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Satellite and in situ measurements of the sea surface and the atmosphere often have inadequate sampling frequencies and often lack consistent global coverage. Because of such limitations, reanalysis model output is frequently used in atmospheric and oceanographic research endeavors to complement satellite and in situ data. The National Aeronautics and Space Administration’s (NASA’s) Goddard Earth Sciences Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) and the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) datasets provide accurate, complete fields through the assimilation of many atmospheric and surface observations. Still, the reanalysis output data must be rigorously and continuously evaluated to understand their strengths and weaknesses. To this end, this study evaluates sea surface skin temperature (SSTskin) and atmospheric temperature and humidity profiles in MERRA-2 and ERAInterim data through comparisons with independent Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) and radiosonde data from theAerosols and Ocean Science Expeditions (AEROSE) cruises, focusing on the representation of spatial and temporal variability. SSTskin values are generally in good agreement with corresponding M-AERI measurements, with the average differences on the order of 0.1 K. Comparisons between MERRA-2 and ERA-Interim relative humidity and air temperature profiles with a total of 553 radiosondes that have been withheld from data assimilation schemes show good correspondence below 500 hPa: the average air temperature difference is, <2 K and the average relative humidity discrepancy is within 10%. These results support the use of these MERRA-2 and ERA-Interim reanalysis fields in a variety of research applications.

Biomass burning is a large source of volatile organic compounds (VOCs) and many other trace species to the atmosphere, which can act as precursors to secondary pollutants such as ozone and fine particles. Measurements performed with a proton-transfer-reaction time-of-flight mass spectrometer during the FIREX 2016 laboratory intensive were analyzed with positive matrix factorization (PMF), in order to understand the instantaneous variability in VOC emissions from biomass burning, and to simplify the description of these types of emissions. Despite the complexity and variability of emissions, we found that a solution including just two emission profiles, which are mass spectral representations of the relative abundances of emitted VOCs, explained on average 85 % of the VOC emissions across various fuels representative of the western US (including various coniferous and chaparral fuels). In addition, the profiles were remarkably similar across almost all of the fuel types tested. For example, the correlation coefficient r2 of each profile between ponderosa pine (coniferous tree) and manzanita (chaparral) is higher than 0.84. The compositional differences between the two VOC profiles appear to be related to differences in pyrolysis processes of fuel biopolymers at high and low temperatures. These pyrolysis processes are thought to be the main source of VOC emissions. “High-temperature” and “low-temperature” pyrolysis processes do not correspond exactly to the commonly used “flaming” and “smoldering” categories as described by modified combustion efficiency (MCE). The average atmospheric properties (e.g., OH reactivity, volatility, etc) of the high- and low-temperature profiles are significantly different. We also found that the two VOC profiles can describe previously reported VOC data for laboratory and field burns.

We conducted direct numerical simulations of turbulent flow over three-dimensional sinusoidal roughness in a channel. A passive scalar is present in the flow with Prandtl number $Pr=0.7$ , to study heat transfer by forced convection over this rough surface. The minimal-span channel is used to circumvent the high cost of simulating high-Reynolds-number flows, which enables a range of rough surfaces to be efficiently simulated. The near-wall temperature profile in the minimal-span channel agrees well with that of the conventional full-span channel, indicating that it can be readily used for heat-transfer studies at a much reduced cost compared to conventional direct numerical simulation. As the roughness Reynolds number, $k^{+}$ , is increased, the Hama roughness function, $\\unicode[STIX]{x0394}U^{+}$ , increases in the transitionally rough regime before tending towards the fully rough asymptote of $\\unicode[STIX]{x1D705}_{m}^{-1}\\log (k^{+})+C$ , where $C$ is a constant that depends on the particular roughness geometry and $\\unicode[STIX]{x1D705}_{m}\\approx 0.4$ is the von Kármán constant. In this fully rough regime, the skin-friction coefficient is constant with bulk Reynolds number, $Re_{b}$ . Meanwhile, the temperature difference between smooth- and rough-wall flows, $\\unicode[STIX]{x0394}\\unicode[STIX]{x1D6E9}^{+}$ , appears to tend towards a constant value, $\\unicode[STIX]{x0394}\\unicode[STIX]{x1D6E9}_{FR}^{+}$ . This corresponds to the Stanton number (the temperature analogue of the skin-friction coefficient) monotonically decreasing with $Re_{b}$ in the fully rough regime. Using shifted logarithmic velocity and temperature profiles, the heat-transfer law as described by the Stanton number in the fully rough regime can be derived once both the equivalent sand-grain roughness $k_{s}/k$ and the temperature difference $\\unicode[STIX]{x0394}\\unicode[STIX]{x1D6E9}_{FR}^{+}$ are known. In meteorology, this corresponds to the ratio of momentum and heat-transfer roughness lengths, $z_{0m}/z_{0h}$ , being linearly proportional to the inner-normalised momentum roughness length, $z_{0m}^{+}$ , where the constant of proportionality is related to $\\unicode[STIX]{x0394}\\unicode[STIX]{x1D6E9}_{FR}^{+}$ . While Reynolds analogy, or similarity between momentum and heat transfer, breaks down for the bulk skin-friction and heat-transfer coefficients, similar distribution patterns between the heat flux and viscous component of the wall shear stress are observed. Instantaneous visualisations of the temperature field show a thin thermal diffusive sublayer following the roughness geometry in the fully rough regime, resembling the viscous sublayer of a contorted smooth wall.

We estimate ocean heat content (OHC) change in the upper 2000 m in the Gulf of Mexico (GOM) from 1950 to 2020 to improve understanding of regional warming. Our estimates are based on 192 890 temperature profiles from the World Ocean Database. Warming occurs at all depths and in most regions except for a small region at northeastern GOM between 200 and 600 m. GOM OHC in the upper 2000 m increases at a rate of 0.38 ± 0.13 ZJ decade-1 between 1970 and 2020, which is equivalent to 1.21 ± 0.41 terawatts (TW). The GOM sea surface temperature (SST) increased ~1.0° ± 0.25°C between 1970 and 2020, equivalent to a warming rate of 0.19° ± 0.05°C decade-1. Although SST in the GOM increases at a rate approximately twice that for the global ocean, the full-depth ocean heat storage rate in the GOM (0.86 ± 0.26 W m-2) applied to the entire GOM surface is comparable to that for the global ocean (0.82–1.11 W m-2). The upper-1000-m layer accounts for approximately 80%–90% of the total warming and variations in the upper 2000 m in the GOM. The Loop Current advective net heat flux is estimated to be 40.7 ± 6.3 TW through the GOM. A heat budget analysis shows the difference between the advective heat flux and the ocean heat storage rate (1.76 ± 1.36 TW, 1992–2017) can be roughly balanced with the annual net surface heat flux from ECCO (-37.9 TW).

The inverse temperature layer (ITL) beneath water‐atmosphere interface within which temperature increases with depth has been observed from measurement of water temperature profile at an inland lake. Strong solar radiation combined with moderate wind‐driven near‐surface turbulence leads to the formation of a pronounced diurnal cycle of the ITL predicted by a physical heat transfer model. The ITL only forms during daytime when solar radiation intensity exceeds a threshold while consistently occurs during nighttime. The largest depth of the ITL is comparable to the e‐fold penetration depth of solar radiation during daytime and at least one order of magnitude deeper during nighttime. The dynamics of the ITL depth variation simulated by a physical model forced by observed water surface solar radiation and temperature is confirmed by the observed water temperature profile in the lake. Plain Language Summary An idealized one‐dimensional heat transfer equation reveals the physical mechanisms of water temperature increasing with depth beneath the water‐atmosphere interface known as inverse temperature layer (ITL). Solar radiation is the dominant forcing of water temperature profile while wind‐driven turbulent mixing is a critical process determining whether the ITL forms. The limited depth of the ITL poses a constraint on the rate of heat transfer from the water body into the atmosphere. The dynamics of the ITL plays an important role in the water and energy cycle of large water bodies such as lakes and oceans. Key Points The formation of inverse temperature layer (ITL) is driven by strong solar radiation and moderate wind‐driven turbulence The ITL depth has pronounced diurnal cycle shallower during daytime than during nighttime A physical model using observed solar radiation and water surface temperature captures the ITL dynamics

The Amazon Basin plays key roles in the carbon and water cycles, climate change, atmospheric chemistry, and biodiversity. It has already been changed significantly by human activities, and more pervasive change is expected to occur in the coming decades. It is therefore essential to establish long-term measurement sites that provide a baseline record of present-day climatic, biogeochemical, and atmospheric conditions and that will be operated over coming decades to monitor change in the Amazon region, as human perturbations increase in the future. The Amazon Tall Tower Observatory (ATTO) has been set up in a pristine rain forest region in the central Amazon Basin, about 150 km northeast of the city of Manaus. Two 80 m towers have been operated at the site since 2012, and a 325 m tower is nearing completion in mid-2015. An ecological survey including a biodiversity assessment has been conducted in the forest region surrounding the site. Measurements of micrometeorological and atmospheric chemical variables were initiated in 2012, and their range has continued to broaden over the last few years. The meteorological and micrometeorological measurements include temperature and wind profiles, precipitation, water and energy fluxes, turbulence components, soil temperature profiles and soil heat fluxes, radiation fluxes, and visibility. A tree has been instrumented to measure stem profiles of temperature, light intensity, and water content in cryptogamic covers. The trace gas measurements comprise continuous monitoring of carbon dioxide, carbon monoxide, methane, and ozone at five to eight different heights, complemented by a variety of additional species measured during intensive campaigns (e.g., VOC, NO, NO2, and OH reactivity). Aerosol optical, microphysical, and chemical measurements are being made above the canopy as well as in the canopy space. They include aerosol light scattering and absorption, fluorescence, number and volume size distributions, chemical composition, cloud condensation nuclei (CCN) concentrations, and hygroscopicity. In this paper, we discuss the scientific context of the ATTO observatory and present an overview of results from ecological, meteorological, and chemical pilot studies at the ATTO site.

A homogeneous, consistent, high-quality in situ temperature dataset covering some decades in time is crucial for the detection of climate changes in the ocean. For the period from 1940 to the present, this study investigates the data quality of temperature profiles from mechanical bathythermographs (MBT) by comparing these data with reference data obtained from Nansen bottle casts and conductivity–temperature–depth (CTD) profilers. This comparison reveals significant systematic errors in MBT measurements. The MBT bias is as large as 0.2°C before 1980 on the global average and reduces to less than 0.1°C after 1980. A new empirical correction scheme for MBT data is derived, where the MBT correction is country, depth, and time dependent. Comparison of the new MBT correction scheme with three schemes proposed earlier in the literature suggests a better performance of the new schemes. The reduction of the biases increases the homogeneity of the global ocean database being mostly important for climate change–related studies, such as the improved estimation of the ocean heat content changes.

A database of temperature‐dependent hexagonal ice aggregate optical properties in the far‐infrared (FIR) spectrum is developed to support FIR missions, particularly the current Polar Radiant Energy in the Far InfraRed Experiment and the upcoming Far‐infrared‐Outgoing‐Radiation Understanding and Monitoring. Based on this data set, simulations of the brightness temperatures (BTs) in the 100–667 cm−1 FIR region are conducted for an anvil‐like ice cloud in a tropical atmosphere. The results show nonnegligible impact of ice cloud temperature on simulated BTs, which can be as large as 3 K due to the difference between fixed 160 or 270 K cloud temperature and the benchmark counterpart, varying in accordance with the ambient temperature profile for a cloud residing between 249.6 and 199.6 K. To enhance the accuracy of FIR radiative transfer modeling, it is recommended to incorporate temperature‐dependent optical properties of ice clouds.

This study evaluates the Noah land surface model (LSM) in its ability to simulate water and heat exchanges over frozen ground in a Tibetan meadow ecosystem. A comprehensive dataset including in situ micrometeorological and soil moisture–temperature profile measurements collected between November and March is utilized, and analyses of the measurements reveal that the measured soil freezing characteristics are better captured by 1) modifying the parameter b₁ implemented in the current Noah LSM that constrains the shape parameter of soil water retention curve utilized by the water potential freezing point depression equation to produce appropriate liquid water content θ liq under subzero temperature conditions and 2) neglecting the ice effect on soil-specific surface and thus matric potential via setting the empirical parameter that accounts for the effect of increase in specific surface of soil particles and ice–liquid water ck to zero. The numerical experiments performed with the Noah model run show that in comparison to the default Noah LSM, adoption of ck = 0 and site-specific b₁ values reduces the overestimation of θ liq across the soil profile. Implementation of augmentations such as the parameterization of diurnally varying thermal roughness length resolves the overestimation of daytime turbulent heat fluxes and underestimation of surface temperature. Further adoption of a new heat conductivity parameterization reduces the overestimation of nighttime surface temperature. An appropriate treatment of phase change efficiency that accounts for changing freezing rate with varying liquid water contents is also needed to reduce the temperature underestimation across soil profiles.

The tropical tropopause layer (TTL) is the transition region between the well-mixed convective troposphere and the radiatively controlled stratosphere with air masses showing chemical and dynamical properties of both regions. The representation of the TTL in meteorological reanalysis data sets is important for studying the complex interactions of circulation, convection, trace gases, clouds, and radiation. In this paper, we present the evaluation of climatological and long-term TTL temperature and tropopause characteristics in the reanalysis data sets ERA-Interim, ERA5, JRA-25, JRA-55, MERRA, MERRA-2, NCEP-NCAR (R1), and CFSR. The evaluation has been performed as part of the SPARC (Stratosphere–troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (S-RIP). The most recent atmospheric reanalysis data sets (ERA-Interim, ERA5, JRA-55, MERRA-2, and CFSR) all provide realistic representations of the major characteristics of the temperature structure within the TTL. There is good agreement between reanalysis estimates of tropical mean temperatures and radio occultation data, with relatively small cold biases for most data sets. Temperatures at the cold point and lapse rate tropopause levels, on the other hand, show warm biases in reanalyses when compared to observations. This tropopause-level warm bias is related to the vertical resolution of the reanalysis data, with the smallest bias found for data sets with the highest vertical resolution around the tropopause. Differences in the cold point temperature maximize over equatorial Africa, related to Kelvin wave activity and associated disturbances in TTL temperatures. Interannual variability in reanalysis temperatures is best constrained in the upper TTL, with larger differences at levels below the cold point. The reanalyses reproduce the temperature responses to major dynamical and radiative signals such as volcanic eruptions and the quasi-biennial oscillation (QBO). Long-term reanalysis trends in temperature in the upper TTL show good agreement with trends derived from adjusted radiosonde data sets indicating significant stratospheric cooling of around −0.5 to −1 K per decade. At 100 hPa and the cold point, most of the reanalyses suggest small but significant cooling trends of −0.3 to −0.6 K per decade that are statistically consistent with trends based on the adjusted radiosonde data sets. Advances of the reanalysis and observational systems over the last decades have led to a clear improvement in the TTL reanalysis products over time. Biases of the temperature profiles and differences in interannual variability clearly decreased in 2006, when densely sampled radio occultation data started being assimilated by the reanalyses. While there is an overall good agreement, different reanalyses offer different advantages in the TTL such as realistic profile and cold point temperature, continuous time series, or a realistic representation of signals of interannual variability. Their use in model simulations and in comparisons with climate model output should be tailored to their specific strengths and weaknesses.