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NASA NTRS1991

Solar Constant (SOLCON) Experiment: Ground Support Equipment (GSE) software development

The Solar Constant (SOLCON) Experiment, the objective of which is to determine the solar constant value and its variability, is scheduled for launch as part of the Space Shuttle/Atmospheric Laboratory for Application and Science (ATLAS) spacelab mission. The Ground Support Equipment (GSE) software was developed to monitor and analyze the SOLCON telemetry data during flight and to test the instrument on the ground. The design and development of the GSE software are discussed. The SOLCON instrument was tested during Davos International Solar Intercomparison, 1989 and the SOLCON data collected during the tests are analyzed to study the behavior of the instrument.

Gibson, M. Alan↗

DOE OSTI2026

CMIP7 Data Request: atmosphere priorities and opportunities

This paper presents a comprehensive overview of the Coupled Model Intercomparison Project Phase 7 (CMIP7) request for data unlocking key research avenues in atmospheric science and provides justification for the resources needed to produce this data. Topics within the CMIP7 Atmosphere Theme centre around processes and feedbacks in atmospheric science such as clouds, aerosols and atmospheric chemistry, atmospheric circulation, temperature variability and extremes, radiative forcings, and Earth system model evaluation. These topics are summarised in this paper as scientific “opportunities” which will be realised through CMIP7 experiments and Earth system model outputs. These opportunities were submitted by a thematic group of atmospheric science community representatives combined with an extended consultation process. The production of these variables will close key gaps and uncertainties identified during previous rounds of CMIP, and will be broadly used by scientific, policy, governmental, industry, and other communities that rely on climate model projections for research and decision making, including supporting the 7th Intergovernmental Panel on Climate Change Assessment Report (AR7). As an author group, we also reflect on the process used to collate this data request and make recommendations to future CMIP governance on implementing a consultation on this scale in the future.

58 GEOSCIENCES↗

NASA NTRS1990

Satellite-derived cloud fields during the FIRE cirrus IFO case study

The First ISCCP Regional Experiment (FIRE) Cirrus Intensive Field Observation (IFO) program measured cirrus cloud properties with a variety of instruments from the surface, aircraft, and satellites. Surface and aircraft observations provide a small scale point and line measurements of different micro- and macro-physical properties of advecting and evolving cloud systems. Satellite radiance data may be used to measure the areal variations of the bulk cloud characteristics over meso- and large scales. Ideally, the detailed cloud properties derived from the small scale measurements should be tied to the bulk cloud properties typically derived from the satellite data. Full linkage of these data sets for a comprehensive description of a given cloud field, one of the goals of FIRE, should lead to significant progress in understanding, measuring, and modeling cirrus cloud systems. The relationships derived from intercomparisons of lidar and satellite data by Minnis et al. are exploited in a mesoscale analysis of the satellite data taken over Wisconsin during the Cirrus IFO case study.

Heck, Patrick W.↗

NASA NTRS2015

Python-Based Scientific Analysis and Visualization of Precipitation Systems at NASA Marshall Space Flight Center

At NASA Marshall Space Flight Center (MSFC), Python is used several different ways to analyze and visualize precipitating weather systems. A number of different Python‐based software packages have been developed, which are available to the larger scientific community. The approach in all these packages is to utilize pre‐existing Python modules as well as to be object‐oriented and scalable. The first package that will be described and demonstrated is the Python Advanced Microwave Precipitation Radiometer (AMPR) Data Toolkit, or PyAMPR for short. PyAMPR reads geolocated brightness temperature data from any flight of the AMPR airborne instrument over its 25‐year history into a common data structure suitable for user‐defined analyses. It features rapid, simplified (i.e., one line of code) production of quick‐look imagery, including Google Earth overlays, swath plots of individual channels, and strip charts showing multiple channels at once. These plotting routines are also capable of significant customization for detailed, publication‐ready figures. Deconvolution of the polarization‐varying channels to static horizontally and vertically polarized scenes is also available. Examples will be given of PyAMPR's contribution toward real‐time AMPR data display during the Integrated Precipitation and Hydrology Experiment (IPHEx), which took place in the Carolinas during May‐June 2014. The second software package is the Marshall Multi‐Radar/Multi‐Sensor (MRMS) Mosaic Python Toolkit, or MMM‐Py for short. MMM‐Py was designed to read, analyze, and display three‐dimensional national mosaicked reflectivity data produced by the NOAA National Severe Storms Laboratory (NSSL). MMM‐Py can read MRMS mosaics from either their unique binary format or their converted NetCDF format. It can also read and properly interpret the current mosaic design (4 regional tiles) as well as mosaics produced prior to late July 2013 (8 tiles). MMM‐Py can easily stitch multiple tiles together to provide a larger regional or national picture of precipitating weather systems. Composites, horizontal and vertical crosssections, and combinations thereof are easily displayed using as little as one line of code. MMM‐Py can also write to the native MRMS binary format, and sub‐sectioning of tiles (or multiple stitched tiles) is anticipated to be in place by the time of this meeting. Thus, MMM‐Py also can be used to power the creation of custom mosaics for targeted regional studies. Overlays of other data (e.g., lightning observations) are easily accomplished. Demonstrations of MMM‐Py, including the creation of animations, will be shown. Finally, Marshall has done significant work to interface Python‐based analysis routines with the U.S. Department of Energy's Py‐ART software package for radar data ingest, processing, and analysis. One example of this is the Python Turbulence Detection Algorithm (PyTDA), an MSFC‐based implementation of the National Center for Atmospheric Research (NCAR) Turbulence Detection Algorithm (NTDA) for the purposes of convective‐scale analysis, situational awareness, and forensic meteorology. PyTDA exploits Py‐ART's radar data ingest routines and data model to rapidly produce aviation‐relevant turbulence estimates from Doppler radar data. Work toward processing speed optimization and better integration within the Py‐ART framework will be highlighted. Python‐based analysis within the Py‐ART framework is also being done for new research related to intercomparison of ground‐based radar data with satellite estimates of ocean winds, as well as research on the electrification of pyrocumulus clouds.

Lang, Timothy J.↗

NASA NTRS1997

Comparative Modeling Studies of Boreal Water and Carbon Balance

The coordination of the modeling and field efforts for an Intensive Field Campaign (IFC) may resemble the chicken and egg dilemma. This session's theme advocates that early and proactive involvement by modeling teams can produce a scientific and operational benefit for the IFC and Experiment. This talk will provide some examples and suggestions originating from the NASA funded IFC's of the FIFE First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment, Oregon Transect Ecosystem Research (OTTER) and predominately Boreal Ecosystem-Atmosphere Study (BOREAS) Experiments. In February 1994 and prior to the final selection of the BOREAS study sites, a group of funded BOREAS investigators agreed to run their models with data for five community types representing the proposed tower flux sites. All participating models were given identical initial values and boundary conditions and driven with identical climate data. The objectives of the intercomparison exercise were: 1) compare simulation results of participating terrestrial, hydrological, and atmospheric models over selected time frames; 2) learn about model behavior and sensitivity to estimated boreal site and vegetation definitions; 3) prioritize BOREAS field data collection efforts supporting modeling studies; 4) identify individual model deficiencies as early as possible. Out of these objectives evolved some important coordination and science issues for the BOREAS Experiment that can be generalized to IFCs and long term archiving of the data. Some problems are acceptable because they are endemic to maintaining fair and open competition prior to the peer review process. Others are logistical and addressable through application of planning, management, and information sciences. This investigator has identified one source of measurement and model incompatibility that is manifest in the IFC scaling approach. Although intuitively obvious, scaling problems are already more formally defined in the Geography literature. An example of the scaling problem will be demonstrated with Vegetation/Ecosystem Mapping and Analysis Project (VEMAP) and OTTER data.

Coughlan, J.↗

NASA NTRS1998

Intercomparisons of Total Precipitable Water from Satellite and Other Long Term Data Sets

Global water vapor data sets from satellite (NVAP) and reanalysis (NCEP and DAO) are intercompared for a 5 year period (1988-1992). Global average indicates that the NCEP and DAO reanalyses are dryer than NVAP over much of the period. Spatial patterns of the NCEP/NVAP and DAO/NVAP differences show regional variations in the 60 month climatogical fields. For example, in the Eastern Pacific just south of the equator NVAP is much dryer than the NCEP and more moist than DAO. Rather large discrepancies exist in other regions as well. North Africa, Saudi Arabia, India, and Australia show that NVAP TPW values are more moist than the NCEP and DAO model analyses by 4-8 mm. In general, the NCEP and DAO exhibits a tendency to be dryer than NVAP over the tropical ocean region. Over the Americas little differences exist except over the west coast. The shapes of the differences fields over the Eastern Pacific region are significantly different between NCEP/NVAP and DAO/NVAP differences. Over South America and Central Africa, DAO TPW values are significantly higher than those of NVAP. These difference fields show monthly and seasonal variability as well. These results will be highlighted in the paper and on the poster.

Chang, Fong-Chiau↗

NASA NTRS2017

Intercomparison of Snow Depth Retrievals over Arctic Sea Ice from Radar Data Acquired by Operation IceBridge

Since 2009, the ultra-wideband snow radar on Operation IceBridge (OIB; a NASA airborne mission to survey the polar ice covers) has acquired data in annual campaigns conducted during the Arctic and Antarctic springs. Progressive improvements in radar hardware and data processing methodologies have led to improved data quality for subsequent retrieval of snow depth. Existing retrieval algorithms differ in the way the air-snow (a-s) and snow-ice (s-i) interfaces are detected and localized in the radar returns and in how the system limitations are addressed (e.g., noise, resolution). In 2014, the Snow Thickness On Sea Ice Working Group (STOSIWG) was formed and tasked with investigating how radar data quality affects snow depth retrievals and how retrievals from the various algorithms differ. The goal is to understand the limitations of the estimates and to produce a well-documented, long-term record that can be used for understanding broader changes in the Arctic climate system. Here, we assess five retrieval algorithms by comparisons with field measurements from two groundbased campaigns, including the BRomine, Ozone, and Mercury EXperiment (BROMEX) at Barrow, Alaska; a field program by Environment and Climate Change Canada at Eureka, Nunavut; and available climatology and snowfall from ERA-Interim (ECMWF (European Centre for Medium-Range Weather Forecasts) Re-Analysis) reanalysis. The aim is to examine available algorithms and to use the assessment results to inform the development of future approaches. We present results from these assessments and highlight key considerations for the production of a long-term, calibrated geophysical record of springtime snow thickness over Arctic sea ice.

Operation IceBridge↗

NASA NTRS1983

Lessons learned from the CSIS

A discussion is presented of the Centralized Storm Information System (CSIS), a joint effort by several organizations including NASA and the National Weather Service, which has been developed to aid the forecaster in evaluating weather data. The CSIS was developed to provide a handling, analyzing, intercomparison, and display system for real-time data from all available sources. The CSIS hardware and software, the impact of the CSIS, and the initial experience gained following the implementation of the CSIS are examined. Several general insights learned from this interactive processing system are examined in detail, including the benefits of an evolutionary bottom up rather than top down design approach, the crucial nature of scheduler function to any real time system, the recognition that meteorological interactive terminals requirements are different from image processing terminals requirements, and the knowledge that forecasters generate a large peak load on computer resources.

Mosher, F. R.↗

NASA NTRS2018

WCRP Task Team for the Intercomparison of ReAnalyses (TIRA): Motivation and Progress

Reanalyses have proven to be an important resource for weather and climate related research, as well as societal applications at large. New atmospheric reanalyses in various forms are produced every few years. In addition, land and ocean communities are producing disciplinary uncoupled reanalyses, and regional reanalyses are emerging in addition to global reanalyses. Systems of data information are being developed to facilitate the intercomparison of reanalyses among themselves and with observations and climate change experiments (e.g. CREATE-IP and WRIT). Current research and development in reanalysis is directed at (1) extending the length of reanalyzed period and (2) use of coupled Earth system models for climate reanalysis. While the World Climate Research Programme (WCRP) involvement in the reanalyses communities through its Data Advisory Council (WDAC) has been substantial, for example in organizing international conferences on reanalyses. However, these efforts have previously not included an analysis of the differences among reanalyses and their inherent uncertainties which are important questions for both users and developers of reanalyses. Therefore, the WCRP Task Team for the Intercomparison of ReAnalyses (TIRA) task team has been formed as collaborative effort to address reanalyses role in WCRP. This constitutes a logical progression that fills the needs of the community and contributes to the WCRP mission. The primary charge to TIRA is to develop a reanalysis intercomparison project plan that will attain the following objectives.1)To foster understanding and estimation of uncertainties in reanalysis data by intercomparison and other means)To communicate new developments and best practices among the reanalyses producing centers3)To enhance the understanding of data and assimilation issues and their impact on uncertainties, leading to improved reanalyses for climate assessment4)To communicate the strengths and weaknesses of reanalyses, their fitness for purpose, and best practices in the use of reanalysis datasets by the scientific communityThis contribution outlines the need for a task team on reanalyses, their intercomparison, the objectives of the team and progress thus far. Results for some pilot intercomparisons will also be discussed.

Bosilovich, Michael↗

NASA NTRS2008

Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors: Implementation, Analysis and Validation - Part 2

The evaluation of a new global monthly leaf area index (LAI) data set for the period July 1981 to December 2006 derived from AVHRR Normalized Difference Vegetation Index (NDVI) data is described. The physically based algorithm is detailed in the first of the two part series. Here, the implementation, production and evaluation of the data set are described. The data set is evaluated both by direct comparisons to ground data and indirectly through inter-comparisons with similar data sets. This indirect validation showed satisfactory agreement with existing LAI products, importantly MODIS, at a range of spatial scales, and significant correlations with key climate variables in areas where temperature and precipitation limit plant growth. The data set successfully reproduced well-documented spatio-temporal trends and inter-annual variations in vegetation activity in the northern latitudes and semi-arid tropics. Comparison with plot scale field measurements over homogeneous vegetation patches indicated a 7% underestimation when all major vegetation types are taken into account. The error in mean values obtained from distributions of AVHRR LAI and high-resolution field LAI maps for different biomes is within 0.5 LAI for six out of the ten selected sites. These validation exercises though limited by the amount of field data, and thus less than comprehensive, indicated satisfactory agreement between the LAI product and field measurements. Overall, the intercomparison with short-term LAI data sets, evaluation of long term trends with known variations in climate variables, and validation with field measurements together build confidence in the utility of this new 26 year LAI record for long term vegetation monitoring and modeling studies.

Ganguly, Sangram↗

NASA NTRS1988

Meteorological Sensor Calibration Facility

The meteorological sensor calibration facility is designed to test and assess radiosonde measurement quality through actual flights in the atmosphere. United States radiosonde temperature measurements are deficient in that they require correction for errors introduced by long- and short-wave radiation. The effect of not applying corrections results in a large bias between day time and night time measurements. This day/night bias has serious implications for users of radiosonde data, of which NASA is one. The derivation of corrections for the U.S. radiosonde is quite important. Determination of corrections depends on solving the heat transfer equation of the thermistor using laboratory measurements of the emissivity and absorptivity of the thermistor coating. The U.S. radiosonde observations from the World Meteorological Organization International Radiosonde Intercomparison were used as the data base to test whether the day/night height bias can be removed. Twenty-five noon time and 26 night time observations were used. Corrected temperatures were used to calculate new geopotentials. Day/night bias in the geopotentials decreased significantly when corrections were introduced. Some testing of thermal lag attendant with the standard carbon hygristor took place. Two radiosondes with small bead thermistors imbedded in the hygristor were flown. Detailed analysis was not accomplished; however, cursory examination of the data showed that the hygristor is at a higher temperature than the external thermistor indicates.

Schmidlin, F. J.↗

NASA NTRS1994

Comparison of upper tropospheric water vapor from GOES, Raman lidar, and Cross-chain Loran Atmospheric Sounding System measurements

Observations of upper tropospheric relative humidity obtained from Raman lidar and Cross-chain Loran Atmospheric Sounding System (CLASS) sonde instruments obtained during the First ISCCP Regional Experiment (FIRE) Cirrus-II field program are compared with satellite measurements from the GOES 6.7-micron channel. The 6.7-micron channel is sensitive to water vapor integrated over a broad layer in the upper troposphere (roughly 500-200 mbar). Instantaneous measurements of the upper tropospheric relative humidity from GOES are shown to agree to within roughly 6% of the nearest lidar observations and 9% of the nearest CLASS observations. The CLASS data exhibit a slight yet systematic dry bias in upper tropospheric humidity, a result which is consistent with previous radiosonde intercomparisons. Temporal stratification of the CLASS data indicates that the magnitude of the bias is dependent upon the time of day, suggesting a solar heating effect in the radiosonde sensor. Using CLASS profiles, the impact of vertical variability in relative humidity upon the GOES upper tropospheric humidity measurements is also examined. The upper tropospheric humidity inferred from the GOES 6.7-micron channel is demonstrated to agree to within roughly 5% of the relative humidity vertically averaged over the depth of atmosphere to which the 6.7-micron channel is sensitive. The results of this study encourage the use of satellite measurements in the 6.7-micron channel to quantitatively describe the distribution and temporal evolution of the upper tropospheric humidity field.

Soden, B. J.↗

NASA NTRS2019

Transitioning the NASA SLR Network to Event Timing Mode for Reduced Systematics, Improved Stability and Data Precision

NASA's legacy Satellite Laser Ranging (SLR) network produces about one-third of the global SLR data to support spacegeodesy. This network of globally distributed stations has been using Time Interval Units (TIU) for range measurements for thelast 25 + years. To improve the reliability of the SLR network and satisfy the need for stable millimeter precision data, a phasedreplacement of the TIUs in the network with picosecond-precise Event Timer Modules was initiated in 2015. This schemeallowed the time of flight and laser transmit epoch measurement to one picosecond resolution. For a network with globalscientific impact, transitioning to a new data generation metrological scheme requires significant data scrutiny and long-termscience data validation. Any long-term testing/measurement has the potential to interrupt the station's daily operational dataflow to the International Laser Ranging Service (ILRS) as the station under test will have to put its test data into quarantine.We have demonstrated a very effective way to test and implement the new device without removing the old hardware andwithout the need for the orbit analysis. This operationally noninvasive scheme performed concurrent test measurements enablinguninterrupted operational data flow to the users, while allowing simultaneous test data capture for short- and long-termsystematics and stability analysis. Extensive analysis of the test data was performed by the NASA SLR engineering team andthe ILRS Analysis Standing Committee, to uncover biases and any dependencies on the satellite ranges (for nonlinear scaleissues). Multi-ETM comparison was also performed at two of the SLR stations through the interchange of hardware to establishthe inter-device range biases and stability. Such benchmarked hardware was subsequently sent to the remaining stationsto allow traceability and normalize the network performance. The range bias intercomparison performed using the multiyearSLR data analysis agreed well with the engineering changes, thus validating the approach to flush out station-specific rangingsystematics affecting precise orbit determination. Such an improvement and rebalancing of the current network will allowan orderly transition of the current NASA SLR network operating at a maximum rate of 10 Hz to the NASA next generationSpace Geodesy Satellite Laser Ranging (SGSLR) network operating at 2 kHz (McGarry et al. in J Geod, 2018. https ://doi.org/10.1007/s0019 0-018-1191-6; Merkowitz et al. in J Geod, 2018. https ://doi.org/10.1007/s0019 0-018-1204-5).

Varghese, Thomas↗

NASA NTRS2015

The Agricultural Model Intercomparison and Improvement Project: Phase I Activities by a Global Community of Science

The Agricultural Model Intercomparison and Improvement Project (AgMIP) was founded in 2010. Its mission is to improve substantially the characterization of world food security as affected by climate variability and change, and to enhance adaptation capacity in both developing and developed countries. The objectives of AgMIP are to: Incorporate state-of-the-art climate, crop/livestock, and agricultural economic model improvements into coordinated multi-model regional and global assessments of future climate impacts and adaptation and other key aspects of the food system. Utilize multiple models, scenarios, locations, crops/livestock, and participants to explore uncertainty and the impact of data and methodological choices. Collaborate with regional experts in agronomy, animal sciences, economics, and climate to build a strong basis for model applications, addressing key climate related questions and sustainable intensification farming systems. Improve scientific and adaptive capacity in modeling for major agricultural regions in the developing and developed world, with a focus on vulnerable regions. Improve agricultural data and enhance data-sharing based on their intercomparison and evaluation using best scientific practices. Develop modeling frameworks to identify and evaluate promising adaptation technologies and policies and to prioritize strategies.

farm crops↗

DOE OSTI2025

Report on the Atmospheric Temperature Changes and their Drivers (ATC) Activity 2025 Spring Meeting

The Atmospheric Temperature Change and their Drivers (ATC) Activity brings together experts interested in improving understanding of atmospheric temperature variability and trends and their representation in climate data records. ATC pursues this goal by fostering intercomparisons of atmospheric temperature datasets, providing and improving uncertainty information for climate data records, comparing observations with model simulations, assessing atmospheric temperature trends and their drivers, and documenting their efforts in review papers and assessment reports. The ATC activity convened at the Wegener Center for Climate and Global Change at the University of Graz in Graz, Austria over April 23 – 25. The purpose of the meeting was to provide updates on research and datasets related to atmospheric temperature change and variability, to identify areas that need further research, and to coordinate ongoing and future collaborations. Meeting themes included theoretical and simulated controls on atmospheric temperature, the development of new and improved atmospheric temperature datasets, and analysis of atmospheric temperature variability and trends. 18 activity members attended the meeting including 12 in-person attendees and 6 remote attendees. Four new early career activity members attended with support from APARC.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1987

An intercomparison of nitrogen-containing species in Nimbus 7 LIMS and SAMS data

Odd-nitrogen chemistry and transport are analyzed using a two-dimensional model and Nimbus 7 data. The Nimbus 7 data include: measurements of O3, NO2, HNO3, H2O, and temperature by the LIMS instrument; N2O, CH4, and temperature measurements by the SAMS instrument; and O3 data from the SBUV instrument. The characteristics of the two-dimensional model used in the study, a modified Guthrie et al. (1984) model, are described. NO2 and HNO3 are calculated using the two-dimensional model, and the computed data are compared with the LIMS NO2 and HNO3 measurements. The model uncertainties are computed based on the photochemical equilibrium assumption, and the role of stratospheric dynamics in determining NO2 and HNO3 is discussed. It is observed that there is good correlation between the LIMS and model data in the upper stratosphere; however, the data do not correspond in the lower stratosphere. The effect of nitrogen sources, such as lightning, on the stratospheric odd nitrogen distribution is examined.

Jackman, Charles H.↗

NASA NTRS1998

Results of the NY-Alesund ozone measurements intercomparison NAOMI

Worldwide, about ten Differential Absorption Lidars are used for long-term monitoring of stratospheric ozone. These systems are an important component of the Network for the Detection of Stratospheric Change. Although DIALs are self-calibrating in principle, regular intercomparisons with other ozone-lidars, microwave radiometers or ozone-sondes are highly desirable to ensure high data quality at a well known level. The Network for the Detection of Stratospheric Change (NDSC) validation policy suggests that such intercomparisons be "blind", meaning all participants submit their data to an impartial referee, without seeing results from the other participants. Here we report on the "blind" intercomparison taking place from January 20th to February 10th 1998 at Ny-Alesund, Spitsbergen (78.92 deg N, 11.95 deg E). Participating groups were from the Alfred Wegener Institute, Potsdam, operating the NDSC DIAL system at Ny-Alesund, from the University of Bremen operating the NDSC microwave radiometer for ozone profiling at Ny-Alesund, and the NASA Goddard Space Flight Center group with the "NDSC travelling standard" STROZ-LITE. The first author acted as the impartial referee. Also used for the intercomparison were data from ECC-6A/Vaisala RS80 ozone sondes routinely launched at Ny-Alesund by the AWI group. A 1% KI solution (3 ml) and the 1986 ECC pump correction (1.092 at 5 hPa) are used. The ECC-data were available to all participants during the campaign and thus were not "blind". Table 1 summarizes the expected performance of the instruments participating in the ozone intercomparison reported in this paper.

Steinbrecht, W.↗

NASA NTRS2024

Scenario Setup and Forcing Data for Impact Model Evaluation and Impact Attribution Within the Third Round of the Inter-Sectoral Model Intercomparison Project (ISIMIP3a)

This paper describes the rationale and the protocol of the first component of the third simulation round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a, http://www.isimip.org, last access: 2 November 2023) and the associated set of climate-related and direct human forcing data (CRF and DHF, respectively). The observation-based climate-related forcings for the first time include high-resolution observational climate forcings derived by orographic downscaling, monthly to hourly coastal water levels, and wind fields associated with historical tropical cyclones. The DHFs include land use patterns, population densities, information about water and agricultural management, and fishing intensities. The ISIMIP3a impact model simulations driven by these observation-based climate-related and direct human forcings are designed to test to what degree the impact models can explain observed changes in natural and human systems. In a second set of ISIMIP3a experiments the participating impact models are forced by the same DHFs but a counterfactual set of atmospheric forcings and coastal water levels where observed trends have been removed. These experiments are designed to allow for the attribution of observed changes in natural, human, and managed systems to climate change, rising CH 4 and CO 2 concentrations, and sea level rise according to the definition of the Working Group II contribution to the IPCC AR6.

Inter Sectoral Impact Model Intercomparison Projec↗