Two questions motivated this study: 1) Will meteorological droughts become more frequent and severe during the twenty-first century? 2) Given the projected global temperature rise, to what extent does the inclusion of temperature (in addition to precipitation) in drought indicators play a role in future meteorological droughts? To answer, we analyzed the changes in drought frequency, severity, and historically undocumented extreme droughts over 1981–2100, using the standardized precipitation index (SPI; including precipitation only) and standardized precipitation-evapotranspiration index (SPEI; indirectly including temperature), and under two representative concentration pathways (RCP4.5 and RCP8.5). As input data, we employed 103 high-resolution (0.44°) simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX), based on a combination of 16 global circulation models (GCMs) and 20 regional circulation models (RCMs). This is the first study on global drought projections including RCMs based on such a large ensemble of RCMs. Based on precipitation only, ~15% of the global land is likely to experience more frequent and severe droughts during 2071–2100 versus 1981–2010 for both scenarios. This increase is larger (~47% under RCP4.5, ~49% under RCP8.5) when precipitation and temperature are used. Both SPI and SPEI project more frequent and severe droughts, especially under RCP8.5, over southern South America, the Mediterranean region, southern Africa, southeastern China, Japan, and southern Australia. A decrease in drought is projected for high latitudes in Northern Hemisphere and Southeast Asia. If temperature is included, drought characteristics are projected to increase over North America, Amazonia, central Europe and Asia, the Horn of Africa, India, and central Australia; if only precipitation is considered, they are found to decrease over those areas.

A novel and simple electrochemical immunoassay for C-reactive protein was developed using metal-organic frameworks (Au-MOFs) as signal unit. In this study, we found MOFs could be used as signal probe. And this new class of signal probe differs from traditional probe. The signal of the copper ions (Cu) from MOFs could be directly detected without acid dissolution and preconcentration, which would greatly simplify the detection steps and reduce the detection time. Moreover, MOFs contain large amounts of Cu ions, providing high electrochemical signals. Our report represents the first example of using MOFs themselves as electrochemical signal probe for biosensors. Platinum nanoparticle modified covalent organic frameworks (Pt-COFs) with high electronic conductivity was employed as the substrate, which is the first time demonstrating the use of Pt-COFs for electrochemical immunoassay. Under the optimized experimental conditions, the proposed sensing strategy provides a linear dynamic ranging from 1 to 400 ng/mL. A detection limit of 0.2 ng/mL was obtained, indicating an improved analytical performance. With these merits, this stable, simple, low-cost, sensitive and selective electrochemical immunoassay shows promise for applications in the point-of-care diagnostics of dieses and environmental monitoring.

A 34 year (1979–2012) high-resolution (7 km grid) atmospheric hindcast over the Bohai Sea and the Yellow Sea (BYS) has been performed using COSMO-CLM (CCLM) forced by ERA-Interim reanalysis data (ERA-I). The accuracy of CCLM in surface wind reproduction and the added value of dynamical downscaling to ERA-I have been investigated through comparisons with the QuikSCAT Level2B 12.5 km version 3 (L2B12v3) swath data and in situ observations. The results revealed that CCLM has a reliable ability to reproduce the regional wind characteristics over the BYS. Added value to ERA-I has been detected in the coastal areas with complex orography. CCLM wind quality had strong seasonal variability, with better performance in the summer relative to ERA-I, even in the offshore areas. CCLM was better able to represent light and moderate winds but had even more added value for strong winds relative to ERA-I. The spatial digital filter method was used to investigate the scale of the added value, and the results show that CCLM adds value to ERA-I mainly in medium scales of wind variability. Furthermore, wind climatology was investigated, and significant increasing trends in the south Yellow Sea especially in winter and spring were found for seasonal mean wind speeds

Surface wind is significant for ocean state climate, ocean mixing, and viability of wind energy techniques. However, surface wind simulated from the regional climate model generally features substantial bias from observation. For the first time, this study compares the performance of five bias correction techniques, (1) linear scaling, (2) variance scaling, (3) quantile mapping based on empirical distribution, (4) quantile mapping based on Weibull distribution, and (5) cumulative distribution functions transformation, in reducing the statistical bias of a regional climate model wind output, which was downscaled from a global climate model CNRM‐CM5 during 1991–2000. The surface wind of JRA55 reanalysis data is used as reference. Results show that all bias correction methods are consistent in reducing the climatological mean bias in spatial patterns and intensities. The linear scaling method always performs the worst among all methods in correcting higher‐order statistical biases such as skewness, kurtosis, and wind power density. The other four bias correction methods are generally similar in reducing the statistical biases of different measures based on spatial distribution maps. However, when it comes to spatial averaged mean of statistical measures over CORDEX‐East Asia in January and July, the quantile mapping based on Weibull distribution generally shows the best skills among all methods in bias reduction.

Abstract. In the last decade, the Climate Limited-area Modeling Community (CLM-Community) has contributed to the Coordinated Regional Climate Downscaling Experiment (CORDEX) with an extensive set of regional climate simulations. Using several versions of the COSMO-CLM-Community model, ERA-Interim reanalysis and eight global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were dynamically downscaled with horizontal grid spacings of 0.44∘ (∼ 50 km), 0.22∘ (∼ 25 km), and 0.11∘ (∼ 12 km) over the CORDEX domains Europe, South Asia, East Asia, Australasia, and Africa. This major effort resulted in 80 regional climate simulations publicly available through the Earth System Grid Federation (ESGF) web portals for use in impact studies and climate scenario assessments. Here we review the production of these simulations and assess their results in terms of mean near-surface temperature and precipitation to aid the future design of the COSMO-CLM model simulations. It is found that a domain-specific parameter tuning is beneficial, while increasing horizontal model resolution (from 50 to 25 or 12 km grid spacing) alone does not always improve the performance of the simulation. Moreover, the COSMO-CLM performance depends on the driving data. This is generally more important than the dependence on horizontal resolution, model version, and configuration. Our results emphasize the importance of performing regional climate projections in a coordinated way, where guidance from both the global (GCM) and regional (RCM) climate modeling communities is needed to increase the reliability of the GCM–RCM modeling chain.

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Countries in East Asia have set ambitious goals for the development of wind energy to meet the increasing energy demand and to mitigate anthropogenic climate change. However, few studies have investigated changes in wind energy over East Asia under future climatic conditions. In this study, we investigate future changes of 100‐m wind speed and wind energy potential over the CORDEX‐East Asia region under the Representative Concentration Pathway (RCP) 8.5 scenario, by using ensemble simulations from the regional climate model Consortium for small‐scale modeling in CLimate Mode (CCLM). A multivariate bias adjustment method based on the N‐dimensional probability density function transform is used to correct raw simulated horizontal wind components. The comparison between future climate (2021–2050 and 2070–2099) and the present climate (1971–2000) shows decreases in wind speed, wind power density, and wind energy output over most of the CORDEX‐East Asia region, especially in the tropics. Projected increases are pronounced over the Himalayan regions, the Indo‐China Peninsula, the South China Sea, and the western Pacific Ocean in summer and over northeastern China, parts of Western China and the Indo‐China Peninsula in winter. Interannual and intra‐annual variability of wind power density are projected to intensify significantly for most of the CORDEX‐East Asia region. The occurrence of weak wind speeds (<3 m/s) is projected to increase, while strong wind speeds (>11 m/s) are projected to decrease over most of the ocean.

The ability of forecasting systems to simulate tropical cyclones is still insufficient, and currently, there is an increased interest in improving model performance for intense tropical cyclones. In this study, the impact of reducing surface drag at high wind speeds on modeling wind and wave conditions during the super Typhoon Lingling event over the northwest Pacific Ocean in 2019 is investigated. The model response with respect to the parameterization for momentum exchange at the ocean surface is demonstrated using a fully coupled regional atmosphere model (the Consortium for Small-Scale Modeling-Climate Limited-area Modeling, CCLM) and a wind wave model (WAM). The active two-way coupling between the atmosphere and ocean waves model is enabled through the introduction of sea state-dependent surface drag into the CCLM and updated winds into the WAM. The momentum exchange with the sea surface is modeled via the dependency of the roughness length (Z0) on the surface stress itself and, when applicable, on the wind speed. Several high-resolution runs are performed using one-way or two-way fully coupled regional atmosphere-wave (CCLM-WAM) models. The model simulations are assessed against the best track data as well as against buoy and satellite observations. The results show that the spectral nudging technique can improve the model’s ability to capture the large-scale circulation, track and intensity of Typhoon Lingling at regional scales. Under the precondition of large-scale constraining, the two-way coupling simulation with the proposed new roughness parameterization performs much better than the simulations used in older studies in capturing the maximum wind speed of Typhoon Lingling due to the reduced drag at extreme wind conditions for the new Z0.