A Validation of ERA5 Reanalysis Data in the Southern Antarctic Peninsula—Ellsworth Land Region, and Its Implications for Ice Core Studies

High spatiotemporal resolution estimation and analysis of global surface CO concentrations using a deep learning model

Ambient carbon monoxide (CO) is a primary air pollutant that poses significant health risks and contributes to the formation of secondary atmospheric pollutants, such as ozone (O3). This study aims to elucidate global CO pollution in relation to health risks and the influence of natural events like wildfires. Utilizing artificial intelligence (AI) big data techniques, we developed a high-performance Convolutional Neural Network (CNN)-based Residual Network (ResNet) model to estimate daily global CO concentrations at a high spatial resolution of 0.07° from June 2018 to May 2021. Our model integrated the global TROPOMI Total Column of atmospheric CO (TCCO) product and reanalysis datasets, achieving desirable estimation accuracies with R-values (correlation coefficients) of 0.90 and 0.96 for daily and monthly predictions, respectively. The analysis reveals that the CO concentrations were relatively high in northern and central China, as well as northern India, particularly during winter months. Given the significant role of wildfires in increasing surface CO levels, we examined their impact in the Indochina Peninsula, the Amazon Rain Forest, and Central Africa. Our results show increases of 60.0%, 28.7%, and 40.8% in CO concentrations for these regions during wildfire seasons, respectively. Additionally, we estimated short-term mortality cases related to CO exposure in 17 countries for 2019, with China having the highest mortality cases of 23,400 (95% confidence interval: 0-99,500). Our findings highlight the critical need for ongoing monitoring of CO levels and their health implications. The daily surface CO concentration dataset is publicly available and can support future relevant sustainable studies, which is accessible at https://doi.org/10.5281/zenodo.11806178.

Dominance of soil moisture over aridity in explaining vegetation greenness across global drylands

Drylands are one of the most sensitive areas to climate change. Despite being characterized by water scarcity and low precipitation, drylands support a wide range of green biodiversity and nearly 40 % of the global population. However, the climate change impacts on dryland characteristics and vegetation dynamics are debatable as the reasons remain poorly understood. Here, we use hydro-meteorological variables from ERA5 reanalysis and GIMMS-NDVI to analyze the changes in dryland aridity and vegetation greenness in the eight selected global dryland regions. The total dryland area (excluding hyperarid) has increased by 12 %, while arid, semiarid, and dry sub-humid areas have increased by 10.5 %, 8 %, and 25 %, respectively. We find a significant increase in aridity in drylands across the globe, except for South Asia. A decrease (increase) in precipitation is the major driver for a significant increase (decrease) in dryland aridity, with a notable contribution from climate warming. Despite decreasing trends in precipitation, vegetation greenness has significantly increased in most dryland regions due to increased soil moisture. Cropland expansion in Europe, Asia, and Australia resulted in the maximum increase in NDVI (Normalized Difference Vegetation Index) in dryland regions. The highest increase, with a ΔNDVI of 0.075, was observed in South Asia. The enhanced vegetation greenness observed is attributed to the expansion of croplands in recent decades, which has increased soil moisture. Overall, we show that monitoring soil moisture variability can provide a more robust explanation for vegetation greenness in the global drylands than aridity change. Moreover, human interventions of climatic alteration through land use change practices, such as cropland expansion, cannot be ignored while explaining the ecosystem dynamics of the drylands.

Associations between fine particulate air pollution with small-airway inflammation: A nationwide analysis in 122 Chinese cities

Alveolar nitric oxide is a non-invasive indicator of small-airway inflammation, a key pathophysiologic mechanism underlying lower respiratory diseases. However, no epidemiological studies have investigated the impact of fine particulate matter (PM2.5) exposure on the concentration of alveolar nitric oxide (CANO). To explore the associations between PM2.5 exposure in multiple periods and CANO, we conducted a nationwide cross-sectional study in 122 Chinese cities between 2019 and 2021. Utilizing a satellite-based model with a spatial resolution of 1 × 1 km, we matched long-term, mid-term, and short-term PM2.5 exposure for 28,399 individuals based on their home addresses. Multivariable linear regression models were applied to estimate the associations between PM2.5 at multiple exposure windows and CANO. Stratified analyses were also performed to identify potentially vulnerable subgroups. We found that per interquartile range (IQR) unit higher in 1-year average, 1-month average, and 7-day average PM2.5 concentration was significantly associated with increments of 17.78% [95% confidence interval (95%CI): 12.54%, 23.26%], 8.76% (95%CI: 7.35%, 10.19%), and 4.00% (95%CI: 2.81%, 5.20%) increment in CANO, respectively. The exposure-response relationship curves consistently increased with the slope becoming statistically significant beyond 20 μg/m3. Males, children, smokers, individuals with respiratory symptoms or using inhaled corticosteroids, and those living in Southern China were more vulnerable to PM2.5 exposure. In conclusion, our study provided novel evidence that PM2.5 exposure in long-term, mid-term, and short-term periods could significantly elevate small-airway inflammation represented by CANO. Our results highlight the significance of CANO measurement as a non-invasive tool for early screening in the management of PM2.5-related inflammatory respiratory diseases.

Southward migration of the zero-degree isotherm latitude over the Southern Ocean and the Antarctic Peninsula: Cryospheric, biotic and societal implications

The seasonal movement of the zero-degree isotherm across the Southern Ocean and Antarctic Peninsula drives major changes in the physical and biological processes around maritime Antarctica. These include spatial and temporal shifts in precipitation phase, snow accumulation and melt, thawing and freezing of the active layer of the permafrost, glacier mass balance variations, sea ice mass balance and changes in physiological processes of biodiversity. Here, we characterize the historical seasonal southward movement of the monthly near-surface zero-degree isotherm latitude (ZIL), and quantify the velocity of migration in the context of climate change using climate reanalyses and projections. From 1957 to 2020, the ZIL exhibited a significant southward shift of 16.8 km decade-1 around Antarctica and of 23.8 km decade-1 in the Antarctic Peninsula, substantially faster than the global mean velocity of temperature change of 4.2 km decade-1, with only a small fraction being attributed to the Southern Annular Mode (SAM). CMIP6 models reproduce the trends observed from 1957 to 2014 and predict a further southward migration around Antarctica of 24 ± 12 km decade-1 and 50 ± 19 km decade-1 under the SSP2-4.5 and SSP5-8.5 scenarios, respectively. The southward migration of the ZIL is expected to have major impacts on the cryosphere, especially on the precipitation phase, snow accumulation and in peripheral glaciers of the Antarctic Peninsula, with more uncertain changes on permafrost, ice sheets and shelves, and sea ice. Longer periods of temperatures above 0 °C threshold will extend active biological periods in terrestrial ecosystems and will reduce the extent of oceanic ice cover, changing phenologies as well as areas of productivity in marine ecosystems, especially those located on the sea ice edge.

High Salinity Shelf Water production rates in Terra Nova Bay, Ross Sea from high-resolution salinity observations

High Salinity Shelf Water (HSSW) formed in the Ross Sea of Antarctica is a precursor to Antarctic Bottom Water (AABW), a water mass that constitutes the bottom limb of the global overturning circulation. HSSW production rates are poorly constrained, as in-situ observations are scarce. Here, we present high-vertical-and-temporal-resolution salinity time series collected in austral winter 2017 from a mooring in Terra Nova Bay (TNB), one of two major sites of HSSW production in the Ross Sea. We calculate an annual-average HSSW production rate of ~0.4 Sv (106 m3 s-1), which we use to ground truth additional estimates across 2012-2021 made from parametrized net surface heat fluxes. We find sub-seasonal and interannual variability on the order of [Formula: see text] [Formula: see text], with a strong dependence on variability in open-water area that suggests a sensitivity of TNB HSSW production rates to changes in the local wind regime and offshore sea ice pack.

Large-scale and regional climatic influences on surface temperature and precipitation in the South Shetland Islands, northern Antarctic Peninsula

Using data from SCAR observations, ERA5 reanalysis, and regional climate model simulations (RACMO), we examined the influence of large- and regional-scale climate forcing on temperature and precipitation variations in the South Shetland Islands (SSI). Specifically, we focused on understanding how regional climate indices influence the temporal variability of temperature and precipitation on the SSI. Our findings indicate that both large- and regional-scale climate indices significantly impact the interannual and seasonal temperature variability in the SSI. For instance, the Amundsen Sea Low, characterised by low-pressure systems over the Amundsen Sea, and sea ice extent in the northwestern part of the Weddell Sea, exert a strong influence on temperature variability (r from -0.64 to -0.87; p < 0.05). In contrast, precipitation variability in this region is primarily controlled by regional climatic indices. Particularly, anomalies in atmospheric and surface pressure over the Drake Passage region strongly regulate the interannual variability of precipitation in the SSI (r from -0.46 to -0.70; p < 0.05). Large-scale climatic indices demonstrate low but statistically significant correlations, including the Southern Annular Mode and deep convection in the central tropical Pacific. Given the importance of temperature and precipitation in the glacier changes, we recommend assessing the impact of the Drake region on SSI glaciers.

Inter-decadal climate variability induces differential ice response along Pacific-facing West Antarctica

West Antarctica has experienced dramatic ice losses contributing to global sea-level rise in recent decades, particularly from Pine Island and Thwaites glaciers. Although these ice losses manifest an ongoing Marine Ice Sheet Instability, projections of their future rate are confounded by limited observations along West Antarctica's coastal perimeter with respect to how the pace of retreat can be modulated by variations in climate forcing. Here, we derive a comprehensive, 12-year record of glacier retreat around West Antarctica's Pacific-facing margin and compare this dataset to contemporaneous estimates of ice flow, mass loss, the state of the Southern Ocean and the atmosphere. Between 2003 and 2015, rates of glacier retreat and acceleration were extensive along the Bellingshausen Sea coastline, but slowed along the Amundsen Sea. We attribute this to an interdecadal suppression of westerly winds in the Amundsen Sea, which reduced warm water inflow to the Amundsen Sea Embayment. Our results provide direct observations that the pace, magnitude and extent of ice destabilization around West Antarctica vary by location, with the Amundsen Sea response most sensitive to interdecadal atmosphere-ocean variability. Thus, model projections accounting for regionally resolved ice-ocean-atmosphere interactions will be important for predicting accurately the short-term evolution of the Antarctic Ice Sheet.

External environmental conditions impact nocturnal activity levels in proboscis monkeys (Nasalis larvatus) living in Sabah, Malaysia

Recently, several diurnal nonhuman anthropoids have been identified displaying varying degrees of nocturnal activity, which can be influenced by activity “masking effects”—external events or conditions that suppress or trigger activity, temporarily altering normal activity patterns. Environmental masking characteristics include nocturnal temperature, rainfall, cloud cover, and moon brightness. Similarly, other ecological characteristics, including proximity to humans and predators and daytime activity, may also trigger or suppress nocturnal activity. Understanding the effects of external conditions on activity patterns is pertinent to effective species conservation. We investigated the presence of nocturnal activity and the influence of masking effects on the level of nocturnal activity displayed by wild proboscis monkeys (Nasalis larvatus) in Sabah, Malaysian Borneo. Dual‐axis accelerometers were attached by collar to six male proboscis monkeys from different one‐male, multi‐female groups to record activity continuously (165–401 days each). We measured the monkeys' nocturnal and diurnal activity levels and investigated the effects of seven potential masking effects. Nocturnal activity was much lower than diurnal activity. Still, proboscis monkeys did display varying levels of nocturnal activity. Generalized linear mixed models identified higher nocturnal activity in the study individuals during nights with cooler temperatures, higher rainfall, and after higher diurnal activity. These three masking effects affected nocturnal activity levels during the observation period that informed our model, although they did not predict nocturnal activity outside of this period. While the generalizability of these results remains uncertain, this study highlights the utility of accelerometers in identifying activity patterns and masking effects that create variability in these patterns.

Six male proboscis monkeys displayed low levels of nocturnal activity, consistent with a diurnal activity pattern.

Nocturnal activity in five of these male proboscis monkeys increased during nights that had cooler temperatures, higher rainfall, and after higher daytime activity.

Water stable isotopes in snow along a traverse of the West Antarctic Ice Sheet: insights into moisture origins, air-masses distillation history, and climatic value

This study investigated the water isotopic content (δ18O, δD, d-excess) of the surface snow along a 995 km traverse over the West Antarctic Ice Sheet from the Möller Ice Stream - Institute Ice Stream to the upper reaches of the Pine Island Glacier drainage basin. The purpose of this study was to evaluate the climatic record preserved in the snow. We analyzed 92 surface samples (~0.15-0.20 m deep), retrieved during 2014/2015 austral summer from every ~10 km along the traverse route, using the laser spectroscopy technique. We computed the isotopic-geographical characteristics and spatial co-isotopic empirical relationships and compared the isotopic results with the tropospheric mean annual temperature and air mass trajectories. Our isotopic results were sensitive to capturing the well-known climatic asymmetry between the Amundsen-Bellingshausen Sea (ABS; which receives more influence from warmer (oceanic) air masses) and Weddell Sea (WS; more influenced by colder (continental) air masses) sectors. Further, the spatial distribution of δs and d-excess and the co-isotopic relationships reflect two preferential fractionation paths: one from the coast of the ABS sector to the WS sector, and another from the coast of the WS sector to the inland. The Pacific Ocean is confirmed as the primary source of moisture.

Long-Term Freezing Temperatures Frequency Change Effect on Wind Energy Gain (Eurasia and North America, 1950–2019)

The persistent freezing conditions in cold regions are the cause of ice accretion on mechanical and instrumental elements of wind turbines. Consequently, remarkable Annual Energy Production (AEP) losses are prone to occur in those wind farms. Following global expansion of wind energy, these areas have had increased study interest in recent years. The goal of these studies is an improved characterisation of the site for the installation of turbines, which could prevent unexpected high AEP losses due to ice accretion on them. In this context, this paper provides an estimation of the freezing temperatures frequency (FTF) at 100 m over latitudes and evaluates the changes during the last 70 years. To that end, hourly surface temperature data (2 m above surface) from the ERA5 reanalysis is used in the [50∘ N, 75∘ N] latitudinal belt for the period 1950–2019. The obtained results show an average reduction of FTF hours of 72.5 h/decade for all the domain, reaching a maximum decrease of 621 h/decade on the southeast coast of Greenland and a 60% annual reduction at a specific location in Scandinavia. In terms of AEP a maximum gain of more than 26% would be projected, as categorised by the the International Energy Agency.

Variability of the Southwestern Patagonia (51°S) Winds in the Recent (1980–2020) Period: Implications for Past Wind Reconstructions

The Southern Hemisphere Westerly Winds (SWW) control the amount and latitudinal distribution of rainfall in southwestern Patagonia. Recent studies have shown that SWW has intensified in the last decades, but their past behavior is not yet well understood. To understand this behavior, it is necessary to analyze climatic data from meteorological stations and reconstruct their variability through paleoclimatic evidence, such as lake cores. Nevertheless, Patagonia is an austral region characterized by its complex topography and quasi lack of a meteorological network. In this work, three reanalyses are studied (MERRA-2, ERA5, and GLDAS) and compared with the Cerro Castillo and Teniente Gallardo stations (~51°S), with the aim of simulating the winds in the past. The results indicate that ERA5 and MERRA-2 simulate well the wind variability in the study region, while GLDAS is less reliable. Therefore, the first two reanalyses could be used to extend the time series of the meteorological station and calibrate a new wind proxy based on the abundance and size of the aeolian particles, reconstructing in a direct way the intensity of the SWW in the past over southwestern Patagonia.

Uncertainty in Drought Identification Due to Data Choices, and the Value of Triangulation

Droughts are complex and gradually evolving conditions of extreme water deficits which can compromise livelihoods and ecological integrity, especially in fragile arid and semi-arid regions that depend on rainfed farming, such as Kitui West in south-eastern Kenya. Against the background of low ground-station density, 10 gridded rainfall products and four gridded temperature products were used to generate an ensemble of 40 calculations of the Standardized Precipitation Evapotranspiration Index (SPEI) to assess uncertainties in the onset, duration, and magnitude of past droughts. These uncertainties were driven more by variations between the rainfall products than variations between the temperature products. Remaining ambiguities in drought occurrence could be resolved by complementing the quantitative analysis with ground-based information from key informants engaged in disaster relief, effectively formulating an ensemble approach to SPEI-based drought identification to aid decision making. The reported trend towards drier conditions in Eastern Africa was confirmed for Kitui West by the majority of data products, whereby the rainfall effect on those increasingly dry conditions was subtler than just annual and seasonal declines and greater annual variation of rainfall, which requires further investigation. Nevertheless, the effects of increasing droughts are already felt on the ground and warrant decisive action.

Evaluation of ERA5 Precipitation Accuracy Based on Various Time Scales over Iran during 2000–2018

In regional studies, reanalysis datasets can extend precipitation time series with insufficient observations. In the present study, the ERA5 precipitation dataset was compared to observational datasets from meteorological stations in nine different precipitation zones of Iran (0.125° × 0.125° grid box) for the period 2000–2018, and measurement criteria and skill detection criteria were applied to analyze the datasets. The results of the daily analysis revealed that the correlation between ERA5 and observed precipitation were larger than 0.5 at 90% of stations. Also, The daily standard relative bias indicated that precipitation was overestimated in zone 6. As detection criteria, the frequency bias index (FBI) and proportion correct (PC) showed that the ERA5 data could capture daily precipitation events. Correlation confidence comparisons between the ERA5 and observational time series at daily, monthly, and seasonal scales revealed that the correlation confidence was higher at monthly and seasonal scales. The standard relative bias results at monthly and seasonal scales followed the daily relative bias results, and most of the ERA5 underestimations during the summer belonged to zone 1 in the coastal area of the Caspian Sea with convective precipitation. In addition, some complex mountainous regions were associated with overestimated precipitation, especially in northwest Iran (zone 6) in different time scales.

An Age Scale for the First Shallow (Sub-)Antarctic Ice Core from Young Island, Northwest Ross Sea

The climate of the sub-Antarctic is important in understanding the environmental conditions of Antarctica and the Southern Ocean. However, regional climate proxy records from this region are scarce. In this study, we present the stable water isotopes, major ion chemistry, and dust records from the first ice core from the (sub-)Antarctic Young Island. We present and discuss various dating approaches based on commonly used ice core proxies, such as stable water isotopes and seasonally deposited ions, together with site-specific characteristics such as melt layers. The dating approaches are compared with estimated precipitation rates from reanalysis data (ERA5) and volcanic cryptotephra shards likely presenting an absolute tie point from a 2001 CE eruption on neighboring Sturge Island. The resulting ice core age scale spans the period 2016 to 1995, with an uncertainty of ±2 years.

Spatiotemporal Dynamics of Snowline Altitude and Their Responses to Climate Change in the Tienshan Mountains, Central Asia, during 2001–2019

Snow cover is an important water resource in arid and semi-arid regions of Central Asia, and is related to agricultural and livestock production, ecosystems, and socio-economic development. The snowline altitude (SLA) is a significant indicator for monitoring the changes in snow cover in mountainous regions under the changing climate. Here, we investigate the spatiotemporal variation of SLA in the Tienshan Mountains (TS) during 2001–2019 using Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products on a grid-by-grid basis. The potential influence of topographic factors (slope gradient and aspect) on SLA and the correlation between SLA, temperature, precipitation, and solar radiation are also investigated. The results are as follows: (1) The annual cycle of SLA shows strong seasonal fluctuations (from about 2000 m in late December to 4100 m in early August). The SLA over the TS exhibits a large spatiotemporal heterogeneity. (2) SLA increases with a steeper slope gradient. The SLA of the northerly aspect is generally less than the southerly. (3) The SLA over the TS generally shows an increasing trend in the recent years (2001–2019). The change trend of SLA varies in different months. Except for a slight decrease in June, the SLA increased in almost all months, especially at the start of the melt season (March and April) and the end of melting season (July and August). (4) The SLA increases with increased temperature/radiation in the TS, and decreases with increased precipitation. Solar radiation is the dominant climatic factor affecting the changes of SLA in the TS. Compared with precipitation, temperature is more correlated to SLA dynamics.

Dynamical Downscaling of ERA5 Data on the North-Western Mediterranean Sea: From Atmosphere to High-Resolution Coastal Wave Climate

A 29-year wind/wave hindcast is produced over the Mediterranean Sea for the period 1990–2018. The dataset is obtained by downscaling the ERA5 global atmospheric reanalyses, which provide the initial and boundary conditions for a numerical chain based on limited-area weather and wave models: the BOLAM, MOLOCH and WaveWatch III (WW3) models. In the WW3 computational domain, an unstructured mesh is used. The variable resolutions reach up to 500 m along the coasts of the Ligurian and Tyrrhenian seas (Italy), the main objects of the study. The wind/wave hindcast is validated using observations from coastal weather stations and buoys. The wind validation provides velocity correlations between 0.45 and 0.76, while significant wave height correlations are much higher—between 0.89 and 0.96. The results are also compared to the original low-resolution ERA5 dataset, based on assimilated models. The comparison shows that the downscaling improves the hindcast reliability, particularly in the coastal regions, and especially with regard to wind and wave directions.

An Assessment of ERA5 Reanalysis for Antarctic Near-Surface Air Temperature

The European Center for Medium-Range Weather Forecasts (ECMWF) released its latest reanalysis dataset named ERA5 in 2017. To assess the performance of ERA5 in Antarctica, we compare the near-surface temperature data from ERA5 and ERA-Interim with the measured data from 41 weather stations. ERA5 has a strong linear relationship with monthly observations, and the statistical significant correlation coefficients (p < 0.05) are higher than 0.95 at all stations selected. The performance of ERA5 shows regional differences, and the correlations are high in West Antarctica and low in East Antarctica. Compared with ERA5, ERA-Interim has a slightly higher linear relationship with observations in the Antarctic Peninsula. ERA5 agrees well with the temperature observations in austral spring, with significant correlation coefficients higher than 0.90 and bias lower than 0.70 °C. The temperature trend from ERA5 is consistent with that from observations, in which a cooling trend dominates East Antarctica and West Antarctica, while a warming trend exists in the Antarctic Peninsula except during austral summer. Generally, ERA5 can effectively represent the temperature changes in Antarctica and its three subregions. Although ERA5 has bias, ERA5 can play an important role as a powerful tool to explore the climate change in Antarctica with sparse in situ observations.

Assessing Raspberry Shake and Boom Sensors for Recording African Elephant Acoustic Vocalizations

Acoustic sensors are increasingly being used in ecological and conservation research, but the choice of sensor can be fraught with trade-offs. In this work we assess the performance of the Raspberry Shake and Boom (RS&amp;B) sensor package for detecting and monitoring African elephants (Loxodonta africana). This is the first documented test of this particular unit for recording animal behavior; the unit was originally designed for detecting tectonic earthquakes and low frequency (&lt;50 Hz) atmospheric acoustics. During a four day deployment in South Africa we tested five RS&amp;B units for recording acoustic and seismic vocalizations generated by a group of African elephants. Our results highlight a varied degree of success in detecting the signals of interest. The acoustic microphone recorded fundamental frequencies of low-frequency (&lt;50 Hz) harmonic vocalizations that were not clearly recorded by more sensitive instruments, but was not able to record higher frequency harmonics due to the low sampling rate (100 Hz). The geophone was not able to consistently record clear seismic waves generated by vocalizations but was able to record higher harmonics. In addition, seismic signals were detected from footsteps of elephants at &lt;50 m distance. We conclude that the RS&amp;B unit currently shows limited potential as a monitoring tool for African elephants and we propose several future directions and deployment strategies to improve the sensitivity of the sensor package.

Global BROOK90 R Package: An Automatic Framework to Simulate the Water Balance at Any Location

The number of global open-source hydrometeorological datasets and models is large and growing. However, with a constantly growing demand for services and tools from stakeholders, not only in the water sector, we still lack simple solutions, which are easy to use for nonexperts. The new R package incorporates the BROOK90 hydrologic model and global open-source datasets used for parameterization and forcing. The aim is to estimate the vertical water fluxes within the soil–water–plant system of a single site or of a small catchment (<100 km2). This includes data scarce regions where no hydrometeorological measurements or reliable site characteristics can be obtained. The end-user only needs to provide a location and the desired period. The package automatically downloads the necessary datasets for elevation (Amazon Web Service Terrain Tiles), land cover (Copernicus: Land Cover 100 m), soil characteristics (ISRIC: SoilGrids250), and meteorological forcing (Copernicus: ERA5 reanalysis). Subsequently these datasets are processed, specific hydrotopes are created, and BROOK90 is applied. In a last step, the output data of all desired variables on a daily scale as well as time-series plots are stored. A first daily and monthly validation based on five catchments within various climate zones shows a decent representation of soil moisture, evapotranspiration, and runoff components. A considerably better performance is achieved for a monthly scale.

Evaluation of Near-Surface Wind Speed Changes during 1979 to 2011 over China Based on Five Reanalysis Datasets

Wind speed data derived from reanalysis datasets has been used in the plan and design of wind farms in China, but the quality of these kinds of data over China remains unknown. In this study, the performances of five sets of reanalysis data, including National Centers for Environmental Predictions (NCEP)-U.S. Department of Energy (DOE) Reanalysis 2 (NCEP-2), Modern-ERA Retrospective Analysis for Research and Applications (MERRA), Japanese 55-year Reanalysis Project (JRA-55), Interim ECMWF Re-Analysis product (ERA-Interim), and 20th Century Reanalysis (20CR) in reproducing the climatology, interannual variation, and long-term trend of near-surface (10 m above ground) wind speed, for the period of 1979–2011 over continental China are comprehensively evaluated. Compared to the gridded data compiled from meteorological stations, all five reanalysis datasets reasonably reproduce the spatial distribution of the climatology of near-surface wind speed, but underestimate the intensity of the near-surface wind speed in most regions except for Tibetan Plateau where the wind speed is overestimated. All five reanalysis datasets show large weaknesses in reproducing the annual cycle of near-surface wind speed averaged over the continental China. The near-surface wind speed derived from the observations exhibit significant decreasing trends over most parts of continental China during 1979 to 2011. Although the spatial patterns of the linear trends reproduced by reanalysis datasets are close to the observation, the magnitudes are weaker in annual, spring, summer and autumn season. The qualities of all reanalysis datasets are limited in winter. For the interannual variability, except for winter, all five reanalysis datasets reasonably reproduce the interannual standard deviation but with larger amplitude. Quantitative comparison indicates that among the five reanalysis datasets, the MERRA (JRA-55) shows the relatively highest (lowest) skill in terms of the climatology and linear trend. These results call for emergent needs for developing high quality reanalysis data that can be used in wind resource assessment and planning.