Assessment of extreme flood events in a changing climate for a long-term planning of socio-economic infrastructure in the Russian Arctic

Climate warming has been more acute in the Arctic than at lower latitudes and this tendency is expected to continue. This generates major challenges for economic activity in the region. Among other issues is the long-term planning and development of socio-economic infrastructure (dams, bridges, roads, etc.), which require climate-based forecasts of the frequency and magnitude of detrimental flood events. To estimate the cost of the infrastructure and operational risk, a probabilistic form of long-term forecasting is preferable. In this study, a probabilistic model to simulate the parameters of the probability density function (PDF) for multi-year runoff based on a projected climatology is applied to evaluate changes in extreme floods for the territory of the Russian Arctic. The model is validated by cross-comparison of the modelled and empirical PDFs using observations from 23 sites located in northern Russia. The mean values and coefficients of variation (CVs) of the spring flood depth of runoff are evaluated under four climate scenarios, using simulations of six climate models for the period 2010–2039. Regions with substantial expected changes in the means and CVs of spring flood depth of runoff are outlined. For the sites located within such regions, it is suggested to account for the future climate change in calculating the maximal discharges of rare occurrence. An example of engineering calculations for maximal discharges with 1 % exceedance probability is provided for the Nadym River at Nadym

The performance of FLake in the Met Office Unified Model

We present results from the coupling of FLake to the Met Office Unified Model (MetUM). The coupling and initialisation are first described, and the results of testing the coupled model in local and global model configurations are presented. These show that FLake has a small statistical impact on screen temperature, but has the potential to modify the weather in the vicinity of areas of significant inland water. Examination of FLake lake ice has revealed that the behaviour of lakes in the coupled model is unrealistic in some areas of significant sub-grid orography. Tests of various modifications to ameliorate this behaviour are presented. The results indicate which of the possible model changes best improve the annual cycle of lake ice. As FLake has been developed and tuned entirely outside the Unified Model system, these results can be interpreted as a useful objective measure of the performance of the Unified Model in terms of its near-surface characteristics

Improving the lake scheme within a coupled WRF‐lake model in the Laurentian Great Lakes

In this study, a one‐dimensional (1‐D) thermal diffusion lake model within the Weather Research and Forecasting (WRF) model was investigated for the Laurentian Great Lakes. In the default 10‐layer lake model, the albedos of water and ice are specified with constant values, 0.08 and 0.6, respectively, ignoring shortwave partitioning and zenith angle, ice melting, and snow effect. Some modifications, including a dynamic lake surface albedo, tuned vertical diffusivities, and a sophisticated treatment of snow cover over lake ice, have been added to the lake model. A set of comparison experiments have been carried out to evaluate the performances of different lake schemes in the coupled WRF‐lake modeling system. Results show that the 1‐D lake model is able to capture the seasonal variability of lake surface temperature (LST) and lake ice coverage (LIC). However, it produces an early warming and quick cooling of LST in deep lakes, and excessive and early persistent LIC in all lakes. Increasing vertical diffusivity can reduce the bias in the 1‐D lake but only in a limited way. After incorporating a sophisticated treatment of lake surface albedo, the new lake model produces a more reasonable LST and LIC than the default lake model, indicating that the processes of ice melting and snow accumulation are important to simulate lake ice in the Great Lakes. Even though substantial efforts have been devoted to improving the 1‐D lake model, it still remains considerably challenging to adequately capture the full dynamics and thermodynamics in deep lakes.Key PointsA dynamic lake surface albedo scheme is added to the lake modelThe new lake model produces a more reasonable LST and LIC than the default lake modelIce melting and snow accumulation are important to simulating lake ice in the Great LakesPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135995/1/jame20346_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135995/2/jame20346.pd

The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of Earth surface variables and fluxes

CC Attribution 3.0 License.Final revised paper also available at http://www.geosci-model-dev.net/6/929/2013/gmd-6-929-2013.pdfInternational audienceSURFEX is a new externalized land and ocean surface platform that describes the surface fluxes and the evolution of four types of surface: nature, town, inland water and ocean. It can be run either coupled or in offline mode. It is mostly based on pre-existing, well validated scientific models. It can be used in offline mode (from point scale to global runs) or fully coupled with an atmospheric model. SURFEX is able to simulate fluxes of carbon dioxide, chemical species, continental aerosols, sea salt and snow particles. It also includes a data assimilation module. The main principles of the organization of the surface are described first. Then, a survey is made of the scientific module (including the coupling strategy). Finally the main applications of the code are summarized. The current applications are extremely diverse, ranging from surface monitoring and hydrology to numerical weather prediction and global climate simulations. The validation work undertaken shows that replacing the pre-existing surface models by SURFEX in these applications is usually associated with improved skill, as the numerous scientific developments contained in this community code are used to good advantage

Global heat uptake by inland waters

Heat uptake is a key variable for understanding the Earth system response to greenhouse gas forcing. Despite the importance of this heat budget, heat uptake by inland waters has so far not been quantified. Here we use a unique combination of global-scale lake models, global hydrological models and Earth system models to quantify global heat uptake by natural lakes, reservoirs, and rivers. The total net heat uptake by inland waters amounts to 2.6 ± 3.2 ×1020 J over the period 1900–2020, corresponding to 3.6% of the energy stored on land. The overall uptake is dominated by natural lakes (111.7%), followed by reservoir warming (2.3%). Rivers contribute negatively (-14%) due to a decreasing water volume. The thermal energy of water stored in artificial reservoirs exceeds inland water heat uptake by a factor ∼10.4. This first quantification underlines that the heat uptake by inland waters is relatively small, but non-negligible

Implementation of a simple thermodynamic sea ice scheme, SICE version 1.0-38h1, within the ALADIN–HIRLAM numerical weather prediction system version 38h1

Sea ice is an important factor affecting weather regimes, especially in polar regions. A lack of its representation in numerical weather prediction (NWP) systems leads to large errors. For example, in the HARMONIE–AROME model configuration of the ALADIN–HIRLAM NWP system, the mean absolute error in 2&thinsp;m temperature reaches 1.5&thinsp;°C after 15 forecast hours for Svalbard. A possible reason for this is that the sea ice properties are not reproduced correctly (there is no prognostic sea ice temperature in the model). Here, we develop a new simple sea ice scheme (SICE) and implement it in the ALADIN–HIRLAM NWP system in order to improve the forecast quality in areas influenced by sea ice. The new parameterization is evaluated using HARMONIE–AROME experiments covering the Svalbard and Gulf of Bothnia areas for a selected period in March–April 2013. It is found that using the SICE scheme improves the forecast, decreasing the value of the 2&thinsp;m temperature mean absolute error on average by 0.5&thinsp;°C in areas that are influenced by sea ice. The new scheme is sensitive to the representation of the form drag. The 10&thinsp;m wind speed bias increases on average by 0.4&thinsp;m s−1 when the form drag is not taken into account. Also, the performance of SICE in March–April 2013 and December 2015–December 2016 was studied by comparing modelling results with the sea ice surface temperature products from MODIS and VIIRS. The warm bias (of approximately 5&thinsp;°C) of the new scheme is indicated for areas of thick ice in the Arctic. Impacts of the SICE scheme on the modelling results and possibilities for future improvement of sea ice representation in the ALADIN–HIRLAM NWP system are discussed.</p

Estimation of the mean depth of boreal lakes for use in numerical weather prediction and climate modelling

ISI Document Delivery No.: AD7AA Times Cited: 0 Cited Reference Count: 21 Cited References: Amante C, 2009, NGDC24 NOAA NESDIS, V24, P1 Balsamo G, 2010, BOREAL ENVIRON RES, V15, P178 CANFIELD DE, 1985, J AQUAT PLANT MANAGE, V23, P25 Champeaux JL, 2004, INT GEOSCI REMOTE SE, P2046 Doganovsky A., 2006, P C 59 HERZ READ GEO, P15 Doganovsky A., 2012, LIMNOL REV 2012, V12, P11, DOI [10.2478/v10194-011-0040-2, DOI 10.2478/V10194-011-0040-2] Eerola K, 2010, BOREAL ENVIRON RES, V15, P130 Hormann K, 2001, COMP GEOM-THEOR APPL, V20, P131, DOI 10.1016/S0925-7721(01)00012-8 Kitaev S., 1984, ECOLOGICAL BASIS LAK, V208 Kondratiev S., 2010, THESIS SAINT PETERSB, P51 Kourzeneva E, 2012, TELLUS A, V64, DOI 10.3402/tellusa.v64i0.15640 Kourzeneva E., 2009, ALADIN NEWSLETTER, V37, P46 Kourzeneva E, 2012, TELLUS A, V64, DOI 10.3402/tellusa.v64i0.17226 Lee R. W., 1997, LIGHT ATTENUATION SH, P97 Mironov D, 2008, PARAMETERIZATION LAK, V11, P41 PGAW (Physical Geography Atlas of the World), 1964, PGAW PHYS GEOGR ATL Samuelsson P, 2010, BOREAL ENVIRON RES, V15, P113 SAW (Small Atlas of the World), 1990, SAW SMALL ATL WORLD Sheffield J, 2006, J CLIMATE, V19, P3088, DOI 10.1175/JCLI3790.1 Tranvik LJ, 2009, LIMNOL OCEANOGR, V54, P2298, DOI 10.4319/lo.2009.54.6_part_2.2298 Walter KM, 2007, PHILOS T R SOC A, V365, P1657, DOI 10.1098/rsta.2007.2036 Choulga, Margarita Kourzeneva, Ekaterina Zakharova, Elena Doganovsky, Arkady Zakharova, Elena/N-7731-2013 Zakharova, Elena/0000-0002-2962-1439 ECMWF The authors thank Yurii Batrak and Suleiman Mostamandi (Russian State Hydrometeorological University), as well as Pavel Andreev (North-West Interregional Territorial Department of the Federal Service for Hydrometeorology and Environmental Monitoring) for useful tips and discussions. Two anonymous reviewers made many useful comments. The project was made possible due to the support from ECMWF. 0 CO-ACTION PUBLISHING JARFALLA TELLUS ALakes influence the structure of the atmospheric boundary layer and, consequently, the local weather and local climate. Their influence should be taken into account in the numerical weather prediction (NWP) and climate models through parameterisation. For parameterisation, data on lake characteristics external to the model are also needed. The most important parameter is the lake depth. Global database of lake depth GLDB (Global Lake Database) is developed to parameterise lakes in NWP and climate modelling. The main purpose of the study is to upgrade GLDB by use of indirect estimates of the mean depth for lakes in boreal zone, depending on their geological origin. For this, Tectonic Plates Map, geological, geomorphologic maps and the map of Quaternary deposits were used. Data from maps were processed by an innovative algorithm, resulting in 141 geological regions where lakes were considered to be of kindred origin. To obtain a typical mean lake depth for each of the selected regions, statistics from GLDB were gained and analysed. The main result of the study is a new version of GLDB with estimations of the typical mean lake depth included. Potential users of the product are NWP and climate models

Retention time of lakes in the Larsemann Hills oasis, East Antarctica

This study provides first estimates of the water transport timescale for five lakes located in the Larsemann Hills oasis (69&deg;&tild;23&prime;S,76&deg;&tild;20&prime;E) in East Antarctica. We estimated lake retention time (LRT) as a ratio of lake volume to the inflow and outflow terms of a lake water balance equation. The LRT was evaluated for lakes of epiglacial and landlocked types, and it was assumed that these lakes are monomictic, with water exchange occurring during the warm season only. We used hydrological observations collected in four seasonal field campaigns to evaluate the LRT. For the epiglacial lakes Progress and Nella/Scandrett, the LRT was estimated at 12-13 and 4-5 years, respectively. For the landlocked lakes Stepped, Sarah Tarn and Reid, our results show a great difference in the LRT calculated from the outflow and inflow terms of the water balance equation. The LRTs for these lakes vary depending on the methods and errors inherent to them. We relied on the estimations from the outflow terms, since they are based on hydrological measurements with better quality. Lake Stepped exchanged water within 1.5 years. Sarah Tarn and Lake Reid are endorheic ponds, with water loss mainly through evaporation. Their LRTs were estimated as 21-22 and 8-9 years, respectively. To improve the LRT estimates, special hydrological observations are needed to monitor the lakes and streams during the warm season with a uniform observational programme. © 2021 Copernicus GmbH. All rights reserved