National Centre for Atmospheric Science

CRU TS (Climatic Research Unit gridded Time Series) is a widely used climate dataset on a 0.5° latitude by 0.5° longitude grid over all land domains of the world except Antarctica. It is derived by the interpolation of monthly climate anomalies from extensive networks of weather station observations. Here we describe the construction of a major new version, CRU TS v4. It is updated to span 1901-2018 by the inclusion of additional station observations, and it will be updated annually. The interpolation process has been changed to use angular-distance weighting (ADW), and the production of secondary variables has been revised to better suit this approach. This implementation of ADW provides improved traceability between each gridded value and the input observations, and allows more informative diagnostics that dataset users can utilise to assess how dataset quality might vary geographically.

Organic aerosol (OA) particles affect climate forcing and human health, but their sources and evolution remain poorly characterized. We present a unifying model framework describing the atmospheric evolution of OA that is constrained by high-time-resolution measurements of its composition, volatility, and oxidation state. OA and OA precursor gases evolve by becoming increasingly oxidized, less volatile, and more hygroscopic, leading to the formation of oxygenated organic aerosol (OOA), with concentrations comparable to those of sulfate aerosol throughout the Northern Hemisphere. Our model framework captures the dynamic aging behavior observed in both the atmosphere and laboratory: It can serve as a basis for improving parameterizations in regional and global models.

Abstract. Secondary organic aerosol (SOA) accounts for a significant fraction of ambient tropospheric aerosol and a detailed knowledge of the formation, properties and transformation of SOA is therefore required to evaluate its impact on atmospheric processes, climate and human health. The chemical and physical processes associated with SOA formation are complex and varied, and, despite considerable progress in recent years, a quantitative and predictive understanding of SOA formation does not exist and therefore represents a major research challenge in atmospheric science. This review begins with an update on the current state of knowledge on the global SOA budget and is followed by an overview of the atmospheric degradation mechanisms for SOA precursors, gas-particle partitioning theory and the analytical techniques used to determine the chemical composition of SOA. A survey of recent laboratory, field and modeling studies is also presented. The following topical and emerging issues are highlighted and discussed in detail: molecular characterization of biogenic SOA constituents, condensed phase reactions and oligomerization, the interaction of atmospheric organic components with sulfuric acid, the chemical and photochemical processing of organics in the atmospheric aqueous phase, aerosol formation from real plant emissions, interaction of atmospheric organic components with water, thermodynamics and mixtures in atmospheric models. Finally, the major challenges ahead in laboratory, field and modeling studies of SOA are discussed and recommendations for future research directions are proposed.

Abstract Equilibrium climate sensitivity, the global surface temperature response to CO doubling, has been persistently uncertain. Recent consensus places it likely within 1.5–4.5 K. Global climate models (GCMs), which attempt to represent all relevant physical processes, provide the most direct means of estimating climate sensitivity via CO quadrupling experiments. Here we show that the closely related effective climate sensitivity has increased substantially in Coupled Model Intercomparison Project phase 6 (CMIP6), with values spanning 1.8–5.6 K across 27 GCMs and exceeding 4.5 K in 10 of them. This (statistically insignificant) increase is primarily due to stronger positive cloud feedbacks from decreasing extratropical low cloud coverage and albedo. Both of these are tied to the physical representation of clouds which in CMIP6 models lead to weaker responses of extratropical low cloud cover and water content to unforced variations in surface temperature. Establishing the plausibility of these higher sensitivity models is imperative given their implied societal ramifications.

Accurate assessment of anthropogenic carbon dioxide (CO 2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO 2 emissions ( E FF ) are based on energy statistics and cement production data, while emissions from land use change ( E LUC ), mainly deforestation, are based on land use and land use change data and bookkeeping models. Atmospheric CO 2 concentration is measured directly and its growth rate ( G ATM ) is computed from the annual changes in concentration. The ocean CO 2 sink ( S OCEAN ) and terrestrial CO 2 sink ( S LAND ) are estimated with global process models constrained by observations. The resulting carbon budget imbalance ( B IM ), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1 σ . For the last decade available (2009–2018), E FF was 9.5±0.5 GtC yr −1 , E LUC 1.5±0.7 GtC yr −1 , G ATM 4.9±0.02 GtC yr −1 (2.3±0.01 ppm yr −1 ), S OCEAN 2.5±0.6 GtC yr −1 , and S LAND 3.2±0.6 GtC yr −1 , with a budget imbalance B IM of 0.4 GtC yr −1 indicating overestimated emissions and/or underestimated sinks. For the year 2018 alone, the growth in E FF was about 2.1 % and fossil emissions increased to 10.0±0.5 GtC yr −1 , reaching 10 GtC yr −1 for the first time in history, E LUC was 1.5±0.7 GtC yr −1 , for total anthropogenic CO 2 emissions of 11.5±0.9 GtC yr −1 (42.5±3.3 GtCO 2 ). Also for 2018, G ATM was 5.1±0.2 GtC yr −1 (2.4±0.1 ppm yr −1 ), S OCEAN was 2.6±0.6 GtC yr −1 , and S LAND was 3.5±0.7 GtC yr −1 , with a B IM of 0.3 GtC. The global atmospheric CO 2 concentration reached 407.38±0.1 ppm averaged over 2018. For 2019, preliminary data for the first 6–10 months indicate a reduced growth in E FF of +0.6 % (range of −0.2 % to 1.5 %) based on national emissions projections for China, the USA, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. Overall, the mean and trend in the five components of the global carbon budget are consistently estimated over the period 1959–2018, but discrepancies of up to 1 GtC yr −1 persist for the representation of semi-decadal variability in CO 2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations shows (1) no consensus in the mean and trend in land use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO 2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO 2 variability by ocean models outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018a, b, 2016, 2015a, b, 2014, 2013). The data generated by this work are available at https://doi.org/10.18160/gcp-2019 (Friedlingstein et al., 2019).

Accurate assessment of anthropogenic carbon dioxide (CO 2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize datasets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO 2 emissions ( E FOS ) are based on energy statistics and cement production data, while emissions from land-use change ( E LUC ), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO 2 concentration is measured directly, and its growth rate ( G ATM ) is computed from the annual changes in concentration. The ocean CO 2 sink ( S OCEAN ) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO 2 sink ( S LAND ) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance ( B IM ), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1 σ . For the first time, an approach is shown to reconcile the difference in our E LUC estimate with the one from national greenhouse gas inventories, supporting the assessment of collective countries' climate progress. For the year 2020, E FOS declined by 5.4 % relative to 2019, with fossil emissions at 9.5 ± 0.5 GtC yr −1 (9.3 ± 0.5 GtC yr −1 when the cement carbonation sink is included), and E LUC was 0.9 ± 0.7 GtC yr −1 , for a total anthropogenic CO 2 emission of 10.2 ± 0.8 GtC yr −1 (37.4 ± 2.9 GtCO 2 ). Also, for 2020, G ATM was 5.0 ± 0.2 GtC yr −1 (2.4 ± 0.1 ppm yr −1 ), S OCEAN was 3.0 ± 0.4 GtC yr −1 , and S LAND was 2.9 ± 1 GtC yr −1 , with a B IM of −0.8 GtC yr −1 . The global atmospheric CO 2 concentration averaged over 2020 reached 412.45 ± 0.1 ppm. Preliminary data for 2021 suggest a rebound in E FOS relative to 2020 of +4.8 % (4.2 % to 5.4 %) globally. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2020, but discrepancies of up to 1 GtC yr −1 persist for the representation of annual to semi-decadal variability in CO 2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO 2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and datasets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this dataset (Friedlingstein et al., 2020, 2019; Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2021 (Friedlingstein et al., 2021).

Abstract A new release of the Max Planck Institute for Meteorology Earth System Model version 1.2 (MPI‐ESM1.2) is presented. The development focused on correcting errors in and improving the physical processes representation, as well as improving the computational performance, versatility, and overall user friendliness. In addition to new radiation and aerosol parameterizations of the atmosphere, several relatively large, but partly compensating, coding errors in the model's cloud, convection, and turbulence parameterizations were corrected. The representation of land processes was refined by introducing a multilayer soil hydrology scheme, extending the land biogeochemistry to include the nitrogen cycle, replacing the soil and litter decomposition model and improving the representation of wildfires. The ocean biogeochemistry now represents cyanobacteria prognostically in order to capture the response of nitrogen fixation to changing climate conditions and further includes improved detritus settling and numerous other refinements. As something new, in addition to limiting drift and minimizing certain biases, the instrumental record warming was explicitly taken into account during the tuning process. To this end, a very high climate sensitivity of around 7 K caused by low‐level clouds in the tropics as found in an intermediate model version was addressed, as it was not deemed possible to match observed warming otherwise. As a result, the model has a climate sensitivity to a doubling of CO 2 over preindustrial conditions of 2.77 K, maintaining the previously identified highly nonlinear global mean response to increasing CO 2 forcing, which nonetheless can be represented by a simple two‐layer model.

Abstract. Ozone holds a certain fascination in atmospheric science. It is ubiquitous in the atmosphere, central to tropospheric oxidation chemistry, yet harmful to human and ecosystem health as well as being an important greenhouse gas. It is not emitted into the atmosphere but is a byproduct of the very oxidation chemistry it largely initiates. Much effort is focused on the reduction of surface levels of ozone owing to its health and vegetation impacts, but recent efforts to achieve reductions in exposure at a country scale have proved difficult to achieve owing to increases in background ozone at the zonal hemispheric scale. There is also a growing realisation that the role of ozone as a short-lived climate pollutant could be important in integrated air quality climate change mitigation. This review examines current understanding of the processes regulating tropospheric ozone at global to local scales from both measurements and models. It takes the view that knowledge across the scales is important for dealing with air quality and climate change in a synergistic manner. The review shows that there remain a number of clear challenges for ozone such as explaining surface trends, incorporating new chemical understanding, ozone–climate coupling, and a better assessment of impacts. There is a clear and present need to treat ozone across the range of scales, a transboundary issue, but with an emphasis on the hemispheric scales. New observational opportunities are offered both by satellites and small sensors that bridge the scales.

Abstract. We describe here the development and evaluation of an Earth system model suitable for centennial-scale climate prediction. The principal new components added to the physical climate model are the terrestrial and ocean ecosystems and gas-phase tropospheric chemistry, along with their coupled interactions. The individual Earth system components are described briefly and the relevant interactions between the components are explained. Because the multiple interactions could lead to unstable feedbacks, we go through a careful process of model spin up to ensure that all components are stable and the interactions balanced. This spun-up configuration is evaluated against observed data for the Earth system components and is generally found to perform very satisfactorily. The reason for the evaluation phase is that the model is to be used for the core climate simulations carried out by the Met Office Hadley Centre for the Coupled Model Intercomparison Project (CMIP5), so it is essential that addition of the extra complexity does not detract substantially from its climate performance. Localised changes in some specific meteorological variables can be identified, but the impacts on the overall simulation of present day climate are slight. This model is proving valuable both for climate predictions, and for investigating the strengths of biogeochemical feedbacks.

Abstract We document the development of the first version of the U.K. Earth System Model UKESM1. The model represents a major advance on its predecessor HadGEM2‐ES, with enhancements to all component models and new feedback mechanisms. These include a new core physical model with a well‐resolved stratosphere; terrestrial biogeochemistry with coupled carbon and nitrogen cycles and enhanced land management; tropospheric‐stratospheric chemistry allowing the holistic simulation of radiative forcing from ozone, methane, and nitrous oxide; two‐moment, five‐species, modal aerosol; and ocean biogeochemistry with two‐way coupling to the carbon cycle and atmospheric aerosols. The complexity of coupling between the ocean, land, and atmosphere physical climate and biogeochemical cycles in UKESM1 is unprecedented for an Earth system model. We describe in detail the process by which the coupled model was developed and tuned to achieve acceptable performance in key physical and Earth system quantities and discuss the challenges involved in mitigating biases in a model with complex connections between its components. Overall, the model performs well, with a stable pre‐industrial state and good agreement with observations in the latter period of its historical simulations. However, global mean surface temperature exhibits stronger‐than‐observed cooling from 1950 to 1970, followed by rapid warming from 1980 to 2014. Metrics from idealized simulations show a high climate sensitivity relative to previous generations of models: Equilibrium climate sensitivity is 5.4 K, transient climate response ranges from 2.68 to 2.85 K, and transient climate response to cumulative emissions is 2.49 to 2.66 K TtC −1 .

Recent extreme events such as the devastating 2003 European summer heat wave raise important questions about the possible causes of any underlying trends, or low-frequency variations, in regional climates. Here, we present new evidence that basin-scale changes in the Atlantic Ocean, probably related to the thermohaline circulation, have been an important driver of multidecadal variations in the summertime climate of both North America and western Europe. Our findings advance understanding of past climate changes and also have implications for decadal climate predictions.

Understanding the influence of solar variability on the Earth's climate requires knowledge of solar variability, solar-terrestrial interactions, and the mechanisms determining the response of the Earth's climate system.We provide a summary of our current understanding in each of these three areas.Observations and mechanisms for the Sun's variability are described, including solar irradiance variations on both decadal and centennial time scales and their relation to galactic cosmic rays.Corresponding observations of variations of the Earth's climate on associated time scales are described, including variations in ozone, temperatures, winds, clouds, precipitation, and regional modes of variability such as the monsoons and the North Atlantic Oscillation.A discussion of the available solar and climate proxies is provided.Mechanisms proposed to explain these climate observations are described, including the effects of variations in solar irradiance and of charged particles.Finally, the contributions of solar variations to recent observations of global climate change are discussed.

Global tropospheric ozone distributions, budgets, and radiative forcings from an ensemble of 26 state‐of‐the‐art atmospheric chemistry models have been intercompared and synthesized as part of a wider study into both the air quality and climate roles of ozone. Results from three 2030 emissions scenarios, broadly representing “optimistic,” “likely,” and “pessimistic” options, are compared to a base year 2000 simulation. This base case realistically represents the current global distribution of tropospheric ozone. A further set of simulations considers the influence of climate change over the same time period by forcing the central emissions scenario with a surface warming of around 0.7K. The use of a large multimodel ensemble allows us to identify key areas of uncertainty and improves the robustness of the results. Ensemble mean changes in tropospheric ozone burden between 2000 and 2030 for the 3 scenarios range from a 5% decrease, through a 6% increase, to a 15% increase. The intermodel uncertainty (±1 standard deviation) associated with these values is about ±25%. Model outliers have no significant influence on the ensemble mean results. Combining ozone and methane changes, the three scenarios produce radiative forcings of −50, 180, and 300 mW m−2, compared to a CO2 forcing over the same time period of 800–1100 mW m−2. These values indicate the importance of air pollution emissions in short‐ to medium‐term climate forcing and the potential for stringent/lax control measures to improve/worsen future climate forcing. The model sensitivity of ozone to imposed climate change varies between models but modulates zonal mean mixing ratios by ±5 ppbv via a variety of feedback mechanisms, in particular those involving water vapor and stratosphere‐troposphere exchange. This level of climate change also reduces the methane lifetime by around 4%. The ensemble mean year 2000 tropospheric ozone budget indicates chemical production, chemical destruction, dry deposition and stratospheric input fluxes of 5100, 4650, 1000, and 550 Tg(O3) yr−1, respectively. These values are significantly different to the mean budget documented by the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report (TAR). The mean ozone burden (340 Tg(O3)) is 10% larger than the IPCC TAR estimate, while the mean ozone lifetime (22 days) is 10% shorter. Results from individual models show a correlation between ozone burden and lifetime, and each model's ozone burden and lifetime respond in similar ways across the emissions scenarios. The response to climate change is much less consistent. Models show more variability in the tropics compared to midlatitudes. Some of the most uncertain areas of the models include treatments of deep tropical convection, including lightning NOx production; isoprene emissions from vegetation and isoprene's degradation chemistry; stratosphere‐troposphere exchange; biomass burning; and water vapor concentrations.

Abstract The ECMWF twentieth century reanalysis (ERA-20C; 1900–2010) assimilates surface pressure and marine wind observations. The reanalysis is single-member, and the background errors are spatiotemporally varying, derived from an ensemble. The atmospheric general circulation model uses the same configuration as the control member of the ERA-20CM ensemble, forced by observationally based analyses of sea surface temperature, sea ice cover, atmospheric composition changes, and solar forcing. The resulting climate trend estimations resemble ERA-20CM for temperature and the water cycle. The ERA-20C water cycle features stable precipitation minus evaporation global averages and no spurious jumps or trends. The assimilation of observations adds realism on synoptic time scales as compared to ERA-20CM in regions that are sufficiently well observed. Comparing to nighttime ship observations, ERA-20C air temperatures are 1 K colder. Generally, the synoptic quality of the product and the agreement in terms of climate indices with other products improve with the availability of observations. The MJO mean amplitude in ERA-20C is larger than in 20CR version 2c throughout the century, and in agreement with other reanalyses such as JRA-55. A novelty in ERA-20C is the availability of observation feedback information. As shown, this information can help assess the product’s quality on selected time scales and regions.

Abstract Demands are growing rapidly in the operational prediction and applications communities for forecasts that fill the gap between medium-range weather and long-range or seasonal forecasts. Based on the potential for improved forecast skill at the subseasonal to seasonal time range, the Subseasonal to Seasonal (S2S) Prediction research project has been established by the World Weather Research Programme/World Climate Research Programme. A main deliverable of this project is the establishment of an extensive database containing subseasonal (up to 60 days) forecasts, 3 weeks behind real time, and reforecasts from 11 operational centers, modeled in part on the The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) database for medium-range forecasts (up to 15 days). The S2S database, available to the research community since May 2015, represents an important tool to advance our understanding of the subseasonal to seasonal time range that has been considered for a long time as a “desert of predictability.” In particular, this database will help identify common successes and shortcomings in the model simulation and prediction of sources of subseasonal to seasonal predictability. For instance, a preliminary study suggests that the S2S models significantly underestimate the amplitude of the Madden–Julian oscillation (MJO) teleconnections over the Euro-Atlantic sector. The S2S database also represents an important tool for case studies of extreme events. For instance, a multimodel combination of S2S models displays higher probability of a landfall over the islands of Vanuatu 2–3 weeks before Tropical Cyclone Pam devastated the islands in March 2015.

We describe Global Atmosphere 7.0 and Global Land 7.0 (GA7.0/GL7.0), the latest science configurations of the Met Office Unified Model (UM) and the Joint UK Land Environment Simulator (JULES) land surface model developed for use across weather and climate timescales. GA7.0 and GL7.0 include incremental developments and targeted improvements that, between them, address four critical errors identified in previous configurations: excessive precipitation biases over India, warm and moist biases in the tropical tropopause layer (TTL), a source of energy non-conservation in the advection scheme and excessive surface radiation biases over the Southern Ocean. They also include two new parametrisations, namely the UK Chemistry and Aerosol (UKCA) GLOMAP-mode (Global Model of Aerosol Processes) aerosol scheme and the JULES multi-layer snow scheme, which improve the fidelity of the simulation and were required for inclusion in the Global Atmosphere/Global Land configurations ahead of the 6th Coupled Model Intercomparison Project (CMIP6). In addition, we describe the GA7.1 branch configuration, which reduces an overly negative anthropogenic aerosol effective radiative forcing (ERF) in GA7.0 whilst maintaining the quality of simulations of the present-day climate. GA7.1/GL7.0 will form the physical atmosphere/land component in the HadGEM3–GC3.1 and UKESM1 climate model submissions to the CMIP6.

Historical reanalyses that span more than a century are needed for a wide range of studies, from understanding large‐scale climate trends to diagnosing the impacts of individual historical extreme weather events. The Twentieth Century Reanalysis (20CR) Project is an effort to fill this need. It is supported by the National Oceanic and Atmospheric Administration (NOAA), the Cooperative Institute for Research in Environmental Sciences (CIRES), and the U.S. Department of Energy (DOE), and is facilitated by collaboration with the international Atmospheric Circulation Reconstructions over the Earth initiative. 20CR is the first ensemble of sub‐daily global atmospheric conditions spanning over 100 years. This provides a best estimate of the weather at any given place and time as well as an estimate of its confidence and uncertainty. While extremely useful, version 2c of this dataset (20CRv2c) has several significant issues, including inaccurate estimates of confidence and a global sea level pressure bias in the mid‐19th century. These and other issues can reduce its effectiveness for studies at many spatial and temporal scales. Therefore, the 20CR system underwent a series of developments to generate a significant new version of the reanalysis. The version 3 system (NOAA‐CIRES‐DOE 20CRv3) uses upgraded data assimilation methods including an adaptive inflation algorithm; has a newer, higher‐resolution forecast model that specifies dry air mass; and assimilates a larger set of pressure observations. These changes have improved the ensemble‐based estimates of confidence, removed spin‐up effects in the precipitation fields, and diminished the sea‐level pressure bias. Other improvements include more accurate representations of storm intensity, smaller errors, and large‐scale reductions in model bias. The 20CRv3 system is comprehensively reviewed, focusing on the aspects that have ameliorated issues in 20CRv2c. Despite the many improvements, some challenges remain, including a systematic bias in tropical precipitation and time‐varying biases in southern high‐latitude pressure fields.

Abstract. Mobility particle size spectrometers often referred to as DMPS (Differential Mobility Particle Sizers) or SMPS (Scanning Mobility Particle Sizers) have found a wide range of applications in atmospheric aerosol research. However, comparability of measurements conducted world-wide is hampered by lack of generally accepted technical standards and guidelines with respect to the instrumental set-up, measurement mode, data evaluation as well as quality control. Technical standards were developed for a minimum requirement of mobility size spectrometry to perform long-term atmospheric aerosol measurements. Technical recommendations include continuous monitoring of flow rates, temperature, pressure, and relative humidity for the sheath and sample air in the differential mobility analyzer. We compared commercial and custom-made inversion routines to calculate the particle number size distributions from the measured electrical mobility distribution. All inversion routines are comparable within few per cent uncertainty for a given set of raw data. Furthermore, this work summarizes the results from several instrument intercomparison workshops conducted within the European infrastructure project EUSAAR (European Supersites for Atmospheric Aerosol Research) and ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) to determine present uncertainties especially of custom-built mobility particle size spectrometers. Under controlled laboratory conditions, the particle number size distributions from 20 to 200 nm determined by mobility particle size spectrometers of different design are within an uncertainty range of around ±10% after correcting internal particle losses, while below and above this size range the discrepancies increased. For particles larger than 200 nm, the uncertainty range increased to 30%, which could not be explained. The network reference mobility spectrometers with identical design agreed within ±4% in the peak particle number concentration when all settings were done carefully. The consistency of these reference instruments to the total particle number concentration was demonstrated to be less than 5%. Additionally, a new data structure for particle number size distributions was introduced to store and disseminate the data at EMEP (European Monitoring and Evaluation Program). This structure contains three levels: raw data, processed data, and final particle size distributions. Importantly, we recommend reporting raw measurements including all relevant instrument parameters as well as a complete documentation on all data transformation and correction steps. These technical and data structure standards aim to enhance the quality of long-term size distribution measurements, their comparability between different networks and sites, and their transparency and traceability back to raw data.

A global archive of high-resolution (3-hourly, 0.5° latitude–longitude grid) window (11–12 μm) brightness temperature (Tb) data from multiple satellites is being developed by the European Union Cloud Archive User Service (CLAUS) project. It has been used to construct a climatology of the diurnal cycle in convection, cloudiness, and surface temperature for all regions of the Tropics. An example of the application of the climatology to the evaluation of the climate version of the U.K. Met. Office Unified Model (UM), version HadAM3, is presented. The characteristics of the diurnal cycle described by the CLAUS data agree with previous observational studies, demonstrating the universality of the characteristics of the diurnal cycle for land versus ocean, clear sky versus convective regimes. It is shown that oceanic deep convection tends to reach its maximum in the early morning. Continental convection generally peaks in the evening, although there are interesting regional variations, indicative of the effects of complex land–sea and mountain–valley breezes, as well as the life cycle of mesoscale convective systems. A striking result from the analysis of the CLAUS data has been the extent to which the strong diurnal signal over land is spread out over the adjacent oceans, probably through gravity waves of varying depths. These coherent signals can be seen for several hundred kilometers and in some instances, such as over the Bay of Bengal, can lead to substantial diurnal variations in convection and precipitation. The example of the use of the CLAUS data in the evaluation of the Met. Office UM has demonstrated that the model has considerable difficulty in capturing the observed phase of the diurnal cycle in convection, which suggests some fundamental difficulties in the model’s physical parameterizations. Analysis of the diurnal cycle represents a powerful tool for identifying and correcting model deficiencies.

Abstract. We describe the HadGEM2 family of climate configurations of the Met Office Unified Model, MetUM. The concept of a model "family" comprises a range of specific model configurations incorporating different levels of complexity but with a common physical framework. The HadGEM2 family of configurations includes atmosphere and ocean components, with and without a vertical extension to include a well-resolved stratosphere, and an Earth-System (ES) component which includes dynamic vegetation, ocean biology and atmospheric chemistry. The HadGEM2 physical model includes improvements designed to address specific systematic errors encountered in the previous climate configuration, HadGEM1, namely Northern Hemisphere continental temperature biases and tropical sea surface temperature biases and poor variability. Targeting these biases was crucial in order that the ES configuration could represent important biogeochemical climate feedbacks. Detailed descriptions and evaluations of particular HadGEM2 family members are included in a number of other publications, and the discussion here is limited to a summary of the overall performance using a set of model metrics which compare the way in which the various configurations simulate present-day climate and its variability.