High-resolution Reanalysis Dataset Research Articles

Remote Midlatitude Control of Rainfall Onset at the Southern African Tropical Edge

Abstract Rainfall over the southern African tropical boundary is highly variable, particularly around the onset of the summer rains. However, understanding of the causes of variability in onset timing is poor. A lack of observational data in the region is compounded by the complexity of climate dynamics and variability at the interface of the tropics and the midlatitudes. The key to onset over the region is the Congo air boundary (CAB), a distinguishing circulation feature present in September and declining in frequency until November. The CAB is crucial to early season rainfall; precipitation is broadly inhibited when the CAB is present, while its breakdown allows large-scale rainfall and onset over central southern Africa. This work identifies a remote midlatitude influence on the timing of CAB breakdown using the high-resolution reanalysis dataset ERA5. Propagating and (upstream) breaking low-wavenumber Rossby waves in the Southern Hemisphere westerly jet are shown to be related to >70% of breakdown events. Breakdown is forced by 1) the replacement of subsidence over eastern southern Africa with synoptically forced ascent and 2) wind field modification that leads to positive 850-hPa continental convergence anomalies and enhanced moisture advection from the Congo basin and Indian Ocean. Upper-level anticyclonic vorticity tendency induced by enhanced convection slows Rossby wave propagation aloft, contributing to wave breaking and the persistence of conditions favorable to convection. The identification of this midlatitude influence on CAB breakdown reveals new potential sources of predictability for onset and demonstrates the significant equatorward extent of midlatitude influences to the tropical edge. Significance Statement This study aims to improve our understanding of the causes of variability in the start date of the summer rainy season in central southern Africa. The research reveals that certain upper-level waves in the Southern Hemisphere westerly jet are associated with patterns of weather that force a large-scale transition from dry pre-onset conditions to widespread rainfall in a time scale of 2–5 days, and that these waves account for a large proportion of such transitions. This finding is of interest to subseasonal weather forecasters and may help to improve the long-range forecasting of onset date.

Performance Evaluation of High-resolution Reanalysis Datasets Over North-central British Columbia

abstract Version 2.1 of Environment and Climate Change Canada’s Canadian Surface Reanalysis (CaSR), based on the Regional Deterministic Reforecast System (RDRS), was implemented in 2022 to provide temporally complete meteorological data over 1980–2018 covering Canada at 10 km spatial resolution. Similarly, the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Land (ERA5-Land) dataset at ∼9 km spatial resolution became available. To assess their performance in complex topography, this paper undertakes spatiotemporal inter-comparisons between the RDRS and ERA5-Land reanalysis products with station-based data across British Columbia’s Skeena and Nechako watersheds for 1980–2018. Results reveal persistent cold biases, ranging from −6.2°C to −1.6°C basin-wide, in reanalysis mean annual air temperatures relative to observations, but biases vary in both space and time. Conversely, reanalysis total annual precipitation shows wet biases, ranging from 25% to 59% basin-wide. Analyses generally show wetting trends for observations and ERA5-Land while RDRS exhibits drying trends. Reanalysis datasets achieve better agreement overall with observations over the Nechako Watershed, likely due to its denser network of meteorological stations and less complex terrain than the Skeena Watershed. Despite some deficiencies, the RDRS and ERA5-Land reanalyses remain particularly useful products to assess regional climate variability and climatic change given their generally skilful representation of spatial patterns and temporal trends in meteorological variables across the Nechako and Skeena watersheds.

Assessment of the spatiotemporal variability of seawater temperature and salinity in the Yellow and Bohai seas from multiple high-resolution reanalysis datasets

Assessment of the spatiotemporal variability of seawater temperature and salinity in the Yellow and Bohai seas from multiple high-resolution reanalysis datasets

Studying the evolution of Uttarkashi cloudburst event from reanalysis datasets–A case study

In recent years, the frequency and severity of cloudburst considerably increased over southern rim of Himalayas due to hot climate that leads to loss of human lives and damage properties. The observed rainfall data shows that cloudburst events with heavy rainfall ∼ 100–200 mm/day are common over the Himalayan region during the summer monsoon period. It is very necessary to understand the mechanisms associated with such type of short span of high impact localised weather events over the regions where observations are limited. Therefore, one of best way to study the mechanism associated with the formation and development of cloudburst is using the available high resolution reanalysis datasets. An effort is made to understand the role of atmospheric conditions that control the evolution of cloudburst event by considering two reanalyses datasets such as high resolution IMDAA and ERA5 reanalyses. The present study analysed a cloudburst case that occurred on 3rd August 2012 at 10 pm with heavy rainfall of ∼ 100 mm in a very short span of time over the Uttarkashi district. Various dynamic and thermodynamic parameters are calculated from the two datasets with an aim of determining the best representation of severity of the cloudburst event. It is noticed that the evolution of dynamic and thermodynamic variables is well represented in the high resolution IMDAA dataset as compared to the ERA5 dataset. The amount and spatial distribution of rainfall from IMDAA reanalyses are well comparable with satellite estimated rainfall (GPM), having better correlation (0.60) with the observed rainfall as compared to the ERA5 (0.28). The rainfall time bias over the Uttarkashi district is larger in ERA5 reanalyses (∼ 5 h) than in the IMDAA (∼ 3 h). The ERA5 is not able to capture such type of localise high rainfall event due to its low resolution, compared to high resolution reanalyses (12 km) of IMDAA. The observations also indicate that the moisture flux from the Bay of Bengal (BoB) and Arabian Sea interacted with northwesterly dry air over Uttarkashi and the orographic uplifting resulted the cloudburst. Overall, results show that the eveolution and mechanism associated with the cloudburst is better represented in IMDAA than the ERA5. More cases are required to be studied to further support the findings of this study.

Relative importance of ENSO and IOD on interannual variability of Indonesian Throughflow transport

IntroductionThe Indonesian Throughflow (ITF) connects the Pacific Ocean and the Indian Ocean. It plays an important role in the global ocean circulation system. The interannual variability of ITF transport is largely modulated by climate modes, such as Central-Pacific (CP) and Eastern-Pacific (EP) El Niño and Indian Ocean Dipole (IOD). However, the relative importance of these climate modes importing on the ITF is not well clarified.MethodsDominant roles of the climate modes on ITF in specific periods are quantified by combining a machine learning algorithm of the random forest (RF) model with a variety of reanalysis datasets.ResultsThe results reveal that during the period from 1993 to 2019, the average ITF transport derived from high-resolution reanalysis datasets is -14.97 Sv with an intensification trend of -0.06 Sv year-1, which mainly occurred in the upper layer. Four periods, which are 1993–2000, 2002–2008, 2009–2012 and 2013–2019, are identified as Niño 3.4, Dipole Mode Index (DMI), no significant dominant index, and DMI dominated, respectively.DiscussionThe corresponding sea surface height differences between the Northwest Tropical Pacific Ocean (NWP) and Southeast Indian Ocean (SEI) in these three periods when exist dominant index are -0.50 cm, 0.99 cm and -3.22 cm, respectively, which are responsible for the dominance of the climate modes. The study provides a new insight to quantify the response of ITF transport to climate drivers.

On the Use of Reanalysis Data to Reconstruct Missing Observed Daily Temperatures in Europe over a Lengthy Period of Time

In this study, a methodology that can reconstruct missing daily values of maximum and minimum temperatures over a long time period under the assumption of a sparse network of meteorological stations is described. To achieve this, a well-established software used for quality control, homogenization and the infilling of missing climatological series data, Climatol, is used to combine a mosaic of data, including daily observations from 15 European stations and daily data from two high-resolution reanalysis datasets, ERA5-Land and MESCAN-SURFEX; this is in order reconstruct daily values over the 2000–2018 period. By comparing frequently used indices, defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) in studies of climate change assessment and goodness-of-fit measures, the reconstructed time series are evaluated against the observed ones. The analysis reveals that the ERA5-Land reconstructions outperform the MESCAN-SURFEX ones when compared to the observations in terms of biases, the various indices evaluated, and in terms of the goodness of fit for both the daily maximum and minimum temperatures. In addition, the magnitude and significance of the observed long-term temporal trends maintained in the reconstructions, in the majority of the stations examined, for both the daily maximum and daily minimum temperatures, is an issue of the greatest relevance in many climatic studies.

Synoptic and mesoscale winds in the complex terrain of Perdigão

For modeling complex atmospheric flows in wind energy studies when employing a chain of models, it is necessary to guarantee accurate wind simulations in all models that make up the chain. With this aim, we evaluated the ERA5 dataset (synoptic) and Weather Research and Forecasting (WRF) simulations (mesoscale) of the wind over Perdigão, which will later serve as input to a microscale model. The Perdigão-2017 measurement campaign is one of the latest and largest experiments over a complex terrain, thus being a valuable dataset for the validation of atmospheric models. Previous long-term simulation studies in Perdigão did not employ a highresolution reanalysis dataset for boundary conditions, nudging techniques, planetary boundary layer (PBL) sensitivity analysis, nor did compare synoptic and mesoscale data against local measurements. Here we simulated the wind in Perdigão using WRF with two one-way nested domains (9-km and 3-km horizontal resolutions) during 45 days, evaluating five PBL schemes. ERA5 reanalysis was used as input to the mesoscale simulations and for the spectral nudging in WRF’s outer domain. Data from the top anemometer of a 100-m tower, located in Perdigão’s SW ridge, were employed as reference in the evaluation of ERA5 and WRF wind speeds and directions. The hourly-averaged 3-km WRF simulations showed wind speed errors of 2.22 m/s RMSE and −0.02 m/s Bias with the YSU PBL scheme. The approximately 31-km ERA5 dataset exhibited total errors of 2.22 m/s (−0.37 m/s) RMSE (Bias). We attributed the similar ERA5 total error to its smoother wind speed values compared to WRF’s, despite its coarser resolution, and not to its faithful representation of the wind in Perdigão. WRF overestimated wind speeds mainly between the NW and N sectors as a result of its misrepresentation of the NW mountain range. Despite ERA5 coarser resolution, its smoothed terrain did not seem to greatly affect the wind near the NW direction. Additionally, both ERA5 and WRF wind speed errors vary linearly with the measured wind speed.

Cyclonic activity in the Mediterranean region from a high-resolution perspective using ECMWF ERA5 dataset

This study focuses on developing a new Cyclone Detection and Tracking Method (CDTM) to take advantage of the recent availability of a high-resolution reanalysis dataset of ECMWF ERA5. The proposed algorithm is used to perform a climatological analysis of the cyclonic activity in the Mediterranean Region (MR) into a 40-year window (1979–2018). The tuning of the new CDTM was based on the comparison with currently available CDTMs and verified through careful subjective analysis to fully exploit the finer details of MR cyclones features. The application of the new CDTM to the ERA5 high-resolution dataset resulted in an increase of 40% in the annual number of cyclones, mainly associated with subsynoptic and baroclinic driven lows. The main cyclogenetic areas and seasonal cycle were properly identified into the MR context, including areas often underestimated, such as the Aegean Sea, and emerging new ones with cyclogenetic potential such as the coast of Tunisia and Libya. The better cyclone features description defined three distinct periods of cyclonic activity in the MR with peculiar and persistent characteristics. In the first period (Apr–Jun), cyclones develop more frequently and present higher velocities and deepening rates. In the second (Jul–Sep), the cyclonic activity is governed by thermal lows spreading slowly over short tracks without reaching significant depths. In the last and longest season (Oct–Mar), cyclones become less frequent, but with the highest deepening rates and the lowest MSLP values, ranking this period as the most favourable to intense storms.

Seasonal and Interannual Variability of the Meridional Overturning Circulation in the Subpolar North Atlantic Diagnosed From a High Resolution Reanalysis Data Set

AbstractSubpolar North Atlantic is a vital region to modulate the variation of Atlantic Meridional Overturning Circulation (MOC). Recently, trans‐basin mooring arrays were deployed to monitor the meridional volume and heat transport in this region. Motivated by these new observations, this study investigates the structure and variability of MOC using a high resolution data assimilative reanalysis product. Our results indicate that the reanalysis product successfully captures the vertical structure and variability for the basinwide integrated stream function. In accord with observations, the meridional volume transport across the section from Greenland to Scotland (i.e., the East Section) is much stronger than that in the Labrador Sea (i.e., the West Section). While the boundary currents in the Labrador Sea display dramatic seasonal variations, their seasonal cycles are largely compensated, leading to very weak seasonality in the MOC. On the other hand, the MOC across the East section has an apparent seasonal cycle with the density changes in the Irminger Basin playing a dominant role. On the interannual time scale, MOC variations across both the West and East sections have comparable amplitudes. In addition, we further split the MOC fluctuations into components induced by barotropic and baroclinic processes. The decomposed fields point out that the isopycnal layer thickness at the west of Greenland is the primary factor to modulate the MOC interannual variability across the West section. MOC interannual variability across the East section is mostly determined by barotropic velocity changes near the pathway of the North Atlantic Current.

Characteristics of warm cores of tropical cyclones in a 25-km-mesh regional climate simulation over CORDEX East Asia domain

In this study, the characteristics of the tropical cyclone (TC) warm cores in high resolution reanalysis dataset (ERA5) and a 25-km-mesh regional climate simulation over CORDEX East Asia domain during 1988–2009 are analyzed. The Kain–Fritsch scheme with new convection trigger function (Ma and Tan, Atmos Res 92:190–211, 2009; KFMT), the renewed Kain-Fritsch convective parameterization (Kain, J Appl Meteorol 43:170–181, 2004; KF) and the simplified Arakawa-Schubert scheme (Arakawa and Schubert, J Atmos Sci 31:674–701, 1974; SAS) are employed to illustrate the impact of cumulus parameterization schemes (CPSs) on the representation of warm core in the regional climate simulation. The TC intensity and warm core strength in ERA5 reanalysis is largely weaker than those in the regional climate simulations. In ERA5 reanalysis and three regional climate simulations, the warm core strength shows a significant positive correlation with TC intensity, but the warm core height has no correlation with TC intensity, especially during the intensifying stage of TCs. The results also show that CPS has a great impact on the warm core structures of simulated TCs. The TC warm core strength is strongest in KFMT experiment and weakest in SAS experiment, which is consistent with the differences in the TC intensities. The TC warm core heights in the KF and KFMT experiments are significantly higher than that in SAS experiment. These differences of TC warm core strength and height are mainly due to the discrepancy in the simulation of convective activities with different CPSs. The results of this study point out that the ability of climate model to simulate TC intensity is strongly related to the model capability to simulate the TC thermal structure, which is influenced by convection representations in the model.

Climatology of diablo winds in Northern California and their relationships with large-scale climate variabilities

The most destructive wildfires recently in Northern California have been linked to the occurrences of Diablo Winds (DWs). This study investigates the climatology of DWs during September–December 1979–2018, and their relationships with various climate modes using observations and two high-resolution reanalysis datasets. Our finding shows that DWs do not have a long-term trend in terms of the annual total number, total duration, and associated maximum wind speeds of DWs over the past 4 decades. However, their associated minimum relative humidity (RH) has decreased significantly, especially in October, which suggests that the dryness during DWs has become more severe with time, possibly leading to an increased chance of fires, and their destructive potential. We also find that the annual total number and duration of DWs have exhibited an quasi-periodic variation, with intervals ranging from 2 to 4 years. The periodic variability of DWs might be attributed to the teleconnections between DWs and climate oscillations, specifically the El Niño–Southern Oscillation (ENSO) and the quasi-biennial oscillation (QBO), through their modulation of pressure systems near California and the location of the Pacific jet stream. It is suggested that when La Niña and the QBO westerly phases co-occur in the spring, DWs in the following fall and winter tend to occur more frequently, and are associated with more intense high winds and dryness as compared to other springtime QBO and ENSO phases. This relationship may be used to predict the seasonal outlook of DWs.

Climatology of Tibetan Plateau vortices derived from multiple reanalysis datasets

The Tibetan Plateau vortex (TPV) is a mesoscale weather system active in the near-surface layer, which is one of the major systems for the generation of precipitation in the Tibetan Plateau (TP). However, no long-term observations of the TPVs are available due to the scarcity of observations in the TP. Thereby, long-term, high-accuracy reanalysis products are a reliable source for the analysis of characteristic TPV activities and possible mechanisms behind. In the present study, an objective analysis method is implemented to obtain a complete dataset of TPV based on several reanalysis products, including the ERA-Interim, ERA40, JRA55, NCEP CFSR, and NASA MERRA2. The TPVs are detected and tracked by the minima in geopotential height at 500 hPa. Results indicate that the TPVs derived from multiple reanalysis products have quite similar spatial patterns and temporal variability. The characteristic parameters of the TPVs derived from a given reanalysis data are related to the resolution of this reanalysis product. Higher-resolution reanalysis products can yield more low-pressure systems, which explains why the TPVs derived from high-resolution reanalysis datasets generally have longer lifetime, stronger and larger vortex scale than those from low-resolution reanalysis products, although the total number of TPVs are similar. The annual average number of TPVs generated in the TP is 63.5, and these TPVs largely originate in the mountainous area of the central western TP around (34° N, 78–95° E) and a belt zone (30° N, 80–84° E) in the southern TP, where the elevation is around 5500 m. The TPVs often dissipate in low valleys and the lee side of mountains. They mainly occur in the warm season during May–September, most active in the summer and least active in the winter. More TPVs form in the daytime than in the nighttime. Those TPVs that move out of the TP account for less than 10–14% of all TPVs, and they usually follow three moving paths: eastward (6.9–7.8%), northeastward (2.3–3.4%) and southward (2.3–3.5%).

Uncertainty estimation of investment planning models under high shares of renewables using reanalysis data

Abstract Variable renewable energy, particularly wind and solar, increasingly affects present and future energy systems. Reanalysis products are often used as a meteorological basis for subsequent energy system studies under high shares of variable renewable energy. Since reanalyses contain considerable biases, it is ex-ante unclear how they impact the results of energy system models. For that purpose, this study applies the high resolution reanalysis data set (6 km grid) to a full model chain, from the meteorological basis via power conversion to the optimal electricity system investment and dispatch, and investigates the implications of initial errors. It is shown that power conversion as well as electricity system model results are highly sensitive to these errors associated with the meteorological input data, in particular under high shares of variable renewable energy. The initial errors are observed to propagate through the model chain with at least the same magnitudes, which leads to distinct impacts on the overall configuration of the German electricity system as well as allocation effects of variable renewable energy capacities.

Comparison of ERA5-Land and UERRA MESCAN-SURFEX Reanalysis Data with Spatially Interpolated Weather Observations for the Regional Assessment of Reference Evapotranspiration

Reanalysis data are being increasingly used as gridded weather data sources for assessing crop-reference evapotranspiration (ET0) in irrigation water-budget analyses at regional scales. This study assesses the performances of ET0 estimates based on weather data, respectively produced by two high-resolution reanalysis datasets: UERRA MESCAN-SURFEX (UMS) and ERA5-Land (E5L). The study is conducted in Campania Region (Southern Italy), with reference to the irrigation seasons (April–September) of years 2008–2018. Temperature, wind speed, vapor pressure deficit, solar radiation and ET0 derived from reanalysis datasets, were compared with the corresponding estimates obtained by spatially interpolating data observed by a network of 18 automatic weather stations (AWSs). Statistical performances of the spatial interpolations were evaluated with a cross-validation procedure, by recursively applying universal kriging or ordinary kriging to the observed weather data. ERA5-Land outperformed UMS both in weather data and ET0 estimates. Averaging over all 18 AWSs sites in the region, the normalized BIAS (nBIAS) was found less than 5% for all the databases. The normalized RMSE (nRMSE) for ET0 computed with E5L data was 17%, while it was 22% with UMS data. Both performances were not far from those obtained by kriging interpolation, which presented an average nRMSE of 14%. Overall, this study confirms that reanalysis can successfully surrogate the unavailability of observed weather data for the regional assessment of ET0.

Drylines in Southern Africa: Rediscovering the Congo Air Boundary

AbstractProjected rainfall decline in southern Africa is likely to be highly sensitive to subtleties in the local atmospheric circulation. In an effort to understand the regional circulation complexities, a novel algorithm is developed to identify the Congo air boundary (CAB) in ERA-5, a high-resolution reanalysis dataset. The CAB, a forgotten feature of the circulation, is defined in the austral spring and early summer, using surface humidity gradients and near-surface wind convergence lines, and it is found to be an indicator of the location of the southern edge of the African rain belt. A related convergence-line and dryline feature, described in this paper as the Kalahari discontinuity (KD), is also identified. It is established that either a dryline CAB or KD is present in southern Africa for over 95% of days between August and December, with arc lengths typically exceeding 10°. The seasonal and diurnal cycles of the CAB and the KD are presented, and their prevalence in station observational data is confirmed. The interannual variability of the CAB latitude and detection frequency is found to explain at least 55% of interannual spring rainfall variability in southern Africa between 15° to 25°S. Links are established with the Angola and Kalahari heat lows and tropical temperate trough events.

An Evaluation of the North American Regional Reanalysis Simulated Soil Moisture Conditions during the 2011–13 Drought Period

Abstract Accurate and timely information on soil moisture conditions is an important component to effectively prepare for the damaging aspects of hydrological extremes. The combination of sparsely dense in situ networks and shallow observation depths of remotely sensed soil moisture conditions often force local and regional decision-makers to rely on numerical methods when assessing the current soil state. In this study, soil moisture from a commonly used, high-resolution reanalysis dataset is compared to observations from the U.S. Climate Reference Network (USCRN). The purpose of this study is to evaluate how well the North American Regional Reanalysis (NARR) captured the evolution, intensity, and spatial extent of the 2012 drought using both raw volumetric values and standardized anomalies of soil moisture. Comparisons revealed that despite a dry precipitation bias of 22% nationally, NARR had predominantly wetter 5-cm volumetric soil conditions over the growing season (April–September) than observed at USCRN sites across the contiguous United States, with differences more pronounced in drier regions. These biases were partially attributed to differences between the dominant soil characteristics assigned to the modeled grid cells and localized soil characteristics at the USCRN stations. However, NARR was able to successfully capture many aspects of the 2012 drought, including the timing, intensity, and spatial extent when using standardized soil moisture anomalies. Standardizing soil moisture conditions reduced the magnitude of systematic biases between NARR and USCRN in many regions and provided a more robust basis for utilizing modeled soil conditions in assessments of hydrological extremes.

Evaluating the representation of Australian East Coast Lows in a regional climate model ensemble

Due to their large influence on both severe weather and water security along the east coast of Australia, it is increasingly important to understand how East Coast Lows (ECLs) may change over coming decades. Changes in ECLs may occur for a number of reasons including changes in the general atmospheric circulation (e.g. poleward shift of storm tracks) and/or changes in local conditions (e.g. changes in sea surface temperatures). Numerical climate models are the best available tool for studying these changes however, in order to assess future projections, climate model simulations need to be evaluated on how well they represent the historical climatology of ECLs. In this paper, we evaluate the performance of a 15-member ensemble of regional climate model (RCM) simulations to reproduce the climatology of cyclones obtained using three high-resolution reanalysis datasets (ERA-Interim, NASA-MERRA and JRA55). The performance of the RCM ensemble is also compared to results obtained from the global datasets that are used to drive the RCM ensemble (four general circulation model simulations and a low resolution reanalysis), to identify whether they offer additional value beyond the driving data. An existing cyclone detection and tracking algorithm is applied to derive a number of ECL characteristics and assess results at a variety of spatial scales. The RCM ensemble offers substantial improvement on the coarse-resolution driving data for most ECL characteristics, with results typically falling within the range of observational uncertainty, instilling confidence for studies of future projections. The study clearly highlights the need to use an ensemble of simulations to obtain reliable projections and a range of possible future changes.

Evaluating the representation of Australian East Coast Lows in a regional climate model ensemble

Due to their large influence on both severe weather and water security along the east coast of Australia, it is increasingly important to understand how East Coast Lows (ECLs) may change over coming decades. Changes in ECLs may occur for a number of reasons including changes in the general atmospheric circulation (e.g. poleward shift of storm tracks) and/or changes in local conditions (e.g. changes in sea surface temperatures). Numerical climate models are the best available tool for studying these changes however, in order to assess future projections, climate model simulations need to be evaluated on how well they represent the historical climatology of ECLs. In this paper, we evaluate the performance of a 15-member ensemble of regional climate model (RCM) simulations to reproduce the climatology of cyclones obtained using three high-resolution reanalysis datasets (ERA-Interim, NASA-MERRA and JRA55). The performance of the RCM ensemble is also compared to results obtained from the global datasets that are used to drive the RCM ensemble (four general circulation model simulations and a low resolution reanalysis), to identify whether they offer additional value beyond the driving data. An existing cyclone detection and tracking algorithm is applied to derive a number of ECL characteristics and assess results at a variety of spatial scales. The RCM ensemble offers substantial improvement on the coarse-resolution driving data for most ECL characteristics, with results typically falling within the range of observational uncertainty, instilling confidence for studies of future projections. The study clearly highlights the need to use an ensemble of simulations to obtain reliable projections and a range of possible future changes.

基于MERRA再分析数据伊犁河流域水储量变化研究

为了弥补GRACE重力卫星无法在小流域上研究水储量问题，本文利用空间高分辨率的MERRA再分析数据分析1980~2014年长时间序伊犁河流域水储量变化特征。结果表明：在空间上，伊犁河流域水储量大部分地区处于亏损状态，最大亏损量为−40.08 mm。流域内水储量变化与降水变化均呈现下降趋势。在年内，流域内平均水储量的上呈现“U”型分布，10月到次年3月冬半年水储量为盈余状态，12月出现最高值(16.1 mm)。4~9月份夏季为处于亏损状态(−14.68 mm)。1980~2014年伊犁河流域国内区域水储量呈增长趋势，而国外区域呈下降趋势。 To solve the problem of GRACE water storage dataset's coarse spatial resolution in the small wa-tershed, high-resolution reanalysis dataset of MERRA was deployed in this study for long term analysis of water storage in Ili River Basin. It was shown that most of the Ili River Basin's water storage was spatially at loss, and the maximum loss amount had reached to −40.08 mm. The trend of water storage agreed with total annual precipitation’s, which were in downward trend. In a year, the monthly water storage change curve was in “U” shape. The water storage was surplus in the winter year (the maximum surplus was 16.1 mm) and under deficit in summer year (the maximum loss was −14.68 mm). In the period of 1980-2014, the Ili River Basin's water storage in domestic part showed a rising trend, while the foreign part was declining at counter.

South American Climatology and Impacts of El Niño in NCEP’s CFSR Data

Understanding regional climate variability is necessary in order to assess the impacts of climate change. Until recently, the best methods for evaluating regional climate variability were via observation networks and coarse-gridded reanalysis datasets. However, the recent development of high-resolution reanalysis datasets offers an opportunity to better evaluate the climatologically diverse continent of South America. This study compares NCEP’s CFS reanalysis dataset with NCEP’s coarser-resolution reanalysis II dataset to determine if CFS reanalysis improves our ability to represent the regional climate of South America. Our results show several regional differences between the CFSR and Re2 data, especially in areas of large topographical gradients. A comparison with the University of Delaware and TRMM precipitation datasets lends credence to some of these differences, such as heavier precipitation associated with anomalous 925 hPa westerlies over northwestern Peru and Ecuador during El Niño. However, our results also stress that caution is advised when using reanalysis data to assess regional climate variability, especially in areas of large topographical gradient such as the Andes. Our results establish a baseline to better study climate change, especially given the release of IPCC AR5 model simulations.