A long-term global atmospheric reanalysis, named ''Japanese 25-year Reanalysis (JRA-25)'' was completed using the Japan Meteorological Agency (JMA) numerical assimilation and forecast system. The analysis covers the period from 1979 to 2004. This is the first long-term reanalysis undertaken in Asia. JMA's latest numerical assimilation system, and specially collected observational data, were used to generate a consistent and high-quality reanalysis dataset designed for climate research and operational monitoring and forecasts. One of the many purposes of JRA-25 is to enhance the analysis to a high quality in the Asian region.Six-hourly data assimilation cycles were performed, producing 6-hourly atmospheric analysis and forecast fields of various physical variables. The global model used in JRA-25 has a spectral resolution of T106 (equivalent to a horizontal grid size of around 120 km) and 40 vertical layers with the top level at 0.4 hPa. In addition to conventional surface and upper air observations, atmospheric motion vector (AMV) wind retrieved from geostationary satellites, brightness temperature from TIROS Operational Vertical Sounder (TOVS), precipitable water retrieved from orbital satellite microwave radiometer radiance and other satellite data are assimilated with three-dimensional variational method (3D-Var). JMA produced daily sea surface temperature (SST), sea ice and three-dimensional ozone profiles for JRA-25. A new quality control method for TOVS data was developed and applied in advance.Many advantages have been found in the JRA-25 reanalysis. Predicted 6-hour global total precipitation distribution and amount are well reproduced both in space and time. The performance of the long time series of the global precipitation is the best among the other reanalyses, with few unrealistic variations from degraded satellite data contaminated by volcanic eruptions. Secondly, JRA-25 is the first reanalysis to assimilate wind profiles around tropical cyclones reconstructed from historical best track information; tropical cyclones were analyzed properly in all the global regions. Additionally, low-level cloud along the subtropical western coast of continents is well simulated and snow depth analysis is also of a good quality. The article also covers material which requires attention when using JRA-25.

We present an overview of results from 11 integrated assessment models (IAMs) that participated in the 33 rd study of the Stanford Energy Modeling Forum (EMF-33) on the viability of large-scale deployment of bioenergy for achieving long-run climate goals. The study explores future bioenergy use across models under harmonized scenarios for future

Abstract. Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

The response of the North Atlantic thermohaline circulation to idealized climate forcing of 1% per year compound increase in CO 2 is examined in three configurations of the Community Climate System Model version 3 that differ in their component model resolutions. The strength of the Atlantic overturning circulation declines at a rate of 22%-26% of the corresponding control experiment maximum overturning per century in response to the increase in CO 2 . The mean meridional overturning and its variability on decadal time scales in the control experiments, the rate of decrease in the transient forcing experiments, and the rate of recovery in periods of CO 2 stabilization all increase with increasing component model resolution. By examining the changes in ocean surface forcing with increasing CO 2 in the framework of the water-mass transformation function, we show that the decline in the overturning is driven by decreasing density of the subpolar North Atlantic due to increasing surface heat fluxes. While there is an intensification of the hydrologic cycle in response to increasing CO 2 , the net effect of changes in surface freshwater fluxes on those density classes that are involved in deep-water formation is to increase their density; that is, changes in surface freshwater fluxes act to maintain a stronger overturning circulation. The differences in the control experiment overturning strength and the response to increasing CO 2 are well predicted by the corresponding differences in the water-mass transformation rate. Reduction of meridional heat transport and enhancement of meridional salt transport from mid-to high latitudes with increasing CO 2 also act to strengthen the overturning circulation. Analysis of the trends in an ideal age tracer provides a direct measure of changes in ocean ventilation time scale in response to increasing CO 2 . In the subpolar North Atlantic south of the Greenland-Scotland ridge system, there is a significant increase in subsurface ages as open-ocean deep convection is diminished and ventilation switches to a predominance of overflow waters. In middle and low latitudes there is a decrease in age within and just below the thermocline in response to a decrease in the upwelling of old deep waters. However, when considering ventilation within isopycnal layers, age increases for layers in and below the thermocline due to the deepening of isopycnals in response to global warming.

SUMMARYThe progress and status of a new atmospheric re-analysis, JRA-25 the Japanese 25-year Re-analysis which covers the 26 years from 1979 to 2004, are introduced. Observational data include some newly produced for JRA-25 and advantages and drawbacks of performance are briefly described. JRA-25 has many advantages such as its handling of precipitation amounts, tropical cyclone analysis, and the extent of low-level cloud along western continents that are among the best compared to other re-analyses. The snow analysis is also good and stable. JRA-25 outputs analysis products every 6 hours.

Abstract. Here we present an update to the FaIR model for use in probabilistic future climate and scenario exploration, integrated assessment, policy analysis, and education. In this update we have focussed on identifying a minimum level of structural complexity in the model. The result is a set of six equations, five of which correspond to the standard impulse response model used for greenhouse gas (GHG) metric calculations in the IPCC's Fifth Assessment Report, plus one additional physically motivated equation to represent state-dependent feedbacks on the response timescales of each greenhouse gas cycle. This additional equation is necessary to reproduce non-linearities in the carbon cycle apparent in both Earth system models and observations. These six equations are transparent and sufficiently simple that the model is able to be ported into standard tabular data analysis packages, such as Excel, increasing the potential user base considerably. However, we demonstrate that the equations are flexible enough to be tuned to emulate the behaviour of several key processes within more complex models from CMIP6. The model is exceptionally quick to run, making it ideal for integrating large probabilistic ensembles. We apply a constraint based on the current estimates of the global warming trend to a million-member ensemble, using the constrained ensemble to make scenario-dependent projections and infer ranges for properties of the climate system. Through these analyses, we reaffirm that simple climate models (unlike more complex models) are not themselves intrinsically biased “hot” or “cold”: it is the choice of parameters and how those are selected that determines the model response, something that appears to have been misunderstood in the past. This updated FaIR model is able to reproduce the global climate system response to GHG and aerosol emissions with sufficient accuracy to be useful in a wide range of applications and therefore could be used as a lowest-common-denominator model to provide consistency in different contexts. The fact that FaIR can be written down in just six equations greatly aids transparency in such contexts.

A new long-term reanalysis project, JRA-25, has set as one of its main goals the realistic representation of tropical cyclones (TCs) in the reanalysis. To supplement in situ observations near TCs, wind profile data (TCR data) are retrieved based on best track information and assimilated. This paper addresses the benefits of using TCR data for the analysis of TCs.TC representation in the JRA-25 reanalysis is compared with other reanalysis data, and an experimental reanalysis (Control) without TCR data. The general result is that JRA-25 successfully represents the location and intensity of each TC. Among TC basins in the Northern Hemisphere, the TC representation in the JRA-25 data in the eastern North Pacific, and in the tropical Atlantic, where upper observations are sparse, is superior compared to other datasets that did not assimilate TCR data. In the western North Pacific, especially around Japan and the East China Sea, TCR data give little improvement in TC representation, since conventional upper observations are dense there and upstream of the active TC regions.TC detection rates in the Northern basins and over the entire globe, are computed using an objective procedure from the reanalysis datasets. The rate in JRA-25 is the highest in all basins among the datasets, and consistent through the period. The high qualified TC representation in intensity and location has a positive effect on a flow field, and hydrologic cycle around TCs. Case studies of TC track forecasts for a recurving TC, in which reanalysis data are used as initial conditions, suggest the JRA-25 data are more realistic than the Control. For these reasons, TCR data is effective in representing TCs and surrounding atmospheric conditions in JRA-25.

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