Abstract: The reanalysis datasets (CRA40) have now been developed in China Meteorological Administration. We aim to compare the differences in surface air temperature (SAT) between observational that has been adjusted for urbanization bias and reanalysis data (NCEPV1, NCEPV2, ERA5, CFSR, MERRA, JRA55, 20CRV3 and CRA40) over mainland China during 1961–2015. The main results are presented as follows. The correlation and standard deviation between the reanalysis data and observations exhibit highly consistent interannual variability and dispersion, with the interannual SAT variability in JRA55 being closest to the observations for 1961–2015 and that of ERA5 for 1979–2015; the dispersions of 20CRV3 is most consistent with the observations for 1961–2015 and that of NCEPV1 for 1979–2015. Although annual mean SAT of the reanalysis is generally 0–2.0 °C lower than the observations, the bias in the SAT climatology of 20CRV3 is the least for 1961–2015 in all reanalysis datasets and that of CRA40 is the least for 1979–2015. The trends of NCEPV1 is closer to the observations than other reanalysis for 1961–2015 and that of 20CRV3 for 1979–2015. The biases in terms of interannual variability, dispersion, climatology, and linear trend are increase with altitude. Overall, in terms of the similarity of multiple measures to the urbanization bias-adjusted observations, JRA55 and CRA40 show the best performances for the periods 1961–2015 and 1979–2015 respectively in reproducing various aspects of climatological and climate change features in mainland China.
Abstract: Since the 1980s, China has undergone rapid urbanization. Meanwhile, the climate has been warming substantially. In this paper, the urbanization effect on observed temperatures from 1980 to 2009 in China is estimated, based on analysis of urban land use from satellite observation. Urban land-use expansion (ΔU) during 1980–2005 is applied as an urbanization index. According to these ΔU values, stations are divided into three categories: (C1) intense urbanization around the stations; (C2) moderate urbanization around the stations; and (C3) minimal urbanization around the stations. Most C1 stations are in municipalities or provincial capitals, while C2 stations tend to be in prefecture-level cities. C3 stations are mostly in counties. The urban heat island (UHI) effect can be estimated if the urban effect on C3 is negligible. The warming of C1 or C2 relative to that of C3 represents their urbanization effects, assuming that the same larger-scale natural warming has affected each category. For C1, the local urbanization effect is 0.258°C/10 a over 1980–2009, accounting for 41% of the total warming; the trend at C2 is 0.099°C/10 a, or 21%. For all China, the urbanization effect is 0.09°C/10a, accounting for 20% of the total national warming. Winter urban warming is greater than in summer. The assumption of negligible urbanization effect on C3 is debatable, and so the true urbanization effect may equal or slightly exceed estimates. Further, the ΔU index may have some uncertainties, for it is only one of the urbanization indices. However, it provides a new and direct estimation of environmental change, in contrast to indirect indices.
TL;DR: The results show that the difference of mean daily temperature between city and suburb is the largest on 24 December in 1995 during the last 4 0 years, and an obvious 12 years cycle of mean annual temperature is found.
Abstract: Variations of mean temperature in Beijing city are ana ly zed in this paper.The results show that the difference of mean daily temperature between city and suburb is the largest on 24 December in 1995 during the last 4 0 years,and the mean daily temperature in the city is 4.6℃ higher than that in the suburb;the difference of temperature between the city and the suburb is the utmost in winter season and the mean seasonal temperature in the city is 1.11℃ higher than that in the suburb,while the difference is the least in spring seaso n,and the temperature in the city is 0.26℃ higher than that in the suburb;for t he inter-annual variability of temperature,the difference of temperature is lit tle from 1961 to 1977,while the difference is great from 1978 to 2000,and the te mperature in the city is 0.62℃ higher than that in the suburb,so the heat islan d effect is reinforced from 1978 to 2000;the difference of temperature is the le ast in 1960's,and the temperature in the city is 0.13℃ higher than that in the suburb,whereas the difference is the maximal in 1990's,and the temperature in th e city is 0.78℃ higher than that in the suburb;the number of high temperature d ays(≥35℃)is going up obviously in recent years,but the highest temperature is not changed greatly,and the highest temperature is higher than 38℃ only in 1997 ,1999 and 2000. The mean annual temperature is increasing apparently during the last 40 years,and it is increasing by 0.43℃/10ɑ in the city and 0.21℃/10ɑ in the suburb,an obvious 12 years cycle of mean annual temperature is found.
Abstract: Many multidecadal atmospheric reanalysis products are available now, but their consistencies and reliability are far from perfect. In this study, atmospheric precipitable water (PW) from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), NCEP/Department of Energy (DOE), Modern Era Retrospective-Analysis for Research and Applications (MERRA), Japanese 55 year Reanalysis (JRA-55), JRA-25, ERA-Interim, ERA-40, Climate Forecast System Reanalysis (CFSR), and 20th Century Reanalysis version 2 is evaluated against homogenized radiosonde observations over China during 1979–2012 (1979–2001 for ERA-40). Results suggest that the PW biases in the reanalyses are within ∼20% for most of northern and eastern China, but the reanalyses underestimate the observed PW by 20%–40% over western China and by ∼60% over the southwestern Tibetan Plateau. The newer-generation reanalyses (e.g., JRA25, JRA55, CFSR, and ERA-Interim) have smaller root-mean-square error than the older-generation ones (NCEP/NCAR, NCEP/DOE, and ERA-40). Most of the reanalyses reproduce well the observed PW climatology and interannual variations over China. However, few reanalyses capture the observed long-term PW changes, primarily because they show spurious wet biases before about 2002. This deficiency results mainly from the discontinuities contained in reanalysis relative humidity fields in the middle-lower troposphere due to the wet bias in older radiosonde records that are assimilated into the reanalyses. An empirical orthogonal function (EOF) analysis revealed two leading modes that represent the long-term PW changes and El Nino–Southern Oscillation-related interannual variations with robust spatial patterns. The reanalysis products, especially the MERRA and JRA-25, roughly capture these EOF modes, which account for over 50% of the total variance. The results show that even during the post-1979 satellite era, discontinuities in radiosonde data can still induce large spurious long-term changes in reanalysis PW and other related fields. Thus, more efforts are needed to remove spurious changes in input data for future long-term reanalyses.
Abstract: The NCEP and NCAR are cooperating in a project (denoted “reanalysis”) to produce a 40-year record of global analyses of atmospheric fields in support of the needs of the research and climate monitoring communities. This effort involves the recovery of land surface, ship, rawinsonde, pibal, aircraft, satellite, and other data; quality controlling and assimilating these data with a data assimilation system that is kept unchanged over the reanalysis period 1957–96. This eliminates perceived climate jumps associated with changes in the data assimilation system. The NCEP/NCAR 40-yr reanalysis uses a frozen state-of-the-art global data assimilation system and a database as complete as possible. The data assimilation and the model used are identical to the global system implemented operationally at the NCEP on 11 January 1995, except that the horizontal resolution is T62 (about 210 km). The database has been enhanced with many sources of observations not available in real time for operations, provided b...
Abstract: The NCEP–DOE Atmospheric Model Intercomparison Project (AMIP-II) reanalysis is a follow-on project to the “50-year” (1948–present) NCEP–NCAR Reanalysis Project. NCEP–DOE AMIP-II re-analysis covers the “20-year” satellite period of 1979 to the present and uses an updated forecast model, updated data assimilation system, improved diagnostic outputs, and fixes for the known processing problems of the NCEP–NCAR reanalysis. Only minor differences are found in the primary analysis variables such as free atmospheric geopotential height and winds in the Northern Hemisphere extratropics, while significant improvements upon NCEP–NCAR reanalysis are made in land surface parameters and land–ocean fluxes. This analysis can be used as a supplement to the NCEP–NCAR reanalysis especially where the original analysis has problems. The differences between the two analyses also provide a measure of uncertainty in current analyses.
Abstract: The Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA’s Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA’s Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses. Focusing on the satellite era, from 1979 to the present, MERRA has achieved its goals with significant improvements in precipitation and water vapor climatology. Here, a brief overview of the system and some aspects of its performance, including quality assessment diagnostics from innovation and residual statistics, is given.By comparing MERRA with other updated reanalyses [the interim version of the next ECMWF Re-Analysis (ERA-Interim) and the Climate Forecast System Reanalysis (CFSR)], advances made in this new generation of reanalyses, as well as remaining deficiencies, are identified. Although there is little difference between the new reanalyses i...
Abstract: The National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR) have cooperated in a project (denoted “reanalysis”) to produce a retroactive record of more than 50 years of global analyses of atmospheric fields in support of the needs of the research and climate monitoring communities. This effort involved the recovery of land surface, ship, rawinsonde, pibal, aircraft, satellite, and other data. These data were then quality controlled and assimilated with a data assimilation system kept unchanged over the reanalysis period. This eliminated perceived climate jumps associated with changes in the operational (real time) data assimilation system, although the reanalysis is still affected by changes in the observing systems. During the earliest decade (1948–57), there were fewer upper-air data observations and they were made 3 h later than the current main synoptic times (e.g., 0300 UTC), and primarily in the Northern Hemisphere, so that the reanalysis is less reliable than for th later 40 years. The reanalysis data assimilation system continues to be used with current data in real time (Climate Data Assimilation System or CDAS), so that its products are available from 1948 to the present. The products include, in addition to the gridded reanalysis fields, 8-day forecasts every 5 days, and the binary universal format representation (BUFR) archive of the atmospheric observations. The products can be obtained from NCAR, NCEP, and from the National Oceanic and Atmospheric Administration/ Climate Diagnostics Center (NOAA/CDC). (Their Web page addresses can be linked to from the Web page of the NCEP–NCAR reanalysis at http:// wesley.wwb.noaa.gov/Reanalysis.html.) This issue of the Bulletin includes a CD-ROM with a documentation of the NCEP–NCAR reanalysis (Kistler et al. 1999). In this paper we present a brief summary and some highlights of the documentation (also available on the Web at http://atmos.umd.edu/ ~ekalnay/). The CD-ROM, similar to the one issued with the March 1996 issue of the Bulletin, contains 41 yr (1958–97) of monthly means of many reanalysis variables and estimates of precipitation derived from satellite and in situ observations (see the appenThe NCEP–NCAR 50-Year Reanalysis: Monthly Means CD-ROM and Documentation