Annual number of 10mm rainfall days (days where there is greater than or equal to 10mm rainfall) averaged over 1991-2020, provided on a 2km BNG grid.This data contains a field for the average over the period, named 'Rainfall 10mm Days'.Data source:HadUK-Grid v1.1.0.0 (downloaded 11/03/2022)More about HadUK-Grid - https://www.metoffice.gov.uk/research/climate/maps-and-data/data/haduk-grid/haduk-grid This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

What does the data show?  The data shows the annual average of precipitation amount (mm) for the 1991-2020 period from HadUK gridded data. It is provided on a 12km British National Grid (BNG).    Limitations of the data  We recommend the use of multiple grid cells or an average of grid cells around a point of interest to help users get a sense of the variability in the area. This will provide a more robust set of values for informing decisions based on the data.    What are the naming conventions and how do I explore the data?    This data contains a field for the average over the 1991-2020 period. It is named 'pr' (precipitation).    To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578    Data source:   ·       Version: HadUK-Grid v1.1.0.0 (downloaded 21/06/2022)  ·       Source: https://catalogue.ceda.ac.uk/uuid/652cea3b8b4446f7bff73be0ce99ba0f  ·       Filename: rainfall_hadukgrid_uk_12km_ann-30y_199101-202012.nc      Useful links  ·       Further information on HadUK-Grid  ·       Further information on understanding climate data within the Met Office Climate Data Portal   

Annual averages of precipitation (mm) for 1991-2020 from HadUK 12km gridded data.This data contains a field for the average over the period. It is named 'pr' (precipitation).HadUK-Grid: https://www.metoffice.gov.uk/research/climate/maps-and-data/data/haduk-grid/haduk-grid Recommendations for use of this data:We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.Data source: https://catalogue.ceda.ac.uk/uuid/652cea3b8b4446f7bff73be0ce99ba0frainfall_hadukgrid_uk_12km_ann-30y_199101-202012.ncHadUK-Grid_v1.1.0.0 (downloaded 21/06/2022)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Annual averages of precipitation (mm/day) for 2050-2079 from UKCP18 regional projections (12km grid), using the RCP8.5 pathway.This data contains a field for the average over the period. It is named 'pr' (precipitation) and 'upper' 'median' or 'lower' as per the description below. E.g. 'pr Lower'UKCP: https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data is from the UKCP18 regional projections using the RCP8.5 scenario. RCP8.5 is the highest of the plausible future emissions scenarios used by the IPCC, sometimes referred to as 'business as usual'.What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean UK precipitation for the period 2050-2079 was taken from each ensemble member. They were then ranked in order from lowest precipitation to highest. The 'lower' field in this data is the second lowest ranked ensemble member. The 'higher' field is the second highest ranked ensemble member. The 'median' field is the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source:pr_rcp85_land-rcm_uk_12km_12_ann-30y_200912-207911.nc (median)pr_rcp85_land-rcm_uk_12km_05_ann-30y_200912-207911.nc (lower)pr_rcp85_land-rcm_uk_12km_04_ann-30y_200912-207911.nc (upper)UKCP18 v20190731 (downloaded 04/11/2021)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Climate data--including 30-Year-normal data--provided by PRISM Climate Group at Oregon State University. Data is in raster formats.

Developed through collaboration between The Nature Conservancy, The University of Washington, and The University of Southern Mississippi, the Climate Wizard enables technical and non-technical audiences alike to easily and intuitively access leading climate change information and visualize the impacts anywhere on Earth. Climate Wizard Custom is a new tool where a user can define a relatively small geographic area of interest and conduct site-specific analyses using both historical data and possible future conditions that are based on low (B1), moderate (A1B), and high (A2) carbon emissions scenarios. Sixteen general circulation models are available to provide a range of possible outcomes, and users can analyze absolute and percentage changes in annual, seasonal or monthly climate conditions in graphic or map form. Since the large climate datasets are stored and analyzed remotely on powerful computers, users of the tool do not need to have fast computers or expensive software, but simply need access to the internet. Using web technologies to develop tools that make climate change analysis more accessible scientists, managers, and policy makers now have the ability to assess the potential impacts of climate change and help guide decisions and actions to prepare for and mitigate those impacts to natural systems and the services they provide.

The Environment Agency has approximately 1000 real time rain gauges which are connected by telemetry. Measurements of the amount of precipitation (mm) are captured in Tipping Bucket Raingauges (TBR). The data reported here gives accumulated totals for each 15 min period. The data is typically transferred once or twice per day. The Rainfall API provides access to these rainfall measurements, and to information on the monitoring stations providing those measurements. It is compatible with (and integrated into) the API for water level/flow readings. Note that for information protection reasons the rainfall monitoring stations do not have names and their geographic location has been reduced to a 100m grid..

What does the data show? The Drought Severity Index is not threshold based. Instead, it is calculated with 12-month rainfall deficits provided as a percentage of the mean annual climatological total rainfall (1981–2000) for that location. It measures the severity of a drought, not the frequency. 12-month accumulations have been selected as this is likely to indicate hydrological drought. Hydrological drought occurs due to water scarcity over a much longer duration (longer than 12 months). It heavily depletes water resources on a large scale as opposed to meteorological or agricultural drought, which generally occur on shorter timescales of 3-12 months. However this categorisation is not fixed, because rainfall deficits accumulated over 12-months could lead to different types of drought and drought impacts, depending on the level of vulnerability to reduced rainfall in a region. The DSI 12 month accumulations are calculated for two baseline (historical) periods 1981-2000 (corresponding to 0.51°C warming) and 2001-2020 (corresponding to 0.87°C warming) and for global warming levels of 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C above the pre-industrial (1850-1900) period. What are the possible societal impacts? The DSI 12-month accumulations measure the drought severity. Higher values indicate more severe drought. The DSI is based on 12-month rainfall deficits. The impacts of the differing length of rainfall deficits vary regionally due to variation in vulnerability. Depending on the level of vulnerability to reduced rainfall, rainfall deficits accumulated over 12 months could lead to meteorological, agricultural and hydrological drought. What is a global warming level? The DSI 12-month accumulations are calculated from the UKCP18 regional climate projections using the high emissions scenario (RCP 8.5) where greenhouse gas emissions continue to grow. Instead of considering future climate change during specific time periods (e.g. decades) for this scenario, the dataset is calculated at various levels of global warming relative to the pre-industrial (1850-1900) period. The world has already warmed by around 1.1°C (between 1850–1900 and 2011–2020), whilst this dataset allows for the exploration of greater levels of warming. The global warming levels available in this dataset are 1.5°C, 2°C, 2.5°C, 3°C and 4°C. The data at each warming level was calculated using a 21 year period. These 21 year periods are calculated by taking 10 years either side of the first year at which the global warming level is reached. This time will be different for different model ensemble members. To calculate the value for the DSI 12-month accumulations, an average is taken across the 21 year period. We cannot provide a precise likelihood for particular emission scenarios being followed in the real world future. However, we do note that RCP8.5 corresponds to emissions considerably above those expected with current international policy agreements. The results are also expressed for several global warming levels because we do not yet know which level will be reached in the real climate as it will depend on future greenhouse emission choices and the sensitivity of the climate system, which is uncertain. Estimates based on the assumption of current international agreements on greenhouse gas emissions suggest a median warming level in the region of 2.4-2.8°C, but it could either be higher or lower than this level. What are the naming conventions and how do I explore the data? This data contains a field for each global warming level and two baselines. They are named ‘DSI12’ (Drought Severity Index for 12 month accumulations), the warming level or baseline, and 'upper' 'median' or 'lower' as per the description below. E.g. 'DSI12 2.5 median' is the median value for the 2.5°C projection. Decimal points are included in field aliases but not field names e.g. 'DSI12 2.5 median' is 'DSI12_25_median'.  To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578 Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘DSI12 2.0°C median’ values. What do the ‘median’, ‘upper’, and ‘lower’ values mean? Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future. For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, DSI 12 month accumulations were calculated for each ensemble member and they were then ranked in order from lowest to highest for each location. The ‘lower’ fields are the second lowest ranked ensemble member. The ‘upper’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble. This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and upper fields, the greater the uncertainty. ‘Lower’, ‘median’ and ‘upper’ are also given for the baseline periods as these values also come from the model that was used to produce the projections. This allows a fair comparison between the model projections and recent past. Useful links This dataset was calculated following the methodology in the ‘Future Changes to high impact weather in the UK’ report. Further information on the UK Climate Projections (UKCP). Further information on understanding climate data within the Met Office Climate Data Portal

This e-book is a quick primer on earth observation of water resources and has been developed jointly by the World Bank and NASA. It provides a basic introduction to hydrologic processes and the types of in-situ and earth observation monitoring approaches to gain a global perspective to help address problems in the real world such as floods, droughts, cyclones, and forecasting for agriculture and water-related disease management applications. It provides a primer for accessing useful NASA data, modeling tools, related interactive viewers and useful links in this regard, that showcase interactive maps to visualize precipitation and even groundwater data and trends and near-real time flood potential from space. This e-book provides an illustrative overview of the use of increasingly powerful free data from satellites that can be critical for monitoring and managing watersheds and aquifers around the world.

HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales) provides hydrographic information in a consistent and comprehensive format for regional and global-scale applications. HydroSHEDS offers a suite of geo-referenced data sets in raster and vector format, including stream networks, watershed boundaries, drainage directions, and ancillary data layers such as flow accumulations, distances, and river topology information. Recently available data derived from HydroSHEDS include comprehensive layers of major basins and smaller sub-basins (~100-2,500 km2) across the globe. These data layers are available to support watershed analyses, hydrological modeling, and freshwater conservation planning at a quality, resolution, and extent that had previously been unachievable in many parts of the world. Data includes Void-Filled elevation, Hydrologically conditioned elevation, drainage directions, flow accumulation, river network, basin outlines, HydroBASINS License information: https://www.hydrosheds.org/page/license

Comprehensive list of data from the Mekong River Commission. The data dashboard includes time series and map data. Time series parameters include: Water level, rainfall, Nitrate, water temperature, Ammonium, phosphorous, sulphate, total suspended, ph, disolved oxygen, evaporation rates, conductivity, nitrogen, air temperature, relative humidity, sediment concentration, for a range of durations depending on location/station selected. Data can be saved and downloaded via creation of a free user account

Monthly averages of global rainfall amount (mm) for 1981-2010 from CRU TS data, provided on an approximately 60km grid.This data contains a field for each month’s average over the period. They are named 'pr' (precipitation) and the month. E.g. 'pr March' is the mean of monthly-total rainfall in March throughout 1981-2010.Data defaults to displaying January averages. Each monthly average is a field in the data. Use 'show table' to view all values, and 'change style' to change which month is displayed in the map.The grid is a lat-long grid, with cells close to the equator measuring approximately 60kmx60km. This is the same as the 60km grid used by UKCP18.Data source: CRU TS v. 4.06 - (downloaded 12/07/22)More about CRU TS - https://crudata.uea.ac.uk/cru/data/hrg/This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Monthly averages of global rainfall amount (mm) for 2040-2069 from CRU TS and UKCP18 RCP2.6, provided on an approximately 60km grid.This data contains a field for each month’s average over the period. They are named 'pr' (precipitation), the month, and 'upper' 'median' or 'lower' as per the description below. E.g. 'pr March Median' is the mean of monthly-total rainfall in March throughout 2040-2069, in the median ensemble member.Data defaults to displaying January averages. Each monthly average is a field in the data. Use 'show table' to view all values, and 'change style' to change which month is displayed in the map.Data has been removed and replaced with 'Null' where the baseline 1981-2010 value was <1mm/month. This is because the percentage change may be unreliable with a very small baseline. 'Null' means that data is not provided, it doesn't mean 0mm precipitation. The grid is a lat-long grid, with cells close to the equator measuring approximately 60kmx60km.More about CRU TS - https://crudata.uea.ac.uk/cru/data/hrg/More about UKCP - https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data combines a baseline 1981-2010 value from CRU TS with a percentage change relative to 1981-2010 from UKCP18. Where the baseline value was <1mm/month, the projection value has been replaced with 'Null' because the percentage change may be unreliable with a very small baseline.The percentage change data is from the UKCP18 regional projections using the RCP2.6 scenario. RCP2.6 is a low emissions scenario, representing a mitigation scenario aiming to limit the increase of global mean temperature to around 2°C above preindustrial levels .What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean global precipitation for the period 2040-2069 was taken from each ensemble member. They were then ranked in order from lowest precipitation to highest. The 'lower' fields are this data is the second lowest ranked ensemble member. The 'higher' fields are the second highest ranked ensemble member. The 'median' fields are the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source: CRU TS v. 4.06 - (downloaded 12/07/22)UKCP18 v.20200110 (downloaded 17/08/22)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Monthly averages of global rainfall amount (mm) for 2070-2099 from CRU TS and UKCP18 RCP2.6, provided on an approximately 60km grid.This data contains a field for each month’s average over the period. They are named 'pr' (precipitation), the month, and 'upper' 'median' or 'lower' as per the description below. E.g. 'pr March Median' is the mean of monthly-total rainfall in March throughout 2070-2099, in the median ensemble member.Data defaults to displaying January averages. Each monthly average is a field in the data. Use 'show table' to view all values, and 'change style' to change which month is displayed in the map.Data has been removed and replaced with 'Null' where the baseline 1981-2010 value was <1mm/month. This is because the percentage change may be unreliable with a very small baseline. 'Null' means that data is not provided, it doesn't mean 0mm precipitation. The grid is a lat-long grid, with cells close to the equator measuring approximately 60kmx60km.More about CRU TS - https://crudata.uea.ac.uk/cru/data/hrg/More about UKCP - https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data combines a baseline 1981-2010 value from CRU TS with a percentage change relative to 1981-2010 from UKCP18. Where the baseline value was <1mm/month, the projection value has been replaced with 'Null' because the percentage change may be unreliable with a very small baseline.The percentage change data is from the UKCP18 regional projections using the RCP2.6 scenario. RCP2.6 is a low emissions scenario, representing a mitigation scenario aiming to limit the increase of global mean temperature to around 2°C above preindustrial levels .What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean global precipitation for the period 2070-2099 was taken from each ensemble member. They were then ranked in order from lowest precipitation to highest. The 'lower' fields are this data is the second lowest ranked ensemble member. The 'higher' fields are the second highest ranked ensemble member. The 'median' fields are the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source: CRU TS v. 4.06 - (downloaded 12/07/22)UKCP18 v.20200110 (downloaded 17/08/22)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Monthly averages of rainfall amount (mm) for 1991-2020 from HadUK gridded data, provided on a 2km BNG grid.This data contains a field for each month’s average over the period. They are named 'pr' (precipitation) and the month. E.g. 'pr March'.Data defaults to displaying January averages. Each monthly average is a field in the data. Use 'show table' to view all values, and 'change style' to change which month is displayed in the map.Data source:HadUK-Grid v1.1.0.0 (downloaded 11/03/2022)More about HadUK-Grid - https://www.metoffice.gov.uk/research/climate/maps-and-data/data/haduk-grid/haduk-gridThis dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

What does the data show?  The data shows monthly averages of precipitation amount (mm) for 1991-2020 from HadUK gridded data. It is provided on a 12km British National Grid (BNG).    Limitations of the dataWe recommend the use of multiple grid cells or an average of grid cells around a point of interest to help users get a sense of the variability in the area. This will provide a more robust set of values for informing decisions based on the data.What are the naming conventions and how do I explore the data?  This data contains a field for each month’s average over the period. They are named 'pr' (precipitation) and the month. E.g. 'pr March' is the rainfall amount for March in the period 1991-2020.    To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578  Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘pr January’ values.  Data source:   ·       Version: HadUK-Grid v1.1.0.0 (downloaded 26/08/2022)  ·       Source: https://catalogue.ceda.ac.uk/uuid/652cea3b8b4446f7bff73be0ce99ba0f  ·       Filename: rainfall_hadukgrid_uk_12km_mon-30y_199101-202012.nc      Useful links  ·       Further information on HadUK-Grid  ·       Further information on understanding climate data within the Met Office Climate Data Portal

Monthly averages of precipitation (mm) for 1991-2020 from HadUK 12km gridded data.This data contains a field for each month’s average over the period. They are named 'pr' (precipitation) and the month. E.g. 'pr July'.Data defaults to displaying January averages. Each monthly average is a field in the data. Use 'show table' to view all values, and 'change style' to change which month is displayed in the map.HadUK-Grid: https://www.metoffice.gov.uk/research/climate/maps-and-data/data/haduk-grid/haduk-grid Recommendations for use of this data:We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.Data source: https://catalogue.ceda.ac.uk/uuid/652cea3b8b4446f7bff73be0ce99ba0frainfall_hadukgrid_uk_12km_mon-30y_199101-202012.ncHadUK-Grid_v1.1.0.0 (downloaded 21/06/2022)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

Monthly averages of precipitation (mm/day) for 2050-2079 from UKCP18 regional projections (12km grid), using the RCP8.5 pathway.This data contains a field for each month’s average over the period. They are named 'pr' (precipitation), the month, and 'upper' 'median' or 'lower' as per the description below. E.g. 'pr July Median'.UKCP: https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/indexWhat is the data?The data is from the UKCP18 regional projections using the RCP8.5 scenario. RCP8.5 is the highest of the plausible future emissions scenarios used by the IPCC, sometimes referred to as 'business as usual'.What do the 'median', 'upper', and 'lower' values mean?This scenario is run as 12 separate ensemble members. To select which ensemble members to use, a single value for the mean UK precipitation for the period 2050-2079 was taken from each ensemble member. They were then ranked in order from lowest precipitation to highest. The 'lower' fields are this data is the second lowest ranked ensemble member. The 'higher' fields are the second highest ranked ensemble member. The 'median' fields are the central (7th) ranked ensemble member.This gives a median value, and a spread of the ensemble members indicating the level of uncertainty in the projections.Recommendations for use of this data:1. We don't recommend using this data at the resolution of a single cell.The higher resolution of this data improves representation of topography, coasts, etc. but at the same time increases some of the uncertainty for individual grid cells. And so it is recommended to work with multiple grid cells, or an average of grid cells around a point to improve certainty.2. Consider whether the lower, median, or upper projections, or a combination, are most suitable for your use case.As described above, the spread of the ensemble members shown by the lower, median, and upper values indicates the level of uncertainty in the projections.Data source:pr_rcp85_land-rcm_uk_12km_12_mon-30y_200912-207911.nc (median)pr_rcp85_land-rcm_uk_12km_05_mon-30y_200912-207911.nc (lower)pr_rcp85_land-rcm_uk_12km_04_mon-30y_200912-207911.nc (upper)UKCP18 v20190731 (downloaded 04/11/2021)This dataset forms part of the Met Office’s Climate Data Portal service. This service is currently in Beta. We would like your help to further develop our service, please send us feedback via the site - https://climate-themetoffice.hub.arcgis.com/

This ongoing dataset contains monthly precipitation measurements from a network of standard can rain gauges at the Jornada Experimental Range in Dona Ana County, New Mexico, USA. Precipitation physically collects within gauges during the month and is manually measured with a graduated cylinder at the end of each month. This network is maintained by USDA Agricultural Research Service personnel. This dataset includes 39 different locations but only 29 of them are current. Other precipitation data exist for this area, including event-based tipping bucket data with timestamps, but do not go as far back in time as this dataset.

This dataset is part of the common observation in the centralized repository for public access, also known as the Common Observatory Repository (CORe), of the USDA ARS Long-Term Agro-ecosystem Research (LTAR) network. This is part of the National Program 216 (NP#216): Agricultural System and Competitiveness and Sustainability. Also The National Wind Erosion Research Network was established in 2014 as a collaborative effort led by the US Department of Agriculture (USDA) Long Term Agro-Ecosystem Research (LTAR) network and the Bureau of Land Management (BLM). The research domain incorporates the diverse soils and vegetation communities in the rangelands and croplands of the western United States, with sites located in New Mexico, Texas, Oklahoma, Arizona, California, Colorado, North Dakota, Utah, Idaho and Washington. We have a tower that collects data for the North Dakota Agricultural Weather Network. Our site is part of the NEON project with a tower that is designed to collect and provide open data that characterize and quantify complex, rapidly changing ecological processes across the US. We have a National Center for Environmental Information (NOAA) tower that collects daily summaries of weather data. A Natural Resource Conservation (NRCS) National Water and Climate tower that collects snow and water data.

A monthly climatology of precipitation and air temperature, both at the surface, and a time series, spanning 1900 to 2010, of monthly mean surface air temperatures, and monthly total precipitation. It is land-only in coverage, and complements the ICOADS (International Comprehensive Ocean-Atmosphere Data Set) data set well. Latest release of data covers period Jan 1900 to Dec 2017.

A range of data for the Orange-Senqu basin, including narrative and numerical data covering rainfall, evaporation, radiation, soil type, groundwater recharge, yield, groundwater quality, dam infrastructure, surface water flows, surface water quality, flood, irrigation, urban water supply. The database can be searched by category or keywork, and will produce particular studies, with coverage of particular regions or the whole basin. Where data is available, it will be linked within the study pages, and provided either in pdf, xls, or GIS-compatable formats.

This dataset measures the amount of rainfall (mm) in five minute intervals at nine rain gauge stations in the Greater Dublin Area. This dataset measures the amount of rainfall (mm) that falls weekly in five minute intervals at nine rain gauge stations in the Greater Dublin Area. 'The dataset contains information fields on location of Outstation (OS_NAME), Point name of raingauge (PT_NAME), interval between readings (Timebase, Derivation), Timedate (Timestamp), Reading in mimilmetres (Value) and an additional field for manual input of reading in case of rain gauge error (Manual).'The outstation code names (also available in text file) are as follows:'BME_TW, Ballymore Eustace'RWD_TW, Roundwood'B_BREENA, Boharnebreena'BMUN_DR, Ballymun Road'CHAPELIZ, Cjhapelizod'GRNGE_PS, Grange Road'RING_MLS, Ringsend Main Lift Station'UCD_SMD, University College Dublin'MOBILE_R, currently located at Civic Offices

A data delivery application that provides web-based access to of soil, water, climate, land management, and geospatial data produced by Conservation Effects Assessment Project (CEAP) watershed research sites across the United States. Data access via ArcGIS Server and MS SQL Server Enhanced data searches and summary options in Tools Access to high-resolution imagery in the Map>Table of Contents Enhanced graphing options on the Get Data page Transparency sliders for individual map components in the Map>Table of Contents

[update 28/03/24 - This description previously stated that the the field “2001-2020 (recent past) change” was a percentage change. This field is actually the difference, in units of mm/day. The table below has been updated to reflect this.]What does the data show? This dataset shows the change in summer precipitation rate for a range of global warming levels, including the recent past (2001-2020), compared to the 1981-2000 baseline period. Here, summer is defined as June-July-August. Note, as the values in this dataset are averaged over a season they do not represent possible extreme conditions. The dataset uses projections of daily precipitation from UKCP18 which are averaged over the summer period to give values for the 1981-2000 baseline, the recent past (2001-2020) and global warming levels. The warming levels available are 1.5°C, 2.0°C, 2.5°C, 3.0°C and 4.0°C above the pre-industrial (1850-1900) period. The recent past value and global warming level values are stated as a percentage change (%) relative to the 1981-2000 value. This enables users to compare summer precipitation trends for the different periods. In addition to the change values, values for the 1981-2000 baseline (corresponding to 0.51°C warming) and recent past (2001-2020, corresponding to 0.87°C warming) are also provided. This is summarised in the table below. Period Description 1981-2000 baseline Average value for the period (mm/day) 2001-2020 (recent past) Average value for the period (mm/day) 2001-2020 (recent past) change Change (mm/day) relative to 1981-2000 1.5°C global warming level change Percentage change (%) relative to 1981-2000 2°C global warming level change Percentage change (%) relative to 1981-2000 2.5°C global warming level change Percentage change (%) relative to 1981-2000 3°C global warming level change Percentage change (%) relative to 1981-2000 4°C global warming level change Percentage change (%) relative to 1981-2000 What is a global warming level? The Summer Precipitation Change is calculated from the UKCP18 regional climate projections using the high emissions scenario (RCP 8.5) where greenhouse gas emissions continue to grow. Instead of considering future climate change during specific time periods (e.g. decades) for this scenario, the dataset is calculated at various levels of global warming relative to the pre-industrial (1850-1900) period. The world has already warmed by around 1.1°C (between 1850–1900 and 2011–2020), whilst this dataset allows for the exploration of greater levels of warming. The global warming levels available in this dataset are 1.5°C, 2°C, 2.5°C, 3°C and 4°C. The data at each warming level was calculated using a 21 year period. These 21 year periods are calculated by taking 10 years either side of the first year at which the global warming level is reached. This time will be different for different model ensemble members. To calculate the value for the Summer Precipitation Change, an average is taken across the 21 year period. We cannot provide a precise likelihood for particular emission scenarios being followed in the real world future. However, we do note that RCP8.5 corresponds to emissions considerably above those expected with current international policy agreements. The results are also expressed for several global warming levels because we do not yet know which level will be reached in the real climate as it will depend on future greenhouse emission choices and the sensitivity of the climate system, which is uncertain. Estimates based on the assumption of current international agreements on greenhouse gas emissions suggest a median warming level in the region of 2.4-2.8°C, but it could either be higher or lower than this level. What are the naming conventions and how do I explore the data? These data contain a field for each warming level and the 1981-2000 baseline. They are named 'pr summer change', the warming level or baseline, and 'upper' 'median' or 'lower' as per the description below. e.g. 'pr summer change 2.0 median' is the median value for summer for the 2.0°C warming level. Decimal points are included in field aliases but not in field names, e.g. 'pr summer change 2.0 median' is named 'pr_summer_change_20_median'. To understand how to explore the data, refer to the New Users ESRI Storymap. Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘pr summer change 2.0°C median’ values. What do the 'median', 'upper', and 'lower' values mean? Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future. For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, the Summer Precipitation Change was calculated for each ensemble member and they were then ranked in order from lowest to highest for each location. The ‘lower’ fields are the second lowest ranked ensemble member. The ‘higher’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble. This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and higher fields, the greater the uncertainty. ‘Lower’, ‘median’ and ‘upper’ are also given for the baseline period as these values also come from the model that was used to produce the projections. This allows a fair comparison between the model projections and recent past. Useful links For further information on the UK Climate Projections (UKCP). Further information on understanding climate data within the Met Office Climate Data Portal.

Find Yorkshire Water data such as daily rainfall, regional reservoir stocks, river levels and demand is monitored and you can see their current position against historical and seasonal trends and fluctuations. The majority of the figures are produced either as a % of total capacity (in the case of reservoir stocks) or as Ml/d which is megalitres per day. 1 megalitre is equivalent to 1 million litres.

Range of environment and water indicators for Western Asia Countries. Data presented online and can be exported as PDF or XLS. The data runs 5 yearly from 1975 and annually from 1990 to 2015, although not every year is provided for each indicator or country. The following water-related indicators are provided, although not every indicator is available for each country. Average precipitation (cubic meters and mm per year), Surface water abstraction (cubic meters per year), domestic water use (cubic meters per year), Access to improved drinking water (percentage) Wastewater produced (cubic meters per day), Desalination production (cubic meters per year), Total freshwater abstraction (cubic meters per year), Groundwater Abstraction (Cubic Meters Per year), total freshwater use (Cubic meters), Total non-conventional use (cubic metesr per yera), Per capita water resources from conventional and non-conventional resources (Cubic meters per year), Per capita total water resource change (% for previous two years), agricultural water use (Cubic meters per year), Access to improved drinking water sources (urban) (Percentage), Wastewater treated in urban wastewater treatment plants(cubic meters per day), Access to improved drinking water sources (rural) (Percentage) Access to improved sanitation (rural) (Percentage), Population using improved drinking water sources (rural) (urban) (Percentage), Population using improved sanitation facilities (rural) (urban) (Percentage)

Daily point rainfall values. This data is collected with rainfall telemetry devices installed at the catchment storage dams, and verified with field observations daily.  This data provides daily rainfall observed for the 24hr period from 8am to 8am. This data provides our customers and community with the daily observed rainfall information. This data is best used in long term rainfall analysis at the four major melbourne storage dams (Maroondah; O'Shannassy; Thomson; and Upper Yarra). This dataset is not suitable for event modelling which requires higher frequency observations.NOTE: Whilst every effort has been taken in collecting, validating and providing the attached data, Melbourne Water Corporation makes no representations or guarantees as to the accuracy or completeness of this data. Any person or group that uses this data does so at its own risk and should make their own assessment and investigations as to the suitability and/or application of the data. Melbourne Water Corporation shall not be liable in any way to any person or group for loss of any kind including damages, costs, interest, loss of profits or special loss or damage, arising from any use, error, inaccuracy, incompleteness or other defect in this data.

[update 28/03/24 - This description previously stated that the the field “2001-2020 (recent past) change” was a percentage change. This field is actually the difference, in units of mm/day. The table below has been updated to reflect this.]What does the data show? This dataset shows the change in winter precipitation rate for a range of global warming levels, including the recent past (2001-2020), compared to the 1981-2000 baseline period. Here, winter is defined as December-January-February. Note, as the values in this dataset are averaged over a season they do not represent possible extreme conditions. The dataset uses projections of daily precipitation from UKCP18 which are averaged over the winter period to give values for the 1981-2000 baseline, the recent past (2001-2020) and global warming levels. The warming levels available are 1.5°C, 2.0°C, 2.5°C, 3.0°C and 4.0°C above the pre-industrial (1850-1900) period. The recent past value and global warming level values are stated as a percentage change (%) relative to the 1981-2000 value. This enables users to compare winter precipitation trends for the different periods. In addition to the change values, values for the 1981-2000 baseline (corresponding to 0.51°C warming) and recent past (2001-2020, corresponding to 0.87°C warming) are also provided. This is summarised in the table below. Period Description 1981-2000 baseline Average value for the period (mm/day) 2001-2020 (recent past) Average value for the period (mm/day) 2001-2020 (recent past) change Change (mm/day) relative to 1981-2000 1.5°C global warming level change Percentage change (%) relative to 1981-2000 2°C global warming level change Percentage change (%) relative to 1981-2000 2.5°C global warming level change Percentage change (%) relative to 1981-2000 3°C global warming level change Percentage change (%) relative to 1981-2000 4°C global warming level change Percentage change (%) relative to 1981-2000 What is a global warming level? The Winter Precipitation Change is calculated from the UKCP18 regional climate projections using the high emissions scenario (RCP 8.5) where greenhouse gas emissions continue to grow. Instead of considering future climate change during specific time periods (e.g. decades) for this scenario, the dataset is calculated at various levels of global warming relative to the pre-industrial (1850-1900) period. The world has already warmed by around 1.1°C (between 1850–1900 and 2011–2020), whilst this dataset allows for the exploration of greater levels of warming. The global warming levels available in this dataset are 1.5°C, 2°C, 2.5°C, 3°C and 4°C. The data at each warming level was calculated using a 21 year period. These 21 year periods are calculated by taking 10 years either side of the first year at which the global warming level is reached. This time will be different for different model ensemble members. To calculate the value for the Winter Precipitation Change, an average is taken across the 21 year period. We cannot provide a precise likelihood for particular emission scenarios being followed in the real world future. However, we do note that RCP8.5 corresponds to emissions considerably above those expected with current international policy agreements. The results are also expressed for several global warming levels because we do not yet know which level will be reached in the real climate as it will depend on future greenhouse emission choices and the sensitivity of the climate system, which is uncertain. Estimates based on the assumption of current international agreements on greenhouse gas emissions suggest a median warming level in the region of 2.4-2.8°C, but it could either be higher or lower than this level. What are the naming conventions and how do I explore the data? These data contain a field for each warming level and the 1981-2000 baseline. They are named 'pr winter change', the warming level or baseline, and 'upper' 'median' or 'lower' as per the description below. e.g. 'pr winter change 2.0 median' is the median value for summer for the 2.0°C warming level. Decimal points are included in field aliases but not in field names, e.g. 'pr winter change 2.0 median' is named 'pr_winter_change_20_median'. To understand how to explore the data, refer to the New Users ESRI Storymap. Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘pr winter change 2.0°C median’ values. What do the 'median', 'upper', and 'lower' values mean? Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future. For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, the Summer Precipitation Change was calculated for each ensemble member and they were then ranked in order from lowest to highest for each location. The ‘lower’ fields are the second lowest ranked ensemble member. The ‘higher’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble. This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and higher fields, the greater the uncertainty. ‘Lower’, ‘median’ and ‘upper’ are also given for the baseline period as these values also come from the model that was used to produce the projections. This allows a fair comparison between the model projections and recent past. Useful links For further information on the UK Climate Projections (UKCP). Further information on understanding climate data within the Met Office Climate Data Portal.

Data from a variety of hydrological parameters for the Zambezi River Basin. Range of data for a range of time periods from 1950s to present day Interface is slow, and cannot export data, but graphs and readouts from graphs possible. Parameters include: Daily discharge Daily Rainfall Water Level River Gauging station