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  • 1
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    Monthly entomological inoculation rates for studying malaria transmission seasonality in Africa (2018)
    PANGAEA
    Details
    Publication Date: 2023-01-13
    Description: A comprehensive literature review is conducted to create a new database of malaria Entomological Inoculation Rates (EIR), a metric of malaria transmission intensity. All field studies include data at a monthly temporal resolution and a duration of at least one year in order to be able to study seasonality variability in transmission. Care is taken to ensure the data collection methodologies adhere to a specific standard and that the location and timing of the measurements are well documented. Auxiliary information on the population and hydrological setting are included. The database includes measurements that cover Sub-Saharan Africa spanning from 1968 to 2013, thus also facilitating analysis of interannual transmission variability over broad regions.
    Keywords: Africa; Africa_cont; MULT; Multiple investigations
    Type: Dataset
    Format: application/zip, 70.7 kBytes
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 2
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    Weather Research and Forecasting Model (WRF) cloud resolving model output, links to NetCDF files (2017)
    PANGAEA
    In:  Supplement to: Tompkins, Adrian Mark; Semie, Addisu G (2017): Organization of tropical convection in low vertical wind shears: role of updraft entrainment. Journal of Advances in Modeling Earth Systems, https://doi.org/10.1002/2016MS000802
    Details
    Publication Date: 2023-01-13
    Description: Radiative-convective equilibrium simulations with a 2 km horizontal resolution are conducted to investigate the impact on convective organization of different parameterizations for horizonal and vertical sub-grid turbulence mixing. Three standard approaches for representing horizontal diffusion produce starkly differing mixing rates, particularly for the entrainment mixing into updrafts, which differ by more than an order of magnitude between the schemes. The simulations demonstrate that the horizontal sub-grid mixing of water vapor is key, with high mixing rates a necessary condition for organization of convection to occur, since entrainment of dry air into updrafts suppresses convection. It is argued that diabatic budgets, while demonstrating the role of spatially heterogeneous radiative heating rates in driving organization, can overlook the role of physical processes such as updraft entrainment. These results may partially explain previous studies that showed that organization is more likely to occur at coarser resolutions, when entrainment is solely represented by subgrid-scale turbulence schemes, highlighting the need for benchmark simulations of higher horizontal resolution. The recommendation is for the use of larger ensembles to ensure robustness of conclusions to subgrid-scale parameterization assumptions when numerically investigating convective organization, possibly through a coordinated community model intercomparison effort.
    Keywords: File content; File format; File name; File size; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 195 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 3
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    VECTRI simulations of malaria incidence in the highlands of Kenya, accounting for climate, model and initial condition uncertainty using a genetic algorithm framework (2018)
    PANGAEA
    In:  Supplement to: Tompkins, Adrian Mark; Thomson, Madeleine C (2018): Uncertainty in malaria simulations in the highlands of Kenya: Relative contributions of model parameter setting, driving climate and initial condition errors. PLoS ONE, 13(9), e0200638, https://doi.org/10.1371/journal.pone.0200638
    Details
    Publication Date: 2023-01-13
    Description: The output is simulated cases per 1000 population for a highland location in the Kenyan highlands. Each file represents a single ensemble member integration of the model in the final generation of the genetic algorithm calibration method outlined in the paper. The global meta data gives the set of parameters used to define this run, as well as the exact version of the model code used (ref. http://www.gitlab.com/tompkins/vectri).
    Keywords: Africa, Kenya; File content; File format; File name; File size; Kenya; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 15 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 4
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    Seasonal forecasts of normalized malaria case anomalies for Uganda 1993-2014 (2019)
    PANGAEA
    In:  Supplement to: Tompkins, Adrian Mark; Colón‐González, Felipe J; Di Giuseppe, Francesca; Namanya, Didas B (2019): Dynamical Malaria Forecasts Are Skillful at Regional and Local Scales in Uganda up to 4 Months Ahead. GeoHealth, 3(3), 58-66, https://doi.org/10.1029/2018GH000157
    Details
    Publication Date: 2023-01-30
    Description: The dataset consists of two components ----- 1. Seasonal forecasts at lead time 1 month and lead time 4 months of temperature and rainfall from the ECMWF extended range EPS and seasonal forecast system 4, and of relevant parameters related to malaria incidence and transmission that are produced by the VECTRI malaria model driven by the forecast data. a) Rain: Monthly averaged rainfall (mm/day) b) Temp: Monthly averaged Two metre temperature (deg C) c) water_frac: The fraction of the gridcell covered by temporary water bodies that can act as breeding sites d) PRd: Parasite Ratio, proportion of people that have detectable infection e) EIR: Entomological Inoculation rate, number of infective bites per person per unit day. f) anneir: EIR converted to annual units g) lneir: log function of EIR as a proxy for clinical cases (see manuscript for details) Global attributes give model version and parameter settings for simulations Data covers period from 1993 to 2014. ----- 2. Normalized district case anomalies from Uganda covering oeriod 2004 to 2010, with model forecast data projected to shapefiles for ease of comparison CSV file with the following format: District name, year, lead month, case anomaly, fc anom mem0, mem1, mem2, mem3
    Keywords: Africa, Uganda; health; malaria; MULT; Multiple investigations; seasonal forecast; Uganda
    Type: Dataset
    Format: application/zip, 2 datasets
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 5
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    (Supplement 1) Seasonal forecasts of temperature, rainfall and other relevant parameters related to malaria incidence and transmission that are produced by the VECTRI malaria model driven by the forecast data, links to netCDF files (2019)
    PANGAEA
    Details
    Publication Date: 2023-01-30
    Keywords: Africa, Uganda; File format; File name; File size; malaria; MULT; Multiple investigations; seasonal forecast; Uganda; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 40 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 6
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    (Supplement 2) Normalized district case anomalies from Uganda covering period 2004 to 2010, link to csv file (2019)
    PANGAEA
    Details
    Publication Date: 2023-01-30
    Keywords: Africa, Uganda; health; malaria; MULT; Multiple investigations; seasonal forecast; Uganda
    Type: Dataset
    Format: application/zip, 875.5 kBytes
    Location Call Number Limitation Availability
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    DATA PANGAEA
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