This dataset contains change factors for the 2- to 100-year daily (24-hour) extreme rainfall storms for the Continental United States from publicly available downscaled climate projections, namely BCCAv.2, LOCA, MACA and NA-CORDEX data sets. Change factors were estimated as the ratio between the historical (period between1950-2005) climate simulations of extreme rainfall and the future (period between 2044-2099) climate simulations of rainfall depths corresponding to the average recurrence interval (e.g. 2-, 5-year). These change factors were computed using the Generalized Extreme Value Distribution, which is widely used to describe rainfall extremes.
This data archive was prepared as part of the outputs of the published article Lopez‐Cantu, T., Prein, A. F., & Samaras, C. (2020). Uncertainties in Future U.S. Extreme Precipitation from Downscaled Climate Projections. Geophysical Research Letters. https://doi.org/10.1029/2019GL086797. When using the data in this archive, citation must be given to the original article.

QGIS file to visualise and analyse climate change risk data and cluster analysis results for Southeast Asian island communities

Town Brook watershed, Catskills, New York. SWATWB was also tested on the Town Brook watershed (Figure 2) in the USA, a 37 km2 sub-catchment of the Cannonsville reservoir basin. The region is typified by steep-to-moderate hillslopes of glacial origins with shallow permeable soils, underlain by a restrictive layer. The climate is humid with an average annual temperature of 8 ¢XC and average annual precipitation of 1123 mm. Elevation in the watershed ranges from 493 to 989 m above mean sea level. The slopes are quite steep with a maximum of 91%, and a mean of 21%. Soils are mainly silt loam or silty clay loam with soil hydrological group C ratings (USDA–NRCS, 2000). Soil depth ranges from less than 50 cm to greater than 1 m and is underlain by a fragipan restricting layer (e.g. coarse-loamy, mixed, active, mesic, to frigid Typic Fragiudepts, Lytic or Typic Dystrudepts common to glacial tills) (Schneiderman et al., 2002). The lowland portion of the watershed is predominantly agricultural, consisting of pasture and row crops (20%) or shrub land (18%), whereas the upper slopes are forested (60%). Water and wetlands comprise 2%. Impervious surfaces occupy

Engineering Climate Datasets encompasses Intensity-Duration-Frequency IDF Files, Canadian Weather Energy and Engineering Datasets CWEEDS , and Canadian Weather Year For Energy Calculation CWEC . IDF tabulates and graphs short-duration rainfall statistics across 563 locations in Canada. CWEEDS is a computer dataset of hourly conditions at specific locations, including data from 1953 until 2005. It also includes long term weather records used in urban planning and green building design, as well as estimates of hourly solar radiation amounts. CWEC datasets are created by combining 12 "Typical Meteorological Months" selected from a database of, usually, 30 years of data. Months are chosen by comparing individual means with long term monthly means for daily global radiation, mean, minimum and maximum DB temperature, mean, minimum and maximum dew point temperature, and mean and maximum wind speed.

Geoengineering by stratospheric aerosol injection has been proposed as a policy response to warming from human emissions of greenhouse gases, but it may produce unequal regional impacts. We present a simple, intuitive risk-based framework for classifying these impacts according to whether geoengineering increases or decreases the risk of substantial climate change, with further classification by the level of existing risk from climate change from increasing carbon dioxide concentrations. This framework is applied to two climate model simulations of geoengineering counterbalancing the surface warming produced by a quadrupling of carbon dioxide concentrations, with one using a layer of sulphate aerosol in the lower stratosphere, and the other a reduction in total solar irradiance. The solar dimming model simulation shows less regional inequality of impacts compared with the aerosol geoengineering simulation. In the solar dimming simulation, 10% of the Earth's surface area, containing 10% of its population and 11% of its gross domestic product, experiences greater risk of substantial precipitation changes under geoengineering than under enhanced carbon dioxide concentrations. In the aerosol geoengineering simulation the increased risk of substantial precipitation change is experienced by 42% of Earth's surface area, containing 36% of its population and 60% of its gross domestic product.

Overview of climate change risk data for Southeast Asian islands considered in the doctoral research.

A data set of simulated hydrologic fluxes and states from the Variable Infiltration Capacity (VIC) model, gridded to a 1/16 degree (~6km) resolution that spans the entire country of Mexico, the conterminous U.S. (CONUS), and regions of Canada south of 53 degrees N for the period 1950-2013. Because of the consistent gridding methodology, the current product reduces transboundary discontinuities making it suitable for estimating large-scale hydrologic phenomena.

The U.S. water supply and carbon sequestration are increasingly threatened by future climate change and air pollution. This study investigates the ecohydrological responses to the individual and combined impacts of climate change and anthropogenic emission changes at two spatial scales by coupling a regional online-coupled meteorology and chemistry model (WRF-Chem) and a water balance model (WaSSI). Combined effects of climate change and anthropogenic emission changes in 2046-2055 relative to 2001-2010 over the US enhance hydrological cycle and carbon sequestration. However, a drying trend occurs in the central and part of the western U.S. Climate change is projected to dominate the ecohydrological changes in most regions. Anthropogenic emission changes under 2001-2010 climate conditions cools down inland water resource regions with 0.01~0.15℃, moisturizes the east and dry the west U.S. More stringent anthropogenic emission control enhances precipitation and ecosystem production in the east and west but has an opposite trend in the central U.S. The ecohydrological modeling in California and North Carolina based on 4-km resolution meteorological data in 2050 and 2005 shows varying changes in magnitudes and spatial patterns compared to results based on 36-km resolution meteorological data. Projected changes in air pollutant emissions may accelerate climatic warming in coastal areas and the state of New Mexico and decrease precipitation, runoff, and carbon sequestration in part of the western U.S. Strategies to address future possible problems such as heatwaves, water stress, and ecosystem productivity should consider the varying interplay between air quality control and climate change at different spatial scales.

*Percent change at Lee's Ferry, the outlet of the Upper Colorado River Basin.

Seven appendices mentioned in the article "Guidelines for a Participatory Smart City Model to Address Amazon's Urban Environmental Problems." Appendix 1 – Questionnaire to consult Manaus´s City Hall Managers Appendix 2 – Questionnaire formulated to consult Manaus´s citizens Appendix 3 - International ranking and statistics used to identify the 25 Best Benchmark Smart Cities Appendix 4 – Table A1 Example of Enablers that support Smart Cities Appendix 5 – Table A2 Profile of Twenty-Five Benchmark Smart Cities Appendix 6 - Answer from Manaus City Hall to questions of Appendix 1 Appendix 7 - VIII Quality Management Subject (Public Call Simulation)

This dataset presents supercritical CO2 (scCO2) dissolution into brine in a Bentheimer sandstone core imaged via X-ray micro-computed tomography, and it is expected that the dataset will contribute to better understanding of dissolution trapping in geologic carbon sequestration. The dissolution experiment was conducted in a high-pressure, high-temperature system built in-house at the National Laboratory for X-ray Micro Computed Tomography (CTLab)’ based at Research School of Physics, the Australian National University (ANU) under experimental conditions relevant to geologic carbon sequestrations at 45 degrees Celsius and 1250 PSI. Initially, scCO2 was trapped in the pore space of the Bentheimer sandstone (porosity equals 0.20) after cycles of drainage-imbibition experiments. In the subsequent dissolution experiment presented in this dataset, fresh brine with no dissolved CO2 was injected from the bottom to the top of the core at volumetric flow rate equals 0.02 ml/min, equivalent to interstitial velocity of 1.5E-5 m/s, to investigate dissolution of the trapped scCO2 into brine. The tomographic data (not included in this dataset; acquired in 2020) were acquired simultaneously as brine was injected via the helical scanning trajectory. Acquisition time for each scan was approximately 30 min, with the resultant voxel size equaling 19.47176 micron. The tomographic data were digitally registered to the high-resolution tomographic data acquired before the dissolution experiment for alignment of pore features and the trapped scCO2 phase, with the voxel size of the 9 resultant registered dissolution scans presented in this dataset (d1-9) equaling 3.923732 micron. The size of the cropped cylindrical sample is 2421 voxel (9.50 mm) in diameter and 4428 voxel (17.37 mm) in height. Identification of the physical phases in this study was accomplished via aConverging Active Contours' (CAC) routine based on the intensity histogram of the tomographic images of the dissolution scans, where the scCO2 phase and the combined brine-and-solid phase were determined based on the intensity histogram of the tomographic images of the dissolution scans; the partially segmented images were then overlaid with the segmented dry scan to produce the finalized three-phase segmented images, where voxels labeled 1 represent the solid sandstone phase, 2 the brine phase, and 3 the scCO2 phase. Subsequent noise reduction measure includes relabeling scCO2 clusters smaller than 234 voxels (equivalent to sphere of radius 15 micron) as brine and relabeling floating grain in the scCO2 phase as scCO2. The initial scCO2 saturation in d1 was 11.9%, and remained unchanged in d2 with mobilization of scCO2 clusters observed between the scans. The scCO2 saturation decreased monotonically in subsequent scans, reaching 1.2% in d9. Please refer to the following publication for experimental details: R. Huang, A.L. Herring and A. Sheppard, Investigation of supercritical CO2 mass transfer in porous media using X-ray micro-computed tomography. Advances in Water Resources (2022), doi: https://doi.org/10.1016/j.advwatres.2022.104338. Data are in .nc format and can be read in ImageJ software via NetCDF plugins (http://www.unidata.ucar.edu/software/netcdf/).

Report about climate change in the Southern and Southwestern Flatlands West NRM region of Australia, focused on Albany Port.

This report was created in reference to Albany Port (AUALH), located in the ABC NRM region Southern and Southwestern Flatlands West. The report is composed of Ports Australia data, CSIRO & BoM trend data, measurements from ACORN-SAT stations, CSIRO future data, CMAR future data, and Jane Mullett's personal analysis.

Climate Smart Seaports is an online decision support toolkit designed to help Australian seaports adapting to climate change and improving their resilience to it. The toolkit lets users access data from various datasets such as CSIRO, BoM, ABS, BITRE as well as their own personal data. Climate Smart Seaports then allows writing and publishing reports based on this data and the user analysis.

Report about climate change in the Southern Slopes Vic East NRM region of Australia, focused on Lakes Entrance.

This report was created in reference to Lakes Entrance (AUBSJ), located in the ABC NRM region Southern Slopes Vic East. The report is composed of CSIRO & BoM trend data, CMAR future data, Jane Mullett's custom data, Jane Mullett's personal analysis. It has been created by Jane Mullett using the Climate Smart Seaports tool.

Climate Smart Seaports is an online decision support toolkit designed to help Australian seaports adapting to climate change and improving their resilience to it. The toolkit lets users access data from various datasets such as CSIRO, BoM, ABS, BITRE as well as their own personal data. Climate Smart Seaports then allows writing and publishing reports based on this data and the user analysis.

Towards the reproducibility in soil erosion modelling:
a new Pan-European soil erosion map
Claudio Bosco ¹, Daniele de Rigo ¹ ² , Olivier Dewitte ¹, Luca Montanarella ¹

¹ European Commission, Joint Research Centre, Institute for Environment and Sustainability,
Via E. Fermi 2749, I-21027 Ispra (VA), Italy
² Politecnico di Milano, Dipartimento di Elettronica e Informazione,
Via Ponzio 34/5, I-20133 Milano, Italy
Soil erosion by water is a widespread phenomenon throughout Europe and has the potentiality, with his on-site and off-site effects, to affect water quality, food security and floods. Despite the implementation of numerous and different models for estimating soil erosion by water in Europe, there is still a lack of harmonization of assessment methodologies. Often, different approaches result in soil erosion rates significantly different. Even when the same model is applied to the same region the results may differ. This can be due to the way the model is implemented (i.e. with the selection of different algorithms when available) and/or to the use of datasets having different resolution or accuracy. Scientific computation is emerging as one of the central topic of the scientific method, for overcoming these problems there is thus the necessity to develop reproducible computational method where codes and data are available. The present study illustrates this approach. Using only public available datasets, we applied the Revised Universal Soil loss Equation (RUSLE) to locate the most sensitive areas to soil erosion by water in Europe. A significant effort was made for selecting the better simplified equations to be used when a strict application of the RUSLE model is not possible. In particular for the computation of the Rainfall Erosivity factor (R) the reproducible research paradigm was applied. The calculation of the R factor was implemented using public datasets and the GNU R language. An easily reproducible validation procedure based on measured precipitation time series was applied using MATLAB language. Designing the computational modelling architecture with the aim to ease as much as possible the future reuse of the model in analysing climate change scenarios is also a challenging goal of the research.

References
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Office for Official Publications of the European Communities, Luxembourg. EUR 17729 EN [6] Farr, T. G., Rosen, P A., Caro, E., Crippen, R., Duren, R., Hensley, S., Kobrick, M., Paller, M., Rodriguez, E., Roth, L., Seal, D., Shaffer, S., Shimada, J., Umland, J., Werner, M., Oskin, M., Burbank, D., Alsdorf, D., 2007. The Shuttle Radar Topography Mission. Review of Geophysics 45, RG2004, DOI:10.1029/2005RG000183 [7] Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P. D., and New, M., 2008. A European daily high-resolution gridded dataset of surface temperature and precipitation. Journal of Geophysical Research 113, (D20) D20119+ DOI:10.1029/2008jd010201 [8] Renard, K. G., Foster, G. R., Weesies, G. A., McCool, D. K., and Yoder, D. C., 1997. Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE). Agriculture handbook 703. US Dept Agric., Agr. Handbook, 703 [9] Bosco, C., Rusco, E., Montanarella, L., Panagos, P., 2009. Soil erosion in the alpine area: risk assessment and climate change. Studi Trentini di scienze naturali 85, 119-125 [10] Bosco, C., Rusco, E., Montanarella, L., Oliveri, S., 2008. Soil erosion risk assessment in the alpine area according to the IPCC scenarios. In: Tóth, G., Montanarella, L., Rusco, E. (Eds.), Threats to Soil Quality in Europe. No. EUR 23438 EN in EUR - Scientific and Technical Research series. Office for Official Publications of the European Communities, pp. 47-58 [11] de Rigo, D. and Bosco, C., 2011. Architecture of a Pan-European Framework for Integrated Soil Water Erosion Assessment. IFIP Advances in Information and Communication Technology 359 (34), 310-31. DOI:10.1007/978-3-642-22285-6_34 [12] Bosco, C., de Rigo, D., Dewitte, O., and Montanarella, L., 2011. Towards a Reproducible Pan-European Soil Erosion Risk Assessment - RUSLE. Geophys. Res. Abstr. 13, 3351 [13] Bollinne, A., Laurant, A., and Boon, W., 1979. L’érosivité des précipitations a Florennes. Révision de la carte des isohyétes et de la carte d’erosivite de la Belgique. Bulletin de la Société géographique de Liége 15, 77-99 [14] Ferro, V., Porto, P and Yu, B., 1999. A comparative study of rainfall erosivity estimation for southern Italy and southeastern Australia. Hydrolog. Sci. J. 44 (1), 3-24. DOI:10.1080/02626669909492199 [15] de Santos Loureiro, N. S. and de Azevedo Coutinho, M., 2001. A new procedure to estimate the RUSLE EI30 index, based on monthly rainfall data and applied to the Algarve region, Portugal. J. Hydrol. 250, 12-18. DOI:10.1016/S0022-1694(01)00387-0 [16] Rogler, H., and Schwertmann, U., 1981. Erosivität der Niederschläge und Isoerodentkarte von Bayern (Rainfall erosivity and isoerodent map of Bavaria). Zeitschrift fur Kulturtechnik und Flurbereinigung 22, 99-112 [17] Nearing, M. A., 1997. A single, continuous function for slope steepness influence on soil loss. Soil Sci. Soc. Am. J. 61 (3), 917-919. DOI:10.2136/sssaj1997.03615995006100030029x [18] Morgan, R. P C., 2005. Soil Erosion and Conservation, 3rd ed. Blackwell Publ., Oxford, pp. 304 [19] Šúri, M., Cebecauer, T., Hofierka, J., Fulajtár, E., 2002. Erosion Assessment of Slovakia at regional scale using GIS. Ecology 21 (4), 404-422 [20] Cebecauer, T. and Hofierka, J., 2008. The consequences of land-cover changes on soil erosion distribution in Slovakia. Geomorphology 98, 187-198. DOI:10.1016/j.geomorph.2006.12.035 [21] Poesen, J., Torri, D., and Bunte, K., 1994. Effects of rock fragments on soil erosion by water at different spatial scales: a review. Catena 23, 141-166. DOI:10.1016/0341-8162(94)90058-2 [22] Wischmeier, W. H., 1959. A rainfall erosion index for a universal Soil-Loss Equation. Soil Sci. Soc. Amer. Proc. 23, 246-249 [23] Iverson, K. E., 1980. Notation as a tool of thought. Commun. ACM 23 (8), 444-465. DOI:10.1145/358896.358899 [24] Quarteroni, A., Saleri, F., 2006. Scientific Computing with MATLAB and Octave. Texts in Computational Science and Engineering. Milan, Springer-Verlag [25] The MathWorks, 2011. MATLAB. http://www.mathworks.com/help/techdoc/ref/ [26] Eaton, J. W., Bateman, D., and Hauberg, S., 2008. GNU Octave Manual Version 3. A high-level interactive language for numerical computations. Network Theory Limited, ISBN: 0-9546120-6-X [27] de Rigo, D., 2011. Semantic Array Programming with Mastrave - Introduction to Semantic Computational Modeling. The Mastrave project. http://mastrave.org/doc/MTV-1.012-1 [28] de Rigo, D., (exp.) 2012. Semantic array programming for environmental modelling: application of the Mastrave library. In prep. [29] Bosco, C., de Rigo, D., Dewitte, O., Poesen, J., Panagos, P.: Modelling Soil Erosion at European Scale. Towards Harmonization and Reproducibility. In prep. [30] R Development Core Team, 2005. R: A language and environment for statistical computing. R Foundation for Statistical Computing. [31] Stallman, R. M., 2009. Viewpoint: Why “open source” misses the point of free software. Commun. ACM 52 (6), 31–33. DOI:10.1145/1516046.1516058 [32] de Rigo, D. 2011. Multi-dimensional weighted median: the module "wmedian" of the Mastrave modelling library. Mastrave project technical report. http://mastrave.org/doc/mtv_m/wmedian [33] Shakesby, R. A., 2011. Post-wildfire soil erosion in the Mediterranean: Review and future research directions. Earth-Science Reviews 105 (3-4), 71-100. DOI:10.1016/j.earscirev.2011.01.001 [34] Zuazo, V. H., Pleguezuelo, C. R., 2009. Soil-Erosion and runoff prevention by plant covers: A review. In: Lichtfouse, E., Navarrete, M., Debaeke, P Véronique, S., Alberola, C. (Eds.), Sustainable Agriculture. Springer Netherlands, pp. 785-811. DOI:10.1007/978-90-481-2666-8_48

Observed rainfall data (1952–2004) and predicted rainfall data (2052–2100).

Changes in the glacier areas from 1966 to 2010 in the Tuanjiefeng region, Qilian Mountain, China.

The GPM Ground Validation Campaign Reports IPHEx dataset provides various reports from the Integrated Precipitation and Hydrology Experiment (IPHEx) which took place from March 6, 2014 to June 16, 2014 in the southern Appalachian Mountains in the eastern United States. The goal of the IPHEx campaign was to collect data that could aid in the development, evaluation, and improvement of remote sensing precipitation algorithms in support of the GPM mission Reports included in this dataset are for the Mission Scientist, Instrument Scientists, and also include Weather Forecasts. Many reports have additional information included as attachments.

In the western United States, the Sierra Nevada region experienced decades of fire suppression-driven changes in forest structure and composition, resulting in increased vulnerability to drought, water stress, tree mortality, and exposure to severe wildfires. Sierra Nevada’s watersheds and forests are predicted to undergo warmer and drier conditions due to climate change, making them even more vulnerable to disturbances. Restoring forests by reducing forest density and fuel accumulation has the potential to improve forest resilience to droughts and climate change, increase water availability, and provide other ecosystem benefits. In this study, we investigated the individual and compounding effects of forest treatments on evapotranspiration and streamflow in the upper Kings River basin under different warming scenarios using the SWAT+ model. We simulated large-scale forest treatments throughout the landscape to evaluate the hydrological response to warming across a water-energy gradient and the extent to which forest treatments can offset the warming-driven response. Warming increased evapotranspiration in energy-limited forests, while in water-limited forests, evapotranspiration declined due to increased water stress. The water made available through biomass reduction due to forest treatments was directed towards increasing potential runoff or sustaining the remaining trees by providing additional water for evapotranspiration, controlled by water/energy availability. We found that large-scale forest restoration in the upper Kings River basin has the potential to partially mitigate warming impacts on streamflow by a maximum of 48% and 36% under +1.5°C and +3.0°C warming, respectively, thus reducing the severity of warming impacts on streamflow and vegetation water stress. These benefits are most prominent in the first year following forest treatment and gradually decline over time, persisting up to 10 years.

Radar ranges: near, standard. Max rain level: weak rain. Parent item: IDRA weather radar measurements - month 2009-07 Measuring instrument: IDRA atmospheric radar in CESAR observatory, Cabauw IRCTR has built a high resolution radar system, IDRA (IRCTR Drizzle Radar), aimed at the detailed observation of the spatial and temporal distribution of rainfall and drizzle. The system was placed at the end of August 2007 on top of a 213 m high meteorological tower in the CESAR (Cabauw Experimental Site for Atmospheric Research) observatory in Cabauw, The Netherlands. This location has several advantages: In the first place, an increased sensitivity due to the reduction of the influence of ground clutter. Secondly, it allows direct observation of the horizontal distribution of low level clouds and fog. Finally, the presence of other instruments in the vicinity enhances the understanding of the physical processes in the atmosphere by synergistically combining their measurements. Data from other instruments at CESAR are available at {http://www.cesar-database.nl}. IDRA provides the horizontal distribution of reflectivity, mean Doppler velocity, Doppler spectrum width and polarimetric parameters like differential reflectivity, linear depolarization ratio or specific differential phase. The data collected is freely available to the scientific community.

Scientific Personnel V. E. Romanovsky, S. S. Marchenko, R.R. Muskett

Partner Organizations:

Alaska Ecoscience, USA

Alfred Wegener Institute, Germany

Centre d'etudes Nordiques, Department de Geographie, Universite Laval, Quebec, Canada

Danish Meteorological Institute, Denmark

Institute of Earth Cryosphere, Russia

Institute of Northern Engineering, UAF

Interdisciplinary Centre on Climate Change and Department of Geography & Environmental Management, University of Waterloo, Canada

International Arctic Research Center, UAF

International Permafrost Association, USA

Melinkov Permafrost Institute, Russia

Moscow Institute of Geography, Russia Academy of Sciences

National Center for Atmospheric Research, USA

NASA Goddard Space Flight Center, USA

Scenarios Network for Alaska Planning (SNAP), UAF

Stokholm University, Sweden

University of Delaware, USA

University of New Hampshire, USA

Water Environment Research Center, UAF

Local Collaborators: Jorgenson, M.T., Alaska Ecoscience, AK

Kholodov, A.L., Geophysical Institute, UAF

Daanen, R., Institute of Northern Engineering, UAF

Kanevskiy M., Institute of Northern Engineering, UAF

Shur, Y., Institute of Northern Engineering, UAF

Walsh, J., International Arctic Research Center, UAF

Fresco, N., Scenarios Network for Alaska Planning, School of Natural Resources & Agricultural Sciences, UAF

Rupp, S., Scenarios Network for Alaska Planning, School of Natural Resources & Agricultural Sciences, UAF

Walter-Anthony, K., Water Environmental Research Center, UAF

International Collaborators: Christensen, J., Danish Meteorological Institute, Denmark

Comiso, J., NASA Goddard Space Flight Center, Oceans and Ice Branch, USA

Duguay, C. R., University of Waterloo, Canada

Frolking, S., Institute for the Study of Earth, Oceans and Space, University of New Hampshire, USA

Georgiadi, A., Moscow Institute of Geography, Russian Academy of Sciences

Groisman, P., National Climatic Data Center, USA

Hachem, S., Université Laval, Québec, Canada

Hubberten, H.-W., Alfred Wegener Institute, Potsdam, Germany

Harden Jennifer, US Geological Survey, Menlo Park, CA, USA

Kattsov, V., Voeikov Main Geophysical Observatory, Russia

Kuhry, P., Stockholm University, Sweden

Lawrence, D., National Center for Atmospheric Research, USA

Malkova, G., Institute of Earth Cryosphere, Russia

Pavlova, T., Voeikov Main Geophysical Observatory, Russia

Rawlins, M., University of New Hampshire, USA

Rinke, A., Alfred Wegener Institute, Potsdam, Germany

Romanovskii, N., Moscow State University, Russia

Saito, K., Japan Agency for Marine-Earth Science Technology, Japan

Shiklomanov, N., University of Delaware, USA

Shiklomanov, A., University of New Hampshire, USA

Shkolnik, I.M., Voeikov Main Geophysical Observatory, Russia

Schirrmeister L, Alfred Wegener Institute, Potsdam, Germany

Schuur A.G. Edward, University of Florida, Gainesville, FL, USA

Stendel, M., Danish Meteorological Institute, Denmark

Wisser, D., Institute for the Study of Earth, Oceans and Space, University of New Hampshire, USA

Zheleznyak, M., Melnikov Permafrost Institute, Russia

Funding: NSF Grants OPP ARC-0652838 [ARC-0520578 and ARC-0632400]

NASA (NNOG6M48G), Alaska EPSCoR (NSF)

The State of Alaska

Study Sites Permafrost Freshwater Interactions

Alaska, Canada, Russia

Permafrost Observatories?Thermal state of permafrost in Russia and Central Asia

Permafrost Freshwater Interactions Project continues investigations began during the Thermal State of Permafrost (TSP) Project with renewed and expanded collaboration. Our efforts focus and expand on permafrost and hydrology changes through geophysical modeling and remote sensing (satellite geodesy). During TSP in cooperation with above mentioned Russian partners a large number of existing boreholes have been identified for possible measurements (candidate sites). Many of these have metadata files on the IPA coordinated GTN-P website. Additional sites will be added to the web site. New boreholes over the next several years are planned. A total of 320 boreholes, located in Russia, Kazakhstan, and Mongolia were considered from the point of view of possibility for continuous geothermal observations (see Figure). Boreholes cover all types of permafrost, from continuous to sporadic, both on the plains and in the mountains. Active (sites where regular observations were carried out recently and are intended to continue in the future), candidate (where equipment for long-term observations can be installed soon), potential (equipment for long-term observation is planned to be installed during the project) and historical (there are some existing data but now these sites are unavailable for observations for different reasons) boreholes were selected. In order to standardize all investigations within the framework of the Project the “Manual for monitoring and reporting temperature data in permafrost boreholes” was developed. It allows better standardized collection, handling and interpretation of obtained data. In the Protocol two types of observation strategies are proposed: Type 1: Long-term high-frequency (hourly to daily) continuous observations in the limited number of key boreholes, which are representative of a given regions (note: these more frequent observations are desirable to depths of 15-20 meters); Type 2: Occasional or periodical measurements in the other available and deeper boreholes (if possible annual or more frequently). As a minimum, and based primarily on cost considerations for the IPY-TSP program, the use of HOBO U12 4-External Channel Data Loggerswith temperature sensors TMC-HD are proposed. At the same time, individual participants can employ other types of loggers and/or thermal cables (chains) with similar sensor characteristics.

Research Goals The goal of our research is to obtain a deeper understanding of the temporal (interannual and decadal time scales) and spatial (north to south and west to east) variability and trends in the permafrost temperatures and physical changes (such as talik and the active layer) in the North of Eurasia and Alaska to develop more reliable predictive capabilities for the projection of these changes into the 21st century. We are employing ground datasets from the global permafrost temperature networks, global positioning system sites of the International Terrestrial Reference Frame organization, together with satellite-derived datasets of physical parameters such as land-surface temperature, gravity field changes, river runoff and snow water equivalent to name a few. Our modeling efforts employ the Geophysical Institute Permafrost Models (GIPL) and Geophysical Inverse Potential Field Theory.