World Climate Research Programme Research Articles

Attribution of multi-annual to decadal changes in the climate system: The Large Ensemble Single Forcing Model Intercomparison Project (LESFMIP)

Multi-annual to decadal changes in climate are accompanied by changes in extreme events that cause major impacts on society and severe challenges for adaptation. Early warnings of such changes are now potentially possible through operational decadal predictions. However, improved understanding of the causes of regional changes in climate on these timescales is needed both to attribute recent events and to gain further confidence in forecasts. Here we document the Large Ensemble Single Forcing Model Intercomparison Project that will address this need through coordinated model experiments enabling the impacts of different external drivers to be isolated. We highlight the need to account for model errors and propose an attribution approach that exploits differences between models to diagnose the real-world situation and overcomes potential errors in atmospheric circulation changes. The experiments and analysis proposed here will provide substantial improvements to our ability to understand near-term changes in climate and will support the World Climate Research Program Lighthouse Activity on Explaining and Predicting Earth System Change.

Ocean negative carbon emissions: A new UN Decade program

Ocean negative carbon emissions: A new UN Decade program

Network connectivity between the winter Arctic Oscillation and summer sea ice in CMIP6 models and observations

Abstract. The indirect effect of winter Arctic Oscillation (AO) events on the following summer Arctic sea ice extent suggests an inherent winter-to-summer mechanism for sea ice predictability. On the other hand, operational regional summer sea ice forecasts in a large number of coupled climate models show a considerable drop in predictive skill for forecasts initialised prior to the date of melt onset in spring, suggesting that some drivers of sea ice variability on longer timescales may not be well represented in these models. To this end, we introduce an unsupervised learning approach based on cluster analysis and complex networks to establish how well the latest generation of coupled climate models participating in phase 6 of the World Climate Research Programme Coupled Model Intercomparison Project (CMIP6) are able to reflect the spatio-temporal patterns of variability in Northern Hemisphere winter sea-level pressure and Arctic summer sea ice concentration over the period 1979–2020, relative to ERA5 atmospheric reanalysis and satellite-derived sea ice observations, respectively. Two specific global metrics are introduced as ways to compare patterns of variability between models and observations/reanalysis: the adjusted Rand index – a method for comparing spatial patterns of variability – and a network distance metric – a method for comparing the degree of connectivity between two geographic regions. We find that CMIP6 models generally reflect the spatial pattern of variability in the AO relatively well, although they overestimate the magnitude of sea-level pressure variability over the north-western Pacific Ocean and underestimate the variability over northern Africa and southern Europe. They also underestimate the importance of regions such as the Beaufort, East Siberian, and Laptev seas in explaining pan-Arctic summer sea ice area variability, which we hypothesise is due to regional biases in sea ice thickness. Finally, observations show that historically, winter AO events (negatively) covary strongly with summer sea ice concentration in the eastern Pacific sector of the Arctic, although now under a thinning ice regime, both the eastern and western Pacific sectors exhibit similar behaviour. CMIP6 models however do not show this transition on average, which may hinder their ability to make skilful seasonal to inter-annual predictions of summer sea ice.

Assesment of the CMIP6 models to study interseasonal SSTvariabilities in the BoB

ABSTRACT The Coupled Model Intercomparison Project (CMIP) of the World Climate Research Program (WCRP) has provided a large number of AOGCMs, publicly available through CMIP6, for a better understanding of global and regional-scale ocean dynamics. This study analyzes the SST outputs of 22 models in CMIP6 with AVHRR database for the NorthWest Bay of Bengal and gives the individual model performances in terms of performance indices and skill scores. It is shown that the CAMS-CSM1, which was designed for the East Asian region, has the best performance at a skill score of 0.95, whereas NorCPM1 has the worst performance with a skill score of 0.55 for the interseasonal timescales in the Bay of Bengal. Correlations of the net heat flux (with a correlation of 0.5) and solar insolation (with a correlation of 0.9) with SST are carried out as they are the primary drivers of SST variability interseasonally. Finally, a case study is conducted to study the seasonal features of upwelling in NorthWest BoB, which shows that only a few models are capable of adequately reproducing the upwelling, and conclude that the CAMS-CSM1 is most suitable for the BoB.

Added value of EURO-CORDEX high-resolution downscaling over the Iberian Peninsula revisited – Part 2: Max and min temperature

Abstract. In the recent past, an increase in computation resources led to the development of regional climate models with increasing domains and resolutions, spanning larger temporal periods. A good example is the World Climate Research Program – Coordinated Regional Climate Downscaling Experiment for the European domain (EURO-CORDEX). This set of regional models encompasses the entire European continent for a 130-year common period until the end of the 21st century, while having a 12 km horizontal resolution. Such simulations are computationally demanding, while at the same time not always showing added value. This study considers a recently proposed metric in order to assess the added value of the EURO-CORDEX hindcast (1989–2008) and historical (1971–2005) simulations for the maximum and minimum temperature over the Iberian Peninsula. This approach allows an evaluation of the higher against the driving lower resolutions relative to the performance of the whole or partial probability density functions by having an observational regular gridded dataset as a reference. Overall, the gains for maximum temperature are more relevant in comparison to minimum temperature, partially due to known problems derived from the snow–albedo–atmosphere feedback. For more local scales, areas near the coast reveal higher added value in comparison with the interior, which displays limited gains and sometimes notable detrimental effects with values around −30 %. At the same time, the added value for temperature extremes reveals a similar range, although with larger gains in coastal regions and in locations from the interior for maximum temperature, contrasting with the losses for locations in the interior of the domain for the minimum temperature.

Aegean Sea-Level Variability in the Past Half-Century Based on Tide Gauge Data

Global sea-level rise induced by global warming has been growing in importance as a research topic in the past few decades. The Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) has strongly emphasized a visually certain trend in the sea-level rise in the past two centuries. Many studies have addressed the trend in sea-level records, both in global and regional scale, as studying the trend renders it possible to make future predictions. The latest study of World Climate Research Programme Global Sea Level Budget Group determined the global sea-level rise between 1993-2018 as 3.1 mm/year. The Aegean as a regional sea is chosen for this study to compare if there are any similarities between the global tendency and the regional using tide gauge records of monthly mean sea-levels in selected 6 stations. The data used in this study were obtained from the Permanent Service for Mean Sea Level (PSMSL), which is an organization that collects and publishes tide gauge records from across the world. The gaps in the raw tide gauge data were imputed by Kalman filtering, the time series were decomposed by using STL decomposition and the loess smoothed trend lines were obtained. The data ranges of time series were divided into 2 segments (from 1969 to 1995 and from 1995 to the end date) and linear trends for each segment were determined as well as the whole duration for each station. Mann-Kendall, Cox-Stuart, and Spearman’s Rho tests were applied on the datasets to detect statistically significant trends. The sea-level trends varied for each station and depending on the segment taken into consideration. 2 negative and 2 positive trends were obtained for the first segment. Positive trends changing from 1.6 mm/year to 7.5 mm/year with an average of 3.7 mm/year were determined for the second segment’s results of all stations.

ACCESS datasets for CMIP6: methodology and idealised experiments

The Australian Community Climate and Earth System Simulator (ACCESS) has contributed to the World Climate Research Programme’s Coupled Model Intercomparison Project Phase 6 (CMIP6) using two fully coupled model versions (ACCESS-CM2 and ACCESS-ESM1.5) and two ocean–sea-ice model versions (1° and 0.25° resolution versions of ACCESS-OM2). The fully coupled models differ primarily in the configuration and version of their atmosphere components (including the aerosol scheme), with smaller differences in their sea-ice and land model versions. Additionally, ACCESS-ESM1.5 includes biogeochemistry in the land and ocean components and can be run with an interactive carbon cycle. CMIP6 comprises core experiments and associated thematic Model Intercomparison Projects (MIPs). This paper provides an overview of the CMIP6 submission, including the methods used for the preparation of input forcing datasets and the post-processing of model output, along with a comprehensive list of experiments performed, detailing their initialisation, duration, ensemble number and computational cost. A small selection of model output is presented, focusing on idealised experiments and their variants at global scale. Differences in the climate simulation of the two coupled models are highlighted. ACCESS-CM2 produces a larger equilibrium climate sensitivity (4.7°C) than ACCESS-ESM1.5 (3.9°C), likely a result of updated atmospheric parameterisation in recent versions of the atmospheric component of ACCESS-CM2. The idealised experiments run with ACCESS-ESM1.5 show that land and ocean carbon fluxes respond to both changing atmospheric CO2 and to changing temperature. ACCESS data submitted to CMIP6 are available from the Earth System Grid Federation (https://doi.org/10.22033/ESGF/CMIP6.2281 and https://doi.org/10.22033/ESGF/CMIP6.2288). The information provided in this paper should facilitate easier use of these significant datasets by the broader climate community.

NAO Influence on the MJO and its Prediction Skill in the Subseasonal-to-Seasonal Prediction Models

AbstractBased on the database of the Subseasonal to Seasonal (S2S) Prediction project of the World Weather Research Programme (WWRP) / World Climate Research Programme (WCRP), the influence of the North Atlantic Oscillation (NAO) on the Madden- Julian Oscillation (MJO) and its forecast skill is investigated. It is found that most models can capture the MJO phase changes following positive and negative NAO events. About 20 days after initialized with a positive (negative) NAO, the forecast MJO appears more frequently in phase 7 (3), which corresponds to reduced (enhanced) convection in the tropical Indian Ocean and enhanced (suppressed) convection in the western Pacific. In most S2S models the MJO prediction skill is dependent on the NAO amplitude and phase in the initial condition. A strong NAO leads to a better MJO forecast skill than a weak NAO. The MJO skill tends to be higher when the forecast starts from a negative NAO than a positive NAO. These results indicates that there is a strong Northern extratropical influence on the MJO and its forecast skill. It is important for numerical models to better represent the NAO influence to improve the simulation and prediction of the MJO.

Land-use harmonization datasets for annual global carbon budgets

Abstract. Land-use change has been the dominant source of anthropogenic carbon emissions for most of the historical period and is currently one of the largest and most uncertain components of the global carbon cycle. Advancing the scientific understanding on this topic requires that the best data be used as input to state-of-the-art models in well-organized scientific assessments. The Land-Use Harmonization 2 dataset (LUH2), previously developed and used as input for simulations of the 6th Coupled Model Intercomparison Project (CMIP6), has been updated annually to provide required input to land models in the annual Global Carbon Budget (GCB) assessments. Here we discuss the methodology for producing these annual LUH2-GCB updates and extensions which incorporate annual wood harvest data updates from the Food and Agriculture Organization (FAO) of the United Nations for dataset years after 2015 and the History Database of the Global Environment (HYDE) gridded cropland and grazing area data updates (based on annual FAO cropland and grazing area data updates) for dataset years after 2012, along with extrapolations to the current year due to a lag of 1 or more years in the FAO data releases. The resulting updated LUH2-GCB datasets have provided global, annual gridded land-use and land-use-change data relating to agricultural expansion, deforestation, wood harvesting, shifting cultivation, regrowth and afforestation, crop rotations, and pasture management and are used by both bookkeeping models and dynamic global vegetation models (DGVMs) for the GCB. For GCB 2019, a more significant update to LUH2 was produced, LUH2-GCB2019 (https://doi.org/10.3334/ORNLDAAC/1851, Chini et al., 2020b), to take advantage of new data inputs that corrected cropland and grazing areas in the globally important region of Brazil as far back as 1950. From 1951 to 2012 the LUH2-GCB2019 dataset begins to diverge from the version of LUH2 used for the World Climate Research Programme's CMIP6, with peak differences in Brazil in the year 2000 for grazing land (difference of 100 000 km2) and in the year 2009 for cropland (difference of 77 000 km2), along with significant sub-national reorganization of agricultural land-use patterns within Brazil. The LUH2-GCB2019 dataset provides the base for future LUH2-GCB updates, including the recent LUH2-GCB2020 dataset, and presents a starting point for operationalizing the creation of these datasets to reduce time lags due to the multiple input dataset and model latencies.

Toward a Society That Predicts and Adapts to Climate Change: Contribution of the World Climate Research Programme (WCRP)

Toward a Society That Predicts and Adapts to Climate Change: Contribution of the World Climate Research Programme (WCRP)

Climate Transition from Warm-Dry to Warm-Wet in Eastern Northwest China

During the second half of the 20th century, eastern Northwest China experienced a warming and drying climate change. To determine whether this trend has continued or changed during the present century, this study systematically analyzes the characteristics of warming and dry–wet changes in eastern Northwest China based on the latest observational data and World Climate Research Programme (WCRP) Coupled Model Intercomparison Project Phase 6 (CMIP6) collection data. The results show that eastern Northwest China has warmed continuously during the past 60 years with a sudden temperature change occurring in the late 1990s. However, the temperature in the 2000s decreased slowly, and that in the 2010s showed a warming trend. The amount of precipitation began to increase in the late 1990s, which indicates a contemporary climate transition from warm-dry to warm-wet in eastern Northwest China. The contribution of precipitation to humidity is significantly more than that of temperature. Long-term and interannual variations dominate the temperature change, with the contribution of the former much stronger than that of the latter. However, interannual variation dominates the precipitation change. The warming accelerates from period to period, and the temperature spatial consistently increased during the three most recent climatic periods. The precipitation decreased from 1961–1990 to 1981–2010, whereas its spatial consistency increased from 1981–2010 to 1991–2019. The significant warming and humidification which began in the late 1990s and is expected to continue until the end of the 21st century in the medium emission scenario. However, the current sub-humid climate will not easily be changed. The warming could cause a climate transition from warm temperate to subtropical by 2040. The dry-to-wet climate transition in eastern Northwest China could be related to a synergistic enhancement of the East Asian summer monsoon and the westerly circulation. This research provides a scientific decision-making basis for implementing western development strategies, ecological protection, and high-quality development of the Yellow River Basin Area as well as that for ecological construction planning and water resource management of eastern Northwest China.

Uncertainty in different precipitation products in the case of two atmospheric river events

One of the World Climate Research Programme Grand Challenges is to evaluate whether existing observations are enough to underpin the assessment of weather and climate extremes. In this study, we focus on extreme associated with atmospheric rivers (ARs). ARs are characterized by intense moisture transport usually from the tropics to the extra-tropics. They can either be beneficial, providing critical water supply, or hazardous, when excessive precipitation accumulation leads to floods. Here, we examine the uncertainty in gridded precipitation products included in the Frequent Rainfall Observations on GridS (FROGS) database during two atmospheric river events in distinct Mediterranean climates: one in California, USA, and another in Portugal. FROGS is composed of gridded daily-precipitation products on a common 1° × 1° grid to facilitate intercomparison and assessment exercises. The database includes satellite, ground-based and reanalysis (RE) products. Results show that the precipitation products based on satellite data, individually or combined with other products, perform least well in capturing daily precipitation totals over land during both cases studied here. The RE and the gauge-based products show the best agreement with local ground stations. As expected, there is an overall underestimation of precipitation by the different products. For the Portuguese AR, the multi-product ensembles reveal mean absolute percentage errors between −25% and −60%. For the western US case, the range is from −60% to −100%.

Assessing Future Impacts of Climate Change on Streamflow within the Alabama River Basin

Global climate change is expected to impact future precipitation and surface temperature trends and could alter local hydrologic systems. This study assessed the likely hydrologic responses and changes in streamflow due to future climate change within the Alabama River Basin (ARB) for the mid-21st century 2045 (“2030–2060”) and end-21st century 2075 (“2060–2090”). Using an integrated modeling approach, General Circulation Model (GCM) datasets; the Centre National de Recherches Météorologiques Climate Model 5 (CNRM-CM5), the Community Earth System Model, version 1–Biogeochemistry (CESM1- BGC.1), and the Hadley Centre Global Environment Model version 2 (HADGEM2-AO.1), under medium Representative Concentration Pathway (RCP) 4.5, and based on World Climate Research Program (WCRP)’s Couple Model Intercomparison Phase 5 (CMIP5), were assimilated into calibrated Soil and Water Assessment Tool (SWAT). Mann–Kendall and Theil Sen’s slope were used to assess the trends and magnitude of variability of the historical climate data used for setting up the model. The model calibration showed goodness of fit with minimum Nash–Sutcliffe Efficiency (NSE) coefficient values of 0.83 and Coefficient of Determination (R2) of 0.88 for the three gages within the ARB. Next, the research assessed changes in streamflow for the years 2045 and 2075 against that of the reference baseline year of 1980. The results indicate situations of likely increase and decrease in mean monthly streamflow discharge and increase in the frequency and variability in peak flows during the periods from the mid to end of the 21st century. Seasonally, monthly streamflow increases between 50% and 250% were found for spring and autumn months with decreases in summer months for 2045. Spring and summer months for 2075 resulted in increased monthly streamflow between 50% and 300%, while autumn and spring months experienced decreased streamflow. While the results are prone to inherent uncertainties in the downscaled GCM data used, the simulated dynamics in streamflow and water availability provide critical information for stakeholders to develop sustainable water management and climate change adaptation options for the ARB.

Evaluating Climate Models with the CLIVAR 2020 ENSO Metrics Package

AbstractEl Niño–Southern Oscillation (ENSO) is the dominant mode of interannual climate variability on the planet, with far-reaching global impacts. It is therefore key to evaluate ENSO simulations in state-of-the-art numerical models used to study past, present, and future climate. Recently, the Pacific Region Panel of the International Climate and Ocean: Variability, Predictability and Change (CLIVAR) Project, as a part of the World Climate Research Programme (WCRP), led a community-wide effort to evaluate the simulation of ENSO variability, teleconnections, and processes in climate models. The new CLIVAR 2020 ENSO metrics package enables model diagnosis, comparison, and evaluation to 1) highlight aspects that need improvement; 2) monitor progress across model generations; 3) help in selecting models that are well suited for particular analyses; 4) reveal links between various model biases, illuminating the impacts of those biases on ENSO and its sensitivity to climate change; and to 5) advance ENSO literacy. By interfacing with existing model evaluation tools, the ENSO metrics package enables rapid analysis of multipetabyte databases of simulations, such as those generated by the Coupled Model Intercomparison Project phases 5 (CMIP5) and 6 (CMIP6). The CMIP6 models are found to significantly outperform those from CMIP5 for 8 out of 24 ENSO-relevant metrics, with most CMIP6 models showing improved tropical Pacific seasonality and ENSO teleconnections. Only one ENSO metric is significantly degraded in CMIP6, namely, the coupling between the ocean surface and subsurface temperature anomalies, while the majority of metrics remain unchanged.

Assessing mean climate change signals in the global CORDEX-CORE ensemble

The new Coordinated Output for Regional Evaluations (CORDEX-CORE) ensemble provides high-resolution, consistent regional climate change projections for the major inhabited areas of the world. It serves as a solid scientific basis for further research related to vulnerability, impact, adaptation and climate services in addition to existing CORDEX simulations. The aim of this study is to investigate and document the climate change information provided by the CORDEX-CORE simulation ensemble, as a part of the World Climate Research Programme (WCRP) CORDEX community. An overview of the annual and monthly mean climate change information in selected regions in different CORDEX domains is presented for temperature and precipitation, providing the foundation for detailed follow-up studies and applications. Initially, two regional climate models (RCMs), REMO and RegCM were used to downscale global climate model output. The driving simulations by AR5 global climate models (AR5-GCMs) were selected to cover the spread of high, medium, and low equilibrium climate sensitivity at a global scale. The CORDEX-CORE ensemble has doubled the spatial resolution compared to the previously existing CORDEX simulations in most of the regions (25,mathrm {km} (0.22^{circ }) versus 50,mathrm {km} (0.44^{circ })) leading to a potentially improved representation of, e.g., physical processes in the RCMs. The analysis focuses on changes in the IPCC physical climate reference regions. The results show a general reasonable representation of the spread of the temperature and precipitation climate change signals of the AR5-GCMs by the CORDEX-CORE simulations in the investigated regions in all CORDEX domains by mostly covering the AR5 interquartile range of climate change signals. The simulated CORDEX-CORE monthly climate change signals mostly follow the AR5-GCMs, although for specific regions they show a different change in the course of the year compared to the AR5-GCMs, especially for RCP8.5, which needs to be investigated further in region specific process studies.

The Global Space-based Stratospheric Aerosol Climatology (version 2.0): 1979–2018

Abstract. A robust stratospheric aerosol climate data record enables the depiction of the radiative forcing of this highly variable component of climate. In addition to the radiative forcing, stratospheric aerosol also plays a key role in the chemical processes leading to ozone depletion. Therefore, stratospheric aerosol is one of the crucial parameters in understanding climate change in the past and potential changes in the future. As a part of Stratospheric-tropospheric Processes and their Role in Climate (SPARC) Stratospheric Sulfur and its Role in Climate (SSiRC) activity, the Global Space-based Stratospheric Aerosol Climatology (GloSSAC) was created (Thomason et al., 2018) to support the World Climate Research Programme's (WCRP) Coupled Model Intercomparison Project Phase 6 (CMIP6) (Eyring et al., 2016). This data set is a follow-on to one created as a part of SPARC's Assessment of Stratospheric Aerosol Properties (ASAP) activity (SPARC, 2006) and a data created for the Chemistry-Climate Model Initiative (CCMI) in 2012 (Eyring and Lamarque, 2012). Herein, we discuss changes to the original release version including those as a part of v1.1 that was released in September 2018 that primarily corrects an error in the conversion of Cryogenic Limb Array Etalon Spectrometer (CLAES) data to Stratospheric Aerosol and Gas Experiment (SAGE) II wavelengths, as well as the new release, v2.0. Version 2.0 is focused on improving the post-SAGE II era (after 2005) with the goal of mitigating elevated aerosol extinction in the lower stratosphere at mid- and high latitudes noted in v1.0 as noted in Thomason et al. (2018). Changes include the use of version 7.0 of the Optical Spectrograph and InfraRed Imaging System (OSIRIS), the recently released Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar Level 3 stratospheric aerosol profile monthly product and the new addition of SAGE III/ISS. Here, we use an observed relationship between (i) OSIRIS extinction at 750 nm and (ii) SAGE II and SAGE III/ISS extinction at 525 nm to derive an altitude–latitude-based monthly climatology of Ångström exponent to compute OSIRIS extinction at 525 nm, resulting in a better agreement between OSIRIS and SAGE measurements. We employ a similar approach to convert OSIRIS 750 nm extinction to 1020 nm extinction for the post-SAGE II period. Additionally, we incorporate the recently released standard CALIPSO stratospheric aerosol profile monthly product into GloSSAC with an improved conversion technique of the 532 nm backscatter coefficient to extinction using an observed relationship between OSIRIS 525 nm extinction and CALIPSO 532 nm backscatter. SAGE III/ISS data are also incorporated in GloSSAC to extend the climatology to the present and to test the approach used to correct OSIRIS/CALIPSO data. The GloSSAC v2.0 netCDF file is accessible at https://doi.org/10.5067/glossac-l3-v2.0 (Thomason, 2020).

Assessments of CMIP3 Climate Models and Projected Climate Changes of Precipitation and Temperature for Vietnam and the Southeast Asia

The main objective of this study is to assess the information of climate simulation and projection of temperature and precipitation based on the results of 23 models from the World Climate Research Programme’s (WCRP) Coupled Model Inter-comparison Project phase three (CMIP3) for Southeast Asian Countries with a more focus on Vietnam. The research is divided into two parts: i) Validation of the simulation of the 1948-2002 period with observations (gridded NCEP and CRU data and Vietnam’s surface station data) and ii) Assessments of projected climate changes for both precipitation and temperature variables. For the first part, depending on areas, main results showed a very systematic bias for the simulations of temperature and precipitation. CMIP3’s simulations have significant issues regarding high altitude regions, which can be explained by coarse of model resolutions to represent the effects of the complex topography, land-surface interactions, and the distorted albedo feedbacks due to extensive snow cover. In the second part, regarding the climate projection for temperature, It is projected to get warmer from 3.5 to 6 degrees in 21st Century in all scenarios. For the details in 2030 and 2050, the average annual temperature will clearly increase in the whole Vietnam. The trend of annual precipitation conditions at multi-scenarios in Southeast Asia compared to the current climate condition is not as clear as that of the temperature. The remarkable issue for Vietnam is in the A2 scenario, which provides the most change for the whole country.

The uncertainty of the BSRN monthly mean Global 1 and Global 2 fluxes due to missing hourly means with and without quality-control and an examination through validation of the NASA GEWEX SRB datasets

The Baseline Surface Radiation Network (BSRN) is a project of the Data and Assessments Panel from the Global Energy and Water Exchanges (GEWEX) under the umbrella of the World Climate Research Programme (WCRP). Currently in the archive there are data from 67 sites located in all seven continents spanning from 1992 to the present. The original BSRN records are at 1-, 2-, 3- or 5-minute intervals, and sophisticated quality-control procedures have been developed to eliminate erroneous records before hourly, daily and monthly means are computed. The resulting gaps from quality-control, however, give rise to uncertainties in computed temporal averages on various scales. There are two types of total shortwave downward fluxes: The Global 1 which is the sum of direct horizontal and diffuse irradiances, observed using the pyrheliometer and radiometer, respectively, and is recommended by the BSRN committee for its higher precision, and the Global 2 which is observed using the pyranometer. It has been found that, compared to Global 2, Global 1 is more susceptible to errors, thus resulting in more gaps in the original records. Here we examine the effect of quality-control on the monthly mean Global 1 and Global 2 and attempt to quantify the resulting uncertainties through analysis of the quality-control procedure and averaging algorithm and comparison with the NASA GEWEX Surface Radiation Budget (SRB) dataset. The SRB project is now making progress toward its Release 4.0 Integrated Products (Rel. 4.0-IP or V4.0-IP) with changes in both algorithm and inputs on the basis of its Release 3.0 (Rel. 3.0 or V3.0) products. The preliminary results from Rel. 4.0-IP span 34 years continuously from July 1983 to June 2017 on a 1° by 1° quasi-equal-area grid system in the form of 3-hourly, daily and monthly means. It is found that Global 2 generally has fewer missing records and is less affected by the quality-check procedure; on average, the monthly mean Global 1 and Global 2 differ by less than 1 W m−2; the GEWEX SRB preliminary GSW(V4.0-IP) monthly mean shortwave downward fluxes agree the best with the BSRN Global 1 monthly means computed from observational records that are nearly complete and that survive the quality-check nearly completely.

Assessing current and future trends of climate extremes across Brazil based on reanalyses and earth system model projections

Brazil experiences extreme weather and climate events that cause numerous economic and social losses, and according to climate change projections, these events will increase in intensity and frequency over this century.This study adds to the body of research on Brazil’s climate change by analyzing the historical patterns and projected changes in temperature and precipitation extremes across Brazil using the World Climate Research Program’s Expert Team on Climate Change Detection and Indices framework. This novel approach analyzes climate extreme events over the past four decades (1980–2016) using multiple gridded observation and reanalysis datasets. Furthermore, future changes in climate extremes are analyzed from 20 downscaled Earth System Models (ESMs) at high horizontal resolution (0.25° of latitude/longitude), under two representative concentration pathway scenarios (RCP4.5 and RCP8.5). Projected changes in the extreme indices are analyzed over mid-twenty-first century (2046–2065) and end-of-twenty-first century (2081–2100) relative to the reference period 1986–2005. Results show consistent warming patterns with increasing (decreasing) trends in warm (cold) extremes in the historical datasets. A similar but more intense warm pattern is projected in the mid and end of the twenty-first century. For precipitation indices, observations show an increase in consecutive dry days and a reduction of consecutive wet days over almost all Brazil. The frequency and intensity of extremely wet days over Brazil are expected to increase according to future scenarios. Designing effective adaptation and mitigation measures in response to changes in climate extremes events depends on this improved understanding of how conditions have and are likely to change in the future at regional scales.

Observations for Model Intercomparison Project (Obs4MIPs): status for CMIP6

Abstract. The Observations for Model Intercomparison Project (Obs4MIPs) was initiated in 2010 to facilitate the use of observations in climate model evaluation and research, with a particular target being the Coupled Model Intercomparison Project (CMIP), a major initiative of the World Climate Research Programme (WCRP). To this end, Obs4MIPs (1) targets observed variables that can be compared to CMIP model variables; (2) utilizes dataset formatting specifications and metadata requirements closely aligned with CMIP model output; (3) provides brief technical documentation for each dataset, designed for nonexperts and tailored towards relevance for model evaluation, including information on uncertainty, dataset merits, and limitations; and (4) disseminates the data through the Earth System Grid Federation (ESGF) platforms, making the observations searchable and accessible via the same portals as the model output. Taken together, these characteristics of the organization and structure of obs4MIPs should entice a more diverse community of researchers to engage in the comparison of model output with observations and to contribute to a more comprehensive evaluation of the climate models. At present, the number of obs4MIPs datasets has grown to about 80; many are undergoing updates, with another 20 or so in preparation, and more than 100 are proposed and under consideration. A partial list of current global satellite-based datasets includes humidity and temperature profiles; a wide range of cloud and aerosol observations; ocean surface wind, temperature, height, and sea ice fraction; surface and top-of-atmosphere longwave and shortwave radiation; and ozone (O3), methane (CH4), and carbon dioxide (CO2) products. A partial list of proposed products expected to be useful in analyzing CMIP6 results includes the following: alternative products for the above quantities, additional products for ocean surface flux and chlorophyll products, a number of vegetation products (e.g., FAPAR, LAI, burned area fraction), ice sheet mass and height, carbon monoxide (CO), and nitrogen dioxide (NO2). While most existing obs4MIPs datasets consist of monthly-mean gridded data over the global domain, products with higher time resolution (e.g., daily) and/or regional products are now receiving more attention. Along with an increasing number of datasets, obs4MIPs has implemented a number of capability upgrades including (1) an updated obs4MIPs data specifications document that provides additional search facets and generally improves congruence with CMIP6 specifications for model datasets, (2) a set of six easily understood indicators that help guide users as to a dataset's maturity and suitability for application, and (3) an option to supply supplemental information about a dataset beyond what can be found in the standard metadata. With the maturation of the obs4MIPs framework, the dataset inclusion process, and the dataset formatting guidelines and resources, the scope of the observations being considered is expected to grow to include gridded in situ datasets as well as datasets with a regional focus, and the ultimate intent is to judiciously expand this scope to any observation dataset that has applicability for evaluation of the types of Earth system models used in CMIP.