The geographical location of Afghanistan and years of environmental degradation in the country make Afghanistan highly prone to intense and recurring natural hazards such as flooding, earthquakes, snow avalanches, landslides, and droughts. These occur in addition to man-made disasters resulting in the frequent loss of live, livelihoods, and property. The creation, understanding and accessibility of hazard, exposure, vulnerability and risk information is key for effective management of disaster risk. Assuring the resilience of new reconstruction efforts to natural hazards, and maximizing the effectiveness of risk reduction investments to reduce existing risks is important to secure lives and livelihoods. So far, there has been limited disaster risk information produced in Afghanistan, and information that does exist typically lacks standard methodology and does not have uniform geo-spatial coverage. To better understand natural hazard and disaster risk, the World Bank and Global Facility for Disaster Reduction and Recovery (GFDRR) are supporting the development of new fluvial flood, flash flood, drought, landslide, avalanche and seismic risk information in Afghanistan, as well as a first-order analysis of the costs and benefits of resilient reconstruction and risk reduction strategies. For fluvial flood risk a flood modeling framework is being developed that consists of three components: • Hydrological analysis which models how much precipitation comes to runoff. The hydrological analysis is used as a back-bone to compute flow and flooding through the full catchment area during selected events as well as selected return periods. The hydrological simulations also form the backbone of the drought risk assessments (work package 3). • Hydrodynamic analysis, to translate runoff into river flow and inundation and flow over floodplain areas. • Flood impact analysis for calculating the impacts of a flood applied to flood prone areas with high damage potential.

The Exploitation of new data sources, data assimilation and ensemble techniques for storm and flood forecasting Project is a NERC Flood Risk for Extreme Events (FREE) Research Programme project (Round 1 - NE/E002137/1 - Duration January 2007 - April 2010) led by Prof AJ Illingworth, University of Reading. This project investigates possible methods of producing ensemble weather forecasts at high-resolution. These ensembles will be used with raingauge and river flow to improve methods of flood forecasting. The dataset includes radiosonde and wind profiles in England and Wales derived using Doppler radar returns from insects. The radial velocity measurements from insects were converted into VAD profiles by fitting a sinusoid to radial velocities at constant range. All measured profiles have been interpolated to the instrument location. Model output files from experiments assimilating radial winds from insects are also available.

Floods in the UK are often caused by extreme rainfall events. At present, weather forecasts can give an indication of a threat of severe storms which might cause flash floods, but are unable to say precisely when and where the downpours will occur, due to the complex range of processes and space-time scales involved. The first stage is to predict the air motions leading to convergence and ascent at a certain location where the precipitation will be initiated, then the development of the precipitation needs to be forecast, and hydrological models used to produce accurate, quantitative, probabilistic flood predictions. Data assimilation is a sophisticated mathematical technique that combines observations with model predictions to give an analysis of the current state of the atmosphere. This analysis may be used to initialise a weather forecast. Although precipitation is well observed by weather radar, attempts to assimilate radar data have had little success; by the time the rain develops the forecast model state is too far from the truth and the air motions are inconsistent with the position of the first radar precipitation echo.

We propose to overcome this problem by assimilating new types of data from weather radars. These provide information on the evolving humidity fields and air motions in the lower atmosphere so that the model can accurately track the developing storm before precipitation appears. The model used will be a new Met Office model that can be run with a resolution (i.e., grid-spacing) of order 1-4km. This enables storm-cloud motions to be explicitly calculated, rather than treated as a sub-grid-scale effect. Furthermore, current operational forecast models are only updated with observations every few hours; in the new approach the model will be updated much more frequently. This should yield weather forecasts with improved locations (in space-time) for rainfall events.

Initialisation errors are not the only cause of inaccuracies in storm-scale weather forecasts. Models are often run only for a small region of the world, and the data on the boundaries of this area provided from a larger-scale model. These data are known as lateral boundary conditions. Errors in these lateral boundary conditions and modelling errors also contribute to the errors in the forecast. Even if these errors were reduced, the nonlinear nature of the storm dynamics ensures that there is a limit, beyond which the value of deterministic forecasts becomes questionable. After that point it becomes important to determine the uncertainties in the forecast precipitation, so an ensemble approach is required. (An ensemble is a collection of perturbed forecasts that may be considered as a statistical sample of the forecast probability distribution.)

The appropriate construction of a storm-scale ensemble is an open question. We propose a structured approach where perturbations will be designed on the basis of physical insight into convective forcing mechanisms. The resulting probabilistic rainfall forecasts can be interfaced to hydrological models used for flood forecasting. For the first time, this project will allow different scales of application of these methods to be supported: ranging from localised flash flooding of small catchments, through to indicative first-alert forecasting with UK-coverage and forecasting of river discharges to the sea. The project will also assess the impacts of improvements in numerical weather prediction on flood forecast performance.

In this project we anticipate fruitful interactions between the different disciplines of observations and measurement, meteorology and hydrology. Radar assimilation software development and ensemble forecasts will take place using Met Office models, so improvements can be implemented operationally very easily. The use of operational radars makes this project well placed to take advantage of data from any extreme events occurring during the period of the study.

OpenLISEM is an open-source hydrological model suited for the simulation of floods, flash floods and erosion events. The following sections provide an overview of the results from the OpenLISEM model used in the exposure mapping A 30x30m flood map (maximum flood height) for the BuPuSa region was developed for several points on the intensity-frequency-duration curve. This curve represents the extreme value analysis (EVA) for the rainfall across the BuPuSa area. Based on 50 years of historic rainfall data from TAMSAT the EVA is developed for a 1000 year period. From this different rainfall intensities area taken which are referred to at the return period. The statistical possibility of a certain rainfall intensity to happen once in X many years. Flood maps were developed for the following return periods: 1/2, 1/10, 1/50, 1/100 and 1/1000. In addition to 5 different return periods, two different scenarios were modeled. A short high intensity rainfall event that typically causes flash floods, and a longer term lower intensity rainfall event that typically causes fluvial (river) floods. These events were represented by respectively a 6h rainfall event and a 14 day rainfall event. As a result 10 different flood maps were developed.

The National Weather Service issues warnings for severe weather that are imminent or actively occurring. This layer shows shorter-term warnings for the following events:Special Marine Warnings - potentially hazardous weather conditions of short duration (up to 2 hours) that may include sustained winds or gusts of 39 mph or greater, hail 0.75” or greater in diameter, or waterspouts.Severe Thunderstorm Warnings - storms with winds of 58 mph or higher or hail 1” or greater in diameter.Tornado Warnings - imminent or active tornados.Extreme Wind Warnings - surface winds of 115 mph or greater associated with non-convective, downslope, derecho, or sustained hurricane winds are expected to occur within one hour.Flash Flood Warnings - conditions are favorable for flash flooding. It does not mean that flash flooding will occur, but it is possible.SourceCurrent Warnings: https://www.weather.gov/source/crh/shapefiles/CurrentWarnings.tar.gzSample DataSee Sample Layer Item for sample data during Weather inactivity!Update FrequencyThe service is updated every 5 minutes using the Aggregated Live Feeds methodology.Area CoveredContiguous United StatesWhat can you do with this layer?Customize the display of each attribute by using the Change Style option for any layer.Query the layer to display only specific types of weather watches and warnings.Add to a map with other weather data layers to provide inside on hazardous weather events.Use ArcGIS Online analysis tools, such as Enrich Data, to determine the potential impact of weather events on populations.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

Tornado TracksThis feature layer, utilizing data from the National Oceanic and Atmospheric Administration (NOAA), displays tornadoes in the United States, Puerto Rico and U.S. Virgin Islands between 1950 and 2024. A tornado track shows the route of a tornado. Per NOAA, "A tornado is a narrow, violently rotating column of air that extends from a thunderstorm to the ground. Because wind is invisible, it is hard to see a tornado unless it forms a condensation funnel made up of water droplets, dust and debris. Tornadoes can be among the most violent phenomena of all atmospheric storms we experience. The most destructive tornadoes occur from supercells, which are rotating thunderstorms with a well-defined radar circulation called a mesocyclone. (Supercells can also produce damaging hail, severe non-tornadic winds, frequent lightning, and flash floods.)"EF-5 Tornado Track (May 3, 1999) near Oklahoma City, OklahomaData currency: December 30, 2024Data source: Storm Prediction CenterData modifications: Added field "Date_Calc"For more information: Severe Weather 101 - Tornadoes; NSSL Research: TornadoesSupport documentation: SPC Tornado, Hail, and Wind Database Format SpecificationFor feedback, please contact: ArcGIScomNationalMaps@esri.comNational Oceanic and Atmospheric AdministrationPer NOAA, its mission is "To understand and predict changes in climate, weather, ocean, and coasts, to share that knowledge and information with others, and to conserve and manage coastal and marine ecosystems and resources."

This service displays post-fire debris flow data for fires that have occurred in 2018. Post-fire debris-flow likelihood, volume, and combined hazards are estimated at both the drainage-basin scale and in a spatially distributed manner along the drainage network within each basin. For more information about these data please visit the scientific backgound information page. Estimates of the probability and volume of debris flows that may be produced by a storm in a recently burned area, using a model with characteristics related to basin shape, burn severity, soil properties, and rainfall.Wildfire can significantly alter the hydrologic response of a watershed to the extent that even modest rainstorms can produce dangerous flash floods and debris flows. The USGS conducts post-fire debris-flow hazard assessments for select fires in the Western U.S. We use geospatial data related to basin morphometry, burn severity, soil properties, and rainfall characteristics to estimate the probability and volume of debris flows that may occur in response to a design storm.More USGS information and FAQs here.

The geographical location of Afghanistan and years of environmental degradation in the country make Afghanistan highly prone to intense and recurring natural hazards such as flooding, earthquakes, snow avalanches, landslides, and droughts. These occur in addition to man-made disasters resulting in the frequent loss of live, livelihoods, and property. The creation, understanding and accessibility of hazard, exposure, vulnerability and risk information is key for effective management of disaster risk. Assuring the resilience of new reconstruction efforts to natural hazards, and maximizing the effectiveness of risk reduction investments to reduce existing risks is important to secure lives and livelihoods. So far, there has been limited disaster risk information produced in Afghanistan, and information that does exist typically lacks standard methodology and does not have uniform geo-spatial coverage. To better understand natural hazard and disaster risk, the World Bank and Global Facility for Disaster Reduction and Recovery (GFDRR) are supporting the development of new fluvial flood, flash flood, drought, landslide, avalanche and seismic risk information in Afghanistan, as well as a first-order analysis of the costs and benefits of resilient reconstruction and risk reduction strategies. For fluvial flood risk a flood modeling framework is being developed that consists of three components: • Hydrological analysis which models how much precipitation comes to runoff. The hydrological analysis is used as a back-bone to compute flow and flooding through the full catchment area during selected events as well as selected return periods. The hydrological simulations also form the backbone of the drought risk assessments (work package 3). • Hydrodynamic analysis, to translate runoff into river flow and inundation and flow over floodplain areas. • Flood impact analysis for calculating the impacts of a flood applied to flood prone areas with high damage potential.

OpenLISEM is an open-source hydrological model suited for the simulation of floods, flash floods and erosion events. The following sections provide an overview of the results from the OpenLISEM model used in the exposure mapping A 30x30m flood map (maximum flood height) for the BuPuSa region was developed for several points on the intensity-frequency-duration curve. This curve represents the extreme value analysis (EVA) for the rainfall across the BuPuSa area. Based on 50 years of historic rainfall data from TAMSAT the EVA is developed for a 1000 year period. From this different rainfall intensities area taken which are referred to at the return period. The statistical possibility of a certain rainfall intensity to happen once in X many years. Flood maps were developed for the following return periods: 1/2, 1/10, 1/50, 1/100 and 1/1000. In addition to 5 different return periods, two different scenarios were modeled. A short high intensity rainfall event that typically causes flash floods, and a longer term lower intensity rainfall event that typically causes fluvial (river) floods. These events were represented by respectively a 6h rainfall event and a 14 day rainfall event. As a result 10 different flood maps were developed.

This service displays post-fire debris flow data for fires that have occurred in 2018. Post-fire debris-flow likelihood, volume, and combined hazards are estimated at both the drainage-basin scale and in a spatially distributed manner along the drainage network within each basin. For more information about these data please visit the scientific backgound information page. Estimates of the probability and volume of debris flows that may be produced by a storm in a recently burned area, using a model with characteristics related to basin shape, burn severity, soil properties, and rainfall.Wildfire can significantly alter the hydrologic response of a watershed to the extent that even modest rainstorms can produce dangerous flash floods and debris flows. The USGS conducts post-fire debris-flow hazard assessments for select fires in the Western U.S. We use geospatial data related to basin morphometry, burn severity, soil properties, and rainfall characteristics to estimate the probability and volume of debris flows that may occur in response to a design storm.More USGS information and FAQs here.

TornadoesThis feature layer, utilizing data from the National Oceanic and Atmospheric Administration (NOAA), displays tornadoes in the United States, Puerto Rico and U.S. Virgin Islands between 1950 and 2024. Per NOAA, "A tornado is a narrow, violently rotating column of air that extends from a thunderstorm to the ground. Because wind is invisible, it is hard to see a tornado unless it forms a condensation funnel made up of water droplets, dust and debris. Tornadoes can be among the most violent phenomena of all atmospheric storms we experience. The most destructive tornadoes occur from supercells, which are rotating thunderstorms with a well-defined radar circulation called a mesocyclone. (Supercells can also produce damaging hail, severe non-tornadic winds, frequent lightning, and flash floods.)"EF-5 Tornado (May 22, 2011) near Joplin, MissouriData currency: December 30, 2024Data source: Storm Prediction CenterData modifications: Added fields Calculated Month and DateFor more information: Severe Weather 101 - Tornadoes; NSSL Research: TornadoesSupport documentation: SPC Tornado, Hail, and Wind Database Format SpecificationFor feedback, please contact: ArcGIScomNationalMaps@esri.comNational Oceanic and Atmospheric AdministrationPer NOAA, its mission is "To understand and predict changes in climate, weather, ocean, and coasts, to share that knowledge and information with others, and to conserve and manage coastal and marine ecosystems and resources."

This service displays post-fire debris flow data for fires that have occurred in 2018. Post-fire debris-flow likelihood, volume, and combined hazards are estimated at both the drainage-basin scale and in a spatially distributed manner along the drainage network within each basin. For more information about these data please visit the scientific backgound information page. Estimates of the probability and volume of debris flows that may be produced by a storm in a recently burned area, using a model with characteristics related to basin shape, burn severity, soil properties, and rainfall.Wildfire can significantly alter the hydrologic response of a watershed to the extent that even modest rainstorms can produce dangerous flash floods and debris flows. The USGS conducts post-fire debris-flow hazard assessments for select fires in the Western U.S. We use geospatial data related to basin morphometry, burn severity, soil properties, and rainfall characteristics to estimate the probability and volume of debris flows that may occur in response to a design storm.More USGS information and FAQs here.

This service displays post-fire debris flow data for fires that have occurred in 2018. Post-fire debris-flow likelihood, volume, and combined hazards are estimated at both the drainage-basin scale and in a spatially distributed manner along the drainage network within each basin. For more information about these data please visit the scientific backgound information page. Estimates of the probability and volume of debris flows that may be produced by a storm in a recently burned area, using a model with characteristics related to basin shape, burn severity, soil properties, and rainfall.Wildfire can significantly alter the hydrologic response of a watershed to the extent that even modest rainstorms can produce dangerous flash floods and debris flows. The USGS conducts post-fire debris-flow hazard assessments for select fires in the Western U.S. We use geospatial data related to basin morphometry, burn severity, soil properties, and rainfall characteristics to estimate the probability and volume of debris flows that may occur in response to a design storm.More USGS information and FAQs here.

This service displays post-fire debris flow data for fires that have occurred in 2018. Post-fire debris-flow likelihood, volume, and combined hazards are estimated at both the drainage-basin scale and in a spatially distributed manner along the drainage network within each basin. For more information about these data please visit the scientific backgound information page. Estimates of the probability and volume of debris flows that may be produced by a storm in a recently burned area, using a model with characteristics related to basin shape, burn severity, soil properties, and rainfall.Wildfire can significantly alter the hydrologic response of a watershed to the extent that even modest rainstorms can produce dangerous flash floods and debris flows. The USGS conducts post-fire debris-flow hazard assessments for select fires in the Western U.S. We use geospatial data related to basin morphometry, burn severity, soil properties, and rainfall characteristics to estimate the probability and volume of debris flows that may occur in response to a design storm.More USGS information and FAQs here.

Road Weather Alerts are issued for metropolitan areas (excluding Darwin), or state-wide in Tasmania, when weather elements or phenomena are expected to contribute to hazardous driving conditions. Ale…Show full descriptionRoad Weather Alerts are issued for metropolitan areas (excluding Darwin), or state-wide in Tasmania, when weather elements or phenomena are expected to contribute to hazardous driving conditions. Alerts are issued only when conditions are likely to be worse than normal for the season and location. For example, alerts for ice on roads are not normally issued for alpine districts in winter unless expected to be unusually severe or widespread. Criteria for issuing Road Weather Alerts are if the following conditions exist and NO severe weather warning, severe thunderstorm warning or flood warning is in force: a) Reduced visibility below 200 metres due to the presence of thick fog, dust, smoke, heavy or very heavy precipitation. Metropolitan areas only, excludes Tasmania. b) Significant snowfall. Below 500 metres in Tasmania. c) Snow or snow showers of moderate or heavy intensity from 12 hours before the warning start time, or during the warning validity period. d) Flooding. e) Predicted localised flash flooding due to heavy rainfalls or inundation from anomalously high tides. f) Slippery roads due to rainfall after a prolonged dry spell of more than 4mm of accumulated precipitation, from 6 hours before the warning start time or during the warning validity period following a dry spell. A dry spell is defined as less than a total of 4mm of precipitation accumulated from daily totals over 5 days, using only daily totals of more than 2mm or ice build-up on roads due to frost or freezing rain, in particular the occurrence of ‘black ice’ or where it is suspected that water draining across roads may freeze. g) Ice on roads. Defined by the presence of: (accumulated precipitation of greater than 2mm or PoP of greater than 25%) and temperature of less than +2 degrees) within 12 hours of the warning start time or during the warning validity period. h) Hail (moderate to heavy precipitation with hail). i) Average wind speeds of at least 65 km/h, or gusts of at least 90 km/h. They are generally issued 12 to 18 hours prior to the onset of the hazardous conditions, updated 6 hourly thereafter until cancelled. Road weather alerts, which are issued by each Australian State/Territory have been combined into a national product for Web Map Service and Web Feature Service layers.

The National Weather Service issues warnings for severe weather that are imminent or actively occurring. This layer shows shorter-term warnings for the following events:Special Marine Warnings - potentially hazardous weather conditions of short duration (up to 2 hours) that may include sustained winds or gusts of 39 mph or greater, hail 0.75” or greater in diameter, or waterspouts.Severe Thunderstorm Warnings - storms with winds of 58 mph or higher or hail 1” or greater in diameter.Tornado Warnings - imminent or active tornados.Extreme Wind Warnings - surface winds of 115 mph or greater associated with non-convective, downslope, derecho, or sustained hurricane winds are expected to occur within one hour.Flash Flood Warnings - conditions are favorable for flash flooding. It does not mean that flash flooding will occur, but it is possible.SourceCurrent Warnings: https://www.weather.gov/source/crh/shapefiles/CurrentWarnings.tar.gzSample DataSee Sample Layer Item for sample data during Weather inactivity!Update FrequencyThe service is updated every 5 minutes using the Aggregated Live Feeds methodology.Area CoveredContiguous United StatesWhat can you do with this layer?Customize the display of each attribute by using the Change Style option for any layer.Query the layer to display only specific types of weather watches and warnings.Add to a map with other weather data layers to provide inside on hazardous weather events.Use ArcGIS Online analysis tools, such as Enrich Data, to determine the potential impact of weather events on populations.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

TornadoesThis feature layer, utilizing data from the National Oceanic and Atmospheric Administration (NOAA), displays tornadoes in the United States, Puerto Rico and U.S. Virgin Islands between 1950 and 2024. Per NOAA, "A tornado is a narrow, violently rotating column of air that extends from a thunderstorm to the ground. Because wind is invisible, it is hard to see a tornado unless it forms a condensation funnel made up of water droplets, dust and debris. Tornadoes can be among the most violent phenomena of all atmospheric storms we experience. The most destructive tornadoes occur from supercells, which are rotating thunderstorms with a well-defined radar circulation called a mesocyclone. (Supercells can also produce damaging hail, severe non-tornadic winds, frequent lightning, and flash floods.)"EF-5 Tornado (May 22, 2011) near Joplin, MissouriData currency: December 30, 2024Data source: Storm Prediction CenterData modifications: Added field "Date_Calc"For more information: Severe Weather 101 - Tornadoes; NSSL Research: TornadoesSupport documentation: SPC Tornado, Hail, and Wind Database Format SpecificationFor feedback, please contact: ArcGIScomNationalMaps@esri.comNational Oceanic and Atmospheric AdministrationPer NOAA, its mission is "To understand and predict changes in climate, weather, ocean, and coasts, to share that knowledge and information with others, and to conserve and manage coastal and marine ecosystems and resources."

This service displays post-fire debris flow data for fires that have occurred in 2018. Post-fire debris-flow likelihood, volume, and combined hazards are estimated at both the drainage-basin scale and in a spatially distributed manner along the drainage network within each basin. For more information about these data please visit the scientific backgound information page. Estimates of the probability and volume of debris flows that may be produced by a storm in a recently burned area, using a model with characteristics related to basin shape, burn severity, soil properties, and rainfall.Wildfire can significantly alter the hydrologic response of a watershed to the extent that even modest rainstorms can produce dangerous flash floods and debris flows. The USGS conducts post-fire debris-flow hazard assessments for select fires in the Western U.S. We use geospatial data related to basin morphometry, burn severity, soil properties, and rainfall characteristics to estimate the probability and volume of debris flows that may occur in response to a design storm.More USGS information and FAQs here.