Evaluation of the ERA5 reanalysis as a reference dataset for fine-scale hydrological modelling over alpine basins

<p>The European Center for Medium-Range Weather Forecasts (ECMWF) has recently released its most advanced reanalysis product, the ERA5 dataset. It was designed and generated with methods giving it multiple advantages over the previous release, the ERA-Interim reanalysis product. Notably, it has a finer spatial resolution, is archived at the hourly time step, uses a more advanced assimilation system, and includes more sources of data. This paper aims to evaluate the ERA5 reanalysis as a potential reference dataset for hydrological modelling by considering the ERA5 precipitation and temperatures as proxies for observations in the hydrological modelling process. This is obtained by using a semi-distributed hydrological model over basins ranging from 40km<sup>2</sup> to 6900 km<sup>2</sup> over the Upper Adige river basin in the Eastern Italian Alps. This study shows that ERA5-based precipitation product is affected by a significant bias which translates to biased runoff at all spatial scales considered in the study. We observed that ERA5 precipitation product generally overestimate low-intensity rainfall and underestimate high rainfall intensity in the region. We analysed how this affects simulation of annual max floods over the study area. The results show that flood simulations are in general surprisingly good, as they result from the combination of two cascading errors: i) overestimation of the soil moisture conditions at the start of the event and ii) the underestimation of the event forcing rainfall. Differences between ERA5 and observation datasets are mostly linked to precipitation, as temperature only marginally influences the hydrological simulation outcomes.</p>

Reanalysis Product-Based Nonstationary Frequency Analysis for Estimating Extreme Design Rainfall

Nonstationarity is one major issue in hydrological models, especially in design rainfall analysis. Design rainfalls are typically estimated by annual maximum rainfalls (AMRs) of observations below 50 years in many parts of the world, including South Korea. However, due to the lack of data, the time-dependent nature may not be sufficiently identified by this classic approach. Here, this study aims to explore design rainfall with nonstationary condition using century-long reanalysis products that help one to go back to the early 20th century. Despite its useful representation of the past climate, the reanalysis products via observational data assimilation schemes and models have never been tested in representing the nonstationary behavior in extreme rainfall events. We used daily precipitations of two century-long reanalysis datasets as the ERA-20c by the European Centre for Medium-Range Weather Forecasts (ECMWF) and the 20th century reanalysis (20CR) by the National Oceanic and Atmospheric Administration (NOAA). The AMRs from 1900 to 2010 were derived from the grids over South Korea. The systematic errors were downgraded through quantile delta mapping (QDM), as well as conventional stationary quantile mapping (SQM). The evaluation result of the bias-corrected AMRs indicated the significant reduction of the errors. Furthermore, the AMRs present obvious increasing trends from 1900 to 2010. With the bias-corrected values, we carried out nonstationary frequency analysis based on the time-varying location parameters of generalized extreme value (GEV) distribution. Design rainfalls with certain return periods were estimated based on the expected number of exceedance (ENE) interpretation. Although there is a significant range of uncertainty, the design quantiles by the median parameters showed the significant relative difference, from −30.8% to 42.8% for QDM, compared with the quantiles by the multi-decadal observations. Even though the AMRs from the reanalysis products are challenged by various errors such as quantile mapping (QM) and systematic errors, the results from the current study imply that the proposed scheme with employing the reanalysis product might be beneficial to predict the future evolution of extreme precipitation and to estimate the design rainfall accordingly.

ПРОСТРАНСТВЕННО-ВРЕМЕННЫЕ ХАРАКТЕРИСТИКИ АПВЕЛЛИНГОВ В ЮГО-ВОСТОЧНОЙ БАЛТИКЕ В 2010-2019 ГГ., "Фундаментальная и прикладная гидрофизика"

В работе представлены результаты верификации и применения предложенного автоматического алгоритма определения апвеллинга по данным реанализа CMEMS Baltic Sea Physical Reanalysis product в юго-восточной части Балтийского моря за 2010—2019 гг. Верификация работы алгоритма выполнена по данным многомесячных наблюдений на морской ледостойкой стационарной платформе D6, судовым данным, полученным в 127-м рейсе НИС «Профессор Штокман» в 2014 г., и результатам выделения апвеллинга по температуре поверхности моря по данным спектрорадиометра MODIS Terra/Aqua. Показано, что наименьшая повторяемость апвеллингов наблюдается в августе-сентябре (5-6 дней в год), наибольшая — в мае—июне и октябре (11-15 дней в год). В период 2010—2013 гг. в исследуемом районе наблюдалось в среднем до 10% отрицательных термических аномалий в теплый период года. С 2014 г. (за исключением 2017 г.) отмечено увеличение повторяемости апвеллингов — в среднем, около 20% дней составляли дни с апвеллингом. Показано, что зимние индексы колебания Восточная Атлантика — Западная Россия, восточноатлантического колебания и весенний индекс скандинавского колебания могут быть использованы для оценок характеристик будущего летнего апвеллинга.

Evaluation of the ERA5 reanalysis as a potential reference dataset for hydrological modelling over North America

The European Centre for Medium-Range Weather Forecasts (ECMWF) recently released its most advanced reanalysis product, the ERA5 dataset. It was designed and generated with methods giving it multiple advantages over the previous release, the ERA-Interim reanalysis product. Notably, it has a finer spatial resolution, is archived at the hourly time step, uses a more advanced assimilation system and includes more sources of data. This paper aims to evaluate the ERA5 reanalysis as a potential reference dataset for hydrological modelling by considering the ERA5 precipitation and temperatures as proxies for observations in the hydrological modelling process, using two lumped hydrological models over 3138 North American catchments. This study shows that ERA5-based hydrological modelling performance is equivalent to using observations over most of North America, with the exception of the eastern half of the US, where observations lead to consistently better performance. ERA5 temperature and precipitation biases are consistently reduced compared to ERA-Interim and systematically more accurate for hydrological modelling. Differences between ERA5, ERA-Interim and observation datasets are mostly linked to precipitation, as temperature only marginally influences the hydrological simulation outcomes.

Differences in the ERA5-Land reanalysis and real observation datasets for calculation of drought indices from two distinct points

<p>Even though, droughts usually correspond to smaller latitudes, during the last decade Latvia has faced several long-term drought events. This have caused awareness of more frequent drought episodes in future due to climate change. Accurate and complete meteorological data are required to calculate realistic drought indices and to estimate drought probability in the future.</p><p>In places were direct meteorological observation data are absent or dataset is incomplete and not sufficient, data from numerical weather forecasting reanalysis such as ERA5 can be used instead or along with direct observations. Reanalysis provide comprehensive snapshots of conditions at regular intervals over long time periods — often years or decades. The European Center for Medium-Range Weather Forecasts (ECMWF) has released its latest reanalysis product, the ERA5-Land dataset (C3S, 2019).</p><p>The goal of this study is to evaluate the ERA5-Land reanalysis product as a substitute for observations in meteorological stations for calculation of drought related indices for time period from 1981 to 2018.  Two meteorological stations more than 200 km apart in Latvia - Riga and Rezekne - were considered. </p><p>Meteoric and agricultural drought indices were calculated with freely available software DrinC (Tigkas et.al., 2013) as well as R – packages spei and pdsi - using monthly mean reanalysis as well as observed meteorological data as input. It is found that meteorological parameters as well as drought indices have high consistency between two data sources. </p><p>References:</p><p>Copernicus Climate Change Service (C3S) (2019): C3S ERA5-Land reanalysis. Copernicus Climate Change Service, <em>12.12.2019</em>. </p><p>Tigkas, Dimitris & Vangelis, Harris & Tsakiris, George. (2013). The Drought Indices Calculator (DrinC).</p><p>The study is supported by fundamental and applied science research programme, project No.: lzp-2019/1-0165 “Spatial and temporal prediction of groundwater drought with mixed models for multilayer sedimentary basin under climate change”.</p>

A revised ocean glider concept to realize Stommel's vision and supplement Argo floats

This paper revisits Stommel's vision for a global glider network and the Argo design specification. A concept of floats with wings, so-called slow underwater gliders, is explored. An analysis of the energy or power consumption shows that, by operating gliders with half the vehicle volume at half the speed compared to present gliders, the energy requirements for long-duration missions can be met with available battery capacities. Simulation experiments of slow gliders are conducted using the horizontal current fields from an eddy-permitting ocean reanalysis product. By employing a semi-Lagrangian, streamwise navigation whereby the glider steers at right angles to ocean currents, we show that the concept is feasible. The simulated glider tracks demonstrate the potential for efficient coverage of key oceanographic features and variability.

An intercomparison of subtropical cut-off lows in the Southern Hemisphere using recent reanalyses: ERA-Interim, NCEP-CFRS, MERRA-2, JRA-55, and JRA-25

Four recent reanalysis products ERA-Interim, NCEP-CFSR, MERRA-2 and JRA-55 are evaluated and compared to an older reanalysis JRA-25, to quantify their confidence in representing Cut-off lows (COLs) in the Southern Hemisphere. The climatology of COLs based on the minima of 300-hPa vorticity ($$\xi_{300}$$ξ300) and 300-hPa geopotential ($$Z_{300}$$Z300) provides different perspectives of COLs and contributes to the understanding of the discrepancies observed in the literature regarding their numbers and seasonality. The COLs compare better among the newest reanalyses than compared to the older reanalysis JRA-25. The difference in number between the latest reanalyses are generally small for both $$\xi_{300}$$ξ300 and, with more COLs identified in $$\xi_{300}$$ξ300 than in $$Z_{300}$$Z300 for all reanalyses. The spatial differences observed between the newest reanalyses are mainly due to differences in the track lengths, which is larger in ERA-Interim and JRA-55 than in NCEP-CFSR and MERRA-2, resulting in disparities in the track density. This is likely due to the difference in the assimilation data system used in each reanalysis product. The largest differences in intensities occur in the $$\xi_{300}$$ξ300, because this field is very sensitive to the reanalysis resolution. The mean separation distance of the COLs that match between the latest reanalyses are generally small, while the older JRA-25 has a broader distribution and larger number of matches with relatively large distances, indicating larger uncertainties in location of COLs. The results show significant improvements for the most recent reanalyses compared to the older JRA-25 reanalysis, indicating a progress in representing the COL properties.

Evaluation of the ERA5 reanalysis as a potential reference dataset for hydrological modeling over North-America

The European Center for Medium-Range Weather Forecasts (ECMWF) has recently released its most advanced reanalysis product, the ERA5 dataset. It was designed and generated with methods giving it multiple advantages over the previous release, the ERA-Interim reanalysis product. Notably, it has a finer spatial resolution, is archived at the hourly time step, uses a more advanced assimilation system and includes more sources of data. This paper aims to evaluate the ERA5 reanalysis as a potential reference dataset for hydrological modelling by considering the ERA5 precipitation and temperatures as proxies for observations in the hydrological modelling process, using two lumped hydrological models over 3138 North-American catchments. This study shows that ERA5-based hydrological modeling performance is equivalent to using observations over most of North-America, with the exception of the Eastern half of the US, where observations lead to consistently better performance. ERA5 temperature and precipitation biases are consistently reduced compared to ERA-Interim and systematically more accurate for hydrological modelling. Differences between ERA5, ERA-Interim and observation datasets are mostly linked to precipitation, as temperature only marginally influences the hydrological simulation outcomes.

A revised ocean glider concept to realize Stommel's vision and supplement Argo floats

This paper revisits Stommel's vision for a global glider network and the Argo design specification. A concept of floats with wings, so-called slow underwater gliders, is explored. An analysis of the energy/power consumption shows that, by operating gliders with half the vehicle volume at half the speed compared to present gliders, the energy requirements for long duration missions can be met with available battery capacities. Simulation experiments of slow gliders are conducted using the horizontal current fields from an eddy-permitting ocean reanalysis product. By employing a semi-Lagrangian, streamwise navigation whereby the glider steers at right angles to ocean currents, we show that the concept is feasible. The simulated glider tracks demonstrate the potential for efficient coverage of key oceanographic features and variability.