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.

Crop year 2012 US map at the county level shows drought-specific disaster designations across the country under USDA's amended rule.

Download a list of crop year 2012 drought-specific designated Primary and Contiguous Counties in PDF File Format.

Crop year 2013 US map at the county level shows drought-specific disaster designations across the country under USDA's amended rule.

Download a list of crop year 2013 drought-specific designated Primary and Contiguous Counties in PDF File Format.

Crop year 2014 US map at the county level shows drought-specific disaster designations across the country under USDA's amended rule.

Download a list of crop year 2014 drought-specific designated Primary and Contiguous Counties in PDF File Format.

Drought affects the planet in many ways, but some of the most severe impacts are to agricultural areas, especially those in developing countries. Prolonged drought may cause crops to fail, resulting in widespread food shortages and famine. While these developing countries may not have sophisticated ground-based sensor networks to monitor drought conditions, we can use satellites to estimate droughts anywhere on Earth. Satellite drought index information from NOAA is summarized within areas identified as agricultural based on an analysis by the USGS and Esri. The map below displays the latest monthly CHIRPS Standardized Precipitation Index product produced by USGS and UC Santa Barbara.

This data delineates New Jersey drought regions. Drought regions provide a regulatory basis for coordinating local responses to regional water-supply shortages. The six drought regions are based on watershed and water-supply considerations. Drought region boundaries coincide with municipal boundaries as referenced by the N.J. Dept of Environmental Protection (NJDEP). Each municipality in New Jersey is assigned to a drought region based on the watershed covering and supplying water to the municipality. Each data record of the file includes name of the drought region. This is the second version of the drought regions. It differs from the original delineation in two ways: 1) The number of drought regions were expanded from five to six in order to account for water-supply issues identified for the New Jersey coastal plain. The original version included the north part of the Coastal Plain in the central region. Version 2 separates a north coastal region, consisting of Monmouth and northern Ocean Counties, from the coastal region to the south. 2) Municipalities in Mercer County receiving water from the Trenton Water Dept. were moved into the southwest region from the northwest. Pennington and Hopewell boroughs were also moved to the southwest region. This is the third version of the drought regions and was released in May 2004. There are two changes from the second version. Roosevelt Boro in Monmouth County was moved to the southwest drought region (from the coastal north) and Berlin Twp in Camden County was moved to the coastal south drought region (from the southwest). Both changes were made in recognition of the location of actual water supply to these municipalities.

Drought Severity Index, 12-Month Accumulations. Projections for a range of future warming levels from UKCP18. Provided on a 12km BNG grid.This 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 is therefore a measure of drought severity, not frequency, and higher values indicate more severe drought.12-month accumulations have been selected as this is likely to indicate hydrological drought - water scarcity over a much longer period of time which heavily deplete water resources on a large scale (as opposed to meterological 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.This data contains a field for each warming level. They are named 'DSI12' (Drought Severity Index for 12 month accumulations), the warming level, 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'. Data defaults to displaying 'DSI12 2.0 median' values, use 'change style' to display other values.The warming levels used are 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C, and two baselines are also provided for 1981-2000 (corresponding to 0.51°C warming) and 2000-2017 (corresponding to 0.835°C warming).What is the data?The data is from the UKCP18 regional projections using the RCP8.5 scenario. Rather than giving projections for a specific date under different scenarios, one scenario is used and projections are given at the different warming levels. So this data shows the expected Drought Severity Index should these warming levels be reached, at the time that the warming level is reached.For full details, see 'Future Changes to high impact weather in the UK'. HM Hanlon, D Bernie, G Carigi and JA Lowe. Climatic Change, 166, 50 (2021) https://doi.org/10.1007/s10584-021-03100-5What 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 was taken from each ensemble member - the mean of a 21yr period centred on the year the warming level was reached. They were then ranked in order from lowest to highest.The 'lower' fields are the second lowest ranked ensemble member.The 'higher' fields are the second highest ranked ensemble member.The 'median' fields are the median average of all ensemble members.This gives a median average value, and a spread of the ensemble members indicating the level of uncertainty in the projections.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/

Date of freeze for historical (1985-2005) and future (2071-2090, RCP 8.5) time periods, and absolute change between them, based on analysis of MACAv2METDATA. Average historical temperature change, between 1948-1968 and 1996-2016 averages, in Celsius. Calculated using averages of minimum and maximum monthly values during these time periods. Values are based on TopoWx data. Download this data or get more information

EM-DAT contains essential core data on the occurrence and effects of over 22,000 mass disasters in the world from 1900 to the present day., including floods, droughts, storm events, famine and disease epidemics.The database is compiled from various sources, including UN agencies, non-governmental organisations, insurance companies, research institutes and press agencies.

gridMET is a dataset of daily high-spatial resolution (~4-km, 1/24th degree) surface meteorological data covering the contiguous US from 1979-yesterday. We have also extended these data to cover southern British Columbia in our real time products. These data can provide important inputs for ecological, agricultural, and hydrological models. These data are updated daily. gridMET is the preferred naming convention for these data; however, the data are also known as cited as METDATA.

This is a geospatial data repository for agricultural economists interested in climate, production or soil data. Everything listed here is openly accessible. Most of it is global or quasi-global, with a few Africa-specific products. For development economists with interest in other open source data sets, I would refer you to a major and comprehensive data set collection effort on DEVECONDATA.

A global dataset of Palmer Drought Severity Index (PDSI) and potential evporation (PE) at 1.0-degree, monthly resolution.

Date of freeze for historical (1985-2005) and future (2071-2090, RCP 8.5) time periods, and absolute change between them, based on analysis of MACAv2METDATA. Average historical temperature change, between 1948-1968 and 1996-2016 averages, in Celsius. Calculated using averages of minimum and maximum monthly values during these time periods. Values are based on TopoWx data. Download this data or get more information

The Water Data Portal (WDP), following ""one-stop shop"" approach, provides access to a large amount of data related to water and agriculture. WDP contains meteorological, hydrological, socio-economic, spatial data layer, satellite images as well as hydrological model setups. The data in the WDP, both spatial & non-spatial, are supported by the standardized metadata and are available for download by user including academia, scientists, researchers and decision makers. However, access is provided in compliance with copyrights, intellectual property rights and data agreements with our partners. Data products include Global Environmental Flow Information System, Global Drought Patterns, Global Irrigated Area Mapping, Flow Management Classes, and regional data on Irrigated Area (Asia and Africa), Glacier and Snow (Asia), Flood Risk Mapping (East Asia) (South East Asia), Flood Risk Mapping (Nigeria), Water Resources Management (Eastern Ganges), Climate Change vulnerability (Nepal), Water Quality Mapping (Sri Lanka), Kabul River Basin Geodatabase, Tana River Basin Information System. The Portal also links to the IWMI Irrigation Benchmarking Service, providing data on irrigation system performance (service delivery, financial, agricultural, environmental, gender) based on voluntary submissions from irrigation schemes across the world.

Leaf level oak isoprene emissions and co2/H2O exchange in the Ozarks, USA BAGeron.csv is the speciated biomass displayed in Figure 1. Biomass Dry Weights.xlsx is used to convert leaf area to dry leaf biomass and is used in Figure 2. Daly Ozarks leaf ISOP.txt and MOFLUX_Isoprene Summary_refined Tcurve data.xlsx are the leaf isoprene emission rate files shown in Figure 2. Harley Aug12_Chris.xls is the leaf isoprene emission rate file shown in Figure 3. Daly Ozarks leaf.txt is the BVOC emissions file used for Figure 7 and Table 4. Drought IS.txt is the review data given in Table 2. Fig4 Aug10 2012 Harley.txt is shown in Figure 4. Fig 5 Aug14 2012 Harley.txt is shown in Figure 5. Daly Ozarks Leaf.txt is used in Fig 7. Drought IS.txt is used in Fig 8. This dataset is associated with the following publication: Geron , C., R. Daly , P. Harley, R. Rasmussen, R. Seco, A. Guenther, T. Karl, and L. Gu. Large Drought-Induced Variations in Oak Leaf Volatile Organic Compound Emissions during PINOT NOIR 2012. CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 146: 8-21, (2016).

Interactive maps from the National Integrated Drought Information System. Drought is one of many factors that can affect the intensity and severity of a fire. Dry, hot, and windy weather combined with dried out (and more flammable) vegetation can increase the potential for large-scale wildfires. Use the interactive map below to explore wildfire, smoke, and air quality data alongside drought and climate conditions. Drought can have significant impacts on water utility operation, including loss of water supply, poor source water quality, increased costs, and reduced revenues. Use the interactive map below to explore water supply data (streamflow, river forecasts, snow water equivalent) alongside drought and climate conditions. Drought can have significant direct and indirect economic impacts on the agricultural sector, reducing the water availability and water quality necessary for productive farms, ranches, and grazing lands. Use the interactive map below to explore agricultural commodities data alongside drought and climate conditions.

Office of the New Mexico State Climatologist provides weather and climate information to our community members. Contains the most current observations from the ZiaMet weather station network, the current CoCoRaHS precipitation map, and the US Drought Monitor map for New Mexico.

The U.S. Drought Monitor (USDM) is updated each Thursday to show the location and intensity of drought across the country. This map shows drought conditions across New Mexico using a five-category system, from Abnormally Dry (D0) conditions to Exceptional Drought (D4). The USDM is a joint effort of the National Drought Mitigation Center, USDA, and NOAA.

NCEI offers several types of climate information generated from examination of the data in the archives. These types of information include record temperatures, record precipitation and snowfall, climate extremes statistics, and other derived climate products.

Open Data for Resilience Initiative (OpenDRI) applies the concepts of the global open data movement to the challenges of reducing vulnerability to natural hazards and the impacts of climate change. OpenDRI supports World Bank Regional Disaster Risk Management Teams to build capacity and long-term ownership of open data projects with client countries that are tailored to meet specific needs and goals of stakeholders around three main areas of Sharing Data, Collecting Data, Using Data. All data is published under an open license. Projects include Open Cities Africa, with national projects in: Niger (flood hostpots and mitigation), Uganda (drought risk information and disaster risk financing), Zanzibar (vunlerability to natural disasters), Pacific Islands (Natural Disasters and Climate Change), Sri Lanka (evidence based methods for natural disaster response), Afghanistan (disaster risk decisionmaking), St Vincent and the Grenadines (hydroclimatic disasters), Saint Lucia (post disaster rehabilitation), Jamaica (storm even impact), Serbia (disaster preparedness), Indonesia (disaster management especially flooding), Seychelles (site specific risks of floods, earthquakes, cyclones, storm surge and tsunamis), Muaritius (under development), Madagascar (under development), Vietnam (natural hazards especially flood risks and climate change impacts), Bangladesh (under development), Pakistan (earthquakes and monsoon floods), Nepal (Seismic risk), Haiti (storms, flooding, landslides, environmental degradation), Guyana (under development), Grenada (under development), Dominica (extreme weather events), Colombia (flooding, landslides, increased vulnerability due to insufficient urban planning), Antigua and Barbuda (cyclones, fires and flooding), Belize (storm, flood and tsunami risks), Bolivia (natural hazards and climate change), Kyrgyz Republic (risk data on meteorological, geological, geophyical and boilogical hazards), Philippines (typhoones and monsoon floods recovery data), Tanzania (flood maps), Mozambique (flood, cyclone and windstorms), Comoros (flood, storm, volcanic eruption), Malawi (information to develop schools, healthcare and agriculture against floods and droughts), Armenia (earthquakes, drought, hailstorms, landslides)

This database collates 3552 development indicators from different studies with data by country and year, including single year and multiple year time series. The data is presented as charts, the data can be downloaded from linked project pages/references for each set, and the data for each presented graph is available as a CSV file as well as a visual download of the graph (both available via the download link under each chart).

Access to adequate supplies of fresh water is becoming an increasingly critical issue in many parts of the world. In arid regions of the southwestern United States, diminishing water supplies and extended periods of drought have generated an interest in non-traditional water resources, and the development of new technologies such as desalination of brackish water to exploit those resources. New Mexico has limited supplies of fresh water, but over the last century there have been claims that the state has very large reserves of brackish groundwater (e.g., Hood and Kister, 1962; McLean, 1970). However, our knowledge of the quality and volume of these brackish water resources varies significantly across the state. Some aquifers and groundwater basins in more densely populated areas have been very thoroughly investigated by multiple individuals and agencies over time periods of years or decades. Despite this foundation of pre-existing research, our knowledge of the distribution of brackish groundwater in many aquifers in New Mexico is often poorly constrained.

PDSI from the Dai dataset. The Palmer Drought Severity Index (PDSI) is devised by Palmer (1965) to represent the severity of dry and wet spells over the U.S. based on monthly temperature and precipitation data as well as the soil-water holding capacity at that location. These data consist of the monthly PDSI over global land areas from 1850 to 2010. Different precipitation/temperature datasets are used in the different files. Update and more information are available at CGD (Climate and Global Dynamics Division). https://web.archive.org/web/*/https://esrl.noaa.gov/psd/data/gridded/data.pdsi.html

Note: To download this raster dataset, go to ArcGIS Open Data Set and click the download button, and under additional resources select any of the download options. Data can also be downloaded from the FSGeodata Clearinghouse.More information about rangeland productivity and the effects of drought are available in this StoryMap; additional drought and rangeland products from the Office of Sustainability and Climate are available in our Climate Gallery. Time enabled image service showing estimates of annual production of rangeland vegetation.Production data were generated using the Normalized Difference Vegetation Index (NDVI) from the Thematic Mapper Suite from 1984 to 2021 at 250 m resolution. The NDVI is converted to production estimates using two regression formulas depending on the level of the NDVI; there is one equation for lower values (and thus lower production values) and one for higher values. This raster dataset yields estimates of annual production of rangeland vegetation and should be useful for understanding trends and variability in forage resources. This raw lbs/acre data that the Z-scores were derived from as well as the Z-scores dataset can be downloaded from: https://data.fs.usda.gov/geodata/rastergateway/rangelands/index.phpMore information about rangeland productivity and the effects of drought are available in this story map.

Production data were generated using the Normalized Difference Vegetation Index (NDVI) from the Thematic Mapper Suite from 1984 to 2021 at 250 m resolution. The NDVI is converted to production estimates using two regression formulas depending on the level of the NDVI; there is one equation for lower values (and thus lower production values) and one for higher values.This raster dataset yields estimates of annual production of rangeland vegetation and should be useful for understanding trends and variability in forage resources.The Rangeland Productivity data can be downloaded here:https://data.fs.usda.gov/geodata/rastergateway/rangelands/index.php

IDSI integrates multi-source remote sensing data from moderate resolution imaging spectroradiometer (MODIS) and tropical rainfall measuring mission (TRMM), ESA Soil Moisture (ASCAT) Products and it synthesizes precipitation deficits, soil thermal stress and vegetation growth status in drought process. Therefore, this method is favourable to monitor the comprehensive drought over South Asia.

A collection of web tools for visualizing past and projected climate and hydrology of the contiguous United States of America addressing questions relating to Agriculture, Climate, Fire Conditions, and Water.

ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience. The tool highlights the likelihood of different natural hazards affecting project areas (very low, low, medium and high), provides guidance on how to reduce the impact of these hazards, and where to find more information. The hazard levels provided are based on published hazard data, provided by a range of private, academic and public organizations. Users and potential partners can contact ThinkHazard! administrators with queries or information to add to the tool, at the ThinkHazard! feedback form. This form is available on every page of the website.

Drought Areas data description: This data layer is derived from copying the designated WRIAs. WRIAs data description: Water Resource Inventory Areas (WRIA) for Washington State at 1:24,000 scale. WRIAs were formalized under WAC 173-500-040 and authorized under the Water Resources Act of 1971, RCW 90.54. Ecology was given the responsibility for the development and management of these administrative and planning boundaries. These boundaries represent the administrative under pinning of this agency's business activities. The original WRIA boundary agreements and judgments were reached jointly by Washington's natural resource agencies (Ecology, Natural Resources, Fish and Wildlife) in 1970.

Drought Areas data description: This data layer is derived from copying the designated WRIAs. WRIAs data description: Water Resource Inventory Areas (WRIA) for Washington State at 1:24,000 scale. WRIAs were formalized under WAC 173-500-040 and authorized under the Water Resources Act of 1971, RCW 90.54. Ecology was given the responsibility for the development and management of these administrative and planning boundaries. These boundaries represent the administrative under pinning of this agency's business activities. The original WRIA boundary agreements and judgments were reached jointly by Washington's natural resource agencies (Ecology, Natural Resources, Fish and Wildlife) in 1970.

Drought Areas data description: This data layer is derived from copying the designated WRIAs. WRIAs data description: Water Resource Inventory Areas (WRIA) for Washington State at 1:24,000 scale. WRIAs were formalized under WAC 173-500-040 and authorized under the Water Resources Act of 1971, RCW 90.54. Ecology was given the responsibility for the development and management of these administrative and planning boundaries. These boundaries represent the administrative under pinning of this agency's business activities. The original WRIA boundary agreements and judgments were reached jointly by Washington's natural resource agencies (Ecology, Natural Resources, Fish and Wildlife) in 1970.

Policysupport.org is home to a range of web-based policy support systems developed, since 2003, collaboratively by AmbioTEK CIC, and applied by King's College London and a range of other partners as specified for each system. The systems are based on the common ecoengine framework for developing web based policy support systems (AmbioTEK) and SimTerra databases (AmbioTEK) but are very varied in their applications (King's College London). Applications in the Policy Support Suite include: WaterWorld: a testbed for the development and implementation of land and water related policies for sites and regions globally, enabling their intended and unintended consequences to be tested in silico before they are tested in vivo. WaterWorld can also be used to understand the hydrological and water resources baseline and water risk factors associated with specific activities under current conditions and under scenarios for land use, land management and climate change. It incorporates detailed spatial datasets at 1-square km and 1 hectare resolution for the entire world, spatial models for biophysical and socio-economic processes along with scenarios for climate, land use and economic change. A series of interventions (policy options) are available which can be implemented and their consequences traced through the socio-economic and biophysical systems. The model integrates with a range of geobrowsers for immersive visualisation of outcomes. AguAAndes: a testbed for the development and implementation of land and water related policies in the Andes, enabling intended and unintended consequences to be tested in silico before they are tested in vivo . It incorporates detailed spatial datasets at 1-square km and 1 hectare resolution for the entire Andes, spatial models for biophysical and socioeconomic processes along with scenarios for climate, land use and economic change. A series of interventions (policy options) are available which can be implemented and their consequences traced through the socio-economic and biophysical systems. CompAndes: a web based tool based on AguAAndes and is developed as a Negotiation Support System (NSS) for negotiations around benefit sharing mechanisms for water. This NSS is a testbed for negotiations around benefit sharing mechanisms for water focusing on sustaining equitable flows of water for all through appropriate land, ecosystem and water management. It is focused on enabling the intended and unintended consequences of benefit sharing mechanisms to be tested in silico before they are tested in vivo. Co$ting Nature: a web based tool for natural capital accounting and analysing the ecosystem services provided by natural environments (i.e. nature's benefits), identifying the beneficiaries of these services and assessing the impacts of human interventions. This PSS is a testbed for the development and implementation of conservation strategies focused on sustaining and improving ecosystem services. MENARA: a web based policy support system for understanding strength, weakness, opportunity and threat (SWOT) at scales from pixel through regional to national considering environment, water, energy, food, economy and population. It is an horizon scanning tool to identify material threats, opportunities and choke points that may precipitate conflict and is designed to help to think through locally appropriate policy responses. FIESTA-FOGINT: a research model to quantify fog inputs in absolute terms and as a proportion of rainfall. Commonly applied to tropical montane cloud affected forests. Also maps the distribution of these forests. EcoActuary: a testbed for the development and implementation of green and grey infrastructure investments focused on reducing the risk to insured assets of multi-hazard risks, including flooding and drought. It incorporates detailed spatial datasets at 1-square km and 1 hectare resolution for the entire world, spatial models for biophysical and socioeconomic processes along with scenarios for climate, land use and economic change. A series of investments can be implemented and their consequences traced through the socio-economic and biophysical systems. An actuary determines the probability (and financial consequences) of risks. They work with accountants, underwriters (and catastrophe modellers) to set insurance rates (premiums). The Eco:Actuary determines mitigation of risk by specific configurations of green infrastructure (GI) and by asset adaptation. It helps understand the asset value protected by GI, alongside other GI co-benefits (ecosystem services). The Eco:Actuary helps advise risk reduction, resilience to avoid losses.