Evaporation decreases the mass and increases the isotope composition of falling drops. Combining and integrating the dependence of the evaporation on the drop diameter and on the drop-environment humidity difference, the square of drop diameter is found to decrease with the square of vertical distance below cloud base. Drops smaller than 0.5 mm evaporate completely before falling 700 m in typical subtropical marine boundary layer conditions. The effect on the isotope ratio of equilibration with the environment, evaporation, and kinetic molecular diffusion is modeled by molecular and eddy diffusive fluxes after Craig and Gordon (1965), with a size-dependent parameterization of diffusion that enriches small drops more strongly, and approaches the rough aerodynamic limit for large drops. Rain shortly approaches a steady state with the subcloud vapor by exchange with a length scale of 40 m. Kinetic molecular diffusion enriches drops up to as they evaporate by up to +5~\permil~for deuterated water (HDO) and +3.5~\permil~for H$_2$$^{18}$O. Rain evaporation enriches undiluted subcloud vapor by +12~\permil~per mm rain, explaining enrichment of vapor in evaporatively cooled downdrafts that contribute to cold pools. Microphysics enriches the vapor lost by the early and complete evaporation of smaller drops in the distribution. Vapor from hydrometeors is more enriched than it would be by Rayleigh distillation or by mixtures of liquid rain and vapor in equilibrium with rain.

The water vapor transport in the extratropics is mainly organized in narrow elongated filaments. These filaments are referred to with a variety of names depending on the contexts. When making landfall on a coastline, they are generally referred to as atmospheric rivers; when occurring at high latitudes, many authors regard them as warm moist intrusions; when occurring ahead of a cold front towards the core on an extratropical cyclone, the most commonly used term is warm conveyor belt. Here, we propose an algorithm that detects these various lines of moisture transport in instantaneous maps of the vertically integrated water vapor transport. The detection algorithm extracts well-defined maxima in the water vapor transport and connects them to lines that we refer to as moisture transport axes. By only requiring a well-defined maximum in the vapor transport, we avoid imposing a threshold in the absolute magnitude of this transport (or the total column water vapor). Consequently, the algorithm is able to pick up moisture transport axes at all latitudes without requiring region-specific tuning or normalization. We demonstrate that the algorithm can detect both atmospheric rivers and warm moist intrusions, but also prominent monsoon air streams. Atmospheric rivers sometimes consist of several distinct moisture transport axes, indicating the merging of several moisture filaments into one atmospheric river. We showcase the synoptic situations and precipitation patterns associated with the occurrence of the identified moisture transport axes in example regions in the low, mid, and high latitudes.

Arctic cyclones are key drivers of sea ice and ocean variability. During the 2019-2020 Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, joint observations of the coupled air-ice-ocean system were collected at multiple spatial scales. Here, we present observations of a pair of strong mid-winter cyclones that impacted the MOSAiC site as it drifted in the central Arctic pack ice, with analytic emphasis on the second cyclone. The sea ice dynamical response showed spatial structure at the scale of the evolving atmospheric wind field. Internal ice stress and the ocean stress play significant roles, resulting in timing offsets between the atmospheric forcing and the ice response and post-cyclone inertial ringing in the ice and ocean. A structured response of sea ice motion and deformation to cyclone passage is seen, and the consequent ice motion then forces the upper ocean currents through frictional drag. The strongest impacts to the sea ice and ocean from the passing cyclone occur as a result of the surface impacts of a strong atmospheric low-level jet (LLJ) behind the trailing cold front. Impacts of the cyclone are prolonged through the coupled ice-ocean inertial response. The local impacts of the approximately 120 km wide LLJ occur over a 12 hour period or less and at scales of a kilometer to a few tens of kilometers, meaning that these impacts occur at smaller spatial scales and faster time scales than many satellite observations and coupled Earth system models can resolve.

A document by Yuya Takane. Click on the document to view its contents.

Existing research has employed various methods to quantify urban heat island (UHI) effects, but the ideal method for individual cities remains unclear. This study investigated how different methods influence UHI understanding in Addis Ababa, a tropical city facing UHI challenges. Three methods were compared: dynamic urbanization, natural and built-up fractions, and urban center vs. surrounding rural areas. Satellite data and spatial analyses revealed maximum daytime UHIs of 4°C and 3.1°C in summer and autumn, respectively. Examining the mean temperature differences between urban and rural areas across methods yielded diverse results. This suggests that while the ‘dynamic urbanization’ method is statistically favorable in this specific case, averaging results from multiple methods produced a more robust and generalizable approach to understanding UHIs in different urban contexts. Ultimately, this study highlights the importance of context-specific method selection for accurately understanding the complex interplay between urban and rural environments.

Arctic clouds play a key role in Arctic climate variability and change; however, contemporary climate models struggle to simulate cloud properties accurately. Model-simulated cloud properties are determined by the physical parameterizations and their interactions within the model configuration. Quantifying effects of individual parameterization changes on model-simulated clouds informs efforts to improve cloud properties in models and provides insights on climate system behavior. This study quantities the influence of individual parameterization schemes on Arctic low cloud properties within the Hadley Centre Global Environmental Model 3 atmospheric model using a suite of experiments where individual parameterization packages are changed one-at-a-time between two configurations: GA6 and GA7.1. The results indicate that individual parameterization changes explain most of the cloud property differences, whereas multiple parameterizations, including non-cloud schemes, contribute to cloud radiative effect differences. The influence of a parameterization change on cloud properties is found to vary by meteorological regime. We employ a three-term decomposition to quantify contributions from (1) regime independent, (2) regime dependent, and (3) the regime frequency of occurrence changes. Decomposition results indicate that each term contributes differently to each cloud property change and that non-cloud parameterization changes make a substantial contribution to the LW and SW cloud radiative effects by modifying clear-sky fluxes differently across regimes. The analysis provides insights on the role of non-cloud parameterizations for setting cloud radiative effects, a model pathway for cloud-atmosphere circulation interactions, and raises questions on the most useful observational approaches for improving models.

The Indian summer monsoon precipitation trend from 1979 to 2022 shows a substantial 40% increase over Northwest India, which is in agreement with the future projections of the Coupled Model Intercomparison Project 6 (CMIP6). The observationally constrained reanalysis dataset reveals that a prominent sea surface warming in the western equatorial Indian Ocean and the Arabian Sea might be responsible for the rainfall enhancement through strengthening the cross-equatorial monsoonal flow and associated evaporation. We show that the cross-equatorial monsoon winds over the Indian Ocean are strengthening due to the merging of Pacific Ocean trade winds and rapid Indian Ocean warming. These winds also enhance the latent heat flux (evaporation), and in combination, this results in increased moisture transport from the ocean toward the land.

Temperature and water vapor are known to fluctuate on multiple scales. In this study 27 years of airborne measurements of temperature and relative humidity from IAGOS (In-service Aircraft for a Global Observing System) are used to parameterize the distribution of water vapor in the upper troposphere and lower stratosphere (UTLS). The parameterization is designed to simulate water vapor fluctuations within gridboxes of atmospheric general circulation models (AGCMs) with typical size of a few tens to a few hundreds kilometers. The distributions currently used in such models are often not supported by observations at high altitude. More sophisticated distributions are key to represent ice supersaturation, a physical phenomenon that plays a major role in the formation of natural cirrus and contrail cirrus. Here the observed distributions are fitted with a beta law whose parameters are adjusted from the gridbox mean variables. More specifically the standard deviation and skewness of the distributions are expressed as empirical functions of the average temperature and specific humidity, two typical prognostic variables of AGCMs. Thus, the distribution of water vapor is fully parameterized for a use in these models. The new parameterization simulates the observed distributions with a determination coefficient always greater than 0.917, with a mean value of 0.997. Moreover, the ice supersaturation fraction in a model gridbox is well simulated with a determination coefficient of 0.983. The parameterization is robust to a selection of various geographical subsets of data and to gridbox sizes varying between 25 to 300 km.

A document by Ehsan Erfani. Click on the document to view its contents.

A document by Ehsan Erfani. Click on the document to view its contents.

The higher-order turbulence scheme, Cloud Layers Unified by Binormals (CLUBB), is known for effectively simulating the transition from cumulus to stratocumulus clouds within leading atmospheric climate models. This study investigates an underexplored aspect of CLUBB: its capacity to simulate near-surface winds and the Planetary Boundary Layer (PBL), with a particular focus on its coupling with surface momentum flux. Using the GFDL atmospheric climate model (AM4), we examine two distinct coupling strategies, distinguished by their handling of surface momentum flux during the CLUBB’s stability-driven substepping performed at each atmospheric time step. The static coupling maintains a constant surface momentum flux, while the dynamic coupling adjusts the surface momentum flux at each CLUBB substep based on the CLUBB-computed zonal and meridional wind speed tendencies. Our 30-year present-day climate simulations (1980-2010) show that static coupling overestimates 10-m wind speeds compared to both control AM4 simulations and reanalysis, particularly over the Southern Ocean (SO) and other midlatitude ocean regions. Conversely, dynamic coupling corrects the static coupling 10-m winds biases in the midlatitude regions, resulting in CLUBB simulations achieving there an excellent agreement with AM4 simulations. Furthermore, analysis of PBL vertical profiles over the SO reveals that dynamic coupling reduces downward momentum transport, consistent with the found wind-speed reductions. Instead, near the tropics, dynamic coupling results in minimal changes in near-surface wind speeds and associated turbulent momentum transport structure. Notably, the wind turning angle serves as a valuable qualitative metric for assessing the impact of changes in surface momentum flux representation on global circulation patterns.

Studies have implicated the importance of longwave (LW) cloud-radiative forcing (CRF) in facilitating or accelerating the upscale development of tropical moist convection. While different cloud types are known to have distinct CRF, their individual roles in driving upscale development through radiative feedback is largely unexplored. We hypothesize that CRF from stratiform regions will have the greatest effect on upscale tropical convection. We test this hypothesis by analyzing output from convection-permitting ensemble Weather Research and Forecasting (WRF) model simulations of tropical cyclone formation. Using a novel column-by-column cloud classification scheme introduced herein, we use this model output to identify the relative contribution of five cloud types (shallow, congestus, and deep convection; and stratiform and anvil clouds) to the direct LW radiative forcing and the upscale development of convection via LW moist static energy variance. Results indicate that stratiform and anvil regions contribute dominantly to the domain averages of these variables.

Local meteorology over the Great Barrier Reef (GBR) can significantly influence ocean temperatures, which in turn impacts coral ecosystems. While El Niño–Southern Oscillation (ENSO) provides insight into the expected synoptic states, it lacks details of the anticipated sub-seasonal weather variability at local scales. This study explores the influence of the Madden-Julian oscillation (MJO) on Australian tropical climate, both independently and in combination with ENSO, with a focus on impacts to the GBR. We find that during El Niño periods, a faster propagating MJO pattern can disrupt background warm, dry conditions, and potentially provide cooling relief via increased cloud cover and stronger winds. Conversely, in La Niña periods, the MJO is prevented from passing the Maritime continent, forcing it to remain in a standing pattern in the Indian Ocean. This leads to reduced atmospheric convection over the GBR, decreased cloud cover and wind, and the generation of a warm ocean anomaly.

As Earth warms, the tropopause is expected to rise, but predictions of its temperature change are less certain. One theory ties tropopause temperature to outgoing longwave radiation (OLR), but this contradicts simulations that exhibit a Fixed Tropopause Temperature (FiTT) even as OLR increases. Another theory ties tropopause temperature to upper tropospheric moisture, but is not precise enough to make quantitative predictions. Here, we argue that tropopause temperature, defined by where radiative cooling becomes negligible, is set by water vapor’s maximum spectroscopic absorption and Clausius-Clapeyron scaling. This “thermospectric constraint’ makes quantitative predictions for tropopause temperature that are borne out in single column and general circulation model experiments where the spectroscopy is modified and the tropopause changes in response. This constraint underpins the FiTT hypothesis, shows how tropopause temperature can decouple from OLR, suggests a way to relate the temperatures of anvil clouds and the tropopause, and shows how spectroscopy manifests in Earth’s general circulation.

• Deep depression occurrences have significantly increased over the eastern side, and decreased over the western side of the North Atlantic. • Deep depressions are linked to high surface temperature patterns in western continental Europe but have little impact on the mean warming.

1 NASA Goddard Institute for Space Studies, New York, NY USA2 Dept. of Applied Physics and Applied Mathematics, Columbia Univ., New York, NY USA3 Dept. of Earth and Atmospheric Sciences, City College of New York, NY USA4 University of California, Los Angeles, Los Angeles, CA5 NASA Jet Propulsion Laboratory, Pasadena, CA USA* Corresponding author: Allegra N. LeGrande ([email protected] | [email protected] )

The effect of modified equator-to-pole temperature gradients on the jet stream by low-level polar warming and upper-level tropical warming on jet streams is not fully understood. We perform four aquaplanet simulations to quantify the impact of different sea surface temperature distributions on jet stream strength, wave amplitudes and jet stream waviness, quantified by a modified Sinuosity Index. A large-scale uniform warming scenario increases the jet strength whereas decreases in jet strength occur in two scenarios where the meridional temperature gradient is reduced. However, all scenarios indicate substantial decreases in the magnitude of large wave amplitudes, jet stream extreme waviness and reduced variability of these diagnostics, suggesting a relationship with weakened baroclinicity. Our findings contradict the earlier proposed mechanism that low-level polar warming weakens the jet stream and increases wave amplitudes and jet stream waviness. We conclude that a weaker jet stream does not necessarily become wavier.

In recent years, efforts to assess the evolving risks of coastal compound surge and rainfall-driven flooding from tropical cyclones (TCs) and extratropical cyclones (ETCs) in a warming climate have intensified. While substantial progress has been made, the persistent challenge lies in obtaining actionable insights into the changing magnitude and spatially-varying flood risks in coastal areas. We employ a physics-based numerical hydrodynamic framework to simulate compound flooding from TCs and ETCs in both current and future warming climate conditions, focusing on the western side of Buzzard Bay in Massachusetts. Our approach leverages hydrodynamic models driven by extensive sets of synthetic TCs downscaled from CMIP6 climate models and dynamically downscaled ETC events using the WRF model forced by CMIP5 simulations. Through this methodology, we quantify the extent to which climate change can potentially reshape the risk landscape of compound flooding in the study area. Our findings reveal a significant increase in TC-induced compound flooding risk due to evolving climatology and sea level rise (SLR). Additionally, there is a heightened magnitude of compound flooding from ETCs, in coastal regions, due to SLR. Inland areas exhibit a decline in rainfall-driven flooding from high-frequency ETC events toward the end of the century compared to the current climate. Our methodology is transferable to other vulnerable coastal regions, serving as a valuable decision-making tool for adaptive measures in densely populated areas. It equips decision-makers and stakeholders with the means to effectively mitigate the destructive impacts of compound flooding arising from both current and future TCs and ETCs.

We study the sensitivity of South Asian Summer Monsoon (SASM) precipitation to Southern Hemisphere (SH) subtropical Absorbed Solar Radiation (ASR) changes using Community Earth System Model 2 simulations. Reducing positive ASR biases over the SH subtropics impacts SASM, and is sensitive to the ocean basin where changes are imposed. Radiation changes over the SH subtropical Indian Ocean (IO) shifts rainfall over the equatorial IO northward causing 1-2 mm/day drying south of equator, changes over the SH subtropical Pacific increases precipitation over northern continental regions by 1-2 mm/day, and changes over the SH subtropical Atlantic have little effect on SASM precipitation. Radiation changes over the subtropical Pacific impacts the SASM through zonal circulation changes, while changes over the IO modify meridional circulation to bring about changes in precipitation over northern IO. Our findings suggest that reducing SH subtropical radiation biases in climate models may also reduce SASM precipitation biases.

Marine cold-air outbreaks, or CAOs, are airmass transformations whereby relatively cold boundary layer (BL) air is transported over relatively warm water. Such convectively-driven conditions are rather ubiquitous in the high-latitudes, occurring most frequently during the winter and spring. To more deeply understand BL and cloud properties during CAO conditions, the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) took place from late 2019 into early 2020. During COMBLE, the U.S. Department of Energy (DOE) first Atmospheric Radiation Measurement Mobile Facility (AMF1) was deployed to Andenes, Norway, far downstream (~1000 km) from the Arctic pack ice. This study examines the two most intense CAOs sampled at the AMF1 site. The observed BL structures are open cellular in nature with high (~3-5 km) and cold (-30 to -50 oC) cloud tops, and they often have pockets of high liquid water paths (LWPs; up to ~1000 g m-2) associated with strong updrafts and enhanced turbulence. We use a high-resolution mesoscale model to explore how well four different turbulence closure methods represent open cellular cloud properties. After applying a radar simulator to the model outputs for direct evaluation, we show that cloud top properties agree well with AMF1 observations (within ~10%), but radar reflectivity and LWP agreement is more variable. The eddy-diffusivity/mass-flux approach produces the deepest cloud layer and therefore the largest and most coherent cellular structures. Our results suggest that the turbulent Prandtl number may play an important role for the simulated BL and cloud properties.

Urban Land Surface Models (ULSMs) simulate energy and water exchanges between the urban surface and atmosphere. When part of numerical weather prediction, ULSMs provide a lower boundary for the atmosphere and improve the applicability of model results in the urban environment compared with non-urban land surface models. However, earlier systematic ULSM comparison projects assessed the energy balance but ignored the water balance which is coupled to the energy balance. Here, we analyze the water balance representation in 19 ULSMs participating in the Urban-PLUMBER project using results for 20 sites spread across a range of climates and urban form characteristics. As observations for most water fluxes are unavailable, we examine the water balance closure, flux timing, and magnitude with a score derived from seven indicators. We find that the water budget is only closed in 57% of the model-site combinations assuming closure when annual total incoming fluxes (precipitation and irrigation) fluxes are within 3% of the outgoing (all other) fluxes. Results show the timing is better captured than magnitude. No ULSM has passed all good water balance indicators for any site. Our results indicate models could be improved by explicitly verifying water balance closure and revising runoff parameterizations. By expanding ULSM evaluation to the water balance and related to latent heat flux performance, we demonstrate the benefits of evaluating processes with direct feedback mechanisms to the processes of interest.

Reliable air temperature forecasts are necessary for mitigating the effects of droughts and Heatwaves. The numerical weather prediction(NWP) model forecasts have significant biases associated and therefore need post-processing. Post-processing of temperature forecasts using probabilistic approaches are lacking in India. In this study, we post-process the Global Ensemble Forecast System (GEFS) and EuropeanCentre for Medium Range Weather Forecasts (ECMWF) NWP model temperature forecasts for short to medium range time scales (1-7 days)using two probabilistic techniques, namely, Bayesian model averaging(BMA) and Nonhomogeneous gaussian regression (NGR). The post-processing techniques are evaluated for temperature (maximum and minimum) predictions across the Indian region. Results show that the probabilistic approaches considerably enhance the temperature predictions across India except the Himalayan regions. These techniques also comprehensively outperform the traditional post-processing techniques such as the running mean and simple linear regression. The NGR performs better than the BMA across all regions and is able to provide highly skillful temperature forecasts at higher lead times as well. Further, the study also assesses the implication of probabilistic post-processing Tmax forecast towards forecast enhancement of heatwaves (HW) in India. Post-processed Tmax forecasts revealed that the NGR approach considerably enhanced the HW prediction skill in India, especially in the northwestern and central Indian regions, considered highly prone to HW. The findings of this study will be useful in developing enhanced HW early warning and prediction systems in India.

This study examines how the geographic location of sea surface temperature (SST) biases influences global atmospheric responses. Utilizing an intermediate-complexity atmospheric model, 106 century-long simulations with idealized SST perturbations—emulating biases in coupled climate models—were performed. The intensity of the global atmospheric response to SST biases is evaluated by quantifying changes in global wave energy and interannual variance. The findings underscore the response's dependency on local background SST. Notably, with an imposed SST bias of +1.5 K, a significant global response is triggered once background SST surpasses approximately 25°C. This geographic dependency is related to the critical SST threshold for intense convection. Consequently, these results highlight the need for heightened focus on tropical oceans, especially the Indo-West Pacific, where SST biases can significantly impact the accuracy of global climate simulations.

Arctic permafrost thaw holds the potential to drastically alter the Earth’s surface in Northern high latitudes. We utilize high-resolution Large Eddy Simulations to investigate the impact of the changing surfaces onto the neutrally stratified Atmospheric Boundary Layer (ABL). A stochastic surface model based on Gaussian Random Fields modeling typical permafrost landscapes is established in terms of two land cover classes: grass land and open water bodies, which exhibit different surface roughness length and surface sensible heat flux. A set of experiments is conducted where two parameters, the lake areal fraction and the surface correlation length, are varied to study the sensitivity of the boundary layer with respect to surface heterogeneity. Our key findings from the simulations are the following: The lake areal fraction has a substantial impact on the aggregated sensible heat flux at the blending height. The larger the lake areal fraction, the smaller the sensible heat flux. This result gives rise to a potential feedback mechanism. When the Arctic dries due to climate heating, the interaction with the ABL may accelerate permafrost thaw. Furthermore, the blending height shows significant dependency on the correlation length of the surface features. A longer surface correlation length causes an increased blending height. This finding is of relevance for land surface models concerned with Arctic permafrost as they usually do not consider a heterogeneity metric comparable to the surface correlation length.