Glossary

Annual maximum

The highest value of an indicator or variable that is attained within one year


Anthropogenic climate change

Climate change that can be identified as resulting from human activities. These activities include the burning of fossil fuels, deforestation, land use changes, livestock, fertilization, etc.

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CLM 4.5

Version 4.5 of the Community Land Model (CLM4.5), which is the land model for the Community Earth System Model (CESM).

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CaMa-Flood

The CaMa-Flood (Catchment-based Macro-scale Floodplain) model is designed to simulate the hydrodynamics in continental-scale rivers.

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Calibrated simulations

Model simulations that are compared with independent observations.


Climate Impact Assessment

The practice of identifying and evaluating the effects of climate change on natural and human systems.

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Climate models

A representation of the the climate on a computer. These models range from relatively simple representing only a few variables to complicated systems where a large number of physical, chemical and biological processes are represented. By studying the results of models, we can better understand the current and future climate.

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Climate variability

Climate variability refers to variations in the state (e.g., the occurrence of extremes, etc.) beyond an individual weather event. Variability may occur due to natural internal processes within the climate system or variations in natural or anthropogenic external forcing. For example, the probability that a summer is extremely warm is larger than it was 20 years ago.

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Droughts

A period of abnormally dry weather long enough to cause a serious hydrological imbalance. There are different types of droughts. A hydrological droughts is when the water supply is low, such as in streams, reservoir and groundwater. An agricultural drought is caused by the limited availablity of soil moisture affecting crop yield. A meteorological drought is a drought when there is a prolonged period of little to no precipitation.

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Emissions trajectories

A projected development in time of the emission of a greenhouse gasses, aerosols and greenhousegases precursors. Often RCP2.6, RCP4.5, RCP6.0 and RCP8.0 are used to respresent low to high future emission scenarios. Here RCP2.6 with relatively low emissions would lead to a low warming of the planet, while RCP8.0 would lead to a very high level of global warming.

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Environmental flow requirements

Environmental flow requirements are the minimum amount and quality of water required to sustain ecosystems and the human livelihoods that depend on it.

Acreman, Michael C., and Michael J. Dunbar. “Defining environmental river flow requirements? A review.” (2004).


Flood depth

Distance between the ground level and water surface.


Flood volume

The amount of water flowing through a cross-section during a flood event.


GFDL-ESM2M

GFDL (Geophysical Fluid Dynamics Laboratory) has constructed NOAA’s first Earth System Models (ESMs). In one model, ESM2M, pressure-based vertical coordinates are used along the developmental path of GFDL’s Modular Ocean Model version 4.1. In the other, ESM2G, an independently developed isopycnal model using the Generalized Ocean Layer Dynamics (GOLD) code base was used.

Dunne, John P., et al. “GFDL’s ESM2 global coupled climate–carbon earth system models. Part I: Physical formulation and baseline simulation characteristics.” Journal of climate 25.19 (2012): 6646-6665.

Dunne, John P., et al. “GFDL’s ESM2 global coupled climate–carbon earth system models. Part II: carbon system formulation and baseline simulation characteristics.” Journal of Climate 26.7 (2013): 2247-2267.


Global hydrological models

Global hydrological models (GHMs) model the land surface hydrologic dynamics of continental-scale river basins.

Gosling, Simon N., and Nigel W. Arnell. “Simulating current global river runoff with a global hydrological model: model revisions, validation, and sensitivity analysis.” Hydrological Processes 25.7 (2011): 1129-1145.


Grid cell

Smallest unit of the geographical domain covered by a numerical model, such as a climate or a hydrological model. Because of the complexity of the processes they represent and the limitations of computing power, these models divide up their modelling domain into a juxtaposition of “boxes” called grid cells. In the case of a climate model, the grid cells are tridimensional and are aligned along each spatial dimension. A climate model calculates the state of the climate system in each cell. Currently ISIMIP uses a grid size of 0.5 degrees or approximately 55 km at the equator.


H08

H08 is one of the 13 global hydrology models following the ISIMIP2a protocol which form the base of simulations for the ISIMIP2a global water sector outputs. H08 is a grid-cell based global hydrological model. It consists of six sub-models, namely land surface hydrology, river routing, reservoir operation, crop growth, environmental flow, and water abstraction. The formulations of sub-models are described in detail in Hanasaki et al. (2008a,b, 2010). In the standard simulation settings, H08 spatially covers the whole globe at a resolution of 0.5°×0.5° in order to assess geographical heterogeneity of hydrology and water use. Simulation period is typically for several decades and calculation interval is a day. The six sub-models exchange water fluxes and updates water storage at each calculation interval with the complete closure of water balance (the error is less than 0.01% of the total input precipitation). These characteristics enable the model to explicitly simulate the major interaction between natural water cycle and major human activities of the globe.

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Hanasaki, Naota, et al. “A global hydrological simulation to specify the sources of water used by humans.” Hydrology and Earth System Sciences 22.1 (2018): 789.


Hamon potential evapotranspiration

An equation to estimate the potential evapotranspiration (PET). The equation uses a dimensionless coefficent, the lenght of the day, the saturation vapor pressure and the average monthly temperature.

Hamon, W. Russell. Estimating potential evapotranspiration. Diss. Massachusetts Institute of Technology, 1960.


Historical period

In the context of climate science, the historical period defines the period of time that started with the start of industrial activities and their resulting impact on greenhouse gas concentrations, and extends until now. Climate conditions over the historical period are often compared with those during pre-industrial times or in the future.


Hydrological cycle

Hydrological cycle (also referred to as water cycle) The cycle in which water evaporates from the oceans and the land surface, is carried over the Earth in atmospheric circulation as water vapor, condenses to form clouds, precipitates again as rain or snow, is intercepted by trees and vegetation, provides runoff on the land surface, infiltrates into soils, recharges groundwater, and/or discharges into streams and flows out into the oceans, and ultimately evaporates again from the oceans or land surface. The various systems involved in the hydrological cycle are usually referred to as hydrological systems.

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IPSL-CMA5a-lr

The IPSL-CM4 model developed at Institut Pierre Simon Laplace (IPSL) contributed to CMIP3. It is a classical climate model that couples an atmosphere-land surface model to a ocean-sea ice model. The IPSL-CM5 model, which is contributes to CMIP5, is an Earth System Model (ESM) that includes all the previous developments. It is a platform that allows for a consistent suite of models with various degrees of complexity, various numbers of components and processes, and different resolutions.

Dufresne, J-L., et al. “Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5.” Climate Dynamics 40.9-10 (2013): 2123-2165.


ISIMIP2b

Simulation round 2b from the Inter-sectoral Impact Model Intercomparison Project designed to provide robust information about the impacts of 1.5°C global warming and related low-emission pathways. The scientific rationale for the scenario design is described in detail in the paper by Frieler et al. 2017 ‘Assessing the impacts of 1.5°C global warming simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b)’.

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Frieler, Katja, et al. “Assessing the impacts of 1.5 C global warming–simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b).” Geoscientific Model Development (2017).


Indicator

Variable (e.g., temperature or rainfall) or combination of variables that is representative of the state of a system. For example, the amount of rainfall and evaporation are important factors in the drought indicator.


JULES-W1

JULES-W1 is one of the 13 global hydrology models following the ISIMIP2a protocol which form the base of simulations for the ISIMIP2a global water sector outputs.

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LPJmL

The LPJmL model is a Dynamic Global Vegetation Model, which was designed to simulate the global terrestrial carbon cycle and the response of carbon and vegetation patterns under climate change. As carbon and water cycles are intimately linked, it was quickly extended to also simulate the terrestrial water cycle (see model history).

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Land cover

Physical material that the land is covered by. For example forest, water, buildings and asphalt.

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Land use

The purpose for which the land is used. For example for agriculture, recreation, cities, etc. See also land use change.

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Levels of global warming

A specific level of global mean temperature compared to a reference period, which is usually representative of pre-industrial conditions. For example, the current mean temperature is 2 degrees warmer as compared to the year 1800.


MATSIRO

MATSIRO is the land surface scheme of an Atmospheric Ocean General Circulation Model, the Model for Interdisciplinary Research On Climate, jointly developed by the Atmosphere and Ocean Research Institute at the University of Tokyo, the National Institute of Environmental Studies, and the Frontier Research Center for Global Change in Japan.

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MIROC5

MIROC5 is an atmosphere-ocean general cirulaton model.

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MPI HM

The MPI-HM is a global hydrological model. It is used to investigate hydrological research questions mostly related to high resolution river routing. While hydrological processes are implemented in similar complexity as in full land surface models, the MPI-HM does not compute any energy related fluxes. MPI-HM is one of the 13 global hydrology models following the ISIMIP2a protocol which form the base of simulations for the ISIMIP2a global water sector outputs; for a full technical description of the ISIMIP2a Simulation Data from Water (global) Sector, see this DOI link: http://doi.org/10.5880/PIK.2017.010

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Model ensemble

When a group of models is run with the same input, this is called a model ensemble. This is often done to get a grasp of the uncertainy of the models. A large difference between the models indicate a high uncertainty, while small diferences indicate a low uncertainy.

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Modelling uncertainty

Uncertainty is a state of incomplete knowledge that can result from a lack of information or from disagreement about what is known or even knowable. It may have many types of sources, from imprecision in the data to ambiguously defined concepts or terminology, or uncertain projections of human behaviour. Uncertainty can therefore be represented by quantitative measures (e.g., a probability density function) or by qualitative statements (e.g., reflecting the judgment of a team of experts).

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ORCHIDEE

ORCHIDEE is a global process-oriented Terrestrial Biosphere Model. It calculates carbon, water and energy fluxes between land surfaces and the atmosphere. The water and energy component computes major biophysical variables (albedo, roughness height, soil humidity) and solves the energy and hydrological balances at a half-hourly time step.

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PCR-GLOBWB

PCR-GLOBWB 2 is a grid-based global hydrology and water resources model devloped at Utrecht University. The computational grid has a 5 arc-minute resolution (~10 km at the equator) and covers all continents except Greenland and Antarctica. Time steps for hydrology and water use are one-day, while the internal time stepping for hydrodynamic river routing is variable. For each grid cell and each time step, PCR-GLOBWB 2 simulates moisture storage as well as the water exchange between the soil, atmosphere and underlying groundwater reservoir. The exchange with the atmosphere comprises precipitation, evaporation from open water, snow and soils and plant transpiration, while the model also simulates snow accumulation, snowmelt, and glacier melt. PCR-GLOBWB simulates runoff partitioned into surface runoff, interflow, and groundwater recharge as well as routing of water over the terrain. Runoff generated by snow and glacier melt, surface runoff, interflow, and groundwater is routed across the river network to the ocean or endorheic lakes and wetlands using the kinematic wave approximation. It also possible to include floodplain inundation and to simulate surface-water temperature. PCR-GLOBWB 2 includes over 6000 manmade reservoirs from the GranD database that are progressively introduced in time and a reservoir operation scheme dependent on each reservoir’s purpose. Human water use is fully integrated with the hydrological model. Thus, at each time step: 1) water demand is estimated for irrigation, livestock, industry, and households; 2) these demands are translated into actual withdrawals from groundwater and surface water (rivers, lakes, and reservoirs) subject to availability of these resources and maximum groundwater pumping capacity in place; and 3) consumptive water use and return flows are calculated per sector. As an option PCR-GLOBWB 2 can be partially or fully coupled to a 2-layer global groundwater model based on MODFLOW and to the hydrodynamic model codes DFLOW-FM, CaMaFlood and LISFLOOD-FP.

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Palmer Drought Severity Index (PDSI)

Precipitation and temperature are combined in the Palmer Drought Severity Index (PDSI), considered as one measure of drought. The PDSI does not include variables such as wind speed, solar radiation, cloudiness and water vapour but is a superior measure to precipitation alone. Strengths: Used around the world, and the code and output are widely available. Scientific literature contains numerous papers related to PSDI. The use of soil data and a total water balance methodology makes it quite robust for identifying drought. Weaknesses: The need for serially complete data may cause problems. PDSI has a timescale of approximately nine months, which leads to a lag in identifying drought conditions based upon simplification of the soil moisture component within the calculations. This lag may be up to several months, which is a drawback when trying to identify a rapidly emerging drought situation. Seasonal issues also exist, as the PDSI does not handle frozen precipitation or frozen soils well. More information here.

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Penman-Monteith equation

An equation used to approximate the net evapotranspiration, based on daily mean temperature, wind speed, relative humidity and solar radiation data.

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Potential evapotranspiration (PET)

Evapotranspiration is the combined loss of water from a given area during a specified period of time, by evaporation from the soil surface and by transpiration from plants.

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Present-day conditions

In the context of climate science, the present-day conditions correspond to the current climate or climate impact or indicator. Present-day conditions are often used as a reference to be compared to future or pre-industrial conditions.


Priestley-Taylor

An equation to approximate the net evapotransporation. In contrast to the Penman-Monteith equation, this equation requires only radiance observations. However, several assumptions are made, making this equation is less exact.

Priestley, Charles Henry Brian, and R. J. Taylor. “On the assessment of surface heat flux and evaporation using large-scale parameters.” Monthly weather review 100.2 (1972): 81-92.


Projections

A projection is an estimate or forecast of the future based on a set of assumptions. For example, given that countries reduce their CO2 emmissions by x%, the global temperature increase will be limited to 2 degrees Celcius.

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Relative change

Change in an indicator in a given period (for example in the future) compared to an earlier period (for example during pre-industrial times), expressed as a percentage of the value of the indicator in the earlier period.


Return level

The highest or lowest value of a given variable, on average occurring once in a given period of time (e.g., in 10 years). For example, a 10-year return level for of 40 degrees indicates that a 40 degrees is attained or exceeded only every 10 summers on average.

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River floods

The overflowing of the normal confines of a river, or the accumulation of water over areas that are not normally submerged.

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River flow

Water flow within a river channel, for example, expressed in meters per second. Also often referred to as river discharge.

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Rootzone soil moisture

Water that is available in those parts of the soil from which plant roots can extract water, thereby being an important limiting factor constraining crop productivity.


Runoff

The flow of water over the surface or through the subsurface, which typically originates from precipitation and/or snow/ice melt.

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Soil moisture

Water stored in or at the land surface and available for evapotranspiration.

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Soil water coloumn

Water that is available within the full depth of the modelled 3D column that is representing the soil within the impact models.


Standardized precipitation and evapotranspiration index (SPEI)

SPEI uses the basis of SPI but includes a temperature component, allowing the index to account for the effect of temperature on drought development through a basic water balance calculation. Strengths: The inclusion of temperature along with precipitation data allows SPEI to account for the impact of temperature on a drought situation. The output is applicable for all climate regimes, with the results being comparable because they are standardized. With the use of temperature data, SPEI is an ideal index when looking at the impact of climate change in model output under various future scenarios.

Weaknesses: The requirement for a serially complete dataset for both temperature and precipitation may limit its use due to insufficient data being available. Being a monthly index, rapidly developing drought situations may not be identified quickly.

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Standardized precipitation index (SPI)

The basis of the SPI index is that it builds upon the relationships of drought to frequency, duration and timescales. It uses historical precipitation records for any location to develop a probability of precipitation that can be computed at any number of timescales, from 1 month to 48 months or longer. There are many versions of SPI available, implemented within various computing software packages.

Strengths: Using precipitation data only is the greatest strength of SPI, as it makes it very easy to use and calculate. SPI is applicable in all climate regimes, and SPI values for very different climates can be compared. The ability of SPI to be computed for short periods of record that contain missing data is also valuable for those regions that may be data-poor or lacking long-term, cohesive datasets.

Weaknesses: With precipitation as the only input, SPI is deficient when accounting for the temperature component, which is important to the overall water balance and water use of a region. This drawback can make it more difficult to compare events of similar SPI values but different temperature scenarios. SPI assumes a prior distribution, which may not be appropriate in all environments, particularly when examining short-duration events or entry into, or exit out of, drought.

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Standardized runoff index (SRI)

The standardized runoff index (SRI) specifies the number of standard deviations from the mean runoff. A low SRI indicates a low runoff, while a high SRI indicates a high runoff.

Shukla, Shraddhanand, and Andrew W. Wood. “Use of a standardized runoff index for characterizing hydrologic drought.” Geophysical research letters 35.2 (2008).


Standardized soil moisture index (SSI)

The standardized soil moisture index (SSI) specifies the number of standard deviations from the mean historice soil moisture. A low SSI indicates a relatively dry soil, while a high SSI indicates a wet soil.

Carrão, Hugo, et al. “An empirical standardized soil moisture index for agricultural drought assessment from remotely sensed data.” International journal of applied earth observation and geoinformation 48 (2016): 74-84.


Storm surge

High sea as a result of wind and atmospheric pressure. This if often occurs during tropical cyclones (i.e., hurricane, typhoon or cyclone)


Surface elevation

The height above sealevel.


Time slices

Periods of time over which the state of a climate or climate impact variable is averaged. For example, the some years are warmer and some are colder. However, when the temperature is averaged over a longer time period (e.g., 20 years) these annual fluctations disappear.


WaterGAP2

WaterGAP2 is a global water availability and water use model. WaterGAP2 is one of the 13 global hydrology models following the ISIMIP2a protocol which form the base of simulations for the ISIMIP2a global water sector outputs.

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