Evaluation of the Twentieth Century Reanalysis Dataset in Describing East Asian Winter Monsoon Variability

The Twentieth Century Reanalysis （20thCR） dataset released in 2010 covers the period 1871-2010 and is one of the longest reanalysis datasets available worldwide. Using ERA-40, ERA-Interim and NCEP-NCAR reanalysis data, as well as HadSLP2 data and meteorological temperature records over eastern China, the performances of 20thCR in reproducing the spatial patterns and temporal variability of the East Asian winter monsoon （EAWM） are examined. Results indicate that 20thCR data： （1） can accurately reproduce the most typical configuration patterns of all sub-factors differences in the main circulation fields over East Asia involved in the EAWM system, albeit with some in comparison to ERA-40 reanalysis data; （2） is reliable and stable in describing the temporal variability of EAWM since the 1930s; and （3） can describe the high-frequency variability of EAWM better than the low-frequency fluctuations, especially in the early period. In conclusion, caution should be taken when using 20thCR data to study interdecadal variabilities or long-term trends of the EAWM, especially prior to the 1930s.

Consistency of Tropospheric Water Vapor between Reanalyses and Himawari-8/AHI Measurements over East Asia

High spatiotemporal resolution radiances from the advanced imagers onboard the new generation of geostationary weather satellites provide a unique opportunity to evaluate the abilities of various reanalysis datasets to depict multilayer tropospheric water vapor(WV),thereby enhancing our understanding of the deficiencies of WV in reanalysis datasets.Based on daily measurements from the Advanced Himawari Imager(AHI)onboard the Himawari-8 satellite in 2016,the bias features of multilayer WV from six reanalysis datasets over East Asia are thoroughly evaluated.The assessments show that wet biases exist in the upper troposphere in all six reanalysis datasets;in particular,these biases are much larger in summer.Overall,we find better depictions of WV in the middle troposphere than in the upper troposphere.The accuracy of WV in the ERA5 dataset is the highest,in terms of the bias magnitude,dispersion,and pattern similarity.The characteristics of the WV bias over the Tibetan Plateau are significantly different from those over other parts of East Asia.In addition,the reanalysis datasets all capture the shift of the subtropical high very well,with ERA5 performing better overall.

A Global Ocean Reanalysis Product in the China Ocean Reanalysis(CORA) Project

The first version of a global ocean reanalysis over multiple decades （1979-2008） has been completed by the National Marine Data and Information Service within the China Ocean Reanalysis （CORA） project. The global ocean model employed is based upon the ocean general circulation model of the Massachusetts Institute of Technology. A sequential data assimilation scheme within the framework of 3D variational （3DVar） analysis, called multi-grid 3DVar, is implemented in 3D space for retrieving multiple-scale observational information. Assimilated oceanic observations include sea level anomalies （SLAs） from multi-altimeters, sea surface temperatures （SSTs） from remote sensing satellites, and in-situ temperature/salinity profiles. Evaluation showed that compared to the model simulation, the annual mean heat content of the global reanalysis is significantly approaching that of World Ocean Atlas 2009 （WOA09） data. The quality of the global temperature climatology was found to be comparable with the product of Simple Ocean Data Assimilation （SODA）, and the major ENSO events were reconstructed. The global and Atlantic meridional overturning circulations showed some similarity as SODA, although significant differences were found to exist. The analysis of temperature and salinity in the current version has relatively larger errors at high latitudes and improvements are ongoing in an updated version. CORA was found to provide a simulation of the subsurface current in the equatorial Pacific with a correlation coefficient beyond about 0.6 compared with the Tropical Atmosphere Ocean （TAO） mooring data. The mean difference of SLAs between altimetry data and CORA was less than 0.1 m in most years.

Performance of surface radiation products of Greenland Ice Sheet using in-situ measurements

Radiation is the direct energy source of the surface natural environment and the main driving force of climate change.It has increasingly become an important meteorological factor affecting the surface heat exchange and glacier mass balance,especially in the glacier changes of the Greenland Ice Sheet(Gr IS).Due to the harsh climatic conditions of Gr IS and sparse observed data,it has become an important way to obtain radiation data from reanalysis datasets.However,the applicability of these radiation data on Gr IS is uncertain and worth exploring.In this work,we evaluate five reanalysis datasets(the fifth generation of European Centre for Medium-Range Weather Forecasts(ERA5),European Centre for Medium-Range Weather Forecasts Interim Reanalysis(ERA-Interim),Japanese 55-year Reanalysis(JRA55),National Centers for Environmental Prediction Reanalysis II(NCEP2)and Modern-Era Retrospective analysis for Research and Applications,Version 2(MERRA-2))during 1997-2022 using observations from 26 Program for Monitoring the Greenland Ice Sheet(PROMICE)automatic weather stations(AWSs)and 3 K-transect AWSs on Gr IS.The conclusions are as follows:ERA5 has the best performances in downward shortwave radiation(SWD)as well as downward and upward longwave radiation(LWD and LWU),but the performance is not the best in upward shortwave radiation(SWU).Based on the radiation budget analysis with ERA5 during 1979-2022,the fluctuation of longwave radiation is greater than that of shortwave radiation.The seasonal variation of shortwave radiation is obvious,while that of longwave radiation is small.The increasing trend of longwave radiation may result from global warming,in which ice sheets absorb more solar radiation and the surface heats up significantly,emitting more LWU.

Intercomparison of CRA-Interim Precipitation Products with ERA5 and JRA-55

Based on the hourly observational data during 2007-2016 from surface meteorological stations in China,this paper compares the influence of 3-hourly precipitation data,mainly from the Chinese Reanalysis-Interim(CRA-Interim),ECMWF Reanalysis 5(ERA5)and Japanese Reanalysis-55(JRA-55),on the simulation of the spatial and temporal distribution of regional precipitation in China and the bias distribution of the simulation.The results show that:(1)The three sets of reanalysis datasets can all reflect the basic spatial distribution characteristics of annual average precipitation in China.The simulation of topographic forced precipitation in complex terrain by using CRA-interim is more detailed,while CRA-interim has larger negative bias in central and East China,and larger positive bias in southwest China.(2)In terms of seasonal precipitation,the three sets of reanalysis datasets overestimate the precipitation in the heavy rainfall zone in spring and summer,especially in southwest China.According to CRA-interim,location of the rain belt in the First Rainy Season in South China is west by south,and the summer precipitation has positive bias in southwest and South China.(3)All of the reanalysis datasets can basically reflect the distribution difference of inter-annual variation of drought and flood,but overall the CRA-Interim generally shows negative bias,while the ERA5 and JRA-55 exhibit positive bias.(4)For the diurnal variation of precipitation in summer,all the reanalysis datasets perform better in simulating the daytime precipitation than in the night,and the bias of CRA-interim is less in the Southeast and Northeast than elsewhere.(5)The ERA5 generally performs the best on the evaluation of quantitative precipitation forecast,the JRA-55 is the next,followed by the CRA-Interim.The CRA-Interim has higher missing rate and lower threat score for heavy rains;however,at the level of downpour,the CRA-Interim performs slightly better.

An observational study of precipitation types in the Alaskan Arctic

The effects of various precipitation types,such as snow,rain,sleet,hail and freezing rain,on regional hydrology,ecology,snow and ice surfaces differ significantly.Due to limited observations,however,few studies into precipitation types have been conducted in the Arctic.Based on the high-resolution precipitation records from an OTT Parsivel^(2) disdrometer in Utqiaġvik,Alaska,this study analysed variations in precipitation types in the Alaskan Arctic from 15 May to 16 October,2019.Results show that rain and snow were the dominant precipitation types during the measurement period,accounting for 92%of the total precipitation.In addition,freezing rain,sleet,and hail were also observed(2,4 and 11 times,respectively),accounting for the rest part of the total precipitation.The records from a neighbouring U.S.Climate Reference Network(USCRN)station equipped with T-200B rain gauges support the results of disdrometer.Further analysis revealed that Global Precipitation Measurement(GPM)satellite data could well characterise the observed precipitation changes in Utqiaġvik.Combined with satellite data and station observations,the spatiotemporal variations in precipitation were verified in various reanalysis datasets,and the results indicated that ECMWF Reanalysis v5(ERA5)could better describe the observed precipitation time series in Utqiaġvik and the spatial distribution of data in the Alaskan Arctic.Modern-Era Retrospective analysis for Research and Applications,Version 2(MERRA-2)overestimated the amount and frequency of precipitation.Japanese 55-year Reanalysis(JRA-55)could better simulate heavy precipitation events and the spatial distribution of the precipitation phase,but it overestimated summer snowfall.

Performance of climate reanalyses in the determination of pan-Arctic terrestrial rain-on-snow events

Rain-on-snow(ROS)events can cause rapid snowmelt,leading to flooding and avalanches in the pan-Arctic and can also lead to starvation and the death of massive ungulates.Reanalysis products(e.g.,ERA-I,ERA5-land,JRA55,MERRA2)are the primary source data for the research about ROS events in the large-scale region.However,the accuracy and reliability of reanalyses have never been evaluated with respect to the determination of terrestrial ROS events.The present study aims to statistically evaluate the performance of reanalysis datasets in identifying ROS events with different criteria based on in-situ rainfall data and MODIS snow cover product.The results show that all reanalysis datasets exhibit poor performance(Recall≤0.16,Kappa coefficient≤0.26,F-score≤0.42,MCC≤0.33)in all criteria in the pan-Arctic,mainly due to the low accuracy of rainfall data(r≤0.56).Nevertheless,the spatial distribution pattern and hot spots of ROS from all reanalysis datasets are essentially close.The hot spots of ROS are mainly located on the coast of Alaska,Norway,and Greenland.All reanalyses demonstrate an increase in rainy days,but there is little overall change in ROS events due to the reduction in snow cover days.This work suggests that none of the current reanalyses are reliable in the determination of ROS events due to the poor representation of the rainfall parameterization scheme.The development of alternative strategies that can investigate ROS events at large-scale is urgently needed in a changing Arctic under rapid warming.

Examining asymmetric outer-core CAPE in sheared tropical cyclones based on the FNL data set

The asymmetric distribution of convective available potential energy(CAPE)in the outer core of sheared tropical cyclones(TCs)is examined using the National Centers for Environmental Prediction Final operational global analysis data.Larger(smaller)CAPE tends to appear in the downshear(upshear)semicircle.This downshear-upshear contrast in CAPE magnitude becomes much more statistically significant in moderate-to-strong shear.The azimuthally asymmetric CAPE is closely associated with the near-surface equivalent potential temperature(e).Larger surface winds occur in the upshear semicircle in strongly sheared TCs,contributing to larger surface latent heat fluxes in those quadrants.More lowlevel air well fueled by the larger surface latent heat fluxes in the upshear quadrants is cyclonically advected into the downstream quadrants.As a result,larger near-surfacee and CAPE are found in the outer core in the downshear quadrants.