteorological community. Examples include reanalysis of tropical cyclones, studies of global precipitation, and detection and tracking of the intertropical convergence zone.

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Adrian M. Tompkins, Douglas J. Parker, Sylvester Danour, Leonard Amekudzi, Caroline L. Bain, Abdul Dominguez, Michael W. Douglas, Andreas H. Fink, David I. F. Grimes, Matthew Hobby, Peter Knippertz, J. Lamb, Kathryn J. Nicklin, and Charles Yorke
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