Previous Reanalysis Research Articles

The ULR-repro3 GPS data reanalysis and its estimates of vertical land motion at tide gauges for sea level science

Abstract. A new reanalysis of Global Navigation Satellite System (GNSS) data at or near tide gauges worldwide was produced by the University of La Rochelle (ULR) group within the third International GNSS Service (IGS) reprocessing campaign (repro3). The new solution, called ULR-repro3, complies with the IGS standards adopted for repro3, implementing advances in data modelling and corrections since the previous reanalysis campaign and extending the average record length by about 7 years. The results presented here focus on the main products of interest for sea level science: the station position time series and associated velocities on the vertical component at tide gauges. These products are useful to estimate accurate vertical land motion at the coast and supplement data from satellite altimetry or tide gauges for an improved understanding of sea level changes and their impacts along coastal areas. To provide realistic velocity uncertainty estimates, the noise content in the position time series was investigated considering the impact of non-tidal atmospheric loading. Overall, the ULR-repro3 position time series show reduced white noise and power-law amplitudes and lower station velocity uncertainties compared with the previous reanalysis. The products are available via SONEL (https://doi.org/10.26166/sonel_ulr7a; Gravelle et al., 2022).

Re-examining the Bayesian colour excess estimation for the local star-forming galaxies observed in the HETDEX pilot survey

ABSTRACTIn my previous reanalysis of the local star-forming galaxies observed in the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) pilot survey, I reported that the overestimation of E(B − V), hence the star formation rate (SFR), undermined the claim of new galaxy population discovery in the original study. Herein, I re-examine whether the E(B − V) overestimation problem can be alleviated in the Bayesian parameter estimation framework by adopting scientifically motivated new priors. I modelled the emission-line fluxes of galaxies using the strong-line method and four model parameters – metallicity $12 + \text{log {}(O/H)}$, nebula emission-line colour excess E(B − V), intrinsic [O iii] λ5007 line flux, and intrinsic [N ii] λ6584 line flux. Based on mock data tests, I found that all input values can be recovered within and around the 1σ credible interval by adopting suitable priors for the intrinsic [O iii] λ5007 and [N ii] λ6584 line fluxes: the inverse gamma distribution reflecting the logical constraint that an intrinsic emission-line flux must exceed the observed (reddened) emission-line flux. The mock data tests were performed for two metallicity calibrations, three colour excess input values [E(B − V) = 0.1, 0.3, and 0.5] and two metallicity input values [$12 + \text{log {}(O/H)}$ = 8.0 and 8.5]. I also found that the new prior can diminish the SFR overestimation eightfold. This study demonstrates how the Bayesian parameter estimation can achieve more accurate estimates with no further observations when the likelihood does not constrain the model parameters correctly.

Global coastal low‐level wind jets revisited through the new ERA5 reanalysis

AbstractThe recent ECMWF (European Centre of Medium‐Range Weather Forecasts) reanalysis product (ERA5) is a 3D‐atmospheric dataset of unparalleled value to advance the characterization and understanding of the main global coastal low‐level jet (CLLJ) systems, due to its finer resolution (horizontal and vertical) and hourly output. Regional climate studies have revealed the added value of higher spatial and temporal resolutions of models and reanalyses for the representation of CLLJs, which play an important role in the definition of the regional climate along the Eastern Boundary Current Systems. ERA5 reveals an improvement in the representation of the wind speed and temperature vertical profiles within the boundary layer in CLLJ regions. This improvement enables a better representation of CLLJs and therefore a new view on their features. ERA5 show larger CLLJ frequencies of occurrence and larger wind speed intensities, when compared with previous reanalysis. The maximum frequency of occurrence ranges from 20% in the West Australian and 73% in the Oman CLLJs, in the summer season, which constitutes an increase of 10% compared to ERA‐Interim. Moreover, a shift for higher wind speeds is also found, where the maximum wind speed approach 30 m·s−1. Typically, CLLJs are found below 500 m above sea level, where the finer vertical discretization results clearly in a better description of the CLLJ peak height. Regarding the diurnal cycles of CLLJs frequency of occurrence, ERA5 exposes higher peaks and larger amplitudes, where the maximum hourly frequency is about 38% in the Oman CLLJ and the diurnal amplitude can vary between 7 and 14%. The diurnal maximum and minimum frequency of CLLJ occurrence can be found between 1900 and 2200 UTC, and between 1000 and 1400 LST, respectively. The momentum and temperature budget profiles reveal significant differences between CLLJ regions and emphasize the relevance of local processes in its occurrences.

On shear layer atomization within closed channels: Numerical simulations of a cough-replicating experiment

Aerosol generation during coughing and sneezing has gained major relevance due to the current COVID pandemic. The atomization involved in this process takes place in the complex context of the respiratory system and develops very rapidly. In order to get further insights on the early spray generation, we introduce a simplified model of physiological coughing or sneezing, in the form of a thin liquid layer subject to a rapid (30 m/s) air stream. The setup is simulated using the Volume-Of-Fluid method with octree mesh adaptation, the latter allowing grid sizes small enough to capture the Kolmogorov length scale. The results confirm the trend to an intermediate distribution between a Log-Normal and a Pareto distribution P(d)∝d−3.3 for the distribution of droplet sizes in agreement with a previous re-analysis of experimental results by one of the authors. The mechanism of atomization does not differ qualitatively from the multiphase mixing layer experiments and simulations. No mechanism for a bimodal distribution, also sometimes observed, is evidenced in these simulations.

IMDAA: High Resolution Satellite-era Reanalysis for the Indian Monsoon Region

AbstractA high resolution regional reanalysis of the Indian Monsoon Data Assimilation and Analysis (IMDAA) project is made available to researchers for deeper understanding of the Indian monsoon and its variability. This 12 km resolution reanalysis covering the satellite-era from 1979 to 2018 using 4D-Var data assimilation method and the UK Met Unified Model is presently the highest resolution atmospheric reanalysis carried out for the Indian monsoon region. Conventional and satellite observations from different sources are used, including Indian surface and upper air observations, of which some were not used in any previous reanalyses. Various aspects of this reanalysis, like quality control and bias correction of observations, data assimilation system, land surface analysis, and verification of reanalysis products, are presented in this paper. Representation of important weather phenomena of each season over India in the IMDAA reanalysis verifies reasonably well against India Meteorological Department (IMD) observations and compares closely with ERA5. Salient features of the Indian summer monsoon are found to be well represented in the IMDAA reanalysis. Characteristics of major semi-permanent summer monsoon features (e.g., Low-level Jet and Tropical Easterly Jet) in IMDAA reanalysis are consistent with ERA5. The IMDAA reanalysis has captured the mean, inter-annual, and intra-seasonal variability of summer monsoon rainfall fairly well. IMDAA produces a slightly cooler winter and a hotter summer than the observations; the reverse for ERA5. IMDAA captured the fine-scale features associated with a notable heavy rainfall episode over complex terrain. In this study, the fine grid spacing nature of IMDAA is compromised due to the lack of comparable resolution observations for verification.

How well is outer tropical cyclone size represented in the ERA5 reanalysis dataset?

The outer tropical cyclone (TC) size was extracted from the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation global atmospheric reanalysis (ERA5), the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), and the ECMWF Interim reanalysis (ERA-I), as well as a hybrid reanalysis-observation dataset, the Cross Calibrated Multi-Platform (CCMP) ocean surface wind vector product. Results are compared with the QuikSCAT Tropical Cyclone Radial Structure Dataset (QSCAT-R). Several size metrics were applied including the radii of 6–15 m s−1 winds. The capability of ERA5 in describing TC outer wind fields was evaluated, and improvements in the representation of outer size assessed.The ERA5 reanalysis can resolve stronger TC winds, which leads to more valid outer size samples, especially for the radii of 12 and 15 m s−1 winds, and for the cases with outer sizes of <300 km. This makes the distribution characteristics of the outer size in the ERA5 reanalysis closer to the observation. These improvements of ERA5 are more obvious in the eastern North Pacific basin where TCs are generally of smaller size. However, ERA5 still underestimates the outer size, similarly to its predecessor ERA-I. The size error in ERA5 becomes more negative with increasing observed outer size, with this tendency also occurring in previous reanalysis datasets. Nevertheless, among the size metrics examined, the radius of 9 m s−1 winds is regarded as the optimal size metric for examining the extent of outer winds, thus providing an effective reference for constructing an objective, multi-decadal dataset of outer size using the ERA5 reanalysis.

Drivers and Surface Signal of Interannual Variability of Boreal Stratospheric Final Warmings

AbstractSpringtime stratospheric final warming (SFW) variability has been suggested to be linked to the tropospheric circulation, particularly over the North Atlantic sector. These findings, however, are based on reanalysis data that cover a rather short period of time (1979 to present). The present work aims to improve the understanding of drivers, trends and surface impact of dynamical variability of boreal SFWs using chemistry‐climate models. We use multidecadal integrations of the fully coupled chemistry‐climate models Community Earth System Model version 1 (Whole Atmosphere Community Climate Model) and ECHAM/Modular Earth Submodel System Atmospheric Chemistry‐O. Four sensitivity experiments are analyzed to assess the impact of external factors; namely, the quasi‐biennial oscillation, sea surface temperature (SST) variability, and anthropogenic emissions. SFWs are classified into two types with respect to their vertical development; that is, events which occur first in the midstratosphere (10‐hPa first SFWs) or first in the upper stratosphere (1‐hPa first SFWs). Our results confirm previous reanalysis results regarding the differences in the time evolution of stratospheric conditions and near‐surface circulation between 10 and 1‐hPa first SFWs. Additionally, a tripolar SST pattern is, for the first time, identified over the North Atlantic in spring months related to the SFW variability. Our analysis of the influence of remote modulators on SFWs revealed that the occurrence of major warmings in the previous winter favors the occurrence of 10‐hPa first SFWs later on. We further found that quasi‐biennial oscillation and SST variability significantly affect the ratio between 1‐hPa first and 10‐hPa first SFWs. Finally, our results suggest that ozone recovery may impact the timing of the occurrence of 1‐hPa first SFWs.

Assessment of MERRA-2 Land Surface Energy Flux Estimates

In the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) system the land is forced by replacing the model-generated precipitation with observed precipitation before it reaches the surface. This approach is motivated by the expectation that the resultant improvements in soil moisture will lead to improved land surface latent heating (LH). Here aspects of the MERRA-2 land surface energy budget and 2-m air temperatures [Formula: see text] are assessed. For global land annual averages, MERRA-2 appears to overestimate the LH (by 5 W m−2), the sensible heating (by 6 W m−2), and the downwelling shortwave radiation (by 14 W m−2) while underestimating the downwelling and upwelling (absolute) longwave radiation (by 10–15 W m−2each). These results differ only slightly from those for NASA’s previous reanalysis, MERRA. Comparison to various gridded reference datasets over boreal summer (June–August) suggests that MERRA-2 has particularly large positive biases (&gt;20 W m−2) where LH is energy limited and that these biases are associated with evaporative fraction biases rather than radiation biases. For time series of monthly means during boreal summer, the globally averaged anomaly correlations [Formula: see text] with reference data were improved from MERRA to MERRA-2, for LH (from 0.39 to 0.48 vs Global Land Evaporation Amsterdam Model data) and the daily maximum T2m(from 0.69 to 0.75 vs Climatic Research Unit data). In regions where [Formula: see text] is particularly sensitive to the precipitation corrections (including the central United States, the Sahel, and parts of South Asia), the changes in the [Formula: see text] [Formula: see text] are relatively large, suggesting that the observed precipitation influenced the [Formula: see text] performance.

Can Missing Data Boundary Estimates Cast Doubt On Previous Conclusions Reevaluating A 10 Year Cost-Effectiveness Analysis (CEA) Of The Diabetes Prevention Program Outcomes Study (DPP/DPPOS)?

In a previous reanalysis of this CEA of placebo, metformin, individual and group lifestyle (ILS and GLS) interventions, we showed, contrary to the original study’s claim, that there appeared to be no place for metformin in diabetes prevention. Here we explore whether unknown (and ignored) results from missing study participants, could have had an effect on the results and to explore the implications for decision uncertainty via probabilistic sensitivity analysis (PSA). Manski (1989) suggested using boundary estimates to estimate potential effects of missing data without making potentially unreasonable assumptions about such data (e.g. ignorability). We implemented this by assuming all missing participants were alternatively diabetic and non-diabetic for each intervention, and assigning mean QALYs and costs conditional on diabetes status. To test the ability to contest our previous conclusion on metformin not having a place in diabetes prevention, we focused on the lifestyle pessimistic case (all missing had diabetes) vs. the metformin optimistic case (all missing remained pre-diabetes). GLS remained cost-effective relative to the other three interventions (pessimistic ILS dominated). The incremental cost-effectiveness ratio (ICER) between GLS pessimistic (highest QALYs) and metformin optimistic was approximately $32,000/QALY. CEAC/Fs showed that GLS pessimistic probability of being cost-effective was the highest of the interventions at a WTP approximately equal to that ICER. If GLS was not available, the ICER between ILS pessimistic and metformin optimistic was approximately $55,700. Even using pessimistic GLS estimates, GLS remained the cost-effective choice. If for some reason, GLS is not available, pessimistic ILS is cost-effective compared to optimistic metformin at conventional WTP threshold values. Based on these data, even when using boundary estimates to the maximal advantage of metformin, there appears to be no place for metformin in diabetes prevention. Other rationales would need to be employed (e.g. heterogeneity of treatment effect, unexplored here).

Assessing surface heat fluxes in atmospheric reanalyses with a decade of data from the NOAA Kuroshio Extension Observatory

AbstractPrevious studies have found large biases and uncertainties in the air‐sea fluxes from Numerical Weather Prediction model reanalyses, which must be identified and reduced in order to make progress on weather and climate predictions. Here air‐sea heat fluxes from NOAA Kuroshio Extension Observatory (KEO) measurements are used to assess two new reanalyses, NCEP's Climate Forecast System Reanalysis (CFSR) and ECMWF Reanalysis‐Interim (ERA‐I), suggesting that these two new generation reanalyses have significantly improved. In both reanalyses, all four flux components (sensible and latent heat flux and net longwave and shortwave radiation) are highly correlated with observation, with the correlation of total net surface heat fluxes above 0.96. Although errors of the net surface heat flux have significantly reduced from previous reanalyses, the Root Mean Square Errors (RMSEs) and biases remain high especially for CFSR: the RMSEs of CFSR and ERA‐I are reduced by 25–30% to 64 and 61 W/m2, respectively, while biases are reduced by 40–60% to 28 and 20 W/m2. But CFSR overestimates the winter heat release by 90 W/m2. The main cause of biases is the latent heat flux, while RMS errors are primarily due to latent heat flux and shortwave radiation errors. Both reanalyses overestimate the wind speed associated with winter storms and underestimate specific humidity in summer. The ERA‐I latent heat flux and its total net surface heat flux are however closer to observation. It is the bulk algorithm in CFSR that is found to be mainly responsible for overestimates of winter heat release in CFSR.

Atmospheric circulation patterns associated with extreme cold winters in the UK

This study examines the atmospheric circulation patterns and surface features associated with the seven coldest winters in the U.K. since 1870, using the 20th Century Reanalysis. Six of these winters are outside the scope of previous reanalysis datasets; we examine them here for the first time. All winters show a marked lack of the climatological southwesterly flow over the UK, displaying easterly and northeasterly anomalies. Six of the seven winters (all except 1890) were associated with a negative phase of the North Atlantic Oscillation; 1890 was characterised by a blocking anticyclone over and northeast of the UK.

The JRA-55 Reanalysis: General Specifications and Basic Characteristics

The Japan Meteorological Agency (JMA) conducted the second Japanese global atmospheric reanalysis, called the Japanese 55-year Reanalysis or JRA-55. It covers the period from 1958, when regular radiosonde observations began on a global basis. JRA-55 is the first comprehensive reanalysis that has covered the last half-century since the European Centre for Medium-Range Weather Forecasts 45-year Reanalysis (ERA-40), and is the first one to apply four-dimensional variational analysis to this period. The main objectives of JRA-55 were to address issues found in previous reanalyses and to produce a comprehensive atmospheric dataset suitable for studying multidecadal variability and climate change. This paper describes the observations, data assimilation system, and forecast model used to produce JRA-55 as well as the basic characteristics of the JRA-55 product. JRA-55 has been produced with the TL319 version of JMA’s operational data assimilation system as of December 2009, which was extensively improved since the Japanese 25-year Reanalysis (JRA-25). It also uses several newly available and improved past observations. The resulting reanalysis products are considerably better than the JRA-25 product. Two major problems of JRA-25 were a cold bias in the lower stratosphere, which has been diminished, and a dry bias in the Amazon basin, which has been mitigated. The temporal consistency of temperature analysis has also been considerably improved compared to previous reanalysis products. Our initial quality evaluation revealed problems such as a warm bias in the upper troposphere, large upward imbalance in the global mean net energy fluxes at the top of the atmosphere and at the surface, excessive precipitation over the tropics, and unrealistic trends in analyzed tropical cyclone strength. This paper also assesses the impacts of model biases and changes in the observing system, and mentions efforts to further investigate the representation of low-frequency variability and trends in JRA-55.

The functional and numerical responses ofTrissolcus basalis(Hymenoptera: Platygastridae) parasitizingNezara viridula(Hemiptera: Pentatomidae) eggs in the field

Trissolcus basalis has been used as a biological control agent of its main host, Nezara viridula, in many countries. However, estimations of its functional and numerical responses in the field are lacking. We estimated the density of N. viridula eggs, the proportion of parasitized N. viridula eggs, and the number of T. basalis adults/trap in the field. We transformed relative parasitoid density to an absolute density, and estimated the parasitoid's attack rate, a, and the mutual interference parameter, m, in two ways: following Arditi & Akçakaya (1990) and using the Holling-Hassell-Varley model with two iterative techniques. The attack rate estimated by both methods were a=1.097 and a=0.767, respectively. Parameter m varied less between methods: m=0.563 and m=0.586, respectively, and when used to calculate the number of parasitized N. viridula eggs per m2, differences with the observed values were not significant. The numerical response of T. basalis was affected by the sex allocation of their progeny and the proportion of adult parasitoids trapped decreased with field parasitoid population density. Theoretical models show that 0<m<1 is a stabilizing factor and previous re-analysis of field data showed a mean m value of 0.8. The Holling-Hassell-Varley model leads to a flexible description of the functional response allowing to predict acceptable weekly host parasitism. The pre-imaginal parasitoid survival and the change in sex ratio as a function of parasitoid density adequately describe the numerical functional response of the parasitoid.

Evaluating the tropospheric variability in National Centers for Environmental Prediction's climate forecast system reanalysis

[1] The National Centers for Environmental Prediction (NCEP) recently completed the latest, and partially coupled, atmosphere-ocean–sea ice model–based climate forecast system reanalysis (CFSR) for the 1979 to current satellite era. In the reanalysis, the observed CO2 concentration and the volcanic aerosols were also prescribed. This paper provides an initial overview of the tropospheric variability in the CFSR by comparing it against available previous reanalyses. CFSR's monthly mean zonal and meridional component of wind U and V, temperature T, and geopotential height H at pressure levels up to 100 mb are compared against those of three other readily available reanalyses NCEP/R1, NCEP/R2 and ERA40 for the period from 1979 to 2008 (2002 for ERA40) and also against modern reanalyses such as JRA, MERRA, and C20. At any given time (analysis hour, day, or month), for the globe as a whole, CFSR analysis agrees reasonably well with the other reanalyses. The CFSR's new coupled model and assimilation system makes use of the recent advances in these areas and hence is possibly an improvement to NCEP's previous reanalyses R1 and R2, which are 15 and 10 years old, respectively. For these long-term climate variability measures the analysis indicates that the CFSR was generally the outlier, with much stronger easterly trades, cooler tropospheric temperatures, and lower geopotential heights during much of the earlier part of the analysis period (1979–∼1998). Consequently, real-time monitoring of many of the ENSO-related climate wind indices in the equatorial Pacific or the wind shear index in the tropical North Atlantic from CFSR may be problematic in the context of historical variability.

Geomagnetic activity related NO&amp;lt;sub&amp;gt;x&amp;lt;/sub&amp;gt; enhancements and polar surface air temperature variability in a chemistry climate model: modulation of the NAM index

Abstract. The atmospheric chemistry general circulation model ECHAM5/MESSy is used to simulate polar surface air temperature effects of geomagnetic activity variations. A transient model simulation was performed for the years 1960–2004 and is shown to develop polar surface air temperature patterns that depend on geomagnetic activity strength, similar to previous studies. In order to eliminate influencing factors such as sea surface temperatures (SST) or UV variations, two nine-year long simulations were carried out, with strong and weak geomagnetic activity, respectively, while all other boundary conditions were held to year 2000 levels. Statistically significant temperature effects that were observed in previous reanalysis and model results are also obtained from this set of simulations, suggesting that such patterns are indeed related to geomagnetic activity. In the model, strong geomagnetic activity and the associated NOx (= NO + NO2) enhancements lead to polar stratospheric ozone loss. Compared with the simulation with weak geomagnetic activity, the ozone loss causes a decrease in ozone radiative cooling and thus a temperature increase in the polar winter mesosphere. Similar to previous studies, a cooling is found below the stratopause, which other authors have attributed to a decrease in the mean meridional circulation. In the polar stratosphere this leads to a more stable vortex. A strong (weak) Northern Hemisphere vortex is known to be associated with a positive (negative) Northern Annular Mode (NAM) index; our simulations exhibit a positive NAM index for strong geomagnetic activity, and a negative NAM for weak geomagnetic activity. Such NAM anomalies have been shown to propagate to the surface, and this is also seen in the model simulations. NAM anomalies are known to lead to specific surface temperature anomalies: a positive NAM is associated with warmer than average northern Eurasia and colder than average eastern North Atlantic. This is also the case in our simulation. Our simulations suggest a link between geomagnetic activity, ozone loss, stratospheric cooling, the NAM, and surface temperature variability. Further work is required to identify the precise cause and effect of the coupling between these regions.

Daily Precipitation Statistics for South America: An Intercomparison between NCEP Reanalyses and Observations

Abstract In this study, the authors document the extent to which the precipitation statistics of the new CFS reanalysis (CFSR) represent an improvement over the earlier reanalyses: the NCEP–NCAR reanalysis (R1) and the NCEP–DOE Second Atmospheric Model Intercomparison Project (AMIP-II) reanalysis (R2). An intercomparison between the CFSR, R1, R2, and observations over South America was made for the period 1979–2006. The CFSR shows notable improvements in the large-scale precipitation patterns compared with the previous reanalyses (R1 and R2). In spite of these improvements, the CFSR has substantial biases in intensity and frequency of occurrence of rainfall events. Over west-central Brazil, the core region of the South American monsoon system (SAMS), the CFSR displays a dry bias during the onset phase of the SAMS wet season and a wet bias during the peak and decay phases of the SAMS wet season. The CFSR also displays a dry bias along the South American coast near the mouth of the Amazon and along the east coast of northeastern Brazil. A wet bias exists in all seasons over southeast Brazil and over the Andes Mountains.

An assessment of oceanic variability in the NCEP climate forecast system reanalysis

At the National Centers for Environmental Prediction (NCEP), a reanalysis of the atmosphere, ocean, sea ice and land over the period 1979–2009, referred to as the climate forecast system reanalysis (CFSR), was recently completed. The oceanic component of CFSR includes many advances: (a) the MOM4 ocean model with an interactive sea-ice, (b) the 6 h coupled model forecast as the first guess, (c) inclusion of the mean climatological river runoff, and (d) high spatial (0.5° × 0.5°) and temporal (hourly) model outputs. Since the CFSR will be used by many in initializing/validating ocean models and climate research, the primary motivation of the paper is to inform the user community about the saline features in the CFSR ocean component, and how the ocean reanalysis compares with in situ observations and previous reanalysis. The net ocean surface heat flux of the CFSR has smaller biases compared to the sum of the latent and sensible heat fluxes from the objectively analyzed air-sea fluxes (OAFlux) and the shortwave and longwave radiation fluxes from the International Satellite Cloud Climatology Project (ISCCP-FD) than the NCEP/NCAR reanalysis (R1) and NCEP/DOE reanalysis (R2) in both the tropics and extratropics. The ocean surface wind stress of the CFSR has smaller biases and higher correlation with the ERA40 produced by the European Centre for Medium-Range Weather Forecasts than the R1 and R2, particularly in the tropical Indian and Pacific Ocean. The CFSR also has smaller errors compared to the QuickSCAT climatology for September 1999 to October 2009 than the R1 and R2. However, the trade winds of the CFSR in the central equatorial Pacific are too strong prior to 1999, and become close to observations once the ATOVS radiance data are assimilated in late 1998. A sudden reduction of easterly wind bias is related to the sudden onset of a warm bias in the eastern equatorial Pacific temperature around 1998/1999. The sea surface height and top 300 m heat content (HC300) of the CFSR compare with observations better than the GODAS in the tropical Indian Ocean and extratropics, but much worse in the tropical Atlantic, probably due to discontinuity in the deep ocean temperature and salinity caused by the six data streams of the CFSR. In terms of climate variability, the CFSR provides a good simulation of tropical instability waves and oceanic Kelvin waves in the tropical Pacific, and the dominant modes of HC300 that are associated with El Nino and Southern Oscillation, Indian Ocean Dipole, Pacific Decadal Oscillation and Atlantic Meridional Overturning Circulation.

An assessment of the surface climate in the NCEP climate forecast system reanalysis

This paper analyzes surface climate variability in the climate forecast system reanalysis (CFSR) recently completed at the National Centers for Environmental Prediction (NCEP). The CFSR represents a new generation of reanalysis effort with first guess from a coupled atmosphere–ocean–sea ice–land forecast system. This study focuses on the analysis of climate variability for a set of surface variables including precipitation, surface air 2-m temperature (T2m), and surface heat fluxes. None of these quantities are assimilated directly and thus an assessment of their variability provides an independent measure of the accuracy. The CFSR is compared with observational estimates and three previous reanalyses (the NCEP/NCAR reanalysis or R1, the NCEP/DOE reanalysis or R2, and the ERA40 produced by the European Centre for Medium-Range Weather Forecasts). The CFSR has improved time-mean precipitation distribution over various regions compared to the three previous reanalyses, leading to a better representation of freshwater flux (evaporation minus precipitation). For interannual variability, the CFSR shows improved precipitation correlation with observations over the Indian Ocean, Maritime Continent, and western Pacific. The T2m of the CFSR is superior to R1 and R2 with more realistic interannual variability and long-term trend. On the other hand, the CFSR overestimates downward solar radiation flux over the tropical Western Hemisphere warm pool, consistent with a negative cloudiness bias and a positive sea surface temperature bias. Meanwhile, the evaporative latent heat flux in CFSR appears to be larger than other observational estimates over most of the globe. A few deficiencies in the long-term variations are identified in the CFSR. Firstly, dramatic changes are found around 1998–2001 in the global average of a number of variables, possibly related to the changes in the assimilated satellite observations. Secondly, the use of multiple streams for the CFSR induces spurious jumps in soil moisture between adjacent streams. Thirdly, there is an inconsistency in long-term sea ice extent variations over the Arctic regions between the CFSR and other observations with the CFSR showing smaller sea ice extent before 1997 and larger extent starting in 1997. These deficiencies may have impacts on the application of the CFSR for climate diagnoses and predictions. Relationships between surface heat fluxes and SST tendency and between SST and precipitation are analyzed and compared with observational estimates and other reanalyses. Global mean fields of surface heat and water fluxes together with radiation fluxes at the top of the atmosphere are documented and presented over the entire globe, and for the ocean and land separately.

Diurnal to Annual Precipitation Sensitivity to Convective and Land Surface Schemes

Abstract Precipitation’s diurnal to annual variance distribution and atmospheric water cycle component interactions are examined globally for sensitivity to convective and land surface schemes. The main regional features of statistics identified in previous reanalyses are robust in unconstrained continuous simulations corresponding to the reanalyses’ convective and land surface schemes. A change from the simplified Arakawa–Schubert (SAS) to the relaxed Arakawa–Schubert (RAS) convection scheme reorganizes the variance of rainfall at low latitudes to a redder spectrum. Despite the potential increase in soil moisture memory, a change from the Oregon State University (OSU2) to the Noah land surface model does not noticeably affect the variance distribution of precipitation. The competition between dynamic and thermodynamic sources of precipitation’s variability is affected by the choice of both the land surface model and the convective scheme. Noah reduces evaporation’s role over land, with vapor convergence compensating, while RAS/SAS sensitivities result in complex regional redistributions of component covariance.

Satellite data reveal the 3‐D moisture structure of Tropical Intraseasonal Oscillation and its coupling with underlying ocean

The water‐vapor profiles obtained from the Atmospheric Infrared Sounder (AIRS) on Satellite Aqua are used to document the 3‐D moisture structure of the boreal‐summer Tropical Intraseasonal Oscillation (TISO) over the Indo‐western Pacific region. With the support of several other Satellite data sets, the interactions between the TISO and underlying ocean are also investigated. The AIRS data reveal much larger tropospheric moisture perturbations than those depicted in previous reanalysis and analysis data sets. It also reveals a drying Atmospheric Boundary Layer (ABL) below the TISO convection probably due to the associated downdrafts. Before the occurrence of TISO convection, both positive Sea Surface Temperature (SST) anomaly and ABL moistening are observed. Further analysis suggests that the positive SST anomaly is the major contributor to the ABL moistening through enhancing surface evaporation. Therefore, the intraseasonal SST anomaly could positively feed back to the atmosphere through moistening the boundary layer, destabilizing the troposphere, and contributing to the northeastward propagation of the TISO.