scholarly journals Greenland liquid water runoff from 1979 through 2017

2020 ◽  
Author(s):  
Kenneth D. Mankoff ◽  
Andreas P. Ahlstrøm ◽  
William Colgan ◽  
Robert S. Fausto ◽  
Xavier Fettweis ◽  
...  
Keyword(s):  
Time Series ◽  
Liquid Water ◽  
Input Data ◽  
Climate Models ◽  
Volume Flow Rate ◽  
Sensitivity Study ◽  
Water Volume ◽  
Daily Maximum ◽  
Water Runoff ◽  
Runoff Water

Abstract. We provide high-resolution datasets of Greenland hydrologic outlets, basins, and streams, and a 1979 through 2017 time series of Greenland liquid water runoff for each outlet. Outlets, basins, and streams are derived from traditional hydrologic routing algorithms over the surface of a 100 m ArcticDEM digital elevation model (DEM) twice: Once to the ice margin and once to the coast. We then partition liquid water runoff from both ice and land from two regional climate models (RCMs; MAR and RACMO) into each basin and at each outlet location. The data include 18903 ice basins and outlets (614 basins greater than 10 km2), 30241 land basins and outlets (958 basins greater than 10 km2), major streams in each basin, and daily runoff water volume flow rate at each outlet from each of two RCMs. We perform a sensitivity study of outlet location change for every ice sheet location over a range of hydrologic routing assumptions and data sets. Annual runoff from the ice ranges from ~136 km3 in 1992 to ~785 km3 in 2012. Daily maximum ice runoff from one basin is as large as 4380 m3 s−1. Both ice runoff magnitude and variability increase over the time series. Land runoff contributes an additional ∼ 35 % to the ice runoff. Comparison with 9 basins instrumented with stream gauges shows a range of (dis)agreement from poor to excellent between our estimated discharge and observations. As part of the journal’s living archive option, and our goal to make an operational product, all input data, code, and results from this study will be updated as needed (when new input data are available, as new features are added, or to fix bugs) and made available at https://doi.org/10.22008/promice/data/freshwater_runoff/v01 (Mankoff, 2020) and at http://github.com/mankoff/freshwater.

scholarly journals Greenland liquid water discharge from 1958 through 2019

2020 ◽  
Vol 12 (4) ◽  
pp. 2811-2841 ◽  
Author(s):  
Kenneth D. Mankoff ◽  
Brice Noël ◽  
Xavier Fettweis ◽  
Andreas P. Ahlstrøm ◽  
William Colgan ◽  
...  
Keyword(s):  
Liquid Water ◽  
Climate Models ◽  
Prediction Interval ◽  
Water Discharge ◽  
Regional Climate ◽  
Sensitivity Study ◽  
Biological Properties ◽  
Discharge Data ◽  
Basin Scale ◽  
Daily Discharge

Abstract. Greenland runoff, from ice mass loss and increasing rainfall, is increasing. That runoff, as discharge, impacts the physical, chemical, and biological properties of the adjacent fjords. However, where and when the discharge occurs is not readily available in an open database. Here we provide data sets of high-resolution Greenland hydrologic outlets, basins, and streams, as well as a daily 1958 through 2019 time series of Greenland liquid water discharge for each outlet. The data include 24 507 ice marginal outlets and upstream basins and 29 635 land coast outlets and upstream basins, derived from the 100 m ArcticDEM and 150 m BedMachine. At each outlet there are daily discharge data for 22 645 d – ice sheet runoff routed subglacially to ice margin outlets and land runoff routed to coast outlets – from two regional climate models (RCMs; MAR and RACMO). Our sensitivity study of how outlet location changes for every inland cell based on subglacial routing assumptions shows that most inland cells where runoff occurs are not highly sensitive to those routing assumptions, and outflow location does not move far. We compare RCM results with 10 gauges from streams with discharge rates spanning 4 orders of magnitude. Results show that for daily discharge at the individual basin scale the 5 % to 95 % prediction interval between modeled discharge and observations generally falls within plus or minus a factor of 5 (half an order of magnitude, or +500 %/-80 %). Results from this study are available at https://doi.org/10.22008/promice/freshwater (Mankoff, 2020a) and code is available at http://github.com/mankoff/freshwater (last access: 6 November 2020) (Mankoff, 2020b).

scholarly journals Models of Gully Erosion by Water

Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3293
Author(s):  
Aleksey Sidorchuk
Keyword(s):  
Time Series ◽  
Dynamic Model ◽  
Land Management ◽  
Surface Runoff ◽  
Model Calibration ◽  
Input Data ◽  
Gully Erosion ◽  
Water Runoff ◽  
Erosion Risk ◽  
Maximum Surface

The type of modelling of gully erosion for the projects of land management depend on the targets and degree of details of these projects, as well as on the availability of input data. The set of four models cover a broad range of possible applications. The most detailed information about predicted gullies, change of their depth, width, and volume throughout the gully lifetime is obtained with the gully erosion and thermoerosion dynamic model. The calculation requires the time series of surface runoff, catchment relief, and lithology and the complex of coefficients and parameters, some of which can be estimated only by model calibration on the measurements. The difficulty in obtaining some of these coefficients makes it necessary to use less complicated models. The stable gully model predicts final gully depths and widths and is useful for projects where only stable gully geometry is used. The modified area–slope approach is used in the two simplest models, where the position on the slopes of possible gullies is calculated without details of the gully geometry. One of these models calculates total erosion potential, taking into account all water runoff transforming a gully. The second calculates gully erosion risk, using the information about slope inclination, contributing area and maximum surface runoff.

scholarly journals A model sensitivity study of the impact of clouds on satellite detection and retrieval of volcanic ash

2015 ◽  
Vol 8 (5) ◽  
pp. 1935-1949 ◽  
Author(s):  
A. Kylling ◽  
N. Kristiansen ◽  
A. Stohl ◽  
R. Buras-Schnell ◽  
C. Emde ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Liquid Water ◽  
Volcanic Ash ◽  
Spectral Band ◽  
Sensitivity Study ◽  
Transfer Model ◽  
Mass Loading ◽  
Ice Clouds ◽  
Medium Range Weather Forecast ◽  
The Impact

Abstract. Volcanic ash is commonly observed by infrared detectors on board Earth-orbiting satellites. In the presence of ice and/or liquid-water clouds, the detected volcanic ash signature may be altered. In this paper the sensitivity of detection and retrieval of volcanic ash to the presence of ice and liquid-water clouds was quantified by simulating synthetic equivalents to satellite infrared images with a 3-D radiative transfer model. The sensitivity study was made for the two recent eruptions of Eyjafjallajökull (2010) and Grímsvötn (2011) using realistic water and ice clouds and volcanic ash clouds. The water and ice clouds were taken from European Centre for Medium-Range Weather Forecast (ECMWF) analysis data and the volcanic ash cloud fields from simulations by the Lagrangian particle dispersion model FLEXPART. The radiative transfer simulations were made both with and without ice and liquid-water clouds for the geometry and channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The synthetic SEVIRI images were used as input to standard reverse absorption ash detection and retrieval methods. Ice and liquid-water clouds were on average found to reduce the number of detected ash-affected pixels by 6–12%. However, the effect was highly variable and for individual scenes up to 40% of pixels with mass loading >0.2 g m−2 could not be detected due to the presence of water and ice clouds. For coincident pixels, i.e. pixels where ash was both present in the FLEXPART (hereafter referred to as "Flexpart") simulation and detected by the algorithm, the presence of clouds overall increased the retrieved mean mass loading for the Eyjafjallajökull (2010) eruption by about 13%, while for the Grímsvötn (2011) eruption ash-mass loadings the effect was a 4% decrease of the retrieved ash-mass loading. However, larger differences were seen between scenes (standard deviations of ±30 and ±20% for Eyjafjallajökull and Grímsvötn, respectively) and even larger ones within scenes. The impact of ice and liquid-water clouds on the detection and retrieval of volcanic ash, implies that to fully appreciate the location and amount of ash, hyperspectral and spectral band measurements by satellite instruments should be combined with ash dispersion modelling.

scholarly journals Joint Occurrence of Daily Temperature and Precipitation Extreme Events over Canada

2014 ◽  
Vol 53 (9) ◽  
pp. 2148-2162 ◽  
Author(s):  
Bárbara Tencer ◽  
Andrew Weaver ◽  
Francis Zwiers
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Negative Consequences ◽  
Temperature And Precipitation ◽  
Joint Occurrence

AbstractThe occurrence of individual extremes such as temperature and precipitation extremes can have a great impact on the environment. Agriculture, energy demands, and human health, among other activities, can be affected by extremely high or low temperatures and by extremely dry or wet conditions. The simultaneous or proximate occurrence of both types of extremes could lead to even more profound consequences, however. For example, a dry period can have more negative consequences on agriculture if it is concomitant with or followed by a period of extremely high temperatures. This study analyzes the joint occurrence of very wet conditions and high/low temperature events at stations in Canada. More than one-half of the stations showed a significant positive relationship at the daily time scale between warm nights (daily minimum temperature greater than the 90th percentile) or warm days (daily maximum temperature above the 90th percentile) and heavy-precipitation events (daily precipitation exceeding the 75th percentile), with the greater frequencies found for the east and southwest coasts during autumn and winter. Cold days (daily maximum temperature below the 10th percentile) occur together with intense precipitation more frequently during spring and summer. Simulations by regional climate models show good agreement with observations in the seasonal and spatial variability of the joint distribution, especially when an ensemble of simulations was used.

scholarly journals The effects of aerosols on precipitation and dimensions of subtropical clouds: a sensitivity study using a numerical cloud model

2006 ◽  
Vol 6 (1) ◽  
pp. 67-80 ◽  
Author(s):  
A. Teller ◽  
Z. Levin
Keyword(s):  
Water Vapor ◽  
Climate Models ◽  
Cloud Model ◽  
Cloud Condensation Nuclei ◽  
Sensitivity Study ◽  
Meteorological Conditions ◽  
Dust Particles ◽  
Noticeable Effect ◽  
Convective Clouds ◽  
Ice Nuclei

Abstract. Numerical experiments were carried out using the Tel-Aviv University 2-D cloud model to investigate the effects of increased concentrations of Cloud Condensation Nuclei (CCN), giant CCN (GCCN) and Ice Nuclei (IN) on the development of precipitation and cloud structure in mixed-phase sub-tropical convective clouds. In order to differentiate between the contribution of the aerosols and the meteorology, all simulations were conducted with the same meteorological conditions. The results show that under the same meteorological conditions, polluted clouds (with high CCN concentrations) produce less precipitation than clean clouds (with low CCN concentrations), the initiation of precipitation is delayed and the lifetimes of the clouds are longer. GCCN enhance the total precipitation on the ground in polluted clouds but they have no noticeable effect on cleaner clouds. The increased rainfall due to GCCN is mainly a result of the increased graupel mass in the cloud, but it only partially offsets the decrease in rainfall due to pollution (increased CCN). The addition of more effective IN, such as mineral dust particles, reduces the total amount of precipitation on the ground. This reduction is more pronounced in clean clouds than in polluted ones. Polluted clouds reach higher altitudes and are wider than clean clouds and both produce wider clouds (anvils) when more IN are introduced. Since under the same vertical sounding the polluted clouds produce less rain, more water vapor is left aloft after the rain stops. In our simulations about 3.5 times more water evaporates after the rain stops from the polluted cloud as compared to the clean cloud. The implication is that much more water vapor is transported from lower levels to the mid troposphere under polluted conditions, something that should be considered in climate models.

scholarly journals Impact of a new condensed toluene mechanism on air quality model predictions in the US

2010 ◽  
Vol 3 (4) ◽  
pp. 2291-2314
Author(s):  
G. Sarwar ◽  
K. W. Appel ◽  
A. G. Carlton ◽  
R. Mathur ◽  
K. Schere ◽  
...  
Keyword(s):  
Air Quality ◽  
Los Angeles ◽  
Production Efficiency ◽  
Sensitivity Study ◽  
Chemical Mechanism ◽  
Ozone Production ◽  
Daily Maximum ◽  
Air Quality Model ◽  
Quality Model ◽  
Mixing Ratios

Abstract. A new condensed toluene mechanism is incorporated into the Community Multiscale Air Quality Modeling system. Model simulations are performed using the CB05 chemical mechanism containing the existing (base) and the new toluene mechanism for the western and eastern US for a summer month. With current estimates of tropospheric emission burden, the new toluene mechanism increases monthly mean daily maximum 8-h ozone by 1.0–3.0 ppbv in Los Angeles, Portland, Seattle, Chicago, Cleveland, northeastern US, and Detroit compared to that with the base toluene chemistry. It reduces model mean bias for ozone at elevated observed ozone mixing ratios. While the new mechanism increases predicted ozone, it does not enhance ozone production efficiency. Sensitivity study suggests that it can further enhance ozone if elevated toluene emissions are present. While changes in total fine particulate mass are small, predictions of in-cloud SOA increase substantially.

Assessing the contribution of multiple forcings to changes in temperature extremes 1981–2020 using CMIP6 climate models

2021 ◽  
Author(s):  
Mastawesha Misganaw Engdaw ◽  
Andrew Ballinger ◽  
Gabriele Hegerl ◽  
Andrea Steiner
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Climate Models ◽  
Temporal Trends ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Cold Temperatures

<p>In this study, we aim at quantifying the contribution of different forcings to changes in temperature extremes over 1981–2020 using CMIP6 climate model simulations. We first assess the changes in extreme hot and cold temperatures defined as days below 10% and above 90% of daily minimum temperature (TN10 and TN90) and daily maximum temperature (TX10 and TX90). We compute the change in percentage of extreme days per season for October-March (ONDJFM) and April-September (AMJJAS). Spatial and temporal trends are quantified using multi-model mean of all-forcings simulations. The same indices will be computed from aerosols-, greenhouse gases- and natural-only forcing simulations. The trends estimated from all-forcings simulations are then attributed to different forcings (aerosols-, greenhouse gases-, and natural-only) by considering uncertainties not only in amplitude but also in response patterns of climate models. The new statistical approach to climate change detection and attribution method by Ribes et al. (2017) is used to quantify the contribution of human-induced climate change. Preliminary results of the attribution analysis show that anthropogenic climate change has the largest contribution to the changes in temperature extremes in different regions of the world.</p><p><strong>Keywords:</strong> climate change, temperature, extreme events, attribution, CMIP6</p><p> </p><p><strong>Acknowledgement:</strong> This work was funded by the Austrian Science Fund (FWF) under Research Grant W1256 (Doctoral Programme Climate Change: Uncertainties, Thresholds and Coping Strategies)</p>

scholarly journals Stationary and Non-Stationary Frameworks for Extreme Rainfall Time Series in Southern Italy

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1477 ◽  
Author(s):  
Davide De Luca ◽  
Luciano Galasso
Keyword(s):  
Time Series ◽  
Climate Models ◽  
Southern Italy ◽  
Regional Climate ◽  
Data Series ◽  
Rainfall Time Series ◽  
Annual Maximum ◽  
Data Set ◽  
Maximum Rainfall ◽  
Rainfall Events

This study tests stationary and non-stationary approaches for modelling data series of hydro-meteorological variables. Specifically, the authors considered annual maximum rainfall accumulations observed in the Calabria region (southern Italy), and attention was focused on time series characterized by heavy rainfall events which occurred from 1 January 2000 in the study area. This choice is justified by the need to check if the recent rainfall events in the new century can be considered as very different or not from the events occurred in the past. In detail, the whole data set of each considered time series (characterized by a sample size N > 40 data) was analyzed, in order to compare recent and past rainfall accumulations, which occurred in a specific site. All the proposed models were based on the Two-Component Extreme Value (TCEV) probability distribution, which is frequently applied for annual maximum time series in Calabria. The authors discussed the possible sources of uncertainty related to each framework and remarked on the crucial role played by ergodicity. In fact, if the process is assumed to be non-stationary, then ergodicity cannot hold, and thus possible trends should be derived from external sources, different from the time series of interest: in this work, Regional Climate Models’ (RCMs) outputs were considered in order to assess possible trends of TCEV parameters. From the obtained results, it does not seem essential to adopt non-stationary models, as significant trends do not appear from the observed data, due to a relevant number of heavy events which also occurred in the central part of the last century.

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