Reanalysis Products Research Articles

Influence of New Parameterization Schemes on Arctic Sea Ice Simulation

Two coupled climate models that participated in the CMIP6 project (Coupled Model Intercomparison Project Phase 6), the Earth System Model of Chinese Academy of Sciences version 2 (CAS-ESM2-0), and the Nanjing University of Information Science and Technology Earth System Model version 3 (NESM3) were assessed in terms of the impact of four new sea ice parameterization schemes. These four new schemes are related to air–ice heat flux, radiation penetration and absorption, melt ponds, and ice–ocean flux, respectively. To evaluate the effectiveness of these schemes, key sea ice variables with and without these new schemes, such as sea ice concentration (SIC) and sea ice thickness (SIT), were compared against observation and reanalysis products from 1980 to 2014. The simulations followed the design of historical experiments within the CMIP6 framework. The results revealed that both models demonstrated improvements in simulating Arctic SIC and SIT when the new parameterization schemes were implemented. The model bias of SIC in some marginal sea ice zones of the Arctic was reduced, especially during March. The SIT was increased and the transpolar gradient of SIT was reproduced. The changes in spatial patterns of SIC and SIT after adding new schemes bear similarities between the two coupled models. This suggests that the new schemes have the potential for broad application in climate models for simulation and future climate scenario projection, especially for those with underestimated SIT.

Impact of the Kuroshio large meander on local atmospheric circulation and precipitation in winter

The Kuroshio, which flows to the south of Japan, typically takes two paths on decadal timescales; the straight path and the large meander path, or the so-called Kuroshio large meander. This phenomenon is characterized by the presence of the cyclonic cold-core eddy located south of Japan, which leads to both negative and positive sea surface temperature (SST) anomalies along the southeastern coast of Japan. To clarify the atmospheric response to these SST anomalies in winter, we conducted a control experiment employing a regional atmospheric model with observed SSTs and two sensitivity experiments in which the SST boundary conditions were substituted with those corresponding to the periods of for the Kuroshio large meander and the straight path. The differences in these two sensitivity experiments showed that the surface wind response to the SST anomalies associated with the Kuroshio large meander was not only characterized by wind divergence over the cyclonic cold-core eddy, as reported previously but also wind convergence along the southeastern coast of Japan. Interestingly, this wind anomaly blew into the positive SST anomaly along the east coast of Japan at around 36°N. Similar wind anomalies along the east coast of Japan were observed in a reanalysis product. The results of the model simulation and the reanalysis product showed that during the Kuroshio large meander period, the number of rainy days increased significantly over the warm SST anomaly, while the precipitation and the number of rainy days decreased over the cyclonic cold-core eddy. Moisture budget analysis revealed that the observed decrease in precipitation was attributed to the disparity between the reduced evaporation and the anomalous horizontal moisture convergence in a region where the surface winds were divergent. This moisture convergence was mainly induced by a decrease in specific humidity, implying this change in specific humidity effectively mitigated the variation in precipitation.

CloudSat Observations Show Enhanced Moisture Transport Events Increase Snowfall Rate and Frequency Over Antarctic Ice Sheet Basins

AbstractElevated moisture transport over the Antarctic ice sheet can increase snowfall and ice mass. Previous studies used ground‐based observations, reanalysis products, and atmospheric models to evaluate the relationship between extreme moisture transport and snowfall properties. Here, we build on previous studies by combining reanalysis and CloudSat radar snowfall retrievals to examine impacts of extreme moisture intrusions on changes in snowfall frequency and intensity over glacier basins on the Antarctic ice sheet. We examine the impacts of enhanced moisture transport events on snowfall frequency and intensity over two different regions on the Antarctic ice sheet: the Amery Ice Shelf of East Antarctica and the Thwaites and Pine Island glacier basins of West Antarctica. We determine when the median integrated water vapor transport from reanalysis exceeds the 95th percentile within the glacier basins of interest to define enhanced moisture transport events. We then use CloudSat radar snowfall retrievals to evaluate differences between snowfall frequency and intensity during enhanced water vapor transport events compared to the seasonal means for 2007–2010. We find that enhanced moisture transport events over the Amery Ice Shelf and Thwaites and Pine Island glacier basins coincide with higher snowfall frequency and intensity. These enhanced moisture transport events have the potential to alter surface mass balance within glacier basins, with implications for future rates of sea level rise.

Reconstructing monthly 0.25° terrestrial evapotranspiration data in a remote arid region using Bayesian-driven ensemble learning method

This study presents a Bayesian-driven ensemble learning framework to minimize errors in evapotranspiration (ET) data assimilation, thereby generating a continuous-scale ET estimation with improved accuracy for the data-scarce arid Central Asia (CA). Five state-of-the-art gridded ET products were extensively tested and utilized to reconstruct new long-term ET data at grid scale, including two Global Land Data Assimilation System (GLDAS)-Land Surface Models (LSM) (Catchment and NOAH), two reanalysis products (European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) and Modern-Era Retrospective Analysis for Research and Applications – ver. 2 (MERRA2)), along with the Global Land Evaporation Amsterdam (GLEAM) satellite ET product ver. 3.6b. Taylor Skill Score was employed to evaluate the input gridded ET datasets, using in situ measurements across four arid biomes — cropland, shrubland, farmland, and grassland —as benchmarks. Bayes-Markov Chain Monte Carlo (Bayes-MCMC)-derived logarithmically transformed predictors from the posterior ensemble anomalies were standardized to resolve the mismatches in the cumulative distribution functions of ET data relating to the in situ observations. We found that the constrained residual errors were more profound between 45th and 95th percentiles for the rescaled total ET anomalies across all the input ET datasets at 95 % confidence interval. Moreover, the weighted ensemble estimates derived from the Bayes-MCMC were instrumental in correcting ET anomalies, leading to the robust reconstruction of a more reliable ensemble mean ET data for Central Asia (CAETens) at monthly temporal and 0.25° spatial resolutions, spanning from 2003 to 2020. Overall, CAETens exhibited superior performance, achieving the highest averaged Kling-Gupta Efficiency of 0.75 and registering the lowest Root Mean Square Error of 6.85 mm/m compared to the standalone gridded ET products. Comparisons of spatial distributions of fine-scale features, and evaluations using standard metrics revealed that all ET products varied significantly (p < 0.05) by biome types. Remarkably, only CAETens exhibited a reasonable low positive bias and pronounced ability to resolve the complex spatiotemporal patterns associated with the input gridded ET products. The study bridges the gap in continuous ET monitoring for sustainable water resources management in CA.

Intercomparison of tropical Indian Ocean circulation in ocean reanalysis and evaluation in CMIP6 climate models

In the present study, we assess the Tropical Indian Ocean (TIO) circulation features from the available ocean reanalysis products and the latest version of Coupled Model Intercomparison Project (CMIP6) climate model simulations. We considered the following reanalysis products; Ocean Reanalysis System 5 (ORAS5), Estimating the Circulation and Climate of the Ocean (ECCO), Global Ocean Data Assimilation System (GODAS), Ensemble Coupled Data Assimilation (ECDA), the Bluelink Reanalysis (BRAN) and Simple Ocean Data Assimilation (SODA) and compared them against in-situ observations and the satellite-derived Ocean Surface Current Analyses Real-time (OSCAR). The reanalysis products underestimate the strength and location of the Wyrtki Jets. The BRAN reanalysis performed well compared to the other products in representing the TIO surface zonal currents, followed by ORAS5. The vertical extension of subsurface zonal currents in the equatorial Indian Ocean and their seasonal maxima are well captured in ORAS5. Thus, our analysis suggests that the ORAS5 is a qualitative product to estimate the TIO circulation. We further evaluated the TIO current patterns simulated by CMIP6 models with in-situ data/ ORAS5. The majority of the models show discrepancies in simulating equatorial and south equatorial current systems with a mean bias of 0.1cms−1 and 0.2cms−1, respectively. NorESM2-MM, NorESM2-LM, CanESM5, CESM2-WACCM-FV2, and E3SM-1-ECA models showed a superior skill in reproducing the TIO circulation compared to the rest of the models. Our analysis highlights the importance of assessing various reanalysis products and coupled climate models in representing the circulation of the TIO and, consequently, their role in depicting regional weather and climate.

Drivers of Laptev Sea interannual variability in salinity and temperature

Abstract. Eurasian rivers provide a quarter of total fresh water to the Arctic, maintaining a persistent fresh layer that covers the surface Arctic Ocean. This freshwater export controls Arctic Ocean stratification, circulation, and basin-wide sea ice concentration. The Lena River supplies the largest volume of runoff and plays a key role in this system, as runoff outflows into the Laptev Sea as a particularly shallow plume. Previous in situ and modelling studies suggest that local wind forcing is a driver of variability in Laptev sea surface salinity (SSS) but there is no consensus on the roles of Lena River discharge and sea ice cover in contributing to this variability or on the dominant driver of variability. Until recently, satellite SSS retrievals were insufficiently accurate for use in the Arctic. However, retreating sea ice cover and continuous progress in satellite product development have significantly improved SSS retrievals, giving satellite SSS data true potential in the Arctic. In this region, satellite-based SSS is found to agree well with in situ data (r&gt;0.8) and provides notable improvements compared to the reanalysis product used in this study (r&gt;0.7) in capturing patterns and variability observed in in situ data. This study demonstrates a novel method of identifying the dominant drivers of interannual variability in Laptev Sea dynamics within reanalysis products and testing if these relationships appear to hold in satellite-based SSS, sea surface temperature (SST) data, and in situ observations. The satellite SSS data firmly establish what is suggested by reanalysis products and what has previously been subject to debate due to the limited years and locations analysed with in situ data; the zonal wind is the dominant driver of offshore or onshore Lena River plume transport. The eastward wind confines the plume to the southern Laptev Sea and drives alongshore transport into the East Siberian Sea, and westward wind drives offshore plume transport into the northern Laptev Sea. This finding is affirmed by the strong agreement in SSS pattern under eastward and westward wind regimes in all reanalyses and satellite products used in this study, as well as with in situ data. The pattern of SST also varies with the zonal wind component and drives spatial variability in sea ice concentration.

Spurious Trends in High Latitude Southern Hemisphere Precipitation Observations

AbstractThe high latitude Southern Hemisphere (SH) is an important region for Earth's climate. Ocean heat content, cryosphere interactions, Antarctic bottom water development and the cloud‐albedo feedbacks need to be understood to form a complete picture of the climate system. However, the high latitude SH is one of the most under‐observed regions due to its remoteness. The advent of satellites and reanalyses have improved our monitoring of this region. Some previous studies observed an increase in precipitation over the SH high latitudes, however we argue that some of the trends in commonly used data sets may be artifacts. We use regression analysis of trends in precipitation and the Southern Annular Mode to contrast these relationships in satellite and reanalysis products, and to evaluate precipitation over the SH. We suggest that sensor changes and the lack of in situ data available for calibration may be responsible for unusual precipitation patterns especially around 65°S.

Transformation of the atlantic water between svalbard and Franz Joseph Land in the late winter 2018–2019

An inflow of warm and salty Atlantic origin waters (AW) from the Nordic Seas to the Arctic Ocean interior is in the list of the major external factors, which control the hydrologic regime of the East-Atlantic sector of the Arctic Ocean. Rapid decay of the sea ice cover in 2000–2010s raised questions on the possible changes in the fate of the inflow under present ice-depleted conditions: whether warm and salty AW will cool and freshen slower (due to less ice to be melted underway), or intensified heat loss to the atmosphere through the open surface will lead to the faster AW cooling on shorter distance? We present rare hydrologic data, collected during the late winter 2019 in the international expedition “Transarktika-2019” in the northern part of the Barents Sea and at the adjoining continental slope of the Nansen Basin. On the basis of field data, supported by the oceanic reanalysis product and numerical modelling we have studied the transformation of AW on its transit between Svalbard and Franz Joseph Land. We show that the observed cooling and desalination of the fraction of AW over the continental slope around this area is controlled by lateral mixing with colder and fresher waters, outflowing from cross-slope canyons, which cut the continental slope: Kvitøya Trough, Franz Victoria Trough and probably, the British Channel. The obtained results demonstrate more intensive transformation of AW on this transit compared to previous studies. Possible explanations of this contrast, which are supported by the earlier studies, may include: the season of the survey when dense water outflow through canyons is at its maximum and gradual “atlantification” of the East-Atlantic sector of the Arctic Ocean, which favours intensification of dense water formation in winter polynyas under conditions of increased seasonality of sea ice. In the latter case, faster cooling and desalination of AW en route in this part of the Arctic Ocean may be considered as a reasonable hypothesis, provided the atlantification of the Nansen Basin is progressing.

Sea ice cover in the Copernicus Arctic Regional Reanalysis

Abstract. The Copernicus Arctic Regional Reanalysis (CARRA) is a novel regional high-resolution atmospheric reanalysis product that covers a considerable part of the European Arctic including substantial amounts of ice-covered areas. Sea ice in CARRA is modelled by means of a one-dimensional thermodynamic sea ice parameterisation scheme, which also explicitly resolves the evolution of the snow layer over sea ice. In the present study, we assess the representation of sea ice cover in CARRA and validate it against a wide set of satellite products and observations from ice mass balance buoys. We show that CARRA adequately represents general interannual trends towards thinner and warmer ice in the Arctic. Compared to ERA5, sea ice in CARRA shows a reduced warm bias in the ice surface temperature. The strongest improvement was observed for winter months over the central Arctic and the Greenland and Barents seas where a 4.91 °C median ice surface temperature error in ERA5 is reduced to 1.88 °C in CARRA on average. Over Baffin Bay, intercomparisons suggest the presence of a cold winter-time ice surface temperature bias in CARRA. No improvement over ERA5 was found in the ice surface albedo with spring-time errors in CARRA being up to 0.08 higher on average than those in ERA5 when computed against the CLARA-A2 satellite retrieval product. Summer-time ice surface albedos are comparable in CARRA and ERA5. Sea ice thickness and snow depth in CARRA adequately resolve the annual cycle of sea ice cover in the Arctic and bring added value compared to ERA5. However, limitations of CARRA indicate potential benefits of utilising more advanced approaches for representing sea ice cover in next-generation reanalyses.

Efficiency of global precipitation datasets in tropical and subtropical catchments revealed by large sampling hydrological modelling

Satellite-based and reanalysis precipitation products are widely adopted as complementary information to in situ measurements for estimating river discharge using hydrological modelling. However, there is still a notable research gap in the literature associated with assessing the accuracy of satellite-based or reanalysis products in different tropical and sub-tropical catchments at large-sampling hydrological modelling with sensitivity analysis. We investigated the accuracy of precipitation, hydrological model performance and parameter sensitivity related to seven precipitation data sets based on satellite and reanalysis products, i.e., CHIRPS, TRMM, GLDAS, IMERG, MERRA-2, PERSIANN-CDR, and ERA5 over 714 contrasting tropical and subtropical catchments located in Brazil. We used the Génie Rural Journalier 4 (GR4J) hydrological model to simulate the hydrological processes of the different catchments with two approaches for the calibration: using measured ground-based precipitation data (approach I) or using each individual satellite/reanalysis precipitation products (approach II) to calibrate the models. The results showed that the precipitation products tend to overestimate precipitation, with the exception of ERA5 and MERRA-2. CHIRPS is the only product that produces unbiased precipitation estimates for most catchments. The model calibration using each precipitation product individually improved the hydrological model performance. CHIRPS, IMERG, and MERRA-2 showed good accuracy in terms of both, precipitation estimation and hydrological simulation performance in the calibration period. In the validation period, the best products in terms of KGE were CHIRPS, IMERG and TRMM (KGE > 0.64). The errors in precipitation products are better compensated via hydrological modelling in wet regions. The model parameter sensitivity varies according to precipitation input, climate, and catchment aridity. Overall, all seven products exhibited their worst hydrological performance in arid regions. This study helps to improve our understanding of the catchment response in tropical and subtropical regions while also providing key insights into the reliability of satellite/reanalysis rainfall products for streamflow simulation. This study is valuable in hydrometeorological applications, climate change assessment, water resources and disaster management, especially in regions with a relatively sparse density of precipitation stations.

Can the aerosol pollution extreme events be revealed by global reanalysis products?

Extreme aerosol pollution poses significant risks to the climate, environment, and human health. To investigate the formation and impacts of aerosol pollution extreme events (APEE), the reanalysis product presents meticulous spatiotemporal information on the three-dimensional distribution of aerosols. However, there is a lack of comprehensive evaluation and information regarding the data quality of reanalysis products employed in APEE research, as well as limited understanding of their spatial and temporal distribution, variation, and long-term trends. To address this scientific gap, we conducted a global study for distribution and variation patterns of APEE using two widely-used reanalysis products, MERRA-2 (Modern-Era Retrospective Analysis for Research-2) and CAMS (Copernicus Atmospheric Monitoring Service). The APEE was defined here as a day when the daily aerosol optical depth (AOD) exceeding its 90th percentile for a given station and month. Eleven distinct land regions worldwide were selected for evaluation by comparing both reanalysis products with MODIS satellite products and ground-based observations in terms of frequency, intensity, and temporal trends of APEE. The analysis indicates that MERRA-2 and CAMS exhibit high matching rates (70 % and 80 %, respectively) in terms of occurrence timeline for APEE at monthly and seasonal scales, while also exhibiting strong monthly correlation coefficients (>0.65) with ground-based observations over selected regions. The total AOD (−0.002 ∼ −0.123 decade−1), APEE AOD (−0.004 ∼ −0.293 decade−1), and APEE frequency (−0.264 ∼ −1.769 day month−1 decade−1) of both observations and reanalysis products in most regions showed a decreasing trend with various magnitude, except for some regions such as South Asia where the trend is increasing. Based on the aforementioned evaluation, it is evident that reanalysis products are effective and useful in identifying the temporal trends associated with APEE.

A Global Coupled Atmosphere-Wave Model System Based on C-Coupler2. Part II: Preliminary Results

A global coupled atmosphere-wave model system (MPAS-NWW3) that consists of MPAS-A (Model for Prediction Across Scales-Atmosphere) and NWW3 (the Third Generation Wave Model, WAVEWATHCH III) with C-Coupler2 (the Community Coupler2) is demonstrated with a focus on the atmospheric results in global and the specific marine area in the year 2020. Results from the two-way coupled MPAS-NWW3 model and standalone MPAS-A are compared with reanalysis products. The coupled model performs better in terms of high wind speeds and long valid hours. This indicates that the coupled model has an obvious inhibitory effect on surface wind in areas with strong winds.

Evaluation of Multisource Datasets in Characterizing Spatiotemporal Characteristics of Extreme Precipitation from 2001 to 2019 in China

Abstract The spatiotemporal characteristics of extreme precipitation intensity are crucial for hydroclimatic studies. This study delineates the spatiotemporal distribution features of extreme precipitation intensity across China from 2001 to 2019 using the gridded daily precipitation dataset CN05.1, constructed from an observation network of over 2400 stations. Furthermore, we evaluate the reliability of 12 widely used precipitation datasets (including gauge-based, satellite retrieval, reanalysis, and fusion products) in monitoring extreme precipitation events. Our findings indicate the following: 1) CN05.1 reveals a consistent spatial distribution characterized by a decline in extreme precipitation intensity from the southeastern coastal regions toward the northwestern inland areas of China. From 2001 to 2019, more pronounced declining intensity trends are discernible in the northern and southwestern regions of China, whereas marked increasing trends manifest in the northeastern and the Yangtze River plain regions. National mean extreme precipitation indices consistently exhibit significant increasing trends throughout China. 2) Datasets based on station observations generally exhibit superior applicability concerning spatiotemporal distribution. 3) Multisource weighted precipitation fusion products effectively capture the temporal variability of extreme precipitation indices. 4) Satellite retrieval datasets exhibit notable performance disparities in representing various intensity indices. Most products tend to overestimate the increasing trends of national mean intensity indices. 5) Reanalysis datasets tend to overestimate extreme precipitation indices, and inadequately capture the trends. ERA5 and JRA-55 underestimate trends, while CFSR and MERRA-2 significantly overestimate the trends. These findings serve as a basis for selecting reliable precipitation datasets for extreme precipitation and hydrological simulation research in China. Significance Statement Extreme precipitation events have increasingly become more widespread, posing significant threats to human lives and property. Accurately understanding the spatiotemporal patterns of these events is imperative for effective mitigation. Despite the proliferation of precipitation products, their capacity to faithfully represent extreme events remains inadequately validated. In this study, we utilize a gauge-based dataset derived from over 2400 gauge stations across China to investigate the spatiotemporal changes in extreme precipitation events from 2001 to 2019. Subsequently, we conduct a rigorous evaluation of 12 widely used precipitation datasets to assess their efficacy in depicting extreme events. The results of this research offer valuable insights into the strengths and weaknesses of various precipitation products in depicting extreme events.

The impact of energy storage on the reliability of wind and solar power in New England

In this study, the potential of wind and solar power to reliably meet the electricity demand of New England is evaluated, as well as the role of energy storage in improving the reliability of the region's renewable energy system. Using 44 years of hourly weather data from 1980 to 2023 obtained from the NASA MERRA-2 reanalysis product, the variability of these renewable resources and their impact on the region's electricity supply and demand is investigated. With varying mixes of wind and solar resources and sufficient resources capacity to generate electricity equal to annual demand, we find that a wind-dominant system can meet approximately 73% of the region's hourly electricity demand, whereas a solar-dominant system can only meet about 69%. However, incorporating 12 h of energy storage enhances the overall reliability of a wind-dominant system to 86%. In comparison, incorporating the same amount of energy storage in a solar-dominant system results in an overall reliability of approximately 87%. Ultimately, our analysis shows that achieving 100% reliability in meeting the annual electricity demand of New England requires addressing the mismatch between electricity demand and resource availability in terms of both location and time. This can be achieved through the integration of significant amounts of energy storage and/or wind and solar resources installations capable of generating electricity that exceeds peak demand by at least 3 times.

An interpretation experiment on eddies’ role in sound propagation in the ocean using ray model

The relationship between mesoscale eddies and ambient acoustic propagation under different conditions were studied using high resolution ocean reanalysis products in South China Sea, which was summarized by a linear-equation representing the convergence zone change with respect to eddy signatures and source positions. Beyond the experiments scales, warm eddies “dragged” the sound propagation and cold eddies “squeezed” that in contrast, and the acoustic amplifying mechanism can be summarized as stronger(eddies), nearer(eddies) and deeper(source).

Intrathermocline Eddy with Lens-Shaped Low Potential Vorticity and Diabatic Forcing Mechanism in the South China Sea

Abstract Intrathermocline eddies (ITEs), characterized by subsurface lens-shaped low potential vorticity (PV), are pervasive in the ocean. However, the abundance and generation mechanisms of these low-PV lenses are poorly understood owing to their weak surface signals and awkward sizes, which present an observational barrier. Using in situ observations of the northern South China Sea (NSCS), a typical ITE with a lens-shaped low PV at a core depth of 30–150 m and a horizontal size of ∼150 km was captured in May 2021. Combined with PV budget analysis, we investigate the underlying generation mechanism of low PVs within these ITEs using high-resolution reanalysis products. The results suggest that wintertime surface buoyancy loss driven by atmospheric diabatic forcing rather than frictional forcing is a crucial favorable condition for the ITE formation. These enhanced surface buoyancy losses produce a net upward PV flux and decrease PV in the weakly stratified and deep winter mixed layer, which are preconditioned by anticyclonic eddies (AEs). While surface heating in the following spring tends to weaken the surface buoyancy loss and gradually causes a downward PV flux, the surface-injected high PV subsequently caps the low-PV water within the surface-intensified AEs and transforms them into ITEs. Approximately 22% of the 58 AEs detected by satellite altimetry in the NSCS are ITEs. More importantly, the lens-shaped low PVs within them are produced primarily by the enhanced surface buoyancy loss during wintertime. These findings provide a new dynamic explanation for the low-PV generation in ITEs, highlighting the crucial role of atmospheric diabatic forcing. Significance Statement Intrathermocline eddies (ITEs), characterized by a lens-like isopycnal structure that bounds low potential vorticity (PV), are active in the oceanic interior. Although a few previous studies revealed the existence of ITEs in the South China Sea, the source and dynamic generation mechanisms of the lens-shaped low PV still remain elusive. We find that the enhanced surface buoyancy loss due to atmospheric diabatic forcing drives an upward surface PV flux and is identified to produce the low PV. The preexisting anticyclonic eddy, combined with seasonal surface heating in spring, can be easily transformed into the ITE. This study provides a new dynamic understanding for the generation mechanism of ITEs’ low PVs and highlights the contribution of atmospheric diabatic forcing.

Validation of global precipitation time series products against tree ring records and remotely sensed vegetation greenness.

Global interpolated climate products are widely used in ecological research to investigate biosphere-climate interactions and to track ecological response to climate variability and climate change. In turn, biological data could also be used for an independent validation of one aspect of climate data quality. All else being equal, more variance explained in biological data identifies the better climate data product. Here, we compare seven global precipitation time series products, including gauge-based datasets (CRU-TS, UDEL-TS, GPCC), re-analysis products (ERA5, CHELSA), a satellite-based dataset (PERSIANN) and a multi-source product that draws on gauge, re-analysis, and satellite data (MSWEP). We focus on precipitation variables, because they are more difficult to interpolate than temperature, and show larger divergence among gridded data products. Our validation is based on 20 years of remotely sensed vegetation greenness (MODIS-EVI) and 120 years of tree ring records from the International Tree Ring Data Bank (ITRDB). The results for the 20-year EVI based validation shows that all gauge and re-analysis data products performed similarly, but were outperformed by the multi-source MSWEP product, especially in regions with low weather station coverage, such as Africa. For analyzing long 120-year time-series, UDEL-TS showed superior performance prior to the 1940s, with especially large margins for northern Asia and the Himalayas region. For other regions, CRU-TS and GPCC could be recommended. We provide maps that can guide the best regional choice of climate product for research involving time series of biological response to historic climate variability and climate change.

High-resolution land surface modeling of the irrigation effects on evapotranspiration over the Yellow River basin

Accurate estimation of irrigation-induced evapotranspiration (ET) is critical for understanding the terrestrial water cycle. However, current estimation has large uncertainties due to the model limitations and the lack of accurate water use data. In this study, a water-energy balanced irrigation scheme is incorporated into the Conjunctive Surface-Subsurface Process version 2 (CSSPv2) model to improve the hydrological simulations over the Yellow River basin (YRB) where irrigation is extensive. The coupled model (CSSPv2-IRR) is calibrated against long-term water use data from provincial survey, and it is used to perform a 6-km resolution simulation over the YRB during 1991–2017. The results show that the coupled model can well reproduce hydrological processes within the basin, and the simulated irrigation amount, ET and surface soil moisture largely agree with the validation datasets. Specifically, the annual irrigation amount and irrigation-induced ET changes from the CSSPv2-IRR are more reasonable than ISIMIP2a and reanalysis products, with a reduction in bias by 79.5–97.3 % and 81.2–98.8 % respectively. The CSSPv2-IRR model simulation suggests that irrigation-induced annual ET change is 26.4 mm/year during 1991–2017, contributing to an 8.9 % increase in annual ET over the YRB, and the increase can reach 44.3 % over major irrigation districts. In addition, the contribution of irrigation to long-term increasing trend in ET over the irrigation districts in the upper reach is greater than the contribution of climate change. This study suggests a growing control of irrigation on the ET over the YRB, which has implications for regional water cycle and water resources management.

Suitability of ERA5-Land reanalysis dataset for hydrological modelling in the Alpine region

Study region: The region of interest is the South-Tyrol in the southeastern Alps, Italy. A comparison of meteorological forcing is performed with reference to this region while hydrological simulations are conducted in the Passirio river basin.Study focus: The objective of this work is to evaluate the suitability of ERA5-Land reanalysis product as a reference dataset for hydrological modelling in topographically complex Alpine regions. ERA5-Land is compared with observational gridded dataset, obtained by means of the Kriging interpolation, available at two contrasting spatial resolutions a coarse grid size of 11 × 8 kilometres and a high-resolution grid size 1 × 1 kilometres. The hydrological coherence of the three datasets (ERA5-Land and the two observational datasets) with observed streamflow time series is then assessed with refer the Passirio/Passer river basin and to its nested and snow-dominated sub-catchment Plan/Pfelders.New hydrological insights for the region: The study assesses ERA5-Land’s suitability for hydrological simulations in the South-Tyrol region by comparing streamflow outcomes. At the annual scale, an overestimation of precipitation of about 40mm/month and a temperature underestimation of about 2.1 °C is reported. These discrepancies influence hydrological simulations, resulting in an overestimation of both streamflow and snow water equivalent. It is thus crucial to consider the limitations of ERA5-Land when using it as forcing for hydrological application in watersheds characterized by complex terrains, such as Alpine region.

Synoptic weather patterns during fire spread events in Siberia

Several recent studies have indicated a strong relationship between extensive wildfires in Siberia and synoptic-scale weather processes. In this study, we used the concept of fire spread events to investigate the relationships between synoptic and surface-level weather conditions and extensive wildfires in Siberia during 2001–2022 using the MODIS and ERA5 reanalysis products. We analyzed the spatio-temporal features and seasonality of fire spread events in the region and found that most of them occurred in the central part of Eastern Siberia (ES) during the summer months, following the wildfire season in the region. A significant positive trend in the annual count of fire spread events was found in ES, coinciding with non-significant negative trends in cloud cover and precipitation and non-significant positive trends in air temperature and the fire weather index. Results show that in the ES region, which accounts for 46 % of the total number of considered events, the main driver of fire spread events is the formation of a positive geopotential height anomaly, which, based on the pattern of the meridional wind component, indicates the presence of an anticyclone above the area of fire spread events. The presence of a high-pressure zone causes a decrease in cloud cover over regions with fires, leading to increases in the amount of incoming solar radiation and surface air temperature and a decrease in precipitation. These conditions contribute to the drying of fuel and an increase in the overall fire hazard level, which in turn leads to an intensification of the combustion process, as evidenced by an increase in the radiative power of fires.